# Notebook from awaemmanuel/2020-S109A
Path: content/homeworks/hw1/cs_s109a_hw1/cs_s109a_hw1.ipynb

  S-109A Introduction to Data Science

## Homework 1: Data Collection - Web Scraping - Data Parsing

**Harvard University**

**Summer 2020**

**Instructor**: Kevin Rader

_____no_output_____

## RUN THIS CELL TO GET THE RIGHT FORMATTING
import requests
from IPython.core.display import HTML
styles = requests.get("https://raw.githubusercontent.com/Harvard-IACS/2018-CS109A/master/content/styles/cs109.css").text
HTML(styles)_____no_output_____

Instructions

- To submit your assignment follow the instructions given in Canvas.
- The deliverables to be submitted in Canvas are:

    a) this python notebook with your code and answers

    b) the bibtex file, `publist.bib`, you created

    c) the CSV file, `publist.csv`, you created

    d) The JSON file, `publist.json` you created

- Exercise **responsible scraping**. Web servers can become slow or unresponsive if they receive too many requests from the same source in a short amount of time. Use a delay of several seconds between requests in your code. This helps to prevent you from getting blocked by the target website. Run the webpage fetching part of the homework only once and do not re-run after you have saved the results in the JSON file (details below).
- Web scraping requests can take several minutes. This is another reason why you should not wait until the last minute to do this homework.

# Data Collection - Web Scraping - Data Parsing

In this homework, your goal is to learn how to acquire, parse, clean, and analyze data. Initially you will read the data from a file, and then later scrape them directly from a website. You will look for specific pieces of information by parsing the data, clean the data to prepare them for analysis, and finally, answer some questions.

In doing so you will get more familiar with three of the common file formats for storing and transferring data, which are:
- CSV, a text-based file format used for storing tabular data that are separated by some delimiter, usually comma or space.
- HTML/XML.
- JavaScript Object Notation (JSON), a text-based open standard designed for transmitting structured data over the web._____no_output_____

# import the necessary libraries
import matplotlib as mpl
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import scipy as sp
import time
pd.set_option('display.width', 500)
pd.set_option('display.max_columns', 100)
pd.set_option('display.notebook_repr_html', True)
%matplotlib inline_____no_output_____

## Help a professor parse their publications and extract information.

### Overview

In this part your goal is to parse the HTML page of a professor containing some of his/her publications, and answer some questions. This page is provided to you in the file `data/publist_super_clean.html`. There are 45 publications in descending order from No. 244 to No. 200.
_____no_output_____

# use this file
PUB_FILEPATH = 'data/publist_super_clean.html'_____no_output_____

 Question 1 [40 pts]: Parsing and Converting to bibTex and CSV using Beautiful Soup and python string manipulation

A lot of the bibliographic and publication information is displayed in various websites in a not-so-structured HTML files. Some publishers prefer to store and transmit this information in a .bibTex file which looks roughly like this (we've simplified a few things):
```
@article {
     author = "John Doyle",
     title = "Interaction between atoms",
     URL = "Papers/PhysRevB_81_085406_2010.pdf",
     journal = "Phys. Rev. B",
     volume = "81"
}
```
You will notice that this file format is a set of items, each of which is a set of key-value pairs. In the python world, you can think of this as a list of dictionaries.
Each line is an item, and has multiple features, or keys, as represented by that line's value for the column corresponding to the key.

You are given an .html file containing a list of papers scraped from the author's website and you are to write the information into .bibTex and .CSV formats. A useful tool for parsing HTML is BeautifulSoup  (http://www.crummy.com/software/BeautifulSoup/) (BS).

**1.1 [5 pts]** Write a function called `make_soup` that accepts `filename` for the HTML filename as an input and returns a BS object.

**1.2 [25 pts]** Write a function that reads in the BS object, parses it, and converts it into a list of dictionaries.  Each element of this list should cerrespond to one paper and should have the following format (with different values for each publication):
```
{'author': 'L.A. Agapito, N. Kioussis and E. Kaxiras',
 'title': 'Electric-field control of magnetism in graphene quantum dots:\n Ab initio calculations',
 'URL': 'Papers/PhysRevB_82_201411_2010.pdf',
 'journal': 'Phys. Rev. B',
 'volume': '82'}
```

**1.3 [5 pts]** Convert the list of dictionaries into standard .bibTex format using python string manipulation, and write the results into a file called `publist.bib`.

**1.4 [5 pts]** Convert the list of dictionaries into standard tabular .csv format using pandas, and write the results into a file called `publist.csv`. The csv file should have a header and no integer index.

#### HINT
- Inspect the HTML code for tags that indicate information chunks such as `title` of the paper.  BeautifulSoup's `find_all` method might be useful.
- Question 1.2 is better handled if you break the code into functions, each performing a small task such as finding the author(s) for each paper.
- Question 1.3 is effectively tackled by first using python string formatting on a template string.
- Make sure you catch exceptions when needed.
- Make sure you check for **missing data** and handle these cases as you see fit.

#### Resources
- [BeautifulSoup Tutorial](https://www.dataquest.io/blog/web-scraping-tutorial-python/).
- More about the [BibTex format](http://www.bibtex.org).

### Answers _____no_output_____

# import the necessary libraries
from bs4 import BeautifulSoup
from bs4.element import Tag
from string import Template
from typing import List_____no_output_____

 **1.1 [5 pts]  Write a function called `make_soup` that accepts as input a string representing the path to an HTML file and returns a BS object.**
    _____no_output_____

def make_soup(file_path: str) -> BeautifulSoup:
    '''Open the file and convert into a BS object.

       Args:
           file_path: (str) path to an HTML file

       Returns:
           A BS object containing the HTML page ready to be parsed.
    '''
    with open(file=file_path, mode="r", encoding="utf-8") as fp:
        contents = BeautifulSoup(fp.read(), 'html.parser')
    return contents_____no_output_____# check your code - print the BS object returned by `make_soup()`
# you should get a familiar HTML page as text (please enable scrolling on the output)
soup = make_soup(PUB_FILEPATH)
print(soup)<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
   "http://www.w3.org/TR/html4/loose.dtd">

<title>Kaxiras E journal publications</title>

<meta content="text/html;charset=utf-8" http-equiv="Content-Type"/>
<link href="../styles/style_pubs.css" rel="stylesheet" type="text/css"/>
<meta content="" name="description"/>
<meta content="Kaxiras E, Multiscale Methods, Computational Materials" name="keywords"/>

"Approaching the intrinsic band gap in suspended high-mobility graphene nanoribbons"

Ming-Wei Lin, Cheng Ling, Luis A. Agapito, Nicholas Kioussis, Yiyang Zhang, Mark Ming-Cheng Cheng,
PHYSICAL REVIEW B  84,  125411 (2011)

"Effect of symmetry breaking on the optical absorption of semiconductor nanoparticles"

JAdam Gali, Efthimios Kaxiras, Gergely T. Zimanyi, Sheng Meng,
PHYSICAL REVIEW B  84,  035325 (2011)

"Influence of CH2 content and network defects on the elastic properties of organosilicate glasses"

Jan M. Knaup, Han Li, Joost J. Vlassak, and Efthimios Kaxiras,
PHYSICAL REVIEW B  83,  054204 (2011)

"Direct correlation of crystal structure and optical properties in wurtzite/zinc-blende
GaAs nanowire heterostructures"

Martin Heiss, Sonia Conesa-Boj, Jun Ren, Hsiang-Han Tseng, Adam Gali,
PHYSICAL REVIEW B  83,  045303 (2011)

"Endothelial shear stress from large-scale blood flow simulations"

Simone Melchionna, Efthimios Kaxiras, Massimo Bernaschi and Sauro Succi,
Phil. Trans. R. Soc. A  369,  2354-2361 (2011)

"Properties of nitrogen-vacancy centers in diamond:
the group theoretic approach"

J R Maze, A Gali, E Togan, Y Chu, A Trifonov,
New Journal of Physics  13,  025025 (2011)

"Lithium-Assisted Plastic Deformation of Silicon Electrodes in
Lithium-Ion Batteries: A First-Principles Theoretical Study"

Kejie Zhao, Wei L. Wang, John Gregoire, Matt Pharr, Zhigang Suo,
Nano Lett.  11,  2962-2967 (2011)

"D-π-A Dye System Containing Cyano-Benzoic Acid as Anchoring
Group for Dye-Sensitized Solar Cells"

 Masataka Katono, Takeru Bessho, Sheng Meng, Robin Humphry-Baker, Guido Rothenberger,
Langmuir  27,  14248-14252 (2011)

"New Insights into the Structure of the Vapor/Water
Interface from Large-Scale First-Principles Simulations"

 Thomas D. Kuhne, Tod A. Pascal, Efthimios Kaxiras, and Yousung Jung,
J. Phys. Chem. Lett.  2,  105-113 (2011)

"Design of Dye Acceptors for Photovoltaics from First-Principles
Calculations"

 Sheng Meng, Efthimios Kaxiras, Md. K. Nazeeruddin, and Michael Gratzel,
J. Phys. Chem. C  115,  9276–9282 (2011)

"Theoretical Study of O-Assisted Selective Coupling of Methanol on
Au(111)"

 Bingjun Xu, Jan Haubrich, Thomas A. Baker, Efthimios Kaxiras, and Cynthia M. Friend,
J. Phys. Chem. C  115,  3703-3708 (2011)

"Properties of copper (fluoro-)phthalocyanine layers deposited
on epitaxial graphene"

 Jun Ren, Sheng Meng, Yi-Lin Wang, Xu-Cun Ma, Qi-Kun Xue, Efthimios Kaxiras,
J. Chem. Phys.  134,  194706 (2011)

"The Role of Surface and Subsurface Point Defects for Chemical Model
Studies on TiO2: A First-Principles Theoretical Study of Formaldehyde
Bonding on Rutile TiO2(110)"

 Jan Haubrich, Efthimios Kaxiras, and Cynthia M. Friend,
Chem. Eur. J.  17,  4496-4506(2011)

"Role of defects in propene adsorption and reaction on a partially
O-covered Au(111) surface"

 Thomas A. Baker, Bingjun Xu, Stephen C. Jensen, Cynthia M. Friend and Efthimios Kaxiras,
Catal. Sci. Technol.  1, 1166-1174  (2011)

"Graphene Structures at an Extreme
Degree of Buckling"

 Youdong Mao, Wei L. Wang, Dongguang Wei, Efthimios Kaxiras, and Joseph G. Sodroski,
ACSNano. ,5, 1395-1400 (2011)

"Stiffening of organosilicate glasses by organic cross-linking"

 H. Li, J.M. Knaup, E. Kaxiras and J.J. Vlassak,
Acta Mater. ,
59, 44-52 (2011).

"Graphene hydrate: theoretical prediction of a new insulating
form of graphene"

 W.L. Wang and E. Kaxiras,
New J. Phys. ,
12, 125012 (2010).

"Electric-field control of magnetism in graphene quantum dots:
 Ab initio calculations"

 L.A. Agapito, N. Kioussis and E. Kaxiras,
Phys. Rev. B ,
82, 201411 (2010).

"Multiscale simulation of cardiovascular flows on the IBM Bluegene/P:
full heart-circulation system at near red-blood cell resolution"

 A. Peters, S. Melchionna, E. Kaxiras, J. Latt, J. Sircar, S. Succi,
2010 ACM/IEEE International Conference for High Performance ,
 doi: 10.1109/SC.2010.33 (2010).

"Optical properties of clusters and molecules from real-time time-dependent
density functional theory using a self-consistent field"

 J. Ren, E. Kaxiras and S. Meng,
Molec. Phys.  108, 1829-1844 (2010).

"Insights from Theory on the Relationship Between Surface Reactivity
and Gold Atom Release"

 T.A. Baker, E. Kaxiras and C.M. Friend,
Top. Catal.  53, 365-377 (2010).

"Embrittlement of Metal by Solute Segregation-Induced Amorphization"

 H.P. Chen, R.K. Kalia, E. Kaxiras, G. Lu, A. Nakano, K. Nomura,
Phys. Rev. Lett.  104, 155502 (2010).

"Electron and Hole Dynamics in Dye-Sensitized Solar Cells:
Influencing Factors and Systematic Trends"

 S. Meng and E. Kaxiras,
NanoLett.  10, 1238-1247 (2010).

"Compositional tuning of ultrathin surface oxides on metal and alloy
substrates using photons: Dynamic simulations and experiments"

 C.L. Chang, S.K.R.S. Sankaranarayanan, D. Ruzmetov, M.H. Engelhard, E. Kaxiras and S. Ramanathan,
Phys. Rev. B  81, 085406 (2010).

"Local Bonding Effects in the Oxidation of CO on Oxygen-Covered
Au(111) from Ab Initio Molecular Dynamics Simulations"

 T.A. Baker, C.M. Friend and E. Kaxiras,
J. Chem. Theory Comput.  6, 279-287 (2010).

"Hydrokinetic approach to large-scale cardiovascular blood flow"

 S. Melchionna, M. Bernaschi, S. Succi, E. Kaxiras, F.J. Rybicki, D. Mitsouras, A.U. Coskun and C.L. Feldman,
Comp. Phys. Comm.  181, 462-472 (2010).

"A flexible high-performance Lattice Boltzmann GPU code for the
simulations of fluid flows in complex geometries"

 M. Bernaschi, M. Fatica, S. Melchionna, S. Succi and E. Kaxiras,
Concurrency Computat.: Pract. Exper.
22, 1-14 (2010).

"Is the nature of magnetic order in copper-oxides and iron-pnictides
different?"

 E. Manousakis, J. Ren, S. Meng and E. Kaxiras,
Sol. St. Comm.  150, 62-65 (2010).

"Theory of Spin-Conserving Excitation of the N-V Center in Diamond"

 A. Gali, E. Janzen, P. Deak, G. Kresse and E. Kaxiras,
Phys. Rev. Lett.  103, 186404 (2009).

"Electric field tuning of oxygen stoichiometry at oxide surfaces:
molecular dynamics isimulations studies iof zirconia"

 S.K.R.S. Sankaranarayanan, E. Kaxiras and S. Ramanathan,
Energy & Environmental Sci.  2, 1196-1204 (2009).

"MUPHY: A parallel MUlti PHYsics/scale code for high performance
bio-fluidic simulations"

 M. Bernaschi, S. Melchionna, S. Succi, M. Fyta, E. Kaxiras
Comp. Phys. Comm.  180, 1495-1502 (2009).

"Nature of Oxidation of the Au(111) Surface: Experiment and
Theoretical Investigation"

 T.A. Baker, B.J. Xu, X.Y. Liu, E. Kaxiras and C.M. Friend,
J. Phys. Chem. C  113, 16561-16564 (2009).

"Prediction of coronary artery plaque progression and potential rupture
from 320-detector row prospectively ECG-gated single heart beat CT angiography:
Lattice Boltzmann evaluation of endothelial shear stress"

 F.J. Rybicki, S. Melchionna, D. Mitsouras, A.U. Coskun, A.G. Whitmore, E. Kaxiras, S. Succi, P.H. Stone and C.L. Feldman,
Int. J. Cardiovasc. Imaging  25, 289-299 (2009).

"Optimization of Mn doping in group-IV-based dilute magnetic semiconductors
by electronic codopants"

 H. Chen, W.G. Zhu, E. Kaxiras, and Z.Y. Zhang,
Phys. Rev. B  79, 235202 (2009).

"Numerical simulation of conformational variability in biopolymer translocation
through wide nanopores"

 M. Fyta, S. Melchionna, M. Bernaschi, E. Kaxiras and S. Succi,
J. Stat. Mech: Th. and Exper.  06, P06009 (2009).

"Control algorithm for multiscale flow simulations of water"

 E.M. Kotsalis, J.H. Walther, E. Kaxiras and P. Koumoutsakos,
Phys. Rev. E - Rap. Comm.  79, 045701 (2009).

"Structural, Electronic, and Optical Properties of Representative Cu-Flavonoid Complexes"

C.E. Lekka, J. Ren, S. Meng and E. Kaxiras,
J. Phys. Chem. B  113, 6478-6483 (2009).

"Topological Frustration in Graphene Nanoflakes: Magnetic Order and Spin Logic Devices"

 W.L. Wang, O.V. Yazyev, S. Meng and E. Kaxiras,
Phys. Rev. Lett.  102, 157201 (2009).

"Comment on 'Ab initio Electronic and Optical Properties of the N-V-Center in Diamond'"

 A. Gali and E. Kaxiras,
Phys. Rev. Lett.  102, 149703 (2009).

"Quantized biopolymer translocation through nanopores: Departure from simple scaling"

 S. Melchionna, M. Bernaschi, M. Fyta, E. Kaxiras and S. Succi,
Phys. Rev. E - Rap. Comm.  79, 030901 (2009).

"Atomistic Simulation of Field Enhanced Oxidation of Al(1000) Beyond the Mott Potential"

S.K.R.S. Sankaranarayanan, E. Kaxiras, S. Ramanathan,
Phys. Rev. Lett.  102, 095504 (2009).

"Effects of chlorine and oxygen coverage on the structure of the Au(111) surface"

T.A. Baker, C.M. Friend and E. Kaxiras,
J. Chem. Phys.  130, 084701 (2009).

"Atomic Oxygen Adsorption on Au(111) Surfaces with Defects"

T.A. Baker, C.M. Friend and E. Kaxiras,
J. Phys. Chem. C  113, 3232-3238 (2009).

"Multiscale simulations of complex systems: computation meets reality"

E. Kaxiras and S. Succi,
Sci. Model. Simul.  15, 59-65 (2008).

"Effective Hamiltonian for FeAs-based superconductors"

E. Manousakis, J. Ren, S. Meng and E. Kaxiras,
Phys. Rev. B  78, 205112 (2008).

Your output should look **like** this:
```
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
   "http://www.w3.org/TR/html4/loose.dtd">

<title>Kaxiras E journal publications</title>
<head>
<meta content="text/html;charset=utf-8" http-equiv="Content-Type"/>
<link href="../styles/style_pubs.css" rel="stylesheet" type="text/css"/>
<meta content="" name="description"/>
<meta content="Kaxiras E, Multiscale Methods, Computational Materials" name="keywords"/>
</head>
<body>
<ol start="244">
<li>
<a href="Papers/2011/PhysRevB_84_125411_2011.pdf" target="paper244">
"Approaching the intrinsic band gap in suspended high-mobility graphene nanoribbons"</a>
<br/>Ming-Wei Lin, Cheng Ling, Luis A. Agapito, Nicholas Kioussis, Yiyang Zhang, Mark Ming-Cheng Cheng,
<i>PHYSICAL REVIEW B </i> <b>84</b>,  125411 (2011)
<br/>
</li>
</ol>
<ol start="243">
<li>
<a href="Papers/2011/PhysRevB_84_035325_2011.pdf" target="paper243">
"Effect of symmetry breaking on the optical absorption of semiconductor nanoparticles"</a>
<br/>JAdam Gali, Efthimios Kaxiras, Gergely T. Zimanyi, Sheng Meng,
<i>PHYSICAL REVIEW B </i> <b>84</b>,  035325 (2011)
<br/>
</li>
</ol>

...

```_____no_output_____**1.2 [25 pts] Write a function that reads in the BS object, parses it, and converts it into a list of dictionaries.  Each element of this list should correspond to one paper and should have the following format (with different values for each publication):**
```
{'author': 'L.A. Agapito, N. Kioussis and E. Kaxiras',
 'title': 'Electric-field control of magnetism in graphene quantum dots:\n Ab initio calculations',
 'URL': 'Papers/PhysRevB_82_201411_2010.pdf',
 'journal': 'Phys. Rev. B',
 'volume': '82'}
```_____no_output_____

# your code here
def get_author(tag: Tag) -> str:
    """ Given a tag, return the author on page otherwise empty string """
    return tag.find("br").next_sibling.strip() if tag.find("br") else ""

def get_title(tag: Tag) -> str:
    """ Given a tag, return the title on page otherwise empty string """
    return tag.find("a").contents[0].strip().strip("\"") if tag.find("a") else ""

def get_title(tag: Tag) -> str:
    """ Given a tag, return the title on page otherwise empty string """
    return tag.find("a").contents[0].strip().strip("\"") if tag.find("a") else ""

def get_url(tag: Tag) -> str:
    """ Given a tag, return the url on page otherwise empty string """
    return tag.find("a")['href'].strip() if tag.find("a")['href'] else ""

def get_journal(tag: Tag) -> str:
    """ Given a tag, return the journal on page otherwise empty string """
    return tag.find("i").contents[0].strip() if tag.find("i") else ""

def get_volume(tag: Tag) -> str:
    """ Given a tag, return the title on page otherwise empty string """
    return tag.find("b").contents[0].strip() if tag.find("b") else ""

def purify_text(text: str) -> str:
    """ Clean up text i.e. remove newline, return and tab characters """
    text = text.strip().rstrip(",")
    text = text.replace('\n',' ')
    text = text.replace('\t','')
    return text_____no_output_____

Using functions above to convert the soup object into a list of dictionaries_____no_output_____

# your code here
def parse_article_tag(tag: Tag) -> dict:
    """ Parse an article soup tag and return a dict """
    return {
        "author": purify_text(get_author(tag)),
        "title": purify_text(get_title(tag)),
        "URL": purify_text(get_url(tag)),
        "journal": purify_text(get_journal(tag)),
        "volume": purify_text(get_volume(tag))
    }

def process_articles(soup: BeautifulSoup) -> List[dict]:
    """ Process articles from a BeautifulSoup object. Returns a list of dictionaries """
    return list(map(parse_article_tag, soup.find_all("li")))_____no_output_____articles_list = process_articles(soup)
articles_list[:5]_____no_output_____

**1.3** [5 pts] Convert the list of dictionaries into standard .bibTex format using python string manipulation, and write the results into a file called `publist.bib`.

__For reference__
```
@article {
     author = "John Doyle",
     title = "Interaction between atoms",
     URL = "Papers/PhysRevB_81_085406_2010.pdf",
     journal = "Phys. Rev. B",
     volume = "81"
}

@article {
     author = "John Doyle",
     title = "Interaction between atoms and another protron",
     URL = "Papers/PhysRevB_81_085406_2011.pdf",
     journal = "Phys. Rev. B",
     volume = "82"
}

```_____no_output_____

# Using Python string Templates
def generate_article(author: str,
                            title: str,
                            url: str,
                            journal: str,
                            volume: str) -> str:
    """ Create a template for bibTex format """
    template = """
    @article {
        author = "$author",
        title = "$title",
        URL = "$url",
        journal = "$journal",
        volume = "$volume"
    }\n"""
    article_template = Template(template)
    return article_template.substitute(author=author, title=title, url=url, journal=journal, volume=volume)_____no_output_____# your code here
ARTICLES_BIB_PATH = "./data/publist.bib"
def write_articles_bib_to_disk(articles: list, bib_out_path: str = ARTICLES_PUB_PATH) -> None:
    """ Take a list of dictionaries and write to bibTex file """
    assert articles, "[ERROR] - Articles are required!"

    articles_bibs = [generate_article(article['author'], article['title'], article['URL'], article['journal'], article['volume'])
               for article in articles_list]
    with open(bib_out_path, "w") as fp:
        fp.writelines(articles_bibs)
    print(f"Done writing {len(articles_bibs)} articles to bibTex")_____no_output_____# Write bibTex file
write_articles_bib_to_disk(articles=articles_list)Done writing 45 articles to bibTex
# check your answer - print the bibTex file
# clear/remove output before making pdf
with open(ARTICLES_BIB_PATH, 'r') as f:
    print(f.read())
    @article {
        author = "Ming-Wei Lin, Cheng Ling, Luis A. Agapito, Nicholas Kioussis, Yiyang Zhang, Mark Ming-Cheng Cheng",
        title = "Approaching the intrinsic band gap in suspended high-mobility graphene nanoribbons",
        URL = "Papers/2011/PhysRevB_84_125411_2011.pdf",
        journal = "PHYSICAL REVIEW B",
        volume = "84"
    }

    @article {
        author = "JAdam Gali, Efthimios Kaxiras, Gergely T. Zimanyi, Sheng Meng",
        title = "Effect of symmetry breaking on the optical absorption of semiconductor nanoparticles",
        URL = "Papers/2011/PhysRevB_84_035325_2011.pdf",
        journal = "PHYSICAL REVIEW B",
        volume = "84"
    }

    @article {
        author = "Jan M. Knaup, Han Li, Joost J. Vlassak, and Efthimios Kaxiras",
        title = "Influence of CH2 content and network defects on the elastic properties of organosilicate glasses",
        URL = "Papers/2011/PhysRevB_83_054204_2011.pdf",
        journal = "PHYSICAL REVIEW B",
        volume = "83"
    }

    @article {
        author = "Martin Heiss, Sonia Conesa-Boj, Jun Ren, Hsiang-Han Tseng, Adam Gali",
        title = "Direct correlation of crystal structure and optical properties in wurtzite/zinc-blende GaAs nanowire heterostructures",
        URL = "Papers/2011/PhysRevB_83_045303_2011.pdf",
        journal = "PHYSICAL REVIEW B",
        volume = "83"
    }

    @article {
        author = "Simone Melchionna, Efthimios Kaxiras, Massimo Bernaschi and Sauro Succi",
        title = "Endothelial shear stress from large-scale blood flow simulations",
        URL = "Papers/2011/PhilTransRSocA_369_2354_2011.pdf",
        journal = "Phil. Trans. R. Soc. A",
        volume = "369"
    }

    @article {
        author = "J R Maze, A Gali, E Togan, Y Chu, A Trifonov",
        title = "Properties of nitrogen-vacancy centers in diamond: the group theoretic approach",
        URL = "Papers/2011/NewJPhys_13_025025_2011.pdf",
        journal = "New Journal of Physics",
        volume = "13"
    }

    @article {
        author = "Kejie Zhao, Wei L. Wang, John Gregoire, Matt Pharr, Zhigang Suo",
        title = "Lithium-Assisted Plastic Deformation of Silicon Electrodes in Lithium-Ion Batteries: A First-Principles Theoretical Study",
        URL = "Papers/2011/NanoLett_11_2962-2967_2011.pdf",
        journal = "Nano Lett.",
        volume = "11"
    }

    @article {
        author = "Masataka Katono, Takeru Bessho, Sheng Meng, Robin Humphry-Baker, Guido Rothenberger",
        title = "D-π-A Dye System Containing Cyano-Benzoic Acid as Anchoring Group for Dye-Sensitized Solar Cells",
        URL = "Papers/2011/Langmuir_27_14248_2011.pdf",
        journal = "Langmuir",
        volume = "27"
    }

    @article {
        author = "Thomas D. Kuhne, Tod A. Pascal, Efthimios Kaxiras, and Yousung Jung",
        title = "New Insights into the Structure of the Vapor/Water Interface from Large-Scale First-Principles Simulations",
        URL = "Papers/2011/JPhysChemLett_2_105-113_2011.pdf",
        journal = "J. Phys. Chem. Lett.",
        volume = "2"
    }

    @article {
        author = "Sheng Meng, Efthimios Kaxiras, Md. K. Nazeeruddin, and Michael Gratzel",
        title = "Design of Dye Acceptors for Photovoltaics from First-Principles Calculations",
        URL = "Papers/2011/JPhysChemC_115_9276-9282_2011.pdf",
        journal = "J. Phys. Chem. C",
        volume = "115"
    }

    @article {
        author = "Bingjun Xu, Jan Haubrich, Thomas A. Baker, Efthimios Kaxiras, and Cynthia M. Friend",
        title = "Theoretical Study of O-Assisted Selective Coupling of Methanol on Au(111)",
        URL = "Papers/2011/JPhysChemC_115_3703-3708_2011.pdf",
        journal = "J. Phys. Chem. C",
        volume = "115"
    }

    @article {
        author = "Jun Ren, Sheng Meng, Yi-Lin Wang, Xu-Cun Ma, Qi-Kun Xue, Efthimios Kaxiras",
        title = "Properties of copper (fluoro-)phthalocyanine layers deposited on epitaxial graphene",
        URL = "Papers/2011/JChemPhys_134_194706_2011.pdf",
        journal = "J. Chem. Phys.",
        volume = "134"
    }

    @article {
        author = "Jan Haubrich, Efthimios Kaxiras, and Cynthia M. Friend",
        title = "The Role of Surface and Subsurface Point Defects for Chemical Model Studies on TiO2: A First-Principles Theoretical Study of Formaldehyde Bonding on Rutile TiO2(110)",
        URL = "Papers/2011/Chemistry_17_4496-4506_2011.pdf",
        journal = "Chem. Eur. J.",
        volume = "17"
    }

    @article {
        author = "Thomas A. Baker, Bingjun Xu, Stephen C. Jensen, Cynthia M. Friend and Efthimios Kaxiras",
        title = "Role of defects in propene adsorption and reaction on a partially O-covered Au(111) surface",
        URL = "Papers/2011/CatalSciTechnol_1_1166_2011.pdf",
        journal = "Catal. Sci. Technol.",
        volume = "1"
    }

    @article {
        author = "Youdong Mao, Wei L. Wang, Dongguang Wei, Efthimios Kaxiras, and Joseph G. Sodroski",
        title = "Graphene Structures at an Extreme Degree of Buckling",
        URL = "Papers/2011/ACSNano_5_1395-1400_2011.pdf",
        journal = "ACSNano.",
        volume = "5"
    }

    @article {
        author = "H. Li, J.M. Knaup, E. Kaxiras and J.J. Vlassak",
        title = "Stiffening of organosilicate glasses by organic cross-linking",
        URL = "Papers/ActaMater_59_44-52_2011.pdf",
        journal = "Acta Mater.",
        volume = "59"
    }

    @article {
        author = "W.L. Wang and E. Kaxiras",
        title = "Graphene hydrate: theoretical prediction of a new insulating  form of graphene",
        URL = "Papers/NewJPhys_12_125012_2010.pdf",
        journal = "New J. Phys.",
        volume = "12"
    }

    @article {
        author = "L.A. Agapito, N. Kioussis and E. Kaxiras",
        title = "Electric-field control of magnetism in graphene quantum dots:  Ab initio calculations",
        URL = "Papers/PhysRevB_82_201411_2010.pdf",
        journal = "Phys. Rev. B",
        volume = "82"
    }

    @article {
        author = "A. Peters, S. Melchionna, E. Kaxiras, J. Latt, J. Sircar, S. Succi",
        title = "Multiscale simulation of cardiovascular flows on the IBM Bluegene/P:  full heart-circulation system at near red-blood cell resolution",
        URL = "Papers/IEEE-SC10_2010.pdf",
        journal = "2010 ACM/IEEE International Conference for High Performance",
        volume = ""
    }

    @article {
        author = "J. Ren, E. Kaxiras and S. Meng",
        title = "Optical properties of clusters and molecules from real-time time-dependent density functional theory using a self-consistent field",
        URL = "Papers/MolPhys_108_1829-1844_2010.pdf",
        journal = "Molec. Phys.",
        volume = "108"
    }

    @article {
        author = "T.A. Baker, E. Kaxiras and C.M. Friend",
        title = "Insights from Theory on the Relationship Between Surface Reactivity and Gold Atom Release",
        URL = "Papers/TopicsCatal_53_365-377_2010.pdf",
        journal = "Top. Catal.",
        volume = "53"
    }

    @article {
        author = "H.P. Chen, R.K. Kalia, E. Kaxiras, G. Lu, A. Nakano, K. Nomura",
        title = "Embrittlement of Metal by Solute Segregation-Induced Amorphization",
        URL = "Papers/PhysRevLett_104_155502_2010.pdf",
        journal = "Phys. Rev. Lett.",
        volume = "104"
    }

    @article {
        author = "S. Meng and E. Kaxiras",
        title = "Electron and Hole Dynamics in Dye-Sensitized Solar Cells: Influencing Factors and Systematic Trends",
        URL = "Papers/NanoLett_10_1238-1247_2010.pdf",
        journal = "NanoLett.",
        volume = "10"
    }

    @article {
        author = "C.L. Chang, S.K.R.S. Sankaranarayanan, D. Ruzmetov, M.H. Engelhard, E. Kaxiras and S. Ramanathan",
        title = "Compositional tuning of ultrathin surface oxides on metal and alloy substrates using photons: Dynamic simulations and experiments",
        URL = "Papers/PhysRevB_81_085406_2010.pdf",
        journal = "Phys. Rev. B",
        volume = "81"
    }

    @article {
        author = "T.A. Baker, C.M. Friend and E. Kaxiras",
        title = "Local Bonding Effects in the Oxidation of CO on Oxygen-Covered Au(111) from Ab Initio Molecular Dynamics Simulations",
        URL = "Papers/JChemTheComp_6_279-287_2010.pdf",
        journal = "J. Chem. Theory Comput.",
        volume = "6"
    }

    @article {
        author = "S. Melchionna, M. Bernaschi, S. Succi, E. Kaxiras, F.J. Rybicki, D. Mitsouras, A.U. Coskun and C.L. Feldman",
        title = "Hydrokinetic approach to large-scale cardiovascular blood flow",
        URL = "Papers/CompPhysComm_181_462-472_2010.pdf",
        journal = "Comp. Phys. Comm.",
        volume = "181"
    }

    @article {
        author = "M. Bernaschi, M. Fatica, S. Melchionna, S. Succi and E. Kaxiras",
        title = "A flexible high-performance Lattice Boltzmann GPU code for the simulations of fluid flows in complex geometries",
        URL = "Papers/ConcComp_22_1-14_2010.pdf",
        journal = "Concurrency Computat.: Pract. Exper.",
        volume = "22"
    }

    @article {
        author = "E. Manousakis, J. Ren, S. Meng and E. Kaxiras",
        title = "Is the nature of magnetic order in copper-oxides and iron-pnictides  different?",
        URL = "Papers/SolStComm_150_62-65_2010.pdf",
        journal = "Sol. St. Comm.",
        volume = "150"
    }

    @article {
        author = "A. Gali, E. Janzen, P. Deak, G. Kresse and E. Kaxiras",
        title = "Theory of Spin-Conserving Excitation of the N-V Center in Diamond",
        URL = "Papers/PhysRevLett_103_186404_2009.pdf",
        journal = "Phys. Rev. Lett.",
        volume = "103"
    }

    @article {
        author = "S.K.R.S. Sankaranarayanan, E. Kaxiras and S. Ramanathan",
        title = "Electric field tuning of oxygen stoichiometry at oxide surfaces: molecular dynamics isimulations studies iof zirconia",
        URL = "Papers/EnEnviSci_2_1196-1204_2009.pdf",
        journal = "Energy & Environmental Sci.",
        volume = "2"
    }

    @article {
        author = "M. Bernaschi, S. Melchionna, S. Succi, M. Fyta, E. Kaxiras",
        title = "MUPHY: A parallel MUlti PHYsics/scale code for high performance  bio-fluidic simulations",
        URL = "Papers/CompPhysComm_180_1495-1502_2009.pdf",
        journal = "Comp. Phys. Comm.",
        volume = "180"
    }

    @article {
        author = "T.A. Baker, B.J. Xu, X.Y. Liu, E. Kaxiras and C.M. Friend",
        title = "Nature of Oxidation of the Au(111) Surface: Experiment and Theoretical Investigation",
        URL = "Papers/JPhysChemC_113_16561-16564_2009.pdf",
        journal = "J. Phys. Chem. C",
        volume = "113"
    }

    @article {
        author = "F.J. Rybicki, S. Melchionna, D. Mitsouras, A.U. Coskun, A.G. Whitmore, E. Kaxiras, S. Succi, P.H. Stone and C.L. Feldman",
        title = "Prediction of coronary artery plaque progression and potential rupture from 320-detector row prospectively ECG-gated single heart beat CT angiography:  Lattice Boltzmann evaluation of endothelial shear stress",
        URL = "Papers/IntJCardImag_25_289-299_2009.pdf",
        journal = "Int. J. Cardiovasc. Imaging",
        volume = "25"
    }

    @article {
        author = "H. Chen, W.G. Zhu, E. Kaxiras, and Z.Y. Zhang",
        title = "Optimization of Mn doping in group-IV-based dilute magnetic semiconductors by electronic codopants",
        URL = "Papers/PhysRevB_79_235202_2009.pdf",
        journal = "Phys. Rev. B",
        volume = "79"
    }

    @article {
        author = "M. Fyta, S. Melchionna, M. Bernaschi, E. Kaxiras and S. Succi",
        title = "Numerical simulation of conformational variability in biopolymer translocation  through wide nanopores",
        URL = "Papers/JStatMech_2009.pdf",
        journal = "J. Stat. Mech: Th. and Exper.",
        volume = "06"
    }

    @article {
        author = "E.M. Kotsalis, J.H. Walther, E. Kaxiras and P. Koumoutsakos",
        title = "Control algorithm for multiscale flow simulations of water",
        URL = "Papers/PhysRevE_79_045701RC_2009.pdf",
        journal = "Phys. Rev. E - Rap. Comm.",
        volume = "79"
    }

    @article {
        author = "C.E. Lekka, J. Ren, S. Meng and E. Kaxiras",
        title = "Structural, Electronic, and Optical Properties of Representative Cu-Flavonoid Complexes",
        URL = "Papers/JPhysChemB_113_6478_2009.pdf",
        journal = "J. Phys. Chem. B",
        volume = "113"
    }

    @article {
        author = "W.L. Wang, O.V. Yazyev, S. Meng and E. Kaxiras",
        title = "Topological Frustration in Graphene Nanoflakes: Magnetic Order and Spin Logic Devices",
        URL = "Papers/PhysRevLett_102_157201_2009.pdf",
        journal = "Phys. Rev. Lett.",
        volume = "102"
    }

    @article {
        author = "A. Gali and E. Kaxiras",
        title = "Comment on '",
        URL = "Papers/PhysRevLett_102_149703_2009.pdf",
        journal = "Ab initio",
        volume = "102"
    }

    @article {
        author = "S. Melchionna, M. Bernaschi, M. Fyta, E. Kaxiras and S. Succi",
        title = "Quantized biopolymer translocation through nanopores: Departure from simple scaling",
        URL = "Papers/PhysRevE_79_030901RC_2009.pdf",
        journal = "Phys. Rev. E - Rap. Comm.",
        volume = "79"
    }

    @article {
        author = "S.K.R.S. Sankaranarayanan, E. Kaxiras, S. Ramanathan",
        title = "Atomistic Simulation of Field Enhanced Oxidation of Al(1000) Beyond the Mott Potential",
        URL = "Papers/PhysRevLett_102_095504_2009.pdf",
        journal = "Phys. Rev. Lett.",
        volume = "102"
    }

    @article {
        author = "T.A. Baker, C.M. Friend and E. Kaxiras",
        title = "Effects of chlorine and oxygen coverage on the structure of the Au(111) surface",
        URL = "Papers/JChemPhys_130_084701_2009.pdf",
        journal = "J. Chem. Phys.",
        volume = "130"
    }

    @article {
        author = "T.A. Baker, C.M. Friend and E. Kaxiras",
        title = "Atomic Oxygen Adsorption on Au(111) Surfaces with Defects",
        URL = "Papers/JPhysChemC_113_3232_2009.pdf",
        journal = "J. Phys. Chem. C",
        volume = "113"
    }

    @article {
        author = "E. Kaxiras and S. Succi",
        title = "Multiscale simulations of complex systems: computation meets reality",
        URL = "Papers/SciModSim_15_59_2008.pdf",
        journal = "Sci. Model. Simul.",
        volume = "15"
    }

    @article {
        author = "E. Manousakis, J. Ren, S. Meng and E. Kaxiras",
        title = "Effective Hamiltonian for FeAs-based superconductors",
        URL = "Papers/PhysRevB_78_205112_2008.pdf",
        journal = "Phys. Rev. B",
        volume = "78"
    }

**1.4** [5 pts] Convert the list of dictionaries into standard tabular .csv format using pandas, and write the results into a file called `publist.csv`. The csv file should have a header and no integer index._____no_output_____

# your code here
ARTICLES_CSV_PATH = "./data/publist.csv"
df = pd.DataFrame(articles_list)_____no_output_____# writing to CSV file
df.to_csv(path_or_buf=ARTICLES_CSV_PATH, header=True, index=False)_____no_output_____

## Follow the stars in IMDb's list of "The Top 100 Stars for 2018"

### Overview
In this part, your goal is to extract information from IMDb's Top 100 Stars for 2018 (https://www.imdb.com/list/ls045252306/) and perform some analysis on each star in the list. In particular we are interested to know:
+ how many performers made their first movie at 17?
+ how many performers started as child actors? (i.e., younger than 12)
+ who is the most proliferate actress or actor in IMDb's list of the Top 100 Stars for 2018?

These questions are addressed in more details in the questions below.

_____no_output_____
 Question 2 [60 pts]: Web Scraping using Beautiful Soup and exploring using Pandas

**2.1 [5 pts]** Download the webpage of the "Top 100 Stars for 2018" (https://www.imdb.com/list/ls045252306/) into a `requests` object and name it `my_page`. Explain what the following attributes are (1 or 2 sentences for each):

- `my_page.text`,
- `my_page.status_code`,
- `my_page.content`.

**2.2 [5 pts]** Create a Beautiful Soup object named `star_soup` using `my_page` as input.

**2.3 [15 pts]** Write a function called `parse_stars` that accepts `star_soup` as its input and generates a list of dictionaries named `starlist` (see definition below). The order of dictionaries does not matter. One of the fields of this dictionary is the `url` of each star's individual page, which you need to save in the `page` field. Note that there is a ton of information about each star on these webpages. Each dictionary corresponds to a star profile and it should have the following data:

```
name: the name of the actor/actress as it appears at the top
gender: 0 or 1: translate the word 'actress' into 1 and 'actor' into '0'
url: the url of the link under their name that leads to a page with details
page: BS object with html text acquired by scraping the above 'url' page'
```

**2.4 [15 pts]** Write a function called `create_star_table`, which takes `starlist` as an input and extracts information about each star (see function definition for the exact information to be extracted and the exact output definition).  Only extract information from the first box on each star's page. If the first box is acting, consider only acting credits and the star's acting debut, if the first box is Directing, consider only directing credits and directorial debut.

**2.6 [6 pts]** We provide a JSON file called `data/staff_starinfo.json` created by CS109 teaching staff for consistency, which you should use for the rest of the homework. Import the contents of this JSON file  into a pandas dataframe called `frame`. Check the types of variables in each column and clean these variables if needed. Add a new column to your dataframe with the age of each actor when they made their first appearance, movie or TV, (name this column `age_at_first_movie`). Check some of the values of this new column. Do you find any problems? You don't need to fix them.

**2.7 [4 pts]** You are now ready to answer the following intriguing questions:
- **2.7.1** How many performers made their first appearance (movie or TV) when he/she was 17 years old?

- **2.7.2** How many performers started as child actors? Define child actor as a person younger than 12 years old.

**2.8 [6 pts]** Use your Python visualization skills to further explore the data:
- **2.8.1** Create 2 scatter plots: one showing the relationship between age at first movie and number of credits, the other between year born and number of credits. What can you say about these relationships? Are there any apparent outliers? Please limit your written responses to 4 sentences or fewer.
- **2.8.2** Create 2 histograms in a single plot comparing the distribution of actors' current ages to actresses' current ages. What does this visualization tell you? (4 sentences or fewer)
- **2.8.3** Create a box plot comparing the credits-per-year-active for actors and actresses. Here we assume all stars in the list are still active. Do these distributions look the same across genders? Comment on anything else of interest gleaned from your plot. (4 sentences or fewer)

**2.9 [2 pts]** Make a plot of the number of credits against the name of actor/actress. Who is the most prolific actress or actor in IMDb's list of the Top 100 Stars for 2018? Define **most prolific** as the performer with the most credits.

**2.10 [2 pts]** In 4 or fewer sentences, comment on what you see in the plots above.  Are there any surprises or patterns?  Please **have some fun** with this question.

### Hints
- Create a variable that groups actors/actresses by the age of their first movie. Use pandas' `.groupby` to divide the dataframe into groups of performers that for example started performing as children (age $<$ 12). The grouped variable is a `GroupBy` pandas object and this object has all of the information needed to then apply operations to each of the groups.
- When cleaning the data make sure the variables with which you are performing calculations are in numerical format.
- The column with the year has some values that are double, e.g. **'2000-2001'** and the column with age has some empty cells. You need to deal with these in a reasonable fashion before performing calculations on the data.
- You should include both movies and TV shows.

### Resources
- The `requests` library makes working with HTTP requests easy. For more on the `requests` library see http://docs.python-requests.org/

### Answers_____no_output_____

import requests
import re # you may use regexes but they are not required

from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry_____no_output_____

**2.1** [5 pts] Download the webpage of the "Top 100 Stars for 2018" (https://www.imdb.com/list/ls045252306/) into a `requests` object and name it `my_page`. Explain what the following attributes are:

- `my_page.text`,
- `my_page.status_code`,
- `my_page.content`.
_____no_output_____

# your code here
IMDB_2018_TOP_100_URL = "https://www.imdb.com/list/ls045252306/"

# To avoid network throttling and responsible scraping, I am leverage the below code
# Source - https://www.peterbe.com/plog/best-practice-with-retries-with-requests
def requests_retry_session(
    retries=3,
    backoff_factor=0.3,
    status_forcelist=(500, 502, 504),
    session=None,
):
    session = session or requests.Session()
    retry = Retry(
        total=retries,
        read=retries,
        connect=retries,
        backoff_factor=backoff_factor,
        status_forcelist=status_forcelist,
    )
    adapter = HTTPAdapter(max_retries=retry)
    session.mount('http://', adapter)
    session.mount('https://', adapter)
    return session

my_page = requests_retry_session().get(IMDB_2018_TOP_100_URL)_____no_output_____

*your answer here*
[Source](https://www.geeksforgeeks.org/response-content-python-requests/?ref=rp)

-  __my_page.text__: This returned the **UNICODE** content of the response fetched from the 2018 top stars URI when  `requests.get`was used.

-  __my_page.status_code__: This returned a number that indicates the status of the server that handled our request call. For this request, we received a 200 which meant the request was OK. However we could have gotten a 404 which would mean that the requested resource was not found.

-  __my_page.content__: This returned the **BYTES** content of the response fetched from the 2018 top stars URI when `requests.get` was used.

_____no_output_____**2.2** [5 pts] Create a Beautiful Soup object named `star_soup` using `my_page` as input.
_____no_output_____

# your code here
def make_top_100_imdb_star_soup(response) -> BeautifulSoup:
    """
    Take a response content and convert into a BS object.

       Args:
           response: (response)  HTTP response object of an HTML page

       Returns:
           A BS object containing the HTML page ready to be parsed.
    """
    return BeautifulSoup(response.content, 'html.parser')_____no_output_____# check your code - you should see familiar HTML code
star_soup = make_top_100_imdb_star_soup(my_page)
print (star_soup.prettify()[:])<!DOCTYPE html>

  <meta charset="utf-8"/>
  <meta content="IE=edge" http-equiv="X-UA-Compatible"/>
  <meta content="app-id=342792525, app-argument=imdb:///list/ls045252306?src=mdot" name="apple-itunes-app"/>

  <title>
   Top 100 Stars of 2018 - IMDb
  </title>

  <link href="https://www.imdb.com/list/ls045252306/" rel="canonical"/>
  <meta content="http://www.imdb.com/list/ls045252306/" property="og:url">

   <link href="https://m.media-amazon.com/images/G/01/imdb/images-ANDW73HA/favicon_desktop_32x32._CB1582158068_.png" rel="icon" sizes="32x32"/>
   <link href="https://m.media-amazon.com/images/G/01/imdb/images-ANDW73HA/favicon_iPad_retina_167x167._CB1582158068_.png" rel="icon" sizes="167x167"/>
   <link href="https://m.media-amazon.com/images/G/01/imdb/images-ANDW73HA/favicon_iPhone_retina_180x180._CB1582158069_.png" rel="icon" sizes="180x180"/>
   <link href="https://m.media-amazon.com/images/G/01/imdb/images-ANDW73HA/apple-touch-icon-mobile._CB479963088_.png" rel="apple-touch-icon"/>
   <link href="https://m.media-amazon.com/images/G/01/imdb/images-ANDW73HA/apple-touch-icon-mobile-76x76._CB479962152_.png" rel="apple-touch-icon" sizes="76x76"/>
   <link href="https://m.media-amazon.com/images/G/01/imdb/images-ANDW73HA/apple-touch-icon-mobile-120x120._CB479963088_.png" rel="apple-touch-icon" sizes="120x120"/>
   <link href="https://m.media-amazon.com/images/G/01/imdb/images-ANDW73HA/apple-touch-icon-web-152x152._CB479963088_.png" rel="apple-touch-icon" sizes="152x152"/>
   <link href="https://m.media-amazon.com/images/G/01/imdb/images-ANDW73HA/android-mobile-196x196._CB479962153_.png" rel="shortcut icon" sizes="196x196"/>
   <meta content="#000000" name="theme-color">
    <link href="https://m.media-amazon.com/images/G/01/imdb/images/imdbsearch-3349468880._CB466670431_.xml" rel="search" title="IMDb" type="application/opensearchdescription+xml"/>

    <meta content="ls045252306" property="pageId">
     <meta content="list" property="pageType"/>
     <meta content="people" property="subpageType"/>
     <link href="https://m.media-amazon.com/images/G/01/imdb/images-ANDW73HA/imdb_fb_logo._CB1542065250_.png" rel="image_src"/>
     <meta content="https://m.media-amazon.com/images/G/01/imdb/images-ANDW73HA/imdb_fb_logo._CB1542065250_.png" property="og:image"/>
     <meta content="115109575169727" property="fb:app_id"/>
     <meta content="Top 100 Stars of 2018 - IMDb" property="og:title"/>
     <meta content="IMDb" property="og:site_name"/>
     <meta content="Top 100 Stars of 2018 - IMDb" name="title"/>
     <meta content="Top 100 Stars of 2018" name="description"/>
     <meta content="Top 100 Stars of 2018" property="og:description"/>
     <meta content="NT03BZ2V5KDVJ8T24FKC" name="request_id"/>

     <link href="https://m.media-amazon.com/images/I/31vI4owPDmL.css" rel="stylesheet" type="text/css">
      <link href="https://m.media-amazon.com/images/I/41zRCwQldGL.css" rel="stylesheet" type="text/css"/>
      <link href="https://m.media-amazon.com/images/G/01/imdb/css/collections/consumersite-3620993703._CB427930302_.css" rel="stylesheet" type="text/css"/>

      <link href="https://m.media-amazon.com/images/G/01/imdb/css/collections/other-2259726002._CB432933419_.css" rel="stylesheet" type="text/css"/>
      <link href="https://m.media-amazon.com/images/G/01/imdb/css/collections/starbarwidget-1368445358._CB440579467_.css" rel="stylesheet" type="text/css"/>
      <link href="https://m.media-amazon.com/images/G/01/imdb/css/collections/watchlistButton-3930250830._CB430639701_.css" rel="stylesheet" type="text/css"/>
      <link href="https://m.media-amazon.com/images/G/01/imdb/css/collections/lists-3898874711._CB466671881_.css" rel="stylesheet" type="text/css"/>

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              <path d="M18.2401737,2.15577889 C18.3613005,2.22685521 18.4456965,2.34775012 18.4712812,2.48683417 C18.5047231,2.63758794 18.5214441,2.97929648 18.5214441,3.5119598 L18.5214441,8.09246231 C18.5214441,8.87919598 18.4710822,9.36160804 18.3703583,9.53969849 C18.2696345,9.71778894 18.0007058,9.80623116 17.5635722,9.80503729 L17.5635722,2.05025126 C17.8944083,2.05025126 18.1199421,2.08542714 18.2401737,2.15577889 Z M18.2085233,11.8426131 C18.9366811,11.8426131 19.4817047,11.8024121 19.8435939,11.7220101 C20.1760582,11.6557965 20.4883129,11.5111601 20.754886,11.2998995 C21.0104507,11.0828833 21.1913005,10.7896393 21.2714441,10.4623116 C21.3705755,10.1053266 21.429696,9.39738693 21.429696,8.33849246 L21.429696,4.18914573 C21.429696,3.07296482 21.3866992,2.32341709 21.3192182,1.94231156 C21.2491064,1.55561593 21.073757,1.19626854 20.8128122,0.904522613 C20.54249,0.592964824 20.1481542,0.369447236 19.6298046,0.233969849 C19.1114549,0.0982914573 18.2658523,0.0295477387 16.7944083,0.0295477387 L14.5251357,0.0295477387 L14.5251357,11.8426131 L18.2085233,11.8426131 Z">
              </path>
              <path d="M26.416721,8.97527638 C26.416721,9.54693467 26.3886536,9.90874372 26.332519,10.0607035 C26.2763844,10.2102513 26.0339305,10.2868342 25.8458198,10.2868342 C25.657709,10.2868342 25.5472313,10.2132663 25.4833333,10.0673367 C25.4194354,9.92140704 25.3925624,9.59095477 25.3925624,9.07175879 L25.3925624,5.94934673 C25.3925624,5.41025126 25.4192363,5.07417085 25.4725841,4.94110553 C25.525932,4.8080402 25.6429786,4.74150754 25.8237242,4.74150754 C26.0094463,4.74150754 26.2584691,4.81748744 26.3211726,4.97065327 C26.3838762,5.1238191 26.416721,5.44884422 26.416721,5.9481407 L26.416721,8.97527638 Z M22.4652009,0.0301507538 L22.4652009,11.8426131 L25.2008686,11.8426131 L25.3901737,11.0900503 C25.6130801,11.37176 25.8917241,11.6034266 26.2083062,11.7702513 C26.5068947,11.921608 26.9517915,11.9975879 27.2963626,11.9975879 C27.741081,12.0083011 28.1774148,11.8742607 28.5408795,11.6152764 C28.8904271,11.360402 29.1125769,11.0588945 29.207329,10.7107538 C29.3020811,10.3626131 29.349059,9.83497487 29.3482628,9.1278392 L29.3482628,5.8160804 C29.3482628,5.10211055 29.3333333,4.63778894 29.301683,4.41889447 C29.2603631,4.17705181 29.1645365,3.94803829 29.0216069,3.74954774 C28.8515909,3.51011348 28.6163121,3.32574882 28.3444083,3.21889447 C28.0116005,3.08534049 27.6555905,3.02074296 27.297557,3.02894472 C26.9482085,3.02894472 26.5009229,3.09949749 26.2029316,3.23819095 C25.8905716,3.38828976 25.6139569,3.60466937 25.3919653,3.87256281 L25.3919653,0.0301507538 L22.4652009,0.0301507538 Z">
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            </svg>

             For Industry Professionals

           <svg class="ipc-icon ipc-icon--launch" fill="currentColor" height="24" role="presentation" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg">
            <path d="M16 16.667H8A.669.669 0 0 1 7.333 16V8c0-.367.3-.667.667-.667h3.333c.367 0 .667-.3.667-.666C12 6.3 11.7 6 11.333 6h-4C6.593 6 6 6.6 6 7.333v9.334C6 17.4 6.6 18 7.333 18h9.334C17.4 18 18 17.4 18 16.667v-4c0-.367-.3-.667-.667-.667-.366 0-.666.3-.666.667V16c0 .367-.3.667-.667.667zm-2.667-10c0 .366.3.666.667.666h1.727L9.64 13.42a.664.664 0 1 0 .94.94l6.087-6.087V10c0 .367.3.667.666.667.367 0 .667-.3.667-.667V6h-4c-.367 0-.667.3-.667.667z">
            </path>
           </svg>

      <svg class="ipc-logo" height="32" id="home_img" version="1.1" viewbox="0 0 64 32" width="64" xmlns="http://www.w3.org/2000/svg">
       <g fill="#F5C518">
        <rect height="100%" rx="4" width="100%" x="0" y="0">
        </rect>
       </g>
       <g fill="#000000" fill-rule="nonzero" transform="translate(8.000000, 7.000000)">
        <polygon points="0 18 5 18 5 0 0 0">
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        <path d="M15.6725178,0 L14.5534833,8.40846934 L13.8582008,3.83502426 C13.65661,2.37009263 13.4632474,1.09175121 13.278113,0 L7,0 L7,18 L11.2416347,18 L11.2580911,6.11380679 L13.0436094,18 L16.0633571,18 L17.7583653,5.8517865 L17.7707076,18 L22,18 L22,0 L15.6725178,0 Z">
        </path>
        <path d="M24,18 L24,0 L31.8045586,0 C33.5693522,0 35,1.41994415 35,3.17660424 L35,14.8233958 C35,16.5777858 33.5716617,18 31.8045586,18 L24,18 Z M29.8322479,3.2395236 C29.6339219,3.13233348 29.2545158,3.08072342 28.7026524,3.08072342 L28.7026524,14.8914865 C29.4312846,14.8914865 29.8796736,14.7604764 30.0478195,14.4865461 C30.2159654,14.2165858 30.3021941,13.486105 30.3021941,12.2871637 L30.3021941,5.3078959 C30.3021941,4.49404499 30.272014,3.97397442 30.2159654,3.74371416 C30.1599168,3.5134539 30.0348852,3.34671372 29.8322479,3.2395236 Z">
        </path>
        <path d="M44.4299079,4.50685823 L44.749518,4.50685823 C46.5447098,4.50685823 48,5.91267586 48,7.64486762 L48,14.8619906 C48,16.5950653 46.5451816,18 44.749518,18 L44.4299079,18 C43.3314617,18 42.3602746,17.4736618 41.7718697,16.6682739 L41.4838962,17.7687785 L37,17.7687785 L37,0 L41.7843263,0 L41.7843263,5.78053556 C42.4024982,5.01015739 43.3551514,4.50685823 44.4299079,4.50685823 Z M43.4055679,13.2842155 L43.4055679,9.01907814 C43.4055679,8.31433946 43.3603268,7.85185468 43.2660746,7.63896485 C43.1718224,7.42607505 42.7955881,7.2893916 42.5316822,7.2893916 C42.267776,7.2893916 41.8607934,7.40047379 41.7816216,7.58767002 L41.7816216,9.01907814 L41.7816216,13.4207851 L41.7816216,14.8074788 C41.8721037,15.0130276 42.2602358,15.1274059 42.5316822,15.1274059 C42.8031285,15.1274059 43.1982131,15.0166981 43.281155,14.8074788 C43.3640968,14.5982595 43.4055679,14.0880581 43.4055679,13.2842155 Z">
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      </svg>

        <svg class="ipc-logo" height="13" version="1.1" viewbox="0 0 51 13" width="51" xmlns="http://www.w3.org/2000/svg">
         <g fill="none" fill-rule="evenodd">
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           <path d="M24.567.026v12.796h2.99l.211-.813c.266.33.564.57.893.739.33.16.812.241 1.19.241.522 0 .98-.136 1.36-.415.384-.273.626-.602.726-.975.105-.377.155-.948.155-1.711v-3.59c0-.776-.013-1.279-.05-1.514-.031-.236-.137-.478-.304-.726A1.666 1.666 0 0 0 31 3.48a2.964 2.964 0 0 0-1.148-.205c-.378 0-.868.075-1.197.23-.322.148-.62.378-.887.682V.026h-3.2zm4.324 9.695c0 .614-.031 1.01-.093 1.172-.062.161-.33.241-.534.241-.198 0-.33-.074-.397-.235-.062-.155-.099-.514-.099-1.08V6.44c0-.583.03-.943.087-1.092.062-.142.192-.217.384-.217.205 0 .477.087.546.249.069.167.106.52.106 1.06v3.282zM.018.026h3.319v12.796H.018zM10.42.026l-.77 5.979-.47-3.25a93.824 93.824 0 0 0-.404-2.73H4.472v12.796H7.38l.012-8.447 1.222 8.447h2.072l1.166-8.633.006 8.633h2.902V.026H10.42zM19.922 12.822c.794 0 1.39-.044 1.787-.13.39-.087.725-.236.992-.46.266-.217.459-.52.564-.905.112-.384.174-1.153.174-2.3V4.534c0-1.21-.05-2.022-.118-2.437a2.286 2.286 0 0 0-.559-1.123c-.291-.335-.725-.577-1.29-.725-.564-.15-1.494-.224-3.1-.224h-2.476v12.796h4.026zm.031-10.488c.13.074.217.192.255.36.037.16.056.532.056 1.11v4.955c0 .856-.056 1.377-.168 1.57-.111.192-.403.285-.88.285V2.216c.359 0 .607.037.737.118z">
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          <g fill-rule="nonzero">
           <path d="M2.75 9.55V2.09H.019V.014h8.083V2.09h-2.73V9.55H2.75z" fill="url(#ipc-svg-gradient-tv-logo-t)" transform="translate(34.14 3.278)">
           </path>
           <path d="M10.061 9.55L6.72.014h2.908L11.5 7.046 13.376.014h2.84L12.874 9.55z" fill="url(#ipc-svg-gradient-tv-logo-v)" transform="translate(34.14 3.278)">
           </path>
          </g>
         </g>
        </svg>

     <input aria-hidden="true" class="imdb-header-search__state EL4bTiUhQdfIvyX_PMRVv sc-gqjmRU hOwCdO" hidden="" id="navSearch-searchState" name="navSearch-searchState" type="checkbox"/>

      <form action="/find" class="_19kygDgP4Og4wL_TIXtDmm imdb-header__search-form sc-dnqmqq iDnumk" id="nav-search-form" method="get" name="nav-search-form" role="search">

           All
           <svg class="ipc-icon ipc-icon--arrow-drop-down navbar__flyout__button-pointer" fill="currentColor" height="24" role="presentation" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg">
            <path d="M0 0h24v24H0V0z" fill="none">
            </path>
            <path d="M8.71 11.71l2.59 2.59c.39.39 1.02.39 1.41 0l2.59-2.59c.63-.63.18-1.71-.71-1.71H9.41c-.89 0-1.33 1.08-.7 1.71z">
            </path>
           </svg>

         <input aria-hidden="true" class="ipc-menu__focused-state" hidden="" id="navbar-search-category-select" name="navbar-search-category-select" tabindex="-1" type="checkbox"/>

               <svg class="ipc-icon ipc-icon--search _2re8nTkPmRXI_TBcLnh1u8" fill="currentColor" height="24" role="presentation" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg">
                <path d="M0 0h24v24H0V0z" fill="none">
                </path>
                <path d="M15.5 14h-.79l-.28-.27a6.5 6.5 0 0 0 1.48-5.34c-.47-2.78-2.79-5-5.59-5.34a6.505 6.505 0 0 0-7.27 7.27c.34 2.8 2.56 5.12 5.34 5.59a6.5 6.5 0 0 0 5.34-1.48l.27.28v.79l4.25 4.25c.41.41 1.08.41 1.49 0 .41-.41.41-1.08 0-1.49L15.5 14zm-6 0C7.01 14 5 11.99 5 9.5S7.01 5 9.5 5 14 7.01 14 9.5 11.99 14 9.5 14z">
                </path>
               </svg>
               All

               <svg class="ipc-icon ipc-icon--movie _2re8nTkPmRXI_TBcLnh1u8" fill="currentColor" height="24" role="presentation" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg">
                <path d="M0 0h24v24H0V0z" fill="none">
                </path>
                <path d="M18 4v1h-2V4c0-.55-.45-1-1-1H9c-.55 0-1 .45-1 1v1H6V4c0-.55-.45-1-1-1s-1 .45-1 1v16c0 .55.45 1 1 1s1-.45 1-1v-1h2v1c0 .55.45 1 1 1h6c.55 0 1-.45 1-1v-1h2v1c0 .55.45 1 1 1s1-.45 1-1V4c0-.55-.45-1-1-1s-1 .45-1 1zM8 17H6v-2h2v2zm0-4H6v-2h2v2zm0-4H6V7h2v2zm10 8h-2v-2h2v2zm0-4h-2v-2h2v2zm0-4h-2V7h2v2z">
                </path>
               </svg>
               Titles

               <svg class="ipc-icon ipc-icon--television _2re8nTkPmRXI_TBcLnh1u8" fill="currentColor" height="24" role="presentation" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg">
                <path d="M0 0h24v24H0V0z" fill="none">
                </path>
                <path d="M21 3H3c-1.1 0-2 .9-2 2v12c0 1.1.9 2 2 2h5v1c0 .55.45 1 1 1h6c.55 0 1-.45 1-1v-1h5c1.1 0 1.99-.9 1.99-2L23 5a2 2 0 0 0-2-2zm-1 14H4c-.55 0-1-.45-1-1V6c0-.55.45-1 1-1h16c.55 0 1 .45 1 1v10c0 .55-.45 1-1 1z">
                </path>
               </svg>
               TV Episodes

               <svg class="ipc-icon ipc-icon--people _2re8nTkPmRXI_TBcLnh1u8" fill="currentColor" height="24" role="presentation" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg">
                <path d="M0 0h24v24H0V0z" fill="none">
                </path>
                <path d="M16 11c1.66 0 2.99-1.34 2.99-3S17.66 5 16 5s-3 1.34-3 3 1.34 3 3 3zm-8 0c1.66 0 2.99-1.34 2.99-3S9.66 5 8 5 5 6.34 5 8s1.34 3 3 3zm0 2c-2.33 0-7 1.17-7 3.5V18c0 .55.45 1 1 1h12c.55 0 1-.45 1-1v-1.5c0-2.33-4.67-3.5-7-3.5zm8 0c-.29 0-.62.02-.97.05.02.01.03.03.04.04 1.14.83 1.93 1.94 1.93 3.41V18c0 .35-.07.69-.18 1H22c.55 0 1-.45 1-1v-1.5c0-2.33-4.67-3.5-7-3.5z">
                </path>
               </svg>
               Celebs

               <svg class="ipc-icon ipc-icon--business _2re8nTkPmRXI_TBcLnh1u8" fill="currentColor" height="24" role="presentation" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg">
                <path d="M0 0h24v24H0V0z" fill="none">
                </path>
                <path d="M12 7V5c0-1.1-.9-2-2-2H4c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h16c1.1 0 2-.9 2-2V9c0-1.1-.9-2-2-2h-8zM6 19H4v-2h2v2zm0-4H4v-2h2v2zm0-4H4V9h2v2zm0-4H4V5h2v2zm4 12H8v-2h2v2zm0-4H8v-2h2v2zm0-4H8V9h2v2zm0-4H8V5h2v2zm9 12h-7v-2h2v-2h-2v-2h2v-2h-2V9h7c.55 0 1 .45 1 1v8c0 .55-.45 1-1 1zm-1-8h-2v2h2v-2zm0 4h-2v2h2v-2z">
                </path>
               </svg>
               Companies

               <svg class="ipc-icon ipc-icon--label _2re8nTkPmRXI_TBcLnh1u8" fill="currentColor" height="24" role="presentation" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg">
                <path d="M0 0h24v24H0V0z" fill="none">
                </path>
                <path d="M17.63 5.84C17.27 5.33 16.67 5 16 5L5 5.01C3.9 5.01 3 5.9 3 7v10c0 1.1.9 1.99 2 1.99L16 19c.67 0 1.27-.33 1.63-.84l3.96-5.58a.99.99 0 0 0 0-1.16l-3.96-5.58z">
                </path>
               </svg>
               Keywords

               <svg class="ipc-icon ipc-icon--find-in-page _2re8nTkPmRXI_TBcLnh1u8" fill="currentColor" height="24" role="presentation" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg">
                <path d="M0 0h24v24H0V0z" fill="none">
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                <path d="M20 19.59V8.83c0-.53-.21-1.04-.59-1.41l-4.83-4.83c-.37-.38-.88-.59-1.41-.59H6c-1.1 0-1.99.9-1.99 2L4 20c0 1.1.89 2 1.99 2H18c.45 0 .85-.15 1.19-.4l-4.43-4.43c-.86.56-1.89.88-3 .82-2.37-.11-4.4-1.96-4.72-4.31a5.013 5.013 0 0 1 5.83-5.61c1.95.33 3.57 1.85 4 3.78.33 1.46.01 2.82-.7 3.9L20 19.59zM9 13c0 1.66 1.34 3 3 3s3-1.34 3-3-1.34-3-3-3-3 1.34-3 3z">
                </path>
               </svg>
               Advanced Search

               <svg class="ipc-icon ipc-icon--chevron-right" fill="currentColor" height="24" role="presentation" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg">
                <path d="M0 0h24v24H0V0z" fill="none">
                </path>
                <path d="M9.29 6.71a.996.996 0 0 0 0 1.41L13.17 12l-3.88 3.88a.996.996 0 1 0 1.41 1.41l4.59-4.59a.996.996 0 0 0 0-1.41L10.7 6.7c-.38-.38-1.02-.38-1.41.01z">
                </path>
               </svg>

         <input aria-autocomplete="list" aria-controls="react-autowhatever-1" autocapitalize="off" autocomplete="off" autocorrect="off" class="imdb-header-search__input _3gDVKsXm3b_VAMhhSw1haV react-autosuggest__input" id="suggestion-search" name="q" placeholder="Search IMDb" type="text" value=""/>

       <button class="nav-search__search-submit _1-XI3_I8iwubPnQ1mmvW97" id="suggestion-search-button" type="submit">
        <svg class="ipc-icon ipc-icon--magnify" fill="currentColor" height="24" role="presentation" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg">
         <path d="M0 0h24v24H0V0z" fill="none">
         </path>
         <path d="M15.5 14h-.79l-.28-.27a6.5 6.5 0 0 0 1.48-5.34c-.47-2.78-2.79-5-5.59-5.34a6.505 6.505 0 0 0-7.27 7.27c.34 2.8 2.56 5.12 5.34 5.59a6.5 6.5 0 0 0 5.34-1.48l.27.28v.79l4.25 4.25c.41.41 1.08.41 1.49 0 .41-.41.41-1.08 0-1.49L15.5 14zm-6 0C7.01 14 5 11.99 5 9.5S7.01 5 9.5 5 14 7.01 14 9.5 11.99 14 9.5 14z">
         </path>
        </svg>
       </button>
       <input name="ref_" type="hidden" value="nv_sr_sm"/>
      </form>

       <svg class="ipc-icon ipc-icon--clear" fill="currentColor" height="24" role="presentation" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg">
        <path d="M0 0h24v24H0V0z" fill="none">
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        <path d="M18.3 5.71a.996.996 0 0 0-1.41 0L12 10.59 7.11 5.7A.996.996 0 1 0 5.7 7.11L10.59 12 5.7 16.89a.996.996 0 1 0 1.41 1.41L12 13.41l4.89 4.89a.996.996 0 1 0 1.41-1.41L13.41 12l4.89-4.89c.38-.38.38-1.02 0-1.4z">
        </path>
       </svg>

      <svg class="ipc-icon ipc-icon--magnify" fill="currentColor" height="24" role="presentation" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg">
       <path d="M0 0h24v24H0V0z" fill="none">
       </path>
       <path d="M15.5 14h-.79l-.28-.27a6.5 6.5 0 0 0 1.48-5.34c-.47-2.78-2.79-5-5.59-5.34a6.505 6.505 0 0 0-7.27 7.27c.34 2.8 2.56 5.12 5.34 5.59a6.5 6.5 0 0 0 5.34-1.48l.27.28v.79l4.25 4.25c.41.41 1.08.41 1.49 0 .41-.41.41-1.08 0-1.49L15.5 14zm-6 0C7.01 14 5 11.99 5 9.5S7.01 5 9.5 5 14 7.01 14 9.5 11.99 14 9.5 14z">
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      </svg>

         <svg class="ipc-logo navbar__imdbpro-menu-toggle__name" height="13" version="1.1" viewbox="0 0 56 13" width="56">
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         Top 100 Stars of 2018

         by

          IMDb-Editors

          |

          created - 13 Nov 2018

          |

          updated - 12 Dec 2018

          |

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          Public

          Here are the 100 stars who consistently ranked the highest on IMDbPro's weekly STARmeter chart throughout 2018. STARmeter rankings are based on the actual pageviews of IMDb’s more than 250 million monthly unique visitors.

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            100 names

              1.

              Karen Gillan

             Actress

              |

              Selfie

             Karen Sheila Gillan was born and raised in Inverness, Scotland, as the only child of Marie Paterson and husband John Gillan, who is a singer and recording artist. She developed a love for acting very early on, attending several youth theatre groups and taking part in a wide range of productions at ...

              2.

              Bryce Dallas Howard

             Actress

              |

              Jurassic World

             Bryce Dallas Howard was born on March 2, 1981, in Los Angeles, California. She was conceived in Dallas, Texas (the reason for her middle name). Her father,

              Ron Howard

             , is a former actor turned Oscar-winning director. Her mother is actress and writer

              Cheryl Howard

             (née Alley). Her famous relatives ...

              3.

              Alicia Vikander

             Actress

              |

              Ex Machina

             Alicia Vikander is a Swedish actress, dancer and producer. She was born and raised in Gothenburg, Västra Götalands län, Sweden, to

              Maria Fahl-Vikander

             , an actress of stage and screen, and Svante Vikander, a psychiatrist. She is of Swedish and one quarter Finnish descent. Alicia began acting as a ...

              4.

              Tom Hardy

             Actor

              |

              Inception

             With his breakthrough performance as Eames in

              Christopher Nolan

             's sci-fi thriller

              Inception

             (2010), English actor Tom Hardy has been brought to the attention of mainstream audiences worldwide. However, the versatile actor has been steadily working on both stage and screen since his television debut...

              5.

              Rebecca Ferguson

             Actress

              |

              Mission: Impossible - Rogue Nation

             Rebecca Ferguson was born Rebecca Louisa Ferguson Sundström in Stockholm, Sweden, and grew up in its Vasastaden district. Her father is Swedish. Her mother, Rosemary Ferguson, is British, of Scottish and Northern Irish descent, and moved to Sweden at the age of 25. Rebecca attended an ...

              6.

              Lily James

             Actress

              |

              Cinderella

             Lily James was born Lily Chloe Ninette Thomson in Esher, Surrey, to Ninette (Mantle), an actress, and Jamie Thomson, an actor and musician. Her grandmother,

              Helen Horton

             , was an American actress. She began her education at Arts Educational School in Tring and subsequently went on to study acting at...

              7.

              Jessica Barden

             Actress

              |

              Hanna

             Jessica Barden is an English actress. She is best known for playing Alyssa in Channel 4 series The End of the F***ing World, and the film The Lobster (2015).

             She also had small roles in Tamara Drewe (2010), Hanna (2011) and Far from the Madding Crowd (2015).

             In 2016 she played Justine in Penny ...

              8.

              Hannah John-Kamen

             Actress

              |

              Ant-Man and the Wasp

             Hannah Dominique E. John-Kamen is a British actress. She is known for her roles as Dutch in the Syfy television series Killjoys, Ornela in the HBO series Game of Thrones, F'Nale Zandor in Steven Spielberg's Ready Player One, and Ghost in Ant-Man and the Wasp.

             Hannah was born in Beverley, Yorkshire, ...

              9.

              Josh Brolin

             Actor

              |

              Avengers: Endgame

             Rugged features and a natural charm have worked for Josh Brolin, the son of actor

              James Brolin

             . He has played roles as a policeman, a hunter, and the President of the United States.

             Brolin was born February 12, 1968 in Santa Monica, California, to Jane Cameron (Agee), a Texas-born wildlife activist,...

              10.

              Tessa Thompson

             Actress

              |

              Creed

             The actress Tessa Lynn Thompson was born on October 3, 1983 in Los Angeles, California. She is the daughter of singer-songwriter

              Marc Anthony Thompson

             and the granddaughter of actor-musician

              Bobby Ramos

             . She was raised in Los Angeles before moving to Brooklyn, New York. Her father is of ...

              11.

              Alexandra Daddario

             Actress

              |

              Baywatch

             Alexandra Anna Daddario was born on March 16, 1986 in New York City, New York, to Christina, a lawyer, and Richard Daddario, a prosecutor. Her brother is actor

              Matthew Daddario

             , her sister is actor

              Catharine Daddario

             , and her grandfather was congressman

              Emilio Daddario

             (Emilio Q. Daddario), of ...

              12.

              Brie Larson

             Actress

              |

              Room

             Brie Larson has built an impressive career as an acclaimed television actress, rising feature film star and emerging recording artist. A native of Sacramento, Brie started studying drama at the early age of 6, as the youngest student ever to attend the American Conservatory Theater in San Francisco...

              13.

              Carla Gugino

             Actress

              |

              Watchmen

             Carla Gugino was born in Sarasota, Florida, to Carl Gugino, an orthodontist. She is of Italian (father) and English-Irish (mother) ancestry. Gugino moved with her mother to Paradise, California, when Carla was just five years old. During her childhood, they moved many times within the state. But ...

              14.

              Emilia Clarke

             Actress

              |

              Game of Thrones

             British actress Emilia Clarke was born in London and grew up in Oxfordshire, England. Her father was a theatre sound engineer and her mother is a businesswoman. Her father was working on a theatre production of "Show Boat" and her mother took her along to the performance. This is when, at the age ...

              15.

              Evangeline Lilly

             Actress

              |

              Ant-Man

             Evangeline Lilly, born in Fort Saskatchewan, Alberta, in 1979, was discovered on the streets of Kelowna, British Columbia, by the famous Ford modeling agency. Although she initially decided to pass on a modeling career, she went ahead and signed with Ford anyway, to help pay for her University of ...

              16.

              Margot Robbie

             Actress

              |

              Suicide Squad

             Margot Elise Robbie was born on July 2, 1990 in Dalby, Queensland, Australia to Scottish parents. Her mother,

              Sarie Kessler

             , is a physiotherapist, and her father, is Doug Robbie. She comes from a family of four children, having two brothers and one sister. She graduated from Somerset College in ...

              17.

              Martha Higareda

             Actress

              |

              Amar te duele

             Higareda was born in Villahermosa, Tabasco, Mexico, the daughter of actress Martha Cervantes and therapist and artist Jose Luis Higareda, and sister of actress Miriam Higareda. She began acting on stage at a very early age, along with dancing jazz, flamenco, tap and folklore. At 14, she moved to ...

              18.

              Michael B. Jordan

             Actor

              |

              Black Panther

             Michael B. Jordan, the middle of three children, was born in Santa Ana, California and raised in Newark, New Jersey. He is the son of Donna (Davis), a high school counselor, and Michael A. Jordan. His middle name, Bakari, means "noble promise" in Swahili. (He is not related to, or named after, ...

              19.

              Ruby Rose

             Actress

              |

              Orange Is the New Black

             Ruby Rose Langenheim (born 20 March 1986), better known as Ruby Rose, is an Australian model, DJ, boxer, recording artist, actress, television presenter, and MTV VJ. Rose emerged in the media spotlight as a presenter on MTV Australia, followed by several high-profile modelling gigs, notably as the ...

              20.

              Olivia Cooke

             Actress

              |

              Ready Player One

             Olivia Cooke was born and raised in Oldham, a former textile manufacturing town in Greater Manchester, North West England. She comes from a family of non-actors; her father, John, is a retired police officer, and her mother is a sales representative. Cooke attended Royton and Crompton Secondary ...

              21.

              Morena Baccarin

             Actress

              |

              Deadpool

             Morena Baccarin was born in Rio de Janeiro, Brazil, to actress

              Vera Setta

             and journalist Fernando Baccarin. Her uncle was actor

              Ivan Setta

             . Morena has Italian and Brazilian Portuguese ancestry. She moved to New York at the age of 10, when her father was transferred there. She attended the LaGuardia...

              22.

              Yvonne Strahovski

             Actress

              |

              Dexter

             Yvonne Jaqueline Strzechowski was born and raised in Australia. Her parents were Polish immigrants. She attended the Santa Sabina College for her high school education. She then went on to study Performance at the University of Western Sydney's School of Contemporary Arts, graduating in 2003. ...

              23.

              Julia Garner

             Actress

              |

              Martha Marcy May Marlene

             Julia Garner is an American actress and model. She is best known for her roles in Electrick Children (2012), We Are What We Are (2013), The Perks of Being a Wallflower (2012), Sin City: A Dame to Kill For (2014), and Grandma (2015).

             Garner also starred in the Netflix series Ozark.

             She had her ...

              24.

              Noah Centineo

             Actor

              |

              To All the Boys I've Loved Before

             Noah Centineo is an American actor. He portrayed Jesus Adams Foster in

              The Fosters

             (2013), for which he was nominated for a Teen Choice Award. Since then, he has received both critical acclaim and audience adoration for starring in a series of romantic comedy films, beginning with

              To All the Boys

             ...

              25.

              Ana de Armas

             Actress

              |

              Blade Runner 2049

             Ana de Armas was born in Cuba on April 30, 1988. At the age of 14, she began her studies at the National Theatre School of Havana, where she graduated after 4 years. At the age of 16, she made her first film,

              Una rosa de Francia

             (2006), directed by

              Manuel Gutiérrez Aragón

             . A few titles came after ...

              26.

              Kiernan Shipka

             Actress

              |

              Carriers

             Kiernan Brennan Shipka is an American actress. She is known for playing Sally Draper on the AMC series

              Mad Men

             (2007), B. D. Hyman in the FX anthology series

              Feud: Bette and Joan

             (2017), and voicing Jinora in the

              Avatar: The Last Airbender

             (2005) spin-off,

              The Legend of Korra

             (2012). She stars as ...

              27.

              John Krasinski

             Actor

              |

              A Quiet Place

             Tall, handsome American film and television star John Krasinski is known for his role as sardonic nice guy Jim Halpert on NBC's popular TV series,

              The Office

             (2005), for which he won a 2007 and 2008 Screen Actors Guild Award for outstanding performance by an ensemble in a comedy series.

             Born John ...

              28.

              Meghan Markle

             Actress

              |

              Remember Me

             Meghan, (born Rachel Meghan Markle) is an US-born member of the British royal family and a former film and television actress.

             Meghan Markle was born on August 4, 1981 and raised in Los Angeles, California and is of mixed-race heritage. During her studies at Northwestern University, she began to ...

              29.

              Jacob Elordi

             Actor

              |

              The Kissing Booth

             Jacob Elordi was born on June 26, 1997 in Brisbane, Australia as Jacob Nathaniel Elordi. He is an actor known for the breakout Netflix Hit The Kissing Booth (2018), Swinging Safari (2017) and is anticipated in HBO/A24 drama series Euphoria (2019). Other titles include 2-Hearts (2019). He grew up ...

              30.

              Parker Posey

             Actress

              |

              Scream 3

             Parker Posey was born two months premature in Baltimore, Maryland, to Lynda (Patton) and Chris Posey. The family moved to Monroe, La. and then Laurel, Mississippi, where Chris became owner of Laurel's own Posey Chevrolet. Parker attended high school at R. H. Watkins High School in Laurel, and ...

              31.

              Rami Malek

             Actor

              |

              Bohemian Rhapsody

             Rami Said Malek (born May 12, 1981) is an American actor. He won a Critics' Choice Award and the Primetime Emmy Award for Outstanding Lead Actor in a Drama Series for his lead role as Elliot Alderson in the USA Network television series Mr. Robot. He also received Golden Globe Award, Screen Actors ...

              32.

              Vanessa Kirby

             Actress

              |

              The Crown

             Vanessa Kirby is an English stage, TV, and film actress. From 2016 to 2018, Kirby portrayed Princess Margaret in Peter Morgan's Netflix series The Crown, for which she won the BAFTA Award for Best Actress in a Supporting Role in a Television Series in 2018. She starred as Estella in the BBC ...

              33.

              Bonnie Aarons

             Actress

              |

              The Nun

             Bonnie Aarons is an actress and writer, known for

              The Nun

             (2018),

              I Know Who Killed Me

             (2007) and

              Mulholland Dr.

             (2001).

              34.

              Sonoya Mizuno

             Actress

              |

              Ex Machina

             Sonoya Mizuno was born on July 1, 1986 in Tokyo, Japan. She is an actress, known for

              Ex Machina

             (2014),

              La La Land

             (2016) and

              Maniac

             (2018).

              35.

              Zendaya

             Actress

              |

              Spider-Man: Homecoming

             Zendaya (which means "to give thanks" in the language of Shona) is an American actress and singer born in Oakland, California. She began her career appearing as a child model working for Macy's, Mervyns and Old Navy. She was a backup dancer before gaining prominence for her role as Rocky Blue on ...

              36.

              Debby Ryan

             Actress

              |

              Insatiable

             Born May 13, 1993 in Huntsville, Alabama, Debby moved to Texas as a small child and lived there for five years, before moving to Wiesbaden, Germany, with her family, where she lived for three years. While in Germany, Debby became fascinated with acting in local plays and musicals. By the age of ...

              37.

              Gal Gadot

             Actress

              |

              Wonder Woman

             Gal Gadot is an Israeli actress, singer, martial artist, and model. She was born in Rosh Ha'ayin, Israel, to a Jewish family. Her parents are Irit, a teacher, and Michael, an engineer, who is a sixth-generation Israeli. She served in the IDF for two years, and won the Miss Israel title in 2004.

             Gal ...

              38.

              Emily Blunt

             Actress

              |

              Edge of Tomorrow

             Emily Olivia Leah Blunt is a British actress known for her roles in

              The Devil Wears Prada

             (2006),

              The Young Victoria

             (2009),

              Edge of Tomorrow

             (2014), and

              The Girl on the Train

             (2016), among many others.

             Blunt was born on February 23, 1983, in Roehampton, South West London, England, the second of ...

              39.

              Timothée Chalamet

             Actor

              |

              Call Me by Your Name

             Timothée Hal Chalamet was born in Manhattan, to

              Nicole Flender

             , a real estate broker and dancer, and Marc Chalamet, a UNICEF editor. His mother, who is from New York, is Jewish, of Russian Jewish and Austrian Jewish descent. His father, who is from Nîmes, France, is of French and English ancestry. ...

              40.

              Naomi Scott

             Actress

              |

              Aladdin

             Naomi Scott is a multi-talented actor, singer and songwriter. She stars as "Jasmine" in Disney's blockbuster live action remake

              Aladdin

             (2019), alongside

              Mena Massoud

             and

              Will Smith

             , directed by Guy Ritchie. Disney released the film in May 2019, and it became one of the biggest films of the year.

             ...

              41.

              Jennifer Lawrence

             Actress

              |

              The Hunger Games

             Was the highest-paid actress in the world in 2015 and 2016. With her films grossing over $5.5 billion worldwide, Jennifer Lawrence is often cited as the most successful actor of her generation. She is also thus far the only person born in the 1990s to have won an acting Oscar.

             Jennifer Shrader ...

              42.

              Joey King

             Actress

              |

              The Act

             Joey King started acting professionally when she was four years old. A national spot for Life Cereal was Joey's first commercial. It has been said that Joey inherited the love of acting from her grandmother, who used to perform in live theater.

             She has appeared in several television shows and movies...

              43.

              Tom Cruise

             Actor

              |

              Top Gun

             In 1976, if you had told fourteen-year-old Franciscan seminary student Thomas Cruise Mapother IV that one day in the not too distant future he would be Tom Cruise, one of the top 100 movie stars of all time, he would have probably grinned and told you that his ambition was to join the priesthood. ...

              44.

              Joel Kinnaman

             Actor

              |

              The Killing

             Charles Joel Nordström Kinnaman, known professionally as Joel Kinnaman, is a Swedish American actor. He is best known for playing the lead role in the Swedish film Easy Money a role that earned him a Guldbagge Award in the "Best Actor" category - and for his role as Frank Wagner in the Johan Falk ...

              45.

              Jessica Chastain

             Actress

              |

              Zero Dark Thirty

             Jessica Michelle Chastain was born in Sacramento, California, and was raised in a middle-class household in a northern California suburb. Her mother, Jerri Chastain, is a vegan chef whose family is originally from Kansas, and her stepfather is a fireman. She discovered dance at the age of nine and ...

              46.

              Alden Ehrenreich

             Actor

              |

              Hail, Caesar!

             Alden Ehrenreich is an American actor. He made his feature film debut in

              Francis Ford Coppola

             's film

              Tetro

             (2009), and appeared in Coppola's subsequent film

              Twixt

             (2011).

             In 2013, he starred as Ethan Wate in the film adaptation of the novel

              Beautiful Creatures

             (2013). He then played the stepson of

             ...

              47.

              Bill Skarsgård

             Actor

              |

              It

             Bill Skarsgård was born on August 9, 1990 in Vällingby, Sweden as Bill Istvan Günther Skarsgård. He is an actor and producer, known for

              It

             (2017),

              It Chapter Two

             (2019) and

              Deadpool 2

             (2018).

              48.

              Zazie Beetz

             Actress

              |

              Atlanta

             Zazie Beetz (born c. 1991) is a German-American actress known for the role of Vanessa on

              Atlanta

             (2016), as well as for starring in

              Deadpool 2

             (2018),

              Applesauce

             (2015), and

              Still Here

             .

             Born in Berlin, Germany, to a German father and an African-American mother, she was raised in Manhattan (New York ...

              49.

              Frances McDormand

             Actress

              |

              Fargo

             Frances Louise McDormand was born on June 23, 1957 in Gibson City, Illinois. She was adopted by Canadian-born parents, Noreen Eloise (Nickleson), a nurse from Ontario, and The Rev. Vernon Weir McDormand, a Disciples of Christ minister from Nova Scotia, who raised her in the suburbs of Pittsburgh. ...

              50.

              Kate Siegel

             Actress

              |

              Hush

             Kate Siegel (born August 9, 1982) is an American actress and screenwriter. She is known for her collaborations with her husband Mike Flanagan, appearing in the acclaimed horror films Oculus (2013), Hush (2016), which she also co-wrote, Ouija: Origin of Evil (2016), and Gerald's Game (2017). Siegel ...

              51.

              Burt Reynolds

             Actor

              |

              Boogie Nights

             Enduring, strong-featured, and genial star of US cinema, Burt Reynolds started off in T.V. westerns in the 1960s and then carved his name into 1970s/1980s popular culture, as a sex symbol (posing nearly naked for "Cosmopolitan" magazine), and on-screen as both a rugged action figure and then as a ...

              52.

              Amber Heard

             Actress

              |

              Aquaman

             Amber Laura Heard was born in Austin, Texas, to Patricia

              Paige Heard

             (née Parsons), an internet researcher, and

              David C. Heard

             (David Clinton Heard), a contractor. She has English, Irish, Scottish, German, and Welsh ancestry.

             Heard appeared in the Academy Award-nominated film,

              North Country

             (2005), ...

              53.

              Alison Brie

             Actress

              |

              GLOW

             Alison Brie was born in Hollywood, California, to Joanne (Brenner), who worked at a non-profit child care agency, and Charles Terry Schermerhorn, a musician and entertainment reporter. Her mother is Jewish and her father has Scottish, Dutch, English, German, and Norwegian ancestry. Brie grew up in ...

              54.

              Chadwick Boseman

             Actor

              |

              Black Panther

             Chadwick Boseman is an American actor. He is known for his portrayal of T'Challa / Black Panther in the Marvel Cinematic Universe (since 2016), particularly in

              Black Panther

             (2018), and for his starring roles in as

              Jackie Robinson

             in

              42

             (2013),

              James Brown

             in

              Get on Up

             (2014), and

              Thurgood Marshall

             ...

              55.

              Daisy Ridley

             Actress

              |

              Star Wars: Episode VII - The Force Awakens

             Daisy Jazz Isobel Ridley is an English actress. She is best known for her breakthrough role as "Rey" in the 2015 film,

              Star Wars: Episode VII - The Force Awakens

             (2015). Daisy was born in Westminster, London, on April 10, 1992. She is the daughter of Louise Fawkner-Corbett and Chris Ridley. Her ...

              56.

              Steve Wilder

             Actor

              |

              The Nice Guys

             Steve Wilder was born on October 23, 1970 in Cooperstown, New York, USA as Steven Wilder Striegel. He is an actor and writer, known for

              The Nice Guys

             (2016),

              Iron Man Three

             (2013) and

              Melrose Place

             (1992).

              57.

              Eliza Dushku

             Actress

              |

              Bring It On

             Eliza Dushku was born in Boston, Massachusetts, to Judith (Rasmussen), a political science professor, and Philip R. Dushku, a teacher and administrator. Her father is Albanian and her mother is American (of Danish, Irish, English, and German descent). She was discovered at the end of a five-month ...

              58.

              Lady Gaga

             Soundtrack

              |

              A Star Is Born

             Lady Gaga, born Stefani Joanne Angelina Germanotta, is an American songwriter, singer, actress, philanthropist, dancer and fashion designer.

             Gaga was born on March 28, 1986 in Manhattan, New York City, to Cynthia Louise (Bissett), a philanthropist and business executive, and Joseph Anthony ...

              59.

              Zoey Deutch

             Actress

              |

              Set It Up

             Zoey Deutch was born in Los Angeles, California. She starred in Everybody Wants Some (2016), Before I Fall (2017), Why Him? (2016), Flower (2017) and Set It Up (2018).

             She recently wrapped production on Buffaloed (2019) which she produced as well, and is currently shooting the series The Politician ...

              60.

              Sally Hawkins

             Actress

              |

              The Shape of Water

             Sally Cecilia Hawkins was born in 1976 in Lewisham hospital, London, England, to Jacqui and Colin Hawkins, authors and illustrators of children's books. She is of English and Irish descent. Hawkins was brought up in Greenwich, in southeast London. She attended James Allen's Girls' School in Dulwich...

              61.

              Jackson Odell

             Soundtrack

              |

              Forever My Girl

             Jackson Odell was born on July 2, 1997 in Colorado, USA as Jackson Reid Odell. He was an actor, known for

              Forever My Girl

             (2018) and

              Great Plains

             (2016). He died on June 8, 2018 in San Fernando, California, USA.

              62.

              Allison Mack

             Actress

              |

              Smallville

             Mack was born in Germany but moved with her family to Long Beach, California, when she was 2. She began acting at 4 with print work and commercials, and began studying at The Young Actors Space in Los Angeles when she was 7. Before joining the cast of

              Smallville

             (2001), Allison starred in the ...

              63.

              Pom Klementieff

             Actress

              |

              Guardians of the Galaxy Vol. 2

             Pom Klementieff (born 3 May 1986) is a French actress. She was trained at the Cours Florent drama school in Paris and has appeared in such films as Loup (2009), Sleepless Night (2011) and Hacker's Game (2015). She plays the role of Mantis in the Marvel Cinematic Universe films Guardians of the ...

              64.

              Jimmy Bennett

             Actor

              |

              Orphan

             James 'Jimmy' Bennett was born on February 9, 1996 in Seal Beach, California. He has appeared in guest starring roles on

              The Guardian

             (2001),

              Judging Amy

             (1999),

              CSI: Crime Scene Investigation

             (2000) and recently

              Everwood

             (2002), and has been cast in some of the most successful productions in that ...

              65.

              Abbie Cornish

             Actress

              |

              Candy

             Abbie Cornish, also known by her rap name Dusk, is an Australian actress and rapper. Following her lead performance in 2004's Somersault, Cornish is best-known for her film roles as the titular heroin addict in the drama Candy (2006), courtier Bess Throckmorton in the historical drama Elizabeth: ...

              66.

              Saoirse Ronan

             Actress

              |

              Hanna

             Saoirse Una Ronan was born in The Bronx, New York City, New York, United States, to Irish parents,

              Monica Ronan

             (née Brennan) and

              Paul Ronan

             , an actor. When Saoirse was three, the family moved back to Dublin, Ireland. Saoirse grew up in Dublin and briefly in Co. Carlow before moving back to Dublin ...

              67.

              Letitia Wright

             Actress

              |

              Black Panther

             Letitia Wright is a British-Guyanese actress. She is known for her portrayal of Shuri in the Marvel Cinematic Universe, beginning in 2018 with

              Black Panther

             (2018) and

              Avengers: Infinity War

             (2018), and for the film

              Urban Hymn

             (2015). She has also starred in

              The Commuter

             (2018) and

              Ready Player One

             ...

              68.

              Elizabeth Olsen

             Actress

              |

              Martha Marcy May Marlene

             Elizabeth Chase "Lizzie" Olsen (born February 16, 1989) is an American actress. She is known for her roles in the films

              Silent House

             (2011),

              Liberal Arts

             (2012),

              Godzilla

             (2014),

              Avengers: Age of Ultron

             (2015), and

              Captain America: Civil War

             (2016). For her role in the critically-acclaimed

              Martha

             ...

              69.

              Dwayne Johnson

             Actor

              |

              Jumanji: Welcome to the Jungle

             Dwayne Douglas Johnson, also known as The Rock, was born on May 2, 1972 in Hayward, California. He is the son of

              Ata Johnson

             (born Feagaimaleata Fitisemanu Maivia) and professional wrestler

              Rocky Johnson

             (born Wayde Douglas Bowles). His father, from Amherst, Nova Scotia, Canada, is black (of Black ...

              70.

              Gemma Chan

             Actress

              |

              The Eternals

             Gemma Chan (born 29 November 1982) is a British film, television, and theatre actress and former fashion model. She portrays Charlotte in season four of the Showtime and ITV2 series Secret Diary of a Call Girl; Ruth in Channel 4's Fresh Meat; Mia Bennett in the BBC's Doctor Who "The Waters of Mars"...

              71.

              Rachel Brosnahan

             Actress

              |

              House of Cards

             Rachel Brosnahan was born in in Milwaukee, Wisconsin in 1990 and is an American actress. She is best known for her role as 'Midge' Maisel in the Amazon Prime Video series

              The Marvelous Mrs. Maisel

             (2017) for which she has won two Golden Globes for Best Performance by an Actress in a Television ...

              72.

              Claire Foy

             Actress

              |

              First Man

             Claire Elizabeth Foy (born 16 April 1984) is an English actress. She studied acting at the Liverpool John Moores University and the Oxford School of Drama and made her screen debut in the pilot of the supernatural comedy series Being Human, in 2008. Following her professional stage debut at the ...

              73.

              Milly Shapiro

             Actress

              |

              Hereditary

             Milly was born in Tampa, Florida to business owners Michelle and Eric Shapiro. She was educated at the Community Montessori School from 18 mos. until 10 years old, when she moved to New York to pursue her career as an actress-singer. Inspired by her sister, Abigail, she began vocal training at the ...

              74.

              Michelle Williams

             Actress

              |

              Blue Valentine

             A small-town girl born and raised in rural Kalispell, Montana, Michelle Ingrid Williams is the daughter of Carla Ingrid (Swenson), a homemaker, and Larry Richard Williams, a commodity trader and author. Her ancestry is Norwegian, as well as German, British Isles, and other Scandinavian. She was ...

              75.

              Henry Cavill

             Actor

              |

              Man of Steel

             Henry William Dalgliesh Cavill was born on the Bailiwick of Jersey, a British Crown dependency in the Channel Islands. His mother, Marianne (Dalgliesh), a housewife, was also born on Jersey, and is of Irish, Scottish and English ancestry. Henry's father, Colin Richard Cavill, a stockbroker, is of ...

              76.

              Amy Adams

             Actress

              |

              Arrival

             Amy Lou Adams was born in Vicenza, Veneto, Italy, to American parents, Kathryn (Hicken) and Richard Kent Adams, a U.S. serviceman who was stationed at Caserma Ederle in Italy at the time. She was raised in a Mormon family of seven children in Castle Rock, Colorado, and has English, as well as ...

              77.

              Chris Hemsworth

             Actor

              |

              The Avengers

             Chris Hemsworth was born in Melbourne, Australia, to Leonie (van Os), a teacher of English, and Craig Hemsworth, a social-services counselor. His brothers are actors

              Liam Hemsworth

             and

              Luke Hemsworth

             . He is of Dutch (from his immigrant maternal grandfather), Irish, English, Scottish, and German ...

              78.

              Lana Condor

             Actress

              |

              To All the Boys I've Loved Before

             Lana Therese Condor is a Vietnamese-born American actress. She made her film debut in

              X-Men: Apocalypse

             (2016), portraying Jubilation Lee / Jubilee. Condor was born on May 11, 1997 in Can Tho, Vietnam and was adopted by her American parents, Mary Carol (Haubold) and journalist Robert Condor, as an ...

              79.

              Jason Momoa

             Actor

              |

              Aquaman

             Joseph Jason Namakaeha Momoa was born on August 1, 1979, in Honolulu, Hawaii. He is the son of Coni (Lemke), a photographer, and Joseph Momoa, a painter. His father is of Hawaiian descent and his mother, who is from Iowa, is of mostly German ancestry. Jason was raised in Norwalk, Iowa, by his ...

              80.

              Richard Madden

             Actor

              |

              Game of Thrones

             Richard Madden, born 18 June 1986, is a Scottish stage, film, and television actor best known for portraying Robb Stark in the HBO series "Game of Thrones" and Prince Kit in Disney's "Cinderella." Starring as David Budd in the BBC miniseries "Bodyguard" has also brought him more international ...

              81.

              Joel Edgerton

             Actor

              |

              The Gift

             Joel Edgerton was born on June 23, 1974 in Blacktown, New South Wales, Australia, to Marianne (van Dort) and Michael Edgerton, who is a solicitor and property developer. His brother is filmmaker

              Nash Edgerton

             . His mother is a Dutch immigrant. Joel went to Hills Grammar School in the Western Suburbs...

              82.

              Cate Blanchett

             Actress

              |

              Carol

             Cate Blanchett was born on May 14, 1969 in Melbourne, Victoria, Australia, to June (Gamble), an Australian teacher and property developer, and Robert DeWitt Blanchett, Jr., an American advertising executive, originally from Texas. She has an older brother and a younger sister. When she was ten ...

              83.

              Alice Eve

             Actress

              |

              Before We Go

             Alice Sophia Eve was born in London, England. Her father is

              Trevor Eve

             and her mother is

              Sharon Maughan

             , both fellow actors. She is the eldest of three children. Eve has English, Irish and Welsh ancestry. Her family moved to Los Angeles, California when she was young as her father tried to crack ...

              84.

              Gary Oldman

             Actor

              |

              Tinker Tailor Soldier Spy

             Gary Oldman is a talented English movie star and character actor, renowned for his expressive acting style. One of the most celebrated thespians of his generation, with a diverse career encompassing theatre, film and television, he is known for his roles as

              Sid Vicious

             in

              Sid and Nancy

             (1986), ...

              85.

              Chris Pratt

             Actor

              |

              Guardians of the Galaxy

             Christopher Michael Pratt is an American film and television actor. He came to prominence for his small-screen roles, including Bright Abbott in

              Everwood

             (2002), Ché in

              The O.C.

             (2003), and Andy Dwyer and

              Parks and Recreation

             (2009), and notable film roles in

              Moneyball

             (2011),

              The Five-Year

             ...

              86.

              Tom Holland

             Actor

              |

              Spider-Man: Homecoming

             Thomas Stanley Holland was born in Kingston-upon-Thames, Surrey, to Nicola Elizabeth (Frost), a photographer, and

              Dominic Holland

             (Dominic Anthony Holland), who is a comedian and author. His paternal grandparents were from the Isle of Man and Ireland, respectively. He lives with his parents and ...

              87.

              Hailee Steinfeld

             Actress

              |

              True Grit

             Hailee Steinfeld was born on December 11, 1996 in Tarzana, California, to Cheri (Domasin), an interior designer, and

              Peter Steinfeld

             , a personal fitness trainer. She has a brother, Griffin. Her uncle is

              Jake Steinfeld

             , a fitness trainer, and her great-uncle is actor

              Larry Domasin

             . Her father is of ...

              88.

              Mina Sundwall

             Actress

              |

              Lost in Space

             Mina Sundwall was born and raised in New York City. Being half Swedish and half Italian, she has also spent a part of her childhood in Europe. Mina landed her first 'role' at age 8 months as a kidnapped baby. Mina is known mostly for the role of Penny in the Netflix Original show "Lost in Space", ...

              89.

              Ryan Reynolds

             Actor

              |

              Deadpool 2

             Ryan Rodney Reynolds was born on October 23, 1976 in Vancouver, British Columbia, Canada, the youngest of four children. His father, James Chester Reynolds, was a food wholesaler, and his mother, Tamara Lee "Tammy" (Stewart), worked as a retail-store saleswoman. He has Irish and Scottish ancestry. ...

              90.

              Cristin Milioti

             Actress

              |

              The Wolf of Wall Street

             Cristin Milioti was born and raised in Cherry Hill, New Jersey. She has Italian, Belgian, Czech, and Irish ancestry, and calls her family "Olive Garden Italian". In middle school, she found her love of acting at Long Lake Camp for the Arts in New York. She attended Cherry Hill High School East, ...

              91.

              Olivia Munn

             Actress

              |

              The Newsroom

             Lisa Olivia Munn was born in Oklahoma City, Oklahoma. Her mother, Kimberly Schmid, lived in Vietnam, and is of Chinese ancestry, while her father, Winston Barrett Munn, is from a family with deep roots in the American South. Olivia's parents divorced when she was two years old, and she was raised ...

              92.

              Lucy Davis

             Actress

              |

              Wonder Woman

             Lucy Davis was born on February 17, 1973 in Solihull, West Midlands, England as Lucy Clare Davis. She is an actress and producer, known for

              Wonder Woman

             (2017),

              Shaun of the Dead

             (2004) and

              The Office

             (2001). She was previously married to

              Owain Yeoman

             .

              93.

              Blake Lively

             Actress

              |

              Gossip Girl

             Blake Lively was born Blake Ellender Brown in Tarzana, California, to a show business family. Her mother,

              Elaine Lively

             (née McAlpin), is an acting coach and talent manager, and her father,

              Ernie Lively

             (born Ernest Wilson Brown, Jr.), is an actor and teacher. Her brother is actor

              Eric Lively

             , and ...

              94.

              Mackenzie Foy

             Actress

              |

              Interstellar

             Mackenzie Christine Foy was born 10 November 2000. She began her career as a child model in 2004, working for Garnet Hill, Polo Ralph Lauren, and Guess Kids. She has also modelled in print ads for companies such as Rubbermaid, Jones Apparel Group, The Walt Disney Company, Mattel, Target Corporation...

              95.

              Amanda Fuller

             Actress

              |

              Last Man Standing

             Amanda Fuller was born in 1984. She is an actress, known for

              Last Man Standing

             (2011),

              Red White & Blue

             (2010) and

              Grey's Anatomy

             (2005).

              96.

              Scarlett Johansson

             Actress

              |

              Her

             Scarlett Johansson was born in New York City. Her mother,

              Melanie Sloan

             , is from a Jewish family from the Bronx, and her father,

              Karsten Johansson

             , is a Danish-born architect, from Copenhagen. She has a sister,

              Vanessa Johansson

             , who is also an actress, a brother, Adrian, a twin brother,

              Hunter

             ...

              97.

              Dichen Lachman

             Actress

              |

              Altered Carbon

             Dichen Lachman was born in Kathmandu, Nepal, to a Tibetan mother and Australian father. Until the age of seven, she lived in Kathmandu with her parents and extended family. Following that, she moved to Adelaide, Australia, with her parents. After dropping out of university, Dichen took up acting ...

              98.

              Sam Rockwell

             Actor

              |

              Moon

             Sam Rockwell was born on November 5, 1968, in San Mateo, California, the only child of two actors,

              Pete Rockwell

             and Penny Hess. The family moved to New York when he was two years old, living first in the Bronx and later in Manhattan. When Sam was five years old, his parents separated, at which ...

              99.

              Sofia Boutella

             Actress

              |

              Star Trek Beyond

             Sofia Boutella is an Algerian actress, dancer and model. She was born in the Bab El Oued district of Algiers in Algeria, the daughter of composer and jazz musician

              Safy Boutella

             , and an architect mother. She started classical dance education when she was five years old. In 1992, at age 10, she left...

              100.

              Evan Rachel Wood

             Actress

              |

              Thirteen

             Evan Rachel Wood was born September 7, 1987, in Raleigh, North Carolina. Her father,

              Ira David Wood III

             , is a theatre actor, writer and director, and her mother,

              Sara Wood

             , is an actress and acting coach. She has two older brothers--

              Dana Wood

             , a musician, and

              Ira David Wood IV

             , who has also acted. ...

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      © 1990-

      2020

      by IMDb.com, Inc.

   <svg style="width:0;height:0;overflow:hidden;display:block" version="1.1" xmlns="http://www.w3.org/2000/svg">
    <defs>
     <lineargradient id="ipc-svg-gradient-tv-logo-t" x1="31.973%" x2="153.413%" y1="53.409%" y2="-16.853%">
      <stop offset="21.89%" stop-color="#D01F49">
      </stop>
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      </stop>
     </lineargradient>
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      </stop>
      <stop offset="83.44%" stop-color="#E8138B">
      </stop>
     </lineargradient>
    </defs>
   </svg>

**2.3 [15 pts] Write a function called `parse_stars` that accepts `star_soup` as its input and generates a list of dictionaries named `starlist` (see definition below)....**_____no_output_____```
Function
--------
parse_stars

Input
------
star_soup: the soup object with the scraped page

Returns
-------
a list of dictionaries; each dictionary corresponds to a star profile and has the following data:

    name: the name of the actor/actress as it appears at the top
    gender: 0 or 1: translate the word 'actress' into 1 and 'actor' into '0'
    url: the url of the link under their name that leads to a page with details
    page: BS object with 'html text acquired by scraping the above 'url' page'

Example:
--------
{'name': Tom Hardy,
  'gender': 0,
  'url': https://www.imdb.com/name/nm0362766/?ref_=nmls_hd,
  'page': BS object with 'html text acquired by scraping the 'url' page'
}

```_____no_output_____

# your code here
def get_artist_name(tag: Tag) -> str:
    """ Get artist name """
    return tag.find("h3").find("a").contents[0].strip() if tag.find("h3").find("a") else ""

def get_artist_url(tag: Tag) -> str:
    """ Get artist url """
    BASE_URL = "https://www.imdb.com"
    URL_SUFFIX = "?ref_=nmls_hd"
    return BASE_URL + tag.find("a").attrs["href"] + URL_SUFFIX

def fetch_artist_page(url: str):
    """ Fetch artist page """
    return make_top_100_imdb_star_soup(requests_retry_session().get(url))

def get_artist_role(tag: Tag) -> str:
    """ Get artist role if possible """
    return (
        tag.find("p", attrs={"class": "text-muted text-small"}).contents[0].strip()
        if tag.find("p", attrs={"class": "text-muted text-small"})
        else ""
    )

def get_artist_job_categories(artist_page) -> list:
    """ Get all artists possible categories """
    return [
        i.find("span").contents[0].strip()
        for i in artist_page.find("div", {"id": "name-job-categories"}).find_all("a")
        if "Actor" in i.find("span").contents[0]
    ]

def get_artist_gender(tag: Tag, artist_page) -> int:
    """ Returns the artist gender as int """
    role = get_artist_role(tag)
    if role in ("Actress", "Actor"):
        return 1 if role == "Actress" else 0
    # Handle things like Soundtrack, and producer that has no Actress/Actor in first box
    else:
        job_categories = get_artist_job_categories(artist_page)
        return 0 if "Actor" in job_categories else 1

def parse_artist_tag(tag: Tag) -> dict:
    """ Parse an artist soup tag and return a dict """
    name = purify_text(get_artist_name(tag))
    url = purify_text(get_artist_url(tag))
    page = fetch_artist_page(url)
    gender = get_artist_gender(tag, page)

    return {
        "name": name,
        "gender": gender,
        "url": url,
        "page": page
    }

def parse_stars(artist_soup : BeautifulSoup) -> list:
    """ Accepts a star_soup as its input and generates a list of dictionaries named starlist"""
    all_stars = artist_soup.find_all('div',attrs = {'class': 'lister-item mode-detail'})
    return list(map(parse_artist_tag, all_stars))_____no_output_____starlist = parse_stars(star_soup)_____no_output_____

This should give you 100_____no_output_____

len(starlist)_____no_output_____# check your code
# this list is large because of the html in the `page` field
# to get a better picture, print only the first element
starlist[0]_____no_output_____

Your output should look like this:
```
{'name': 'Karen Gillan',
 'gender': 1,
 'url': 'https://www.imdb.com/name/nm2394794',
 'page':
 <!DOCTYPE html>

 <html xmlns:fb="http://www.facebook.com/2008/fbml" xmlns:og="http://ogp.me/ns#">
 <head>
 <meta charset="utf-8"/>
 <meta content="IE=edge" http-equiv="X-UA-Compatible"/>
 <meta content="app-id=342792525, app-argument=imdb:///name/nm2394794?src=mdot" name="apple-itunes-app"/>
 <script type="text/javascript">var IMDbTimer={starttime: new Date().getTime(),pt:'java'};</script>
 <script>
     if (typeof uet == 'function') {
       uet("bb", "LoadTitle", {wb: 1});
     }
 </script>
 <script>(function(t){ (t.events = t.events || {})["csm_head_pre_title"] = new Date().getTime(); })(IMDbTimer);</script>
 <title>Karen Gillan - IMDb</title>
 <script>(function(t){ (t.events = t.events || {})["csm_head_post_title"] = new Date().getTime(); })(IMDbTimer);</script>
...

 ```_____no_output_____**2.4** [15 pts] Write a function called `create_star_table`, which takes `starlist` as an input and extracts information about each star (see function definition for the exact information to be extracted and the exact output definition).  Only extract information from the first box on each star's page. If the first box is acting, consider only acting credits and the star's acting debut, if the first box is Directing, consider only directing credits and directorial debut._____no_output_____```
Function
--------
create_star_table

Input
------
the starlist

Returns
-------

a list of dictionaries; each dictionary corresponds to a star profile and has the following data:

    star_name: the name of the actor/actress as it appears at the top
    gender: 0 or 1 (1 for 'actress' and 0 for 'actor')
    year_born : year they were born
    first_movie: title of their first movie or TV show
    year_first_movie: the year they made their first movie or TV show
    credits: number of movies or TV shows they have made in their career.

--------
Example:

{'star_name': Tom Hardy,
  'gender': 0,
  'year_born': 1997,
  'first_movie' : 'Batman',
  'year_first_movie' : 2017,
  'credits' : 24}

```_____no_output_____

# your code here
def get_artist_year_born(page) -> int:
    """ Returns the year an artist is born """
    return int(page.find("time")["datetime"].split("-")[0]) if page.find("time") else 1900

def get_all_artist_movies(page) -> list:
    """ Returns a list of soups for artist movies """
    return [text for text in page.find("div", {"class": "filmo-category-section"}).children if text != "\n"]

def get_artist_first_movie_info(page) -> str:
    """ Returns artist first movie and year first movie was made """
    artist_movies = get_all_artist_movies(page)
    first_movie = artist_movies[-1].find("span", {"class": "year_column"}).next_sibling.next_sibling.contents[0].text.strip()
    year_first_movie = int(artist_movies[-1].find("span", {"class": "year_column"}).contents[0].lstrip("\n\xa0").rstrip("\n")[:4])
    return (purify_text(first_movie), year_first_movie)

def get_artist_credits(page) -> str:
    """ Returns the artist credits """
    all_artist_credits = [i for i in page.find("div", {"id": f"filmography"}).children if i != "\n"]
    return all_artist_credits[0].find("a").next_sibling.strip().lstrip("(").rstrip(")").replace(" credits", "")

def parse_single_star(star: dict) -> dict:
    """ Takes a star dictionary from above stage and augments the data further """
    page = star["page"]
    name = star["name"]
    gender = star["gender"]
    year_born = get_artist_year_born(page)
    first_movie, year_first_movie = get_artist_first_movie_info(page)
    credits = get_artist_credits(page)
    return {
        "name": name,
        "gender": gender,
        "year_born": year_born,
        "first_movie": first_movie,
        "year_first_movie": year_first_movie,
        "credits": credits
    }

def create_star_table(star_list: list)-> list:
    """ Create a star table using stars_list as input """
    assert star_list, "[ERROR] - Star List is required!"
    return list(map(parse_single_star, star_list))_____no_output_____# DO NOT RERUN THE HTTP REQUESTS TO IMDb WHEN SUBMITTING - THIS WILL TAKE SOME TIME
star_table = create_star_table(starlist)_____no_output_____# check your code
star_table_____no_output_____

Your output should look like this (the order of elements is not important):
```
[{'name': 'Karen Gillan',
  'gender': 1,
  'year_born': '1987',
  'first_movie': 'Rebus',
  'year_first_movie': '2006',
  'credits': '63'},
 {'name': 'Bryce Dallas Howard',
  'gender': 1,
  'year_born': '1981',
  'first_movie': 'Parenthood',
  'year_first_movie': '1989',
  'credits': '38'},
    ...
```_____no_output_____**2.5**[4 pts] Now that you have scraped all the info you need, it's good practice to save the last data structure you created to disk. Save the data structure to a JSON file named `starinfo.json` and submit this JSON file in Canvas. If you do this, if you have to restart, you won't need to redo all the requests and parsings from before.
_____no_output_____

import json # investivate the `dump` method_____no_output_____# your code here
# your code here
ARTIST_TABLE_DUMP_PATH = "./data/starinfo.json"
with open(ARTIST_TABLE_DUMP_PATH, "w") as f:
  json.dump(star_table, f, ensure_ascii=False, indent=4)_____no_output_____

To check your JSON saving, re-open the JSON file and reload the code_____no_output_____

with open("./data/starinfo.json", "r") as fd:
    star_table = json.load(fd)

# output should be the same
star_table_____no_output_____

**2.6** [6 pts] We provide a JSON file called `data/staff_starinfo.json` created by CS109 teaching staff for consistency, which you should use for the rest of the homework. Import the contents of this JSON file  into a pandas dataframe called `frame`. Check the types of variables in each column and clean these variables if needed. Add a new column to your dataframe with the age of each actor when they made their first appearance, movie or TV, (name this column `age_at_first_movie`). Check some of the values of this new column. Do you find any problems? You don't need to fix them._____no_output_____

# your code here
STAR_INFO_PATH = "./data/staff_starinfo_2018.json"
frame = pd.read_json(STAR_INFO_PATH, orient="records")_____no_output_____# Inspecting dataframe types
frame.dtypes_____no_output_____# Adding new column for age_at_first_movie
frame["age_at_first_movie"] = frame["year_first_movie"] - frame["year_born"]_____no_output_____# Inspect new columns
frame.head()_____no_output_____frame.describe()_____no_output_____frame.nlargest(10,'credits')_____no_output_____# verifying my Lady Gaga data vs the TA's data
star_table[57]_____no_output_____

**Answer**:

- The only observation I can see is that some performer's gender is wrongly labeled. Which shows the intracies of data scraping and the format of the page. Successful web scraping is dependent on the web page structure. Using just the first box of the performer does not always have "Actor" or "Actress". Lady Gaga had "Soundtrack". Digging deeper on their page shows that Actress is the gender designation.

- The statistical values seem okay and nothing else weird, besides what I have mentioned above, is obvious.
_____no_output_____**2.7** [4 pts] You are now ready to answer the following intriguing questions:
- **2.7.1** How many performers made their first appearance (movie or TV) when he/she was 17 years old?
- **2.7.2** How many performers started as child actors? Define child actor as a person younger than 12 years old.
_____no_output_____

# 2.7.1 - Peformers making their first appearance at 17 years old
first_performance_17 = frame[frame["age_at_first_movie"] == 17].shape[0]
print(f"{first_performance_17} performers made their first appearance at 17 years old")3 performers made their first appearance at 17 years old
# 2.7.2 - Child actors
child_actors_cnt = frame[frame["age_at_first_movie"] < 12].shape[0]
print(f"{child_actors_cnt} performers started as child actors")20 performers started as child actors

**2.8 [6 pts]** Use your Python visualization skills to further explore the data:
- **2.8.1** Create 2 scatter plots: one showing the relationship between age at first movie and number of credits, the other between year born and number of credits. What can you say about these relationships? Are there any apparent outliers? Please limit your written responses to 4 sentences or fewer.
- **2.8.2** Create 2 histograms in a single plot comparing the distribution of actors' current ages to actresses' current ages. What does this visualization tell you? (4 sentences or fewer)
- **2.8.3** Create a box plot comparing the credits-per-year-active for actors and actresses. Here we assume all stars in the list are still active. Do these distributions look the same across genders? Comment on anything else of interest gleaned from your plot.(4 sentences or fewer)_____no_output_____

# 2.8.1
fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(15, 6))
ax[0].scatter(x=frame["age_at_first_movie"], y=frame["credits"])
ax[1].scatter(x=frame["year_born"], y=frame["credits"],color = "red")
plt.show()_____no_output_____

**Answer**:

- For the first scatterplot, age at first movie vs credits, without any statistical diagnostics we can see somewhat positive linear relationship. We have two observations that are extreme on `y-axis` and one extreme on the `x-axis`. These outliers can influence any linear regression model we try to fit on this model.

- For the second scatterplot, year born vs credits, we see a strong negative linear relationship. In this plot we have one observation that is extreme on both `x-axis` and `y-axis`, definitely an influential point. The other is also an outlier. These outliers can also skew the spread and influence, largely, any linear regression model we try to fit to this data.

- The second plot can be observed to show that the older the performer, the possibility of having more credits because they may have had more time to accumulate this.

- The observations on the first plot does not show a strong linear relationship between age at first movie and credits, however it can be greatly skewed by child actors we say that were 20 out of 100 performers._____no_output_____

# 2.8.2
frame["age_current"] = 2020 - frame["year_born"]
plt.figure(figsize=(15, 5))
plt.subplot(1, 2, 1)
plt.hist(frame[frame['gender']==0]['age_current'],  color='blue')
plt.xlabel('Age Group')
plt.title('Actors')

plt.subplot(1, 2, 2)
plt.hist(frame[frame['gender']==1]['age_current'],  color='red')
plt.xlabel('Age Group')
plt.title('Actress')
plt.show()_____no_output_____

**Answer**:

- Both the age distribution of actors and actresses are right skewed.
- The actor's age distribution has a outlier of an actor that started their career really late.
- The actress age distribution is a bit more normally distributed than actors however still has a long right tail.
- There are more actresses than actors in the top 100 peformers for 2018 and their median age is between 35 - 40. The majority of actors seem to be between 23 and 52 year old, while actresses seem to be between 27 and 40 year old._____no_output_____

# 2.8.3
years_active = (2020 - frame["year_first_movie"])
frame["credits_per_year_active"] = frame["credits"] / years_active
frame[["gender", "credits_per_year_active"]].boxplot(by=['gender'], sym ='', figsize = [6, 6])_____no_output_____

**Answer**

- Yes, there seems to be a difference in the amount of credits per year active between actors and actresses.

- On average, actresses seem to get more credits per year of active work than their actor colleagues.

- The median for actresses also seem higher than actors as well.
_____no_output_____**2.9** [2 pts] Make a plot of the number of credits against the name of actor/actress. Who is the most prolific actress or actor in IMDb's list of the Top 100 Stars for 2018? Define **most prolific** as the performer with the most credits. **_____no_output_____

# your code here
plt.figure(figsize=(20, 10))
names = frame['name']
credits = frame['credits']
x = names
y = credits

x_pos = [idx for idx, _ in enumerate(x)]

plt.bar(x_pos, credits, color='green')

plt.ylabel('Credits')
plt.xlabel('Actor/Actress Names')
plt.title('Actor/Actress Credits')

plt.xticks(x_pos, x)
plt.setp(plt.gca().get_xticklabels(), rotation=90, horizontalalignment='right')
plt.show()_____no_output_____

**Answer**:

We can see from the chart above that __Lady Gaga__ is the most prolific performer with the most credits. _____no_output_____

# Verifying the most prolific perform as seem from above chart
most_prolific_performer = frame[frame.credits == frame.credits.max()]
most_prolific_performer_____no_output_____

**2.10 [2 pts]** In 4 or fewer sentences, comment on what you see in the plots above.  Are there any surprises or patterns?  Please **have some fun** with this question._____no_output_____

frame.nlargest(10,'credits')_____no_output_____# Lady Gaga data I scraped and validated
star_table[57]_____no_output_____

**Answer**:

- From above we can see that the The majority of the performers with top credit are actors and not actresses, expect for Lady Gaga. This may show a gender disparity.

- Lady Gaga also is an outlier, in gaining credits, when compared to other actresses.

- There are two outliers from the bar chart above, one which is Lady Gaga and the other Burt Reynolds.

- The data provided by the TA is not correctly labeled for gender for an artist like Lady Gaga. You can see this from the code above.
- Lady Gaga should have a gender designation of 1 and not 0.

- As mentioned in 2.1 above, the successful scraping of data for analysis is largely dependent on the structure of the webpage.  Using just the first box of the performer does not always have "Actor" or "Actress". Lady Gaga had "Soundtrack". Digging deeper on their page shows that Actress is the gender designation.

- This shows that data validation is really important for a successful data exploration.
_____no_output_____