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empet/FieldsMedalists.ipynb

Last active August 29, 2015 14:04
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Fields Medalists Age at the time of medal award
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FieldsMedalists.ipynb
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"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"The age of Fields Medalists at the time of medal award"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Fields Medal](http://www.mathunion.org/general/prizes/fields/details) is a kind of Nobel Prize in Mathematics. It is awarded every four years at the International Congress of Mathematicians. Unlike Nobel Prize, the Fields Medal is \n",
" awarded only to mathematicians under the age of 40. "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from IPython.display import Image\n",
"#Image(url='http://goo.gl/lP6Duw')#upload.wikimedia.org\n",
"Image(filename='fieldsmedalfront.jpg')\n"
],
"language": "python",
"metadata": {},
"outputs": [
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"metadata": {},
"output_type": "pyout",
"prompt_number": 3,
"text": [
"<IPython.core.display.Image at 0x30a27f0>"
]
}
],
"prompt_number": 3
},
{
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"collapsed": false,
"input": [
"Image(filename='fieldsmedalback.jpg')"
],
"language": "python",
"metadata": {},
"outputs": [
{
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Ww3S8YLJFyzsOxk2qvXDdCRSd4taiaejPzD/4KXfsk2vwv8Sy+N/D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\n",
"metadata": {},
"output_type": "pyout",
"prompt_number": 4,
"text": [
"<IPython.core.display.Image at 0x30a2e80>"
]
}
],
"prompt_number": 4
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In this notebook we illustrate by a few methods of visualization the age of the Fields Medalists. "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"import numpy as np\n",
"from IPython.display import HTML"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"nameFM=[]\n",
"birth=[]\n",
"award=[]\n",
"\n",
"f = open(\"FieldsMedalists.txt\", \"r\")\n",
"for line in f.readlines():\n",
" line = line.strip()\n",
" parts = line.split(\",\")\n",
" nameFM.append(parts[0])\n",
" birth.append(int(parts[1]))\n",
" award.append(int(parts[2]))\n",
"L=len(nameFM) \n",
"\n",
"data=np.empty((L,3))\n",
"data[:,0]=birth\n",
"data[:,1]=award\n",
"data[:,2]=data[:,1]-data[:,0]\n",
"\n",
"\n",
"df=pd.DataFrame( data, index=nameFM, columns=['Birth Year', 'Award Year','Age']) \n",
"print 'The list of Fields Medalists, ordered by award year:'\n",
"h = HTML(df.to_html());h"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"The list of Fields Medalists, ordered by award year:\n"
]
},
{
"html": [
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Birth Year</th>\n",
" <th>Award Year</th>\n",
" <th>Age</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Jesse DOUGLAS</th>\n",
" <td> 1897</td>\n",
" <td> 1936</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Lars Valerian AHLFORS</th>\n",
" <td> 1907</td>\n",
" <td> 1936</td>\n",
" <td> 29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Atle SELBERG</th>\n",
" <td> 1917</td>\n",
" <td> 1950</td>\n",
" <td> 33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Laurent SCHWARTZ</th>\n",
" <td> 1915</td>\n",
" <td> 1950</td>\n",
" <td> 35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Kunihiko KODAIRA</th>\n",
" <td> 1915</td>\n",
" <td> 1954</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jean-Pierre SERRE</th>\n",
" <td> 1926</td>\n",
" <td> 1954</td>\n",
" <td> 28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Klaus Friedrich ROTH</th>\n",
" <td> 1925</td>\n",
" <td> 1958</td>\n",
" <td> 33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rene THOM</th>\n",
" <td> 1923</td>\n",
" <td> 1958</td>\n",
" <td> 35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Lars HORMANDER</th>\n",
" <td> 1931</td>\n",
" <td> 1962</td>\n",
" <td> 31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>John Willard MILNOR</th>\n",
" <td> 1931</td>\n",
" <td> 1962</td>\n",
" <td> 31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Michael Francis ATIYAH</th>\n",
" <td> 1929</td>\n",
" <td> 1966</td>\n",
" <td> 37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Paul Joseph COHEN</th>\n",
" <td> 1934</td>\n",
" <td> 1966</td>\n",
" <td> 32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Alexander GROTHENDIECK</th>\n",
" <td> 1928</td>\n",
" <td> 1966</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Stephen SMALE</th>\n",
" <td> 1930</td>\n",
" <td> 1966</td>\n",
" <td> 36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Alan BAKER</th>\n",
" <td> 1939</td>\n",
" <td> 1970</td>\n",
" <td> 31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Heisuke HIRONAKA</th>\n",
" <td> 1931</td>\n",
" <td> 1970</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Serge NOVIKOV</th>\n",
" <td> 1938</td>\n",
" <td> 1970</td>\n",
" <td> 32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>John Griggs THOMPSON</th>\n",
" <td> 1932</td>\n",
" <td> 1970</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Enrico BOMBIERI</th>\n",
" <td> 1946</td>\n",
" <td> 1974</td>\n",
" <td> 28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>David Bryant MUMFORD</th>\n",
" <td> 1937</td>\n",
" <td> 1974</td>\n",
" <td> 37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Pierre Rene DELIGNE</th>\n",
" <td> 1944</td>\n",
" <td> 1978</td>\n",
" <td> 34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Charles Louis FEFFERMAN</th>\n",
" <td> 1949</td>\n",
" <td> 1978</td>\n",
" <td> 29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Gregori A MARGULIS</th>\n",
" <td> 1946</td>\n",
" <td> 1978</td>\n",
" <td> 32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Daniel G. QUILLEN</th>\n",
" <td> 1940</td>\n",
" <td> 1978</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Alain CONNES</th>\n",
" <td> 1947</td>\n",
" <td> 1982</td>\n",
" <td> 35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>William P. THURSTON</th>\n",
" <td> 1946</td>\n",
" <td> 1982</td>\n",
" <td> 36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Shing-Tung YAU</th>\n",
" <td> 1949</td>\n",
" <td> 1982</td>\n",
" <td> 33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Simon K. DONALDSON</th>\n",
" <td> 1957</td>\n",
" <td> 1986</td>\n",
" <td> 29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Gerd FALTINGS</th>\n",
" <td> 1954</td>\n",
" <td> 1986</td>\n",
" <td> 32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Michael H. FREEDMAN</th>\n",
" <td> 1951</td>\n",
" <td> 1986</td>\n",
" <td> 35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Vladimir DRINFELD</th>\n",
" <td> 1954</td>\n",
" <td> 1990</td>\n",
" <td> 36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Vaughan F.R. JONES</th>\n",
" <td> 1952</td>\n",
" <td> 1990</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Shigefumi MORI</th>\n",
" <td> 1951</td>\n",
" <td> 1990</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Edward WITTEN</th>\n",
" <td> 1951</td>\n",
" <td> 1990</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jean BOURGAIN</th>\n",
" <td> 1954</td>\n",
" <td> 1994</td>\n",
" <td> 40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Pierre-Louis LIONS</th>\n",
" <td> 1956</td>\n",
" <td> 1994</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jean-Christophe YOCCOZ</th>\n",
" <td> 1957</td>\n",
" <td> 1994</td>\n",
" <td> 37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Efim ZELMANOV</th>\n",
" <td> 1955</td>\n",
" <td> 1994</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Richard E. BORCHERDS</th>\n",
" <td> 1959</td>\n",
" <td> 1998</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W. Timothy GOWERS</th>\n",
" <td> 1963</td>\n",
" <td> 1998</td>\n",
" <td> 35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Maxim KONTSEVICH</th>\n",
" <td> 1964</td>\n",
" <td> 1998</td>\n",
" <td> 34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Curtis T. MCMULLEN</th>\n",
" <td> 1958</td>\n",
" <td> 1998</td>\n",
" <td> 40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Laurent LAFFORGUE</th>\n",
" <td> 1966</td>\n",
" <td> 2002</td>\n",
" <td> 36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Vladimir VOEVODSKY</th>\n",
" <td> 1966</td>\n",
" <td> 2002</td>\n",
" <td> 36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Andrei OKOUNKOV</th>\n",
" <td> 1969</td>\n",
" <td> 2006</td>\n",
" <td> 37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grigori PERELMAN</th>\n",
" <td> 1966</td>\n",
" <td> 2006</td>\n",
" <td> 40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Terence TAO</th>\n",
" <td> 1975</td>\n",
" <td> 2006</td>\n",
" <td> 31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Wendelin WERNER</th>\n",
" <td> 1968</td>\n",
" <td> 2006</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Elon LINDENSTRAUSS</th>\n",
" <td> 1970</td>\n",
" <td> 2010</td>\n",
" <td> 40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ngo Bao CHAU</th>\n",
" <td> 1972</td>\n",
" <td> 2010</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Stanislav SMIRNOV</th>\n",
" <td> 1970</td>\n",
" <td> 2010</td>\n",
" <td> 40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Cedric VILLANI</th>\n",
" <td> 1973</td>\n",
" <td> 2010</td>\n",
" <td> 37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Artur Avila</th>\n",
" <td> 1979</td>\n",
" <td> 2014</td>\n",
" <td> 35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Manjul Bhargava</th>\n",
" <td> 1974</td>\n",
" <td> 2014</td>\n",
" <td> 40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Martin Hairer</th>\n",
" <td> 1975</td>\n",
" <td> 2014</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Maryam Mirzakhani</th>\n",
" <td> 1977</td>\n",
" <td> 2014</td>\n",
" <td> 37</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 6,
"text": [
"<IPython.core.display.HTML at 0x30a29e8>"
]
}
],
"prompt_number": 6
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we sort the DataFrame increasingly by Age:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"dfs=df.sort(columns='Age')\n",
"hh = HTML(dfs.to_html());hh"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Birth Year</th>\n",
" <th>Award Year</th>\n",
" <th>Age</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Enrico BOMBIERI</th>\n",
" <td> 1946</td>\n",
" <td> 1974</td>\n",
" <td> 28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jean-Pierre SERRE</th>\n",
" <td> 1926</td>\n",
" <td> 1954</td>\n",
" <td> 28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Simon K. DONALDSON</th>\n",
" <td> 1957</td>\n",
" <td> 1986</td>\n",
" <td> 29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Lars Valerian AHLFORS</th>\n",
" <td> 1907</td>\n",
" <td> 1936</td>\n",
" <td> 29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Charles Louis FEFFERMAN</th>\n",
" <td> 1949</td>\n",
" <td> 1978</td>\n",
" <td> 29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Terence TAO</th>\n",
" <td> 1975</td>\n",
" <td> 2006</td>\n",
" <td> 31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>John Willard MILNOR</th>\n",
" <td> 1931</td>\n",
" <td> 1962</td>\n",
" <td> 31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Lars HORMANDER</th>\n",
" <td> 1931</td>\n",
" <td> 1962</td>\n",
" <td> 31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Alan BAKER</th>\n",
" <td> 1939</td>\n",
" <td> 1970</td>\n",
" <td> 31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Gerd FALTINGS</th>\n",
" <td> 1954</td>\n",
" <td> 1986</td>\n",
" <td> 32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Paul Joseph COHEN</th>\n",
" <td> 1934</td>\n",
" <td> 1966</td>\n",
" <td> 32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Gregori A MARGULIS</th>\n",
" <td> 1946</td>\n",
" <td> 1978</td>\n",
" <td> 32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Serge NOVIKOV</th>\n",
" <td> 1938</td>\n",
" <td> 1970</td>\n",
" <td> 32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Shing-Tung YAU</th>\n",
" <td> 1949</td>\n",
" <td> 1982</td>\n",
" <td> 33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Atle SELBERG</th>\n",
" <td> 1917</td>\n",
" <td> 1950</td>\n",
" <td> 33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Klaus Friedrich ROTH</th>\n",
" <td> 1925</td>\n",
" <td> 1958</td>\n",
" <td> 33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Pierre Rene DELIGNE</th>\n",
" <td> 1944</td>\n",
" <td> 1978</td>\n",
" <td> 34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Maxim KONTSEVICH</th>\n",
" <td> 1964</td>\n",
" <td> 1998</td>\n",
" <td> 34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W. Timothy GOWERS</th>\n",
" <td> 1963</td>\n",
" <td> 1998</td>\n",
" <td> 35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rene THOM</th>\n",
" <td> 1923</td>\n",
" <td> 1958</td>\n",
" <td> 35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Artur Avila</th>\n",
" <td> 1979</td>\n",
" <td> 2014</td>\n",
" <td> 35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Alain CONNES</th>\n",
" <td> 1947</td>\n",
" <td> 1982</td>\n",
" <td> 35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Michael H. FREEDMAN</th>\n",
" <td> 1951</td>\n",
" <td> 1986</td>\n",
" <td> 35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Laurent SCHWARTZ</th>\n",
" <td> 1915</td>\n",
" <td> 1950</td>\n",
" <td> 35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Vladimir VOEVODSKY</th>\n",
" <td> 1966</td>\n",
" <td> 2002</td>\n",
" <td> 36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Laurent LAFFORGUE</th>\n",
" <td> 1966</td>\n",
" <td> 2002</td>\n",
" <td> 36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Stephen SMALE</th>\n",
" <td> 1930</td>\n",
" <td> 1966</td>\n",
" <td> 36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>William P. THURSTON</th>\n",
" <td> 1946</td>\n",
" <td> 1982</td>\n",
" <td> 36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Vladimir DRINFELD</th>\n",
" <td> 1954</td>\n",
" <td> 1990</td>\n",
" <td> 36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Andrei OKOUNKOV</th>\n",
" <td> 1969</td>\n",
" <td> 2006</td>\n",
" <td> 37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Cedric VILLANI</th>\n",
" <td> 1973</td>\n",
" <td> 2010</td>\n",
" <td> 37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jean-Christophe YOCCOZ</th>\n",
" <td> 1957</td>\n",
" <td> 1994</td>\n",
" <td> 37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Maryam Mirzakhani</th>\n",
" <td> 1977</td>\n",
" <td> 2014</td>\n",
" <td> 37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Michael Francis ATIYAH</th>\n",
" <td> 1929</td>\n",
" <td> 1966</td>\n",
" <td> 37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>David Bryant MUMFORD</th>\n",
" <td> 1937</td>\n",
" <td> 1974</td>\n",
" <td> 37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Pierre-Louis LIONS</th>\n",
" <td> 1956</td>\n",
" <td> 1994</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Vaughan F.R. JONES</th>\n",
" <td> 1952</td>\n",
" <td> 1990</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ngo Bao CHAU</th>\n",
" <td> 1972</td>\n",
" <td> 2010</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Wendelin WERNER</th>\n",
" <td> 1968</td>\n",
" <td> 2006</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Daniel G. QUILLEN</th>\n",
" <td> 1940</td>\n",
" <td> 1978</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Alexander GROTHENDIECK</th>\n",
" <td> 1928</td>\n",
" <td> 1966</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>John Griggs THOMPSON</th>\n",
" <td> 1932</td>\n",
" <td> 1970</td>\n",
" <td> 38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Edward WITTEN</th>\n",
" <td> 1951</td>\n",
" <td> 1990</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Kunihiko KODAIRA</th>\n",
" <td> 1915</td>\n",
" <td> 1954</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Heisuke HIRONAKA</th>\n",
" <td> 1931</td>\n",
" <td> 1970</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Martin Hairer</th>\n",
" <td> 1975</td>\n",
" <td> 2014</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Richard E. BORCHERDS</th>\n",
" <td> 1959</td>\n",
" <td> 1998</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Efim ZELMANOV</th>\n",
" <td> 1955</td>\n",
" <td> 1994</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Shigefumi MORI</th>\n",
" <td> 1951</td>\n",
" <td> 1990</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jesse DOUGLAS</th>\n",
" <td> 1897</td>\n",
" <td> 1936</td>\n",
" <td> 39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grigori PERELMAN</th>\n",
" <td> 1966</td>\n",
" <td> 2006</td>\n",
" <td> 40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Curtis T. MCMULLEN</th>\n",
" <td> 1958</td>\n",
" <td> 1998</td>\n",
" <td> 40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Elon LINDENSTRAUSS</th>\n",
" <td> 1970</td>\n",
" <td> 2010</td>\n",
" <td> 40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Stanislav SMIRNOV</th>\n",
" <td> 1970</td>\n",
" <td> 2010</td>\n",
" <td> 40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Jean BOURGAIN</th>\n",
" <td> 1954</td>\n",
" <td> 1994</td>\n",
" <td> 40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Manjul Bhargava</th>\n",
" <td> 1974</td>\n",
" <td> 2014</td>\n",
" <td> 40</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 10,
"text": [
"<IPython.core.display.HTML at 0x3d614e0>"
]
}
],
"prompt_number": 10
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.plot(dfs['Age'], 'o-')\n",
"plt.title('Ages of Fields Medalists')\n",
"plt.xlabel('Index of Fields Medalists in increasing order of age')\n",
"plt.ylabel('Age in the award year')\n",
"plt.axis([-1,L+1, 27,41])"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 11,
"text": [
"[-1, 57, 27, 41]"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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IFJTyiHRoZ+Ps3g19+8LWrdC9eyhVEBHJS3smHK84q1fDyJEK9CISHcUM9tXA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\nQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0xc9ee6d8>"
]
}
],
"prompt_number": 11
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The mean age of Fields Medalists is:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print np.mean(dfs['Age']).round(2)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"35.57\n"
]
}
],
"prompt_number": 12
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import plotly.plotly as py\n",
"from plotly.graph_objs import *\n",
"\n",
"py.sign_in('empet','my_api_key')\n",
"awName=[]\n",
"for year, name in zip(award, nameFM):\n",
" awName.append(str(year)+', '+name)\n",
"Age=data[:,2].tolist() \n",
"\n",
"anno_text = \"Source: \\\n",
"<a href='http://www.mathunion.org/index.php?id=prizewinners'>[1]</a> and \\\n",
"<a href='http://en.wikipedia.org/'>[2]</a>\"\n",
"\n",
"data = Data([Bar(y=np.arange(1,L+1), \n",
" x=Age,\n",
" text=awName,\n",
" orientation='h', \n",
" marker=Marker(color='rgb(127,205,187)'))])\n",
"\n",
"layout = Layout(\n",
" title='The age of Fields Medalists at the time of medal award',\n",
" font=Font(family='Raleway, sans-serif'\n",
" ),\n",
" showlegend=False,\n",
" xaxis=XAxis(\n",
" title='Age',\n",
" range=[20,41],\n",
" gridwidth=2\n",
" ),\n",
" yaxis=YAxis(title='The index of medalists sorted by award year'),\n",
" bargap=0.15,\n",
" autosize=False,\n",
" width=500,\n",
" height=830,\n",
" annotations=Annotations([\n",
" Annotation(\n",
" x=0,\n",
" y=1,\n",
" xref='paper',\n",
" yref='paper',\n",
" text=anno_text,\n",
" font=Font(\n",
" size=14\n",
" ),\n",
" showarrow=False,\n",
" xanchor='left',\n",
" yanchor='bottom'\n",
" )\n",
" ]) \n",
")\n",
"fig = Figure(data=data, layout=layout)\n",
"\n",
"py.iplot(fig, filename='FieldsMedalists', height=840) \n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\"seamless=\"seamless\" src=\"https://plot.ly/~empet/22\" height=\"840\" width=\"100%\"></iframe>"
],
"metadata": {},
"output_type": "display_data",
"text": [
"<IPython.core.display.HTML at 0xc4a8a20>"
]
}
],
"prompt_number": 13
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"E. Petrisor, UPT"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from IPython.core.display import HTML\n",
"def css_styling():\n",
" styles = open(\"./styles/custom.css\", \"r\").read()\n",
" return HTML(styles)\n",
"css_styling()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<style>\n",
" @font-face {\n",
" font-family: \"Computer Modern\";\n",
" src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n",
" }\n",
" div.cell{\n",
" width:800px;\n",
" margin-left:16% !important;\n",
" margin-right:auto;\n",
" }\n",
" h1 {\n",
" font-family: Helvetica, serif;\n",
" }\n",
" h4{\n",
" margin-top:12px;\n",
" margin-bottom: 3px;\n",
" }\n",
" div.text_cell_render{\n",
" font-family: Computer Modern, \"Helvetica Neue\", Arial, Helvetica, Geneva, sans-serif;\n",
" line-height: 145%;\n",
" font-size: 130%;\n",
" width:800px;\n",
" margin-left:auto;\n",
" margin-right:auto;\n",
" }\n",
" .CodeMirror{\n",
" font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n",
" }\n",
" .prompt{\n",
" display: None;\n",
" }\n",
" .text_cell_render h5 {\n",
" font-weight: 300;\n",
" font-size: 22pt;\n",
" color: #4057A1;\n",
" font-style: italic;\n",
" margin-bottom: .5em;\n",
" margin-top: 0.5em;\n",
" display: block;\n",
" }\n",
" \n",
" .warning{\n",
" color: rgb( 240, 20, 20 )\n",
" } \n",
"</style>\n",
"<script>\n",
" MathJax.Hub.Config({\n",
" TeX: {\n",
" extensions: [\"AMSmath.js\"]\n",
" },\n",
" tex2jax: {\n",
" inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ],\n",
" displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ]\n",
" },\n",
" displayAlign: 'center', // Change this to 'center' to center equations.\n",
" \"HTML-CSS\": {\n",
" styles: {'.MathJax_Display': {\"margin\": 4}}\n",
" }\n",
" });\n",
"</script>\n"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 17,
"text": [
"<IPython.core.display.HTML at 0xaf5ecf8>"
]
}
],
"prompt_number": 17
}
],
"metadata": {}
}
]
}
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