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kokes/koubsky.ipynb

Last active September 25, 2015 19:59
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koubsky.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Koubského linka"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<blockquote class=\"twitter-tweet\" lang=\"en\"><p lang=\"sk\" dir=\"ltr\">Přemýšlím o definici nejlepšího věku: když a dokud umíte uběhnout 10 km za tolik minut, kolik je vám let.</p>&mdash; Petr Koubský (@petrkou) <a href=\"https://twitter.com/petrkou/status/647406779983360000\">September 25, 2015</a></blockquote> <script async src=\"//platform.twitter.com/widgets.js\" charset=\"utf-8\"></script>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ale to by snad šlo i nějak dopočítat. Pohled do statistik nachází [pražskej Night Run](http://www.night-run.cz/vysledky/2015/s-night-run-10km/z-praha). Pražská Grand Prix má víc dat, ale nemaj roky narození.\n",
"\n",
"---"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"from pyquery import PyQuery as pq\n",
"import re\n",
"from datetime import datetime\n",
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"from pylab import rcParams\n",
"rcParams['figure.figsize'] = 15, 10\n",
"rcParams['font.size'] = 18"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"rurl = 'http://www.night-run.cz/vysledky/2015/s-night-run-10km/z-praha'\n",
"p = pq(rurl)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"res = zip(p.find('table.res-zavod td.c-jm'), p.find('table.res-zavod td.c-cas'))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Máme jen rok narození, tak čistě frekvenčně losujem číslo a podle počtu dnů v roce určujeme, jestli už měl danej holomek letos narozeniny."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"def parsuj(jm, cas):\n",
" rok = int(re.search('([0-9]{4})\\)', pq(jm).text()).group(1))\n",
" \n",
" trs = datetime(2015, 9, 19).timetuple().tm_yday / 365.0\n",
" vek = (2014-rok) + (np.random.rand() < trs)*1\n",
"\n",
" hr, mn, sec = map(float, pq(cas).text().split(':'))\n",
" minut = 60*hr + mn + sec/60\n",
" \n",
" return (vek, minut)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>vek</th>\n",
" <th>cas</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>29</td>\n",
" <td>34.547450</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>26</td>\n",
" <td>36.351583</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>29</td>\n",
" <td>36.885933</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>27</td>\n",
" <td>37.090217</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>26</td>\n",
" <td>37.407417</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" vek cas\n",
"0 29 34.547450\n",
"1 26 36.351583\n",
"2 29 36.885933\n",
"3 27 37.090217\n",
"4 26 37.407417"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df=pd.DataFrame(map(lambda x: parsuj(x[0], x[1]), res), columns=['vek', 'cas'])\n",
"df.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Šťastnejch bylo 24 z 973.\n"
]
}
],
"source": [
"print 'Šťastnejch bylo %s z %s.' % ((df['cas'] < df['vek']).value_counts()[True], len(df))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Prvních pět\n"
]
},
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>vek</th>\n",
" <th>cas</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>46</td>\n",
" <td>38.852900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>49</td>\n",
" <td>38.970067</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>44</td>\n",
" <td>39.261900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>45</td>\n",
" <td>40.214817</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>54</td>\n",
" <td>40.716900</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" vek cas\n",
"9 46 38.852900\n",
"10 49 38.970067\n",
"11 44 39.261900\n",
"18 45 40.214817\n",
"22 54 40.716900"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print 'Prvních pět'\n",
"(df[df['cas'] < df ['vek']]).head(5)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x10579e2d0>]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"RK5CYII=\n"
],
"text/plain": [
"<matplotlib.figure.Figure at 0x10579e390>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df.plot(kind='scatter', x='vek', y='cas', title='Vek versus doba ubehnuti 10 km')\n",
"plt.plot([30, 70], [30, 70], 'k-')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Stěžujte si [na twitteru](http://twitter.com/kondrej)."
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.9"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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