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@Yoshiharu-Ikutani
Created August 6, 2017 08:42
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"GoogleFinance から取得した株式データを ggplot を使って可視化する \n",
"米国株式のデータは pandas_datareader.date で簡単に取得できるが, 日本株のデータは取得できない \n",
"この notebook では 自作関数 GoogleFinance を使って, 日本株のデータを取得・可視化する"
]
},
{
"cell_type": "code",
"execution_count": 402,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# -*- coding: utf-8 -*-\n",
"import pandas\n",
"from ggplot import *\n",
"import datetime\n",
"from GoogleFinance import GoogleFinance"
]
},
{
"cell_type": "code",
"execution_count": 403,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"cp = pandas.read_csv('./csv/company_it.csv')"
]
},
{
"cell_type": "code",
"execution_count": 404,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# get stock code from company name\n",
"def get_code(name, cp):\n",
" return int(cp[cp['name'] == name]['code'])"
]
},
{
"cell_type": "code",
"execution_count": 405,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# 日本株式は market を 'TYO' に指定\n",
"name = ['アエリア', 'アズジェント', 'ASJ', 'enish']\n",
"code = [get_code(n, cp) for n in name]\n",
"# code = [3758, 4288, 2351, 3667]\n",
"comb = pandas.DataFrame({'name' : name, 'code' : code})\n",
"market = 'TYO'"
]
},
{
"cell_type": "code",
"execution_count": 406,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>2351</th>\n",
" <th>3667</th>\n",
" <th>3758</th>\n",
" <th>4288</th>\n",
" <th>Date</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>404</td>\n",
" <td>457</td>\n",
" <td>356</td>\n",
" <td>437</td>\n",
" <td>2016-08-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>402</td>\n",
" <td>475</td>\n",
" <td>359</td>\n",
" <td>439</td>\n",
" <td>2016-08-09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>403</td>\n",
" <td>470</td>\n",
" <td>354</td>\n",
" <td>437</td>\n",
" <td>2016-08-10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>412</td>\n",
" <td>480</td>\n",
" <td>364</td>\n",
" <td>435</td>\n",
" <td>2016-08-12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>416</td>\n",
" <td>484</td>\n",
" <td>362</td>\n",
" <td>454</td>\n",
" <td>2016-08-15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>420</td>\n",
" <td>482</td>\n",
" <td>354</td>\n",
" <td>448</td>\n",
" <td>2016-08-16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>420</td>\n",
" <td>474</td>\n",
" <td>354</td>\n",
" <td>444</td>\n",
" <td>2016-08-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>422</td>\n",
" <td>462</td>\n",
" <td>362</td>\n",
" <td>451</td>\n",
" <td>2016-08-18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>423</td>\n",
" <td>465</td>\n",
" <td>351</td>\n",
" <td>459</td>\n",
" <td>2016-08-19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>428</td>\n",
" <td>482</td>\n",
" <td>338</td>\n",
" <td>455</td>\n",
" <td>2016-08-22</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 2351 3667 3758 4288 Date\n",
"0 404 457 356 437 2016-08-08\n",
"1 402 475 359 439 2016-08-09\n",
"2 403 470 354 437 2016-08-10\n",
"3 412 480 364 435 2016-08-12\n",
"4 416 484 362 454 2016-08-15\n",
"5 420 482 354 448 2016-08-16\n",
"6 420 474 354 444 2016-08-17\n",
"7 422 462 362 451 2016-08-18\n",
"8 423 465 351 459 2016-08-19\n",
"9 428 482 338 455 2016-08-22"
]
},
"execution_count": 406,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"date = GoogleFinance.call(str(code[0]), market)['date']\n",
"date = pandas.to_datetime(date)\n",
"px = pandas.DataFrame({n: GoogleFinance.call(str(n), market)['CLOSE'] for n in code})\n",
"px['Date'] = date\n",
"px.head(10)"
]
},
{
"cell_type": "code",
"execution_count": 407,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"data = pandas.melt(px, id_vars='Date').dropna()\n",
"data = data.rename(columns = {'Date':'Date','variable':'Stocks','value':'Price'}) # common to rename these columns\n",
"data = data.astype({'Stocks': str, 'Price': int})"
]
},
{
"cell_type": "code",
"execution_count": 408,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# for i in range(len(code)): \n",
"# data['Stocks'] = data['Stocks'].where(data.Stocks != str(code[i]), name[i])\n",
"# data['Stocks'] = unicode(data['Stocks'])"
]
},
{
"cell_type": "code",
"execution_count": 409,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"p = ggplot(data, aes('Date','Price',color='Stocks'))\n",
"p = p + geom_line(size=2.) + scale_x_date(labels='%b %d %y',breaks=date_breaks('week') )"
]
},
{
"cell_type": "code",
"execution_count": 410,
"metadata": {},
"outputs": [
{
"data": {
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u3buxadOmsIq9adMm7N69G29/+9vR29uLgwcP4o477gAAbNu2bcpziYiIaPHIqcYQxgEI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ggEc1JKyzP+FsxPJX7SVuLfBgb5el9/5bmp+InIf69eTFOnUEoAkCk74fPRP/k6YLvf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\nBxlPn+Fo/zfom3jtku3juR56x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HYEMS2Djrp93LbpgzNctylkWcY0V3+VkcW+Ty3L4uD5\nr9I3/jrFUpqinqFYSmGYJVqqbubde/4YSZI40f9dXjj1mRn7OhQvkiRhmjq3bvwAu9p+fN4xWZbF\nf7zx/zGSOM4tG/4Le9t/Blg7cwpX9v//WrPa5/VK5nJ/1xcYTZ7izi0fIupfd3UGOAvLOadyTzeu\nr/4TZmMzxff/8rIccy29P6e4nt+nV0okcvllVQXXHiHAF8HQ0NBl7+twOKipqSEWi1EqzS0QNT3L\nkb6v43NV41R99I6/zGD8IKY1e63poKeRm9f/Ai1VtwKQKYzRPfYs3WPPkMoP4laruKf9E9TXXXq7\nHWzHlRM9RJ/+GmlF5j0334NTgm9rGZTDL5Fw54m7CozXOuh0alTH303I2IGMyoRjPz5/BK9aRSLb\nj1bKo5ge6hKPIDPT1Sspcbrr/ox44MVZx6HKbu7Y9D9YX3PXjMfThRGeOfGHJPMD1AS3sHfd+6kN\nbqnMaSRUzfk34qQHJCTFIrC+hLfhyqp5GGYJCWnBDorZ4jhPHv0Y6cJI5TFFdhL1tWNhUtLz6GaB\nkpFDNwrUBrdz79bfmtUtXy0s9n16pO9rHOr9yiWPBz3NPLjj92fc2p/Mnmc4fphY+gyxdCfZYmzG\nPi3RW6kLbcepeFEVD46pP6qHsLeN/on9PNf5aVxqkPfe/H8qFS88Hs+1L5dXKuE+ehDX0QOYXh/5\nt92N3rbevs1jmqDM3slosfO6GliReV0Ca2kup1jOOXUfeA3vCz+isGsPufvftSzHfKvP6dVgJee0\nsbHxmp5PcGUIAb4IrrYAN02dp098slJ5YRqJgLsejzOM2xHC7QhjWSYjyaMV8be+5m60FMQypykp\ncSxZw2FG2dL/afyFrejBAZRoGodXJhJqRourFCcUipOKXbrPTKFFx/m+S2erFqGhlMIomSimF9n0\noJheFMt96aDner0dAwxpL1HKWOhKmljkCfyBCLKsIEsKEgqyJKMqbiK+9XTU3kfI2zT7vFgGlmVe\ncqv+an3AKcODABgNs4/nQoqlDKnCILKk8sa5LzCSPDrv9tX+jdzc/ovUBrfMqGZxOViWRbowQlFP\nUeXfgCwpWJaFpmcolFL43DVLrvCw0JyWjAKHer9cbt8tcfvGD1MT2IRT9eFU/aiye8F23jktDsBg\n/ACvnPmbeeM+XmeUQimNaZW4uf0X2d70cOW5a/IFrBVRJscxw1FcJ47gfvM15NzM9RHa+g2oo8NI\nxQJ6YwuFvbdSWtfBhSuL15LAEcJm+VnOOfV9/zu4Oo+Tvf9dFHftWZZjvtXn9GogBLhgsYgM+Apj\nWRavdf8dQ4lDuB0h6oLb0c0iLdFbaa2+rdJcoxiXSZ52Yuqwe32BHvPbnDl5EPfBR6nP3USlobuq\n27foNFvkqalmSIEOxC46tyGngSBSIshDlUdna3JRpKZ0CM9dzRjBCPkxBayyzpDtXDOShTNs4m8N\nsJ530jfxKiPJAW5t/ONKp8KlIkuKvbrwamOaeF5+Ds+br2JJEsmf/2XMyPxl2lwOPzUOu67zO3d9\nioKWJJ7rRZVd5YYntpsrqwbfefPXGc908f2jv4nHGaUuuA0LC9PUMS0dh+JhW9MjFYf/YizLJKdN\nYlkmhVKS5zv/tNIB0Ra/TvKlZCVH73FEuLn9A4B9J0GVnTRF9iLLKrpRQDeLGKZGyNuKxxGmZOTI\namlcPhPD1MlrSTQ9g6ZnyWmTxNKn6Rp5iqKeQkLm1o4Psqn+wSVP89R7eWPd22kI7WIwfoBErh/d\nKFAy8uhGnpJRIKeNVy4wtzS8m22NP7bkc10JUiZN8JtfqbT8nkKvayB/650oEzE8+1/Gef5s5bn/\n296dB0dxnwkf/3b33KP7BgkQp7kPcxi8BmwwtmPHgJPYwU52U7aTLSqO46ztyuV6q/z+sevKJrsu\n15vXS1LZ5Y2TcrAdQgzGOL5kMDHGGISEuAwSCCHQgY6R5p4+3j9GGiQkIQGjAcPzqaLEzPT0dD9z\n9NO/3/P7tb3uJPa6k8RKxhBcvAyjKHkHQiUcAsvCcvc/77m4MZwfgHltzN0uhLgy0gI+BMPZAm5a\nBp9U/ZamhjoWjHyK7MxibF4TzWmh2i38dXbaDzkINfQ+V1JsVteFWQBNR3MqGCEVrPh9jkwD721f\nUHfiKGo4nWBnCCNqEXLUEnAdJeA8jqH6SQtPpzP0j6j6KGyundxUZDGp+E5cbjeqPb4N3o/exl1V\njunxElh2D7Ex4yBJl6u/HMlsYVCCAdLe/iv2upOJ+yKTpxP4yqq+C5sm9uovcB7cT6x0ApHZ8wZd\nv9vt5lx7HYfq/8rJc58QiDQNuOy8sY8yveTrhGMdHK7fTLP/C/zhhq4a9N6lSC57JnbNk0jEIV5j\nramOxFUTh0JTnYn5pweTlz6JheO/f0XzTw+FZZmcavmUcKyDSUV39ekxuOQWsGgE1d+JYhiY3jQs\nj7ffxZRIGGfVfpzle9A6OzAdTtRoBL1oJKGFi3u1bqvtbbj2f06sZDR68Sichypx7f47aiQMQGTi\nFPTRpTBqDLnTZgz5s6oE/NiaGtCaGhJ/tQ4flt2B75/+GTPj4uM6roS0LCZf0mIai5H9f38JQNsP\nfgy25LSd3dAxHSbSAi6GSlrArzJV0Rhd+yz5DTYCtTDQJICKzSJjQhTNadFZYyfWqaE6LLKnR8ie\nFkGzmyh+P1ZrANMXxp5nx8gvoiAvH8XQMVQFX6wRwxyJZS3ACgfwvrkBw67w1LRO2vXD/HruEood\n3QMJz5cHhG6/E5uvFXtdLelvbcQifiU2vXAkevEoYsWj4y3GsRj2M3Xo+YVY3oGvznfJLOv8/LfZ\nuaAoWJEwhIIouo7ldDGkK/ZcQDtbT9pbG9H8nZgeL8Ely/G++xaOI1XoJaOJTJoKTifEYjgPVeDa\n+xmaL15GYT9Zg14yBiNv8Mtie515zB/3XeaNfZwW/3F8odOoii3+T7XR5DvIgdN/prz2VdKchfz9\n2EvEjN4HGJc9C7CIxDqZVHQ3C8b/M6piwx9pQkHBZc/EpjkxLYODpzdR17obtyOHdFchwUgLjR2H\nUBQVm+rCprlQFZVWfw26GcGmuvA4s9HNCKFoOw4tLVFa4rJnkO0dQ0n2fAozpw9aZpIMiqIyJu/W\noS1sWaidHTgOVeI6ED9J1AsKUf1+1M4OVH8HauT8CYalKMTGTUQJh1H0GJbdjmW3g82O7dTJRAKt\nFxTR+bWHsRzOfuu7zaxsgrevSNwOz11IZNosXHt24Sr/DOexwziPHcZSFPQ7v4KWnYuek9d/K7au\n4961A+fhA6gBf/8xiUVxVuwltHjZ0OIirmm2ulocRw4QXrgEMz1j0OW1c00oloWem5+05FsIcXVJ\nC/gQDHcNeOMnLkKNNuxpZuIKjGZEwYgqODJNsiYGyRrRgj0W6GoZO0ss6sQW68AW9KEG/CjBAMog\nb6Xp9mDZbKCq8aS2w0dT8RgeHDURl6qyceliouHwAE82cZV/huNwFVpLM8oFo9BNjxcMAzUSxlJV\n9BHFGNk5mJk58b9Z2RiZ2X1bznUdtdOH2tmBYhjxAW2mGV+/ZaI1NeI4dgStY+BWXdPjJVY8mti4\nCZjpGdhOn0IN+LE8HkxPGqbHi+XxdrV+erCdrce5/3PsJ46jALERxfi/+jWstAw8H72Lqzw+j7il\nKJiZWajBAEq0a47vjCzMzEzsdbXEikcTXHYPxKIo0Uj8xMDhxHK5sVwuLJsdj6kTVDSwX3zKufer\nnud02+eJ2yOyZjN5xH1kuEeS5irErrmwLOuSpvAbjGnqGGYUu81zzbWEqR0+0PW+l9zWdbztrRgn\na7Cdrcd29vSASWs3S7NhpqdjaTa01nMX/Z7EikcTnruAWOmEAQdWDrrtnR04D5SjtrXi/OJQ4n7T\n4SQyYzaKYaKEAvHPVTiMGgqi+jsTyxgFhRgFRegFRegFI1DDITJefwXT7aH9u08OWwLWp2UxGkVr\nbQabAyMnN/67cRVda5/RoeivtdZZsRdP2d9QLIvo+En4Vz446HqcFXvxfvgOkSkzCNyTvJKs6yWm\n1xJpARdDJafS14ARk0/DTRZmRhZYJrbGBuwnjmM/WY1W34Zyqu9MKM4LbluA6U3DTEvH9KahtbWi\ntrWAzYal2VD0GGqo7zSCh0aVAjDO6734JehVlfDchYTnLgRdRzvXhO1sPfb6U9jq6xID1IycXNS2\nVuz1ddjr6/qsxvR4MbJysJxOtJZm1A4fQ2lTNT1eLLsdzdeOpaooNhuWooJpogYDiRbHS2FpGqFZ\n8wjddkci2QouuRM9vxDnwUpsZ+rQ2uMt3nrhCELzFhGbcBNKJEzm/1uHvf4UmX/47aCv43C6CC1e\nRnTshHjPQD9xnj7qG4kEvCBjKium/+/E3OrdFEVBU5I3d7Sq2gad8SVldB3bmTrsJ6pxnKxGaz0H\ndCfEt6D6O3AeOoDW1ND35M/pQh9ZQvjmBSixKGpnJ2Z6OmZ6JmZ6BpbLfb50xNeOvbYGMyMT0+VC\nicVQolEUPYaZloE+suSyelN6bU96BqFblwJgzJxD2sEKYq0taI1nce/d3e9zjMxsAnff3+/rm5aF\nnl+IrbkR9+6dhBYtAUVB9bWDaYDNjqVp57/r0Qi2s/VYLjdGdg6oGpaqxhPoriRaa20B08DIKwBD\nR/O1owb8uM+cRjvXhNbclOjticfYSWT6HIz8AlA1TJcLy+mKn2g64/96JeixKIphxLdLs1315P2a\nYJp4tr+Ha3/8e26pKo7qL7CdOR1/3y9Ca45fwEkuwCPE9eMaOfre2DyfbMdx7MiAj1s2W6IV18jM\nRi8uwbI7sBzOeKuuNw3Tm9a3xc6yzh/MLSveSt7dymwYoCgcDoTgdD0T0/qvi+2XzYZRNBKjaCSR\nOfPjZQDtrWCamLn5KMEAWnMjWnsrWnsbantb/K+vDTUY6DWbhKUoGOkZmOmZWHZbfESnpsWTa1XF\n9KYRm3AT+ojiRMu93eE438IQjaL62rDXHMdefwrV34meV4CRX4AaDKJ0vZ4aDKAE4n9Nj4fIjDlE\nps/uWw+sqkSnzSI6bVa8drizI55g9EicLbeHzgfW4Nr7KbaGM/EWb6crHuNoOF7eEAnHW81dbtRQ\nEO/7b+MlniyaGZnxfVS79tXuoDQ3n+L0mbSET7F40tN9ku8h0WOofn+8S/syW28viWWhNZzBWbUf\n1d9JdOJk9DHjsADN146Zlh5/z2IxlFgUJRbFVl8Xj5nDgZFXgOV0Ya+twX7qBEqP1iLTET/FtNef\nwl5/6vxLAmZ+IdHCEegjS9BHFMcvSjLEpNnMzEraDBJDYYybiOOWW/E1N8OxI9jq6zDdbiy3N/6d\ndsUTVyMnb+D3TFEIz1tE2ra/4v7s77j2fgqKiqJfeeuapdlQjP6nOrW6tkuJRtA6fLj3fnrxdTkc\nmF2JuOpr73VibSlK/LOu2eJ/bbbEbcvtxnR74z1Wbg9qZ0e8/r2lGQwDy+nETMtA0VQimg2PoWNp\nNkLzbyU2vu9Fk65FSjhM2tubsNfWYGkagTvvRWtrxf3Z3/F89C4dD/3TRXs2bF0DMI18GYApxPVC\nEvBrgNmVWKudPlA1jMwsYqXjiY2dgF444vIHPPZMShQFy5vGhZ3vxxqPAjA+7QpqthWl15XZLI8X\nfcw49DEXXKrbNFH9najtbSjhEEZuPmZW9qUlixcmWoqCmZVD5OYFRG5ecPn70B+HEzO3/xpvo2gk\ngfsufiEZLAu3241RvgdnZXm8xT8SRm3uW+bjqDnGN7wF+FY/gfNIHWroCKD0amk0M3MwcnKxV3+B\nrbkBJeBHDfhROzvjcQ3Hu2WNjEz8Kx/EyI+3linhcLzluOukQIlFu/5GsJ09E28t9XqJjp+ENnYC\npsMZL6VxxE/ysNvPx70rybfXHMNZtR9by/m5dRwnqy8tvkcP9bqp5xWc/9yPKAZDx1m1H1flPiy7\nnfC8W4mVjsOVlX1Nd0EPJFY6Pj6Q8zJEJ0+j027Ds+NDtPZWoGtAqcMBuo6i6/FEWtdBUdFHjESJ\nxE8gsax4r4EZP/lWLAujazCn1uHD0rR471tOLtHsXIz8Aoy8gvh4i67vptZQj/NgZVdvgR7/LEV6\nnGx2fba0rlItS1Ux7Y7ENimWldjOS6VEIqhdc8hbQPevRdqWPxNavJzo2PGYOX2vgHmtUNtbSX/z\ndbTWFky3B//930AvHoUSCeM4fABb41m8774VLy3pr6fAMNDOxQdvd3+nhRBfflIDPgSpuBAP0LvF\nOgUsy+LRvfvwxXRenj2LcTlfjsTmy1S32Kte0bISSTOm2dUbYaCGQrjKP8PWNQ/5xZgudyLRvpCl\nqlh2R7wOH+KlCTZbPDm6gq+5BfFEXKHXgEaInzxGpszAzM6J1+o3xmdlMbOyUQL++Gfa7kgMdjSz\ncuKz6Og6trOnUaIR9FGlREvHYw1hMBpc+zWgPSX9s2pZoMdQDDPeej7QMhf7HenxuBIOYzmdoChX\nFlfLQolEUCLheO1+Ztb5Ft3uixUZRjwhN4z4Z9/oOnEIhVBDga7eqmC8QaKgCD2/EOx2lHAINeDH\npmlkZ2fT1taGeugA7j2fJF4+VjyK0G3LBi3lSDVvUwP2ja+ihkPoufn4Vz0Uj00XrbmRjNdeQYlF\niY0cReCur56fAtWyUCJhbGfrSf/raxgZWfgefyKp2/dl+i3tdq1//6UGXAyVtIBfQyKmhUON1/qe\nDYX5rK2NgK7j1DRcqopTUylxu5mcHr+i4rlIhDPhMDMyMi5rdoqTwSC+mE623U6R68KqcpF0ioKV\nlo6R1veKmLGS0WT8aT1aZwfR0vHoRSNR4HwLYziE7cxp1HAIIyOT6JTpmGkZ5+v+09Lj5TSGgfeD\nbTgOVaLosfhMH6qKXjSyq47eEW/Z7vprZmQRGzMWRyxKxqkTRL44ApEwSjQSb+3sqo9WovHE2+oq\nCzLyCohMm0Vs3MREK2lkxpxLCkd02swrDukNR1G6TmgGWWawdXQZMIm/jO2yXK7+19dVfoKmYRHv\nzbuU00HL48XweFHtdtT8fEyHi0hOHkZOXryGuu4E9vo6bH/+I8Eld2J6vPHafj0KloWZnkls9NhB\nB0JDfA5456FKbI0NGNk5GPkF6HkF8R6+S6xjd1Ttx/HBOyimQXTsBPxfWR2fVakHI7+QztXfjJen\nnKkj8/frMAqKUELB+OB64/zVfQ2p/xbiuiIJ+DXgdydO8nlbO42RCAVOJx5N42Sw74DJblPS08l2\n2PmstQ3dspifncU/jRlNsWvwqxH29FlrfJDVvOyslEwvJwZmedPo+NbjKKHgwN3puo7Weg4jN3/g\nsh2bjcDd9xNYcV+8y9/QsWz2QZMP027HPnU67XMX9m21Mc14Pbtl9hrQKMTVFJ06g+jUGRCN4Pn4\nQ1yV+/CW/a3fZfXcfDofWIPW4Yu3xqtqr4GpSjCIo+YLnAfKeyW93SxNw8jNi8/2NARKTE+MXQjN\nvYXQbcsGTOD1ktH4/vF7eD7+EMehSmyN5+f2txyOrpPsDELzFg3ptYUQXw6SgF8D2mMxGiMRFKCp\nq4vfo2nMy85ipMtFxDQJGyYhw2BPWxuHOzsTz3WpKnva2tnT1k6B08mcrExmZWZSGwxSGwyS73Ry\nW24uk9L71njvaYtP7bcgJzsl+ykuznJ7Ln61Q5sNY6hXwVNVcDgSLY5XRFWT11IqRLI5nASX3YOR\nm4+95hjY7Vi2rvndAfupE9hamsn+3f8ZdFUWEJ1wE9GxE9A62uOzwZxrQuvwYWtqvKTNslSV2D0r\nCd00bfBl3R4Cd32V0MLFqB0+zLSugfX2q3fBMyHE8JIE/BrwYEkxD5YUM9LlojoQIGyYTMtIx95P\ni4lf19nX1o5uWUxI8+LWNF6tO82+tnaaIhH+1tjE3xp7X21xy9kGFufm8sMJ47B1rbPaH6A6EMCp\nqswYxqvrCSHEsFMUIrPn9Xt1WsXfScYbf0Rrb0XvmnknPhjVTFx3wLI7MAqLiEyf3e9ARyUSRms5\nF69xHyIjJw9n0Qi4hHplMyNzWK92KoS4dkgCfg0Y4znf6tld3z2QNJuNJfm9SxSemjAe07KoDgQo\nb/dxwNdBjsPOnKwsTgaCvNPYyMctLQDkOBx83tZGfdcFd2ZnZeLUZI5eIcT1yUpLx/ftx1EiEax+\nxl8MaR1dc80LIUSySAJ+nVAVhYlpaUxMS+OhkuLzD+TDrbk5/K9DhxNJOECapnFzdhZrSuSgIoS4\nztnjA4+FEOJaIQn4DWBSehrPTprAxtNnuCk9jfnZ2UzJSL/4lS+FEEIIIcSwkAT8BjE/O5v52TLY\nUgghhBDiapPiXyGEEEIIIVJIEnAhhBBCCCFSSBJwIYQQQgghUkgScCGEEEIIIVJIEnAhhBBCCCFS\nSBJwIYQQQgghUkgScCGEEEIIIVJIEnAhhBBCCCFSSBJwIYQQQgig+u1aAAAVr0lEQVQhUkgScCGE\nEEIIIVJIEnAhhBBCCCFSSBJwIYQQQgghUkgScCGEEEIIIVJIEnAhhBBCCCFSSBJwIYQQQgghUkgS\ncCGEEEIIIVJIEnAhhBBCCCFSSBJwIYQQQgghUkixLMu62htxPevo6GDv3r3MnTuXjIyMq7051wWJ\nafJJTIeHxDV5JJbJJzFNPompGCppAR9mfr+f7du34/f7r/amXDckpsknMR0eEtfkkVgmn8Q0+SSm\nYqgkARdCCCGEECKFJAEXQgghhBAihSQBF0IIIYQQIoW0559//vmrvRHXM8uycDgclJaW4nQ6r/bm\nXBckpsknMR0eEtfkkVgmn8Q0+SSmYqhkFhQhhBjE+vXrmTlzJnPnzr3amyKEEOI6YLvaG3A1rF+/\nnsbGRp599llstuELwa5du9i5cyexWIypU6fy1a9+NfF6H374IUeOHKG5uZklS5Zwxx13DLiexsZG\n3n33Xc6cOUMoFKK/TosDBw6wfft2fD4faWlprF69mjFjxgzXrvVRXl7Orl27aG1txel0MmXKFJYv\nX47b7R70uc8//zxPPvkkubm5Ay5TWVnJBx98QDAYZNy4caxatQqPxwPA7t272b9/P01NTUyfPp0H\nHnhgwPV0dnayZcsWzpw5g9/v56mnniI7O7vXMtXV1bz33nu0tLTgcrm4++67mT59+hAjceVefPFF\nAoEAqqqiKAr5+fnMmjWLuXPnoqrJrRoLBoNs3ryZ6upqPB4Py5cvZ+bMmcDQYtXTYO9DNBrl3Xff\n5eDBg5imSWFhIY899lhS92cw3bFVFCVx35NPPpn06cJqamrYunUrPp+PkpISVq9eTVZWFgBVVVV8\n+umnNDQ0UFxczKOPPjrgenRdZ+PGjZw5cwafz8d3vvMdxo4dm3j8j3/8I7W1tYnbhmGQl5fH97//\n/aTuz8UM5+/p2bNn2bx5M83NzeTn57Ny5UpGjBgBwIkTJ9i+fTtnz57F5XLxL//yLxdd1+bNm6mt\nraWlpYVVq1YxZ86cxGNbtmyhsrIycds0TTRN4+c//3lS92eohuuE70aO5/V0zP/Xf/3XXrd1XWf+\n/Pnce++9Sd8nMXxuuAS8ra2NU6dO4XQ6OXr0KNOmTRuW1zl+/Dg7d+7kO9/5Dunp6WzYsIGysjJW\nrFgBQE5ODitWrODzzz8fdF2apjFt2jTmz5/Phg0b+jxeXV3N+++/zze+8Q2Ki4tTPv3RJ598wt//\n/ndWr17NuHHj6OjoYOvWrfzhD3/gscceu+IfvKamJt566y0ee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5o1a1Ja5iGEEOL69d57\n71FZWcmdd97Z79z9IrXkmC+Gk5SgCCGEEEIIkUJSgiKEEEIIIUQKSQIuhBBCCCFECkkCLoQQQggh\nRApJAi6EEEIIIUQKSQIuhBBCCCFECkkCLoQQQgghRApJAi6EEEIIIUQKSQIuhBBCCCFECkkCLoQQ\nQgghRApJAi6EEEIIIUQKSQIuhBBCCCFECkkCLoQQQgghRApJAi6EEEIIIUQKSQIuhBBCCCFECkkC\nLoQQ15DS0lLcbjfp6elkZWVx6623sm7dOkzTHPS5J0+eRFEUdF1PwZYKIYS4XJKACyHENWbLli10\ndnZSW1vLT3/6U37xi1/w+OOPX+3NEkIIkSSSgAshxDUqMzOTlStX8tprr/H73/+eqqoqtm7dypw5\nc8jIyGDUqFE8//zzieWXLFkCQFZWFmlpaezatQuA//mf/2HKlClkZ2dz9913U1tbezV2RwghRBdJ\nwIUQ4hq3YMECSkpK+Pjjj/F6vbzyyiu0t7ezdetW/uu//ou//vWvAOzYsQOA9vZ2/H4/ixYt4s03\n3+Tf/u3f+Mtf/kJzczOLFy/m4Ycfvpq7I4QQNzxJwIUQ4ktg5MiRtLa2cvvttzNjxgxUVWXmzJk8\n/PDDbN++fcDnrVu3jp/97GdMmTIFm83Gz3/+c/bv3y+t4EIIcRVJAi6EEF8C9fX15OTksHv3bu64\n4w7y8/PJzMxk3bp1nDt3bsDn1dbW8tRTT5GVlUVWVhY5OTlYlkV9fX0Kt14IIURPkoALIcQ1bs+e\nPdTX13PbbbfxyCOPsHLlSurq6vD5fKxduxbLsgBQFKXPc0eNGsVvfvMb2tvbE/9CoRC33nprqndD\nCCFEF0nAhRDiGtXR0cFbb73FmjVr+Pa3v82MGTPo7OwkJycHl8vFZ599xquvvppYPj8/H1VVqamp\nSdy3du1aXnjhBQ4ePAiAz+fjjTfeSPm+CCGEOM92tTdACCFEb/fffz82mw1VVZk6dSpPP/00a9eu\nBeDll1/mmWee4Qc/+AFLly7loYceor29HQCPx8Nzzz3HP/zDPxCLxXjnnXd44IEH8Pv9rFmzhtra\nWjIzM1mxYgUPPvjg1dxFIYS4oSlWd9+lEEIIIYQQYthJCYoQQgghhBApJAm4EEIIIYQQKSQJuBBC\nCCGEECkkCbgQQgghhBApJAm4EEIIIYQQKSQJuBBCCCGEECkkCbgQQgghhBApJAm4EEIIIYQQKSQJ\nuBBCCCGEECn0/wGy8yzgovjLyAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11682aad0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<ggplot: (292041961)>"
]
},
"execution_count": 410,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p"
]
},
{
"cell_type": "code",
"execution_count": 401,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>code</th>\n",
" <th>name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>3758</td>\n",
" <td>アエリア</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>4288</td>\n",
" <td>アズジェント</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2351</td>\n",
" <td>ASJ</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3667</td>\n",
" <td>enish</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" code name\n",
"0 3758 アエリア\n",
"1 4288 アズジェント\n",
"2 2351 ASJ\n",
"3 3667 enish"
]
},
"execution_count": 401,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"comb"
]
}
],
"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": "2.7.13"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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