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chewbranca/heatmap_test.ipynb

Created January 9, 2017 19:08
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heatmap_test.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"\n",
"np.random.seed(24)\n",
"df = pd.DataFrame({'A': np.linspace(1, 10, 10)})\n",
"df = pd.concat([df, pd.DataFrame(np.random.randn(10, 4), columns=list('BCDE'))],\n",
" axis=1)\n",
"df.iloc[0, 2] = np.nan\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
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"\n",
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" <td id=\"T_e6bb975e_d69e_11e6_a1f8_acbc32c50aadrow7_col4\" class=\"data row7 col4\">\n",
" 0.519818\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_e6bb975e_d69e_11e6_a1f8_acbc32c50aad\" class=\"row_heading level4 row8\">\n",
" 8\n",
" \n",
" <td id=\"T_e6bb975e_d69e_11e6_a1f8_acbc32c50aadrow8_col0\" class=\"data row8 col0\">\n",
" 9\n",
" \n",
" <td id=\"T_e6bb975e_d69e_11e6_a1f8_acbc32c50aadrow8_col1\" class=\"data row8 col1\">\n",
" 1.68658\n",
" \n",
" <td id=\"T_e6bb975e_d69e_11e6_a1f8_acbc32c50aadrow8_col2\" class=\"data row8 col2\">\n",
" -1.32596\n",
" \n",
" <td id=\"T_e6bb975e_d69e_11e6_a1f8_acbc32c50aadrow8_col3\" class=\"data row8 col3\">\n",
" 1.42898\n",
" \n",
" <td id=\"T_e6bb975e_d69e_11e6_a1f8_acbc32c50aadrow8_col4\" class=\"data row8 col4\">\n",
" -2.08935\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_e6bb975e_d69e_11e6_a1f8_acbc32c50aad\" class=\"row_heading level4 row9\">\n",
" 9\n",
" \n",
" <td id=\"T_e6bb975e_d69e_11e6_a1f8_acbc32c50aadrow9_col0\" class=\"data row9 col0\">\n",
" 10\n",
" \n",
" <td id=\"T_e6bb975e_d69e_11e6_a1f8_acbc32c50aadrow9_col1\" class=\"data row9 col1\">\n",
" -0.12982\n",
" \n",
" <td id=\"T_e6bb975e_d69e_11e6_a1f8_acbc32c50aadrow9_col2\" class=\"data row9 col2\">\n",
" 0.631523\n",
" \n",
" <td id=\"T_e6bb975e_d69e_11e6_a1f8_acbc32c50aadrow9_col3\" class=\"data row9 col3\">\n",
" -0.586538\n",
" \n",
" <td id=\"T_e6bb975e_d69e_11e6_a1f8_acbc32c50aadrow9_col4\" class=\"data row9 col4\">\n",
" 0.29072\n",
" \n",
" </tr>\n",
" \n",
" </tbody>\n",
" </table>\n",
" "
],
"text/plain": [
"<pandas.core.style.Styler at 0x1199dadd0>"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import seaborn as sns\n",
"\n",
"cm = sns.light_palette(\"green\", as_cmap=True)\n",
"\n",
"s = df.style.background_gradient(cmap=cm)\n",
"s\n"
]
}
],
"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": "2.7.11"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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