{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Markdown cell Title\n", "\n", "With **some** text" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Test\n" ] } ], "source": [ "print(\"Test\")" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ABCD
2013-01-01-0.1800210.3532620.0927321.307977
2013-01-021.6852971.224822-0.6337520.469845
2013-01-03-0.758091-2.0115910.007983-0.232754
2013-01-041.2104860.727872-0.178372-1.008124
2013-01-05-0.345644-0.4831280.1094030.362049
2013-01-060.6970370.033166-0.0214611.473813
\n", "
" ], "text/plain": [ " A B C D\n", "2013-01-01 -0.180021 0.353262 0.092732 1.307977\n", "2013-01-02 1.685297 1.224822 -0.633752 0.469845\n", "2013-01-03 -0.758091 -2.011591 0.007983 -0.232754\n", "2013-01-04 1.210486 0.727872 -0.178372 -1.008124\n", "2013-01-05 -0.345644 -0.483128 0.109403 0.362049\n", "2013-01-06 0.697037 0.033166 -0.021461 1.473813" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import numpy as np\n", "import pandas as pd\n", "\n", "dates = pd.date_range('20130101',periods=6)\n", "\n", "df = pd.DataFrame(np.random.randn(6,4),index=dates,columns=list('ABCD'))\n", "\n", "df" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04',\n", " '2013-01-05', '2013-01-06'],\n", " dtype='datetime64[ns]', freq='D')" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dates" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " A B C D\n", "2013-01-01 -0.180021 0.353262 0.092732 1.307977\n", "2013-01-02 1.685297 1.224822 -0.633752 0.469845\n", "2013-01-03 -0.758091 -2.011591 0.007983 -0.232754\n", "2013-01-04 1.210486 0.727872 -0.178372 -1.008124\n", "2013-01-05 -0.345644 -0.483128 0.109403 0.362049\n", "2013-01-06 0.697037 0.033166 -0.021461 1.473813\n" ] } ], "source": [ "print(df)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 2 }