{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# from_string" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import io\n", "\n", "def from_string(_str, **kwargs):\n", " # http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.from_csv.html\n", " return pd.DataFrame.from_csv(io.StringIO(_str), **kwargs)\n", "\n", "_csv = \"\"\"a,b,c\n", "1,2,3\n", "4,5,6\n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " a b c\n", "0 1 2 3\n", "1 4 5 6" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.read_csv(io.StringIO(_csv))" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pyperclip\n", "\n", "def from_clipboad(**kwargs):\n", " return from_string(pyperclip.paste(), **kwargs)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " a b c\n", "0 1 2 3\n", "1 4 5 6" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pyperclip.copy(_csv)\n", "pd.read_clipboard(sep=\",\")" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "10\n", " a b c d e ... V W X Y Z\n", "0 1 1 1 1 1 ... 1 1 1 1 1\n", "\n", "[1 rows x 52 columns]\n", "20\n", " a b c d e f g h i j ... Q R S T U V W X Y Z\n", "0 1 1 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1 1 1\n", "\n", "[1 rows x 52 columns]\n" ] } ], "source": [ "import string\n", "\n", "df_wide = pd.DataFrame(\n", " np.random.random_integers(1, size=(1, len(string.ascii_letters))),\n", " columns=list(string.ascii_letters))\n", "\n", "with pd.option_context('display.max_columns', 10):\n", " print(pd.options.display.max_columns)\n", " print(df_wide)\n", "\n", "print(pd.options.display.max_columns)\n", "print(df_wide)\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "hide_input": false, "kernelspec": { "display_name": "Python [default]", "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": "3.5.2" }, "toc": { "toc_cell": false, "toc_number_sections": true, "toc_threshold": 6, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 0 }