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June 2, 2016 15:39
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Learn more about bidirectional Unicode charactersOriginal file line number Diff line number Diff line change @@ -0,0 +1,262 @@ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# DeclarativeWidgets DataFrame Sync Test 2" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from IPython.core.display import HTML, display, clear_output\n", "import pandas as pd\n", "# pd.show_versions()\n", "\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "<link rel=\"import\" href=\"urth_components/urth-viz-table/urth-viz-table.html\" is=\"urth-core-import\">" ], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%%html\n", "<link rel=\"import\" href=\"urth_components/urth-viz-table/urth-viz-table.html\" is=\"urth-core-import\">" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "collapsed": false }, "outputs": [], "source": [ "df1 = pd.DataFrame([[1,2],[3,4]], columns=['a','b'])\n", "df1.columns.name = 'df1'\n", "df2 = pd.DataFrame([[5,6],[7,8]], columns=['c','d'])\n", "df2.columns.name = 'df2'\n", "df3 = pd.DataFrame([[9,10],[11,12]], columns=['e','f'])\n", "df3.columns.name = 'df3'\n", "df2_orig = df2.copy()" ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def print_df(idx:int):\n", " global df1, df2, df3\n", " clear_output()\n", " print(idx)\n", " if idx > 1:\n", " display(df3.style.set_properties(subset=['f'], **{'background-color': 'pink'}))\n", " else:\n", " display(df2.style.set_properties(subset=['c'], **{'background-color': 'pink'}))" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "<template is=\"urth-core-bind\">\n", " <urth-core-dataframe id='df1' ref=\"df1\" value=\"{{df1}}\" auto></urth-core-dataframe>\n", " <urth-viz-table datarows=\"{{df1.data}}\" columns=\"{{df1.columns}}\" selection=\"{{sel1}}\" rows-visible=6>\n", " </urth-viz-table>\n", "</template>" ], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%%html\n", "<template is=\"urth-core-bind\">\n", " <urth-core-dataframe id='df1' ref=\"df1\" value=\"{{df1}}\" auto></urth-core-dataframe>\n", " <urth-viz-table datarows=\"{{df1.data}}\" columns=\"{{df1.columns}}\" selection=\"{{sel1}}\" rows-visible=6>\n", " </urth-viz-table>\n", "</template>" ] }, { "cell_type": "code", "execution_count": 66, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3\n" ] }, { "data": { "text/html": [ "\n", " <style type=\"text/css\" >\n", " \n", " \n", " #T_dbaab18a_28d7_11e6_a50b_0242ac110002row0_col1 {\n", " \n", " background-color: pink;\n", " \n", " }\n", " \n", " #T_dbaab18a_28d7_11e6_a50b_0242ac110002row1_col1 {\n", " \n", " background-color: pink;\n", " \n", " }\n", " \n", " </style>\n", "\n", " <table id=\"T_dbaab18a_28d7_11e6_a50b_0242ac110002\" None>\n", " \n", "\n", " <thead>\n", " \n", " <tr>\n", " \n", " <th class=\"blank\">\n", " \n", " <th class=\"col_heading level0 col0\">e\n", " \n", " <th class=\"col_heading level0 col1\">f\n", " \n", " </tr>\n", " \n", " </thead>\n", " <tbody>\n", " \n", " <tr>\n", " \n", " <th id=\"T_dbaab18a_28d7_11e6_a50b_0242ac110002\" class=\"row_heading level1 row0\">\n", " \n", " 0\n", " \n", " \n", " <td id=\"T_dbaab18a_28d7_11e6_a50b_0242ac110002row0_col0\" class=\"data row0 col0\">\n", " \n", " 9\n", " \n", " \n", " <td id=\"T_dbaab18a_28d7_11e6_a50b_0242ac110002row0_col1\" class=\"data row0 col1\">\n", " \n", " 10\n", " \n", " \n", " </tr>\n", " \n", " <tr>\n", " \n", " <th id=\"T_dbaab18a_28d7_11e6_a50b_0242ac110002\" class=\"row_heading level1 row1\">\n", " \n", " 1\n", " \n", " \n", " <td id=\"T_dbaab18a_28d7_11e6_a50b_0242ac110002row1_col0\" class=\"data row1 col0\">\n", " \n", " 11\n", " \n", " \n", " <td id=\"T_dbaab18a_28d7_11e6_a50b_0242ac110002row1_col1\" class=\"data row1 col1\">\n", " \n", " 12\n", " \n", " \n", " </tr>\n", " \n", " </tbody>\n", " </table>\n", " " ], "text/plain": [ "<pandas.core.style.Styler at 0x7f4636e57278>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%%html\n", "<template is=\"urth-core-bind\">\n", " <template is=\"dom-if\" if=\"{{sel1}}\" auto>\n", " <urth-core-function ref=\"print_df\" arg-idx=\"[[sel1.0]]\" result=\"{{df_out}}\" auto>\n", " </urth-core-function>\n", " </template>\n", "</template>" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "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": "3.5.1" } }, "nbformat": 4, "nbformat_minor": 0 }