{ "cells": [ { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md \n" } }, "source": [ "## Examples - plot_scatters()" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "pycharm": { "is_executing": false } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(1342, 4)\n" ] } ], "source": [ "from am4894pd.utils import df_dummy_ts # used to generate some dummy data\n", "from am4894plots.plots import plot_scatters\n", "\n", "# generate some dummy time series data\n", "df = df_dummy_ts(n_cols=4, freq='1min')\n", "print(df.shape)\n", "#display(df.head())" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "pycharm": { "name": "#%%\n" }, "scrolled": false }, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_scatters(df, renderer='notebook', h=400, w=600)" ] } ], "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": "3.8.1" }, "pycharm": { "stem_cell": { "cell_type": "raw", "metadata": { "collapsed": false }, "source": [] } } }, "nbformat": 4, "nbformat_minor": 1 }