{ "cells": [ { "cell_type": "markdown", "source": [ "# Multi Cruve plot\n", "Depending on the user needs, more information may be conveyed by displaying a graph with multiple curves. This can be done with py50 using the multi_curve_plot() method. \n", "\n", "First, import the package and convert the DataFrame instantiate into the PlotCurve class. " ], "metadata": { "collapsed": false }, "id": "b458819069d1fe3f" }, { "cell_type": "code", "id": "initial_id", "metadata": { "collapsed": true, "ExecuteTime": { "end_time": "2026-05-21T04:11:43.776507Z", "start_time": "2026-05-21T04:11:42.834859Z" } }, "source": [ "import pandas as pd\n", "from py50 import PlotCurve, CBMARKERS, CBPALETTE" ], "outputs": [], "execution_count": 1 }, { "cell_type": "code", "source": [ "df = pd.read_csv('../dataset/multiple_example.csv')\n", "data = PlotCurve(df)\n", "data.show()" ], "metadata": { "collapsed": false, "ExecuteTime": { "end_time": "2026-05-21T04:11:43.805052Z", "start_time": "2026-05-21T04:11:43.778642Z" } }, "id": "f1dc86f48023ca86", "outputs": [ { "data": { "text/plain": [ " Compound Name Compound Conc % Inhibition 1 % Inhibition 2 \\\n", "0 Drug 1 100000.0 90 94 \n", "1 Drug 1 33300.0 97 89 \n", "2 Drug 1 11100.0 86 89 \n", "3 Drug 1 3700.0 81 88 \n", "4 Drug 1 1240.0 63 70 \n", "\n", " % Inhibition Avg \n", "0 92.0 \n", "1 93.0 \n", "2 87.5 \n", "3 84.5 \n", "4 66.5 " ], "text/html": [ "
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