{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "#### New to Plotly?\n", "Plotly's Python library is free and open source! [Get started](https://plotly.com/python/getting-started/) by downloading the client and [reading the primer](https://plotly.com/python/getting-started/).\n", "
You can set up Plotly to work in [online](https://plotly.com/python/getting-started/#initialization-for-online-plotting) or [offline](https://plotly.com/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plotly.com/python/getting-started/#start-plotting-online).\n", "
We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!\n", "#### Version Check\n", "Plotly's python package is updated frequently. Run `pip install plotly --upgrade` to use the latest version. " ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'3.1.1'" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import plotly\n", "plotly.__version__" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Basic Overlaid Area Chart" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import plotly.plotly as py\n", "import plotly.graph_objs as go\n", "\n", "trace1 = go.Scatter(\n", " x=[1, 2, 3, 4],\n", " y=[0, 2, 3, 5],\n", " fill='tozeroy'\n", ")\n", "trace2 = go.Scatter(\n", " x=[1, 2, 3, 4],\n", " y=[3, 5, 1, 7],\n", " fill='tonexty'\n", ")\n", "\n", "data = [trace1, trace2]\n", "py.iplot(data, filename='basic-area')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Overlaid Area Chart Without Boundary Lines" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import plotly.plotly as py\n", "import plotly.graph_objs as go\n", "\n", "trace1 = go.Scatter(\n", " x=[1, 2, 3, 4],\n", " y=[0, 2, 3, 5],\n", " fill='tozeroy',\n", " mode= 'none'\n", ")\n", "trace2 = go.Scatter(\n", " x=[1, 2, 3, 4],\n", " y=[3, 5, 1, 7],\n", " fill='tonexty',\n", " mode= 'none'\n", ")\n", "\n", "data = [trace1, trace2]\n", "py.iplot(data, filename='basic-area-no-bound')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Interior Filling for Area Chart" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import plotly.plotly as py\n", "import plotly.graph_objs as go\n", "\n", "trace0 = go.Scatter(\n", " x=[1, 2, 3, 4],\n", " y=[3, 4, 8, 3],\n", " fill= None,\n", " mode='lines',\n", " line=dict(\n", " color='rgb(143, 19, 131)',\n", " )\n", ")\n", "trace1 = go.Scatter(\n", " x=[1, 2, 3, 4],\n", " y=[1, 6, 2, 6],\n", " fill='tonexty',\n", " mode='lines',\n", " line=dict(\n", " color='rgb(143, 19, 131)',\n", " )\n", ")\n", "\n", "data = [trace0, trace1]\n", "py.iplot(data, filename='filling-interior-area')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Stacked Area Chart" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import plotly.plotly as py\n", "import plotly.graph_objs as go\n", "\n", "# Add original data\n", "x=['Winter', 'Spring', 'Summer', 'Fall']\n", "\n", "trace0 = dict(\n", " x=x,\n", " y=[40, 60, 40, 10],\n", " hoverinfo='x+y',\n", " mode='lines',\n", " line=dict(width=0.5,\n", " color='rgb(131, 90, 241)'),\n", " stackgroup='one'\n", ")\n", "trace1 = dict(\n", " x=x,\n", " y=[20, 10, 10, 60],\n", " hoverinfo='x+y',\n", " mode='lines',\n", " line=dict(width=0.5,\n", " color='rgb(111, 231, 219)'),\n", " stackgroup='one'\n", ")\n", "trace2 = dict(\n", " x=x,\n", " y=[40, 30, 50, 30],\n", " hoverinfo='x+y',\n", " mode='lines',\n", " line=dict(width=0.5,\n", " color='rgb(184, 247, 212)'),\n", " stackgroup='one'\n", ")\n", "data = [trace0, trace1, trace2]\n", "\n", "fig = dict(data=data)\n", "py.iplot(fig, filename='stacked-area-plot-hover', validate=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Stacked Area Chart with Normalized Values" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import plotly.plotly as py\n", "import plotly.graph_objs as go\n", "\n", "trace0 = dict(\n", " x=['Winter', 'Spring', 'Summer', 'Fall'],\n", " y=['40', '20', '30', '40'],\n", " mode='lines',\n", " line=dict(width=0.5,\n", " color='rgb(184, 247, 212)'),\n", " stackgroup='one',\n", " groupnorm='percent'\n", ")\n", "trace1 = dict(\n", " x=['Winter', 'Spring', 'Summer', 'Fall'],\n", " y=['50', '70', '40', '60'],\n", " mode='lines',\n", " line=dict(width=0.5,\n", " color='rgb(111, 231, 219)'),\n", " stackgroup='one'\n", ")\n", "trace2 = dict(\n", " x=['Winter', 'Spring', 'Summer', 'Fall'],\n", " y=['70', '80', '60', '70'],\n", " mode='lines',\n", " line=dict(width=0.5,\n", " color='rgb(127, 166, 238)'),\n", " stackgroup='one'\n", ")\n", "trace3 = dict(\n", " x=['Winter', 'Spring', 'Summer', 'Fall'],\n", " y=['100', '100', '100', '100'],\n", " mode='lines',\n", " line=dict(width=0.5,\n", " color='rgb(131, 90, 241)'),\n", " stackgroup='one'\n", ")\n", "data = [trace0, trace1, trace2, trace3]\n", "layout = go.Layout(\n", " showlegend=True,\n", " xaxis=dict(\n", " type='category',\n", " ),\n", " yaxis=dict(\n", " type='linear',\n", " range=[1, 100],\n", " dtick=20,\n", " ticksuffix='%'\n", " )\n", ")\n", "fig = dict(data=data, layout=layout)\n", "py.iplot(fig, filename='stacked-area-plot-norm', validate=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Select Hover Points" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import plotly.plotly as py\n", "import plotly.graph_objs as go\n", "\n", "trace0 = go.Scatter(\n", " x=[0,0.5,1,1.5,2],\n", " y=[0,1,2,1,0],\n", " fill= 'toself',\n", " fillcolor = '#ab63fa',\n", " hoveron = 'points+fills',\n", " line = dict(\n", " color = '#ab63fa'\n", " ),\n", " text = \"Points + Fills\",\n", " hoverinfo = 'text'\n", ")\n", "\n", "trace1 = go.Scatter(\n", " x=[3,3.5,4,4.5,5],\n", " y=[0,1,2,1,0],\n", " fill='toself',\n", " fillcolor = '#e763fa',\n", " hoveron = 'points',\n", " line = dict(\n", " color = '#e763fa'\n", " ),\n", " text = \"Points only\",\n", " hoverinfo = 'text'\n", ")\n", "\n", "data = [trace0, trace1]\n", "\n", "layout = go.Layout(\n", " title = \"hover on points or fill\",\n", " xaxis = dict(\n", " range = [0,5.2]\n", " ),\n", " yaxis = dict(\n", " range = [0,3]\n", " )\n", ")\n", "\n", "fig = go.Figure(data=data,layout=layout)\n", "py.iplot(data, filename='select-hover-points')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Reference\n", "See https://plotly.com/python/reference/#scatter-line\n", "and https://plotly.com/python/reference/#scatter-fill \n", "for more information and attribute options!" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Collecting git+https://github.com/plotly/publisher.git\n", " Cloning https://github.com/plotly/publisher.git to /tmp/pip-req-build-ewWF0_\n", "Building wheels for collected packages: publisher\n", " Running setup.py bdist_wheel for publisher ... \u001b[?25ldone\n", "\u001b[?25h Stored in directory: /tmp/pip-ephem-wheel-cache-zaYWOc/wheels/99/3e/a0/fbd22ba24cca72bdbaba53dbc23c1768755fb17b3af0f33966\n", "Successfully built publisher\n", "Installing collected packages: publisher\n", " Found existing installation: publisher 0.11\n", " Uninstalling publisher-0.11:\n", " Successfully uninstalled publisher-0.11\n", "Successfully installed publisher-0.11\n", "\u001b[33mYou are using pip version 10.0.1, however version 18.0 is available.\n", "You should consider upgrading via the 'pip install --upgrade pip' command.\u001b[0m\n" ] } ], "source": [ "from IPython.display import display, HTML\n", "\n", "display(HTML(''))\n", "display(HTML(''))\n", "\n", "! pip install git+https://github.com/plotly/publisher.git --upgrade\n", "import publisher\n", "publisher.publish(\n", " 'area.ipynb', 'python/filled-area-plots/', 'Filled Area Plots | plotly',\n", " 'How to make filled area plots in Python with Plotly.',\n", " title = 'Filled Area Plots | plotly',\n", " name = 'Filled Area Plots',\n", " thumbnail='thumbnail/area.jpg', language='python',\n", " has_thumbnail='true', display_as='basic', order=3.5,\n", " ipynb='~notebook_demo/8')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.15rc1" } }, "nbformat": 4, "nbformat_minor": 2 }