{ "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": [ "'3.2.0'" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import plotly\n", "plotly.__version__" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Simple Bubble 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", "trace0 = go.Scatter(\n", " x=[1, 2, 3, 4],\n", " y=[10, 11, 12, 13],\n", " mode='markers',\n", " marker=dict(\n", " size=[40, 60, 80, 100],\n", " )\n", ")\n", "\n", "data = [trace0]\n", "py.iplot(data, filename='bubblechart-size')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Setting Marker Size and Color" ] }, { "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", "trace0 = go.Scatter(\n", " x=[1, 2, 3, 4],\n", " y=[10, 11, 12, 13],\n", " mode='markers',\n", " marker=dict(\n", " color=['rgb(93, 164, 214)', 'rgb(255, 144, 14)',\n", " 'rgb(44, 160, 101)', 'rgb(255, 65, 54)'],\n", " opacity=[1, 0.8, 0.6, 0.4],\n", " size=[40, 60, 80, 100],\n", " )\n", ")\n", "\n", "data = [trace0]\n", "py.iplot(data, filename='bubblechart-color')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Scaling the Size of Bubble Charts\n", "To scale the bubble size, use the attribute `sizeref`. We recommend using the following formula to calculate a `sizeref` value:
\n", "`sizeref = 2. * max(array of size values) / (desired maximum marker size ** 2)`
\n", "Note that setting 'sizeref' to a value greater than 1, decreases the rendered marker sizes, while setting 'sizeref' to less than 1, increases the rendered marker sizes. See https://plotly.com/python/reference/#scatter-marker-sizeref for more information.\n", "Additionally, we recommend setting the sizemode attribute: https://plotly.com/python/reference/#scatter-marker-sizemode to area." ] }, { "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", "size = [20, 40, 60, 80, 100, 80, 60, 40, 20, 40]\n", "trace0 = go.Scatter(\n", " x=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],\n", " y=[11, 12, 10, 11, 12, 11, 12, 13, 12, 11],\n", " mode='markers',\n", " marker=dict(\n", " size=size,\n", " sizemode='area',\n", " sizeref=2.*max(size)/(40.**2),\n", " sizemin=4\n", " )\n", ")\n", "\n", "data = [trace0]\n", "py.iplot(data, filename='bubblechart-size-ref')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Hover Text with Bubble Charts" ] }, { "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", "trace0 = go.Scatter(\n", " x=[1, 2, 3, 4],\n", " y=[10, 11, 12, 13],\n", " text=['A
size: 40', 'B
size: 60', 'C
size: 80', 'D
size: 100'],\n", " mode='markers',\n", " marker=dict(\n", " color=['rgb(93, 164, 214)', 'rgb(255, 144, 14)', 'rgb(44, 160, 101)', 'rgb(255, 65, 54)'],\n", " size=[40, 60, 80, 100],\n", " )\n", ")\n", "\n", "data = [trace0]\n", "py.iplot(data, filename='bubblechart-text')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Bubble Charts with Colorscale" ] }, { "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", "data = [\n", " {\n", " 'x': [1, 3.2, 5.4, 7.6, 9.8, 12.5],\n", " 'y': [1, 3.2, 5.4, 7.6, 9.8, 12.5],\n", " 'mode': 'markers',\n", " 'marker': {\n", " 'color': [120, 125, 130, 135, 140, 145],\n", " 'size': [15, 30, 55, 70, 90, 110],\n", " 'showscale': True\n", " }\n", " }\n", "]\n", "\n", "py.iplot(data, filename='scatter-colorscale')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Categorical Bubble Charts" ] }, { "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", "import pandas as pd\n", "import math\n", "\n", "data = pd.read_csv(\"https://raw.githubusercontent.com/plotly/datasets/master/gapminderDataFiveYear.csv\")\n", "df_2007 = data[data['year']==2007]\n", "df_2007 = df_2007.sort_values(['continent', 'country'])\n", "slope = 2.666051223553066e-05\n", "hover_text = []\n", "bubble_size = []\n", "\n", "for index, row in df_2007.iterrows():\n", " hover_text.append(('Country: {country}
'+\n", " 'Life Expectancy: {lifeExp}
'+\n", " 'GDP per capita: {gdp}
'+\n", " 'Population: {pop}
'+\n", " 'Year: {year}').format(country=row['country'],\n", " lifeExp=row['lifeExp'],\n", " gdp=row['gdpPercap'],\n", " pop=row['pop'],\n", " year=row['year']))\n", " bubble_size.append(math.sqrt(row['pop']*slope))\n", "\n", "df_2007['text'] = hover_text\n", "df_2007['size'] = bubble_size\n", "sizeref = 2.*max(df_2007['size'])/(100**2)\n", "\n", "trace0 = go.Scatter(\n", " x=df_2007['gdpPercap'][df_2007['continent'] == 'Africa'],\n", " y=df_2007['lifeExp'][df_2007['continent'] == 'Africa'],\n", " mode='markers',\n", " name='Africa',\n", " text=df_2007['text'][df_2007['continent'] == 'Africa'],\n", " marker=dict(\n", " symbol='circle',\n", " sizemode='area',\n", " sizeref=sizeref,\n", " size=df_2007['size'][df_2007['continent'] == 'Africa'],\n", " line=dict(\n", " width=2\n", " ),\n", " )\n", ")\n", "trace1 = go.Scatter(\n", " x=df_2007['gdpPercap'][df_2007['continent'] == 'Americas'],\n", " y=df_2007['lifeExp'][df_2007['continent'] == 'Americas'],\n", " mode='markers',\n", " name='Americas',\n", " text=df_2007['text'][df_2007['continent'] == 'Americas'],\n", " marker=dict(\n", " sizemode='area',\n", " sizeref=sizeref,\n", " size=df_2007['size'][df_2007['continent'] == 'Americas'],\n", " line=dict(\n", " width=2\n", " ),\n", " )\n", ")\n", "trace2 = go.Scatter(\n", " x=df_2007['gdpPercap'][df_2007['continent'] == 'Asia'],\n", " y=df_2007['lifeExp'][df_2007['continent'] == 'Asia'],\n", " mode='markers',\n", " name='Asia',\n", " text=df_2007['text'][df_2007['continent'] == 'Asia'],\n", " marker=dict(\n", " sizemode='area',\n", " sizeref=sizeref,\n", " size=df_2007['size'][df_2007['continent'] == 'Asia'],\n", " line=dict(\n", " width=2\n", " ),\n", " )\n", ")\n", "trace3 = go.Scatter(\n", " x=df_2007['gdpPercap'][df_2007['continent'] == 'Europe'],\n", " y=df_2007['lifeExp'][df_2007['continent'] == 'Europe'],\n", " mode='markers',\n", " name='Europe',\n", " text=df_2007['text'][df_2007['continent'] == 'Europe'],\n", " marker=dict(\n", " sizemode='area',\n", " sizeref=sizeref,\n", " size=df_2007['size'][df_2007['continent'] == 'Europe'],\n", " line=dict(\n", " width=2\n", " ),\n", " )\n", ")\n", "trace4 = go.Scatter(\n", " x=df_2007['gdpPercap'][df_2007['continent'] == 'Oceania'],\n", " y=df_2007['lifeExp'][df_2007['continent'] == 'Oceania'],\n", " mode='markers',\n", " name='Oceania',\n", " text=df_2007['text'][df_2007['continent'] == 'Oceania'],\n", " marker=dict(\n", " sizemode='area',\n", " sizeref=sizeref,\n", " size=df_2007['size'][df_2007['continent'] == 'Oceania'],\n", " line=dict(\n", " width=2\n", " ),\n", " )\n", ")\n", "\n", "data = [trace0, trace1, trace2, trace3, trace4]\n", "layout = go.Layout(\n", " title='Life Expectancy v. Per Capita GDP, 2007',\n", " xaxis=dict(\n", " title='GDP per capita (2000 dollars)',\n", " gridcolor='rgb(255, 255, 255)',\n", " range=[2.003297660701705, 5.191505530708712],\n", " type='log',\n", " zerolinewidth=1,\n", " ticklen=5,\n", " gridwidth=2,\n", " ),\n", " yaxis=dict(\n", " title='Life Expectancy (years)',\n", " gridcolor='rgb(255, 255, 255)',\n", " range=[36.12621671352166, 91.72921793264332],\n", " zerolinewidth=1,\n", " ticklen=5,\n", " gridwidth=2,\n", " ),\n", " paper_bgcolor='rgb(243, 243, 243)',\n", " plot_bgcolor='rgb(243, 243, 243)',\n", ")\n", "\n", "fig = go.Figure(data=data, layout=layout)\n", "py.iplot(fig, filename='life-expectancy-per-GDP-2007')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Reference\n", "See https://plotly.com/python/reference/#scatter for more information and chart attribute options!" ] }, { "cell_type": "code", "execution_count": 1, "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 /private/var/folders/tc/bs9g6vrd36q74m5t8h9cgphh0000gn/T/pip-req-build-IqekGg\n", "Building wheels for collected packages: publisher\n", " Running setup.py bdist_wheel for publisher ... \u001b[?25ldone\n", "\u001b[?25h Stored in directory: /private/var/folders/tc/bs9g6vrd36q74m5t8h9cgphh0000gn/T/pip-ephem-wheel-cache-nsvXuo/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" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/IPython/nbconvert.py:13: ShimWarning: The `IPython.nbconvert` package has been deprecated since IPython 4.0. You should import from nbconvert instead.\n", " \"You should import from nbconvert instead.\", ShimWarning)\n", "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/publisher/publisher.py:53: UserWarning: Did you \"Save\" this notebook before running this command? Remember to save, always save.\n", " warnings.warn('Did you \"Save\" this notebook before running this command? '\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", " 'bubble.ipynb', 'python/bubble-charts/', 'Python Bubble Charts | plotly',\n", " 'How to make bubble charts in Python with Plotly.',\n", " title = 'Bubble Charts | plotly',\n", " name = 'Bubble Charts', language='python',\n", " has_thumbnail='true', thumbnail='thumbnail/bubble.jpg',\n", " display_as='basic', order=3,\n", " ipynb= '~notebook_demo/1/new-to-plotly-plotlys-python-library-i',\n", " redirect_from='python/bubble-charts-tutorial/',\n", ")" ] }, { "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": "2.7.12" } }, "nbformat": 4, "nbformat_minor": 1 }