{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "#### New to Plotly?\n", "Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by downloading the client and [reading the primer](https://plot.ly/python/getting-started/).\n", "
You can set up Plotly to work in [online](https://plot.ly/python/getting-started/#initialization-for-online-plotting) or [offline](https://plot.ly/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plot.ly/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!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 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": [ "'3.6.1'" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import plotly\n", "plotly.__version__" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### U.S. Airports Map" ] }, { "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", "import pandas as pd\n", "\n", "df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_february_us_airport_traffic.csv')\n", "df.head()\n", "\n", "df['text'] = df['airport'] + '' + df['city'] + ', ' + df['state'] + '' + 'Arrivals: ' + df['cnt'].astype(str)\n", "\n", "scl = [ [0,\"rgb(5, 10, 172)\"],[0.35,\"rgb(40, 60, 190)\"],[0.5,\"rgb(70, 100, 245)\"],\\\n", " [0.6,\"rgb(90, 120, 245)\"],[0.7,\"rgb(106, 137, 247)\"],[1,\"rgb(220, 220, 220)\"] ]\n", "\n", "data = [ go.Scattergeo(\n", " locationmode = 'USA-states',\n", " lon = df['long'],\n", " lat = df['lat'],\n", " text = df['text'],\n", " mode = 'markers',\n", " marker = dict( \n", " size = 8, \n", " opacity = 0.8,\n", " reversescale = True,\n", " autocolorscale = False,\n", " symbol = 'square',\n", " line = dict(\n", " width=1,\n", " color='rgba(102, 102, 102)'\n", " ),\n", " colorscale = scl,\n", " cmin = 0,\n", " color = df['cnt'],\n", " cmax = df['cnt'].max(),\n", " colorbar=dict(\n", " title=\"Incoming flights
February 2011\"\n", " )\n", " ))]\n", "\n", "layout = dict(\n", " title = 'Most trafficked US airports
(Hover for airport names)', \n", " geo = dict(\n", " scope='usa',\n", " projection=dict( type='albers usa' ),\n", " showland = True,\n", " landcolor = \"rgb(250, 250, 250)\",\n", " subunitcolor = \"rgb(217, 217, 217)\",\n", " countrycolor = \"rgb(217, 217, 217)\",\n", " countrywidth = 0.5,\n", " subunitwidth = 0.5 \n", " ),\n", " )\n", "\n", "fig = go.Figure(data=data, layout=layout )\n", "py.iplot(fig, filename='d3-airports' )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### North American Precipitation Map" ] }, { "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", "import pandas as pd\n", "\n", "df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2015_06_30_precipitation.csv')\n", "\n", "scl = [0,\"rgb(150,0,90)\"],[0.125,\"rgb(0, 0, 200)\"],[0.25,\"rgb(0, 25, 255)\"],\\\n", "[0.375,\"rgb(0, 152, 255)\"],[0.5,\"rgb(44, 255, 150)\"],[0.625,\"rgb(151, 255, 0)\"],\\\n", "[0.75,\"rgb(255, 234, 0)\"],[0.875,\"rgb(255, 111, 0)\"],[1,\"rgb(255, 0, 0)\"]\n", "\n", "data = [go.Scattergeo(\n", " lat = df['Lat'],\n", " lon = df['Lon'],\n", " text = df['Globvalue'].astype(str) + ' inches',\n", " marker = dict(\n", " color = df['Globvalue'],\n", " colorscale = scl,\n", " reversescale = True,\n", " opacity = 0.7,\n", " size = 2, \n", " colorbar = dict(\n", " thickness = 10,\n", " titleside = \"right\",\n", " outlinecolor = \"rgba(68, 68, 68, 0)\",\n", " ticks = \"outside\",\n", " ticklen = 3,\n", " showticksuffix = \"last\",\n", " ticksuffix = \" inches\",\n", " dtick = 0.1\n", " ) \n", " )\n", ")]\n", "\n", "layout = dict(\n", " geo = dict(\n", " scope = 'north america',\n", " showland = True,\n", " landcolor = \"rgb(212, 212, 212)\",\n", " subunitcolor = \"rgb(255, 255, 255)\",\n", " countrycolor = \"rgb(255, 255, 255)\",\n", " showlakes = True,\n", " lakecolor = \"rgb(255, 255, 255)\",\n", " showsubunits = True,\n", " showcountries = True,\n", " resolution = 50,\n", " projection = dict(\n", " type = 'conic conformal',\n", " rotation = dict(\n", " lon = -100\n", " )\n", " ),\n", " lonaxis = dict(\n", " showgrid = True,\n", " gridwidth = 0.5,\n", " range= [ -140.0, -55.0 ],\n", " dtick = 5\n", " ),\n", " lataxis = dict (\n", " showgrid = True,\n", " gridwidth = 0.5,\n", " range= [ 20.0, 60.0 ],\n", " dtick = 5\n", " )\n", " ),\n", " title = 'US Precipitation 06-30-2015
Source: NOAA',\n", ")\n", "\n", "fig = go.Figure(data=data, layout=layout )\n", "py.iplot(fig, filename='precipitation')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Reference\n", "See https://plot.ly/python/reference/#scattergeo and https://plot.ly/python/reference/#layout-geo for more information and chart attribute options!" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "scrolled": true }, "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 c:\\users\\priyat~1\\appdata\\local\\temp\\pip-req-build-s9h9i_vt\n", "Building wheels for collected packages: publisher\n", " Running setup.py bdist_wheel for publisher: started\n", " Running setup.py bdist_wheel for publisher: finished with status 'done'\n", " Stored in directory: C:\\Users\\PRIYAT~1\\AppData\\Local\\Temp\\pip-ephem-wheel-cache-6ol6d604\\wheels\\99\\3e\\a0\\fbd22ba24cca72bdbaba53dbc23c1768755fb17b3af0f33966\n", "Successfully built publisher\n", "Installing collected packages: publisher\n", " Found existing installation: publisher 0.13\n", " Uninstalling publisher-0.13:\n", " Successfully uninstalled publisher-0.13\n", "Successfully installed publisher-0.13\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Anaconda\\Anaconda3\\lib\\site-packages\\IPython\\nbconvert.py:13: ShimWarning:\n", "\n", "The `IPython.nbconvert` package has been deprecated since IPython 4.0. You should import from nbconvert instead.\n", "\n", "C:\\Anaconda\\Anaconda3\\lib\\site-packages\\publisher\\publisher.py:53: UserWarning:\n", "\n", "Did you \"Save\" this notebook before running this command? Remember to save, always save.\n", "\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", " 'scatter-plot-on-map.ipynb', 'python/scatter-plots-on-maps/', 'Python Scatter Plots on Maps | Examples | Plotly',\n", " 'How to make scatter plots on maps in Python. Scatter plots on maps highlight geographic areas and can be colored by value.',\n", " title = 'Python Scatter Plots on Maps | Plotly',\n", " name = 'Scatter Plots on Maps',\n", " has_thumbnail='true', thumbnail='thumbnail/scatter-plot-on-maps.jpg', \n", " language='python',\n", " display_as='maps', order=2,\n", " ipynb= '~notebook_demo/57') " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "anaconda-cloud": {}, "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": "3.7.1" } }, "nbformat": 4, "nbformat_minor": 1 }