{
"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 dowloading 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!"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Imports\n",
"The tutorial below imports [NumPy](http://www.numpy.org/), [Pandas](https://plotly.com/pandas/intro-to-pandas-tutorial/), and [SciPy](https://www.scipy.org/)."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import plotly.plotly as py\n",
"import plotly.graph_objs as go\n",
"from plotly.tools import FigureFactory as FF\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"import scipy"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Import Data"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"For this example we will use some real data of wind speeds sampled every 10 minutes."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wind_data = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/wind_speed_laurel_nebraska.csv')\n",
"df = wind_data[0:10]\n",
"\n",
"table = FF.create_table(df)\n",
"py.iplot(table, filename='wind-data-sample')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Histogram"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We will be producing a `histogram` with the \"10 Min Std Dev\" column of our data. For more info on the histogram charts, you can checkout the [documentation page](https://plotly.com/python/histograms/)."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data = [\n",
" go.Histogram(\n",
" x=wind_data['10 Min Std Dev'],\n",
" histnorm='probability'\n",
" )\n",
"]\n",
"py.iplot(data, filename='wind-data-histogram')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Box Plots"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We will be producing a `box plot` with the \"10 Min Std Dev\" column of our data again. For more info on the histogram charts, you can checkout the [documentation page](https://plotly.com/python/box-plots/)."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data = [\n",
" go.Box(\n",
" y=wind_data['10 Min Std Dev'],\n",
" )\n",
"]\n",
"\n",
"py.iplot(data, filename='wind-data-box-plot')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Scatterplot Matrix"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We will be producing a `scatterplot matrix` with all the columns of our data. For more info on the histogram charts, you can checkout the [documentation page](https://plotly.com/python/scatterplot-matrix/)."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"This is the format of your plot grid:\n",
"[ (1,1) x1,y1 ] [ (1,2) x2,y2 ] [ (1,3) x3,y3 ]\n",
"[ (2,1) x4,y4 ] [ (2,2) x5,y5 ] [ (2,3) x6,y6 ]\n",
"[ (3,1) x7,y7 ] [ (3,2) x8,y8 ] [ (3,3) x9,y9 ]\n",
"\n"
]
},
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fig = FF.create_scatterplotmatrix(wind_data,\n",
" height=1000,\n",
" width=1000,\n",
" title='Wind Data - Scatterplot Matrix')\n",
"py.iplot(fig, filename='wind-data-scatterplot-matrix')"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"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 /var/folders/ld/6cl3s_l50wd40tdjq2b03jxh0000gp/T/pip-T9GlYL-build\n",
"Installing collected packages: publisher\n",
" Found existing installation: publisher 0.10\n",
" Uninstalling publisher-0.10:\n",
" Successfully uninstalled publisher-0.10\n",
" Running setup.py install for publisher ... \u001b[?25l-\b \b\\\b \bdone\n",
"\u001b[?25hSuccessfully installed publisher-0.10\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/brandendunbar/Desktop/test/venv/lib/python2.7/site-packages/IPython/nbconvert.py:13: ShimWarning: The `IPython.nbconvert` package has been deprecated. You should import from nbconvert instead.\n",
" \"You should import from nbconvert instead.\", ShimWarning)\n",
"/Users/brandendunbar/Desktop/test/venv/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",
" 'python-Statistics-Charts.ipynb', 'python/statistics-charts/', 'Statistics Charts | plotly',\n",
" 'Learn how to plot statistical data with various charts using Python.',\n",
" title='Statistics Charts in Python. | plotly',\n",
" name='Statistics Charts',\n",
" language='python',\n",
" page_type='example_index', has_thumbnail='false', display_as='statistics', order=5,\n",
" ipynb= '~notebook_demo/116')"
]
},
{
"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": "2.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 0
}