# Statistics Charts in Python/v3

Learn how to plot statistical data with various charts using Python.

See our Version 4 Migration Guide for information about how to upgrade.

#### New to Plotly?¶

Plotly's Python library is free and open source! Get started by dowloading the client and reading the primer.
You can set up Plotly to work in online or offline mode, or in jupyter notebooks.
We also have a quick-reference cheatsheet (new!) to help you get started!

#### Imports¶

The tutorial below imports NumPy, Pandas, and SciPy.

In [1]:
import plotly.plotly as py
import plotly.graph_objs as go
from plotly.tools import FigureFactory as FF

import numpy as np
import pandas as pd
import scipy


#### Import Data¶

For this example we will use some real data of wind speeds sampled every 10 minutes.

In [2]:
wind_data = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/wind_speed_laurel_nebraska.csv')
df = wind_data[0:10]

table = FF.create_table(df)
py.iplot(table, filename='wind-data-sample')

Out[2]:

#### Histogram¶

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.

In [3]:
data = [
go.Histogram(
x=wind_data['10 Min Std Dev'],
histnorm='probability'
)
]
py.iplot(data, filename='wind-data-histogram')

Out[3]:

#### Box Plots¶

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.

In [4]:
data = [
go.Box(
y=wind_data['10 Min Std Dev'],
)
]

py.iplot(data, filename='wind-data-box-plot')

Out[4]:

#### Scatterplot Matrix¶

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.

In [5]:
fig = FF.create_scatterplotmatrix(wind_data,
height=1000,
width=1000,
title='Wind Data - Scatterplot Matrix')
py.iplot(fig, filename='wind-data-scatterplot-matrix')

This is the format of your plot grid:
[ (1,1) x1,y1 ]  [ (1,2) x2,y2 ]  [ (1,3) x3,y3 ]
[ (2,1) x4,y4 ]  [ (2,2) x5,y5 ]  [ (2,3) x6,y6 ]
[ (3,1) x7,y7 ]  [ (3,2) x8,y8 ]  [ (3,3) x9,y9 ]


Out[5]: