jupyter

jupytext kernelspec plotly notebook_metadata_filter text_representation all extension format_name format_version jupytext_version .md markdown 1.1 1.1.1 display_name language name Python 2 python python2 description display_as has_thumbnail language layout name order page_type permalink thumbnail Learn how to plot statistical data with various charts using Python. statistics false python base Statistics Charts 5 example_index python/statistics-charts/ /images/static-image

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Imports

The tutorial below imports NumPy, Pandas, and SciPy.

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.

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')

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.

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

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.

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

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

Scatterplot Matrix (SPLOM)

We will be producing a scatterplot matrix chart, also known as a SPLOM chart, with all the columns of our data. For more info on SPLOM traces, you can checkout the documentation page.

fig = go.Figure(data=go.Splom(
    dimensions=[
        dict(label=col, values=wind_data[col]) for col in wind_data.columns
    ]
))

fig.update_layout(
    title='Wind Data - Scatterplot Matrix',
    height=1000,
    width=1000,
)
py.iplot(fig, filename='wind-data-scatterplot-matrix')

from IPython.display import display, HTML

display(HTML('<link href="proxy.php?url=https%3A%2F%2Ffonts.googleapis.com%2Fcss%3Ffamily%3DOpen%2BSans%3A600%2C400%2C300%2C200%7CInconsolata%7CUbuntu%2BMono%3A400%2C700" rel="stylesheet" type="text/css" />'))
display(HTML('<link rel="stylesheet" type="text/css" href="proxy.php?url=http%3A%2F%2Fhelp.plot.ly%2Fdocumentation%2Fall_static%2Fcss%2Fipython-notebook-custom.css">'))

! pip install git+https://github.com/plotly/publisher.git --upgrade
import publisher
publisher.publish(
    'python-Statistics-Charts.ipynb', 'python/statistics-charts/', 'Statistics Charts | plotly',
    'Learn how to plot statistical data with various charts using Python.',
    title='Statistics Charts in Python. | plotly',
    name='Statistics Charts',
    language='python',
    page_type='example_index', has_thumbnail='false', display_as='statistics', order=5,
    ipynb= '~notebook_demo/116')