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jupyter
jupytext kernelspec plotly
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extension format_name format_version jupytext_version
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description display_as has_thumbnail language layout name order page_type permalink thumbnail
Learn how to perform frequency counts using Python.
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python
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Frequency Counts
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python/frequency-counts/
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New to Plotly?

Plotly's Python library is free and open source! Get started by downloading 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

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

Make the Data

We are generating a 1D dataset from a Weibull Distribution which has the distribution

$$ \begin{align*} X = \log(U)^{\frac{1}{a}} \end{align*} $$

where $U$ is drawn from the Uniform Distribution.

x=np.random.weibull(1.25, size=1000)
print(x[:10])

Histogram

By using a histogram, we can properly divide a 1D dataset into bins with a particular size or width, so as to form a discrete probability distribution

trace = go.Histogram(x=x, xbins=dict(start=np.min(x), size=0.25, end=np.max(x)),
                   marker=dict(color='rgb(0, 0, 100)'))

layout = go.Layout(
    title="Histogram Frequency Counts"
)

fig = go.Figure(data=go.Data([trace]), layout=layout)
py.iplot(fig, filename='histogram-freq-counts')

Larger Bins

We can experiment with our bin size and the histogram by grouping the data into larger intervals

trace = go.Histogram(x=x, xbins=dict(start=np.min(x), size=0.75, end=np.max(x)),
                   marker=dict(color='rgb(0, 0, 100)'))

layout = go.Layout(
    title="Histogram Frequency Counts"
)

fig = go.Figure(data=go.Data([trace]), layout=layout)
py.iplot(fig, filename='histogram-freq-counts-larger-bins')
from IPython.display import display, HTML

display(HTML('<link href="//fonts.googleapis.com/css?family=Open+Sans:600,400,300,200|Inconsolata|Ubuntu+Mono:400,700" rel="stylesheet" type="text/css" />'))
display(HTML('<link rel="stylesheet" type="text/css" href="http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css">'))

! pip install git+https://github.com/plotly/publisher.git --upgrade
import publisher
publisher.publish(
    'python-Frequency-Counts.ipynb', 'python/frequency-counts/', 'Frequency Counts | plotly',
    'Learn how to perform frequency counts using Python.',
    title='Frequency Counts in Python. | plotly',
    name='Frequency Counts',
    language='python',
    page_type='example_index', has_thumbnail='false', display_as='statistics', order=2,
    ipynb= '~notebook_demo/111')