frequency-counts.md

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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 perform frequency counts using Python. statistics false python base Frequency Counts 2 example_index python/frequency-counts/ /images/static-image

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Imports

The tutorial below imports numpy, pandas, and scipy

importplotly.plotlyaspyimportplotly.graph_objsasgofromplotly.toolsimportFigureFactoryasFFimportnumpyasnpimportpandasaspdimportscipy

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')

fromIPython.displayimportdisplay, HTMLdisplay(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">')) ! pipinstallgit+https://github.com/plotly/publisher.git--upgradeimportpublisherpublisher.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')