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DOC: add header formatting to stat demos
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‎examples/statistics/boxplot_color_demo.py

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"""Box plots with custom fill colors.
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"""
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=================================
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Box plots with custom fill colors
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=================================
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This plot illustrates how to create two types of box plots
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(rectangular and notched), and how to fill them with custom

‎examples/statistics/boxplot_demo.py

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"""Demo of artist customization in box plots.
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"""
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=========================================
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Demo of artist customization in box plots
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=========================================
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This example demonstrates how to use the various kwargs
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to fully customize box plots. The first figure demostrates

‎examples/statistics/boxplot_vs_violin_demo.py

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"""Box plot - violin plot comparison.
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"""
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===================================
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Box plot vs. violin plot comparison
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===================================
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Note that although violin plots are closely related to Tukey's (1977) box
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plots, they add useful information such as the distribution of the sample

‎examples/statistics/bxp_demo.py

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"""Demo of the boxplot drawer function
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"""
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===================================
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Demo of the boxplot drawer function
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===================================
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This example demonstrates how to pass pre-computed box plot
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statistics to the box plot drawer. The first figure demostrates

‎examples/statistics/customized_violin_demo.py

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"""Demo of violin plot customization.
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"""
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=================================
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Demo of violin plot customization
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This example demonstrates how to fully customize violin plots.
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The first plot shows the default style by providing only

‎examples/statistics/errorbar_demo.py

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"""Demo of the errorbar function.
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"""
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=============================
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Demo of the errorbar function
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=============================
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This exhibits the most basic use of of the error bar method.
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In this case, constant values are provided for both the error

‎examples/statistics/errorbar_demo_features.py

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"""Demo of the different ways of specifying error bars.
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"""
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===================================================
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Demo of the different ways of specifying error bars
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===================================================
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Errors can be specified as a constant value (as shown in
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`errorbar_demo.py`), or as demonstrated in this example, they can be

‎examples/statistics/errorbar_limits.py

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"""Demo of how to include upper and lower limits in error bars
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"""
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===========================================================
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Demo of how to include upper and lower limits in error bars
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===========================================================
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In matplotlib, errors bars can have "limits". Applying limits to the
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error bars essentially makes the error unidirectional. Because of that,

‎examples/statistics/errorbars_and_boxes.py

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"""Demo on creating boxes from error bars using PatchCollection
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"""
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============================================================
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Demo on creating boxes from error bars using PatchCollection
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============================================================
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In this example, we snazz up a pretty standard error bar plot by adding
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a rectangle patch defined by the limits of the bars in both the x- and

‎examples/statistics/histogram_demo_cumulative.py

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"""Demo of using histograms to plot a cumulative distribution.
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"""
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==========================================================
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Demo of using histograms to plot a cumulative distribution
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==========================================================
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This shows how to plot a cumulative, normalized histogram as a
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step function as means of visualization the empirical cumulative

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