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‎notebooks/distplot.md

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---
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jupyter:
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jupytext:
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notebook_metadata_filter: all
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text_representation:
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extension: .md
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format_name: markdown
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format_version: '1.1'
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jupytext_version: 1.1.1
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kernelspec:
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display_name: Python 2
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display_name: Python 3
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language: python
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name: python2
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name: python3
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language_info:
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codemirror_mode:
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name: ipython
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version: 3
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file_extension: .py
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mimetype: text/x-python
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name: python
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nbconvert_exporter: python
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pygments_lexer: ipython3
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version: 3.6.7
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plotly:
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description: How to make interactive Distplots in Python with Plotly.
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display_as: statistical
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title: Python Distplots | plotly
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---
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<!-- #region {"deletable": true, "editable": true} -->
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#### New to Plotly?
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Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by downloading the client and [reading the primer](https://plot.ly/python/getting-started/).
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<br>You can set up Plotly to work in [online](https://plot.ly/python/getting-started/#initialization-for-online-plotting) or [offline](https://plot.ly/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plot.ly/python/getting-started/#start-plotting-online).
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<br>We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!
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<!-- #endregion -->
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<!-- #region {"deletable": true, "editable": true} -->
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#### Version Check
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Note: Distplots are available in version <b>1.11.0+</b><br>
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Run `pip install plotly --upgrade` to update your Plotly version
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<!-- #endregion -->
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```python deletable=true editable=true
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import plotly
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plotly.__version__
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```
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The distplot figure factory displays a combination of statistical representations of numerical data, such as histogram, kernel density estimation or normal curve, and rug plot.
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<!-- #region {"deletable": true, "editable": true} -->
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#### Basic Distplot
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<!-- #endregion -->
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```python deletable=true editable=true
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import plotly.plotly as py
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import plotly.figure_factory as ff
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A histogram, a kde plot and a rug plot are displayed.
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```python
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import plotly.figure_factory as ff
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import numpy as np
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x = np.random.randn(1000)
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hist_data = [x]
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group_labels = ['distplot']
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group_labels = ['distplot'] # name of the dataset
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fig = ff.create_distplot(hist_data, group_labels)
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py.iplot(fig, filename='Basic Distplot')
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fig.show()
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```
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<!-- #region {"deletable": true, "editable": true} -->
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#### Plot Multiple Datasets
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<!-- #endregion -->
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```python deletable=true editable=true
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import plotly.plotly as py
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```python
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import plotly.figure_factory as ff
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import numpy as np
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# Add histogram data
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x1 = np.random.randn(200)-2
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x1 = np.random.randn(200) - 2
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x2 = np.random.randn(200)
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x3 = np.random.randn(200)+2
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x4 = np.random.randn(200)+4
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x3 = np.random.randn(200) + 2
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x4 = np.random.randn(200) + 4
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# Group data together
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hist_data = [x1, x2, x3, x4]
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# Create distplot with custom bin_size
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fig = ff.create_distplot(hist_data, group_labels, bin_size=.2)
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# Plot!
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py.iplot(fig, filename='Distplot with Multiple Datasets')
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fig.show()
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```
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<!-- #region {"deletable": true, "editable": true} -->
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#### Use Multiple Bin Sizes
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<!-- #endregion -->
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```python deletable=true editable=true
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import plotly.plotly as py
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import plotly.figure_factory as ff
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Different bin sizes are used for the different datasets with the `bin_size` argument.
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```python
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import plotly.figure_factory as ff
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import numpy as np
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# Add histogram data
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# Create distplot with custom bin_size
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fig = ff.create_distplot(hist_data, group_labels, bin_size=[.1, .25, .5, 1])
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# Plot!
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py.iplot(fig, filename='Distplot with Multiple Bin Sizes')
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fig.show()
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```
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<!-- #region {"deletable": true, "editable": true} -->
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#### Customize Rug Text, Colors & Title
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<!-- #endregion -->
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```python deletable=true editable=true
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import plotly.plotly as py
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```python
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import plotly.figure_factory as ff
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import numpy as np
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x1 = np.random.randn(26)
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x2 = np.random.randn(26) + .5
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hist_data = [x1, x2]
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group_labels = ['2014', '2015']
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rug_text_one = ['a', 'b', 'c', 'd', 'e',
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'f', 'g', 'h', 'i', 'j',
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'k', 'l', 'm', 'n', 'o',
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'p', 'q', 'r', 's', 't',
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rug_text_one = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j',
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'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't',
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'u', 'v', 'w', 'x', 'y', 'z']
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rug_text_two = ['aa', 'bb', 'cc', 'dd', 'ee',
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'ff', 'gg', 'hh', 'ii', 'jj',
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'kk', 'll', 'mm', 'nn', 'oo',
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'pp', 'qq', 'rr', 'ss', 'tt',
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rug_text_two = ['aa', 'bb', 'cc', 'dd', 'ee', 'ff', 'gg', 'hh', 'ii', 'jj',
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'kk', 'll', 'mm', 'nn', 'oo', 'pp', 'qq', 'rr', 'ss', 'tt',
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'uu', 'vv', 'ww', 'xx', 'yy', 'zz']
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rug_text = [rug_text_one, rug_text_two]
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rug_text = [rug_text_one, rug_text_two] # for hover in rug plot
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colors = ['rgb(0, 0, 100)', 'rgb(0, 200, 200)']
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# Create distplot with custom bin_size
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fig = ff.create_distplot(
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hist_data, group_labels, bin_size=.2,
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[x1, x2], group_labels, bin_size=.2,
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rug_text=rug_text, colors=colors)
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fig['layout'].update(title='Customized Distplot')
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# Plot!
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py.iplot(fig, filename='Distplot Colors')
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fig.update(layout_title_text='Customized Distplot')
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fig.show()
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```
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<!-- #region {"deletable": true, "editable": true} -->
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#### Plot Normal Curve
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<!-- #endregion -->
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```python deletable=true editable=true
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import plotly.plotly as py
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```python
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import plotly.figure_factory as ff
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import numpy as np
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x1 = np.random.randn(200)
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x2 = np.random.randn(200) + 2
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hist_data = [x1, x2]
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group_labels = ['Group 1', 'Group 2']
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colors = ['#3A4750', '#F64E8B']
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colors = ['slategray', 'magenta']
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# Create distplot with curve_type set to 'normal'
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fig = ff.create_distplot(hist_data, group_labels, bin_size=.5, curve_type='normal', colors=colors)
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fig = ff.create_distplot([x1, x2], group_labels, bin_size=.5,
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curve_type='normal', # override default 'kde'
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colors=colors)
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# Add title
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fig['layout'].update(title='Distplot with Normal Distribution')
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# Plot!
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py.iplot(fig, filename='Distplot with Normal Curve')
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fig.update(layout_title_text='Distplot with Normal Distribution')
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fig.show()
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```
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<!-- #region {"deletable": true, "editable": true} -->
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#### Plot Only Curve and Rug
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<!-- #endregion -->
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```python deletable=true editable=true
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import plotly.plotly as py
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```python
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import plotly.figure_factory as ff
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import numpy as np
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x1 = np.random.randn(200) - 1
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fig = ff.create_distplot(hist_data, group_labels, show_hist=False, colors=colors)
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# Add title
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fig['layout'].update(title='Curve and Rug Plot')
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# Plot!
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py.iplot(fig, filename='Curve and Rug')
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fig.update(layout_title_text='Curve and Rug Plot')
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fig.show()
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```
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<!-- #region {"deletable": true, "editable": true} -->
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#### Plot Only Hist and Rug
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<!-- #endregion -->
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```python deletable=true editable=true
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import plotly.plotly as py
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```python
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import plotly.figure_factory as ff
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import numpy as np
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x1 = np.random.randn(200) - 1
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colors = ['#835AF1', '#7FA6EE', '#B8F7D4']
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# Create distplot with curve_type set to 'normal'
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fig = ff.create_distplot(hist_data, group_labels, colors=colors, bin_size=.25, show_curve=False)
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fig = ff.create_distplot(hist_data, group_labels, colors=colors, bin_size=.25,
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show_curve=False)
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# Add title
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fig['layout'].update(title='Hist and Rug Plot')
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# Plot!
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py.iplot(fig, filename='Hist and Rug')
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fig.update(layout_title_text='Hist and Rug Plot')
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fig.show()
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```
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<!-- #region {"deletable": true, "editable": true} -->
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#### Plot Hist and Rug with Different Bin Sizes
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<!-- #endregion -->
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```python deletable=true editable=true
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import plotly.plotly as py
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```python
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import plotly.figure_factory as ff
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import numpy as np
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x1 = np.random.randn(200) - 2
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group_labels = ['Group 1', 'Group 2', 'Group 3']
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colors = ['#393E46', '#2BCDC1', '#F66095']
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# Create distplot with curve_type set to 'normal'
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fig = ff.create_distplot(hist_data, group_labels, colors=colors,
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bin_size=[0.3, 0.2, 0.1], show_curve=False)
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# Add title
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fig['layout'].update(title='Hist and Rug Plot')
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# Plot!
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py.iplot(fig, filename='Hist and Rug Different Bin Size')
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fig.update(layout_title_text='Hist and Rug Plot')
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fig.show()
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```
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<!-- #region {"deletable": true, "editable": true} -->
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#### Plot Only Hist and Curve
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<!-- #endregion -->
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```python deletable=true editable=true
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import plotly.plotly as py
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```python
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import plotly.figure_factory as ff
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import numpy as np
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x1 = np.random.randn(200) - 2
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bin_size=.2, show_rug=False)
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# Add title
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fig['layout'].update(title='Hist and Curve Plot')
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# Plot!
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py.iplot(fig, filename='Hist and Curve')
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fig.update(layout_title_text='Hist and Curve Plot')
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fig.show()
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```
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<!-- #region {"deletable": true, "editable": true} -->
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#### Distplot with Pandas
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<!-- #endregion -->
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```python deletable=true editable=true
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import plotly.plotly as py
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```python
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import plotly.figure_factory as ff
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import numpy as np
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import pandas as pd
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df = pd.DataFrame({'2012': np.random.randn(200),
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'2013': np.random.randn(200)+1})
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py.iplot(ff.create_distplot([df[c] for c in df.columns], df.columns, bin_size=.25),
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filename='distplot with pandas')
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fig = ff.create_distplot([df[c] for c in df.columns], df.columns, bin_size=.25)
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fig.show()
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```
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<!-- #region {"deletable": true, "editable": true} -->
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#### Reference
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<!-- #endregion -->
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```python deletable=true editable=true
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```python
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help(ff.create_distplot)
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```
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```python
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```python deletable=true editable=true
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from IPython.display import display, HTML
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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" />'))
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display(HTML('<link rel="stylesheet" type="text/css" href="http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css">'))
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!pip install git+https://github.com/plotly/publisher.git --upgrade
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import publisher
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publisher.publish(
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'distplots.ipynb', 'python/distplot/', 'Python Distplots | plotly',
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'How to make interactive Distplots in Python with Plotly. ',
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title = 'Python Distplots | plotly',
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name = 'Distplots',
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has_thumbnail='true', thumbnail='thumbnail/distplot.jpg',
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language='python', page_type='example_index',
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display_as='statistical', order=5,
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ipynb= '~notebook_demo/23')
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```
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```python deletable=true editable=true
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```

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