#!/usr/bin/env python
# coding: utf-8

# #### New to Plotly?
# Plotly's Python library is free and open source! [Get started](https://plotly.com/python/getting-started/) by downloading the client and [reading the primer](https://plotly.com/python/getting-started/).
# <br>You can set up Plotly to work in [online](https://plotly.com/python/getting-started/#initialization-for-online-plotting) or [offline](https://plotly.com/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plotly.com/python/getting-started/#start-plotting-online).
# <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!

# #### Version Check
# Note: Violin Plots are available in version <b>1.12.1+</b><br>
# Run  `pip install plotly --upgrade` to update your Plotly version.

# In[1]:


import plotly
plotly.__version__


# #### One Violin

# In[2]:


import plotly.plotly as py
import plotly.figure_factory as ff
import plotly.graph_objs as go

import numpy as np
from scipy import stats

data_list = np.random.randn(100)
data_list.tolist()

fig = ff.create_violin(data_list, colors='#604d9e')
py.iplot(fig, filename='One Violin')


# #### Multiple Violins

# In[3]:


import plotly.plotly as py
import plotly.figure_factory as ff
import plotly.graph_objs as go

import numpy as np
import pandas as pd
from scipy import stats

np.random.seed(619517)
Nr = 250
y = np.random.randn(Nr)
gr = np.random.choice(list("ABCDE"), Nr)
norm_params = [(0, 1.2), (0.7, 1), (-0.5, 1.4), (0.3, 1), (0.8, 0.9)]

for i, letter in enumerate("ABCDE"):
    y[gr == letter] *= norm_params[i][1] + norm_params[i][0]
df = pd.DataFrame(dict(Score = y, Group = gr))

fig = ff.create_violin(df, data_header='Score', group_header='Group',
                       height=500, width=800)
py.iplot(fig, filename='Multiple Violins')


# #### Violin Plots with Colorscale

# In[4]:


import plotly.plotly as py
import plotly.figure_factory as ff
import plotly.graph_objs as go

import numpy as np
import pandas as pd
from scipy import stats

np.random.seed(619517)
Nr = 250
y = np.random.randn(Nr)
gr = np.random.choice(list("ABCDE"), Nr)
norm_params = [(0, 1.2), (0.7, 1), (-0.5, 1.4), (0.3, 1), (0.8, 0.9)]

for i, letter in enumerate("ABCDE"):
    y[gr == letter] *= norm_params[i][1] + norm_params[i][0]
df = pd.DataFrame(dict(Score = y, Group = gr))

data_header = 'Score'
group_header = 'Group'

group_stats = {}
groupby_data = df.groupby([group_header])

for group in "ABCDE":
    data_from_group = groupby_data.get_group(group)[data_header]
    stat = np.median(data_from_group)
    group_stats[group] = stat

fig = ff.create_violin(df, data_header='Score', group_header='Group',
                       colors='YlOrRd', height=500, width=800,
                       use_colorscale=True, group_stats=group_stats)
py.iplot(fig, filename='Violin Plots with Colorscale')


# #### Violin Plots with Dictionary Colors

# In[5]:


import plotly.plotly as py
import plotly.figure_factory as ff
import plotly.graph_objs as go

import numpy as np
import pandas as pd
from scipy import stats

np.random.seed(619517)
Nr = 250
y = np.random.randn(Nr)
gr = np.random.choice(list("ABCDE"), Nr)
norm_params = [(0, 1.2), (0.7, 1), (-0.5, 1.4), (0.3, 1), (0.8, 0.9)]

for i, letter in enumerate("ABCDE"):
    y[gr == letter] *= norm_params[i][1] + norm_params[i][0]
df = pd.DataFrame(dict(Score = y, Group = gr))

data_header = 'Score'
group_header = 'Group'

colors_dict = dict(A = 'rgb(25, 200, 120)',
                   B = '#aa6ff60',
                   C = (0.3, 0.7, 0.3),
                   D = 'rgb(175, 25, 122)',
                   E = 'rgb(255, 150, 226)')

fig = ff.create_violin(df, data_header='Score', group_header='Group',
                       colors=colors_dict, height=500, width=800,
                       use_colorscale=False)
py.iplot(fig, filename='Violin Plots with Dictionary Colors')


# #### Reference

# In[7]:


help(ff.create_violin)


# In[8]:


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">'))

get_ipython().system(' pip install git+https://github.com/plotly/publisher.git --upgrade')
import publisher
publisher.publish(
    'violin-plot.ipynb', 'python/legacy/violin-plot/', 'Violin Plots [Legacy]',
    'How to make Violin Plots in Python with Plotly. A Violin Plot is a plot of numeric data with probability distributions drawn on both sides on the plotted data.',
    title='Python Violin Plots | plotly',
    name='Violin Plots',
    thumbnail='thumbnail/violin-plot.jpg', language='python',
    has_thumbnail='true', display_as='legacy_charts', order=2,
    ipynb= '~notebook_demo/26')


# In[ ]: