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

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# #### Imports
# The tutorial below imports [numpy](http://www.numpy.org/), [pandas](https://plotly.com/pandas/intro-to-pandas-tutorial/), and [scipy](https://www.scipy.org/)

# In[1]:


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 distrubution
# 
# $$
# \begin{align*}
# X = \log(U)^{\frac{1}{a}}
# \end{align*}
# $$
# 
# where $U$ is drawn from the `Uniform Distribution`.

# In[17]:


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

# In[21]:


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

# In[20]:


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')


# In[1]:


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(
    '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')


# In[ ]: