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

# # Welcome to an example Binder

# This notebook uses a Python environment with a few libraries, including `dask`, all of which were specificied using a `conda` [environment.yml](../edit/environment.yml) file. To demo the environment, we'll show a simplified example of using `dask` to analyze time series data, adapted from Matthew Rocklin's excellent repo of [dask examples](https://github.com/blaze/dask-examples) — check out that repo for the full version (and many other examples).

# ## Setup plotting

# In[1]:


get_ipython().run_line_magic('matplotlib', 'inline')


# ## Turn on a global progress bar

# In[2]:


from dask.diagnostics import ProgressBar


# In[3]:


progress_bar = ProgressBar()
progress_bar.register()


# ## Generate fake data

# In[4]:


import dask.dataframe as dd


# In[5]:


df = dd.demo.make_timeseries(start='2000', end='2015', dtypes={'A': float, 'B': int},
                             freq='5s', partition_freq='3M', seed=1234)


# ## Compute and plot a cumulative sum

# In[6]:


df.A.cumsum().resample('1w').mean().compute().plot();