import numpy as np
x = np.arange(25)

x

x = da.arange(25, chunks=(5,))

y = x ** 2

y

y.visualize()

da.sqrt(x)[-1].visualize()

x = da.arange(250, chunks=(5,))

x.visualize()

x = da.ones((15, 15), chunks=(5,5))
x.sum(axis=1).visualize()

import dask.multiprocessing

y.compute(get = dask.multiprocessing.get)

import dask.dataframe as dd

cols = ['square_id', 'timestamp', 'country_code',
        'sms_in', 'sms_out','call_in','call_out', 'internet']

dtypes = {'square_id': int, 'timestamp': int, 'countrycode': int, 
          'sms_in': float,'sms_out': float, 'call_in': float, 'call_out': float, 'internet': float}

df = dd.read_csv?

df = dd.read_csv

"""
Explanation: <h3>Import dask and specifically dataframe class</h3>

Dask is a thread process scheduler and ...
End of explanation
"""


df_a = dd.read_csv('data/split/*.csv', header=0, names=cols, dtype=dtypes, sep="\t")

"""
Explanation: <h1>MISSING SEPERATOR ARGS FOR SPACE DELIMITED FILE!!!</h1>
End of explanation
"""


