duarteocarmo

# exercise 8.2.6

from matplotlib.pyplot import figure, plot, subplot, title, show, bar, legend, scatter
import numpy as np
from scipy.io import loadmat
import matplotlib.pyplot as plt
import neurolab as nl
from sklearn import model_selection
from scipy import stats
from Project_Clean_data import raw, header, is_binary

duarteocarmo

For the pattern "cat" [0, 16] "are" [2, 6] "to" we found 6363 matches in 0:15:43.31:
['cations are used to']
['cations== arrays are used to']
['cation modalities are audito']
['catalogue == compared to']
['cations are the to']
['cations since they are easy to']
['cations are used to']
['catalan has a shared histo']
['cations) are able to']

duarteocarmo

/Users/duarteocarmo/anaconda/bin/python /Users/duarteocarmo/PycharmProjects/Big_Data_Good/Challenge_1/test_letter.py

For the pattern "cat" [0, 16] "are" [2, 6] "to" we found the following matches in 0:00:38.24:
cations are used to
cations== arrays are used to
cation modalities are audito
cation software|deskto
cation software|deskto
cation factors are used to
cations when compared to

duarteocarmo

from Project_Clean_data import raw
from Project_Clean_data import header
import numpy as np
import xlsxwriter

# We could also define binary headers and only calculate there.


# build statistics function
def __get_basic_stats__(x):

duarteocarmo

from Project_Import_data import raw
from Project_Import_data import header
import numpy as np
import math
import random
import pandas as pd


since_first = header[26]
since_last = header[27]