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In [1]:

import numpy as np
import pandas as pd

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In [2]:

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,a,b,c,d
ONE,11,12,13,14
TWO,21,22,23,24
THREE,31,32,33,34

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In [3]:

print(df)

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a   b   c   d
ONE    11  12  13  14
TWO    21  22  23  24
THREE  31  32  33  34

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In [4]:

a = df.values

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In [5]:

print(a)

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[[11 12 13 14]
[21 22 23 24]
[31 32 33 34]]

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In [6]:

print(type(a))

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<class 'numpy.ndarray'>

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In [7]:

a = np.arange(6).reshape(2, 3)
print(a)

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[[0 1 2]
[3 4 5]]

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In [8]:

df = pd.DataFrame(a, index=['ONE', 'TWO'], columns=['a', 'b', 'c'])
print(df)

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a  b  c
ONE  0  1  2
TWO  3  4  5

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In [9]:

df.to_csv('data/temp/sample_pd.csv')

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In [10]:

with open('data/temp/sample_pd.csv') as f:

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,a,b,c
ONE,0,1,2
TWO,3,4,5

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In [11]:

with open('data/src/sample_nan.csv') as f:

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11,12,,14
21,,,24
31,32,33,34

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In [12]:

print(df)

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0     1     2   3
0  11  12.0   NaN  14
1  21   NaN   NaN  24
2  31  32.0  33.0  34

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In [13]:

with open('data/src/sample_pandas_normal.csv') as f:

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name,age,state,point
Alice,24,NY,64
Bob,42,CA,92
Charlie,18,CA,70
Dave,68,TX,70
Ellen,24,CA,88
Frank,30,NY,57

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In [14]:

print(df)

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name  age state  point
0    Alice   24    NY     64
1      Bob   42    CA     92
2  Charlie   18    CA     70
3     Dave   68    TX     70
4    Ellen   24    CA     88
5    Frank   30    NY     57

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In [15]:

print(df.dtypes)

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name     object
age       int64
state    object
point     int64
dtype: object

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In [16]:

print(df.select_dtypes('int'))

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age  point
0   24     64
1   42     92
2   18     70
3   68     70
4   24     88
5   30     57

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In [17]:

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In [18]:

print(a)

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[[24 64]
[42 92]
[18 70]
[68 70]
[24 88]
[30 57]]

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In [19]:

print(type(a))

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<class 'numpy.ndarray'>

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In [20]:

print(a.dtype)

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int64

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