In [1]:

    

import numpy as np
import pandas as pd


    

In [2]:

    

with open('data/src/sample_header_index.csv') as f:
    print(f.read())


    

    




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

In [3]:

    

df = pd.read_csv('data/src/sample_header_index.csv', index_col=0)
print(df)


    

    




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

In [4]:

    

a = df.values


    

In [5]:

    

print(a)


    

    




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

In [6]:

    

print(type(a))


    

    




<class 'numpy.ndarray'>

In [7]:

    

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


    

    




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

In [8]:

    

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


    

    




     a  b  c
ONE  0  1  2
TWO  3  4  5

In [9]:

    

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


    

In [10]:

    

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


    

    




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

In [11]:

    

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


    

    




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

In [12]:

    

df = pd.read_csv('data/src/sample_nan.csv', header=None)
print(df)


    

    




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

In [13]:

    

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


    

    




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

In [14]:

    

df = pd.read_csv('data/src/sample_pandas_normal.csv')
print(df)


    

    




      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

In [15]:

    

print(df.dtypes)


    

    




name     object
age       int64
state    object
point     int64
dtype: object

In [16]:

    

print(df.select_dtypes('int'))


    

    




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

In [17]:

    

a = pd.read_csv('data/src/sample_pandas_normal.csv').select_dtypes('int').values


    

In [18]:

    

print(a)


    

    




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

In [19]:

    

print(type(a))


    

    




<class 'numpy.ndarray'>

In [20]:

    

print(a.dtype)


    

    




int64