In [1]:

    

import pandas as pd
import numpy as np

starting_date = '20160701'
sample_numpy_data = np.array(np.arange(24)).reshape((6,4))
dates_index = pd.date_range(starting_date, periods=6)
sample_df = pd.DataFrame(sample_numpy_data, index=dates_index, columns=list('ABCD'))

sample_df_2 = sample_df.copy()
sample_df_2['Fruits'] = ['apple', 'orange','banana','strawberry','blueberry','pineapple']

sample_series = pd.Series([1,2,3,4,5,6], index=pd.date_range(starting_date, periods=6))
sample_df_2['Extra Data'] = sample_series *3 +1

second_numpy_array = np.array(np.arange(len(sample_df_2)))  *100 + 7
sample_df_2['G'] = second_numpy_array

sample_df_2


    

    
Out[1]:






  

    

      

      
A
      
B
      
C
      
D
      
Fruits
      
Extra Data
      
G
    
  
  

    

      
2016-07-01
      
0
      
1
      
2
      
3
      
apple
      
4
      
7
    
    

      
2016-07-02
      
4
      
5
      
6
      
7
      
orange
      
7
      
107
    
    

      
2016-07-03
      
8
      
9
      
10
      
11
      
banana
      
10
      
207
    
    

      
2016-07-04
      
12
      
13
      
14
      
15
      
strawberry
      
13
      
307
    
    

      
2016-07-05
      
16
      
17
      
18
      
19
      
blueberry
      
16
      
407
    
    

      
2016-07-06
      
20
      
21
      
22
      
23
      
pineapple
      
19
      
507
    
  

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pd.set_option('display.precision', 2)
sample_df_2.describe()


    

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s = pd.Series(['A', 'B', 'C', 'Aaba', 'Baca', np.nan, 'CABA', 'dog', 'cat'])
s.str.lower()


    

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