In [1]:

    

import numpy as np
import pandas as pd


    

In [2]:

    

df = pd.DataFrame(columns=['y'], index=np.arange(10), data=np.random.random(10) * 100)
df['y'] = df['y'].map(round)
df.head()


    

    
Out[2]:






  

    

      

      
y
    
  
  

    

      
0
      
46
    
    

      
1
      
95
    
    

      
2
      
69
    
    

      
3
      
84
    
    

      
4
      
57
    
  

In [3]:

    

df.to_csv('./data/bar.csv', index_label='x')


    

In [4]:

    

df = pd.DataFrame(columns=['y'], index=np.arange(100), data=sorted(np.random.random(100)**2))
df['y'] = df['y'].map(lambda x: round(x, 5))
df.head()


    

    
Out[4]:






  

    

      

      
y
    
  
  

    

      
0
      
0.00007
    
    

      
1
      
0.00027
    
    

      
2
      
0.00718
    
    

      
3
      
0.00754
    
    

      
4
      
0.01250
    
  

In [5]:

    

df.to_csv('./data/line.csv', index_label='x')


    

In [6]:

    

df = pd.DataFrame(columns=['y'], index=np.arange(20), data=np.random.random(20))
df['y'] = df['y'].map(lambda x: round(x, 2))
df.head()


    

    
Out[6]:






  

    

      

      
y
    
  
  

    

      
0
      
0.72
    
    

      
1
      
0.51
    
    

      
2
      
0.64
    
    

      
3
      
0.13
    
    

      
4
      
0.29
    
  

In [7]:

    

df.to_csv('./data/scatter.csv', index_label='x')


    

In [8]:

    

df = pd.DataFrame(columns=['y1', 'y2', 'y3'], index=np.arange(100))
df['y1'] = pd.Series(sorted(np.random.random(100)*10)).map(lambda x: round(x, 2))
df['y2'] = pd.Series(sorted(np.random.random(100)*15)).map(lambda x: round(x, 2))
df['y3'] = pd.Series(sorted(np.random.random(100)*50)).map(lambda x: round(x, 2))
df.head()


    

    
Out[8]:






  

    

      

      
y1
      
y2
      
y3
    
  
  

    

      
0
      
0.10
      
0.20
      
0.67
    
    

      
1
      
0.19
      
0.22
      
0.85
    
    

      
2
      
0.20
      
0.24
      
1.84
    
    

      
3
      
0.20
      
0.36
      
1.95
    
    

      
4
      
0.29
      
0.73
      
2.41
    
  

In [9]:

    

df.to_csv('./data/multiline.csv', index_label='x')