python pandas demo

1.

import pandas as pd

web_stats = {'Day':[1,2,3,4,5,6],
             'Visitors':[43,34,65,56,29,76],
             'Bounce Rate':[65,67,78,65,45,52]}

df = pd.DataFrame(web_stats)
print(df.head())

输出

   Day  Visitors  Bounce Rate
0    1        43           65
1    2        34           67
2    3        65           78
3    4        56           65
4    5        29           45

2.

import pandas as pd

web_stats = {'Day':[1,2,3,4,5,6],
             'Visitors':[43,34,65,56,29,76],
             'Bounce Rate':[65,67,78,65,45,52]}

df = pd.DataFrame(web_stats)
#print(df.head())
print(df.tail())

输出：

   Day  Visitors  Bounce Rate
1    2        34           67
2    3        65           78
3    4        56           65
4    5        29           45
5    6        76           52

3.

import pandas as pd

web_stats = {'Day':[1,2,3,4,5,6],
             'Visitors':[43,34,65,56,29,76],
             'Bounce Rate':[65,67,78,65,45,52]}

df = pd.DataFrame(web_stats)
#print(df.head())
print(df.tail(2))

输出

   Day  Visitors  Bounce Rate
4    5        29           45
5    6        76           52

 4.

import pandas as pd
import pickle
import numpy as np

dates=pd.date_range('20180310',periods=6)
df = pd.DataFrame(np.random.randn(6,4), index=dates, columns=['A','B','C','D'])#生成6行4列位置
print(df)

输出

                   A         B         C         D
2018-03-10  0.984919 -0.139348  0.160758 -0.251948
2018-03-11  0.891051 -0.116031  0.491253  0.262518
2018-03-12 -0.922257  0.761505  0.690123 -1.655246
2018-03-13  0.524870 -0.704932 -0.734333  0.619541
2018-03-14 -0.970407 -0.704575 -0.762169  0.829132
2018-03-15 -1.630999 -1.768938  0.744758 -0.521628