pandas学习笔记

引入所需要的包：

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

 

一、创建对象

通过传递一个list对象来创建一个Series

s = pd.Series([1,3,5,np.nan,6,8])

>>> s
0    1.0
1    3.0
2    5.0
3    NaN
4    6.0
5    8.0
dtype: float64

通过传递一个numpy array，时间索引以及列标签来创建一个DataFrame

ata =pd.date_range('20170701',periods=6)

>>> data
DatetimeIndex(['2017-07-01', '2017-07-02', '2017-07-03', '2017-07-04',
               '2017-07-05', '2017-07-06'],
              dtype='datetime64[ns]', freq='D')

通过传递一个能够被转换成类似序列结构的字典对象来创建一个DataFrame

df2 = pd.DataFrame({'A':1,
                    'B':pd.Timestamp('20170702'),
                    'C':pd.Series(1,index=list(range(4)),dtype='float32'),
                    'D':np.array([3]*4,dtype='int32'),
                    'E':pd.Categorical(['test','train','test','train']),
                    'F':'foo'})

>>> df2
   A          B    C  D      E    F
0  1 2017-07-02  1.0  3   test  foo
1  1 2017-07-02  1.0  3  train  foo
2  1 2017-07-02  1.0  3   test  foo
3  1 2017-07-02  1.0  3  train  foo

二、 查看数据

1、查看frame中头部和尾部的行

index = pd.date_range('1/1/2000', periods=8)
s = pd.Series(np.random.randn(5), index=['a', 'b', 'c', 'd', 'e'])
df = pd.DataFrame(np.random.randn(8, 3),index=index,columns=['A', 'B', 'C'])
>>> df.head()
                   A         B         C
2000-01-01 -0.944924 -0.081706 -1.161476
2000-01-02 -0.205432  0.271903  0.668626
2000-01-03 -0.505713  1.804659 -1.232667
2000-01-04  0.048007  1.246067  0.083038
2000-01-05 -0.561152  0.987697 -0.268812
>>> df.tail(3)
                   A         B         C
2000-01-06  0.613778 -0.357461  1.649822
2000-01-07  1.045096 -1.840059  1.413085
2000-01-08 -1.481738 -0.663567  0.437833