14-numpy笔记-莫烦pandas-2
代码
import pandas as pd
import numpy as np
dates = pd.date_range('20130101', periods=6)
df=pd.DataFrame(np.arange(24).reshape((6,4)), index=dates, columns=['A','B','C','D'])
print('-1-')
print(df)
print('-2-')
print(df['A'],df.A)
print('-3-')
print(df[0:3],df['20130102':'20130104'])
print('-4-')
print(df.loc['20130102'])
print('-5-')
# 打印AB列
print(df.loc[:,['A','B']])
print('-6-')
print(df.loc['20130102',['A','B']])
# 筛选 [行，列] : 左闭右开
# 第三行，零初始
print('-7-')
print(df.iloc[3])
print('-8-')
print(df.iloc[3,1])
print('-9-')
print(df.iloc[3:5,1:3])
print('-10-')
print(df.iloc[[1,3,5],1:3])
print('-11-')
print(df.ix[:3,['A','C']])
print('-12-')
#条件筛选
print(df[df.A > 8])
结果
-1-
A B C D
2013-01-01 0 1 2 3
2013-01-02 4 5 6 7
2013-01-03 8 9 10 11
2013-01-04 12 13 14 15
2013-01-05 16 17 18 19
2013-01-06 20 21 22 23
-2-
2013-01-01 0
2013-01-02 4
2013-01-03 8
2013-01-04 12
2013-01-05 16
2013-01-06 20
Freq: D, Name: A, dtype: int32 2013-01-01 0
2013-01-02 4
2013-01-03 8
2013-01-04 12
2013-01-05 16
2013-01-06 20
Freq: D, Name: A, dtype: int32
-3-
A B C D
2013-01-01 0 1 2 3
2013-01-02 4 5 6 7
2013-01-03 8 9 10 11 A B C D
2013-01-02 4 5 6 7
2013-01-03 8 9 10 11
2013-01-04 12 13 14 15
-4-
A 4
B 5
C 6
D 7
Name: 2013-01-02 00:00:00, dtype: int32
-5-
A B
2013-01-01 0 1
2013-01-02 4 5
2013-01-03 8 9
2013-01-04 12 13
2013-01-05 16 17
2013-01-06 20 21
-6-
A 4
B 5
Name: 2013-01-02 00:00:00, dtype: int32
-7-
A 12
B 13
C 14
D 15
Name: 2013-01-04 00:00:00, dtype: int32
-8-
13
-9-
B C
2013-01-04 13 14
2013-01-05 17 18
-10-
B C
2013-01-02 5 6
2013-01-04 13 14
2013-01-06 21 22
-11-
A C
2013-01-01 0 2
2013-01-02 4 6
2013-01-03 8 10
-12-
A B C D
2013-01-04 12 13 14 15
2013-01-05 16 17 18 19
2013-01-06 20 21 22 23
