import pandas as pd

import numpy as np

df = pd.DataFrame(np.arange(24).reshape(6,4), columns=list('ABCD'))

print(df)

a = df['A'].between(3,13)

# 可直接利用a选中满足范围的所有行

print('df[a] is: \n', df[a])

# 利用a选中某一列

# 注意这里的两种类型不同,第一种是series,第二种是Dataframe,加不加[]的微妙区别

r1 = df[a]['D']

print(r1)

print('r1的类型是:', type(r1))

r2 = df[a][['D']]

print(r2)

print('r2的类型是:', type(r2))

# 选中某两列

print(df[a][['D','C']])

#注意between()中括号内是左闭右闭区间,所以可以用如下方式写,相当与筛选某一元素

print(df[df['A'].between(12,12)][['A','B']])

#     A   B   C   D

# 0   0   1   2   3

# 1   4   5   6   7

# 2   8   9  10  11

# 3  12  13  14  15

# 4  16  17  18  19

# 5  20  21  22  23

# df[a] is:

#      A   B   C   D

# 1   4   5   6   7

# 2   8   9  10  11

# 3  12  13  14  15

# 1     7

# 2    11

# 3    15

# Name: D, dtype: int64

# r1的类型是: <class 'pandas.core.series.Series'>

#     D

# 1   7

# 2  11

# 3  15

# r2的类型是: <class 'pandas.core.frame.DataFrame'>

#     D   C

# 1   7   6

# 2  11  10

# 3  15  14

#     A   B

# 3  12  13

import pandas as pd

import numpy as np

df = pd.DataFrame(np.arange(24).reshape(6,4), columns=list('ABCD'))

print(df)

a = df['A'].between(3,13)

# 可直接利用a选中满足范围的所有行

print('df[a] is: \n', df[a])

# 利用a选中某一列

# 注意这里的两种类型不同,第一种是series,第二种是Dataframe,加不加[]的微妙区别

r1 = df[a]['D']

print(r1)

print('r1的类型是:', type(r1))

r2 = df[a][['D']]

print(r2)

print('r2的类型是:', type(r2))

# 选中某两列

print(df[a][['D','C']])

#     A   B   C   D

# 0   0   1   2   3

# 1   4   5   6   7

# 2   8   9  10  11

# 3  12  13  14  15

# 4  16  17  18  19

# 5  20  21  22  23

# df[a] is:

#      A   B   C   D

# 1   4   5   6   7

# 2   8   9  10  11

# 3  12  13  14  15

# 1     7

# 2    11

# 3    15

# Name: D, dtype: int64

# r1的类型是: <class 'pandas.core.series.Series'>

#     D

# 1   7

# 2  11

# 3  15

# r2的类型是: <class 'pandas.core.frame.DataFrame'>

#     D   C

# 1   7   6

# 2  11  10

# 3  15