数据选择的常用方法

在ipython解释器下，构造测试数据：

In [1]: import numpy as np

In [2]: import pandas as pd

In [3]: dates = pd.date_range('20211107', periods=6)

In [4]: data = pd.DataFrame(np.random.randn(6, 4), index=d
   ...: ates, columns=['A', 'B', 'C', 'D'])

In [5]: data
Out[5]:
                   A         B         C         D
2021-11-07 -0.877244  1.713848  0.144780  0.011379
2021-11-08 -0.213253  0.344520 -0.658004  0.648373
2021-11-09  0.408933 -0.145004 -1.644283 -0.402420
2021-11-10  0.687184  0.412389  0.571787  0.069970
2021-11-11  0.984974 -1.827038  1.206369 -1.701110
2021-11-12  2.179770 -0.607483 -0.170085  0.617194
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按行标签选择数据：

In [11]: data.loc['2021-11-07']
Out[11]:
A   -0.877244
B    1.713848
C    0.144780
D    0.011379
Name: 2021-11-07 00:00:00, dtype: float64
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列标签获取多列数据：

In [15]: data.loc[:, ['A', 'B']]
Out[15]:
                   A         B
2021-11-07 -0.877244  1.713848
2021-11-08 -0.213253  0.344520
2021-11-09  0.408933 -0.145004
2021-11-10  0.687184  0.412389
2021-11-11  0.984974 -1.827038
2021-11-12  2.179770 -0.607483
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结合行标签和列标签获取多行多列数据：

In [16]: data.loc['2021-11-07':'2021-11-09', ['A', 'B']]
Out[16]:
                   A         B
2021-11-07 -0.877244  1.713848
2021-11-08 -0.213253  0.344520
2021-11-09  0.408933 -0.145004
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根据行标签和列标签获取某行多列数据：

In [17]: data.loc['2021-11-07', ['A', 'B']]
Out[17]:
A   -0.877244
B    1.713848
Name: 2021-11-07 00:00:00, dtype: float64
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根据特定行标签和特定的列标签获取某一个值：

# 方法一：
In [19]: data.loc['2021-11-07', 'A']
Out[19]: -0.877244243377641
# 方法二： 
In [20]: data.at['2021-11-07', 'A']
Out[20]: -0.877244243377641
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按索引位置（第几个位置，0索引为第一个位置）获取数据：

In [22]: data
Out[22]:
                   A         B         C         D
2021-11-07 -0.877244  1.713848  0.144780  0.011379
2021-11-08 -0.213253  0.344520 -0.658004  0.648373
2021-11-09  0.408933 -0.145004 -1.644283 -0.402420
2021-11-10  0.687184  0.412389  0.571787  0.069970
2021-11-11  0.984974 -1.827038  1.206369 -1.701110
2021-11-12  2.179770 -0.607483 -0.170085  0.617194

In [23]: data.iloc[0]
Out[23]:
A   -0.877244
B    1.713848
C    0.144780
D    0.011379
Name: 2021-11-07 00:00:00, dtype: float64