pandas 获取pandas中某个索引值前后的行数
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Get number of rows before and after a certain index value in pandas
提问by jkokorian
Let's say I have the following:
假设我有以下内容：
In [1]: import pandas as pd
import numpy as np
df = pd.DataFrame(data=np.random.rand(11),index=pd.date_range('2015-04-20','2015-04-30'),columns=['A'])
Out[1]:
A
2015-04-20 0.694983
2015-04-21 0.393851
2015-04-22 0.690138
2015-04-23 0.674222
2015-04-24 0.763175
2015-04-25 0.761917
2015-04-26 0.999274
2015-04-27 0.907871
2015-04-28 0.464818
2015-04-29 0.005733
2015-04-30 0.806351
I have some complicated method that identifies a single index as being interesting, for example '2015-04-25'. I can retrieve the row with that index using:
我有一些复杂的方法可以将单个索引标识为有趣的，例如“2015-04-25”。我可以使用该索引检索行：
In [2]: df.loc['2015-04-25']
Out[2]:
A 0.761917
Name: 2015-04-25 00:00:00, dtype: float64
What would be the nicest way to obtain a number of n rows before and/or after that index value?
在该索引值之前和/或之后获取 n 行数的最佳方法是什么？
What I would like to do is something like:
我想做的是：
In[3]: df.getRowsBeforeLoc('2015-04-25',3)
Out[3]:
2015-04-22 0.690138
2015-04-23 0.674222
2015-04-24 0.763175
2015-04-25 0.761917
Or equivalently:
或等效地：
In[3]: df.getRowsAfterLoc('2015-04-25',3)
Out[3]:
2015-04-25 0.761917
2015-04-26 0.999274
2015-04-27 0.907871
2015-04-28 0.464818
(I don't have a strong opinion on whether or not the row that corresponds to the target index value itself is included.)
（对于是否包含与目标索引值本身对应的行，我没有强烈的意见。）
回答by EdChum
locsupports slicing the beg/end point is included in the range:
loc支持切片 beg/end 点包含在范围内：
In [363]:
df.loc[:'2015-04-25']
Out[363]:
A
2015-04-25 0.141787
2015-04-26 0.598237
2015-04-27 0.106461
2015-04-28 0.297159
2015-04-29 0.058392
2015-04-30 0.621325
In [364]:
df.loc['2015-04-25':]
Out[364]:
A
2015-04-25 0.141787
2015-04-26 0.598237
2015-04-27 0.106461
2015-04-28 0.297159
2015-04-29 0.058392
2015-04-30 0.621325
To get either first/last (n) rows use head/tail:
要获取第一行/最后一行 (n) 行，请使用head/ tail：
In [378]:
df.loc[:'2015-04-25'].head(3)
Out[378]:
A
2015-04-20 0.827699
2015-04-21 0.901140
2015-04-22 0.427304
In [377]:
df.loc[:'2015-04-25'].tail(3)
Out[377]:
A
2015-04-23 0.002189
2015-04-24 0.041965
2015-04-25 0.141787
update
更新
To get the row before/after a specifc value we can use get_locon the index to return an integer position and then use this with ilocto get the previous/next row:
要获取特定值之前/之后的行，我们可以get_loc在索引上使用以返回整数位置，然后使用它iloc来获取上一行/下一行：
In [388]:
df.index.get_loc('2015-04-25')
Out[388]:
5
In [391]:
df.iloc[df.index.get_loc('2015-04-25')-1]
Out[391]:
A 0.041965
Name: 2015-04-24 00:00:00, dtype: float64
In [392]:
df.iloc[df.index.get_loc('2015-04-25')+1]
Out[392]:
A 0.598237
Name: 2015-04-26 00:00:00, dtype: float64
