pandas选取特定索引的行

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[python] view plain copy

print?

>>> import numpy as np
>>> import pandas as pd
>>> index=np.array([2,4,6,8,10])
>>> data=np.array([3,5,7,9,11])
>>> data=pd.DataFrame({’num’:data},index=index)
>>> print(data)
num
2 3
4 5
6 7
8 9
10 11
>>> select_index=index[index>5]
>>> print(select_index)
[ 6 8 10]
>>> data[’num’].loc[select_index]
6 7
8 9
10 11
Name: num, dtype: int32
>>>

>>> import numpy as np>>> import pandas as pd>>> index=np.array([2,4,6,8,10])>>> data=np.array([3,5,7,9,11])>>> data=pd.DataFrame({'num':data},index=index)>>> print(data)    num2     34     56     78     910   11>>> select_index=index[index>5]>>> print(select_index)[ 6  8 10]>>> data['num'].loc[select_index]6      78      910    11Name: num, dtype: int32>>>

注意，不能用iloc，iloc是将序列当作数组来访问，下标又会从0开始：

[python] view plain copy

print?

>>> data[‘num’].iloc[2:5]
6 7
8 9
10 11
Name: num, dtype: int32
>>> data[’num’].iloc[[2,3,4]]
6 7
8 9
10 11
Name: num, dtype: int32
>>>

>>> data['num'].iloc[2:5]6      78      910    11Name: num, dtype: int32>>> data['num'].iloc[[2,3,4]]6      78      910    11Name: num, dtype: int32>>>

转自博客：
http://blog.csdn.net/o1101574955/article/details/51638128

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