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pandas implements selecting rows at a specific index

Apr 20, 2018 pm 02:11 PM
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Below I will share with you a pandas implementation of selecting rows of a specific index. It has a good reference value and I hope it will be helpful to everyone. Come and take a look together

As shown below:

>>> 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
>>>
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Note that iloc cannot be used. iloc accesses the sequence as an array, and the subscript will start from 0:

>>> 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 
>>>
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Related recommendations:

Method for selecting rows and columns based on pandas data samples

pandas groupby grouping method to select the first few rows of each group to record

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