Home > Backend Development > Python Tutorial > pandas implements selecting rows at a specific index

pandas implements selecting rows at a specific index

不言
Release: 2018-04-20 14:11:02
Original
5775 people have browsed it

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
>>>
Copy after login

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 
>>>
Copy after login

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

The above is the detailed content of pandas implements selecting rows at a specific index. For more information, please follow other related articles on the PHP Chinese website!

Related labels:
source:php.cn
Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Popular Tutorials
More>
Latest Downloads
More>
Web Effects
Website Source Code
Website Materials
Front End Template