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This article will explain in detail how to use Loc and iloc in pandas. Xiaobian thinks it is quite practical, so share it with you as a reference. I hope you can gain something after reading this article.

Loc and iloc

Loc and iloc are often used to select rows and columns, and their functions are similar, but their usage is different.

Usage:

years = ['2010','2014','2017'] df[df.year.isin(years)]

loc: Select rows and columns by label (column and index)

iloc: Select rows and columns by index position

Select the data in rows 1~3 and columns 1~2 of df, and use iloc:

df.iloc[:3,:2]

Use loc:

df.loc[:2,['group','year']]1

Tip: When loc is used, the index refers to the index value, including the upper boundary. The iloc index refers to the position of the row, excluding the upper boundary.

Select rows 1, 3 and 5, year and value_1 columns:

df.loc[[1,3,5],['year','value_1']]

About "how to use Loc and iloc in pandas" this article is shared here, I hope the above content can be of some help to everyone, so that you can learn more knowledge, if you think the article is good, please share it for more people to see.

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