Column Selection in Pandas

In Pandas, we often want to select the columns of a pandas DataFrame based on their index value, and if we would like to choose columns based on integer indexing, we can use the .iloc function. If we would like to select columns based on label indexing, we can use the.loc function in Pandas. 

Selecting columns based on the user's given name is the basic way to choose a single column from a dataframe and just put the string name of the column in brackets. It returns a pandas series. Passing a list in the brackets lets us select multiple columns at the same time, and to choose columns, we must select one of the following options, Type SELECT, followed by the column names in the order in which we want them to appear on the report. To separate the column names, use commas. Use DataFrame.loc[] and DataFrame.iloc[] to collect single or multiple columns from pandas DataFrame by column names/label or index position respectively and where loc[] is used with column labels/names and iloc[] is used with column index/position in Pandas. 

Here is an example of column selection in Pandas:

Fig : Preview of the output that you will get on running this code from your IDE.

Code

In this solution we're using Pandas library.

Instructions

Follow the steps carefully to get the output easily.

1. Install pandas on your IDE(Any of your favorite IDE).
2. Copy the snippet using the 'copy' and paste it in your IDE.
3. Add required dependencies and import them in Python file(import pandas).
4. Add print statement at end of the code(refer preview of the output).
5. Run the file to generate the output.

I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.

I found this code snippet by searching for 'how to do column selection in pandas' in kandi. You can try any such use case!

Environment Tested

I tested this solution in the following versions. Be mindful of changes when working with other versions.

1. The solution is created in PyCharm 2021.3.
2. The solution is tested on Python 3.9.7.
3. Pandas version-v1.5.2.

Using this solution, we are able to implement column selection in pandas with simple steps. This process also facilities an easy way to use, hassle-free method to create a hands-on working version of code which would help us to implement column selection in pandas.

Dependent Library

You can also search for any dependent libraries on kandi like 'pandas'.

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