Applying Condition in Pandas

The function in pandas is used to group rows of a DataFrame based on the values in one or more columns. It returns a GroupBy object, a special type of DataFrame grouped by one or more columns. The GroupBy object can then perform various operations on the grouped data. 

In pandas, you can concatenate strings of a grouped DataFrame using the “apply()” function and a custom function that concatenates the strings. 

• apply(): In pandas, the apply() function is used to apply a function to each element, row, or column of a DataFrame or a Series.

You can use any other method to concatenate strings, like using “pd.Series.str.cat()” or “pd.Series.agg()” with a custom function that concatenates the strings. 

• pd.Series.str.cat(): pd.Series.str.cat() is a pandas function that concatenates all elements in a Series of strings into a single string.  
• pd.Series.agg(): pd.Series.agg() is a pandas function that applies one or multiple aggregation functions to a Series, returning the result in the form of a scalar or a Series, depending on the number of functions passed and the number of groups in the input. 

For more information about concatenating strings of a GroupedBy Pandas DataFrame, please look at the code below. 

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. 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 'Applying a condition 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 apply condition 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 apply condition in pandas.

Dependent Library

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

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