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Group a dataframe by column using Pandas

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by sneha@openweaver.com dot icon Updated: Mar 30, 2023

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A dataframe is a two-dimensional data structure, i.e., data is aligned in a tabular fashion in rows and columns. It is used to store and analyze data in a structured form. It is similar to a spreadsheet, SQL table, or dictionary of Series objects.


Pandas is a Python library used for data analysis and manipulation. It provides data structures and operations for manipulating numerical tables and time series. It is built on top of the NumPy library and provides an easy-to-use data structure for working with rows and columns of data.


Pandas are fast and efficient and can be used for data cleaning and analysis.

  • Pandas groupby is a method for grouping data objects into Series (columns) or DataFrames (a group of Series) based on values in one or more columns.
  • To group a dataframe by column using Pandas, use the groupby() function.

Here is an example of how to group a dataframe by column using Pandas.




Fig1: Preview of Output when the code is run in IDE.

Code


In this solution we're using groupby() of pandas.

group DataFrame by column value using pandas

PythondotLines of Code : 20dotLicense : Strong Copyleft (CC BY-SA 4.0)

Dependent Libraries : 
from pandas import DataFrame
columns = ["b", "c", "d", "e"]
data = [[100, 369, 203, 314], [100, 228, 784, 366], [200, 811, 664, 202], [200, 531, 932, 575]]
df = DataFrame(data=data,columns=columns)

def split_dfs(df, col):
    return [group[1] for group in list(df.groupby(col))]

dfs = split_dfs(df, "b")

for df_group in dfs:
    print(df_group)

    b    c    d    e
0  100  369  203  314
1  100  228  784  366
     b    c    d    e
2  200  811  664  202
3  200  531  932  575

Instructions

Follow the steps carefully to get the output easily.

  1. Install Jupyter Notebook on your computer.
  2. Open terminal and install the required libraries with following commands.
  3. Install Pandas - pip install pandas
  4. Copy the snippet using the 'copy' button and paste it into that file.
  5. Run the file using run button.


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 '"Group dataframe by column using Pandas" in kandi. You can try any such use case!

Dependent Libraries

pandasby pandas-dev

Python doticonstar image 38689 doticonVersion:v2.0.2doticon
License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

Support
    Quality
      Security
        License
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            pandasby pandas-dev

            Python doticon star image 38689 doticonVersion:v2.0.2doticon License: Permissive (BSD-3-Clause)

            Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
            Support
              Quality
                Security
                  License
                    Reuse

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

                      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 Python3.9.6.
                      2. The solution is tested on pandas 1.4.4 version.


                      Using this solution, we are able to group a dataframe by column using Pandas.



                      This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us to group a dataframe by column using Pandas

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