How to Check Pandas Version in Your Python Script?

check pandas version

Check Pandas Version: This article will explain you how to get the version of pandas directly in a python code or with the package installer called pip.

What is the Pandas Library?

Pandas is a Python library primarily used for data analysis. It is very popular and has a very active community of contributors. Pandas is essentially based on two Python libraries: Matplotlib for data visualization and NumPy for mathematical operations. It is a kind of overlay of these two libraries.

Pandas introduced two new types of objects for data storage that facilitate analytical tasks: Series, which have a list-like structure, and data frames, which have a tabular structure.

Many versions are deployed each year and at times it will be necessary to know the exact version of your installed Pandas library (to avoid certain conflicts for example).

There are several methods to check the version of python of which here are the most used:

  • The pandas pd.show_versions() function
  • __version__ attribute
  • Check Your Pandas Version with Pip

In the following we will detail these 3 methods.

Check Pandas Version Using __version__ attribute

Like most python packages, you can get the version number of pandas with the version attribute.

The first step is to import the pandas library and then use the print() function combined with the version attribute:

# __version__

import pandas as pd




Check Pandas Version With The Dependencies: pd.show_versions()

The pandas.show_versions() function allows to generate detailed information like Python versions, dependent packages and operating system type.

# show_versions()

import pandas as pd



commit           : 5e238bf1706dd712ed32dda23e52b
python           :
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.19041
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 12, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 1.3.2
numpy            : 1.21.2
pytz             : 2021.1
dateutil         : 2.8.2
pip              : 19.0.3
setuptools       : 40.8.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

How to Check Your Pandas Version with Pip?

With pip, it is also possible to get your Pandas version. This works equally well with the Windows command prompt, Powershell, Linux shell or MacOS terminal.

Here is an example with the Windows command prompt :

(venv) C:\Users\amiradata\Projects\>pip show pandas
Name: pandas
Version: 1.3.2
Summary: Powerful data structures for data analysis, time series, and statistics
Author: The Pandas Development Team
License: BSD-3-Clause
Location: c:\users\ayed7\pycharmprojects\sharepoint\venv\lib\site-packages
Requires: pytz, python-dateutil, numpy


This tutorial describes the different methods to check the version of pandas. These methods are easy to use.

If you want to know the latest version of pandas released, you can consult this link:

I also wrote a tutorial to install a specific version of a library: pip install specific version.

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By ayed_amira

I'm a data scientist. Passionate about new technologies and programming I created this website mainly for people who want to learn more about data science and programming :)

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