Find the version of the Pandas and its dependencies in Python

Pandas is a crucial package for data analysis in Python. Different versions may have compatibility issues, so it's important to check your Pandas version and its dependencies. Python provides several methods to retrieve this information.

Finding Pandas Version

The simplest way to check the Pandas version is using the __version__ attribute ?

import pandas as pd
print(pd.__version__)

2.1.4

Alternative Methods to Check Version

Using pkg_resources

import pkg_resources
version = pkg_resources.get_distribution("pandas").version
print(version)

2.1.4

Using importlib.metadata

from importlib.metadata import version
print(version('pandas'))

2.1.4

Checking Dependencies with show_versions()

To view detailed information about Pandas and all its dependencies, use the show_versions() function ?

import pandas as pd
pd.show_versions()

INSTALLED VERSIONS
------------------
commit           : d9cdd2ee5a58015ef6f4d15c7226110c9d8e659c
python           : 3.11.4
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-91-generic
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8

pandas           : 2.1.4
numpy            : 1.24.3
pytz             : 2023.3
dateutil         : 2.8.2
setuptools       : 68.0.0
pip              : 23.1.2
Cython           : 3.0.5
pytest           : 7.4.0
hypothesis       : 6.82.0
sphinx           : 7.1.2
blosc            : None
feather          : None
xlsxwriter       : 3.1.1
lxml.etree       : 4.9.2
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 3.1.2
IPython          : 8.12.2
pandas_datareader: None
bs4              : 4.12.2
bottleneck       : 1.3.5
fastparquet      : 0.8.1
matplotlib       : 3.7.1
numexpr          : 2.8.4
odfpy            : None
openpyxl         : 3.0.10
scipy            : 1.10.1
sqlalchemy       : 2.0.18
tables           : 3.8.0
xlrd             : 2.0.1
xlwt             : 1.3.0

Getting Specific Dependency Versions

You can check individual dependency versions programmatically ?

import pandas as pd
import numpy as np

print(f"Pandas: {pd.__version__}")
print(f"NumPy: {np.__version__}")

# Check if optional dependencies are available
try:
    import matplotlib
    print(f"Matplotlib: {matplotlib.__version__}")
except ImportError:
    print("Matplotlib: Not installed")

try:
    import scipy
    print(f"SciPy: {scipy.__version__}")
except ImportError:
    print("SciPy: Not installed")

Pandas: 2.1.4
NumPy: 1.24.3
Matplotlib: 3.7.1
SciPy: 1.10.1

Comparison of Methods

Conclusion

Use pd.__version__ for quick version checks and pd.show_versions() for comprehensive dependency information. This helps troubleshoot compatibility issues and ensure proper environment setup.