How to Install `pandas` in Python

v3.0.2 Data & Science Python >=3.11 Apache-2.0

Powerful data structures for data analysis, time series, and statistics

Install pip install pandas

What is pandas?

Powerful data structures for data analysis, time series, and statistics

pandas: A Powerful Python Data Analysis Toolkit

pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real-world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open-source data analysis/manipulation tool available in any language. It is already well on its way towards this goal.

- Main Features - Where to get it - Dependencies - Installation from sources - License - Documentation - Background - Getting Help - Discussion and Development - Contributing to pandas

PyPI page → Author: The Pandas Development Team <[email protected]>

Quick Start

Minimal example to get started with pandas:

import pandas as pd

df = pd.DataFrame({"name": ["Alice", "Bob"], "age": [30, 25]})
print(df)
print(df["age"].mean())  # 27.5

# Read from CSV
# df = pd.read_csv("data.csv")

Installation

pip (standard)

pip install pandas

Virtual environment (recommended)

python -m venv venv
source venv/bin/activate   # Windows: venv\Scripts\activate
pip install pandas

pip3

pip3 install pandas

conda

conda install -c conda-forge pandas

Poetry

poetry add pandas

Dependencies

Installing pandas will also install these packages:

numpy numpy python-dateutil tzdata tzdata

Verify the Installation

After installing, confirm the package is available:

python -c "import pandas; print(pandas.__version__)"

If this prints a version number, installation succeeded. If you see a ModuleNotFoundError, see the errors section below.

Installation Errors

Common errors when installing pandas with pip.

ModuleNotFoundError: No module named 'pandas'

Cause: The package is not installed in the current Python environment.

Fix: Run pip install pandas. If using a virtual environment, ensure it is activated first.

ModuleNotFoundError: No module named 'pandas' (installed but still failing)

Cause: pip installed the package into a different Python than the one running your script.

Fix: Use python -m pip install pandas to install into the interpreter you are running.

ImportError: cannot import name 'X' from 'pandas'

Cause: The function or class does not exist in the installed version.

Fix: Check the version with pip show pandas and upgrade with pip install --upgrade pandas.

pip: command not found

Cause: pip is not in PATH or Python was not added to PATH during installation.

Fix: Try python -m pip install pandas. On macOS/Linux try pip3.

PermissionError: [Errno 13] Permission denied

Cause: No write access to the system Python package directory.

Fix: Use a virtual environment, or add --user: pip install --user pandas

SSL: CERTIFICATE_VERIFY_FAILED

Cause: pip cannot verify PyPI's SSL certificate — common behind corporate proxies.

Fix: Try: pip install --trusted-host pypi.org --trusted-host files.pythonhosted.org pandas

MemoryError when loading data

Cause: Dataset is too large to fit in RAM.

Fix: Read in chunks, filter columns on load, or consider Polars/Dask for out-of-core processing.

Runtime Errors

Common errors when using pandas after installation.

KeyError: 'column_name'

Cause: The column does not exist in the DataFrame.

Fix: Inspect columns with df.columns.tolist(). Watch for leading/trailing whitespace in column names.

ValueError: Cannot convert float NaN to integer

Cause: The column contains NaN values but is being cast to int.

Fix: Fill or drop NaN values first: df['col'].fillna(0).astype(int)

MemoryError

Cause: The dataset is too large to fit in RAM.

Fix: Use chunked reading: pd.read_csv(file, chunksize=10000) or switch to Polars or Dask.

pandas.errors.ParserError: Error tokenizing data

Cause: Inconsistent column counts or wrong delimiter in the CSV.

Fix: Try pd.read_csv(file, on_bad_lines='skip') or specify sep=',' explicitly.

Recent Releases

Version	Released
`3.0.2` latest	2026-03-31
`3.0.1`	2026-02-17
`3.0.0`	2026-01-21
`3.0.0rc2`	2026-01-14
`3.0.0rc1`	2025-12-19

Full release history on PyPI →

Manage pandas

Upgrade to latest version

pip install --upgrade pandas

Install a specific version

pip install pandas==3.0.2

Uninstall

pip uninstall pandas

Check what is installed

pip show pandas

Last updated: 2026-04-11 • Data from PyPI

How to Install pandas in Python