A common error you may encounter when using Python is modulenotfounderror: no module named ‘statsmodels’.
This error occurs when the Python interpreter cannot detect the statsmodels in your current environment.
You can install statsmodels in Python 3 with python -m pip install statsmodels.
This tutorial goes through the exact steps to troubleshoot this error for the Windows, Mac and Linux operating systems.
Table of contents
- ModuleNotFoundError: no module named ‘statsmodels’
- Always Use a Virtual Environment to Install Packages
- Installing statsmodels Using Anaconda
- Summary
ModuleNotFoundError: no module named ‘statsmodels’
What is statsmodels?
Statsmodels is a Python library for statistical data analysis, statistical testing, and modelling. Statsmodels relies on the numerical and scientific libraries NumPy and SciPy and the visualization library matplotlib.
The simplest way to install statsmodels is to use the package manager for Python called pip. The following installation instructions are for the major Python version 3.
Always Use a Virtual Environment to Install Packages
It is always best to install new libraries within a virtual environment. You should not install anything into your global Python interpreter when you develop locally. You may introduce incompatibilities between packages, or you may break your system if you install an incompatible version of a library that your operating system needs. Using a virtual environment helps compartmentalize your projects and their dependencies. Each project will have its environment with everything the code needs to run. Most ImportErrors and ModuleNotFoundErrors occur due to installing a library for one interpreter and using the library with another interpreter. Using a virtual environment avoids this. In Python, you can use virtual environments and conda environments. We will go through how to install statsmodels with both.
How to Install statsmodels on Windows Operating System
First, you need to download and install Python on your PC. Ensure you select the install launcher for all users and Add Python to PATH checkboxes. The latter ensures the interpreter is in the execution path. Pip is automatically on Windows for Python versions 2.7.9+ and 3.4+.
You can check your Python version with the following command:
python3 --version
You can install pip on Windows by downloading the installation package, opening the command line and launching the installer. You can install pip via the CMD prompt by running the following command.
python get-pip.py
You may need to run the command prompt as administrator. Check whether the installation has been successful by typing.
pip --version
statsmodels installation on Windows Using pip
To install statsmodels, first, create the virtual environment. The environment can be any name, in this we choose “env”:
virtualenv env
You can activate the environment by typing the command:
env\Scripts\activate
You will see “env” in parenthesis next to the command line prompt. You can install statsmodels within the environment by running the following command from the command prompt.
python3 -m pip install statsmodels
We use python -m pip to execute pip using the Python interpreter we specify as Python. Doing this helps avoid ImportError when we try to use a package installed with one version of Python interpreter with a different version. You can use the command which python to determine which Python interpreter you are using.
How to Install statsmodels on Mac Operating System using pip
Open a terminal by pressing command (⌘) + Space Bar to open the Spotlight search. Type in terminal and press enter. To get pip, first ensure you have installed Python3:
python3 --version
Python 3.8.8
Download pip by running the following curl command:
curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
The curl command allows you to specify a direct download link. Using the -o option sets the name of the downloaded file.
Install pip by running:
python3 get-pip.py
To install statsmodels, first create the virtual environment:
python3 -m venv env
Then activate the environment using:
source env/bin/activate
You will see “env” in parenthesis next to the command line prompt. You can install statsmodels within the environment by running the following command from the command prompt.
python3 -m pip install statsmodels
How to Install statsmodels on Linux Operating Systems
All major Linux distributions have Python installed by default. However, you will need to install pip. You can install pip from the terminal, but the installation instructions depend on the Linux distribution you are using. You will need root privileges to install pip. Open a terminal and use the commands relevant to your Linux distribution to install pip.
Installing pip for Ubuntu, Debian, and Linux Mint
sudo apt install python-pip3
Installing pip for CentOS 8 (and newer), Fedora, and Red Hat
sudo dnf install python-pip3
Installing pip for CentOS 6 and 7, and older versions of Red Hat
sudo yum install epel-release
sudo yum install python-pip3
Installing pip for Arch Linux and Manjaro
sudo pacman -S python-pip
Installing pip for OpenSUSE
sudo zypper python3-pip
statsmodels installation on Linux with Pip
To install statsmodels, first create the virtual environment:
python3 -m venv env
Then activate the environment using:
source env/bin/activate
You will see “env” in parenthesis next to the command line prompt. You can install statsmodels within the environment by running the following command from the command prompt.
Once you have activated your virtual environment, you can install statsmodels using:
python3 -m pip install statsmodels
Installing statsmodels Using Anaconda
Anaconda is a distribution of Python and R for scientific computing and data science. You can install Anaconda by going to the installation instructions. Once you have installed Anaconda, you can create a virtual environment and install statsmodels.
To create a conda environment, you can use the following command:
conda create -n project python=3.8
You can specify a different Python 3 version if you like. Ideally, choose the latest version of Python. Next, you will activate the project container. You will see “project” in parentheses next to the command line prompt.
source activate project
Now you’re ready to install statsmodels using conda.
Once you have activated your conda environment, you can install statsmodels using the following command:
conda install -c anaconda statsmodels
Check statsmodels Version
Once you have successfully installed statsmodels, you can check its version. If you used pip to install statsmodels, you can use pip show from your terminal.
python3 -m pip show statsmodels
Name: statsmodels
Version: 0.12.2
Summary: Statistical computations and models for Python
Second, within your python program, you can import the statsmodels and then reference the __version__ attribute:
import statsmodels
print(statsmodels.__version__)
0.12.2
If you used conda to install statsmodels, you could check the version using the following command:
conda list -f statsmodels
# Name Version Build Channel
statsmodels 0.12.0 py38haf1e3a3_0 anaconda
Summary
Congratulations on reading to the end of this tutorial. The modulenotfounderror occurs if you misspell the module name, incorrectly point to the module path or do not have the module installed in your Python environment. If you do not have the module installed in your Python environment, you can use pip to install the package. However, you must ensure you have pip installed on your system. You can also install Anaconda on your system and use the conda install command to install statsmodels.
Go to the online courses page on Python to learn more about Python for data science and machine learning.
For further reading on missing modules in Python, go to the article:
- How to Solve Python ModuleNotFoundError: no module named ‘urllib2’.
- How to Solve ModuleNotFoundError: no module named ‘plotly’.
- How to Solve Python ModuleNotFoundError: No module named ‘django’.
Have fun and happy researching!
Suf is a senior advisor in data science with deep expertise in Natural Language Processing, Complex Networks, and Anomaly Detection. Formerly a postdoctoral research fellow, he applied advanced physics techniques to tackle real-world, data-heavy industry challenges. Before that, he was a particle physicist at the ATLAS Experiment of the Large Hadron Collider. Now, he’s focused on bringing more fun and curiosity to the world of science and research online.