PyCharm for Windows
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Set Up PyCharm on Windows for Data Science

Configure Conda or venv interpreters, use WSL for Linux tools, and run Jupyter notebooks inside PyCharm 2026.1.1 on Windows 10/11 (64-bit).

File: pycharm-2026.1.1.exe • OS: Windows 10 / 11 (64-bit)
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Conda interpreter setup

1) Install Miniconda/Anaconda

If you don't have Conda, install Miniconda (lighter) or Anaconda (batteries-included) for Windows 64-bit.

2) Add Conda interpreter in PyCharm

Open Settings → Python Interpreter → AddConda EnvironmentNew. Name it ds-env, choose Python 3.x.

3) Install data packages

From Python Interpreter click + to add numpy, pandas, matplotlib, scikit-learn, jupyter.

4) Verify environment

Run import numpy as np; print(np.__version__) in the Python Console to confirm packages are available.

venv (Virtualenv) setup

1) Create a new project

File → New Project → New environment using Virtualenv. Pick a location like C:\Users\You\PycharmProjects\ds-demo.

2) Install packages

Open Settings → Python Interpreter+ and install numpy, pandas, matplotlib.

3) Freeze requirements (optional)

Use the Terminal (Alt+F12): pip freeze > requirements.txt for reproducibility.

WSL interpreter (Ubuntu on Windows)

1) Enable WSL

Run as Administrator: wsl --install, reboot, then open Ubuntu from Start Menu.

2) Install Python/Conda inside WSL

In Ubuntu: sudo apt update && sudo apt install python3-venv or install Miniconda for Linux (WSL).

3) Add WSL interpreter in PyCharm

Settings → Python Interpreter → AddWSL → select your distro (Ubuntu) and the Python path (or Conda env).

4) Test notebooks and packages

Open a .ipynb file and run a few cells. Install missing packages via the interpreter manager.

Jupyter notebooks in PyCharm

  • Open or create a .ipynb file to use the built-in notebook editor
  • Select the correct interpreter (Conda/venv/WSL) for the kernel
  • Use the variable viewer and charts for quick inspection

Troubleshooting tips

  • Interpreter not detected: re-add via Settings → Python Interpreter → Add
  • Can't import numpy: confirm you're using the right interpreter for the project
  • Slow indexing: exclude large data folders from the project
  • WSL connection errors: ensure WSL is running and distro is initialized

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