On the command line, navigate to the directory where you saved the wheel file which already has all the respective libraries included. There are two main options: Install a complete distribution like Anaconda, Canopy, WinPython, etc. Here I take NumPy as an example:ĭownload appropriate wheel file, in my case, for numpy, it is “numpy-1.10.1+mkl-cp34-none-win_amd64.whl” from the unofficial extension packages site Installing matplotlib through pip by automatically downloading the files from the python index as you're trying to do here will most probably fail for windows. The steps of installation of Numpy, SciPy, Pandas, and Matplotlib are the same.
#How to install matplotlib on windows how to#
Install NumPy, SciPy, Pandas, and Matplotlib How to install Python packages on Windows Some of our C++ programs require the installation of Python and two associated packagesNumPy and Matplotlib. You should downgrade to python 3. matplotlib hasn’t made a wheel yet for version 3.9 so your python attempted to build it from source. This step makes my life easier, because I don’t need to navigate to the scripts directory anytime I run ‘pip’ or ‘python’. Tongmeng118 Sorry but we do not offer matplotlib from an IBM webpage, but you can find it on below article. edit: matplotlib has now released wheels for python 3.9 so pip install -upgrade matplotlib should work. Please note, after installed Python, I added the ‘Scripts’ directory in Python package where the ‘pip.exe’ and ‘pip3.exe’ located, in my case the path is ‘C:\Python34\Scripts’, to the PATH environment variables. The steps described below would also work for 32-bit.
Thanks to Christoph Gohlke, who provides the non-official Python extension packages for Windows. With these unofficial packages, there is a simple way to install these libraries on Windows.įor clarity, I’m using Python 3.4.3 on 64-bit Windows 7. However, if you are using Python on Windows, it seems not easy to install these packages. NLTK (the Natural Language Toolkit) is a leading platform for building Python programs to work with human language data. Scikit-learn is a simple and efficient package for data mining and analysis in Python. NumPy, SciPy, Pandas, and Matplotlib are fundamental scientific computing and visualization packages with Python.
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