I tried to install Pandas on my Windows 10 laptop using pip, but I'm getting an Error: "could not build wheels for pandas, which is required to install pyproject.toml-based projects," it typically indicates a problem with building the required wheels for the Pandas library during installation, this error commonly occurs when attempting to install a Python package that has a dependency on Pandas.

One possible solution to this issue is to ensure that the necessary development tools and dependencies are installed on your system. Sometimes, missing or outdated dependencies can prevent the successful building of Pandas wheels.

To solve issue, you can try the below steps:

  1. Ensure that you have the latest version of pip installed by running:
    pip install --upgrade pip
  2. Make sure that you have the required development tools and libraries installed on your system. On Linux, you can typically install them using your package manager. For example, on Ubuntu or Debian-based systems, you can run:
    sudo apt-get install build-essential python3-dev
  3. Try installing Pandas separately before installing the package that depends on it. You can do this by running:
    pip install pandas
  4. If you're still encountering the error, consider using a virtual environment to isolate your Python environment and dependencies. This can help prevent conflicts between different packages and versions. You can create a virtual environment using the following commands:
    python -m venv myenv
    source myenv/bin/activate
  5. Once inside the virtual environment, try installing the package again using pip. Remember to install Pandas separately if it's a dependency:
    pip install <package_name>


When we encountered the same issue, we found a solution in the Prophet documentation. The command that worked for us was:

python -m pip install prophet

Using python -m at the beginning of the pip command helped resolve the problem.

Additionally, we followed another solution provided by downloading the Microsoft C++ Build Tools. We installed them and clicked on the button near Microsoft C++ Build Tools to specify which exact components to install. After rebooting our Win 11, we were able to install the needed Python module. Our computer was entirely clean of C++ stuff, and doing this solved our problem when running pip install TTS.


We encountered an error related to Microsoft Visual C++ before encountering the wheel error for Pandas. To resolve this, we followed these steps:

  1. We installed Microsoft Visual C++.
  2. After installing Microsoft Visual C++, we used pip install pandas to install the Pandas package without encountering any errors.
  3. Then, we proceeded to install another package, pip install transform, and encountered no errors during this installation either.
  4. We also ensured that we were using 64-bit Python instead of 32-bit Python. This is important because Pandas does not provide 32-bit wheels for Python 3.10. While they have win32 wheels for Python 3.8 and Python 3.9, installing Pandas from source on a 32-bit system can be a difficult task and cannot be done directly within pip.
  5. If your system is capable of running 64-bit Python, we highly recommend switching to it to avoid compatibility issues with Pandas and other packages.

It addresses potential issues related to Microsoft Visual C++ dependencies and ensures compatibility with Pandas by using 64-bit Python. By installing Microsoft Visual C++ and switching to 64-bit Python, we were able to install Pandas and other packages without encountering any errors.


I;m also getting error "ERROR: Failed building wheel for numpy , ERROR: Could not build wheels for numpy, which is required to install pyproject.toml-based projects",install numpy in my system.We solved the issue by following these steps:

  1. We updated the pyproject.toml file, which contains all the library, dependency, and dev dependency information, with the version of NumPy that we installed using the pip install numpy command.
  2. We ran poetry lock to update the poetry.lock file, which contains detailed information about the library.
  3. Then, we ran poetry install again, and it worked fine.

It ensures that the project's dependencies are correctly specified and aligned with the installed versions. Updating the pyproject.toml file with the exact version of NumPy that was installed helps prevent version conflicts and ensures consistency across environments. 

Running poetry lock updates the lock file with the resolved versions of all dependencies, providing a stable environment for installation. Finally, running poetry install installs the dependencies according to the updated lock file, resolving any issues and ensuring that the project is set up correctly.