Python

importerror: missing required dependencies [‘numpy’] ( Lets Fix )

importerror: missing required dependencies [‘numpy’] error occurs mainly because of incompatibility of NumPy module in any python library. In this article, we will practically see some scenarios where we face this issue and also explore the best ways to fix this.

importerror: missing required dependencies [‘numpy’] ( Root Cause and Fix ) –

As we mentioned this Importerror is because of the incompatibility of the NumPy module inside any python module. The best way to fix this issue is to uninstall the current NumPy package and reinstall the latest version. Some time upgrading of the NumPy version also works fine.

Solution 1: Reinstalling numpy –

We can either use a pip package manager to install the NumPy module.

pip uninstall numpy
pip install numpy

 

Solution 2: Upgrading the Numpy package –

if you do not want to install the current Numpy package, upgrading is also a good path. Here is the command to upgrade the Numpy package.

pip install --upgrade numpy

If you have the latest version already installed in the system, Then upgrading will not make any changes. Just like the below scenario-

importerror missing required dependencies [‘numpy’]

Solution 3: Using Python3 -m

specifically, this solution will work in Python 3 , Please use the below command-

python3 -m pip uninstall numpy

 

Solution 4: Using conda package manager-

Similar to pip package manager , we have conda in Anaconda distribution.

conda install -c anaconda numpy

 

importerror: missing required dependencies [‘numpy’] ( Real Scenarios )-

suppose you are installing the Keras library which is built on top of NumPy and pandas libraries. Suppose if you are installing Keras and facing an incompatibility issue, The above solutions will work for you. Basically, what’s happens if you see the develop branch for such modules, It clearly says which module version should be there for a successful installation. If older is already existing then it first removes and reinstalls the required one. But sometimes the complete process goes in bad directions and we end up with this error.

 

Thanks
Data Science Learner Team