In this article, we will discuss how to fix the No module named numpy using Python.
Numpy is a module used for array processing. The error “No module named numpy ” will occur when there is no NumPy library in your environment i.e. the NumPy module is either not installed or some part of the installation is incomplete due to some interruption. We will discuss how to overcome this error.
In Python, we will use pip function to install any module
Syntax:
pip install module_name
Example: How to install NumPy
pip install numpy
Output:
Collecting numpy
Downloading numpy-3.2.0.tar.gz (281.3 MB)
|████████████████████████████████| 281.3 MB 9.7 kB/s
Collecting py4j==0.10.9.2
Downloading py4j-0.10.9.2-py2.py3-none-any.whl (198 kB)
|████████████████████████████████| 198 kB 52.8 MB/s
Building wheels for collected packages: numpy
Building wheel for numpy (setup.py) … done
Created wheel for numpy: filename=numpy-3.2.0-py2.py3-none-any.whl size=281805912 sha256=c6c9edb963f9a25f31d11d88374ce3be6b3c73ac73ac467ef40b51b5f4eca737
Stored in directory: /root/.cache/pip/wheels/0b/de/d2/9be5d59d7331c6c2a7c1b6d1a4f463ce107332b1ecd4e80718
Successfully built numpy
Installing collected packages: py4j, numpy
Successfully installed py4j-0.10.9.2 numpy-3.2.0
We can verify by again typing same command then output will be:
Output:
Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (1.1.5)
To get the numpy description like the current version in our environment we can use show command
Example: To get NumPy description
pip show numpy
Output:
Name: numpy
Version: 1.19.5
Summary: NumPy is the fundamental package for array computing with Python.
Home-page: https://www.numpy.org
Author: Travis E. Oliphant et al.
Author-email: None
License: BSD
Location: /usr/local/lib/python3.7/dist-packages
Requires:
Required-by: yellowbrick, xgboost, xarray, wordcloud, torchvision, torchtext, tifffile, thinc, Theano-PyMC, tensorflow, tensorflow-probability, tensorflow-hub, tensorflow-datasets, tensorboard, tables, statsmodels, spacy, sklearn-pandas, seaborn, scs, scipy, scikit-learn, scikit-image, resampy, qdldl, PyWavelets, python-louvain, pystan, pysndfile, pymc3, pyerfa, pyemd, pyarrow, plotnine, patsy, pandas, osqp, opt-einsum, opencv-python, opencv-contrib-python, numexpr, numba, nibabel, netCDF4, moviepy, mlxtend, mizani, missingno, matplotlib, matplotlib-venn, lightgbm, librosa, Keras-Preprocessing, kapre, jpeg4py, jaxlib, jax, imgaug, imbalanced-learn, imageio, hyperopt, holoviews, h5py, gym, gensim, folium, fix-yahoo-finance, fbprophet, fastprogress, fastdtw, fastai, fa2, ecos, daft, cvxpy, cufflinks, cmdstanpy, cftime, Bottleneck, bokeh, blis, autograd, atari-py, astropy, arviz, altair, albumentations
The installation remains same for all other operating systems and software just the platform changes. If our installation is successful any NumPy code will work fine
Example: Program to create a NumPy array and display
Python3
#import module import numpy # create an numpy array with 5 elements data = numpy.array([ 1 , 2 , 3 , 4 , 5 ]) # display data |
Output:
array([1, 2, 3, 4, 5])