How to rank items in a multidimensional array using numpy?

This recipe helps you rank items in a multidimensional array using numpy

Recipe Objective

How to rank items in a multidimensional array using numpy? This is also done in case of multidimensional array by using "matrix_rank". Lets understand this with practical implementation.

Step 1 - Import library

import numpy as np

Step 2 - Take a Sample array

Sample_array = np.array([[22,33,4],[55,66,77],[88,99,11],[98,76,54]]) print("This is a Sample array:","\n",Sample_array)
This is a Sample array: 
 [[22 33  4]
 [55 66 77]
 [88 99 11]
 [98 76 54]]

Step 3 - Get the rank

np.linalg.matrix_rank(Sample_array)
3

What Users are saying..

profile image

Ameeruddin Mohammed

ETL (Abintio) developer at IBM
linkedin profile url

I come from a background in Marketing and Analytics and when I developed an interest in Machine Learning algorithms, I did multiple in-class courses from reputed institutions though I got good... Read More

Relevant Projects

Deep Learning Project for Time Series Forecasting in Python
Deep Learning for Time Series Forecasting in Python -A Hands-On Approach to Build Deep Learning Models (MLP, CNN, LSTM, and a Hybrid Model CNN-LSTM) on Time Series Data.

ML Model Deployment on AWS for Customer Churn Prediction
MLOps Project-Deploy Machine Learning Model to Production Python on AWS for Customer Churn Prediction

Demand prediction of driver availability using multistep time series analysis
In this supervised learning machine learning project, you will predict the availability of a driver in a specific area by using multi step time series analysis.

End-to-End Snowflake Healthcare Analytics Project on AWS-2
In this AWS Snowflake project, you will build an end to end retraining pipeline by checking Data and Model Drift and learn how to redeploy the model if needed

Many-to-One LSTM for Sentiment Analysis and Text Generation
In this LSTM Project , you will build develop a sentiment detection model using many-to-one LSTMs for accurate prediction of sentiment labels in airline text reviews. Additionally, we will also train many-to-one LSTMs on 'Alice's Adventures in Wonderland' to generate contextually relevant text.

Learn Hyperparameter Tuning for Neural Networks with PyTorch
In this Deep Learning Project, you will learn how to optimally tune the hyperparameters (learning rate, epochs, dropout, early stopping) of a neural network model in PyTorch to improve model performance.

Build a Graph Based Recommendation System in Python-Part 2
In this Graph Based Recommender System Project, you will build a recommender system project for eCommerce platforms and learn to use FAISS for efficient similarity search.

Learn How to Build PyTorch Neural Networks from Scratch
In this deep learning project, you will learn how to build PyTorch neural networks from scratch.

Deep Learning Project for Beginners with Source Code Part 1
Learn to implement deep neural networks in Python .

MLOps Project to Deploy Resume Parser Model on Paperspace
In this MLOps project, you will learn how to deploy a Resume Parser Streamlit Application on Paperspace Private Cloud.

OSZAR »