MACHINE LEARNING RECIPES
DATA CLEANING PYTHON
DATA MUNGING
PANDAS CHEATSHEET
ALL TAGS
# How to find the grouped mean in numpy?

# How to find the grouped mean in numpy?

This recipe helps you find the grouped mean in numpy

How to find the grouped mean in numpy? Grouped mean as we all know that what is mean which nothing but the sum of all elements divided by total number of elements. A grouped is nothing but the mean of the data which is placed in intervals or we can say mean of grouped data. For this the individual values are not available and we are also not able to calculate there sum unlike the other listed data. For calculating the grouped mean firstly we have to determine the midpoint of each class then these midpoints is going to be multiplied with frequencies of the corresponding intervals or classes. Then the sum of the products divided by the total number of values will be the value of mean.

```
import numpy as np
```

```
Sample_array = np.array([[11,22,35],[45,55,65],[75,85,95]])
print("This is a Sample array:","\n",Sample_array)
```

This is a Sample array: [[11 22 35] [45 55 65] [75 85 95]]

```
print("The mean of each row is:","\n",Sample_array.mean(axis=1), "\n")
print("The mean of each column is:","\n",Sample_array.mean(axis=0))
```

The mean of each row is: [22.66666667 55. 85. ] The mean of each column is: [43.66666667 54. 65. ]

Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.

In this human activity recognition project, we use multiclass classification machine learning techniques to analyse fitness dataset from a smartphone tracker.

In this machine learning resume parser example we use the popular Spacy NLP python library for OCR and text classification.

In this deep learning project, we will predict customer churn using Artificial Neural Networks and learn how to model an ANN in R with the keras deep learning package.

In this project you will use Python to implement various machine learning methods( RNN, LSTM, GRU) for fake news classification.

In this NLP AI application, we build the core conversational engine for a chatbot. We use the popular NLTK text classification library to achieve this.

In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.

This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.

In this project, we are going to talk about Time Series Forecasting to predict the electricity requirement for a particular house using Prophet.

There are different time series forecasting methods to forecast stock price, demand etc. In this machine learning project, you will learn to determine which forecasting method to be used when and how to apply with time series forecasting example.