# Data Science

## How to extract features using PCA in Python

How to extract features using PCA in Python Principal Component Analysis (PCA) is a technique used to reduce the dimensionality of a dataset. It does this by finding the directions in which the data varies the most, and representing the data in terms of these directions. By representing the data in this way, it can …

## How to reduce dimensionality using PCA in Python

How to reduce dimensionality using PCA in Python Principal Component Analysis (PCA) is a technique for dimensionality reduction that is commonly used in machine learning and data analysis. It works by identifying the directions (principal components) in the data that have the most variation and projecting the data onto these directions. By doing so, it …

## How to reduce dimensionality on Sparse Matrix in Python

How to reduce dimensionality on Sparse Matrix in Python One way to reduce the dimensionality of a sparse matrix in Python is by using the Singular Value Decomposition (SVD) technique. SVD is a matrix factorization method that can be used to decompose a matrix into three separate matrices: a matrix of singular values, a left …

## How to determine Spearman’s correlation in Python

How to determine Spearman’s correlation in Python Spearman’s correlation, also known as rank correlation, is a statistical method that is used to measure the strength of a monotonic relationship between two variables. It ranges from -1 to 1, where -1 indicates a strong negative correlation, 0 indicates no correlation, and 1 indicates a strong positive …

## How to determine Pearson’s correlation in Python

How to determine Pearson’s correlation in Python Pearson’s correlation is a statistical method that is used to measure the strength of a linear relationship between two variables. It ranges from -1 to 1, where -1 indicates a strong negative correlation, 0 indicates no correlation, and 1 indicates a strong positive correlation. In Python, we can …

## How to generate stacked BAR using Python

How to generate stacked BAR using Python Creating a stacked bar chart in Python is a great way to display the distribution of different categories of data. Here is an example of how you can create a stacked bar chart in Python using the popular library matplotlib: import matplotlib.pyplot as plt import numpy as np …

## How to generate grouped PIE plot using Python

How to generate grouped PIE plot using Python Creating a grouped pie chart in Python can be accomplished using the matplotlib library. The first step is to import the library and the necessary submodules for creating a pie chart. import matplotlib.pyplot as plt import numpy as np Next, you’ll need to create the data that …

## How to generate grouped BAR plot using Python

How to generate grouped BAR plot using Python A grouped bar plot is a way to visualize data by plotting multiple groups of rectangular bars together. Each group of bars represents a different category of the data, and the length of each bar represents the value of the data. Grouped bar plots are useful for …

## How to generate scatter plot using Python and Seaborn package

How to generate scatter plot using Python and Seaborn package

## How to generate time series data using Python and Seaborn package

How to generate time series data using Python and Seaborn package A time series is a series of data points collected at regular intervals of time. Time series data is commonly used in finance, economics, and other fields to track changes over time. There are various ways to generate time series data in Python, but …