Python Matplotlib #dataanalytics #python3 #datascience #software

#Python #Matplotlib For #DataVisualization

Plot Types Matplotlib supports various plot types:-✈️

Here I have Share My experience to explain the different plot types supported by Matplotlib.

Line plots are used to display data points connected by straight lines. They're ideal for showing trends over time or continuous data.

x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]

Scatter plots display individual data points as markers on a 2D plane. They're useful for showing the relationship between two variables.
x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]

Bar plots use rectangular bars to represent data. They're commonly used to compare quantities across different categories.
categories = ['A', 'B', 'C', 'D']
values = [3, 7, 2, 5]

Histograms represent the distribution of numerical data. They divide the data into bins and show the frequency of data points in each bin.
import numpy as np

Box plots, also known as box-and-whisker plots, display the distribution of data based on five summary statistics: minimum, first quartile, median, third quartile, and maximum.

Pie charts represent data as slices of a circular graph, where each slice's size corresponds to its proportion of the whole.
sizes = [35, 30, 20, 15]
labels = ['A', 'B', 'C', 'D']