Statistical data visualisation Technique

and also add iris data frame

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

Distribution Plot

Histplot

displot

Kernel Density Estimate

Distplot

Box plot

violinplot

figer size

pairplot

drop

heat map

join plot

$$

$$

sns.distplot(iris.SL) sns.displot(iris.SL) sns.histplot(iris.SL) sns.kdeplot(iris.SL) sns.boxplot(x = iris['Flower Type'],y = iris.PL, hue=y) sns.boxenplot(x=iris['Flower Type'],y=iris.PL,hue=) sns.violinplot(x=iris['Flower Type'],y=iris.SL) sns.swarmplot(x=iris['Flower Type'],y=iris.SL,) sns.stripplot(y=iris['Flower Type'],x=iris.SL) sns.barplot(y=iris['Flower Type'],x=iris.SL sns.pointplot(x=iris['Flower Type'],y=iris.SL, sns.scatterplot(x=iris.SL,y=iris.PL) sns.countplot(x=iris.SL,hue=iris['Flower'],width = 2) sns.pairplot(iris,hue = 'Flower Type' ) sns.heatmap(c,annot = True ) sns.jointplot(data=iris)

plt.figure(figsize = (15,10))