Seaborn || sns

Distribution plots

distplot, joinplot, pairplot

import seaborn as sns
import numpy as np

df = sns.load_dataset("tips")

df.head()  # tip is dependent feature
           # others are independent features

	total_bill	tip	sex	smoker	day	time	size
0	16.99	1.01	Female	No	Sun	Dinner	2
1	10.34	1.66	Male	No	Sun	Dinner	3
2	21.01	3.50	Male	No	Sun	Dinner	3
3	23.68	3.31	Male	No	Sun	Dinner	2
4	24.59	3.61	Female	No	Sun	Dinner	4

df.dtypes

total_bill     float64
tip            float64
sex           category
smoker        category
day           category
time          category
size             int64
dtype: object

Correlation with Heatmap

df.corr() # correlarion can only be found out if values are floating point or integers

# corr values range b/w -1 to +1

	total_bill	tip	size
total_bill	1.000000	0.675734	0.598315
tip	0.675734	1.000000	0.489299
size	0.598315	0.489299	1.000000

Observations :- 1) +ve corr ->> Total bill inc then tip will also inc

sns.heatmap(df.corr())

<matplotlib.axes._subplots.AxesSubplot at 0x2d218d27108>

JointPlot

Univariate analysis

sns.jointplot(x='tip',y='total_bill',data=df,kind='hex') # hex=hexagonal shape

<seaborn.axisgrid.JointGrid at 0x2d219541988>

sns.jointplot(x='tip',y='total_bill',data=df,kind='reg') # reg gives probablity density line(on graph) and regression line (inside plot)

<seaborn.axisgrid.JointGrid at 0x2d2197b6d88>

Pair plot

same data row is matched with another variable's value

sns.pairplot(df, hue='sex')

<seaborn.axisgrid.PairGrid at 0x2d219f05bc8>

Dist Plot

sns.distplot(df['tip'])

<matplotlib.axes._subplots.AxesSubplot at 0x2d21a51bcc8>

sns.distplot(df['tip'],kde =False,bins=10)

<matplotlib.axes._subplots.AxesSubplot at 0x2d21a657dc8>

Categorical Plots

Count Plot

sns.countplot('sex',data=df)

<matplotlib.axes._subplots.AxesSubplot at 0x2d21a6d2688>

Bar Plot

sns.barplot(x='total_bill',y='sex',data=df)

<matplotlib.axes._subplots.AxesSubplot at 0x2d21b8f2788>

Box Plot

sns.boxplot('sex', 'total_bill', data=df)

<matplotlib.axes._subplots.AxesSubplot at 0x2d21b950348>

sns.boxplot(x='day', y='total_bill', data=df, palette='rainbow')

<matplotlib.axes._subplots.AxesSubplot at 0x2d21b9b9a48>

 sns.boxplot(data=df, orient='v')

<matplotlib.axes._subplots.AxesSubplot at 0x2d21baf1708>

 sns.boxplot(x='total_bill', y='day', hue='smoker', data=df)

<matplotlib.axes._subplots.AxesSubplot at 0x2d21bb73288>

Violin Plot

sns.violinplot(x="total_bill",y='day',data=df, palette='rainbow')

<matplotlib.axes._subplots.AxesSubplot at 0x2d21bc73488>