Table of Contents

• 1  Description
• 2  Imports
• 3  Load the data
• 4  Boxplots
• 5  Count plots
• 6  regplot
• 7  Pareto Chart

Description

This is an example tutorial to use my module bhishan for the plotly extension for pandas.

Imports

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

%load_ext autoreload
%load_ext watermark

%autoreload 2
%watermark -a "Bhishan Poudel" -d -v -m
%watermark -iv

Bhishan Poudel 2021-07-11 

CPython 3.7.7
IPython 7.22.0

compiler   : Clang 4.0.1 (tags/RELEASE_401/final)
system     : Darwin
release    : 19.6.0
machine    : x86_64
processor  : i386
CPU cores  : 4
interpreter: 64bit
pandas  1.2.4
seaborn 0.11.0
numpy   1.19.5

# my local library
import sys
sys.path.append("/Users/poudel/Dropbox/a00_Bhishan_Modules/")
sys.path.append("/Users/poudel/Dropbox/a00_Bhishan_Modules/bhishan")
from bhishan import bp

Load the data

# print(sns.get_dataset_names())

df = sns.load_dataset('titanic')

Boxplots

df.bp.plot_boxplot_cats_num(['pclass','sex'],'age',show=True)

Count plots

df.bp.countplot(['pclass','parch'],1,2)

df.bp.plot_count_cat('pclass',show=True)

regplot

df = sns.load_dataset('titanic')
df.head(2)

	survived	pclass	sex	age	sibsp	parch	fare	embarked	class	who	adult_male	deck	embark_town	alive	alone
0	0	3	male	22.0	1	0	7.2500	S	Third	man	True	NaN	Southampton	no	False
1	1	1	female	38.0	1	0	71.2833	C	First	woman	False	C	Cherbourg	yes	False

df = sns.load_dataset('titanic')
cols1 = ['fare','age']
cols2 = ['age','fare']
target = 'survived'
df.bp.regplot_binn(cols1,cols2,target,1,2)

sns.lmplot(x='age',y='fare',data=df,hue='survived')

<seaborn.axisgrid.FacetGrid at 0x7fa2b18f1910>

Pareto Chart

tips = sns.load_dataset('tips')
tips.bp.plot_pareto('size',thr=90)