This is an example tutorial to use my module bhishan for the plotly extension for pandas.
import numpy as np
import pandas as pd
import seaborn as sns
import bhishan
from bhishan import bp
import matplotlib.pyplot as plt
%load_ext autoreload
%load_ext watermark
%autoreload 2
%watermark -a "Bhishan Poudel" -d -v -m
%watermark -iv
Bhishan Poudel 2020-09-28 CPython 3.7.7 IPython 7.18.1 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 json 2.0.9 numpy 1.18.4 autopep8 1.5.2 seaborn 0.11.0 bhishan 0.3.1 pandas 1.1.0
# print(sns.get_dataset_names())
df = sns.load_dataset('titanic')
df.bp.plot_boxplot_cats_num(['pclass','sex'],'age',show=True)
df.bp.countplot(['pclass','parch'],1,2)
df.bp.plot_count_cat('pclass',show=True)
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 0x7f9de1d1d8d0>
tips = sns.load_dataset('tips')
tips.bp.plot_pareto('size',thr=90)