How to detect outliers using plotly in python?

Description

To create box plot to detect the outliers in a data set variable.

  • Read the data set.
  • Scaling the feature variables.
  • Initialize the box plot object form plotly
    library.
  • Declare the plotting variables.
  • Pass it into the go.box(variable).
  • Use py.iplot(variable) to create the box
    plot.
  • Box plot used to detect the outliers
    attributes in a variable.

#import plotly library

import plotly.plotly as py

import plotly.graph_objs as go

#import pandas library

import pandas as pd

#read the data set

data=pd.read_excel(‘/home/soft23/soft23/
Sathish/Pythonfiles/flyer.xlsx’)

df=pd.DataFrame(data)

#declare the variable

y0 = df[‘FlyingReturnsMiles’]

#assign into box plot object

trace0 = go.Box(y=y0)

#store it in a variable

#because plotting object takes 1 argument only

data1 = [trace0]

#plotting the variable

py.iplot(data1)

Source code(Two variable):

#import plotly library

import plotly.plotly as py

import plotly.graph_objs as go

#import pandas library

import pandas as pd

#read the data set

data=pd.read_excel(‘/home/soft23/soft23/http://slogix.in/
Sathish/Pythonfiles/flyer.xlsx’)

df=pd.DataFrame(data)

#declare the variable

y0 = df[‘FFP#’]

y1 = df[‘EnrollDuration’]

#assign into box plot object

trace0 = go.Box(y=y0)

trace1 = go.Box(y=y1)

#store it in a variable

#because plotting object takes 1 argument only

data1 = [trace0,trace1]

py.iplot(data1)

Leave Comment

Your email address will not be published. Required fields are marked *

clear formSubmit