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Cumulative Univariate Analysis

Cumulative Univariate Analysis

Continue learning plots that can be used to undertake univariate analysis when there are certain data attributes.

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Let’s extend our knowledge of univariate analysis with some advanced plots:

Cumulative histogram

A cumulative histogram is a graphical representation of the cumulative distribution of a numeric variable. It shows the cumulative frequency of the data points that are less than or equal to a certain value xx.

Advantages

Disadvantages

Can help us identify percentile values for a numeric variable

Can be tricky to identify specific values within a data set, as the focus is on the overall distribution of the data

Easy to interpret and aesthetically pleasing

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Cumulative histogram: Plotly Express

All we have to do is add a cumulative=True argument.

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# Import libraries
import plotly.express as px
import plotly.graph_objects as go
import pandas as pd
import numpy as np
# Import dataset
golf = pd.read_csv('/usr/local/csvfiles/driving_distances.csv')
# Create the plot
fig = px.histogram(data_frame=golf, 
                   x='avg_drive_distance',
                   cumulative=True)
# Show the plot
fig.show()

Cumulative histogram: Plotly graph objects

The process is the same. However, we can now add cumulative_enabled=True.

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# Import libraries
import plotly.express as px
import plotly.graph_objects as go
import pandas as pd
import numpy as np
# Import dataset
golf = pd.read_csv('/usr/local/csvfiles/driving_distances.csv')
# Create the plot
trace = go.Histogram(x=golf['avg_drive_distance'], 
                     histnorm='probability density',
                     cumulative_enabled=True)
# Add to the figure
fig = go.Figure(data=[trace])
# Show the plot
fig.show()

Empirical cumulative distribution function

An empirical cumulative distribution function (ECDF) is similar to a cumulative ...