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Brainy Fact
You may create a figure with many plots known as subplots side by side sharing either the same x-axis or
same y-axis. Following is the code to create 3 subplots with shared y-axis:
fig, (ax1, ax2, ax3) = plt.subplots(1, 3, sharey=True)
Box Plot (Whisker Plot)
Box Plot represents the summary of the set of data values where a box is created for each having properties like
minimum, first quartile, median, third quartile and maximum. A vertical line goes through the box at the median.
Here x-axis denotes the data to be plotted while the y-axis shows the frequency distribution.
Box plots can also be used to plot outliers and these outliers are plotted outside the graph as dots or circles
since they do not belong to the range of data and are part of the graph for visualisation.
The six parts of the box plots are:
• First Quartile (Q1): From 0 percentile to 25th percentile: the middle number between the smallest number
and the median of the dataset.
• Second Quartile/Median (Q2): From 25th Percentile to 50th percentile: the middle value of the dataset
where 50th percentile is also termed as mean of the whole distribution.
• Third Quartile (Q3): From 50th percentile to 75th percentile: the middle value between the median and the
highest value of the dataset.
• Interquartile range (IQR): From 25th to 75th percentile.
• Fourth Quartile (whiskers plot): From 75th percentile to 100th percentile.
• Outliers: Shown as small circles scattered outside the box plots.
First quartile (25th percentile) Second quartile (75th percentile)
Q 1 Median Q 3
Min (Q1-1.5*IQR) Max (Q3+1.5*IQR)
Outliers Whisker Whisker
Interquartile range (IQR)
Matplotlib uses a built-in function boxplot() to create box plots. For example:
import matplotlib.pyplot as plt
eng = [82,76,24,40,67,62,78,67,72,82]
maths = [62,5,32,96,95,90,95,15,71,11]
science = [68,86,19,49,15,16,16,75,65,31]
Data Science 235

