PLOTTING WITH PYPLOT II – HISTOGRAM, FREQUENCY DISTRIBUTION, BOXPLOTS (CLASS - XII) PART - 3

PLOTTING WITH PYPLOT II – HISTOGRAM, 

FREQUENCY DISTRIBUTION, BOXPLOTS

Chapter – 4 (PART -3)

Class – XII

Creating Box Plots:

The box plot has become the standard technique for presenting the 5-number summary which consists of:

1. The minimum range value

2. The maximum range value

3. The upper quartile

4. The lower quartile

5. The median

A box plot is used to show the range and middle half of ranked data. Ranked data is numerical data such as numbers etc. The middle half of the data is represented by the box. The highest and lowest scores are joined to the box by straight lines. The regions above the upper quartile and below the lower quartile each contain 25% of the data.

The five-number summary is shown in the diagram below.

Creating Boxplots with boxplot() of Pyplot:

The syntax of boxplot is:

matplotlib.pyplot.boxplot(x, notch = None, vert = None, meanline = None, showmeans = None,

showbox = None)

 

Parameters:

x	Array or a sequence of vectors. The input data.
notch	bool, optional (False); If True, will produce a notched box plot. Otherwise, a rectangular boxplot is produced.
vert	bool, optional (True); If True (default), makes the boxes vertical. If False, everything is drawn horizontally.
meanline	bool, optional (False); If True (and showmeans is True), will try to render the mean as a line spanning the full width of the box.
showbox	bool, optional (True); Show the central box.
showmeans	bool, optional (False); Show the arithmetic means.

Some examples of Boxplot:

1. Draw the plain boxplot
import numpy as np import matplotlib.pyplot as plt x = [5, 10, 15, 20, 30, 40, 65, 75, 90, 120, 150, 200, 250] plt.boxplot(x) plt.show()

2. Draw the boxplot with mean shown
import numpy as np import matplotlib.pyplot as plt x = [5, 10, 15, 20, 30, 40, 65, 75, 90, 120, 150, 200, 250] plt.boxplot(x, showmeans = True) plt.show()

3. Draw a notched boxplot
import numpy as np import matplotlib.pyplot as plt x = [5, 10, 15, 20, 30, 40, 65, 75, 90, 120, 150, 200, 250] plt.boxplot(x, showmeans = True, notch = True) plt.show()

4.Draw the boxplot without the central box
import numpy as np import matplotlib.pyplot as plt x = [5, 10, 15, 20, 30, 40, 65, 75, 90, 120, 150, 200, 250] plt.boxplot(x, showbox = False) plt.show()

Customizing/Adding Details to the Plots:

Use <matplotlib.pyplot>.title() to add title for your plot.

Use <matplotlib.pyplot>.xticks()/yticks() for setting xticks and yticks.

Use <matplotlib.pyplot>.xlim()/ylim() for setting xlimit and ylimit.

Use <matplotlib.pyplot>.xlabel()/ylabel() for setting x-axis label and y-axis label.

Use <matplotlib.pyplot>.legend() to add legends to our plot.

Question:Create a boxplot from the following set of data and (i) change the orientation to horizontal, (ii) Add title as ‘Horizontal Boxplot’, (iii) Y-axis title as ‘Value Range x = [44, 54, 65, 85, 110, 56, 97, 74, 96, 54, 64, 76, 94, 82, 73, 76]
Solution: import numpy as np import matplotlib.pyplot as plt x = [44, 54, 65, 85, 110, 56, 97, 74, 96, 54, 64, 76, 94, 82, 73, 76] plt.boxplot(x, vert = False, showmeans = True) plt.title("Horizontal Boxplot") plt.xlabel("Value Range") plt.show()

NOTE: This is the notes of Chapter - IV Plotting with Pyplot - II  - Histogram, Frequency, BoxPlots. It is important for every students, who are going to appear in Class - XII CBSE BOARD Exam as well as competitive level exam.

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