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Making matplotlib scatter plots from dataframes in Python's pandas
Using Pandas, we can create a dataframe and can create a figure and axes variable using subplot() method. After that, we can use the ax.scatter() method to get the required plot.
Steps
Make a list of the number of students.
Make a list of marks that have been obtained by the students.
To represent the color of each scattered point, we can have a list of colors.
Using Pandas, we can have a list representing the axes of the data frame.
Create fig and ax variables using subplots method, where default nrows and ncols are 1.
Set the “Students count” label using plt.xlabel() method.
Set the “Obtained marks” label using plt.ylabel() method.
To create a scatter point, use the data frame created in step 4. Points are students_count, marks and color.
To show the figure, use plt.show() method.
Example
from matplotlib import pyplot as plt
import pandas as pd
no_of_students = [1, 2, 3, 5, 7, 8, 9, 10, 30, 50]
marks_obtained_by_student = [100, 95, 91, 90, 89, 76, 55, 10, 3, 19]
color_coding = ['red', 'blue', 'yellow', 'green', 'red', 'blue', 'yellow', 'green', 'yellow', 'green']
df = pd.DataFrame(dict(students_count=no_of_students,
marks=marks_obtained_by_student, color=color_coding))
fig, ax = plt.subplots()
plt.xlabel('Students count')
plt.ylabel('Obtained marks')
ax.scatter(df['students_count'], df['marks'], c=df['color'])
plt.show()Output
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