import matplotlib.pyplot as plt

x = [2015, 2016, 2017, 2018, 2019, 2020, 2021] y = [1, 2, 5, 10, 21, 40, 54]

plt.plot(x, y) plt.show()

plt.plot(x, y, marker='o', linestyle='--', color='g') plt.show()

plt.plot(x, y, marker='o', linestyle='--', color='g') plt.xlabel('Years') plt.ylabel('Revenue') plt.title('Revenue per year') plt.show()

x = ['Data Science', 'Web Development', 'Mobile Development'] y = [400, 500, 250] plt.bar(x, y) plt.show()

prices = [1000, 2300, 3001, 3450, 4200, 4780, 5100, 5500, 6000, 7500] bins = [1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000] plt.hist(prices, bins) plt.show()

x = [2015, 2016, 2017, 2018, 2019, 2020, 2021] y = [1, 2, 5, 10, 21, 40, 54] plt.scatter(x, y) plt.show()

import pandas as pd df = pd.read_csv('/work/StudentsPerformance.csv') df.head()

df.columns

bins=[0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] plt.hist(df['math score'], bins) plt.xlabel('Math score') plt.ylabel('Number of students') plt.show()

y = df['math score'] x = df['reading score']

plt.scatter(x, y) plt.xlabel('Math score') plt.ylabel('Reading score') plt.show()