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Matplotlib Exercises/Exercise 1 - Line Graph/Line Graph 1.py

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+from matplotlib import pyplot as plt
+
+x = [4, 8, 9]
+y = [10, 12, 15]
+plt.plot(x, y)
+plt.title("Line graph")
+plt.ylabel('Y axis')
+plt.xlabel('X axis')
+plt.show()

Matplotlib Exercises/Exercise 1 - Line Graph/Line Graph 2.py

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+from matplotlib import pyplot as plt
+from matplotlib import style
+
+style.use('ggplot')
+x = [16, 8, 10]
+y = [8, 16, 6]
+x2 = [8, 15, 11]
+y2 = [6, 15, 7]
+plt.plot(x, y, 'r', label='line one', linewidth=5)
+plt.plot(x2, y2, 'm', label='line two', linewidth=5)
+plt.title('Epic Info')
+fig = plt.figure()
+plt.ylabel('Y axis')
+plt.xlabel('X axis')
+plt.legend()
+plt.grid(True, color='k')
+plt.show()

Matplotlib Exercises/Exercise 2 - Bar Graph/Bar Graph 1.py

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+from matplotlib import pyplot as plt
+
+players = [ 'Ankit', 'Dhoni', 'Rohit','Shikhar']
+runs = [51,87,45,67]
+plt.bar(players,runs,color = 'green')
+plt.title('Score Card')
+plt.xlabel('Players')
+plt.ylabel('Runs')
+plt.show()

Matplotlib Exercises/Exercise 2 - Bar Graph/Bar Graph 2.py

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+from matplotlib import pyplot as plt
+
+players = ['Ankit', 'Dhoni', 'Rohit','Shikhar']
+runs = [51,87,45,67]
+plt.barh(players,runs, color = 'green')
+plt.title('Score Card')
+plt.xlabel('Players')
+plt.ylabel('Runs')
+plt.show()

Matplotlib Exercises/Exercise 3 - Histogram/Histogram 1.py

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+from matplotlib import pyplot as plt
+
+population_age = [21,53,60,49,25,27,30,42,40,1,2,102,95,8,15,105,70,65,55,70,75,60,52,44,43,42,45]
+bins = [0,10,20,30,40,50,60,70,80,90,100]
+plt.hist(population_age, bins, histtype='bar', rwidth=0.8)
+plt.xlabel('age groups')
+plt.ylabel('Number of people')
+plt.title('Histogram')
+plt.show()

Matplotlib Exercises/Exercise 3 - Histogram/Histogram 2.py

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+from matplotlib import pyplot as plt
+# Importing Numpy Library
+import numpy as np
+
+plt.style.use('fivethirtyeight')
+mu = 50
+sigma = 7
+x = np.random.normal(mu, sigma, size=200)
+fig, ax = plt.subplots()
+ax.hist(x, 20)
+ax.set_title('Historgram')
+ax.set_xlabel('bin range')
+ax.set_ylabel('frequency')
+fig.tight_layout()
+plt.show()

Matplotlib Exercises/Exercise 4 - Pie Chart/Pie Chart 1.py

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+from matplotlib import pyplot as plt
+
+# Pie chart, where the slices will be ordered and plotted counter-clockwise:
+Players = 'Ankit', 'Dhoni', 'Rohit', 'Yuvraj'
+Runs = [25, 30, 15, 10]
+explode = (0, 0.1, 0, 0) # it "explode" the 2nd slice
+fig1, ax1 = plt.subplots()
+ax1.pie(Runs, explode=explode, labels=Players, autopct='%1.1f%%', shadow=True, startangle=90)
+ax1.axis('equal') # Equal aspect ratio ensures that pie is drawn as a circle.
+plt.show()

Matplotlib Exercises/Exercise 5 - Scatter Plot/Scatter Plot 1.py

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+from matplotlib import pyplot as plt
+from matplotlib import style
+
+style.use('ggplot')
+x = [5, 7, 10]
+y = [18, 10, 6]
+x2 = [6, 9, 11]
+y2 = [7, 14, 17]
+plt.scatter(x, y)
+plt.scatter(x2, y2, color='g')
+plt.title('Epic Info')
+plt.ylabel('Y axis')
+plt.xlabel('X axis')
+plt.show()

Matplotlib Exercises/Exercise 5 - Scatter Plot/Scatter Plot 2.py

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+import matplotlib.pyplot as plt
+
+x = [2, 2.5, 3, 3.5, 4.5, 4.7, 5.0]
+y = [7.5, 8, 8.5, 9, 9.5, 10, 10.5]
+x1 = [9, 8.5, 9, 9.5, 10, 10.5, 12]
+y1 = [3, 3.5, 4.7, 4, 4.5, 5, 5.2]
+plt.scatter(x, y, label='high income low saving', color='g')
+plt.scatter(x1, y1, label='low income high savings', color='r')
+plt.xlabel('saving*100')
+plt.ylabel('income*1000')
+plt.title('Scatter Plot')
+plt.legend()
+plt.show()

Matplotlib Exercises/Exercise 6 - 3D Plot/3D Plot 1.py

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+from mpl_toolkits import mplot3d
+import numpy as np
+import matplotlib.pyplot as plt
+
+fig = plt.figure()
+ax = plt.axes(projection='3d')
+z = np.linspace(0, 1, 100)
+x = z * np.sin(20 * z)
+y = z * np.cos(20 * z)
+ax.plot3D(x, y, z, 'gray')
+ax.set_title('3D line plot')
+plt.show()