Changing Line Style
Good! More customizing stuff to go!
Additionally, we can customize more line parameters, such as color, line style, points style. These are the simplest, but the .plot() function has many more parameters available to set (you can read about this in the documentation). Let's consider all of the mentioned parameters:
For example, let's modify our example plot even more!
1234567891011121314151617181920212223242526# Import the libraries import matplotlib.pyplot as plt import pandas as pd # Load the data data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/ed80401e-2684-4bc4-a077-99d13a386ac7/co2.csv', index_col = 0) # Filter the data ita = data.loc['Italy'] swe = data.loc['Sweden'] # Create Figure and Axes objects fig, ax = plt.subplots() # Initialize lines ax.plot(ita.index.astype(int), ita.values, label = 'Italy', color = 'green', marker = '1', linestyle = '--') ax.plot(swe.index.astype(int), swe.values, label = 'Sweden', color = 'blue', marker = 'v', linestyle = ':') # Add axis labels ax.set_xlabel('Year') ax.set_ylabel('CO2 emission level (tonnes per person)') # Display the legend, title, and plot plt.legend() plt.title('CO2 Emission Levels in Italy and Sweden') plt.show()
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Completion rate improved to 2.94Changing Line Style
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Good! More customizing stuff to go!
Additionally, we can customize more line parameters, such as color, line style, points style. These are the simplest, but the .plot() function has many more parameters available to set (you can read about this in the documentation). Let's consider all of the mentioned parameters:
For example, let's modify our example plot even more!
1234567891011121314151617181920212223242526# Import the libraries import matplotlib.pyplot as plt import pandas as pd # Load the data data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/ed80401e-2684-4bc4-a077-99d13a386ac7/co2.csv', index_col = 0) # Filter the data ita = data.loc['Italy'] swe = data.loc['Sweden'] # Create Figure and Axes objects fig, ax = plt.subplots() # Initialize lines ax.plot(ita.index.astype(int), ita.values, label = 'Italy', color = 'green', marker = '1', linestyle = '--') ax.plot(swe.index.astype(int), swe.values, label = 'Sweden', color = 'blue', marker = 'v', linestyle = ':') # Add axis labels ax.set_xlabel('Year') ax.set_ylabel('CO2 emission level (tonnes per person)') # Display the legend, title, and plot plt.legend() plt.title('CO2 Emission Levels in Italy and Sweden') plt.show()
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