Adding One More Line

Quite good! That's a good visualization! Let's expand our chart with new data.

We may want to compare the emission levels by displaying several lines on a single chart. It can be easily done by calling the .plot() method of Axes object multiple times. For instance, if you call ax.plot() two times, you will get two lines on one chart. By default, the first line will be blue, the second one will be orange.


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# 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) 
ax.plot(swe.index.astype(int), swe.values)

# Display the plot
plt.show()

Everything was clear?

Thanks for your feedback!

Section 1. Chapter 4

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Course Content

Visualization in Python with matplotlib

Adding One More Line

Quite good! That's a good visualization! Let's expand our chart with new data.


              1234567891011121314151617181920
            
# 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) 
ax.plot(swe.index.astype(int), swe.values)

# Display the plot
plt.show()

Everything was clear?

Thanks for your feedback!

Section 1. Chapter 4