Add Lables and Titles
Opgave
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- Add custom labels on the axes:
'Year'for the x-axis and'CO2 emission per person (metric tonnes)'for the y-axis. - Add title plot
'CO2 emissions (tonnes per person) in the USA and Canada'. - Initialize legend and display the plot.
Løsning
# 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)
# Create Figure and Axes objects
fig, ax = plt.subplots()
# Save data for the US and Canada
usa = data.loc['United States']
can = data.loc['Canada']
# Initialize the plot
ax.plot(usa.index.astype(int), usa.values, label = 'United States')
ax.plot(can.index.astype(int), can.values, label = 'Canada')
# Set custom labels on axis
ax.set_xlabel('Year')
ax.set_ylabel('CO2 emission per person (metric tonnes)')
# Add plot title
plt.title('CO2 emissions (tonnes per person) in the USA and Canada')
# Display the plot
plt.legend()
plt.show()
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Sektion 1. Kapitel 9
# 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)
# Create Figure and Axes objects
fig, ax = plt.subplots()
# Save data for the US and Canada
usa = data.loc['United States']
can = data.loc['Canada']
# Initialize the plot
ax.plot(usa.index.astype(int), usa.values, label = 'United States')
ax.plot(can.index.astype(int), can.values, label = 'Canada')
# Set custom labels on axis
ax.___('___')
___.___('___')
# Add plot title
___('CO2 emissions (tonnes per person) in the USA and Canada')
# Display the plot
plt.___()
___
