Page 322 - Informatics_Practices_Fliipbook_Class12
P. 322
(viii) Retrieve the number of occurrences for each unique value in the Mode column.
(ix) Add a new column Energy Efficiency (kWh/km) to the DataFrame to be calculated as 1 / Fuel
Efficiency (km/l).
(x) Concatenate the DataFrame transportDF with a new DataFrame df2 in a row-wise manner.
(xi) Write the contents of the DataFrame transportDF to a CSV file named transport_details.csv.
(xii) Group the DataFrame by Mode and calculate the average values for each group.
(xiii) Drop the Fuel Efficiency (km/l) column from the DataFrame.
(xiv) Rename the column Speed (km/h) to Speed in km per hour.
Ans. (i) transportDF[['Mode', 'Capacity']]
(ii) transportDF[transportDF['Speed (km/h)'] > 50]
(iii) transportDF[transportDF['Fuel Efficiency (km/l)'] == 0]
(iv) transportDF.iloc[1:4]
(v) transportDF.index = ['A', 'B', 'C', 'D', 'E']
(vi) transportDF.describe()
(vii) transportDF['Speed (km/h)'].max()
(viii) transportDF['Mode'].value_counts()
(ix) transportDF['Energy Efficiency (kWh/km)'] = 1 / transportDF['Fuel Efficiency (km/l)']
(x) pd.concat([transportDF, df2], ignore_index=True)
(xi) transportDF.to_csv('transport_details.csv', index=False)
(xii) transportDF.groupby('Mode').mean()
(xiii) transportDF.drop(columns=['Fuel Efficiency (km/l)'], inplace=True)
(xiv) transportDF.rename(columns={'Speed (km/h)': 'Speed in km per hour'},
inplace=True)
Program 11: Consider the following dataset representing the monthly tax revenue collected by a government
department for a year (in lakhs): [500, 600, 550, 700, 800, 750, 900, 850, 950, 1000, 950, 1100]. Write a Python
program using Matplotlib to create a line plot to visualize the tax revenue trends. Provide appropriate labels for the
axis and title for the Figure. The Figure should comprise gridlines and should be saved as "taxRevenue.png".
Ans. import matplotlib.pyplot as plt
taxRevenue = [500, 600, 550, 700, 800, 750, 900, 850, 950, 1000, 950, 1100]
months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct',
'Nov', 'Dec']
plt.figure(figsize=(10, 6)) # Set the figure size
plt.plot(months, taxRevenue, marker='o', linestyle='-', color='b', label='Tax
Revenue (in lakhs)')
plt.xlabel('Months')
308 Touchpad Informatics Practices-XII

