Pandas: Find average consumption of wine per person greater than a given number

Last update on April 04 2025 13:43:00 (UTC/GMT +8 hours)

20. Wine Consumption Analysis

Write a Pandas program to find average consumption of wine per person greater than 2 in world alcohol consumption dataset.

Test Data:

   Year       WHO region                Country Beverage Types  Display Value
0  1986  Western Pacific               Viet Nam           Wine           0.00
1  1986         Americas                Uruguay          Other           0.50
2  1985           Africa           Cte d'Ivoire           Wine           1.62
3  1986         Americas               Colombia           Beer           4.27
4  1987         Americas  Saint Kitts and Nevis           Beer           1.98   

Sample Solution:

Python Code :

import pandas as pd
# World alcohol consumption data
w_a_con = pd.read_csv('world_alcohol.csv')
print("World alcohol consumption sample data:")
print(w_a_con.head())
print("\nAverage consumption of wine per person greater than 2:")
print(w_a_con[(w_a_con['Beverage Types'] == 'Wine') & (w_a_con['Display Value'] > .2)].count())

Sample Output:

World alcohol consumption sample data:
   Year       WHO region      ...      Beverage Types Display Value
0  1986  Western Pacific      ...                Wine          0.00
1  1986         Americas      ...               Other          0.50
2  1985           Africa      ...                Wine          1.62
3  1986         Americas      ...                Beer          4.27
4  1987         Americas      ...                Beer          1.98

[5 rows x 5 columns]

Average consumption of wine per person greater than 2:
Year              9
WHO region        9
Country           9
Beverage Types    9
Display Value     9
dtype: int64

Click to download world_alcohol.csv

For more Practice: Solve these Related Problems:

• Write a Pandas program to filter records where 'Beverage Types' is 'Wine' and 'Display Value' is greater than 2, then list the countries in descending order of consumption.
• Write a Pandas program to extract rows for 'Wine' with consumption above 2 and then calculate the mean consumption grouped by 'WHO region'.
• Write a Pandas program to select wine records with 'Display Value' >2 and then pivot the data to show consumption per year.
• Write a Pandas program to filter the dataset for wine with high consumption and then rank the countries based on 'Display Value'.

Python Code Editor:

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