Pandas: Filtering records by multiple condition, Comparison, Arithmetic Operators in a given dataframe

Last update on April 04 2025 13:43:33 (UTC/GMT +8 hours)

13. High Consumption and Beer Filter

Write a Pandas program to find out the records where consumption of beverages per person average >=5 and Beverage Types is Beer from 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("\nThe world alcohol consumption details: average consumption of \nbeverages per person >=5 and Beverage Types is Beer:")
print(w_a_con[(w_a_con['Display Value'] >= 5) & (w_a_con['Beverage Types'] == 'Beer')].head(10))

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]

The world alcohol consumption details: average consumption of 
beverages per person >=5 and Beverage Types is Beer:
    Year WHO region         Country Beverage Types  Display Value
41  1986     Europe  Czech Republic           Beer           6.82

Click to download world_alcohol.csv

For more Practice: Solve these Related Problems:

• Write a Pandas program to filter records where 'Display Value' is greater than or equal to 5 and 'Beverage Types' exactly equals 'Beer', then count these records.
• Write a Pandas program to extract rows with consumption >= 5 for 'Beer' and then compute the sum of 'Display Value' for these entries.
• Write a Pandas program to select records with high consumption for Beer, and then group by 'Country' to calculate totals.
• Write a Pandas program to filter the dataset for 'Beer' with consumption above the threshold and then rank the records by 'Display Value'.

Python Code Editor:

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