Pandas: Filter by combine 2 logical operators in a given dataframe

Last update on April 04 2025 13:43:30 (UTC/GMT +8 hours)

19. Consumption Range Filtering

Write a Pandas program to filter all records where the average consumption of beverages per person from .5 to 2.50 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("\nFilter all records where the average consumption of beverages per person from .5 to 2.50.:")
print(w_a_con[(w_a_con['Display Value'] < 2.5) & (w_a_con['Display Value']>.5)].head())

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]

Filter all records where the average consumption of beverages per person from .5 to 2.50.:
    Year WHO region      ...      Beverage Types Display Value
2   1985     Africa      ...                Wine          1.62
4   1987   Americas      ...                Beer          1.98
8   1986   Americas      ...             Spirits          1.55
11  1989   Americas      ...                Beer          0.62
17  1989     Africa      ...                Beer          2.23

[5 rows x 5 columns]

Click to download world_alcohol.csv

For more Practice: Solve these Related Problems:

• Write a Pandas program to filter records where 'Display Value' lies between 0.5 and 2.50, inclusive, and then count the filtered rows.
• Write a Pandas program to extract rows with consumption in the range 0.5 to 2.50 and then compute the average 'Display Value'.
• Write a Pandas program to select records with 'Display Value' between 0.5 and 2.50 and then group by 'Year' to calculate sums.
• Write a Pandas program to filter the dataset for a specific consumption range and then sort the results by 'Country'.

Python Code Editor:

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