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

Pandas Filter: Exercise-20 with Solution

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

Python Code Editor:


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Previous: 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.
Next: Write a Pandas program to filter rows based on row numbers ended with 0, like 0, 10, 20, 30 from world alcohol consumption dataset.

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