Pandas: Find average consumption of wine per person greater than a given number
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'.
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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.
Python Code Editor:
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