Pandas: Filtering records by multiple condition, Comparison, Arithmetic, Boolean Operators in a given dataframe
Write a Pandas program to find out the records where consumption of beverages per person average >=4 and Beverage Types is Beer, Wine, Spirits 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 >=4 and Beverage Types is Beer:")
print(w_a_con[(w_a_con['Display Value'] >= 4) & ((w_a_con['Beverage Types'] == 'Beer') | (w_a_con['Beverage Types'] == 'Wine')| (w_a_con['Beverage Types'] == 'Spirits'))].head(10))
Sample Output:
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 >=4 and Beverage Types is Beer: Year WHO region Country Beverage Types Display Value 3 1986 Americas Colombia Beer 4.27 21 1989 Americas Costa Rica Spirits 4.51 41 1986 Europe Czech Republic Beer 6.82 57 1989 Europe Croatia Wine 5.10 91 1989 Europe Bulgaria Beer 4.43 96 1985 Europe Luxembourg Wine 7.38
Click to download world_alcohol.csv
Python Code Editor:
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