Pandas: Filter by values of specific Columns using Boolean OR , AND, OR Logic in a given dataframe
Write a Pandas program to find out the 'WHO region, 'Country', 'Beverage Types' in the year '1986' or '1989' where WHO region is 'Americas' or 'Europe' from the 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 ('WHO region','Country','Beverage Types') \nin the year ‘1986’ or ‘1989’ where WHO region is ‘Americas’ or 'Europe':")
print(w_a_con[((w_a_con['Year']==1985) | (w_a_con['Year']==1989)) & ((w_a_con['WHO region']=='Americas') | (w_a_con['WHO region']=='Europe'))][['WHO region','Country','Beverage Types']].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 ('WHO region','Country','Beverage Types') in the year ‘1986’ or ‘1989’ where WHO region is ‘Americas’ or 'Europe': WHO region ... Beverage Types 11 Americas ... Beer 21 Americas ... Spirits 26 Europe ... Wine 35 Americas ... Spirits 44 Europe ... Other 50 Europe ... Other 55 Americas ... Wine 57 Europe ... Wine 64 Americas ... Beer 78 Americas ... Other [10 rows x 3 columns]
Click to download world_alcohol.csv
Python Code Editor:
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Next: 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.What is the difficulty level of this exercise?
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