Pandas: Filter by values using Boolean OR, AND Logic in a given dataframe
10. Dual Year-Region Filtering
Write a Pandas program to find out the alcohol consumption details in the year '1986' or '1989' where WHO region is 'Americas' 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 in the year '1986' or '1989' where WHO region is 'Americas' :")
print(w_a_con[((w_a_con['Year']==1986) | (w_a_con['Year']==1989)) & (w_a_con['WHO region']=='Americas')].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 in the year '1986' or '1989' where WHO region is 'Americas' :
Year WHO region ... Beverage Types Display Value
1 1986 Americas ... Other 0.50
3 1986 Americas ... Beer 4.27
8 1986 Americas ... Spirits 1.55
11 1989 Americas ... Beer 0.62
21 1989 Americas ... Spirits 4.51
47 1986 Americas ... Other 0.04
55 1989 Americas ... Wine 0.04
64 1989 Americas ... Beer 1.26
74 1986 Americas ... Spirits 2.06
78 1989 Americas ... Other 0.00
[10 rows x 5 columns]
Click to download world_alcohol.csv
For more Practice: Solve these Related Problems:
- Write a Pandas program to filter records for years 1986 or 1989 with 'Americas' region and then sort by 'Display Value'.
- Write a Pandas program to extract records for 1986 and 1989 where the 'Americas' region appears, and then compute the total consumption per year.
- Write a Pandas program to select records for years 1986 or 1989 with 'Americas' region and then group the results by country.
- Write a Pandas program to filter the dataset for the given years and region, and then calculate the average consumption for each beverage type.
Python Code Editor:
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