Pandas: Selecting consecutive columns, rows
Write a Pandas program to select consecutive columns and also select rows with Index label 0 to 9 with some columns 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("\nSelect consecutive columns:")
print(w_a_con.loc[:,"Country":"Display Value"].head())
print("\nAlternate command:")
print(w_a_con.iloc[:,2:5].head())
print("\nSelect rows with Index label 0 to 9 with specific columns:")
print(w_a_con.loc[0:9,["Year","Country","Display Value"]])
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] Select consecutive columns: Country Beverage Types Display Value 0 Viet Nam Wine 0.00 1 Uruguay Other 0.50 2 Cte d'Ivoire Wine 1.62 3 Colombia Beer 4.27 4 Saint Kitts and Nevis Beer 1.98 Alternate command: Country Beverage Types Display Value 0 Viet Nam Wine 0.00 1 Uruguay Other 0.50 2 Cte d'Ivoire Wine 1.62 3 Colombia Beer 4.27 4 Saint Kitts and Nevis Beer 1.98 Select rows with Index label 0 to 9 with specific columns: Year Country Display Value 0 1986 Viet Nam 0.00 1 1986 Uruguay 0.50 2 1985 Cte d'Ivoire 1.62 3 1986 Colombia 4.27 4 1987 Saint Kitts and Nevis 1.98 5 1987 Guatemala 0.00 6 1987 Mauritius 0.13 7 1985 Angola 0.39 8 1986 Antigua and Barbuda 1.55 9 1984 Nigeria 6.10
Click to download world_alcohol.csv
Python Code Editor:
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