Pandas: Access every other column from a given dataframe
Write a Pandas program to filter all records starting from the 'Year' column, access every other column 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("\nFrom the 'Year' column, access every other column:")
print(w_a_con.loc[:,'Year'::2].head(10))
print("\nAlternate solution:")
print(w_a_con.iloc[:,0::2].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] From the 'Year' column, access every other column: 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 Alternate solution: 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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Previous: Write a Pandas program to filter all columns where all entries present, check which rows and columns has a NaN and finally drop rows with any NaNs from world alcohol consumption dataset.
Next: Write a Pandas program to filter all records starting from the 2nd row, access every 5th row from world alcohol consumption dataset.
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