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Pandas: Access every other column from a given dataframe

Pandas Filter: Exercise-26 with Solution

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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