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Pandas: Select first 2 rows, 2 columns and specific two columns of a given dataframe


Write a Pandas program to select first 2 rows, 2 columns and specific two 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 first 2 rows:")
print(w_a_con.iloc[:2])
print("\nSelect first 2 columns:")
print(w_a_con.iloc[:,:2].head())
print("\nSelect 2 specific columns:")
print(w_a_con[['Display Value', 'Year']])

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 first 2 rows:
   Year       WHO region   Country Beverage Types  Display Value
0  1986  Western Pacific  Viet Nam           Wine            0.0
1  1986         Americas   Uruguay          Other            0.5

Select first 2 columns:
   Year       WHO region
0  1986  Western Pacific
1  1986         Americas
2  1985           Africa
3  1986         Americas
4  1987         Americas

Select 2 specific columns:
    Display Value  Year
0            0.00  1986
1            0.50  1986
2            1.62  1985
3            4.27  1986
4            1.98  1987
5            0.00  1987
6            0.13  1987
7            0.39  1985
8            1.55  1986
9            6.10  1984
10           0.20  1987
11           0.62  1989
12           0.00  1985
13           0.00  1984
14           0.05  1985
15           0.07  1987
16           0.06  1984
17           2.23  1989
18           1.62  1984
19           1.08  1984
20           0.00  1986
21           4.51  1989
22           2.67  1984
23           0.44  1984
24            NaN  1985
25           0.00  1984
26           1.36  1985
27           2.22  1984
28           0.11  1987
29            NaN  1986
..            ...   ...
70           1.02  1986
71           0.57  1985
72           0.00  1987
73           0.01  1986
74           2.06  1986
75           0.00  1989
76           0.02  1985
77           0.01  1985
78           0.00  1989
79           2.09  1989
80           0.84  1985
81           2.54  1985
82           2.25  1987
83            NaN  1986
84           0.00  1986
85           0.01  1985
86           1.83  1986
87           0.01  1989
88           0.42  1987
89           0.70  1986
90           0.01  1989
91           4.43  1989
92           0.00  1986
93            NaN  1987
94           3.06  1985
95           0.00  1984
96           7.38  1985
97           0.00  1984
98           0.00  1984
99           0.00  1985

[100 rows x 2 columns]

Click to download world_alcohol.csv

Python Code Editor:


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