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Pandas: Find and drop the missing values

Pandas Filter: Exercise-4 with Solution

Write a Pandas program to find and drop the missing values 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("\nMissing values:")
print(w_a_con.isnull())
print("\nDropping the missing values:")
print(w_a_con.dropna())

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]

Missing values:
     Year  WHO region  Country  Beverage Types  Display Value
0   False       False    False           False          False
1   False       False    False           False          False
2   False       False    False           False          False
3   False       False    False           False          False
4   False       False    False           False          False
5   False       False    False           False          False
6   False       False    False           False          False
7   False       False    False           False          False
8   False       False    False           False          False
9   False       False    False           False          False
10  False       False    False           False          False
11  False       False    False           False          False
12  False       False    False           False          False
13  False       False    False           False          False
14  False       False    False           False          False
15  False       False    False           False          False
16  False       False    False           False          False
17  False       False    False           False          False
18  False       False    False           False          False
19  False       False    False           False          False
20  False       False    False           False          False
21  False       False    False           False          False
22  False       False    False           False          False
23  False       False    False           False          False
24  False       False    False           False           True
25  False       False    False           False          False
26  False       False    False           False          False
27  False       False    False           False          False
28  False       False    False           False          False
29  False       False    False           False           True
..    ...         ...      ...             ...            ...
70  False       False    False           False          False
71  False       False    False           False          False
72  False       False    False           False          False
73  False       False    False           False          False
74  False       False    False           False          False
75  False       False    False           False          False
76  False       False    False           False          False
77  False       False    False           False          False
78  False       False    False           False          False
79  False       False    False           False          False
80  False       False    False           False          False
81  False       False    False           False          False
82  False       False    False           False          False
83  False       False    False           False           True
84  False       False    False           False          False
85  False       False    False           False          False
86  False       False    False           False          False
87  False       False    False           False          False
88  False       False    False           False          False
89  False       False    False           False          False
90  False       False    False           False          False
91  False       False    False           False          False
92  False       False    False           False          False
93  False       False    False           False           True
94  False       False    False           False          False
95  False       False    False           False          False
96  False       False    False           False          False
97  False       False    False           False          False
98  False       False    False           False          False
99  False       False    False           False          False

[100 rows x 5 columns]

Dropping the missing values:
    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   1987               Americas      ...               Other          0.00
6   1987                 Africa      ...                Wine          0.13
7   1985                 Africa      ...             Spirits          0.39
8   1986               Americas      ...             Spirits          1.55
9   1984                 Africa      ...               Other          6.10
10  1987                 Africa      ...                Wine          0.20
11  1989               Americas      ...                Beer          0.62
12  1985        Western Pacific      ...                Beer          0.00
13  1984  Eastern Mediterranean      ...               Other          0.00
14  1985        Western Pacific      ...             Spirits          0.05
15  1987                 Africa      ...                Wine          0.07
16  1984               Americas      ...                Wine          0.06
17  1989                 Africa      ...                Beer          2.23
18  1984                 Europe      ...             Spirits          1.62
19  1984                 Africa      ...                Beer          1.08
20  1986        South-East Asia      ...                Wine          0.00
21  1989               Americas      ...             Spirits          4.51
22  1984                 Europe      ...             Spirits          2.67
23  1984                 Europe      ...                Beer          0.44
25  1984  Eastern Mediterranean      ...               Other          0.00
26  1985                 Europe      ...                Wine          1.36
27  1984  Eastern Mediterranean      ...                Beer          2.22
28  1987        Western Pacific      ...                Beer          0.11
30  1986                 Africa      ...               Other          4.48
31  1986        Western Pacific      ...                Wine          0.00
..   ...                    ...      ...                 ...           ...
68  1989                 Africa      ...                Beer          0.12
69  1986                 Africa      ...             Spirits          0.42
70  1986                 Africa      ...             Spirits          1.02
71  1985                 Africa      ...               Other          0.57
72  1987                 Africa      ...               Other          0.00
73  1986  Eastern Mediterranean      ...               Other          0.01
74  1986               Americas      ...             Spirits          2.06
75  1989  Eastern Mediterranean      ...               Other          0.00
76  1985                 Africa      ...                Beer          0.02
77  1985                 Africa      ...             Spirits          0.01
78  1989               Americas      ...               Other          0.00
79  1989                 Europe      ...               Other          2.09
80  1985                 Africa      ...               Other          0.84
81  1985                 Europe      ...                Wine          2.54
82  1987                 Europe      ...             Spirits          2.25
84  1986        South-East Asia      ...               Other          0.00
85  1985                 Africa      ...                Wine          0.01
86  1986               Americas      ...                Wine          1.83
87  1989  Eastern Mediterranean      ...                Wine          0.01
88  1987  Eastern Mediterranean      ...                Beer          0.42
89  1986  Eastern Mediterranean      ...                Wine          0.70
90  1989                 Africa      ...                Wine          0.01
91  1989                 Europe      ...                Beer          4.43
92  1986                 Africa      ...             Spirits          0.00
94  1985                 Europe      ...             Spirits          3.06
95  1984                 Africa      ...               Other          0.00
96  1985                 Europe      ...                Wine          7.38
97  1984        South-East Asia      ...                Wine          0.00
98  1984                 Africa      ...                Wine          0.00
99  1985        South-East Asia      ...                Wine          0.00

[95 rows x 5 columns]

Click to download world_alcohol.csv

Python Code Editor:


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