Pandas: Match if a given column has a particular sub string in a given dataframe

Last update on May 28 2022 13:40:10 (UTC/GMT +8 hours)

Pandas Filter: Exercise-16 with Solution

Write a Pandas program to filter those records where WHO region contains "Ea" substring 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())
# Remove NA / NaN values
new_w_a_con = w_a_con.dropna()
print("\nMatch if  a given column has a particular sub string:")
print(new_w_a_con[new_w_a_con["WHO region"].str.contains("Ea")])

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]

Match if  a given column has a particular sub string:
    Year             WHO region      ...      Beverage Types Display Value
13  1984  Eastern Mediterranean      ...               Other          0.00
20  1986        South-East Asia      ...                Wine          0.00
25  1984  Eastern Mediterranean      ...               Other          0.00
27  1984  Eastern Mediterranean      ...                Beer          2.22
36  1987  Eastern Mediterranean      ...                Beer          0.07
38  1987  Eastern Mediterranean      ...               Other          0.00
52  1986  Eastern Mediterranean      ...                Wine          0.00
53  1984  Eastern Mediterranean      ...                Beer          0.00
58  1984  Eastern Mediterranean      ...             Spirits          0.00
59  1989  Eastern Mediterranean      ...               Other          0.00
60  1987  Eastern Mediterranean      ...               Other          0.00
63  1985  Eastern Mediterranean      ...               Other          0.00
65  1989  Eastern Mediterranean      ...                Beer          0.00
66  1987  Eastern Mediterranean      ...                Wine          0.01
73  1986  Eastern Mediterranean      ...               Other          0.01
75  1989  Eastern Mediterranean      ...               Other          0.00
84  1986        South-East Asia      ...               Other          0.00
87  1989  Eastern Mediterranean      ...                Wine          0.01
88  1987  Eastern Mediterranean      ...                Beer          0.42
89  1986  Eastern Mediterranean      ...                Wine          0.70
97  1984        South-East Asia      ...                Wine          0.00
99  1985        South-East Asia      ...                Wine          0.00

[22 rows x 5 columns]

Click to download world_alcohol.csv

Python Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous: Write a Pandas program to filter the specified columns and records by range from world alcohol consumption dataset.

Next: Write a Pandas program to filter those records where WHO region matches with multiple values (Africa, Eastern Mediterranean, Europe) from world alcohol consumption dataset.

Python: Tips of the Day

Find current directory and file's directory:

To get the full path to the directory a Python file is contained in, write this in that file:

import os dir_path = os.path.dirname(os.path.realpath(__file__))

(Note that the incantation above won't work if you've already used os.chdir() to change your current working directory, since the value of the __file__ constant is relative to the current working directory and is not changed by an os.chdir() call.)

To get the current working directory use

import os cwd = os.getcwd()

Documentation references for the modules, constants and functions used above:

The os and os.path modules.

The __file__ constant

os.path.realpath(path) (returns "the canonical path of the specified filename, eliminating any symbolic links encountered in the path")

os.path.dirname(path) (returns "the directory name of pathname path")

os.getcwd() (returns "a string representing the current working directory")

os.chdir(path) ("change the current working directory to path")

Ref: https://bit.ly/3fy0R6m