Lambda expression in python and its usage in data science

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Python, the famous programming language created by Guido van Rossum is a muli-paradigm language. It supports Object Oriented programming, procedural programming, and functional programming.

According to Wikipedia,

Functional programming is a programming paradigm where programs are constructs by applying and composing functions.

Python follows these principles and the usage of functional programming in this language is by using the keyword lambda.

The lambda keyword is used to create an anonymous function that accepts any number of the argument. The signature of this function is :

lambda <parameter_list>: <expression_to_evaluate>

Example of lambda function:

list_name =['atangana','paul','amidou','omar','hasan']

list(map(lambda name : name.capitalize(), list_name))

In this example, we apply the lambda function

lambda name : name.capitalize() that take each word in list_name and capitalize it.

After discovering the lambda function, let's do some manipulation with it using the Malaria dataset in Africa download from Kaggle with this link.

After downloading this dataset, let's explore it with some useful pandas functions to know our data.

Apply head(), info() and describe() method

import pandas as pd
data = pd.read_csv('DatasetAfricaMalaria.csv')

data.head()
data.info()
data.describe()

Application of lambda function in Malaria dataset

List of the country in the dataset that the country name starts with "C"

filtering_cond = data['Country Name'].apply(lambda country: country.startswith('C'))
data[filtering_cond]
 

List of the country without malaria cases reported

filtering_cond = data['Malaria cases reported'].apply(lambda nbre_malaria_case: nbre_malaria_case==0) 
data[filtering_cond]

These two previous examples show you some applications of lambda function in python with a pandas data frame.

You can find the source code of this blog post here.