Problem Formulation

Given the following DataFrame df:

import pandas as pd df = pd.DataFrame([{'A':1, 'B':2, 'C':2, 'D':4}, {'A':4, 'B':8, 'C':3, 'D':1}, {'A':2, 'B':7, 'C':1, 'D':2}, {'A':3, 'B':5, 'C':1, 'D':2}]) print(df) ''' A B C D

0 1 2 2 4

1 4 8 3 1

2 2 7 1 2

3 3 5 1 2 '''

Challenge: How to apply a function f to each cell in the DataFrame?

For example, you may want to apply a function that replaces all odd values with the value 'odd'.

import pandas as pd df = pd.DataFrame([{'A':1, 'B':2, 'C':2, 'D':4}, {'A':4, 'B':8, 'C':3, 'D':1}, {'A':2, 'B':7, 'C':1, 'D':2}, {'A':3, 'B':5, 'C':1, 'D':2}]) def f(cell): if cell%2 == 1: return 'odd' return cell # ... <Apply Function f to each cell> ... print(df) ''' A B C D

0 odd 2 2 4

1 4 8 odd odd

2 2 odd odd 2

3 odd odd odd 2 '''

Solution: DataFrame applymap()

The Pandas DataFrame df.applymap() method returns a new DataFrame where the function f is applied to each cell of the original DataFrame df. You can pass any function object as a single argument into the df.applymap() function, either defined as a lambda expression or a normal function.

Example 1: Replace Odd Values in DataFrame

Here’s an example where each cell of the DataFrame is checked against whether it is an odd value. If so, it is replaced with the string 'odd':

def f(cell): if cell%2 == 1: return 'odd' return cell df_new = df.applymap(f) print(df_new) ''' A B C D

0 odd 2 2 4

1 4 8 odd odd

2 2 odd odd 2

3 odd odd odd 2 '''

Example 2: Create Two DataFrames with Even and Odd Values Replaced

A slightly advanced example uses two lambda functions to create two new DataFrames where one has all odd and the other has all even values replaced:

import pandas as pd df = pd.DataFrame([{'A':1, 'B':2, 'C':2, 'D':4}, {'A':4, 'B':8, 'C':3, 'D':1}, {'A':2, 'B':7, 'C':1, 'D':2}, {'A':3, 'B':5, 'C':1, 'D':2}]) df_even = df.applymap(lambda x: 'odd' if x%2 else x)

df_odd = df.applymap(lambda x: x if x%2 else 'even') print(df_even) ''' A B C D

0 odd 2 2 4

1 4 8 odd odd

2 2 odd odd 2

3 odd odd odd 2 ''' print(df_odd) ''' A B C D

0 1 even even even

1 even even 3 1

2 even 7 1 even

3 3 5 1 even '''

We used the concept of a ternary operator to concisely define the replacement function using the keyword lambda to create a function object “on the fly”.

Recommended Tutorial: Understanding the Ternary Operator in Python

This tutorial idea was proposed by Finxter student Kyriakos.

Email validation in PHP can be done in different ways. In general, a website will have client-side validation.

I prefer both client and server-side validation. It is applicable not only for emails but also to all inputs received from the end users. It will make the website more robust.

Validating email or other user inputs is a basic precautionary step before processing.

In this article, we will see how to validate email on the server-side. PHP provides various alternates to validate email with its built-in constants and functions. Some of them are listed below.

Ways to validate email in PHP

1. Using FILTER_VALIDATE_EMAIL.
2. Using pattern matching with regular expression.
3. By validating the domain name from the email address.

The following quick example uses PHP filter FILTER_VALIDATE_EMAIL. It is the best method of validating email in PHP.

<?php

$email = 'test@example.com';

isValidEmail($email); // using FILTER_VALIDATE_EMAIL - this is the best option to use in PHP

function isValidEmail($email)

{ return filter_var($email, FILTER_VALIDATE_EMAIL) !== false;

}

?>

Let us see other methods to validate email using PHP script.

Using FILTER_SANITIZE_EMAIL for input sanitization

The FILTER_SANITIZE_EMAIL is used to clean the email data submitted by the user.

In this example, the $email is hard coded with an example email address. You can supply email input from the form data posted to PHP using GET or POST methods.

It adds a prior step to sanitize the email data before validating its format. For validating the format of the sanitized email data, it uses FILTER_VALIDATE_EMAIL.

filter-sanitize-email.php

<?php

// this script explains the difference between FILTER_SANITIZE_EMAIL and FILTER_VALIDATE_EMAIL // validation is to test if an email is in valid email format and FILTER_VALIDATE_EMAIL should be used.

// sanitization is to clean an user input before using it in the program and FILTER_SANITIZE_EMAIL should be used.

$email = "test@example.com";

$cleanEmail = filter_var($email, FILTER_SANITIZE_EMAIL); // after sanitization use the email and check for valid email or not

if (filter_var($cleanEmail, FILTER_VALIDATE_EMAIL)) { // the email is valid and use it

}

?>

Using pattern matching with regular expression

If you are expecting a regex pattern to validate the email format, this example code will help.

This code has a regex pattern in a variable and is used to validate email with PHP preg_match().

In PHP, the preg_match() is for pattern matching with a given subject that is an email address here.

This code has the validateWithRegex() function to process the PHP email validation. It applies converts the input email string to lower case and trims before applying preg_match().

Then, it returns a boolean true if the match is found for the email regex pattern.

email-regex.php

<?php

validateWithRegex($email); // Using regular expression (regex). If for some reason you want to validate email via a regex use this

// function. The best way to validate is via FILTER_VALIDATE_EMAIL only.

function validateWithRegex($email)

{ $email = trim(strtolower($email)); // the regex I have used is from PHP version 8.1.7 which is used in php_filter_validate_email // reference: https://github.com/php/php-src/blob/PHP-...ers.c#L682 $emailRegex = '/^(?!(?:(?:\\x22?\\x5C[\\x00-\\x7E]\\x22?)|(?:\\x22?[^\\x5C\\x22]\\x22?)){255,})(?!(?:(?:\\x22?\\x5C[\\x00-\\x7E]\\x22?)|(?:\\x22?[^\\x5C\\x22]\\x22?)){65,}@)(?:(?:[\\x21\\x23-\\x27\\x2A\\x2B\\x2D\\x2F-\\x39\\x3D\\x3F\\x5E-\\x7E\\pL\\pN]+)|(?:\\x22(?:[\\x01-\\x08\\x0B\\x0C\\x0E-\\x1F\\x21\\x23-\\x5B\\x5D-\\x7F\\pL\\pN]|(?:\\x5C[\\x00-\\x7F]))*\\x22))(?:\\.(?:(?:[\\x21\\x23-\\x27\\x2A\\x2B\\x2D\\x2F-\\x39\\x3D\\x3F\\x5E-\\x7E\\pL\\pN]+)|(?:\\x22(?:[\\x01-\\x08\\x0B\\x0C\\x0E-\\x1F\\x21\\x23-\\x5B\\x5D-\\x7F\\pL\\pN]|(?:\\x5C[\\x00-\\x7F]))*\\x22)))*@(?:(?:(?!.*[^.]{64,})(?:(?:(?:xn--)?[a-z0-9]+(?:-+[a-z0-9]+)*\\.){1,126}){1,}(?:(?:[a-z][a-z0-9]*)|(?:(?:xn--)[a-z0-9]+))(?:-+[a-z0-9]+)*)|(?:\\[(?:(?:IPv6:(?:(?:[a-f0-9]{1,4}(?::[a-f0-9]{1,4}){7})|(?:(?!(?:.*[a-f0-9][:\\]]){7,})(?:[a-f0-9]{1,4}(?::[a-f0-9]{1,4}){0,5})?::(?:[a-f0-9]{1,4}(?::[a-f0-9]{1,4}){0,5})?)))|(?:(?:IPv6:(?:(?:[a-f0-9]{1,4}(?::[a-f0-9]{1,4}){5}:)|(?:(?!(?:.*[a-f0-9]:){5,})(?:[a-f0-9]{1,4}(?::[a-f0-9]{1,4}){0,3})?::(?:[a-f0-9]{1,4}(?::[a-f0-9]{1,4}){0,3}:)?)))?(?:(?:25[0-5])|(?:2[0-4][0-9])|(?:1[0-9]{2})|(?:[1-9]?[0-9]))(?:\\.(?:(?:25[0-5])|(?:2[0-4][0-9])|(?:1[0-9]{2})|(?:[1-9]?[0-9]))){3}))\\]))$/iDu'; if (preg_match($emailRegex, $email) === 1) { return true; } else { return false; }

}

?>

By validating the domain name from the email string

This method is a very simple one for validating email. It validates email by ensuring its host DNS validness.

It uses the PHP checkdnsrr() function to validate DNS by a hostname or the site IP address.

This function returns a boolean true if the host has any DNS records found. And thereby, the email in that host can be considered in a valid format.

It follows the below list of steps.

1. It extracts the domain name from the email.
2. It extracts the username prefixed before the @ symbol.
3. It ensures that the username and domain name are not empty.
4. It checks if the DNS details are not empty about the host extracted from the input email.

domain-validate-email.php

<?php // simplest custom email validation using email's domain validation

function validateEmail($email)

{ $isEmailValid = FALSE; if (! empty($email)) { $domain = ltrim(stristr($email, '@'), '@') . '.'; $user = stristr($email, '@', TRUE); // validate email's domain using DNS if (! empty($user) && ! empty($domain) && checkdnsrr($domain)) { $isEmailValid = TRUE; } } return $isEmailValid;

}

?>

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Problem Formulation and Solution Overview

In this article, you’ll learn how to ignore (upper/lower/title) case characters when dealing with Strings in Python.

The main reason for ignoring the case of a String is to perform accurate String comparisons or to return accurate search results.

For example, the following three (3) Strings are not identical. If compared with each other, they would return False.

This is because each character in the ASCII Table assigns different numeric values for each key or key combination on the keyboard.

This article outlines various ways to ignore the case of Strings.

Question: How would we write code to compare Strings?

We can accomplish this task by one of the following options:

• Method 1: Use a lower() and a lambda
• Method 2: Use upper() and List Comprehension
• Method 3: Use title()
• Method 4: Use casefold()
• Method 5: Use lower() and Dictionary Comprehension
• Bonus: Convert CSV of Full Names to title case

Method 1: Use lower() and a lambda

This method uses lower() and a lambda to convert a List of Strings to lower case to search for an Employee.

staff = ['Andy', 'MAci', 'SteVe', 'DarCY', 'Harvey']

staff_lower = list((map(lambda x: x.lower(), staff)))

print(staff_lower)

Above declares a List of Rivers Clothing Employees. If we were searching for an Employee, such as Darcy, using this List, no results would return as Darcy and DarCY are not the same. Let’s fix this issue.

Info: A lambda function is a one-liner that, in this case, converts each List element in staff to lower case. Then, converts to a map() object and back to a List. The output saves to staff_lower and is output to the terminal.

If a comparison was made now, it would find the correct Employee.

if ('Darcy'.lower() == staff_lower[3]): print('Match Found!')

Method 2: Use upper() and List Comprehension

This method uses upper() and a list comprehension to convert a List of Strings to upper case and search for an Employee.

brands = ['ChaNnel', 'CLINique', 'DIOR', 'Lancome', 'MurAD']

brands_upper = [x.upper() for x in brands]

print(brands_upper)

Above declares a List of the Top five (5) Beauty Brands in the world. If we were searching for a Company, such as Channel, using this List, no results would return as Channel and ChaNnel are not the same. Let’s fix this issue.

A List Comprehension is called and converts each element in brands to upper case. The results are saved to brands_upper and output to the terminal.

If a comparison was made now, it would find the correct Brand.

my_fav = 'Murad'

if (my_fav.upper() == brands_upper[4]): print(f'{my_fav} Found!')

Method 3: Use title()

This method uses title() to convert each word in a String to upper case. Great use of this is to convert a Full Name to title case. This ensures both the First, Middle and Last Names are as expected.

full_name = 'jessica a. barker'.title()

print(full_name)

Above accepts a string, appends the title() method to the string, saves it to full_name and outputs to the terminal.

Jessica A. Barker

Method 4: Use casefold() and a Dictionary

This method uses casefold() to convert a String to lower case. This method does more than lower(): it uses Unicode Case Folding Rules.

phrase = 'Nichts ist unmöglich für den Unwilligen!'

cfold = phrase.casefold()

print(cfold)

Above creates a quote in German and saves it to phrase. This ensures all characters are correctly converted to lower case, thus making a caseless match.

What does this say?

Method 5: Use lower() and Dictionary Comprehension

This method uses Use lower() to convert Dictionary values into lower case using Dictionary Comprehension.

employees = {'Sandy': 'Coder', 'Kevin': 'Network Specialist', 'Amy': 'Designer'}

result = {k: v.lower() for k, v in employees.items()}

print(result)

Above creates a Dictionary containing Rivers Employees Names and associated Job Title. This saves to employees.

Next, Dictionary Comprehension is used to loop through the values in the key:value Dictionary pairs and convert the values to lower case. The output saves to result and is output to the terminal.

Bonus: CSV Column to title() case

In this Bonus section, a CSV file you are working with contains a column of Full Names. You want to ensure all data entered in this column is in title() case. This can be accomplished by running the following code.

Contents of finxter_users.csv file

import pandas as pd users = pd.read_csv('finxter_users.csv')

users['Full_Name'] = users['Full_Name'].str.title()

print(users)

Above imports the Pandas library. For installation instructions, click here.

Next, the finxter_users.csv file (contents shown above) is read and saved to the DataFrame users.

The highlighted line directly accesses all values in the users['Full_Name'] column and converts each entry to title() case. This saves back to users['Full_Name'] and is output to the terminal.

Note: Don’t forget to save the DataFrame to keep the changes.

Summary

These six (6) methods of ignoring cases in Strings should give you enough information to select the best one for your coding requirements.

Programmer Humor

Question: Why do programmers always mix up Halloween and Christmas?
Answer: Because Oct 31 equals Dec 25.

(If you didn’t get this, read our articles on the oct() and int() Python built-in functions!)