String Methods—Concatenate and Match

Learn about the pandas string methods used for concatenation and pattern matching.

Introduction

Let's continue exploring the commonly used advanced transformations that can be applied to string values. In particular, we’ll dive into the methods that allow us to concatenate and match string values. As before, we’ll use the mock customer dataset from an e-commerce platform.

Preview of Mock E-Commerce Customer Dataset

customer_id

title

first_name

last_name

ip_address

email

264-42-4576

Mr

gino

Crowdson

82.48.134.48/5

gcrowdson0@tamu.edu

165-49-2539

Ms

hailey

kirsche

61.122.97.13/13

ekirsche1@rambler.ru

763-23-7634

Dr

Viviyan

Peschet

253.140.11.162/2

rpeschet@ning.com

Note that the columns in the DataFrame for this dataset have already been converted into StringDtype.

Concatenate

Joining strings is a common operation to perform for string values, and the cat() string method allows us to do so. For instance, we can concatenate the first_name and last_name columns to create a new full_name column with white space between the names, as shown below:

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# Concatenate first and last names

df['full_name'] = df['first_name'].str.cat(others=df['last_name'],

                                           sep=' ')



# View output

print(df[['full_name', 'first_name', 'last_name']])

If null values are present, we can use the na_rep parameter to specify the string to replace them. The last row in the output below illustrates how the null value in the first_name column was replaced with another string ('unknown') in the ...

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