4 Powerful Ways to Split and Extract Data from Template Strings in Python

Introduction

In a recent discussion a fan asked how to split template strings that contain commas and brackets. The data example is shown below.

The problem is to extract individual items from such strings.

Four Practical Solutions

Method 1

Use double list slicing: first split by commas, then by brackets, with conditional logic to handle missing commas.

Method 2

Use Excel's text-to-columns feature to split by commas, then replace brackets [ and ] with commas.

Method 3

Apply pandas slicing; replace right brackets with commas when commas are missing, then split.

Method 4

Use pandas apply with a lambda to replace brackets and split the string.

df['新增一列']=df.数据1.apply(lambda x:x.replace('[','').replace(']',''))
df.新增一列=df.新增一列.str.split(',',expand=True)[0]

Note that the original string must not be directly converted to a list, otherwise it will be split incorrectly.

Conclusion

The four methods demonstrate efficient ways to split and extract data from template strings in Python, with the apply and lambda approach generally offering the best performance.