Several ways to convert a list of strings into a list of numeric values ​​in python

Preface

To convert a list of strings to a list of numeric values, you can use Python's built-in methods andpandasornumpyetc. Here are a few common ways to achieve this transformation.

Method 1: Use Python's map() and float() or int()

If you have a list containing a string of numbers, you can usemap()The function converts each string into a numeric value.

# Example string liststr_list = ['1.5', '2.3', '3.8', '4.1']

# Use map() and float() to convert to a list of numeric values ​​(floating type)num_list = list(map(float, str_list))

# Output the converted numerical listprint(num_list)

Output:

[1.5, 2.3, 3.8, 4.1]

If the data is an integer, you can useint()To convert:

# Example string list (integral)str_list_int = ['1', '2', '3', '4']

# Use map() and int() to convert to a list of integersnum_list_int = list(map(int, str_list_int))

# Output the converted numerical listprint(num_list_int)

Output:

[1, 2, 3, 4]

Method 2: Use List Comprehension

List comprehensions provide a concise way to iterate through a list of strings and convert them.

# Example string liststr_list = ['1.5', '2.3', '3.8', '4.1']

# Use list comprehension and float() to convert to a numeric listnum_list = [float(item) for item in str_list]

# Output the converted numerical listprint(num_list)

Output:

[1.5, 2.3, 3.8, 4.1]

Method 3: Use pandas conversion

If you have a more complex list of strings, or your data comes from a CSV file,pandasProvides an easy way to convert string columns to numeric values.

import pandas as pd

# Example string liststr_list = ['1.5', '2.3', '3.8', '4.1']

# Use pandas' Series and to_numeric() to convert to a numeric listnum_list = pd.to_numeric(str_list, errors='coerce').tolist()

# Output the converted numerical listprint(num_list)

Output:

[1.5, 2.3, 3.8, 4.1]

Method 4: Use numpy to convert

If you have a large list,numpyProvides a more efficient numerical calculation method.

import numpy as np

# Example string liststr_list = ['1.5', '2.3', '3.8', '4.1']

# Use numpy to convert a list of strings to a numeric array of floating typesnum_array = (str_list, dtype=float)

# Output the converted numeric arrayprint(num_array)

Output:

[1.5 2.3 3.8 4.1]

Summarize:

• map()andfloat() / int(): This is the easiest way to work with small lists.
• List comprehension: Simple and efficient, especially suitable for situations where flexible conversion is required.
• pandas: Suitable for handling lists of strings from CSV or more complex datasets, providing additional functionality to handle outliers.
• numpy: Suitable for handling large-scale data, especially when you need to do numerical calculations.

Through these methods, you can convert a list of strings into a list of numerical values, making it easy to perform numerical analysis and calculation.

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