Converting a list to floats in Python
A list can store multiple elements of different data types. Therefore, we may encounter situations where we have to change the type of elements in a list. For example, we may have a list of strings where each string is in the form of a floating point value.
In this tutorial, we will convert the elements of a list from strings to floating point numbers in Python.
forConvert all items in a list to floating point numbers in Python
using a loop
We can forloop over the list using and float()convert each element to a floating point type using the function.
We can then use append()the add function to append each element to a new list.
For example,
lst = ["1.5", "2.0", "2.5"]
float_lst = []
for item in lst:
float_lst.append(float(item))
print(float_lst)
Output:
[1.5, 2.0, 2.5]
Convert all items in a list to floating point numbers using list comprehension in Python
The list comprehension method creates a new list in a single line of code. It achieves the same result but is more compact and elegant.
For example,
lst = ["1.2", "3.4", "5.6"]
float_lst = [float(item) for item in lst]
print(float_lst)
Output:
[1.5, 2.0, 2.5]
Use the function in Python numpy.float_()to convert the items in the list into floating point numbers
numpy.float_()The function creates an array with floating point numbers NumPy. We can pass a list to this function to create an array with floating point numbers. We can then use list()the function to convert this array into a list.
For example,
import numpy as np
lst = ["1.5", "2.0", "2.5"]
float_lst = list(np.float_(lst))
print(float_lst)
Output:
[1.5, 2.0, 2.5]
numpy.array()Convert the items in a list to floating point numbers
using the function in Python
This is similar to the previous approach. Instead of using numpy.array()the function, we will use the dtypefunction and specify the parameter floatas numpy.float_().
Please refer to the code below.
import numpy as np
lst = ["1.5", "2.0", "2.5"]
float_lst = list(np.array(lst, dtype="float"))
print(float_lst)
Output:
[1.5, 2.0, 2.5]
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