I have a script which reads a text file, pulls decimal numbers out of it as strings and places them into a list.

So I have this list:

my_list = ['0.49', '0.54', '0.54', '0.55', '0.55', '0.54', '0.55', '0.55', '0.54']

How do I convert each of the values in the list from a string to a float?

I have tried:

for item in my_list: float(item)

But this doesn't seem to work for me.

2

13 Answers

[float(i) for i in lst]

to be precise, it creates a new list with float values. Unlike the map approach it will work in py3k.

4

map(float, mylist) should do it.

(In Python 3, map ceases to return a list object, so if you want a new list and not just something to iterate over, you either need list(map(float, mylist) - or use SilentGhost's answer which arguably is more pythonic.)

1

This would be an other method (without using any loop!):

import numpy as np
list(np.float_(list_name))

1

float(item) do the right thing: it converts its argument to float and and return it, but it doesn't change argument in-place. A simple fix for your code is:

new_list = []
for item in list: new_list.append(float(item))

The same code can written shorter using list comprehension: new_list = [float(i) for i in list]

To change list in-place:

for index, item in enumerate(list): list[index] = float(item)

BTW, avoid using list for your variables, since it masquerades built-in function with the same name.

2

you can even do this by numpy

import numpy as np
np.array(your_list,dtype=float)

this return np array of your list as float

you also can set 'dtype' as int

1

You can use the map() function to convert the list directly to floats:

float_list = map(float, list)

You can use numpy to convert a list directly to a floating array or matrix.

 import numpy as np list_ex = [1, 0] # This a list list_int = np.array(list_ex) # This is a numpy integer array

If you want to convert the integer array to a floating array then add 0. to it

 list_float = np.array(list_ex) + 0. # This is a numpy floating array

you can use numpy to avoid looping:

import numpy as np
list(np.array(my_list).astype(float)

1

This is how I would do it.

my_list = ['0.49', '0.54', '0.54', '0.54', '0.54', '0.54', '0.55', '0.54', '0.54', '0.54', '0.55', '0.55', '0.55', '0.54', '0.55', '0.55', '0.54', '0.55', '0.55', '0.54']
print type(my_list[0]) # prints <type 'str'>
my_list = [float(i) for i in my_list]
print type(my_list[0]) # prints <type 'float'>

import numpy as np
my_list = ['0.49', '0.54', '0.54', '0.54', '0.54', '0.54', '0.55', '0.54', '0.54', '0.54', '0.55', '0.55', '0.55', '0.54', '0.55', '0.55', '0.54',
'0.55', '0.55', '0.54']
print(type(my_list), type(my_list[0]))
# <class 'list'> <class 'str'>

which displays the type as a list of strings. You can convert this list to an array of floats simultaneously using numpy:

 my_list = np.array(my_list).astype(np.float) print(type(my_list), type(my_list[0])) # <class 'numpy.ndarray'> <class 'numpy.float64'>

I had to extract numbers first from a list of float strings:

 df4['sscore'] = df4['simscore'].str.findall('\d+\.\d+')

then each convert to a float:

 ad=[] for z in range(len(df4)): ad.append([float(i) for i in df4['sscore'][z]])

in the end assign all floats to a dataframe as float64:

 df4['fscore'] = np.array(ad,dtype=float)

I have solve this problem in my program using:

number_input = float("{:.1f}".format(float(input())))
list.append(number_input)

1

for i in range(len(list)): list[i]=float(list[i])

Your Answer

Sign up or log in

Sign up using Google Sign up using Facebook Sign up using Email and Password Submit

Post as a guest

Post Your Answer Discard

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy