Hướng dẫn convert to float python

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.

Wenuka

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asked Oct 23, 2009 at 15:33

2

[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.

answered Oct 23, 2009 at 15:34

SilentGhostSilentGhost

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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.)

answered Oct 23, 2009 at 15:34

Tim PietzckerTim Pietzcker

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

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

answered May 26, 2018 at 12:35

Amin KianyAmin Kiany

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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.

answered Oct 23, 2009 at 15:44

Denis OtkidachDenis Otkidach

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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

answered Sep 16, 2018 at 12:37

AlirezaAlireza

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

float_list = map(float, list)

answered May 23, 2021 at 4:44

mnaghd01mnaghd01

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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

answered Jan 7, 2016 at 15:13

bfree67bfree67

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you can use numpy to avoid looping:

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

answered Jul 9, 2020 at 0:48

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 
my_list = [float(i) for i in my_list]
print type(my_list[0]) # prints 

Stephen Rauch♦

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answered Jan 27, 2018 at 23:41

SamlexSamlex

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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]))   
#  

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]))  
    #  

answered May 16, 2018 at 12:33

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)

answered Mar 5, 2019 at 13:34

Max KleinerMax Kleiner

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I have solve this problem in my program using:

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

sentence

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answered Sep 4, 2018 at 13:53

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

double-beep

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answered May 23, 2019 at 16:05