How to convert a pandas column containing float array to int array

Question

I have a pandas dataframe. One of it's columns contains variable-length float arrays. I need to convert them to arrays of uint8 because actually these arrays contain grayscale images with values from 0 to 255. Currently arrays dimention is 1. I understand that it's possible to iterate over rows and do conversion in this cycle. But hope there is an out of box solution cause this task seems to be common. I also tryed the following df['grayscale255'] = df['grayscale255'].astype('uint8'), but it doesn't work becuase

TypeError: only size-1 arrays can be converted to Python scalars

Data snippet:

Please include a small subset of your data as a copyable piece of code that can be used for testing as well as your expected output for the provided data. See MRE - Minimal, Reproducible, Example, and How to make good reproducible pandas examples. — Henry Ecker
– Henry Ecker ♦, Commented May 29, 2021 at 15:07
to kumar: apply('uint8') causes the same error because as I think this is actually a df column, and not an array. Sorry, it's not possible to add a comment to your answer so had to downvote — Dmitry
– Dmitry, Commented May 29, 2021 at 15:09

Henry Ecker · Accepted Answer · 2021-05-29 15:17:39Z

Use apply + astype

df['grayscale255'] = df['grayscale255'].apply(lambda x: x.astype('uint8'))

Or apply np.ubyte:

df['grayscale255'] = df['grayscale255'].apply(np.ubyte)

df:

   random_len         grayscale255
0           4    [72, 195, 17, 79]
1           3        [70, 97, 198]
2           4  [161, 129, 163, 48]
3           2            [152, 22]
4           3        [40, 23, 175]

Sample Data:

import numpy as np
import pandas as pd

np.random.seed(5)

df = pd.DataFrame({'random_len': np.random.randint(1, 5, size=5)})
df['grayscale255'] = df['random_len'].apply(
    lambda x: np.random.random(size=x) * 200
)

   random_len                                       grayscale255
0           4  [72.74737942011788, 195.8889998322892, 17.9642...
1           3  [70.82760858300028, 97.32759937167242, 198.164...
2           4  [161.6563366066534, 129.89177664881987, 163.89...
3           2           [152.87452173223647, 22.180152347812744]
4           3  [40.830949566118434, 23.81907149565208, 175.58...

shivesh kumar · Accepted Answer · 2021-05-29 15:05:54Z

-1

df['grayscale255'] = df['grayscale255'].apply('uint8')

Try this

answered May 29, 2021 at 15:05

shivesh kumar

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1 Comment

Jeremy Caney Over a year ago

Take a look at the accepted answer, which came in around the same time as yours. It offers the same basic guidance, but with the level of detail and context we hope for on Stack Overflow.

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