Invalid value error during converting string to int

Question

I have a data set and there is a feature which containing numbers in string like

"153", "45", "13", "345"

I'd like to convert these values to integer with python and i wrote this line of code:

df.column = df.column.astype("int")

But i'm getting this error:

invalid literal for int() with base 10: '2,83E+05'

There is some value like:

3.89E+05, 2.60E+05, 3,13E+05

How can i convert it to any numerical data type? Thanks in advance

enter code here

AlecZ · Accepted Answer · 2022-03-10 14:37:52Z

1

Problem isn't the scientific notation per se, but the fact that they are float values AND they're in scientific notation. I found that this works as a one line solution:

df.column.astype('float64').astype('int64')

If your string values are in European convention, you can add the following line as well to put in a pandas-friendly format.

df.column = df.apply(lambda x: str(x.column).replace(',','.'), axis=1)
df.column.astype('float64').astype('int64')

edited Mar 10, 2022 at 14:37

answered Mar 10, 2022 at 12:40

AlecZ

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4 Comments

Berkay Çamur Over a year ago

it says 'could not convert string to float: '2,83E+05' ' I actually tried a thing that similar to that.

AlecZ Over a year ago

See the update, should work with your number conventions

Berkay Çamur Over a year ago

I dropped all NA values but there is still "Cannot convert non-finite values (NA or inf) to integer" error.

AlecZ Over a year ago

You can filter infinite values (or NA, or other specific) with numpy: df = df.column.replace({numpy.inf:0, numpy.nan:0})

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