How do I fix invalid literal for int() with base 10 error in pandas

Others might encounter the following issue, when the string is a float:

    >>> int("34.54545")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: invalid literal for int() with base 10: '34.54545'

The workaround for this is to convert to a float first and then to an int:

>>> int(float("34.54545"))
34

Or pandas specific:

df.astype(float).astype(int)

I run this

int('260,327,021')

and get this

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-448-a3ba7c4bd4fe> in <module>()
----> 1 int('260,327,021')

ValueError: invalid literal for int() with base 10: '260,327,021'

I assure you that not everything in your dataframe is a number. It may look like a number, but it is a string with commas in it.

You'll want to replace your commas and then turn to an int

pd.Series(['260,327,021']).str.replace(',', '').astype(int)

0    260327021
dtype: int64