How to convert dtype from ‘0’ to ‘int64’?

I started working with a dataset, which is a collection of murder reports.There is a column “Perpetrator Age” in which there are simple integers. But when I looked at his type, it turned out that he was dtype('O').

In order to work with this column further, I want to change its type to dtype('int64'). I tried to do it like this:

data['Perpetrator Age'] = data['Perpetrator Age'].astype(int)

and got this error:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-64-50a3c796ab1e> in <module>()
----> 1 data['Perpetrator Age'] = data['Perpetrator Age'].astype(int)

4 frames
/usr/local/lib/python3.7/dist-packages/pandas/core/dtypes/cast.py in astype_nansafe(arr, dtype, copy, skipna)
    972         # work around NumPy brokenness, #1987
    973         if np.issubdtype(dtype.type, np.integer):
--> 974             return lib.astype_intsafe(arr.ravel(), dtype).reshape(arr.shape)
    975 
    976         # if we have a datetime/timedelta array of objects

pandas/_libs/lib.pyx in pandas._libs.lib.astype_intsafe()

ValueError: invalid literal for int() with base 10: ' '

I saw advice for the “object” type, which must first be converted to a string, and then to “int”. Tried it, it didn’t work either, same error appeared. Please tell me how I can fix this?

Answer

As mentioned in the comments, the first row of your df is apparently an empty space (' '). You can either remove it, replace it with something else, or skip it:

df['column_1'].iloc[1:].astype('int')