🔒 anyone help me convert this columns to certains types

[candid wolf]

i've been trying to convert the last 3 columns to int type but nothing seems to work to me

[fervent jackal]

@candid wolf

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[clever relic]

how were you trying?

[candid wolf]

pd.to_numeric(df1['peak'])

df1['peak'].astype(int)

[clever relic]

And what happens?

[candid wolf]

didn't work

[clever relic]

That's not very descriptive. Do you get an error?

[candid wolf]

here is my code ```py
for i in ['peak', 'online', 'follows']:
df1[i] = df1[i].str.replace(',', '').str.replace('—', '')
df1[i] = df1[i].astype(int)

the column 'peak' converted to int successfuly

but the other failed

i guess because of the empty raws

[clever relic]

The error actually sounds like one of these columns is already numeric, rather. What does df1.info() say?

[candid wolf]

peak is int but other are all object

[clever relic]

Well, because peak already got converted to int, you can't use this piece of code again because it'll fail on trying to do df1["peak"].str.

As for the empty rows, to represent them you could replace them with pd.NA and then do .astype("Int64") - that's a pandas dtype that allows NA values.

[candid wolf]

alr will try that

[candid wolf]

what am i doing wrong here?

it remains as an object type

[clever relic]

.astype isn't an inplace operation. You need to assign the new column back to df1 or you're just discarding it.

[candid wolf]

thanks man it worked

[fervent jackal]

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