Filter on a pandas string column as numeric without creating a new column

Question

This is a quite easy task, however, I am stuck here. I have a dataframe and there is a column with type string, so characters in it:

Category
AB00
CD01
EF02
GH03
RF04

Now I want to treat these values as numeric and filter on and create a subset dataframe. However, I do not want to change the dataframe in any way. I tried:

df_subset=df[df['Category'].str[2:4]<=3]

of course this does not work, as the first part is a string and cannot be evaluated as numeric and compared to 69.

I tried

df_subset=df[int(df['Category'].str[2:4])<=3]

but I am not sure about this, I think it is wrong or not the way it should be done.

df['Category'].str[2:4]<='69'? Are you comparing to 69 or to 3? — BigBen
– BigBen, Commented Jan 11, 2023 at 15:47
maybe your problem is solved here: stackoverflow.com/questions/11350770/… — Pablo
– Pablo, Commented Jan 11, 2023 at 15:47

RomanPerekhrest · Accepted Answer · 2023-01-11 15:46:35Z

1

Add type conversion to your expression:

df[df['Category'].str[2:].astype(int) <= 3]

  Category
0     AB00
1     CD01
2     EF02
3     GH03

answered Jan 11, 2023 at 15:46

RomanPerekhrest

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mozway · Accepted Answer · 2023-01-11 15:51:06Z

1

As you have leading zeros, you can directly use string comparison:

df_subset = df.loc[df['Category'].str[2:4] <= '03']

Output:

  Category
0     AB00
1     CD01
2     EF02
3     GH03

answered Jan 11, 2023 at 15:51

mozway

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