Is there a Python equivalent to SQL's "WHERE LIKE "%%"?-CodePudding

I am trying to add a new column into a Pandas DataFrame. I want it to be based on my 'SKU' column and basically say "if the SKU ends with -RF, write "USED" into the new column, elif SKU ends with -NEW, write "NEW" into the new column, else don't do anything.

I know in my SQL you can write this like "...WHERE LIKE "%-RF", I'm looking for something that does the same job as that.

This was the (unfinished) function as I was attempting to make it. I'm trying to figure out what goes in place of the "something_to_do_with" placeholders.

    if sku_column == something_to_do_with_-RF:
        val = "USED"
    elif sku_column == something_to_do_with_-NEW:
        val = "NEW"
    else:
        continue

CodePudding user response：

No need for a loop.

df.loc[df['sku'].str.endswith("-RF"),'column'] = 'USED'
df.loc[df['sku'].str.endswith("-NEW"),'column'] = 'NEW'

CodePudding user response：

The equivalent of SQL's joker %a_text in pandas is pandas.Series.str.endswith(a_text).

In your case, it might be better to use pandas.Series.str.extract with a regex to capture the desired text and map it with a pre-defined dictionnary.

Try this :

dico = {'RF': 'USED', 'NEW': 'NEW'}

df['new_col'] = df['SKU'].str.extract('.-(RF|NEW)$', expand=False).map(dico)