I'm having difficulty with Pandas when trying to convert this column to a date. The table doesn't include a year, so I think that's making the conversion difficult.  28 JUL Unnamed: 0 Alura *Alura - 7/12 68,00 0 28 JUL NaN Passei Direto S/A. - 3/12 19,90 1 31 JUL NaN Drogarias Pacheco 25,99 2 31 JUL NaN Mundo Verde - Rj - Sho 5,90 3 31 JUL NaN Paypal *99app 4,25 4 04 AGO NaN Saldo em atraso 1.091,17 5 04 AGO NaN Crédito de atraso 1.091,17 6 06 AGO NaN Apple.Com/Bill 34,90 7 07 AGO NaN Pagamento em 07 AGO 1.091,17 8 07 AGO NaN Juros de atraso 16,86 9 07 AGO NaN IOF de atraso 4,43 10 07 AGO NaN Multa de atraso 21,91 11 08 AGO NaN Apple.Com/Bill 21,90 12 09 AGO NaN Google Youtubepremium 20,90 13 10 AGO NaN Amazon.Com.Br 41,32 14 12 AGO NaN Uber *Uber *Trip 17,91 15 12 AGO NaN Uber *Uber *Trip 16,94 16 12 AGO NaN Mia Cookies 47,50 17 13 AGO NaN Uber *Uber *Trip 16,96 18 13 AGO NaN Uber *Uber *Trip 19,98 19 16 AGO NaN Uber *Uber *Trip 11,93 20 16 AGO NaN Uber *Uber *Trip 9,97 21 18 AGO NaN Uber *Uber *Trip 9,91 22 22 AGO NaN Uber *Uber *Trip 9,96 23 23 AGO NaN Amazonprimebr 14,90 24 27 AGO NaN Paypal *Sacocheiotv 15,00 25 27 AGO NaN Pag*Easymarketpleno 6,50  I tried to transform it using this code, but it's not working: df["Data"] = pd.to_datetime(df["Data"], format="%d %b", errors="coerce")  Incorrect output: Data Local Valor 0 1900-07-28 Alura *Alura - 7/12 68,00 1 1900-07-28 Passei Direto S/A. - 3/12 19,90 2 1900-07-31 Drogarias Pacheco 25,99 3 1900-07-31 Mundo Verde - Rj - Sho 5,90 4 1900-07-31 Paypal *99app 4,25 7 NaT Apple.Com/Bill 34,90 9 NaT Juros de atraso 16,86 10 NaT IOF de atraso 4,43 11 NaT Multa de atraso 21,91 12 NaT Apple.Com/Bill 21,90 13 NaT Google Youtubepremium 20,90 14 NaT Amazon.Com.Br 41,32 15 NaT Uber *Uber *Trip 17,91 16 NaT Uber *Uber *Trip 16,94 17 NaT Mia Cookies 47,50 18 NaT Uber *Uber *Trip 16,96 19 NaT Uber *Uber *Trip 19,98 20 NaT Uber *Uber *Trip 11,93 21 NaT Uber *Uber *Trip 9,97 22 NaT Uber *Uber *Trip 9,91 23 NaT Uber *Uber *Trip 9,96 24 NaT Amazonprimebr 14,90 25 NaT Paypal *Sacocheiotv 15,00 26 NaT Pag*Easymarketpleno 6,50  Could someone help me with this?
This looks like Brazilian Portuguese, you should install the pt_BR locale on your machine, then run: import locale locale.setlocale(locale.LC_ALL, 'pt_BR.UTF-8') df['Data_converted'] = pd.to_datetime(df['Data'], format='%d %b', errors='coerce')  Output:  Data Data_converted 0 28 JUL 1900-07-28 1 04 AGO 1900-08-04  And, if you want to force the year: df['Data_converted'] = pd.to_datetime('2025 ' + df['Data'], format='%Y %d %b', errors='coerce')  Output:  Data Data_converted 0 28 JUL 2025-07-28 1 04 AGO 2025-08-04 