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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?
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?
Share Improve this question edited 2 days ago mozway 259k13 gold badges49 silver badges93 bronze badges asked 2 days ago leotricanoleotricano 11 silver badge New contributor leotricano is a new contributor to this site. Take care in asking for clarification, commenting, and answering. Check out our Code of Conduct. 1 |1 Answer
Reset to default 4This 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
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AGOtoAUGat the very least, so use a mapping. As for the year, well, I just hope you know that it only spans a single year otherwise you'll have quite a bit more difficulty – roganjosh Commented 2 days ago