Reputation:
i just need to make the format of data-frame be like 2020-22-01
not like 2020-01-22
.
the code is:
confirmed_file=pd.read_json('https://api.covid19api.com/country/egypt/status/confirmed/live')
confirmed_file["Date"] = pd.to_datetime(confirmed_cases["Date"]).dt.date
Upvotes: 0
Views: 41
Reputation: 39820
You can format the date using strftime
:
confirmed_file["Date"] = pd.to_datetime(confirmed_file["Date"]).dt.strftime('%Y-%d-%m')
Full Example:
>>> import pandas as pd
>>>
>>> confirmed_file=pd.read_json('https://api.covid19api.com/country/egypt/status/confirmed/live')
>>> confirmed_file["Date"]
0 2020-01-22 00:00:00+00:00
1 2020-01-23 00:00:00+00:00
2 2020-01-24 00:00:00+00:00
3 2020-01-25 00:00:00+00:00
4 2020-01-26 00:00:00+00:00
...
475 2021-05-11 00:00:00+00:00
476 2021-05-12 00:00:00+00:00
477 2021-05-13 00:00:00+00:00
478 2021-05-14 00:00:00+00:00
479 2021-05-15 00:00:00+00:00
Name: Date, Length: 480, dtype: datetime64[ns, UTC]
>>> confirmed_file["Date"] = pd.to_datetime(confirmed_file["Date"]).dt.strftime('%Y-%d-%m')
>>> confirmed_file["Date"]
0 2020-22-01
1 2020-23-01
2 2020-24-01
3 2020-25-01
4 2020-26-01
...
475 2021-11-05
476 2021-12-05
477 2021-13-05
478 2021-14-05
479 2021-15-05
Name: Date, Length: 480, dtype: object
Upvotes: 2