I have a data frame that looks like this:
price
Date
2022-01-01 19:20:00 100
2022-01-01 19:27:00 100
2022-01-02 19:31:00 102
I want the dataframe to only have unique dates:
price
Date
2022-01-01 19:20:00 100
2022-01-02 19:31:00 102
How can I achieve that?
You can simply use duplicated:
# pre-requisite
df['Date'] = pd.to_datetime(df['Date'])
df[~df['Date'].dt.date.duplicated()]
Or if working with the index:
df[~df.index.to_series().dt.date.duplicated().values]
Output:
Date price
0 2022-01-01 19:20:00 100
2 2022-01-02 19:31:00 102
You can extract the date from the datetime column using df.Date.dt.date, put that into a new column using assign, and after that use drop_duplicates based on only that column. Last, you might want to drop the newly create column that has only the date information. In code that reads
df = (
df.assign(new_date=lambda df:df.Date.dt.date)
.drop_duplicates(subset=["new_date"])
.drop(columns=["new_date"])
)
