Merging Date and Hour in Pandas

November 30, 2021

I have two columns in Pandas DataFrame, one containing a date as a string and one containing the hour of the day as an int.

I want to convert this into a datetime stamp.

I have managed this but feel it is slow.

The data is:

df = pd.DataFrame({'Date': {0: '01/12/2017',
                            1: '01/12/2017',
                            2: '01/12/2017',
                            3: '01/12/2017',
                            4: '01/12/2017'},
                   'Hour': {0: 0, 1: 1, 2: 2, 3: 3, 4: 4},
                   'Rented Bike Count': {0: 254, 1: 204, 2: 173, 3: 107, 4: 78}})

where the dtypes of Date is object and Hour is int64

and I am currently merging date and hour using:

# Generate the datetime column
df['datetime'] = pd.to_datetime(df.apply(lambda x: f"{x['Date']} {x['Hour']}:00:00", axis=1))

# Remove the old datetime columns
df = df.drop('Date', axis=1).drop('Hour', axis=1)

Is there a faster way of doing this?

>Solution :

I’d do:

# is your data day-first or month-first?
df['datetime'] = pd.to_datetime(df['Date'], dayfirst=True) + pd.to_timedelta(df['Hour'], unit='H')

df = df.drop(['Date','Hour'], axis=1)