I'm working on a df that gives me Date in a integer form, and i want to convert it into Datetime so i can continue to manipulate it.

Basically i have this DF where i have a Column like this below

    DATE
18010101
18010101
18010101
18010101
18010101
... ... ... ... ... ...
20123124
20123124
20123124
20123124
20123124

the respective order in this dateset is (Year, month, day, hour)

i've already tried to do something like this

df["Year"] = df.DATE[0:2]
df["Month"] = df.DATE[2:4]~

but it converts it into a float and for the first line example, it becomes similar to this

DATE    Year
18010101    18010101.0

where it was supposed to be

Year = 2018 or 18

I would appreciate a lot the help of you guys.

CodePudding user response：

Use Series.str.extract and a regex

df = pd.DataFrame([[18010101], [18010101], [18010101], [18010101], [18010101],
                   [20123124], [20123124], [20123124], [20123124], [20123124]],
                  columns=['DATE'])
df[['year', 'month', 'day', 'hour']] = df['DATE'].astype(str).str.extract(r'(\d{2})(\d{2})(\d{2})(\d{2})')

CodePudding user response：

Earlier, you tried to split an int like a string. But you can first convert it into a string (by .astype(str)) and then split it. Check the lines below.

date_str = df.DATE.astype(str)
df["Year"] = date_str.str[0:2]
df["Month"] = date_str.str[2:4]