Reputation: 319
data = [07222020051111, 07222020051058, 07222020051107]
df = pd.DataFrame(data, columns = ['time'])
I am seeking to transform the data in the 'time' column to display as follows:
time
0 2020-07-22 05:11:11
1 2020-07-22 05:10:58
2 2020-07-22 05:11:07
I have tried:
df['time'] = df['time'].dt.strptime('%m-%d-%Y %H:%m:%s')
df['time'] = pd.to_numeric(df['time'])
both without success.
I am very new to this so please excuse if this seems very basic.
Upvotes: 0
Views: 1978
Reputation: 109
use to_datetime function to convert a column to datetime type:
df['timestamp'] = pd.to_datetime(df['time'], format='%m%d%Y%H%M%S')
here's the format arg is your data's date format, and not your desired output format
Upvotes: 1
Reputation: 36
If you use the datetime module to parse the strings into dates first then creating the dataframe using datetimes for data takes care of it.
data = ["07222020051111", "07222020051058", "07222020051107"]
data2 = [datetime.datetime.strptime(i,"%m%d%Y%H%M%S") for i in data]
df = pd.DataFrame(data2, columns = ['time'])
should do it
Upvotes: 0