I am working on a data cleaning project using Python 3 and a panda's dataframe. As a specific example: one of the changes I want to make is to a certain section of the dataframe that includes dates in a different format from the remained of the dataframe. I am able to make the changes I want to the format of the dates using a for loop, but I do not now how to insert these dates back into the dataframe.
Below is the code I have for parsing and rearranging the current datetime format (m/d/yy hh:mm)to the desired datetime format (yyyy/mm/dd hh:mm):
wrongDateFormat = df.iloc[807:1029]
for b in wrongDateFormat['datetime']:
date = b.split()[0]
time = b.split()[1]
date = date.split('/')
year = date[2]
year = "20" + year
month = date[0]
if int(month) < 10:
month = '0' + str(month)
day = date[1]
if int(day) < 10:
day = '0' + str(day)
b = year + '/' + month + '/' + day + ' ' + time
print(b)
This code outputs:
2006/08/24 6:36
2006/08/23 11:59
2006/08/22 7:55
2006/08/21 2:25
2006/08/20 9:15
2006/08/19 8:16
Does anyone know how I can update the original dataframe with these new dates? Thanks in advance. It seems like the .set_value method used in this similar resolved question has depreciated since version 0.21.0.
