Sorting with csv library, error says my dates don't match '%Y-%m-%d' format when it does - csv

Question

I'm trying to sort a CSV by date first then time second. With Pandas, it was easy by using df = df.sort_values(by=['Date', 'Time_UTC']). In the csv library, the code is (from here):
with open ('eqph_csv_29May2020_noF_5lines.csv') as file:
reader = csv.DictReader(file, delimiter=',')
date_sorted = sorted(reader, key=lambda Date: datetime.strptime('Date', '%Y-%m-%d'))
print(date_sorted)
The datetime documentation clearly says these codes are right. Here's a sample CSV (no delimiter):
Date Time_UTC Latitude Longitude
2020-05-28 05:17:31 16.63 120.43
2020-05-23 02:10:27 15.55 121.72
2020-05-20 12:45:07 5.27 126.11
2020-05-09 19:18:12 14.04 120.55
2020-04-10 18:45:49 5.65 126.54

Answer 1

csv.DictReader returns an iterator that yields a dict for each row in the csv file. To sort it on a column from each row, you need to specify that column in the sort function:
date_sorted = sorted(reader, key=lambda row: datetime.strptime(row['Date'], '%Y-%m-%d'))
To sort on both Date and Time_UTC, you could combine them into one string and convert that to a datetime:
date_sorted = sorted(reader, key=lambda row: datetime.strptime(row['Date'] + ' ' + row['Time_UTC'], '%Y-%m-%d %H:%M:%S'))

Answer 2

Nick's answer worked and used it to revise mine. I used csv.reader() instead.
lon,lat = [],[]
xy = zip(lon,lat)
with open ('eqph_csv_29May2020_noF_20lines.csv') as file:
reader = csv.reader(file, delimiter=',')
next(reader)
date_sorted = sorted(reader, key=lambda row: datetime.strptime
(row[0] + ' ' + row[1], '%Y-%m-%d %H:%M:%S'))
for row in date_sorted:
lon.append(float(row[2]))
lat.append(float(row[3]))
for i in xy:
print(i)
Result
(6.14, 126.2)
(14.09, 121.36)
(13.74, 120.9)
(6.65, 125.42)
(6.61, 125.26)
(5.49, 126.57)
(5.65, 125.61)
(11.33, 124.64)
(11.49, 124.42)
(15.0, 119.79) # 2020-03-19 06:33:00
(14.94, 120.17) # 2020-03-19 06:49:00
(6.7, 125.18)
(5.76, 125.14)
(9.22, 124.01)
(20.45, 122.12)
(5.65, 126.54)
(14.04, 120.55)
(5.27, 126.11)
(15.55, 121.72)
(16.63, 120.43)