Time Stamp is Returning Year in Seconds for Datetime

user_12935982 0
Viewed 60

I have data that has a "YEAR" column. The second column is "JFK", which is the wind speeds. I need to convert the YEAR column to show arbitrary months and time. But it needs to keep the year.

For instance, I have some data at the year 1972. I want it the column to read:

1972-01-01 00:00:00.000000000

But instead, I am getting:

1970-01-01 00:00:00.000001972

When I type the following:

winds["YEAR"] = pd.to_datetime(winds["YEAR"],errors='ignore')

For some reason, the year is showing up in seconds. Any help will be appreciated.

jupyter pandas timestamp datetime python
2 Answers

Use format=%Y

winds["YEAR"] = pd.to_datetime(winds["YEAR"],format='%Y')

Also, this solution assume that your input is an integer/float since it would correctly parse a string without the need for format.

user_119177300

You first need to parse the given column into a datetime and then format the resulting datetime into a string.

Demo:

import pandas as pd

df = pd.DataFrame({'year': [1972]})
df['year'] = pd.to_datetime(df['year'], format='%Y').dt.strftime('%Y-%m-%d 00:00:00.000000000')
print(df)

Output:

                            year
0  1972-01-01 00:00:00.000000000
user_108195730
Related