Every time you encounter pandas dataframe a column date format problems will always be pit, the following record of commonly used time and date function ....
1, string into date str->date
import datetime date_str = '2006-01-03' date_ = (date_str,'%Y-&m-%d')
This is the conversion of a single string, where "%Y-%m-%d" represents the format of the date string, if date_str = '2006/1/3', it can be written as "%Y/%m/%d", and so on.
In general, we often manipulate a column of a dataframe:
The apply function can be applied:
def strptime_row(rowi): return (rowi,'%Y/%m/%d') df['date'] = df['date'].apply(strptime_row)
may apply () function is a bit less efficient, there should be specialized for a particular column date formatting operations function, such as
import pandas as pd df['date'] = pd.to_datetime(df['date'])
to_datetime () function can parse a variety of different date representation (such as "7/6/2011", June 7, 2011), the standard date format (such as ISO8601) parsing is very fast.
There is also parse () function, can recognize almost all humans can understand the date representation (but unfortunately not in Chinese), such as:
from import parse
parse('Jan 31,2008 10:45 AM')
2, the date is converted to a string
You can use the strftime() function
summarize
The above is a small introduction to the python about time and date format conversion problems, I hope to help you, if you have any questions please leave me a message, I will reply to you in time. I would also like to thank you very much for your support of my website!
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