Is there a way in pandas to convert my column date which has the following format '1997-01-31' to '199701', without including any information about the day?
I tried solution of the following form:
df['DATE'] = df['DATE'].apply(lambda x: datetime.strptime(x, '%Y%m'))
but I obtain this error : 'ValueError: time data '1997-01-31' does not match format '%Y%m''
Probably the reason is that I am not including the day in the format. Is there a way better to pass from YYYY-MM_DD format to YYYYMM in pandas?
One way is to convert the date to date time and then use strftime. Just a note that you do lose the datetime functionality of the date
df = pd.DataFrame({'date':['1997-01-31' ]})
df['date'] = pd.to_datetime(df['date'])
df['date'] = df['date'].dt.strftime('%Y%m')
date
0 199701
Might not need to go through the datetime conversion if the data are sufficiently clean (no incorrect strings like 'foo' or '001231'):
df = pd.DataFrame({'date':['1997-01-31', '1997-03-31', '1997-12-18']})
df['date'] = [''.join(x.split('-')[0:2]) for x in df.date]
# date
#0 199701
#1 199703
#2 199712
Or if you have null values:
df['date'] = df.date.str.replace('-', '').str[0:6]
Related
I am pulling a time series from a csv file which has dates in "mm/dd/yyyy" format
df = pd.read_csv(lib_file.csv)
df['Date'] = df['Date'].apply(lambda x:datetime.strptime(x,'%m/%d/%Y').strftime('%d/%m/%Y'))
below is the output
I convert dtypes for ['Date'] from object to datetime64
df['Date'] = pd.to_datetime(df['Date'])
but that changes my dates as well
how do I fix it?
Try this:
df['Date'] = pd.to_datetime(df['Date'], infer_datetime_format=True)
This will infer your dates based on the first non-NaN element which is being correctly parsed in your case and will not infer the format for each and every row of the dataframe.
just using the below code helped
df = pd.read_csv(lib_file.csv)
df['Date'] = pd.to_datetime(df['Date])
I'm trying to figure out how to reformat a date in a pandas df. The source date is a string in the format of %Y-%m-%d %H:%M:%S. I use the following code to convert it do a date field in a format=%Y-%m-%d.
df['Date'] = pd.to_datetime(df['Date'], format='%Y-%m-%d').dt.date
How do I convert a date field in the format of %Y-%m-%d into %m/%d/%Y ?
Thanks!
i think this should help
df['Date'] = pd.to_datetime(df['Date'], format='%Y-%m-%d').dt.date
df['Date'] = df['Date'].dt.strftime('%m/%d/%Y')
you can try a one liner
df['Date'] = pd.to_datetime(df['Date'], format='%Y-%m-%d').dt.strftime('%m/%d/%Y')
I have a dataframe with date information in one column.
The date visually appears in the dataframe in this format: 2019-11-24
but when you print the type it shows up as:
Timestamp('2019-11-24 00:00:00')
I'd like to convert each value in the dataframe to a format like this:
24-Nov
or
7-Nov
for single digit days.
I've tried using various datetime and strptime commands to convert but I am getting errors.
Here's a way to do:
df = pd.DataFrame({'date': ["2014-10-23","2016-09-08"]})
df['date_new'] = pd.to_datetime(df['date'])
df['date_new'] = df['date_new'].dt.strftime("%d-%b")
date date_new
0 2014-10-23 23-Oct
1 2016-09-08 08-Sept
I have a data frame with a column 'Date' with data type datetime64. The values are in YYYY-MM-DD format.
How can I convert it to YYYY-MM format and use it as a datetime64 object itself.
I tried converting my datetime object to a string in YYYY-MM format and then back to datetime object in YYYY-MM format but it didn't work.
Original data = 1988-01-01.
Converting datatime object to string in YY-MM format
df['Date']=df['Date'].dt.strftime('%Y-%m')
This worked as expected, my column value became
1988-01
Converting the string back to datetime object in Y-m format
df['Date']=pd.to_datetime(df['Date'],format= '%Y-%m')
I was expecting the Date column in YYYY-MM format but it became YYYY-MM-DD format.
1988-01-01
Can you please let me know if I am missing something.
Thanks
It is expected behaviour, in datetimes the year, month and day arguments are required.
If want remove days need month period by to_period:
df['Date'] = df['Date'].dt.to_period('M')
df['Date'] = pd.to_datetime(df['Date'],format= '%Y-%m').dt.to_period('M')
Sample:
df = pd.DataFrame({'Date':pd.to_datetime(['1988-01-01','1999-01-15'])})
print (df)
Date
0 1988-01-01
1 1999-01-15
df['Date'] = df['Date'].dt.to_period('M')
print (df)
Date
0 1988-01
1 1999-01
I have a particular format of date in my dataframe as
df:
Date
12-Jun-16
22-Jan-12
I want to covert it to this format
df:
Date
12-Jan-2015
Any help as to how to do it?
I think you need convert column to_datetime and then if need change format add strftime:
df.Date = pd.to_datetime(df.Date).dt.strftime('%d-%b-%Y')
print (df)
Date
0 12-Jun-2016
1 22-Jan-2012