I am new to python (coming from R), and I am trying to understand how I can convert a timestamp series in a pandas dataframe (in my case this is called df['timestamp']) into what I would call a string vector in R. is this possible? How would this be done?
I tried df['timestamp'].apply('str'), but this seems to simply put the entire column df['timestamp'] into one long string. I'm looking to convert each element into a string and preserve the structure, so that it's still a vector (or maybe this a called an array?)
Best Answer
Consider the dataframe df
df = pd.DataFrame(dict(timestamp=pd.to_datetime(['2000-01-01'])))dftimestamp0 2000-01-01Use the datetime accessor dt to access the strftime method. You can pass a format string to strftime and it will return a formatted string. When used with the dt accessor you will get a series of strings.
df.timestamp.dt.strftime('%Y-%m-%d')0 2000-01-01Name: timestamp, dtype: objectVisit strftime.org for a handy set of format strings.
Use astype
>>> import pandas as pd>>> df = pd.to_datetime(pd.Series(['Jul 31, 2009', '2010-01-10', None])) >>> df.astype(str)0 2009-07-311 2010-01-102 NaTdtype: objectreturns an array of strings
Following on from VinceP's answer, to convert a datetime Series in-place do the following:
df['Column_name']=df['Column_name'].astype(str)