changing date formate in a data frame python-CodePudding

I have a data frame with two columns, one are dates and the other are values, the date formate is 1913-01-01T00:00:00.000Z but I want it to change to 1913-01 and remove everything else, the problem is id like to do it for the whole data frame. this is what I have so far

#fixing the format of the date in the DFs and shortning them.
import datetime as dt
inflation['Yearmon'] = pd.to_datetime(inflation['Yearmon'])
inflation.rename(columns = {'Yearmon':'Date'}, inplace = True)

CodePudding user response：

I suggest you to look at the documentation of to_datetime; there's a specific command to send the function to set the format of the function output like:

pd.to_datetime(inflation['Yearmon'], format='%Y%m' , errors='ignore')

hope it helps in some ways, but I'm on holidays and cannot see if it works properly. (don't judge me for being on stackoverflow on holidays hahaha)

CodePudding user response：

Your question is a bit unclear: How does your input look like, exactly. A sample would be helpful (even better would be a MRE, look here and here).

I'm assuming your input looks something like

inflation = pd.DataFrame({
    "Yearmon": ["1913-01-01T00:00:00.000Z", "1913-02-01T00:00:00.000Z", "1914-07-01T00:00:00.000Z"],
    "Value": [0.1, 0.2, 0.3]
})

i.e. you have basically strings in the Yearmon column. If that's the case, then you could simply do

inflation["Yearmon"] = inflation["Yearmon"].str[:7]

to get

   Yearmon  Value
0  1913-01    0.1
1  1913-02    0.2
2  1914-07    0.3

If you actually have datetimes in the Yearmon column, i.e. in the example

inflation["Yearmon"] = pd.to_datetime(inflation["Yearmon"])

then this

inflation["Yearmon"] = inflation["Yearmon"].dt.strftime("%Y-%m")

would produce the same output.

But the result is always a column of strings!