I have the following DF
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45 2018-01-012
73 2018-02-083
74 2018-02-084
75 2018-02-085
76 2018-02-086
I want to extract the month name and year in a simple way in the following format:
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45 Jan-20182
73 Feb-20183
74 Feb-20184
75 Feb-20185
76 Feb-20186
I have used the df.Date.dt.to_period("M") which return "2018-01" format.
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Answer
Cast you date from object to actual datetime and use dt to access what you need.
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import pandas as pd2
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df = pd.DataFrame({'Date':['2019-01-01','2019-02-08']})4
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df['Date'] = pd.to_datetime(df['Date'])6
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# You can format your date as you wish8
df['Mon_Year'] = df['Date'].dt.strftime('%b-%Y')9
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# the result is object/string unlike `.dt.to_period('M')` that retains datetime data type.11
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print(df['Mon_Year'])13
Visual Format without affecting data types
We could also work with style to get the visual in the way we want without messing with underlying types
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# note: returns a style object not df2
df.style.format({"Date": lambda t: t.strftime("%b-%Y")})3