CODEWITHSUNDEEP
pythonpandasdataframejupyter-notebook
olividir
olividir

Reputation: 73

Converting predefined quarter in pandas

I am having small problem. I have a practice data frame (still learning) with coulmn which has year and quarters per-defined like so 

 Date       Column2      Column3
   2004 Q-1    Other data   Other data
   2004 Q-2    Other Data   Other data

up to 2019. Pandas sees this as object, and I have been trying to convert it to date and quarter.

I have tried:

df['Date'] = df['Date'].str.replace(' Q-', '').astype(int) which gave error

invalid literal for int() with base 10: '2019 4'

df['Date'] = df.ddate.dt.to_period("Q") but my df doesn't have ddate attribute

df['Date'] = pd.to_datetime(df['Date'], format='%Y %q') with error:

'q' is a bad directive in format '%Y %q'

I am currently out of ideas of how to convert this so pandas can read this as quarters per year.

Upvotes: 3

Views: 275

Answers (1)

wwnde
wwnde

Reputation: 26676

You weren't as explicit. Do you want the date extracted from year quarter? Looks to me thats likely. If it is, please my attempt below. If aint, clarify to get help. Staggered it to be readable (I am a readable code enthusiast, like to demistify coding :-) );

data['Date'] = data['Date'].str.replace(r'-','')

enter image description here

data['Date'] = data['Date'].str.replace(' ',r'')

enter image description here

data['Date']=pd.to_datetime(data['Date'])

enter image description here

If wanted EndMonth:

data.set_index('Date', inplace=True)
data['EndMonth']= data.index.to_period('M').to_timestamp('M')

enter image description here

Upvotes: 1

Related Questions