python - Pandas convert yearly to monthly -


i'm working on pulling financial data, in formatted in yearly , other monthly. model need of monthly, therefore need same yearly value repeated each month. i've been using stack post , trying adapt code data.

here dataframe:

df.head()     date ticker value 0 1999-12-31  ecb/ra6  1.0 1 2000-12-31  ecb/ra6  4.0 2 2001-12-31  ecb/ra6  2.0 3 2002-12-31  ecb/ra6  3.0 4 2003-12-31  ecb/ra6  2.0

here desired output first 5 rows:

   date ticker value 0 1999-12-31  ecb/ra6  1.0 1 2000-01-31  ecb/ra6  4.0 2 2000-02-28  ecb/ra6  4.0 3 2000-13-31  ecb/ra6  4.0 4 2000-04-30  ecb/ra6  4.0

and code:

df['date'] = pd.to_datetime(df['date'], format='%y-%m') df = df.pivot(index='date', columns='ticker') start_date = df.index.min() - pd.dateoffset(day=1) end_date = df.index.max() + pd.dateoffset(day=31) dates = pd.date_range(start_date, end_date, freq='m') dates.name = 'date' df = df.reindex(dates, method='ffill')  df = df.stack('ticker') df = df.sortlevel(level=1) df = df.reset_index()

however, not repeating months expected

you want resample

first, need set index resample work. backfill , reset index.

df.set_index('date').resample('m').bfill().reset_index()           date   ticker  value 0  1999-12-31  ecb/ra6    1.0 1  2000-01-31  ecb/ra6    4.0 2  2000-02-29  ecb/ra6    4.0 3  2000-03-31  ecb/ra6    4.0 4  2000-04-30  ecb/ra6    4.0 5  2000-05-31  ecb/ra6    4.0 6  2000-06-30  ecb/ra6    4.0 7  2000-07-31  ecb/ra6    4.0 8  2000-08-31  ecb/ra6    4.0 9  2000-09-30  ecb/ra6    4.0 10 2000-10-31  ecb/ra6    4.0 11 2000-11-30  ecb/ra6    4.0 12 2000-12-31  ecb/ra6    4.0 13 2001-01-31  ecb/ra6    2.0 14 2001-02-28  ecb/ra6    2.0 15 2001-03-31  ecb/ra6    2.0 ...

to handle per ticker

df.set_index('date').groupby('ticker', group_keys=false) \     .resample('m').bfill().reset_index()

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