python - Pandas calculate days elapsed and percent change -

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i have df hierarchical index (id & date) , measure m. add 2 new measures df; first percent change of measure m prior observation , second days elapsed. within "window" of id (i.e. first observation within each id 0 both new measures)

one way group id, differences want , sew new dataframe. suggestions on how better and/or in place welcome.

new_df = pd.dataframe() grouped = your_df.groupby('id') grp_id in grouped.groups:     grp = grouped.get_group(grp_id)     grp["diff"] = np.concatenate([np.array([0]),np.diff(grp['m'].values)]) #    differences of m     grp["days_elapsed"] = np.concatenate([np.array([none]),days_elapsed(grp.index.values)]) #      new_df = new_df.append(grp)

and function elapsed days pandas timeindex:

def days_elapsed(l): res= [] print l x in range(1,len(l)):      res.append((l[x]-l[x-1])/np.timedelta64(1, 'd'))  return res

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