我认为你需要添加NaN
s by loc http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.loc.html进而merge http://pandas.pydata.org/pandas-docs/stable/generated/pandas.merge.html左连接:
np.random.seed(10)
N = 365
rng = pd.date_range('2015-01-01', periods=N)
df_tr_2014 = pd.DataFrame(np.random.randint(10, size=(N, 3)), index=rng).reset_index()
df_tr_2014.columns = ['datetime','7d','15d','20d']
df_tr_2014.insert(1,'month', df_tr_2014['datetime'].dt.month)
df_tr_2014.insert(2,'day_m', df_tr_2014['datetime'].dt.day)
#print (df_tr_2014.head())
N = 366
rng = pd.date_range('2016-01-01', periods=N)
df_te = pd.DataFrame(index=rng)
df_te['month'] = df_te.index.month
df_te['day_m'] = df_te.index.day
df_te = df_te.reset_index()
#print (df_te.tail())
df2 = df_te.copy()
df1 = df_tr_2014.copy()
df1 = df1.set_index('datetime')
df1.index += pd.offsets.DateOffset(years=1)
#correct 29 February
y = df1.index[0].year
df1 = df1.reindex(pd.date_range(pd.datetime(y,1,1), pd.datetime(y,12,31)))
idx = df1.index[(df1.index.month == 2) & (df1.index.day == 29)]
df1.loc[idx, :] = df1.loc[idx - pd.Timedelta(1, unit='d'), :].values
df1.loc[idx, 'day_m'] = idx.day
df1[['month','day_m']] = df1[['month','day_m']].astype(int)
df1[['7d','15d', '20d']] = df1[['7d','15d', '20d']].astype(float)
df1.loc[np.arange(len(df1.index)) % 30 == 0, ['7d','15d','20d']] = 0
df1 = df1.reset_index()
print (df1.iloc[57:62])
index month day_m 7d 15d 20d
57 2016-02-27 2 27 2.0 0.0 1.0
58 2016-02-28 2 28 2.0 3.0 5.0
59 2016-02-29 2 29 2.0 3.0 5.0
60 2016-03-01 3 1 0.0 0.0 0.0
61 2016-03-02 3 2 7.0 6.0 9.0