I have two DataFrames (with DatetimeIndex) and want to update the first frame (the older one) with data from the second frame (the newer one).
You can use the combine function.
import pandas as pd
# your data
# ===========================================================
df1 = pd.DataFrame(np.ones(12).reshape(4,3), columns='A B C'.split(), index=pd.date_range('2015-07-09 12:00:00', periods=4, freq='H'))
df2 = pd.DataFrame(np.ones(16).reshape(4,4)*2, columns='A B C D'.split(), index=pd.date_range('2015-07-09 14:00:00', periods=4, freq='H'))
# processing
# =====================================================
# reindex to populate NaN
result = df2.reindex(np.union1d(df1.index, df2.index))
Out[248]:
A B C D
2015-07-09 12:00:00 NaN NaN NaN NaN
2015-07-09 13:00:00 NaN NaN NaN NaN
2015-07-09 14:00:00 2 2 2 2
2015-07-09 15:00:00 2 2 2 2
2015-07-09 16:00:00 2 2 2 2
2015-07-09 17:00:00 2 2 2 2
combiner = lambda x, y: np.where(x.isnull(), y, x)
# use df1 to update result
result.combine(df1, combiner)
Out[249]:
A B C D
2015-07-09 12:00:00 1 1 1 NaN
2015-07-09 13:00:00 1 1 1 NaN
2015-07-09 14:00:00 2 2 2 2
2015-07-09 15:00:00 2 2 2 2
2015-07-09 16:00:00 2 2 2 2
2015-07-09 17:00:00 2 2 2 2
# maybe fillna(method='ffill') if you like