Pandas merge on `datetime` or `datetime` in `datetimeIndex`

Question

Currently I have two data frames representing excel spreadsheets. I wish to join the data where the dates are equal. This is a one to many join as one spread sheet has a dat

Answer 1

Let's use this numpy method by @piRSquared:

df1 = pd.DataFrame({'date': ['2015-01-01', '2015-01-02', '2015-01-03'], 
                    'data': ['A', 'B', 'C']})
df2 = pd.DataFrame({'date': ['2015-01-01 to 2015-01-02', '2015-01-01 to 2015-01-02', '2015-01-02 to 2015-01-03'], 
                    'data': ['E', 'F', 'G']})

df2[['start', 'end']] = df2['date'].str.split(' to ', expand=True)
df2['start'] = pd.to_datetime(df2.start)
df2['end'] = pd.to_datetime(df2.end)
df1['date'] = pd.to_datetime(df1['date'])

a = df1['date'].values
bh = df2['end'].values
bl = df2['start'].values

i, j = np.where((a[:, None] >= bl) & (a[:, None] <= bh))

pd.DataFrame(np.column_stack([df1.values[i], df2.values[j]]),
             columns=df1.columns.append(df2.columns))

Output:

                  date data                      date data                start                  end
0  2015-01-01 00:00:00    A  2015-01-01 to 2015-01-02    E  2015-01-01 00:00:00  2015-01-02 00:00:00
1  2015-01-01 00:00:00    A  2015-01-01 to 2015-01-02    F  2015-01-01 00:00:00  2015-01-02 00:00:00
2  2015-01-02 00:00:00    B  2015-01-01 to 2015-01-02    E  2015-01-01 00:00:00  2015-01-02 00:00:00
3  2015-01-02 00:00:00    B  2015-01-01 to 2015-01-02    F  2015-01-01 00:00:00  2015-01-02 00:00:00
4  2015-01-02 00:00:00    B  2015-01-02 to 2015-01-03    G  2015-01-02 00:00:00  2015-01-03 00:00:00
5  2015-01-03 00:00:00    C  2015-01-02 to 2015-01-03    G  2015-01-02 00:00:00  2015-01-03 00:00:00