Merging dataframes with pandas with two keys

Question

I have two datasets, one with individual reports and one with regional conditions. There are many more individual rows than regional, but I want to append the regional data onto each individual. The problem I am facing is that I must merge using two primary keys, eg

Individual - 5000 rows
Code | Time | Data1 | Data2 | Data3

Regional - 100 rows
Code | Time | RData1 | RData2

--I have attemped and failed using:

df = individual.merge(regional, how='left', on=['Code', 'Time'])

--Which leaves RData1,2 as null values in the new df, which does, to its credit look like

df - 5000 rows
Code | Time | Data1 | Data2 | Data3 | RData1 | RData2

but the null values don't help me...

Example Data
What I am seeing

Answer 1

Data

Generate random df

 rng = pd.date_range('2015-02-24', periods=5, freq='T')
    df = pd.DataFrame({ 'Time': rng, 'data1': np.random.randn(len(rng)),'code':[201, 897,345, 70,879] }) 
    df.set_index(['Time','code'], inplace=True)
    df

Generate random df1

df1 = pd.DataFrame({ 'Time': rng, 'data1': np.random.randn(len(rng)),'code':[201, 30,345, 70,879] }) 
df1.set_index(['Time','code'], inplace=True)
df1

merge on indexes can be done as follows

result =df1.merge(df, left_index=True, right_index=True, suffixes=('_Left','_Right'))
result

Or better

result =pd.merge(df, df1,left_index=True, right_index=True, suffixes=('_Left','_Right'))
result