1.6 Parsing Dates from Text Files

When parsing multiple text file columns into a single date column, the new date column is prepended to the data and then index_col specification is indexed off of the new set of columns rather than the original ones:

In [1]: print(open('tmp.csv').read())
KORD,19990127, 19:00:00, 18:56:00, 0.8100
KORD,19990127, 20:00:00, 19:56:00, 0.0100
KORD,19990127, 21:00:00, 20:56:00, -0.5900
KORD,19990127, 21:00:00, 21:18:00, -0.9900
KORD,19990127, 22:00:00, 21:56:00, -0.5900
KORD,19990127, 23:00:00, 22:56:00, -0.5900

In [2]: date_spec = {'nominal': [1, 2], 'actual': [1, 3]}

In [3]: df = pd.read_csv('tmp.csv', header=None,
   ...:                  parse_dates=date_spec,
   ...:                  keep_date_col=True,
   ...:                  index_col=0)
   ...: 

# index_col=0 refers to the combined column "nominal" and not the original
# first column of 'KORD' strings
In [4]: df
Out[4]: 
                                 actual     0         1          2          3  \
nominal                                                                         
1999-01-27 19:00:00 1999-01-27 18:56:00  KORD  19990127   19:00:00   18:56:00   
1999-01-27 20:00:00 1999-01-27 19:56:00  KORD  19990127   20:00:00   19:56:00   
1999-01-27 21:00:00 1999-01-27 20:56:00  KORD  19990127   21:00:00   20:56:00   
1999-01-27 21:00:00 1999-01-27 21:18:00  KORD  19990127   21:00:00   21:18:00   
1999-01-27 22:00:00 1999-01-27 21:56:00  KORD  19990127   22:00:00   21:56:00   
1999-01-27 23:00:00 1999-01-27 22:56:00  KORD  19990127   23:00:00   22:56:00   

                        4  
nominal                    
1999-01-27 19:00:00  0.81  
1999-01-27 20:00:00  0.01  
1999-01-27 21:00:00 -0.59  
1999-01-27 21:00:00 -0.99  
1999-01-27 22:00:00 -0.59  
1999-01-27 23:00:00 -0.59  