Padding python pivot tables with 0
I'm going to be general here, since there was no sample code or data provided. Let's say your original dataframe is called df and has columns Date and Sales.
I would try creating a list that has all dates from 01-01-2014 to 12-31-2015. Let's call this list dates. I would also create an empty list called sales (i.e. sales = []). At the end of this workflow, sales should include data from dt['Sales'] AND placeholders for dates that are not within the data frame. In your case, these placeholders will be 0. In my answer, the names of the columns in the dataframe are capitalized; names of lists start with a lower case. 
Next, I would iterate through dates and check to see if each date is in dt['Date']. Each iteration through the list dates will be called date (i.e. date = dates[i]).

If date is in dt['Date'], I would append the Sales data for that date into sales. You can find the date in the dataframe through this command: df['Date']==date.  So, to append the corresponding Sales data into the list, I would use this command sales.append(df[df['Date']==date]['Sales'].
If date is NOT in dt['Date'], I would append a placeholder into sales (i.e. sales.append(0).

Once you iterate through all the dates in the list, I would create the final dataframe with dates and sales. The final dataframe should have both your original data and placeholders for dates that were not in the original data.
I have a pivot table which has an index of dates ranging from 01-01-2014 to 12-31-2015. I would like the index to range from 01-01-2013 to 12-31-2016 and do not know how without modifying the underlying dataset by inserting a row in my pandas dataframe with those dates in the column I want to use as my index for the pivot table.
Is there a way to accomplish this wihtout modifying the underlying dataset?