Operations between series require non-duplicated indices, otherwise Pandas doesn’t know how to align values in calculations. This isn’t the case with your data currently. If you are certain that your series are aligned by position, you can call reset_index on each dataframe:
PriceList[0] is a float. PriceList[0][1] is trying to access the first element of a float. Instead, do or
PriceList[0] is a float. PriceList[0][1] is trying to access the first element of a float. Instead, do or
With a clustered index the rows are stored physically on the disk in the same order as the index. Therefore, there can be only one clustered index. With a non clustered index there is a second list that has pointers to the physical rows. You can have many non clustered indices, although each new index … Read more
Reference: Data Structures > More on Lists Caveats follow Note that while this is perhaps the cleanest way to answer the question as asked, index is a rather weak component of the list API, and I can’t remember the last time I used it in anger. It’s been pointed out to me in the comments that because this answer is heavily … Read more
An index is used to speed up searching in the database. MySQL have some good documentation on the subject (which is relevant for other SQL servers as well): http://dev.mysql.com/doc/refman/5.0/en/mysql-indexes.html An index can be used to efficiently find all rows matching some column in your query and then walk through only that subset of the table to … Read more
Reference: Data Structures > More on Lists Caveats follow Note that while this is perhaps the cleanest way to answer the question as asked, index is a rather weak component of the list API, and I can’t remember the last time I used it in anger. It’s been pointed out to me in the comments that because this answer is heavily … Read more
I think the problem is given in the error message, although it is not very easy to spot: ‘Too many indices’ means you’ve given too many index values. You’ve given 2 values as you’re expecting data to be a 2D array. Numpy is complaining because data is not 2D (it’s either 1D or None). This is a … Read more
I think the problem is given in the error message, although it is not very easy to spot: ‘Too many indices’ means you’ve given too many index values. You’ve given 2 values as you’re expecting data to be a 2D array. Numpy is complaining because data is not 2D (it’s either 1D or None). This is a … Read more
DataFrame.reset_index is what you’re looking for. If you don’t want it saved as a column, then do: If you don’t want to reassign: