1. A computer-implemented method to generate a graphical visualization in a web-based document application, comprising: identifying a data type for each column in a data table having a first set of data; differentiating the data types between each of the columns in the data table; determining a second data set derived from the first data set and corresponding to at least one graphical visualization with an expected data set in a plurality of graphical visualizations, and when the data type for a respective column is not relevant to the expected data set of the at least one graphical visualization, removing the respective column in the data table; selecting a set of graphical visualizations comprised of each graphical visualization having the expected data set suitable for the second data set; ranking, based on a criteria and the second data set, each graphical visualization in the set of graphical visualizations to graphically represent the second data set; generating at least one graphical visualization from the set of graphical visualizations for display based on the ranking; and determining each of the second data sets by: rearranging at least one of the columns to correspond with a respective graphical visualization in the set of graphical visualizations, and partitioning the columns in the data table to form separate partitioned second data sets, each set having columns with similar data types; and examining the partitioned second data sets to determine respective data structures.
1. A computer-implemented method to generate a graphical visualization in a web-based document application, comprising: identifying a data type for each column in a data table having a first set of data; differentiating the data types between each of the columns in the data table; determining a second data set derived from the first data set and corresponding to at least one graphical visualization with an expected data set in a plurality of graphical visualizations, and when the data type for a respective column is not relevant to the expected data set of the at least one graphical visualization, removing the respective column in the data table; selecting a set of graphical visualizations comprised of each graphical visualization having the expected data set suitable for the second data set; ranking, based on a criteria and the second data set, each graphical visualization in the set of graphical visualizations to graphically represent the second data set; generating at least one graphical visualization from the set of graphical visualizations for display based on the ranking; and determining each of the second data sets by: rearranging at least one of the columns to correspond with a respective graphical visualization in the set of graphical visualizations, and partitioning the columns in the data table to form separate partitioned second data sets, each set having columns with similar data types; and examining the partitioned second data sets to determine respective data structures. 2. The computer-implemented method according to claim 1 , wherein identification of the data type is determined by analyzing information from each of the columns in the data table, the extracted information including at least one of primitive types of column values, column labels, value formatting, known values and customized properties.