and some support for out-of-core computations pandas has minimal dict-like hdfstore classwhich uses pytables to store pandas objectsin [ ]store pd hdfstore('mydata 'in [ ]store['obj 'frame in [ ]store['obj _col'frame[' 'in [ ]store out[ ]file pathmydata obj dataframe obj _col series objects contained in the hdf file can be retrieved in dict-like fashionin [ ]store['obj 'out[ ] message hello world foo if you work with huge quantities of datai would encourage you to explore pytables and py to see how they can suit your needs since many data analysis problems are io-bound (rather than cpu-bound)using tool like hdf can massively accelerate your applications hdf is not database it is best suited for write-onceread-many datasets while data can be added to file at any timeif multiple writers do so simultaneouslythe file can become corrupted reading microsoft excel files pandas also supports reading tabular data stored in excel (and higherfiles using the excelfile class interally excelfile uses the xlrd and openpyxl packagesso you may have to install them first to use excelfilecreate an instance by passing path to an xls or xlsx filexls_file pd excelfile('data xls'data stored in sheet can then be read into dataframe using parsetable xls_file parse('sheet ' data loadingstorageand file formats www it-ebooks info