statsmodels offers some functions for input and output. These include a reader for STATA files, a class for generating tables for printing in several formats and two helper functions for pickling.
Users can also leverage the powerful input/output functions provided by pandas.io. Among other things, pandas (a statsmodels dependency) allows reading and writing to Excel, CSV, and HDF5 (PyTables).
foreign.StataReader(fname[, missing_values, ...]) | Stata .dta file reader. |
foreign.StataWriter(fname, data[, ...]) | A class for writing Stata binary dta files from array-like objects |
foreign.genfromdta(fname[, missing_flt, ...]) | Returns an ndarray or DataFrame from a Stata .dta file. |
foreign.savetxt(fname, X[, names, fmt, ...]) | Save an array to a text file. |
table.SimpleTable(data[, headers, stubs, ...]) | Produce a simple ASCII, CSV, HTML, or LaTeX table from a rectangular (2d!) array of data, not necessarily numerical. |
table.csv2st(csvfile[, headers, stubs, title]) | Return SimpleTable instance, created from the data in csvfile, which is in comma separated values format. |
smpickle.save_pickle(obj, fname) | Save the object to file via pickling. |
smpickle.load_pickle(fname) | Load a previously saved object from file |
The following are classes and functions used to return the summary of estimation results, and mostly intended for internal use. There are currently two versions for creating summaries.
summary.Summary() | class to hold tables for result summary presentation |
summary2.Summary() | Methods |