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|