7.17. Input-Output iolib

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).

7.17.1. Examples

SimpleTable: Basic example

7.17.2. Module Reference

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()