It possible a very fast metadata scraping (Pandas read_sas can also do it if you pass the value iterator=True). This package offers the possibility to read only the metadata making Some specific columns, and you want to do it quick.
Look to many (sas) files looking for the datasets that contain Pandas read_sas reads those labels,īut in order to recover them you have to work a bit harder.Ĭompared to R Haven, pyreadstat offers the possibility to read only the headers: Sometimes you want to take a Labels, you as user will have to take the decision whether to use those values or not. In addition pyreadstat exposes the variable labels in an easy way (see later). However it is still possible to manually set the encoding. To utf-8, so that you don't have to care about that anymore. Thas is possible because readstat extracts the original encoding and translates If you want strings you have to specify the encoding manually. Encoding On python 3, pandas.read_sas reads all strings as bytes. However, it is possible to keep the original pandas behavior and get always datetimes.Ĥ. Pyreadstat transforms dates to dates and datetimes to datetimes, so that you have a better correspondence with the originalĭata. To know looking only at the data if the variable was originally a datetime (if it had a time) or not. That means if you have a date such a '01-01-2018' it will be transformed to '01-01-2018 00:00:00' (it always inserts a Reading dates and datetimes sas7bdat and pandas.read_sas convert both date and datetime variables into datetime. Pyreadstat can do that and also extract value labels from SPSS and STATA files.ģ. Reading Value Labels Neither sas7bdat and pandas.read_sas gives the possibility to read sas7bcat catalog files. Pyreadstat is the fastest for python and matches the speeds of R Haven. Good Performance: Here a comparison of reading a 190 Mb sas7dat file having 202 K rowsīy 70 columns with numeric, character and date-like columns using different methods. The file itself in the case of spss or stata, or in catalog files in sas), convert both dates and datetime variables to datetime,Īnd you have to specify the encoding otherwise in python 3 instead of strings you get bytes.ġ. Possibility to recover value labels (stored in However, those methods are slow (important if you want to read several large files), do not give the Python) package sas7bdat or the (cythonized) methodįrom pandas. That is already possible using either the (pure
The original motivation came from reading sas7bdat files in python. The original applications in this regard. Do not use it for critical tasks such as reporting to the authorities. The results may have inaccuracies deriving from the fact most of the data formatsĪre not open. If you would like to read R RData and Rds files into python in an easy way, Meaning pyreadstat is a python equivalent to R Haven.ĭetailed documentation on all available methods is in the Readstat is the library used in the back of the R library This module is a wrapper around the excellent Readstat C library byĮvan Miller. A python package to read and write sas (sas7bdat, sas7bcat, xport), spps (sav, zsav, por) and stata (dta) data files
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