In most cases, data acquired by Expyriment needs to be further processed before a statistical analysis can be performed. This processing entails an aggregation of the dependent variables over all factor-level combinations of the experimental design. Expyriment provides an easy, but flexible way to automate this process with the included data preprocessing module of the misc package (:doc:`expyriment.misc.data_preprocessing`).
In some cases, one might export the recorded data to preprocess it in other programmes. Expyriment allows for this, too.
The method misc.data_preprocessing.write_concatenated_data() in
:doc:`Data Preprocessing <expyriment.misc.data_preprocessing>`
allows to export the concatenated data as a CSV (comma separated values) file.
The method misc.data_preprocessing.write_concatenated_data() in
:doc:`Data Preprocessing <expyriment.misc.data_preprocessing>`
also allows to export the concatenated data as an R data frames,
which can then be imported into R.
Please be aware that this functionality needs the rpy2 package installed.
Alternatively, you may use the R module expyriment_data.R to handle xpd files without
data preprocessing in Python. The R function read.expyriment.data concatinates all
raw data and returns an R data frame with all subjects. Between subject factors will
be added as variables to the data matrix.