load_eprime_log

bidsaid.parsers.load_eprime_log(log_filepath, convert_to_seconds=None, initial_column_headers=('ExperimentName', 'Subject'))[source]

Loads E-Prime 3 log file as a Pandas Dataframe.

Important

If the log file extension is “edat3”, use bidsaid.parsers.convert_edat3_to_tsv() to convert it to text form. If exporting manually, remove the checkmark from the “Unicode” field. The type of text file the edat file is exported as is irrelevent.
Data are assumed to have at least one element that is an digit or float during parsing.

Parameters

log_filepathstr or Path: Path to the Presentation log file (i.e text, log, excel files).
convert_to_secondslist[str] or None, default=None: Convert the time resolution of the specified columns from milliseconds to seconds. See EPrime Timing.
initial_column_headersIterable[str], default=(“ExperimentName”, “Subject”): The initial column headers for data.

Returns

pandas.Dataframe: A Pandas DataFrame of the behavioral log data.

Notes

This function works by first identifying the line containing the column headers specified in initial_column_headers and using that line to extract the delimiter (assumed to be the delimiter for the data). After, all blank lines are removed then the remaining lines in the log file is iterated through to identify the boundaries of the experimental log data. Data is assumed to to contain at least one digit or float (which includes NaN).