utils

Tools for file handling, logger parametrization, dataframe manipulation…

Functions

column_names_to_snake_case(df)	Converts the dataframe's column names from camel case to snake case, and replace spaces by underscores
concatenate_non_na(row, col_names)	Function to concatenate values of N columns into a list, excluding NaN
convert_to_path(input_path)	Return the input_path in a PathLike format.
download_from_geo(gsm_ids_to_download, ...)	Download idat files from GEO (Gene Expression Omnibus) given one or several GSM ids.
download_from_link(dl_link, output_folder[, ...])	Download a file and save it to the target.
get_chromosome_number(chromosome_id[, ...])	From a string representing the chromosome ID, get the chromosome number.
get_column_as_flat_array(df, column[, remove_na])	Get values from one or several columns of a pandas dataframe, and return a flatten list of the values.
get_files_matching(root_path, pattern)	Equivalent to Path.rglob() for MultiplexedPath.
get_logger([level])	Get the current logger and sets its level if the parameter level is defined
get_logger_level()	return the current logger level
get_resource_folder(module_path[, ...])	Find the resource folder, and creates it if it doesn't exist and if the parameter is set to True (default)
load_object(filepath[, object_type])	Load any object from a pickle file:
merge_alt_chromosomes(chromosome_id)	Merges the alternative chromosomes with their respective reference chromosome, e.g. 22_KI270928V1_ALT-> 22.
merge_dataframe_by(df, by, **kwargs)	Merge a dataframe by one or several columns, using the merge_series_values function :param df: input dataframe :type df: pandas.DataFrame
merge_series_values(items[, how])	Merge the values of a series into a single value.
remove_probe_suffix(probe_id)	Remove the last part of a probe ID, split by underscore.
save_object(object_to_save, filepath)	Save any object as a pickle file
set_channel_index_as(df, column[, drop])	Use an existing column specified by argument column as the new channel index.
set_level_as_index(df, level[, drop_others])	Change the index of a MultiIndexed DataFrame, to a single Index, using a level of the MultiIndex.
set_logger(level)	Set the logger verbosity level