Datasets:

ICILS
/

isco_esco_occupations_taxonomy

	import os

	def generate_labels(df, column_names, output_dir):
	"""
	Generates a list of unique values for each column in the specified dataframe,
	and writes each list to a separate file with the specified filename.

	Args:
	df (pandas.DataFrame): The dataframe to generate code lists from.
	column_names (list): A list of column names to generate code lists for.
	output_dir (str): The directory to write the code list files to.
	"""
	# Create the output directory if it doesn't exist
	os.makedirs(output_dir, exist_ok=True)

	# Iterate over the specified columns and generate a list of unique values for each column
	for column_name in column_names:
	if column_name == "ESCO_CODE":
	values = sorted(set(str(code) for code in df[column_name].tolist()))
	elif column_name == "ISCO_CODES":
	values = sorted(set(item for sublist in df[column_name].tolist() for item in sublist))
	elif column_name == "ESCO_LABELS":
	values = sorted(set(item for sublist in df[column_name].tolist() for item in sublist))
	values = sorted(set([str(val).strip() for val in values]))
	else:
	values = sorted(set(df[column_name].astype(str).tolist()))
	filename = os.path.join(output_dir, f"{column_name.lower()}.txt")
	with open(filename, "w") as f:
	f.write("\n".join(values))

	columns_list = [
	"ISCO_CODE_1",
	"ISCO_CODE_2",
	"ISCO_CODE_3",
	"ISCO_CODE_4",
	"ISCO_LABEL_1",
	"ISCO_LABEL_2",
	"ISCO_LABEL_3",
	"ISCO_LABEL_4",
	"ISCO_CODES",
	"ESCO_CODE",
	"ESCO_LABELS",
	"ESCO_OCCUPATION",
	]

	for column_name in columns_list:
	generate_labels(
	isco_structure_df,
	[column_name],
	"../isco_esco_occupations_taxonomy/labels"
	)