<commit_before>import numpy as np
import pandas as pd
import os
from os import walk

PATH = '/home/darth/Desktop/pandas'

def main():
	# get all the CSV files in the PATH dir
	files = list_files(path=PATH)

	# create empty df, where dfs shall be appended
	data = pd.DataFrame(dtype=str)

	# for file in files:
	for index in range(len(files)):
		print('{}'.format(index), end=' ')
		data = data.append(pd.read_csv(filepath_or_buffer=files[index], header=None, na_values=['--']))
		print()
	
	for index in range(0, 47):
		print(data.iloc[index])

def list_files(path):
	file_list = []
	for (dirpath, dirnames, filenames) in walk(path):
		file_list.extend(os.path.join(dirpath, filename) for filename in filenames)
	return file_list

if __name__ == '__main__':
	main()<commit_msg>Gives the data summary for columns 0, 2-12, 17, 19, and 21 -- in the Kyoto University honeypot system dataset<commit_after>import numpy as np
import pandas as pd
import os
from os import walk

PATH = '/home/darth/Desktop/pandas'

def main():
	# get all the CSV files in the PATH dir
	files = list_files(path=PATH)

	# create empty df, where dfs shall be appended
	data = pd.DataFrame(dtype=str)

	# append the dfs from each file to the data df
	for file in files:
		data = data.append(pd.read_csv(filepath_or_buffer=file, header=None, engine='python'))
	
	print(data.describe())

def list_files(path):
	file_list = []
	for (dirpath, dirnames, filenames) in walk(path):
		file_list.extend(os.path.join(dirpath, filename) for filename in filenames)
	return file_list

if __name__ == '__main__':
	main()
{'fraction_non_alphanumeric': 0.11731135066582118, 'fraction_numerical': 0.008243500317057704, 'mean_word_length': 4.655913978494624, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '783739', 'n_tokens_mistral': 580, 'n_tokens_neox': 541, 'n_words': 177}