convert traffik from json files which generates from pcap to csv

json2csv.py

import json
import pandas as pd
import sys
import glob, os

def jsonToDataframe(file):
	classify = file.replace(".json","")
	print("Reading", file)
	with open(file, 'r') as f:
		json_buff = json.load(f)
		f.close()

	for i,item in enumerate(json_buff):
		"""try:
			item["_source"]["layers"].pop('frame')
			item["_source"]["layers"].pop('_ws')
			item["_source"]["layers"]["ip"].pop('ip.checksum')
		except KeyError: pass"""

		dns_key = None
		try:
			dns_data = item["_source"]["layers"]["dns"]
			dns_key = 'dns'
		except KeyError: pass

		try:
			dns_data = item["_source"]["layers"]["mdns"]
			dns_key = 'mdns'
		except KeyError: pass

		if dns_key != None:
			for dnsitem_key, dnsitem_val in dns_data.items():
				if dnsitem_key == 'Answers' or dnsitem_key == 'Queries' or dnsitem_key == 'Authoritative nameservers':
					problematic_dns = dns_data[dnsitem_key]
					if problematic_dns != '':
						for problematic_key,problematic_data in problematic_dns.items():
							item["_source"]["layers"][dns_key][dnsitem_key] = {'details':problematic_data}

		if item["_source"]["layers"]["eth"]["eth.src"] != "ff:ff:ff:ff:ff:ff":
			item["_source"]["layers"]["eth"].pop('eth.src')
			item["_source"]["layers"]["eth"].pop('eth.src_tree')
		if item["_source"]["layers"]["eth"]["eth.dst"] != "ff:ff:ff:ff:ff:ff":
			item["_source"]["layers"]["eth"].pop('eth.dst')
			item["_source"]["layers"]["eth"].pop('eth.dst_tree')

		item["_source"]["layers"]["class"] = classify if classify.count('normal') < 1 else 'normal'
		json_buff[i] = item["_source"].pop('layers')
	data = pd.io.json.json_normalize(json_buff)

	cols = data.columns.tolist()
	cols.remove('class')
	cols.append('class')
	return data[cols]

df = pd.DataFrame()
for file in sorted(glob.glob("*.json")):
	df = df.append(jsonToDataframe(file))
	df.info(verbose=False)
df.replace({'\"':'','\'':''},inplace=True,regex=True)
print("Finish importing all json files in current dir")

cols = df.columns.tolist()
cols.remove('class')
cols.append('class')

df[cols].to_csv(path_or_buf='out.csv', index=False, encoding='utf-8')
df.info(verbose=False)
print("Success compiling files into out.csv!")