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parse_345.py
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parse_345.py
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#!/usr/bin/env python
# coding: utf-8
# ## Corporate insider trading data ##
# This notebook contains a few functions to parse forms 3, 4 and 5 (see the [SEC FAQ](https://www.sec.gov/fast-answers/answersform345htm.html) for details about these forms). The function *parse_345()* takes the form and return a dataframe in which each row is a transaction reported in the form. The text from the request serves as input for the *parse_345()*. The input is cleaned and later passes through the function that extracts the data from the form.
#
# **Caveats:**
# Current function covers only files with xml. Function *parse_345()* is a parser. You need to feed a SEC txt link into it. There are many python and r packages to get a direct link to the filings.
# required
import pandas as pd
from bs4 import BeautifulSoup as bs
import requests
import re
import numpy as np
def parse_345(link):
def clean_text_xml(file):
page = file.split("\\n")
cleanedPage = ""
counter = 0
documentStart = re.compile('\<XML\>')
documentEnd = re.compile('\<\/XML\>')
for line in page:
if counter == 0:
if documentStart.search(line) is not None:
counter = counter + 1
else:
continue
else:
if documentEnd.search(line) is not None:
counter = 0
else:
cleanedPage = cleanedPage + line + " "
cleanedPage = bs(cleanedPage, "xml")
return(cleanedPage)
def get_identity(text):
counter = 0
infoList = list()
issuer = text.find("issuer")
if issuer.find("issuerCik") is not None:
infoList.append(["firmCIK", issuer.find("issuerCik").text.strip()])
if issuer.find("issuerName") is not None:
infoList.append(["firmName", issuer.find("issuerName").text.strip()])
if issuer.find("issuerTradingSymbol") is not None:
infoList.append(["firmTicker", issuer.find("issuerTradingSymbol").text.strip()])
owner = text.find("reportingOwnerId")
if owner.find("rptOwnerCik") is not None:
infoList.append(["executiveCIK", owner.find("rptOwnerCik").text.strip()])
if owner.find("rptOwnerName") is not None:
infoList.append(["executiveName", owner.find("rptOwnerName").text.strip()])
address = text.find("reportingOwnerAddress")
if address.find("rptOwnerStreet1") is not None:
infoList.append(["ownerAddress1", address.find("rptOwnerStreet1").text.strip()])
if address.find("rptOwnerStreet2") is not None:
infoList.append(["ownerAddress2", address.find("rptOwnerStreet2").text.strip()])
if address.find("rptOwnerCity") is not None:
infoList.append(["ownerCity", address.find("rptOwnerCity").text.strip()])
if address.find("rptOwnerState") is not None:
infoList.append(["ownerState", address.find("rptOwnerState").text.strip()])
if address.find("rptOwnerZipCode") is not None:
infoList.append(["ownerZipCode", address.find("rptOwnerZipCode").text.strip()])
relationship = text.find("reportingOwnerRelationship")
if relationship.find("isDirector") is not None:
infoList.append(["isDirector", relationship.find("isDirector").text.strip()])
if relationship.find("isOfficer") is not None:
infoList.append(["isOfficer", relationship.find("isOfficer").text.strip()])
if relationship.find("isTenPercentOwner") is not None:
infoList.append(["isTenPercentOwner", relationship.find("isTenPercentOwner").text.strip()])
if relationship.find("isOther") is not None:
infoList.append(["isOther", relationship.find("isOther").text.strip()])
if relationship.find("officerTitle") is not None:
infoList.append(["officerTitle", relationship.find("officerTitle").text.strip()])
if relationship.find("otherText") is not None:
infoList.append(["otherText", relationship.find("otherText").text.strip()])
if text.find("documentType") is not None:
infoList.append(["documentType", text.find("documentType").text.strip()])
if text.find("periodOfReport") is not None:
infoList.append(["periodOfReport", text.find("periodOfReport").text.strip()])
if text.find("notSubjectToSection16") is not None:
infoList.append(["notSubjectToSection16", text.find("notSubjectToSection16").text.strip()])
if text.find("dateOfOriginalSubmission") is not None:
infoList.append(["dateOfOriginalSubmission", text.find("dateOfOriginalSubmission").text.strip()])
dataDict = dict()
for item in infoList:
dataDict[item[0]] = item[1]
data = pd.DataFrame.from_dict([dataDict])
return(data)
def get_transaction_row(transaction):
infoTransaction = list()
if transaction.find("securityTitle") is not None:
infoTransaction.append(["securityTitle", transaction.find("securityTitle").text.strip()])
if transaction.find("transactionDate") is not None:
infoTransaction.append(["transactionDate", transaction.find("transactionDate").text.strip()])
if transaction.find("conversionOrExercisePrice") is not None:
infoTransaction.append(["conversionOrExercisePrice", transaction.find("conversionOrExercisePrice").text.strip()])
if transaction.find("transactionCoding") is not None:
trnsctnCoding = transaction.find("transactionCoding")
if trnsctnCoding.find("transactionFormType") is not None:
infoTransaction.append(["transactionFormType", trnsctnCoding.find("transactionFormType").text.strip()])
if trnsctnCoding.find("transactionCode") is not None:
infoTransaction.append(["transactionCode", trnsctnCoding.find("transactionCode").text.strip()])
if trnsctnCoding.find("equitySwapInvolved") is not None:
infoTransaction.append(["equitySwapInvolved", trnsctnCoding.find("equitySwapInvolved").text.strip()])
if transaction.find("transactionAmounts") is not None:
trnsctnAmounts = transaction.find("transactionAmounts")
if trnsctnAmounts.find("transactionShares") is not None:
infoTransaction.append(["transactionShares", trnsctnAmounts.find("transactionShares").text.strip()])
if trnsctnAmounts.find("transactionPricePerShare") is not None:
infoTransaction.append(["transactionPricePerShare", trnsctnAmounts.find("transactionPricePerShare").text.strip()])
if trnsctnAmounts.find("transactionAcquiredDisposedCode") is not None:
infoTransaction.append(["transactionAcquiredDisposedCode", trnsctnAmounts.find("transactionAcquiredDisposedCode").text.strip()])
if transaction.find("exerciseDate") is not None:
infoTransaction.append(["exerciseDate", transaction.find("exerciseDate").text.strip()])
if transaction.find("expirationDate") is not None:
infoTransaction.append(["expirationDate", transaction.find("expirationDate").text.strip()])
if transaction.find("underlyingSecurity") is not None:
trnsctnUnderlying = transaction.find("underlyingSecurity")
if trnsctnUnderlying.find("underlyingSecurityTitle") is not None:
infoTransaction.append(["underlyingSecurityTitle", trnsctnUnderlying.find("underlyingSecurityTitle").text.strip()])
if trnsctnUnderlying.find("underlyingSecurityShares") is not None:
infoTransaction.append(["underlyingSecurityShares", trnsctnUnderlying.find("underlyingSecurityShares").text.strip()])
if transaction.find("sharesOwnedFollowingTransaction") is not None:
infoTransaction.append(["sharesOwnedFollowingTransaction", transaction.find("sharesOwnedFollowingTransaction").text.strip()])
if transaction.find("directOrIndirectOwnership") is not None:
infoTransaction.append(["directOrIndirectOwnership", transaction.find("directOrIndirectOwnership").text.strip()])
if transaction.find("natureOfOwnership") is not None:
infoTransaction.append(["natureOfOwnership", transaction.find("natureOfOwnership").text.strip()])
return(infoTransaction)
def get_non_derivative_table(text):
tableNonDerivative = text.find_all(re.compile(r"nonDerivativeTransaction|nonDerivativeHolding"))
infoNonTable = list()
for transaction in tableNonDerivative:
transactionDict = dict()
infoTransaction = get_transaction_row(transaction)
for item in infoTransaction:
transactionDict[item[0]] = item[1]
transactionDict["table"] = "I: Non-Derivative Securities"
infoNonTable.append(pd.DataFrame.from_dict([transactionDict]))
if len(infoNonTable) > 0:
data = pd.concat(infoNonTable, sort = False, ignore_index = True)
else:
data = pd.DataFrame()
return(data)
def get_derivative_table(text):
tableDerivative = text.find_all(re.compile(r"derivativeTransaction|derivativeHolding"))
infoTable = list()
for transaction in tableDerivative:
infoTransaction = get_transaction_row(transaction)
transactionDict = dict()
for item in infoTransaction:
transactionDict[item[0]] = item[1]
transactionDict["table"] = "II: Derivative Securities"
infoTable.append(pd.DataFrame.from_dict([transactionDict]))
if len(infoTable) > 0:
data = pd.concat(infoTable, sort = False, ignore_index = True)
else:
data = pd.DataFrame()
return(data)
linkRequest = str(requests.get(link, headers={'User-Agent': 'Mozilla'}).content)
text = clean_text_xml(linkRequest)
identityData = get_identity(text)
dataNonTable = get_non_derivative_table(text)
dataDerivativeTable = get_derivative_table(text)
identityData["edgar.link"] = link
dataNonTable["edgar.link"] = link
dataDerivativeTable["edgar.link"] = link
data = pd.concat([dataNonTable,dataDerivativeTable], sort = False, ignore_index = True)
data = pd.merge(data, identityData, on = "edgar.link")
if text.find("footnotes") is not None:
data["footnotes"] = text.find("footnotes").text
return(data)