Zecca Lehn ZeccaLehn

Firm Name	Investment Sector	Location (City)	Investment Stage	URL
1776	Technology, Health, Transportation, Energy, Education	Washington, D.C.	Early Stage Venture, Seed	https://www.1776.vc/
11.2 Capital	Healthcare, Security, Finance	San Francisco, CA	Early Stage, Seed	http://www.112capital.com/
122 West Ventures	Information Technology, Telecoms, Media, and Communications	San Francisco, CA	Early Stage	122west.vc/
1517 Fund	Clean Technology, Consumer Discretionary, Healthcare, Industrials, Information Technology, Telecoms, Media, and Communications	San Francisco, CA	Early Stage: Seed, Early Stage: Start-up	www.1517fund.com
1confirmation	Financial Services	San Francisco, CA	Early Stage Venture, Seed	www.1confirmation.com
3Rodeo	Business Services, Information Technology, Telecoms, Media, and Communications	Los Angeles, CA	Early Stage, Early Stage: Seed	www.3rodeo.com
4490 Ventures	Technology, Financial Services, Agriculture, Education	Madison, WI	Early Stage Venture, Seed	http:

	pip install cryptography

	-----------------


	from cryptography.fernet import Fernet
	from cryptography.hazmat.primitives import hashes
	from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC
	import base64
	import os

	## Download
	from google.colab import files
	df.to_csv('df.csv')
	files.download('df.csv')

	## Upload
	from google.colab import files
	df = files.upload()

	## Save CSV on remotely in Colab

	from urllib.request import urlopen
	from bs4 import BeautifulSoup

	import pandas as pd
	import random
	from urllib.parse import urlparse
	import urllib.request
	import lxml.html

	# randLink = str(seedFunds.iloc[int(random.uniform(1, len(seedFunds))), 4])

	import pandas as pd
	import seaborn as sns
	import matplotlib.pyplot as plt

	data = pd.read_csv('Stages.csv').dropna()

	x = "Stage"
	y = "Experimental"

	plt.figure(figsize=(15,16))

	var allDeals = document.getElementsByClassName('u-uncoloredLink js-syndicate_click');

	var links = []
	for (var i=0; i < allDeals.length; i++) {
	links.push(allDeals[i].getAttribute('data-url'));
	};

	var csvContent = "data:text/csv;charset=utf-8,";
	links.forEach(function(rowArray){
	csvContent += rowArray + "\r\n";

	import requests, zipfile, io

	url = 'https://www.huduser.gov/portal/datasets/hads/hads2013n_ASCII.zip'
	filename = 'thads2013n.txt'

	r = requests.get(url)
	z = zipfile.ZipFile(io.BytesIO(r.content))
	z.extractall()

	import pandas as pd

	import pandas as pd
	from IPython.display import FileLinks # FileLink
	import os

	data = pd.DataFrame([['a', 'b'],['c', 'd'],['e','f']], columns = ['foo', 'bar']) # .values.tolist()
	directory = 'testdata/'
	filename = 'data2.csv'
	pathtofile = directory + filename

	if not os.path.exists(directory):