Jonathan Kim jykim16

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I hereby claim:

I am jykim16 on github.
I am jykim16 (https://keybase.io/jykim16) on keybase.
I have a public key whose fingerprint is 3D86 5D65 4E4F 725D 5F48 5304 A600 34C5 FB9E 98AB

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Download the following repositories and run yarn install in each:

	import pandas as pd
	df = pd.read_csv("sample_data_3.csv")
	df['ts'] = pd.to_datetime(df['ts'])

	# Consider only the rows with country_id = "BDV" (there are 844 such rows).
	# For each site_id, we can compute the number of unique user_id's found in these 844 rows.
	# Which site_id has the largest number of unique users? And what's the number?
	is_BDV = df['country_id']=='BDV'
	df_is_BDV = df[is_BDV]
	df_is_BDV_by_site = df_is_BDV.groupby('site_id')

	#use:
	#get_product_ranking('sample_data.tsv', 1)

	import json
	from collections import defaultdict

	def get_product_ranking(file, rank_method=1):
	# Outputs most popular product(s) based on rank method
	# rank_method = 1 is based on the unique number of users who purchased each product
	# rank_method = 2 is based on the total quantity of each product sold

	def equalsWhenOneCharRemoved(x, y):
	lengthDiff = len(y) - len(x)
	if not (lengthDiff == 1 or lengthDiff == -1):
	return False
	for pointer in range(len(x)):
	if x[pointer] == y[pointer]:
	continue
	else:
	if x[pointer:] == y[pointer+1:]:
	return True