Uliana Ustinova 1vth1nk3r

1vth1nk3r / pillow_sql

Last active June 10, 2023 10:30

Pillow Palooza project sql questons

	1. What is the most common room type in NYC Airbnb listings?
	'entire home/apt' — 13266, but 'private room' pretty close

	SELECT room_type, count(*) FROM "room_types"
	GROUP BY room_type;


	2. What is the average price of a listing by room type?
	shared - 53.65, entire – 197.17, private – 81.67

1vth1nk3r / user-months

Last active November 16, 2021 14:57

	# copying a part of userinfo, filling empty churn_date with the year end, getting months
	users2 = users[['user_id','reg_date','churn_date']].copy()
	users2['churn_date'] = users2['churn_date'].fillna(pd.to_datetime('2018-12-31', format='%Y-%m-%d') )
	users2['reg_month'] = users2['reg_date'].dt.month
	users2['churn_month'] = users2['churn_date'].dt.month

	# black magic. making rows with months when the user was subscribed
	# 0 1 .. 12
	# true false user_id
	def makemonths(row):

1vth1nk3r / dtc: Improving Data Visualizations 0

Last active December 10, 2021 08:28

	f, (ax1, ax2) = plt.subplots(1, 2, figsize = (15, 15))

	sns.barplot('people_per_market', 'state', hue = 'is_selected',
	dodge = False, data = markets_by_state, ax = ax1)
	sns.scatterplot('log_pop', 'log_markets', hue = 'is_selected',
	data = markets_by_state, ax = ax2, s = 100)
	ax1.legend_.remove()
	ax2.legend_.remove()

1vth1nk3r / seaborn from dtc 0 style

Last active December 10, 2021 08:28

	import seaborn as sns

	sns.set() #default sns style
	sns.set_style('whitegrid') # "white", "dark", "whitegrid", "darkgrid", "ticks"

	sns.set_palette('Purples')
	# divergent RdBu, PRGn, RdBu_r, PRGn_r
	# sequential Greys, Blues, PuRd, GnBu
	# bright, colorblind
	# custom ["#39A7D0", "#36ADA4"]