diff --git a/commands.txt b/commands.txt
new file mode 100644
index 00000000..5fc34bd7
--- /dev/null
+++ b/commands.txt
@@ -0,0 +1,32 @@
+
+sudo cp ~/nft-deal-score/viz/ui.R /srv/shiny-server/nft-deal-score/
+sudo cp ~/nft-deal-score/viz/server.R /srv/shiny-server/nft-deal-score/
+sudo cp ~/nft-deal-score/viz/www/styles.css /srv/shiny-server/nft-deal-score/www/
+sudo cp ~/nft-deal-score/viz/data.Rdata /srv/shiny-server/nft-deal-score
+
+sudo touch /srv/shiny-server/nft-deal-score/ui.R
+sudo touch /srv/shiny-server/nft-deal-score/server.R
+sudo touch /srv/shiny-server/nft-deal-score/www/styles.css
+sudo touch /srv/shiny-server/nft-deal-score/data.Rdata
+
+sudo cp ~/data_science/viz/thorchain-console/ui.R /srv/shiny-server/thorchain-console/
+sudo cp ~/data_science/viz/thorchain-console/server.R /srv/shiny-server/thorchain-console/
+sudo cp ~/data_science/viz/thorchain-console/www/styles.css /srv/shiny-server/thorchain-console/www/
+sudo cp ~/data_science/viz/thorchain-console/data.RData /srv/shiny-server/thorchain-console
+sudo cp ~/data_science/viz/native-token-recycling/data.RData /srv/shiny-server/native-token-recycling
+
+sudo cp ~/dfk_calculator_data.RData /rstudio-data/
+
+sudo cp ~/nft_deal_score_data.RData /rstudio-data/
+sudo cp ~/test.py /rstudio-data/
+python /rstudio-data/test.py
+sudo touch /rstudio-data/dfk_calculator_data.RData
+
+sudo touch /srv/shiny-server/thorchain-console/ui.R
+sudo touch /srv/shiny-server/thorchain-console/server.R
+sudo touch /srv/shiny-server/thorchain-console/www/styles.css
+sudo touch /srv/shiny-server/thorchain-console/data.RData
+sudo touch /srv/shiny-server/native-token-recycling/data.RData
+
+sudo cp ~/data_science/viz/thorchain-console/server.R /srv/shiny-server/thorchain-console
+sudo touch /srv/shiny-server/thorchain-console/server.R
\ No newline at end of file
diff --git a/convert_to_rdata.R b/convert_to_rdata.R
index eef89f82..771faf61 100644
--- a/convert_to_rdata.R
+++ b/convert_to_rdata.R
@@ -2,26 +2,77 @@ library(data.table)
 library(dplyr)
 library(plotly)
 
-pred_price <- read.csv('~/nft-deal-score/data/pred_price.csv') %>% as.data.table()
+isRstudio <- Sys.info()[["user"]] == 'rstudio-connect'
+
+file.location <- ifelse(
+	isRstudio
+	, "/rstudio-data/"
+	, '~/git/nft-deal-score/viz/'
+)
+
+read_csv <- function(fname) {
+	dir <- ifelse(isRstudio, '/rstudio-data/', '~/git/nft-deal-score/data/')
+	fname <- paste0(dir, fname)
+	dt <- read.csv(fname) %>% as.data.table()
+}
+
+# load all csvs
+pred_price <- read_csv('pred_price.csv')
 pred_price[, token_id := as.numeric(token_id) ]
 pred_price <- pred_price[ collection != 'meerkatmillionaires' ]
 pred_price <- pred_price[order(token_id)]
 
-attributes <- read.csv('~/nft-deal-score/data/attributes.csv') %>% as.data.table()
-feature_values <- read.csv('~/nft-deal-score/data/feature_values.csv') %>% as.data.table()
-sales <- read.csv('~/nft-deal-score/data/model_sales.csv') %>% as.data.table()
-listings <- read.csv('~/nft-deal-score/data/listings.csv') %>% as.data.table()
-coefsdf <- read.csv('~/nft-deal-score/data/coefsdf.csv') %>% as.data.table()
-tokens <- read.csv('~/nft-deal-score/data/tokens.csv') %>% as.data.table()
+attributes <- read_csv('attributes.csv')
+attributes[, feature_name := trimws(feature_name) ]
+attributes[, feature_value := trimws(as.character(feature_value)) ]
+feature_values <- read_csv('feature_values.csv')
+sales <- read_csv('model_sales.csv')
+listings <- read_csv('listings.csv')
+coefsdf <- read_csv('coefsdf.csv')
+tokens <- read_csv('tokens.csv')
+tokens[, token_id := clean_token_id]
+sales[, price := as.numeric(price)]
+sales[, token_id := as.numeric(token_id)]
+listings[, token_id := as.numeric(token_id)]
+listings <- listings[ !(collection == 'Stoned Ape Crew' & token_id == 764) ]
+listings <- listings[ !(collection == 'Solana Monkey Business' & token_id == 953) ]
+tokens[, token_id := as.numeric(token_id)]
 
+# manual adjustments to price
+ids_1 <- attributes[ (collection == 'Aurory') & (feature_value == 'Solana Blob') ]$token_id
+pred_price[  collection == 'Aurory' & token_id %in% eval(ids_1), pred_price := (pred_price * 0.8) ]
 
-# save(pred_price, attributes, feature_values, sales, listings, coefsdf, tokens, file='data.Rdata')
-save(pred_price, attributes, feature_values, sales, listings, coefsdf, tokens, file='~/nft-deal-score/viz/data.Rdata')
-load('~/git/nft-deal-score/viz/data.Rdata')
-write.csv(listings, '~/git/nft-deal-score/data/listings.csv', row.names=F)
-write.csv(attributes, '~/git/nft-deal-score/data/attributes.csv', row.names=F)
-write.csv(sales, '~/git/nft-deal-score/data/model_sales.csv', row.names=F)
-write.csv(sales, '~/git/nft-deal-score/data/model_sales.csv', row.names=F)
-write.csv(coefsdf, '~/git/nft-deal-score/data/coefsdf.csv', row.names=F)
-write.csv(tokens, '~/git/nft-deal-score/data/tokens.csv', row.names=F)
-write.csv(pred_price, '~/git/nft-deal-score/data/pred_price.csv', row.names=F)
\ No newline at end of file
+ids_2 <- attributes[ (collection == 'Aurory') & (feature_value == 'Long Blob Hair ') ]$token_id
+pred_price[  collection == 'Aurory' & token_id %in% eval(ids_2), pred_price := (pred_price * 0.90) ]
+
+ids_3 <- attributes[ (collection == 'Aurory') & (grepl( 'Mask', feature_value, fixed = TRUE)) ]$token_id
+pred_price[  collection == 'Aurory' & token_id %in% eval(ids_3), pred_price := (pred_price * 0.975) ]
+
+# filter for only collections that have all data
+a <- unique(pred_price[, list(collection)])
+b <- unique(sales[, list(collection)])
+c <- unique(listings[, list(collection)])
+d <- merge(merge(a, b), c)
+
+pred_price <- merge(pred_price, d, by=c('collection'))
+attributes <- merge(attributes, d, by=c('collection'))
+feature_values <- merge(feature_values, d, by=c('collection'))
+sales <- merge(sales, d, by=c('collection'))
+listings <- merge(listings, d, by=c('collection'))
+coefsdf <- merge(coefsdf, d, by=c('collection'))
+tokens <- merge(tokens, d, by=c('collection'))
+
+save(
+	pred_price
+	, attributes
+	, feature_values
+	, sales
+	, listings
+	, coefsdf
+	, tokens
+	, file = paste0(file.location,'nft_deal_score_data.Rdata')
+)
+save(
+	listings
+	, file = paste0(file.location,'nft_deal_score_listings_data.Rdata')
+)
diff --git a/format_data.py b/format_data.py
index 48c045b8..f2b71923 100644
--- a/format_data.py
+++ b/format_data.py
@@ -361,32 +361,46 @@ def solana():
 
 	collection = 'Cets On Creck'
 	collection = 'Astrals'
+
+
+
 	metadata = pd.read_csv('./data/metadata.csv')
-	print(sorted(metadata.collection.unique()))
-	metadata = metadata[metadata.collection == collection]
-	print(sorted(metadata.collection.unique()))
+	# print(sorted(metadata.collection.unique()))
+	# metadata = metadata[metadata.collection == collection]
+	# print(sorted(metadata.collection.unique()))
 	metadata = metadata[-(metadata.feature_name.isin(['adj_nft_rank_0','adj_nft_rank_1','adj_nft_rank_2','nft_rank']))]
 	len(metadata.token_id.unique())
 	id_map = pd.read_csv('./data/mint_to_token_id_map.csv')
 	id_map = pd.read_csv('./data/tokens.csv')
-	id_map = id_map[id_map.collection == collection]
+	cs = ['SOLGods']
+	id_map = id_map[id_map.collection.isin(cs)]
+	metadata = metadata[metadata.collection.isin(cs)]
+	sorted(id_map.collection.unique())
+	sorted(metadata.collection.unique())
 
-	id_map['token_id'] = id_map.token_id.astype(int)
-	metadata['token_id'] = metadata.token_id.astype(int)
+	# id_map['token_id'] = id_map.token_id.astype(int)
+	# metadata['token_id'] = metadata.token_id.astype(int)
+	id_map['token_id'] = id_map.token_id.astype(str)
+	metadata['token_id'] = metadata.token_id.astype(str)
 
-	metadata = merge(metadata, id_map[['collection','token_id','mint_address','image_url']], ensure = True)
+	metadata = merge(metadata, id_map[['collection','token_id','mint_address','image_url']], ensure = False)
+	metadata = metadata[metadata.collection.isin(cs)]
 
 	metadata['feature_name'] = metadata.feature_name.apply(lambda x: x.title() )
 	# metadata['image_url'] = metadata.token_id.apply(lambda x: 'https://metadata.degods.com/g/{}.png'.format(x - 1) )
 	metadata.head()
+	metadata = metadata[-(metadata.feature_name.isin(['Nft_Rank','Adj_Nft_Rank_0','Adj_Nft_Rank_1','Adj_Nft_Rank_2']))]
+	# print(metadata.groupby('feature_name').token_id.count().reset_index().sort_values('token_id', ascending=0).head(10))
 
 	metadata = metadata[metadata.feature_name != 'L3G3Nd4Ry']
 
-	print(sorted(metadata.collection.unique()))
-	sorted(metadata[metadata.collection == collection].feature_name.unique())
+	# print(sorted(metadata.collection.unique()))
+	# sorted(metadata[metadata.collection == collection].feature_name.unique())
+	# sorted(metadata.feature_name.unique())
 
 	# metadata[['collection']].drop_duplicates().to_csv('~/Downloads/tmp.csv', index=False)
 
+	metadata['token_id'] = metadata.token_id.astype(int)
 	for collection in metadata.collection.unique():
 		print(collection)
 		mdf = metadata[metadata.collection == collection]
diff --git a/load_data.py b/load_data.py
index ebb85525..b6e27ee9 100644
--- a/load_data.py
+++ b/load_data.py
@@ -138,6 +138,7 @@ def mints_from_me():
 		offset += 500
 	lp_df = pd.DataFrame(lp_data)
 	lp_df.to_csv('./data/me_lp_collections.csv', index=False)
+	lp_df = pd.read_csv('./data/me_lp_collections.csv')
 
 	it = 0
 	l_data = []
@@ -249,10 +250,30 @@ def mints_from_me():
 	m_df.to_csv('./data/me_update_authorities.csv', index=False)
 
 	m_df = pd.read_csv('./data/me_update_authorities.csv')
+	def f(x):
+		x = re.sub('\(|\)', '', x)
+		x = re.sub(' ', '_', x)
+		x = re.sub('\'', '', x)
+		return(x)
+	m_df['collection'] = m_df.name.apply(lambda x: f(x) )
+
+	x = 'asf (asf)'
+	f(x)
+
+	seen = [ x for x in m_df.collection.unique() if os.path.exists('./data/mints/{}/'.format(x)) and len(os.listdir('./data/mints/{}/'.format(x))) ]
+	print(len(seen))
+	# m_df = m_df.merge(lp_df)
+	len(m_df)
+	it = 0
 	rpc = 'https://red-cool-wildflower.solana-mainnet.quiknode.pro/a1674d4ab875dd3f89b34863a86c0f1931f57090/'
-	for row in m_df.iterrows():
+	for row in m_df.sort_values('collection').iterrows():
+		it += 1
+		if it % 100 == 0:
+			print('#{}/{}'.format(it, len(m_df)))
 		row = row[1]
-		collection = row['name']
+		collection = row['collection']
+		if collection in seen:
+			continue
 		update_authority = row['update_authority']
 		print('Working on {}...'.format(collection))
 		collection_dir = re.sub(' ', '_', collection)
@@ -260,7 +281,7 @@ def mints_from_me():
 		dir = './data/mints/{}/'.format(collection_dir)
 		if not os.path.exists(dir):
 			os.makedirs(dir)
-		else:
+		elif len(os.listdir(dir)):
 			# print('Already have {}.'.format(collection))
 			print('Seen')
 			continue
@@ -278,7 +299,48 @@ def mints_from_me():
 			os.system('metaboss -r {} -t 300 decode mint --list-file {} --output {}'.format(rpc, fname, dir_mints))
 
 
+	data = []
+	for path in os.listdir('./data/mints/'):
+		if os.path.isdir('./data/mints/'+path):
+			collection = re.sub('_', ' ', path).strip()
+			for fname in os.listdir('./data/mints/'+path):
+				f = './data/mints/'+path+'/'+fname
+				if os.path.isfile(f) and '.json' in f:
+					with open(f) as file:
+						j = json.load(file)
+						for m in j:
+							data += [[ collection, m ]]
+	df = pd.DataFrame(data, columns=['collection','mint_address'])
+	df = df[df.collection != 'etc']
+	df = df.drop_duplicates()
+	df['n'] = 1
+	g = df.groupby(['mint_address']).n.sum().reset_index()
+	g = g[g.n > 1]
+	tmp_0 = g[['mint_address']].merge(df).groupby('collection').n.count().reset_index().sort_values('n', ascending=0)
+	tmp_0.tail(20)
+	tmp = g.merge(df[[ 'collection','mint_address' ]])
+	tmp = tmp.sort_values(['mint_address','collection'])
+	tmp[tmp.collection == 'Fractals']
+	df[df.mint_address == '11gATLu654HjcVhkuarVy9YVm11CL74vjEmi1RhojRi']
+	# tmp.sort_values(['mint_address','collection']).head()
+	rem = tmp.collection.unique()
+	# len(rem)
+	# len(df.collection.unique())
+	# tmp.head()
+	# tmp = g[['mint_address']].merge(df).groupby('collection').n.count().reset_index().sort_values('n', ascending=0)
+	# tmp[tmp.collection == 'Fractals']
+	# tmp.head(20)
+	'Fractals' in rem
+	'Fractals' in df[-df.collection.isin(rem)].collection.unique()
+	print(sorted(df.collection.unique()))
+	len(df.collection.unique())
+	sorted(df.collection.unique)
+	df[['collection']].drop_duplicates().sort_values('collection').to_csv('~/Downloads/tmp.csv', index=False)
+	len(df[-df.collection.isin(rem)])
+	len(df[-df.collection.isin(rem)].drop_duplicates(subset=['mint_address']))
+	df[-df.collection.isin(rem)].to_csv('./data/collection_mints.csv', index=False)
 	len(df)
+	len(df.drop_duplicates(subset=['mint_address']))
 	len(df[df.twitter.notnull()])
 	len(df[ (df.twitter.notnull()) & (df.website.notnull())])
 
diff --git a/objects/saved_params.pickle b/objects/saved_params.pickle
index e69de29b..44c19886 100644
Binary files a/objects/saved_params.pickle and b/objects/saved_params.pickle differ
diff --git a/requirements.txt b/requirements.txt
index fb4a06e2..4cf7a642 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,12 +1,14 @@
-beautifulsoup4==4.10.0
+beautifulsoup4==4.11.1
+kutils==0.3.0
 matplotlib==3.3.2
 numpy==1.19.2
 pandas==1.1.3
 requests==2.24.0
-scikit_learn==1.0.1
+scikit_learn==1.0.2
+scipy==1.5.2
 seaborn==0.11.0
 selenium==3.141.0
 snowflake==0.0.3
-snowflake_connector_python==2.4.3
+snowflake_connector_python==2.7.2
 statsmodels==0.12.0
-tensorflow==2.6.0
+tensorflow==2.4.1
diff --git a/scrape_listings.R b/scrape_listings.R
new file mode 100644
index 00000000..bfb2d5c5
--- /dev/null
+++ b/scrape_listings.R
@@ -0,0 +1,95 @@
+
+isRstudio <- Sys.info()[["user"]] == 'rstudio-connect'
+if(isRstudio) {
+	source("/home/data-science/data_science/util/util_functions.R")
+} else {
+	source("~/data_science/util/util_functions.R")
+	setwd('~/git/nft-deal-score')
+}
+
+library(httr)
+library(jsonlite)
+
+
+query <- "
+	SELECT DISTINCT project_name AS collection
+	, mint AS tokenMint
+	, token_id
+	FROM solana.dim_nft_metadata
+"
+mints <- QuerySnowflake(query)
+colnames(mints) <- c('collection','tokenMint','token_id')
+
+collections <- c(
+	'meerkat_millionaires_country_club','solgods','cets_on_creck','stoned_ape_crew','degods','aurory','thugbirdz','solana_monkey_business','degenerate_ape_academy','pesky_penguins'
+)
+
+get_me_url <- function(collection, offset) {
+	return(paste0('https://api-mainnet.magiceden.dev/v2/collections/',collection,'/listings?offset=',offset,'&limit=20'))
+}
+get_smb_url <- function(page) {
+	return(paste0('https://market.solanamonkey.business/api/items?limit=40&page=',page))
+}
+
+new_listings <- data.table()
+collection <- collections[1]
+for(collection in collections) {
+	print(paste0('Working on ', collection, '...'))
+	has_more <- TRUE
+	offset <- 0
+	while(has_more) {
+		print(paste0('Offset #', offset))
+		url <- get_me_url(collection, offset)
+		response <- GET(url)
+		content <- rawToChar(response$content)
+		content <- fromJSON(content)
+		# content <- rbindlist(content, fill=T) 
+		has_more <- nrow(content) >= 20
+		if(nrow(content) > 0 && length(content) > 0) {
+			df <- merge(content, mints, by=c('tokenMint')) %>% as.data.table()
+			df <- df[, list(collection, token_id, price)]
+			offset <- offset + 20
+			new_listings <- rbind(new_listings, df)
+		} else {
+			has_more <- FALSE
+		}
+	}
+}
+
+for(collection in c('Solana Monkey Business')) {
+	print(paste0('Working on ', collection, '...'))
+	has_more <- TRUE
+	page <- 1
+	while(has_more) {
+		print(paste0('Page #', page))
+		url <- get_smb_url(page)
+		response <- GET(url)
+		content <- rawToChar(response$content)
+		content <- fromJSON(content)
+		# content <- rbindlist(content, fill=T)
+		content <- content %>% as.data.table()
+		has_more <- nrow(content) > 0 && 'price' %in% colnames(content)
+		if(has_more) {
+			content <- content[, list(mint, price)]
+			content <- unique(content)
+			content$price <- as.numeric(content$price) / (10^9)
+			has_more <- nrow(content) >= 40
+			colnames(content)[1] <- 'tokenMint'
+			df <- merge(content, mints, by=c('tokenMint')) %>% as.data.table()
+			df <- df[, list(collection, token_id, price)]
+			page <- page + 1
+			new_listings <- rbind(new_listings, df)
+		}
+	}
+}
+new_listings <- unique(new_listings)
+
+listings <- read.csv('./data/listings.csv') %>% as.data.table()
+rem <- unique(new_listings$collection)
+listings <- listings[ !(collection %in% eval(rem)), ]
+listings <- listings[, list(collection, token_id, price)]
+listings <- rbind(listings, new_listings)
+listings <- listings[order(collection, price)]
+
+write.csv(listings, './data/listings.csv', row.names=F)
+
diff --git a/scrape_sol_nfts.py b/scrape_sol_nfts.py
index db45b90c..fcfaee02 100644
--- a/scrape_sol_nfts.py
+++ b/scrape_sol_nfts.py
@@ -40,14 +40,22 @@ def how_rare_is_api():
 	j.keys()
 	t_data = []
 	metadata = pd.DataFrame()
-	for d in j['result']['data'][8:]:
-		collection = 'Cets on Creck'
-		collection = 'SOLGods'
-		collection = 'Meerkat Millionaires'
-		collection = d['url'][1:]
+	d = {
+		'Degen Apes': 'degenapes'
+		, 'Pesky Penguins': 'peskypenguinclub'
+		, 'Aurory': 'aurory'
+		, 'Solana Monkey Business': 'smb'
+		, 'Thugbirdz': 'thugbirdz'
+	}
+	for collection, url in d.items():
+		# collection = 'Cets on Creck'
+		# collection = 'SOLGods'
+		# collection = 'Meerkat Millionaires'
+		# collection = d['url'][1:]
 		print('Working on collection {}, {}, {}'.format(collection, len(t_data), len(metadata)))
-		url = 'https://api.howrare.is/v0.1/collections'+d['url']
-		url = 'https://api.howrare.is/v0.1/collections/meerkatmillionaires'
+		# url = 'https://api.howrare.is/v0.1/collections'+d['url']
+		# url = 'https://api.howrare.is/v0.1/collections/meerkatmillionaires'
+		url = 'https://api.howrare.is/v0.1/collections/'+url
 		r = requests.get(url)
 		j = r.json()
 		for i in j['result']['data']['items']:
@@ -64,27 +72,50 @@ def how_rare_is_api():
 	old = pd.read_csv('./data/tokens.csv')
 	sorted(old.collection.unique())
 	l0 = len(old)
+	do_merge = True
 	tokens = pd.DataFrame(t_data, columns=['collection','token_id','nft_rank','mint_address','image_url'])
-	# old = old.merge(tokens, how='left', on=['collection','token_id'])
-	old = old.append(tokens)
-	# old['nft_rank'] = old.nft_rank_y.fillna(old.nft_rank_y)
-	# del old['nft_rank_x']
-	# del old['nft_rank_y']
+	if do_merge:
+		old['token_id'] = old.token_id.astype(str)
+		tokens['token_id'] = tokens.token_id.astype(str)
+		old = old.merge(tokens, how='left', on=['collection','token_id'])
+		old[old.collection == 'Solana Monkey Business']
+		for c in [ 'nft_rank','mint_address','image_url' ]:
+			old[c] = old[c+'_x'].fillna(old[c+'_y'])
+			del old[c+'_x']
+			del old[c+'_y']
+		old['clean_token_id'] = old.clean_token_id.fillna(old.token_id)
+		old['chain'] = old.chain.fillna('Solana')
+	else:
+		old = old.append(tokens)
 	print('Adding {} rows'.format(len(old) - l0))
+	old[old.nft_rank.isnull()].groupby('collection').token_id.count()
 	old.to_csv('./data/tokens.csv', index=False)
 
 	old = pd.read_csv('./data/metadata.csv')
-	old = old[-(old.collection == 'Meerkat Millionaires Cc')]
+	a = old[['collection','token_id']].drop_duplicates()
+	a['exclude'] = 0
+	a['token_id'] = a.token_id.astype(str)
+	metadata['token_id'] = metadata.token_id.astype(str)
+	m = metadata.merge(a, how='left')
+	m = m[m.exclude.isnull()]
+	len(m[m.exclude.isnull()].token_id.unique())
+	del m['exclude']
+	# old = old[-(old.collection == 'Meerkat Millionaires Cc')]
 	print(sorted(old.collection.unique()))
 	l0 = len(old)
 	metadata.collection.unique()
 	# metadata = pd.DataFrame(t_data, columns=['collection','token_id','nft_rank','mint_address','image_url'])
 	# old = old.merge(tokens, how='left', on=['collection','token_id'])
-	old = old.append(metadata)
+	old = old.append(m[['collection','token_id','name','value']].rename(columns={'name':'feature_name','value':'feature_value'}) )
+	old['token_id'] = old.token_id.astype(str)
+	old = old.drop_duplicates(subset=['collection','token_id','feature_name'])
 	# old['nft_rank'] = old.nft_rank_y.fillna(old.nft_rank_y)
 	# del old['nft_rank_x']
 	# del old['nft_rank_y']
 	print('Adding {} rows'.format(len(old) - l0))
+	print(old.groupby('collection').token_id.count())
+	old[old.collection.isin(metadata.collection)]
+	old[(old.collection == 'Thugbirdz') & (old.token_id == '1206')]
 	old.to_csv('./data/metadata.csv', index=False)
 
 
@@ -580,7 +611,7 @@ def scrape_opensea_listings(browser, collections=['BAYC','MAYC']):
 	old.groupby('collection').token_id.count()
 	old.to_csv('./data/listings.csv', index=False)
 
-def scrape_listings(browser, collections = [ 'solgods','cets-on-creck','stoned-ape-crew','degods','aurory','thugbirdz','smb','degenapes','peskypenguinclub' ], alerted = [], is_listings = True):
+def scrape_listings(browser, collections = [ 'meerkat-millionaires-cc','solgods','cets-on-creck','stoned-ape-crew','degods','aurory','thugbirdz','smb','degenapes','peskypenguinclub' ], alerted = [], is_listings = True):
 	print('Scraping solanafloor listings...')
 	data = []
 	m_data = []
@@ -775,6 +806,7 @@ def scrape_listings(browser, collections = [ 'solgods','cets-on-creck','stoned-a
 
 	old = pd.read_csv('./data/listings.csv')
 	listings = pd.DataFrame(data, columns=['collection','token_id','price']).drop_duplicates()
+	listings.groupby('collection').price.min()
 	# others = scrape_magic_eden()
 	# listings = listings.append(others).drop_duplicates()
 	# d = {
@@ -788,10 +820,13 @@ def scrape_listings(browser, collections = [ 'solgods','cets-on-creck','stoned-a
 	# 	,'degods': 'DeGods'
 	# }
 	listings['collection'] = listings.collection.apply(lambda x: clean_name(x))
+	listings.groupby('collection').price.min()
+	listings.groupby('collection').price.count()
 	listings[listings.token_id=='1656']
 	listings[listings.token_id==484]
 
 	old = old[ -(old.collection.isin(listings.collection.unique())) ]
+	old = old[old.collection != 'Meerkat Millionaires Cc']
 	pred_price = pd.read_csv('./data/pred_price.csv')
 	listings.token_id.values[:3]
 	pred_price.token_id.values[:3]
diff --git a/scratch.sql b/scratch.sql
index 93f1d9a9..df84125a 100644
--- a/scratch.sql
+++ b/scratch.sql
@@ -1,3 +1,380 @@
+
+
+WITH base AS (
+	SELECT native_to_address, COUNT(1) AS n
+	FROM thorchain.swaps
+	WHERE block_timestamp >= '2022-04-01'
+	GROUP BY 1
+)
+select b.n, s.* from thorchain.swaps s 
+JOIN base b ON b.native_to_address = s.native_to_address
+where block_timestamp >= '2022-04-10'
+ORDER BY block_timestamp, n, tx_id
+LIMIT 100
+
+
+
+SELECT MIN(block_timestamp) AS mn
+, MAX(block_timestamp) AS mx
+, COUNT(1) AS n
+FROM flipside_dev_db.thorchain.liquidity_actions
+
+
+SELECT MIN(block_timestamp) AS mn
+, MAX(block_timestamp) AS mx
+, COUNT(1) AS n
+FROM flipside_dev_db.thorchain.liquidity_actions
+
+
+SELECT MIN(block_timestamp) AS mn
+, MAX(block_timestamp) AS mx
+, COUNT(1) AS n
+FROM flipside_dev_db.thorchain.bond_actions
+
+SELECT 
+
+
+
+https://app.flipsidecrypto.com/dashboard/small-lp-actions-LD1XQ9
+
+
+https://app.flipsidecrypto.com/dashboard/pool-ranks-UbtLg9
+https://app.flipsidecrypto.com/dashboard/price-shift-_-JpTq
+https://app.flipsidecrypto.com/dashboard/tho-rchain-average-age-of-synth-holders-Z2AXIx
+https://app.flipsidecrypto.com/dashboard/thor-64-standardized-tvl-over-time-all-pools-Zf6w-L
+https://app.flipsidecrypto.com/dashboard/tho-rchain-pool-ranks-RNNzza
+https://app.flipsidecrypto.com/dashboard/thorchain-synth-mints-burns-aH0lCY
+
+https://discord.com/channels/889577356681945098/889577399308656662/951960381411192842
+
+solana-keygen recover 'prompt:?key=3/0' --outfile ~/.config/solana/tmp.json
+
+
+SELECT *
+, instructions[0]:parsed:info:lamports / POWER(10, 9) AS sol_amount
+FROM solana.fact_transactions
+WHERE block_timestamp >= '2022-01-02'
+AND tx_id = '5H6UQqbxa2wtryax6SAZgjXB9B6Za4ip6GsheqopAsbLCrLMPvYf35H551SaAKNy6bi6BceRGtkwwP9LRoN7RiVo'
+
+
+SELECT *
+FROM solana.fact_transfers
+WHERE block_timestamp >= '2022-01-02'
+AND tx_id = '393xRouisz4DuMxzARAqPy7FVYQZtkfpmAMuDXXj39uvASFYtMijHM9hyVzXSocsB4fk2woLNfnWTM4qXJxJsWBw'
+
+SELECT lp.tx_id
+, lp.signers[0] as signer
+, t.instructions[0]:parsed:info:lamports / POWER(10, 9) AS sol_amount
+FROM solana.fact_staking_lp_actions lp
+JOIN solana.fact_transactions t ON t.tx_id = lp.tx_id
+WHERE lp.block_timestamp >= '2022-01-01'
+AND lp.event_type = 'delegate' 
+AND tx_id = '393xRouisz4DuMxzARAqPy7FVYQZtkfpmAMuDXXj39uvASFYtMijHM9hyVzXSocsB4fk2woLNfnWTM4qXJxJsWBw'
+LIMIT 10
+
+sudo apt-get build-dep python E: You must put some 'deb-src' URIs in your sources.list
+
+
+SELECT project_name
+, COUNT(1) AS n
+, SUM( CASE WHEN address IS NULL THEN 1 ELSE 0 END) AS n_nulls
+FROM crosschain.address_labels
+WHERE blockchain = 'solana'
+AND label_subtype = 'nf_token_contract'
+GROUP BY 1
+
+-- MEv1 De-Listing
+WITH mints AS (
+	SELECT DISTINCT project_name
+	, mint
+	, token_id
+	FROM solana.dim_nft_metadata
+)
+SELECT pre_token_balances[0]:mint::string AS mint
+, t.*
+, m.project_name
+, m.token_id
+FROM solana.fact_transactions t
+JOIN mints m ON m.mint = t.pre_token_balances[0]:mint::string
+WHERE block_timestamp >= CURRENT_DATE - 30
+AND tx_id = '3CxhnTCXYX1zH6HbNESFsZLwdHfTe7RUYF8tAgB168hciVjUGggp2PwVEsnDvpd2kNqMha7kH2be7NtSTppAnXzn'
+AND instructions[0]:data = 'TE6axTojnpk'
+AND instructions[0]:programId = 'MEisE1HzehtrDpAAT8PnLHjpSSkRYakotTuJRPjTpo8'
+AND succeeded = TRUE
+LIMIT 100
+
+ENwHiaH9NA9veUqRzGozjWnTuR9xcNvHcPZVFMi3Ca9L
+
+
+WITH mints AS (
+	SELECT DISTINCT project_name
+	, mint
+	, token_id
+	FROM solana.dim_nft_metadata
+)
+SELECT instructions[0]:data AS data
+, COUNT(1) AS n
+, COUNT(1) AS nn
+FROM solana.fact_transactions t
+JOIN mints m ON m.mint = t.pre_token_balances[0]:mint::string
+WHERE block_timestamp >= '2022-04-17'
+AND instructions[0]:programId = 'M2mx93ekt1fmXSVkTrUL9xVFHkmME8HTUi5Cyc5aF7K'
+AND succeeded = TRUE
+GROUP BY 1
+ORDER BY 2 DESC
+
+
+-- MEv2 De-Listing
+WITH mints AS (
+	SELECT DISTINCT project_name
+	, mint
+	, token_id
+	FROM solana.dim_nft_metadata
+), rem AS (
+	SELECT pre_token_balances[0]:mint::string AS mint
+	, m.project_name
+	, m.token_id
+	, t.tx_id AS remove_tx
+	, block_timestamp AS remove_time
+	, ROW_NUMBER() OVER (PARTITION BY mint ORDER BY block_timestamp DESC) AS rn
+	FROM solana.fact_transactions t
+	JOIN mints m ON m.mint = t.pre_token_balances[0]:mint::string
+	WHERE block_timestamp >= CURRENT_DATE - 3
+	AND LEFT(instructions[0]:data::string, 4) IN ('ENwH','3GyW')
+	AND instructions[0]:programId = 'M2mx93ekt1fmXSVkTrUL9xVFHkmME8HTUi5Cyc5aF7K'
+), add AS (
+	SELECT pre_token_balances[0]:mint::string AS mint
+	, m.project_name
+	, m.token_id
+	, t.tx_id AS listing_tx
+	, block_timestamp AS listing_time
+	, ROW_NUMBER() OVER (PARTITION BY mint ORDER BY block_timestamp DESC) AS rn
+	FROM solana.fact_transactions t
+	JOIN mints m ON m.mint = t.pre_token_balances[0]:mint::string
+	WHERE block_timestamp >= CURRENT_DATE - 3
+	AND LEFT(instructions[0]:data::string, 4) IN ('2B3v')
+	AND instructions[0]:programId = 'M2mx93ekt1fmXSVkTrUL9xVFHkmME8HTUi5Cyc5aF7K'
+	AND succeeded = TRUE
+)
+SELECT a.*
+, r.remove_tx
+, r.remove_time
+, CASE WHEN r.remove_time IS NULL OR a.listing_time > r.remove_time THEN 1 ELSE 0 END AS is_listed
+FROM add a
+LEFT JOIN rem r ON r.mint = a.mint AND r.rn = 1
+WHERE a.rn = 1
+
+thor12209cxpf4mpm8qxdyzmm4k8mfuyjt4fysnwyjj
+
+WITH base AS (
+	SELECT from_address AS address 
+	, block_timestamp::date AS date
+	, -from_amount AS amount
+	, 'From Swap' AS tx_type
+	FROM thorchain.swaps
+	WHERE from_address = 'thor12209cxpf4mpm8qxdyzmm4k8mfuyjt4fysnwyjj'
+	AND from_asset = 'THOR.RUNE'
+
+	UNION ALL
+
+	SELECT native_to_address AS address 
+	, block_timestamp::date AS date
+	, to_amount AS amount
+	, 'To Swap' AS tx_type
+	FROM thorchain.swaps
+	WHERE native_to_address = 'thor12209cxpf4mpm8qxdyzmm4k8mfuyjt4fysnwyjj'
+	AND to_asset = 'THOR.RUNE'
+
+	UNION ALL
+
+	SELECT from_address AS address 
+	, block_timestamp::date AS date
+	, -rune_amount AS amount
+	, 'From Transfer' AS tx_type
+	FROM thorchain.transfers
+	WHERE from_address = 'thor12209cxpf4mpm8qxdyzmm4k8mfuyjt4fysnwyjj'
+
+	UNION ALL
+
+	SELECT to_address AS address 
+	, block_timestamp::date AS date
+	, rune_amount AS amount
+	, 'To Transfer' AS tx_type
+	FROM thorchain.transfers
+	WHERE to_address = 'thor12209cxpf4mpm8qxdyzmm4k8mfuyjt4fysnwyjj'
+)
+SELECT *
+FROM base
+ORDER BY date DESC
+
+68. [Hard] $RUNE Distribution
+Calculate the distribution of $RUNE holdings by address. Include RUNE that is in liquidity pools. (e.g. if I have 100 $RUNE in my wallet and LP 50, I should still be considered to be holding 100). In terms of charts, feel free to create a histogram or whichever visual you think works best!
+
+Hint: use thorchain.transfers and thorchain.liquidity_actions
+
+70. [Hard] Weighted-average LP duration
+What is the average duration of liquidity held in each pool, weighted by the size of the LP?
+
+Hint: use thorchain.liquidity_actions
+
+69. [Medium] LP Size Distribution
+What is the current distribution of LP size for each pool? You will have to use both 'add_liquidity' and 'remove_liquidity' to determine which LPs are stil current.
+
+Hint: use thorchain.liquidity_actions
+
+71. [Easy] Block Rewards vs Swap Fees
+Breakdown the yield from block rewards vs swap fees, both total and by pool. Show how the proportions have changed over time since the network started.
+
+Hint: use thorchain.block_rewards
+
+
+72. [Medium] Swap Volume vs LP Rewards
+Chart the weekly swap volume and LP rewards on the same chart. What is the relationship between the two?
+
+Hint: use thorchain.daily_pool_stats to get swap volume and earnings_to_pools from thorchain.daily_earnings to get LP rewards
+
+73. [Hard] Realized APY
+Visualize the realized APY of LP-ers that have removed liquidity from THORChain. What was their actual APY vs HODL (accounting for impermanent loss) when you pro-rate it for how long they were LP-ing for? Are certain pools out-performing others?
+
+Hint: use thorchain.liquidity_actions
+
+
+SELECT *
+FROM THORCHAIN.DAILY_POOL_STATS
+WHERE pool_name ilike '%luna%'
+ORDER BY day DESC
+
+
+WITH base AS (
+	SELECT from_address AS address 
+	, block_timestamp::date AS date
+	, rune_amount AS lp_amount
+	, 'Add LP' AS tx_type
+	FROM thorchain.liquidity_actions
+	WHERE from_address = 'thor12209cxpf4mpm8qxdyzmm4k8mfuyjt4fysnwyjj'
+	AND lp_action = 'add_liquidity'
+
+	UNION ALL
+
+	SELECT from_address AS address 
+	, block_timestamp::date AS date
+	, -rune_amount AS lp_amount
+	, 'Rem LP' AS tx_type
+	FROM thorchain.liquidity_actions
+	WHERE from_address = 'thor12209cxpf4mpm8qxdyzmm4k8mfuyjt4fysnwyjj'
+	AND lp_action = 'remove_liquidity'
+
+	UNION ALL
+
+	SELECT native_to_address AS address 
+	, block_timestamp::date AS date
+	, to_amount AS amount
+	, 'To Swap' AS tx_type
+	FROM thorchain.swaps
+	WHERE native_to_address = 'thor12209cxpf4mpm8qxdyzmm4k8mfuyjt4fysnwyjj'
+	AND to_asset = 'THOR.RUNE'
+
+	UNION ALL
+
+	SELECT from_address AS address 
+	, block_timestamp::date AS date
+	, -rune_amount AS amount
+	, 'From Transfer' AS tx_type
+	FROM thorchain.transfers
+	WHERE from_address = 'thor12209cxpf4mpm8qxdyzmm4k8mfuyjt4fysnwyjj'
+
+	UNION ALL
+
+	SELECT to_address AS address 
+	, block_timestamp::date AS date
+	, rune_amount AS amount
+	, 'To Transfer' AS tx_type
+	FROM thorchain.transfers
+	WHERE to_address = 'thor12209cxpf4mpm8qxdyzmm4k8mfuyjt4fysnwyjj'
+)
+SELECT *
+FROM base
+ORDER BY date DESC
+
+-- 2B3v: listing
+-- ENwH: de-listing
+-- 3GyW: sale
+
+WITH mints AS (
+	SELECT DISTINCT project_name
+	, mint
+	, token_id
+	FROM solana.dim_nft_metadata
+)
+SELECT pre_token_balances[0]:mint::string AS mint
+, t.*
+, m.project_name
+, m.token_id
+FROM solana.fact_transactions t
+JOIN mints m ON m.mint = t.pre_token_balances[0]:mint::string
+WHERE block_timestamp >= CURRENT_DATE - 2
+AND tx_id = '3CxhnTCXYX1zH6HbNESFsZLwdHfTe7RUYF8tAgB168hciVjUGggp2PwVEsnDvpd2kNqMha7kH2be7NtSTppAnXzn'
+AND LEFT(instructions[0]:data::string, 4) IN ('2B3v')
+AND instructions[0]:programId = 'M2mx93ekt1fmXSVkTrUL9xVFHkmME8HTUi5Cyc5aF7K'
+AND succeeded = TRUE
+LIMIT 100
+
+
+
+
+
+
+SELECT MIN(block_timestamp) AS mn
+, MAX(block_timestamp) AS mx
+, COUNT(1) AS n
+FROM flipside_prod_db.thorchain.liquidity_actions
+
+
+SELECT MIN(block_timestamp) AS mn
+, MAX(block_timestamp) AS mx
+, COUNT(1) AS n
+FROM flipside_prod_db.thorchain.prices
+
+liquidity_actions
+bond_actions
+
+
+SELECT MIN(block_timestamp) AS mn
+, MAX(block_timestamp) AS mx
+, COUNT(1) AS n
+FROM flipside_prod_db.thorchain.bond_actions
+
+
+SELECT MIN(block_timestamp) AS mn
+, MAX(block_timestamp) AS mx
+, COUNT(1) AS n
+FROM flipside_prod_db.thorchain.pool_block_balances
+WHERE rune_amount > 0 and COALESCE(rune_amount_usd, 0) = 0
+
+SELECT MIN(block_timestamp) AS mn
+, MAX(block_timestamp) AS mx
+, COUNT(1) AS n
+FROM flipside_prod_db.thorchain.pool_block_balances
+WHERE asset_amount > 0 and COALESCE(asset_amount_usd, 0) = 0
+
+SELECT *
+FROM flipside_prod_db.thorchain.pool_block_balances
+WHERE (asset_amount > 0 and COALESCE(asset_amount_usd, 0) = 0)
+OR (rune_amount > 0 and COALESCE(rune_amount_usd, 0) = 0)
+ORDER BY block_timestamp DESC
+LIMIT 10000
+
+SELECT block_timestamp::date AS date
+, COUNT(1) AS n
+FROM flipside_prod_db.thorchain.pool_block_balances
+WHERE (asset_amount > 0 and COALESCE(asset_amount_usd, 0) = 0)
+OR (rune_amount > 0 and COALESCE(rune_amount_usd, 0) = 0)
+ORDER BY block_timestamp DESC
+GROUP BY 1
+ORDER BY 1
+
+
+
 WITH active_vault_events_cte AS
   (SELECT max(block_timestamp)::string AS recency, min(block_timestamp)::string AS start_time,
           'active_vault_events' AS "table"
diff --git a/solana_model.py b/solana_model.py
index 74cc3d7e..1e14c027 100644
--- a/solana_model.py
+++ b/solana_model.py
@@ -364,12 +364,12 @@ def train_model(check_exclude=False, supplement_with_listings=True, use_saved_pa
 	collections = [ x for x in collections if not x in ['Bakc','BAKC','MAYC'] ]
 	collections = [ x for x in collections if not x in ['Astrals','Cets on Cleck','DeFi Pirates'] ]
 	collections = ['Cets on Creck']
-	collections = list(s_df[['collection']].drop_duplicates().merge(m_df[['collection']].drop_duplicates()).collection.unique())
 	s_df.groupby('collection').block_timestamp.max()
 	collections = ['Meerkat Millionaires']
+	collections = list(s_df[['collection']].drop_duplicates().merge(m_df[['collection']].drop_duplicates()).collection.unique())
 	print(sorted(collections))
 	for collection in collections:
-		if collection in ['Astrals','BAYC','MAYC']:
+		if collection in ['Astrals','Bakc','BAYC','MAYC']:
 			continue
 		if not collection in saved_params.keys():
 			saved_params[collection] = {}
@@ -381,7 +381,7 @@ def train_model(check_exclude=False, supplement_with_listings=True, use_saved_pa
 		print('\nWorking on collection {}'.format(collection))
 		sales = s_df[ s_df.collection == collection ]
 		sales[sales.sim==0].block_timestamp.max()
-		metadata = m_df[ m_df.collection == collection ].drop_duplicates()
+		metadata = m_df[ m_df.collection == collection ].drop_duplicates(subset=['token_id','feature_name'], keep='last')
 		metadata = metadata[metadata.feature_name != 'Genesis Role?']
 		metadata[metadata.token_id=='1']
 		metadata[metadata.feature_name=='Genesis Role?'].feature_value.unique()
@@ -629,7 +629,14 @@ def train_model(check_exclude=False, supplement_with_listings=True, use_saved_pa
 						mn = coefs.val.min()
 						if mn >= 0:
 							df, bst_p, bst_r = ku.get_bst_params( model, df, X_new, y, target_col, col, verbose = True, wt_col='wt', params = [bst_p] )
+					coefs['col'] = coefs.col.apply(lambda x: re.sub('std_', '', x) )
+					coefs['n'] = 0
+					n = pd.DataFrame()
+					for c in cat_metadata.columns:
+						if not c in [ 'collection','token_id' ]:
+							coefs.loc[ coefs.col == c, 'n' ] = len(cat_metadata[cat_metadata[c] == 1])
 					coefs.to_csv('./data/coefs/{}_{}_{}.csv'.format(collection, model, it), index=False)
+
 				test = ku.apply_model( model, bst_p, df, test, cur_std_pred_cols, target_col, col)
 				if model in ['rfr']:
 					df[col] = df[col] + df['rarity_value_'+it]
diff --git a/update.py b/update.py
index 6693a07e..a0b9941c 100644
--- a/update.py
+++ b/update.py
@@ -52,13 +52,16 @@ ld.add_solana_sales()
 ld.add_eth_sales()
 
 # update listings
-# ssn.scrape_listings(browser, ['smb'])
-# ssn.scrape_listings(browser, ['cets-on-creck'])
+# ssn.scrape_listings(browser, ['meerkat-millionaires-cc'])
+# ssn.scrape_listings(browser, ['thugbirdz'])
 ssn.scrape_listings(browser)
 ssn.scrape_randomearth(browser)
 ssn.scrape_opensea_listings(browser)
 # ssn.scrape_listings(browser, ['smb','aurory'])
 
+listings = pd.read_csv('./data/listings.csv')
+listings[listings.collection == 'Solana Monkey Business'].sort_values('price').head(20)
+
 # update model
 # ssn.convert_collection_names()
 # sm.train_model(True, False)
diff --git a/update_data.R b/update_data.R
new file mode 100644
index 00000000..8bcfc110
--- /dev/null
+++ b/update_data.R
@@ -0,0 +1,14 @@
+
+install.packages('reticulate')
+library(reticulate)
+
+switch(
+  Sys.info()[["user"]],
+  "rstudio-connect" = source("/home/data-science/data_science/util/util_functions.R"),
+  source("~/data_science/util/util_functions.R")
+)
+
+# use_python("/usr/local/bin/python")
+
+py_run_file("script.py")
+
diff --git a/utils.py b/utils.py
index 5c1f0c77..86a199ca 100644
--- a/utils.py
+++ b/utils.py
@@ -40,7 +40,7 @@ def clean_token_id(df):
 
 def clean_name(name):
 	x = re.sub('-', '', name).lower()
-	x = re.sub(' ', '', name).lower()
+	x = re.sub(' ', '', x).lower()
 	if x in clean_names.keys():
 		return(clean_names[x])
 	name = name.title()
diff --git a/viz/global.R b/viz/global.R
index 97c086c9..a0264728 100644
--- a/viz/global.R
+++ b/viz/global.R
@@ -1,5 +1,5 @@
 # setwd('~/git/nft-deal-score/viz')
-source("~/data_science/util/util_functions.R")
+# source("~/data_science/util/util_functions.R")
 library(data.table)
 library(shiny)
 library(ggplot2)
diff --git a/viz/server.R b/viz/server.R
index 39a33bc5..61c36667 100644
--- a/viz/server.R
+++ b/viz/server.R
@@ -1,5 +1,14 @@
 server <- function(input, output, session) {
-	load('data.Rdata')
+	# load('data.Rdata')
+
+	file.location <- ifelse(
+		Sys.info()[["user"]] == "rstudio-connect"
+		, "/rstudio-data/"
+		, '~/git/nft-deal-score/viz/'
+	)
+	load(paste0(file.location, 'nft_deal_score_data.RData'))
+	load(paste0(file.location, 'nft_deal_score_listings_data.RData'))
+	# load(paste0(file.location, 'data.RData'))
 
     metadata <- unique(attributes[, list(collection, feature_name, feature_value)])
 
@@ -81,6 +90,20 @@ server <- function(input, output, session) {
 		)
 	})
 
+	output$minfloorinput <- renderUI({
+		textInput(
+			inputId = 'minfloorinput'
+			, label = NULL
+			, width = "100%"
+		)
+	})
+	output$maxfloorinput <- renderUI({
+		textInput(
+			inputId = 'maxfloorinput'
+			, label = NULL
+			, width = "100%"
+		)
+	})
 	output$maxrarityrankinput2 <- renderUI({
 		textInput(
 			inputId = 'maxrarityrank2'
@@ -509,10 +532,12 @@ server <- function(input, output, session) {
 		}
         t <- ''
         if (nrow(data)) {
-            p <- format(round(mean(head(data$price, 100)), 1), big.mark=',')
-            f <- format(round(mean(head(data$vs_floor, 100)), 1), big.mark=',')
+			data <- head(data, 100)
+            p <- format(round(mean(data$price), 1), big.mark=',')
+            f <- format(round(mean(data$vs_floor), 1), big.mark=',')
 			data[, pct_vs_floor := (vs_floor + price) / price ]
-            pct <- format(round(mean(head(data$pct_vs_floor, 100)), 1), big.mark=',')
+			pct <- sum(data$price) / sum(data$mn_20)
+            pct <- format(round(pct, 1), big.mark=',')
 			chain <- getChain()
 			currency <- ifelse( chain == 'Solana', 'SOL', ifelse(chain == 'Ethereum', 'ETH', 'LUNA') )
             t <- paste0(p, ' $',currency,' (+',f,' / ',pct,'x vs the floor)')
@@ -823,6 +848,18 @@ server <- function(input, output, session) {
             r <- as.numeric(input$maxrarityrank2)
             data <- data[ nft_rank <= eval(r) ]
         }
+        if(input$minfloorinput != '') {
+            r <- as.numeric(input$minfloorinput)
+            data <- data[ minfloorinput >= eval(r) ]
+        }
+        if(input$maxfloorinput != '') {
+            r <- as.numeric(input$maxfloorinput)
+            data <- data[ maxfloorinput <= eval(r) ]
+        }
+        if(input$maxrarityrank2 != '') {
+            r <- as.numeric(input$maxrarityrank2)
+            data <- data[ nft_rank <= eval(r) ]
+        }
         if(input$minrarityrank2 != '') {
             data <- data[ nft_rank >= eval(as.numeric(input$minrarityrank2)) ]
         }
diff --git a/viz/ui.R b/viz/ui.R
index a1d553e1..f01cbc02 100644
--- a/viz/ui.R
+++ b/viz/ui.R
@@ -146,34 +146,48 @@ fluidPage(
 		, bsTooltip(id = "historical-sales-tooltip", title = "This app is still in beta - sales data may be incomplete or delayed", placement = "bottom", trigger = "hover")
 		, fluidRow(
             class = 'filters'
-			, column(3
+			, column(2
 				, div(
 					class = "inputtitle"
 					, "Min Deal Score Rank"
 				)
 				, fluidRow(uiOutput("minnftrankinput2"))
 			)
-			, column(3
+			, column(2
 				, div(
 					class = "inputtitle"
 					, "Max Deal Score Rank"
 				)
 				, fluidRow(uiOutput("maxnftrankinput2"))
 			)
-			, column(3
+			, column(2
 				, div(
 					class = "inputtitle"
 					, "Min Rarity Rank"
 				)
 				, fluidRow(uiOutput("minrarityrankinput2"))
 			)
-			, column(3
+			, column(2
 				, div(
 					class = "inputtitle"
 					, "Max Rarity Rank"
 				)
 				, fluidRow(uiOutput("maxrarityrankinput2"))
 			)
+			, column(2
+				, div(
+					class = "inputtitle"
+					, "Min Floor"
+				)
+				, fluidRow(uiOutput("minfloorinput"))
+			)
+			, column(2
+				, div(
+					class = "inputtitle"
+					, "Max Floor"
+				)
+				, fluidRow(uiOutput("maxfloorinput"))
+			)
 			, column(3
 				, div(
 					class = "inputtitle"
diff --git a/viz/update_data.R b/viz/update_data.R
new file mode 100644
index 00000000..e72b7acd
--- /dev/null
+++ b/viz/update_data.R
@@ -0,0 +1,8 @@
+
+isRstudio <- Sys.info()[["user"]] == 'rstudio-connect'
+if(isRstudio) {
+	source("/home/data-science/data_science/util/util_functions.R")
+} else {
+	source('~/git/nft-deal-score/scrape_listings.R')
+}
+source("/home/data-science/data_science/util/util_functions.R")
\ No newline at end of file