%>%
City_MedianValuePerSqft_AllHomes group_by(RegionID, RegionName, State, Metro, CountyName, SizeRank) %>%
summarise(Nobs = n()) %>%
arrange(SizeRank) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
%>%
City_MedianValuePerSqft_AllHomes group_by(date) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
%>%
City_MedianValuePerSqft_AllHomes filter(SizeRank <= 30,
year(date) %in% c(1995, 2000, 2005, 2010, 2015, 2020),
month(date) == 1) %>%
mutate(year = year(date)) %>%
select(SizeRank, year, RegionName, value) %>%
spread(year, value) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
%>%
City_MedianValuePerSqft_AllHomes filter(year(date) %in% c(1995, 2000, 2005, 2010, 2015, 2020),
month(date) == 1,
== "CA") %>%
State mutate(year = year(date)) %>%
select(SizeRank, year, RegionName, value) %>%
spread(year, value) %>%
slice(1:30) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {