search for: counti

hi, i have 2 tables (counties and towns). counties has_many towns and towns belong_to counties. now my question: i thought i would need to do is say @counties = Counties.find(:all). should that not return to me all counties in the counties table WITH all towns associated with each county? in my view i was getting error...

I''m having some really weird problems with an app I''m writing. Everything is working as expected on my development machine (OSX, Rails 0.14.4) but is cacking out with weird errors on the Textdrive demo site (FreeBSD, Rails 1.0.0). It complains about missing variables, with errors like this: undefined local variable or method `rawcode'' for

I am using "maps". I am running the following code to get this list of all the counties: map('county', plot=FALSE)$names In the output, all counties have first the state listed and then, after a comma, the name of the county. However, county # 2395 (State = south dakota) has no county name. Anyone knows what this county is? Thank you! -- Dimitri Liakhovitski marketfusi...

I'm working with the nationwide county maps data, and trying to remove the internal county boundary lines. The only map() function parameter that I've found that gets me anywhere close to my desired result leaves small white segments on parts of the map. I believe this is due to the low resolution, because when I look at individual states, the lty parameter solves the problem. Does

Dear Rers, is there a way to color counties on a full US map based on a criterion one establishes (i.e., all counties I assign the same number should be the same color)? I explored a bit and looks like the package "maps" might be of help. library(maps) One could get a map of the US: map('usa') One could get countries with...

Dear All: I tried to replicate a case study described by Prof. Harrell in Chapter 7 of his Regression Modeling Strategies book, but failed on using anova.Design to reproduce his table 7.1, Following is the code: rm(list=ls()) library(Hmisc) library(Design) getHdata(counties) counties$older <- counties$age6574 + counties$age75 label(counties$older) <- '% age >= 65, 1990' counties$pdensity <- log10(counties$pop.density+1) label(counties$pdensity) <- 'log 10 of 1992 pop per 1990 miles^2' dd <- datadist(counties) options(datadist='...

Hi, I would like to plot a map of US counties using different colors. map() seems to be the function to use, e.g. library(maps); map('usa'); map('county', 'colorado', add=T,fill = T, col=c(1:5)) plots Colorado counties using colours 1 to 5. However, I want each color to represent a certain value - a value to be pi...

I am working with census data. My columns of interest are... PercentOld - the percentage of people in each county that are over 65 County - the county in each state State - the state in the US There are about 3100 rows, with each row corresponding to a county within a state. I want to return the top five "PercentOld" by state. But I want the County and the Value. I tried

...0 and rms 3.3-0 , but can not reproduce figure 7.8 of the handouts *Regression Modeling Strategies* ( http://biostat.mc.vanderbilt.edu/wiki/pub/Main/RmS/course2.pdf) by the following code. Could any one help me figure out how to solve this? setwd('C:/Rharrell') require(rms) load('data/counties.sav') older <- counties$age6574 + counties$age75 label(older) <- '% age >= 65, 1990' pdensity <- logb(counties$pop.density+1, 10) label(pdensity) <- 'log 10 of 1992 pop per 1990 miles^2' counties <- cbind(counties, older, pdensity) # add 2 vars. not in data...

Quick question. Say I have a geographical database with counties and zip codes where counties have and belong to many zip codes. zip_codes (id, zip_code) counties (id, name) When I create the association table, the Rails way says to do the following: counties_zip_codes (county_id, zip_code_id). However, given that zip_codes.zip_code is itself a candidate...

Dear R-users: I am trying to use the following code to reproduce the figures on page 140 of Prof. Frank Harrell's book 'Regression Modeling Strategies': rm(list=ls()) options(width=128) library(Hmisc) library(Design) getHdata(counties) counties$older <- counties$age6574 + counties$age75 label(counties$older) <- '% age >= 65, 1990' counties$pdensity <- log10(counties$pop.density+1) label(counties$pdensity) <- 'log 10 of 1992 pop per 1990 miles^2' dd <- datadist(counties) options(datadist='...

...object: Slot Zt must by dims['q'] by > dims['n']*dims['s'] > > In the above, the response is person-level diabetes status as a function of AGE=age, SEX=sex, poolt=average county diabetes prevalence for previous years, poolx=pooled county diabetes prevalence for counties with similar age, sex, race, and income structure, poverty=county poverty rate, fastfood=number of fastfood places per 100,000 people in the county, and a county random effect. > > If I leave out fastfood, the model gets at least fitted - although it doesn't converge (yet): > &gt...

...ivan Poor mental health days 3.9 2.6 5.2 2.6 3.3 5 Sullivan Low birthweight 7.7 7.0 8.4 6.1 8.0 6 Sullivan Adult smoking 29.0 22.0 37.0 15.0 20.0 I'd like to graph high and low for "Premature death" for each of the three counties, with 3 vertical line segments, one connecting those two points for each county. I can get the two points for each county: >xyplot(low+high ~ county, data=subset(chr, item=="Premature death")) but I have not yet been able to figure out how to draw the 3 vertical line segments. Bee...

...ic variables for each county of California over 37 years. My dependent variable is square feet of office floor space permitted to be added in a county. Independent variables include for example change in number of office jobs in same county same year (and lagged years). Smaller (less populous) counties have many years in which there were no permits taken out; the largest counties had at least some permitted square footage each year. Among the set of years and places where permits were taken out, smaller counties tend to more permitted square footage per capita. I imagine the relationships ar...

...ow(70)))) # preferable? I think it's more intuitive. boxplot(x1~county, data=sortdata, col=rainbow(70)) Hope this helps, Rui Barradas Em 22-05-2012; 23:17, "Peterso" escreveu: > The "county" is a factor and I want to plot county vs variable x1 in the order that the counties are listed now, > which is in the order of the rank variable. But when plotting, county is sorted in alphabetical order again. How can > I plot the graph with the county in the rank order? > > the following command plots county in alphabetical order even though the data frame s...

R-listers, I'm working on a project where I need to get the lowercase of the county variable in a dataset alike to the example below (only difference is that the full dataset has all the states and counties in the southeast United States). I keep getting this strange error with the lowerize function (which didn't occur the first few times I use the code below), and oddly enough the error doesn't happen with the function CapLeading (which is in the same package). > correlfile[1:3,] s...

Dear R-users, I have an outcome variable and I'm unsure about how to treat it. Any advice? I have spending data for each county in the state of California (N=58). Each county has been allocated money to spend on any one of the following four categories: A, B, C, and D. Each county may spend the money in any way they see fit. This also means that the county need not spend all the money that

Hi, I have the following dataframe. The County Column has many empty spaces at the end. I want to cut out the empty space and put them back into the dataframe. How can this be done? > head(DailyCounty) Date County GFCPer GFCEquip Acre nFires Date2 1 2001-01-04 00:00:00 Appling 1 1 0.20 1 2001-01-04 2 2001-01-05 00:00:00 Appling

...to analyze with a large data on building permits is to find time series effect of urban policy on buildings as well as cross-sectional effects in any. In 1990 the specialZone urban policy was introduced. I guess that the effects of this specialZone policy would be different from countys. There are counties that do not welcome this specialZone forced to design it. One of the important aims is to find 1) time series effect using Dummy variable, 2) cross-sectional effects using specialZones variable below. The data has items like year(1970-2000), floorSpace, county, specialZones agianst permitting...

Hi, I'm having a bit of trouble with 'scales="free"' in the segplot() function of latticeExtra. Say we need panels for each year, showing only those counties that are represented in each one: ---<--------------------cut here---------------start------------------->--- library(latticeExtra) data(USCancerRates) uscr.w <- subset(USCancerRates, state == "Washington") uscr.w$year <- gl(4, 10, length=nrow(uscr.w), labels=format(seq(200...