similar to: reading json tables

Hello, Everyone. Does anyone know how to create a Nightingale’s Rose chart by using R? Hopefully, the graph could be displayed like this: http://mbostock.github.com/protovis/ex/crimea-rose.html Thanks a lot. Kind regards, Henry [[alternative HTML version deleted]]

Hi, Got some issues regarding Kerberos and Directory Server and hope someone can help me out. Used these for the configiruation : http://www.centos.org/docs/5/html/Deployment_Guide-en-US/ch-kerberos.html http://www.redhat.com/docs/manuals/dir-server/8.1/install/index.html Server : CentOS 5.4 with Kerberos and Directory Server installed Client : CentOS 5.4 I use putty to connect to the client,

Hi all, I am trying to use nonlinear regression (nls) to analyze some seed germination data, but am having problems with error codes. The data that I have closely matches the germination dataset included in the drc package. Here is the head of the data temp species start end germinated TotSeeds TotGerminated Prop 1 10 wheat 0 1 0 20 0 0.0 2 10 wheat

Hi Keep your messages in the list, you increase your chance to get some answer. I changed your data to groupedData object (see below), but I did not find any problem in it. plot(wlg) gives reasonable picture and I am not such expert to see any problem with data. Seems to me, that something has to be wrong with nlsList function. > wheat.list <- nlsList(Prop ~ SSlogis(end,Asym, xmid,

Dear group, I know this issue has been already covered, and before you reply I must say I have read the R-FAQ and search the mailing list archive. I still can't manage to change my factor to numeric as I couldn't find any clear answer. Here is my df : Pose1 <- structure(list(DESCRIPTION = structure(c(1L, 2L, 3L, 4L, 5L, 8L), .Label = c(" SUGAR NO.11 May/10 ", "COTTON

I have a data frame called "pose": DESCRIPTION QUANITY CLOSING.PRICE 1 WHEAT May/10 1 467.75 2 WHEAT May/10 2 467.75 3 WHEAT May/10 1 467.75 4 WHEAT May/10 1 467.75 5 COTTON NO.2 May/10 1 78.13 6 COTTON NO.2 May/10 3 78.13 7 COTTON NO.2 May/10 1 78.13

Since good server designs have come up in the past, I wanted to point out a "low-cost" server option that has good I/O, and the vendor offers _your_choice_ of not only Fedora Core or Red Hat Enterprise Linux, but _also_ CentOS _shipped_ with it! IN-A-NUTSHELL ... Starting at just over $750, you can get a single Socket-939 Opteron 1xx (dual-core is an option) system with up to 4GiB of

Dear group, I have these 2 following data frame: allcon <- structure(list(DESCRIPTION = structure(1:17, .Label = c("COFFEE C Jul/10", "COPPER May/10", "CORN Jul/10", "CORN May/10", "COTTON NO.2 Jul/10", "CRUDE OIL miNY May/10", "GOLD Jun/10", "HENRY HUB NATURAL GAS May/10", "ROBUSTA COFFEE (10)

Dear group, I have 3 data frames I would like to merge. Here they are: pose16 <- structure(list(DESCRIPTION = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 12L), .Label = c("COPPER May/10", "COTTON NO.2 Jul/10", "CRUDE OIL miNY May/10", "GOLD Jun/10", "ROBUSTA COFFEE (10) Jul/10", "SOYBEANS Jul/10", "SUGAR NO.11

Dear R-users, I have a dataset as like below, and I want to subtotal the values of rice,wheat and maize by year for each fid. fid      year     rice     wheat      maize ------------------------------------------------ 1        1995      5        NA           NA 1        1995      NA        3           NA 1        1995      NA       NA           2 1        1996      4        NA           NA 1  

Hi, I am new to R. My problem is with the ordered logistic model. Here is my question: Generate an order discrete variable using the variable wrwage1 = wages in first full calendar quarter after benefit application in the following way: * wage*1*Ordered *= 1 *if*0 *· wrwage*1 *< *1000 2 *if*1000 *· wrwage*1 *< *2000 3 *if*2000 *· wrwage*1 *< *3000 4 *if*3000 *· wrwage*1 *<

Every hour I get a mail from logcheck with a line like Nov 6 12:08:34 wheat fetchnews[13617]: clamping maxage for comp.os.linux.admin to global expire 50 The strange thing is that syslog is filled with similar lines, but this is the only one I get in the report. It is the last such line in each group: # many similar lines deleted Nov 6 12:08:32 wheat fetchnews[13617]: comp.std.c++: considering

Am using Fedora Core RPM Samba 3.0.7 and am trying to get VFS recycle to work. Here is the relevant smb.conf: [global] workgroup = SSVMTN netbios name = MONARCH security = DOMAIN password server = GOATSEYE encrypt passwords = yes server string = Monarch Server wins server = 172.16.1.100 dns proxy = No name

Dear R-List, My questions concerns missing values. Specifically, is is possible to use different "types" of missingness in a dataset and not a one-size-fits-all NA? For example, data may be missing because of an outright refusal by a respondent to answer a question, or because she didn't know an answer, or because the item simply did not apply. In later analysis it is sometimes

Dear group, Here is my df : df3 <- structure(list(DESCRIPTION = c("COPPER May/10", "COTTON NO.2 Jul/10", "CRUDE OIL miNY May/10", "GOLD Jun/10", "ROBUSTA COFFEE (10) Jul/10", "SOYBEANS Jul/10", "SUGAR NO.11 Jul/10", "SUGAR NO.11 May/10", "WHEAT Jul/10", "SPCL HIGH GRADE ZINC USD",

Dear group, Here is my data frame: position100415 <- structure(list(DESCRIPTION = structure(1:9, .Label = c(" SUGAR NO.11 Jul/10 ", " SUGAR NO.11 May/10 ", "CORN May/10 ", "COTTON NO.2 Jul/10 ", "CRUDE OIL miNY May/10 ", "ROBUSTA COFFEE (10) Jul/10 ", "SILVER May/10 ", "SOYBEANS Jul/10 ", "WHEAT May/10

Dear group, Here is my data frame: > dput(u) structure(list(DESCRIPTION = structure(c(2L, 5L, 6L, 7L, 9L, 11L, 12L, 15L, 14L, 16L, 1L, 10L, 3L, 4L, 13L, 8L, 17L), .Label = c("COFFEE C Jul/10", "COPPER May/10", "CORN Jul/10", "CORN May/10", "COTTON NO.2 Jul/10", "CRUDE OIL miNY May/10", "GOLD Jun/10", "HENRY HUB

Dear list, here are my two data frames: av <- structure(list(DESCRIPTION = c("COFFEE C Sep/10", "COPPER Sep/10", "CORN Dec/10", "CRUDE OIL miNY Sep/10", "GOLD Aug/10", "HENRY HUB NATURAL GAS Sep/10", "PALLADIUM Sep/10", "SILVER Sep/10", "SOYBEANS Nov/10", "SPCL HIGH GRADE ZINC USD", "SUGAR

Dear all R2.10 WinXP I have a dataset dealing with the way different wheat cultivars build their yield. Wheat ears are organised in spikelets where the spikelets can be numbered from the bottom, with even numbers on one side and odd on the other. I know how many kernels there were in each spikelet after some months spent counting them... Now I want to illustrate the differences between the

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