Hi, I worked through this excellent tutorial: #Elegant regression results tables and plots in R: the finalfit package https://www.r-bloggers.com/elegant-regression-results-tables-and-plots-in-r-the-finalfit-package/ Now I am applying it to my own data. In the tutorial there is mention of: # Tables can be knitted to PDF, Word or html documents. We do this in # RStudio from a .Rmd document. Example chunk: # ```{r, echo = FALSE, results='asis'} # knitr::kable(example_table, row.names=FALSE, # align=c("l", "l", "r", "r", "r", "r")) # ``` I am having a difficult time understanding how this works? I have read through the help: ?knitr #"This function takes an input file, extracts the R code in it according to a list of patterns, evaluates the code and writes the output in another file. #It can also tangle R source code from the input document (purl() is a wrapper to knit(..., tangle = TRUE)). #The knitr.purl.inline option can be used to also tangle the code of inline expressions (disabled by default)." install.packages("knitr") library(knitr) ?knit ?stitch install.packages("stitch")#package 'stitch' is not available (for R version 3.5.1) ?spin install.packages("spin") #package 'spin' is not available (for R version 3.5.1)Warning in install.packages : Perhaps you meant 'SPIn' ? I have also looked at the github and knitr author's links https://github.com/yihui/knitr https://yihui.name/knitr/demo/stitch/ https://github.com/yihui/knitr/blob/master/inst/examples/knitr-spin.Rmd If I understand this correctly I have to have a template already in place as the input object, is that correct? How would I construct this it that is so? I also tried writing out directly to pdf and png with no success. #pdf("c:/WHP/Appeals/OutputPDFs/EX&DE V1.pdf") #png("c:/WHP/Appeals/OutputPDFs/EX&DE V1.png") #opts_chunk$set(fig.path = "c:/WHP/Appeals/OutputPDFs/EX&DE V1.pdf") <--I don't even understand what this does, poached it from one of the google sites I have been reviewing and tried to make it work? #This is the script I would like the output placed in PDF explanatory = c("claimStatusId", "AgeCat", "PatientGender", "PayorID") dependent = "AppealOverturned" # Appeals Status appdf1DT2 %>% summary_factorlist(dependent, explanatory, p=TRUE, add_dependent_label=TRUE) #dev.off() str(appdf1DT2) # Classes 'data.table' and 'data.frame': 3983 obs. of 21 variables: # $ ClaimServiceID : Factor w/ 3983 levels "51318639","51318640",..: 1 2 4 3 5 12 6 8 7 9 ... # $ LineNumber : Factor w/ 140 levels "1","2","3","4",..: 1 2 4 3 5 7 1 3 2 4 ... # $ claimStatusId : Factor w/ 2 levels "2","3": 2 2 2 2 2 1 1 1 1 1 ... # $ PatientGender : Factor w/ 3 levels "F","M","UNK": 2 2 2 2 2 1 1 1 1 1 ... # $ PayorID : Factor w/ 19 levels "000","234","239",..: 1 1 1 1 1 1 1 1 1 1 ... # $ AppealID : Factor w/ 512 levels "79765","116998",..: 1 1 1 1 1 2 2 2 2 2 ... # $ ZipCode : Factor w/ 223 levels "2155","3037",..: 72 72 72 72 72 102 102 102 102 102 ... # $ EditID : Factor w/ 21 levels "","0","001X",..: 2 12 8 12 8 8 2 8 12 8 ... # $ CurrentBilled : num 14394 14394 14394 14394 14394 ... # $ ClaimLineSavings : num 0 0 0 0 0 ... # $ StatusChangeMo : Factor w/ 7 levels "2018-01","2018-02",..: 4 4 4 4 4 4 4 4 4 4 ... # $ Grouping : Factor w/ 9 levels "","Agencies",..: 4 4 4 4 4 4 4 4 4 4 ... # $ AppealOverturned : Factor w/ 2 levels "1","2": 2 2 2 2 2 1 1 1 1 1 ... # $ PrimaryDX : Factor w/ 360 levels "","8442","912",..: 2 2 2 2 2 171 171 171 171 171 ... # $ RevCodeCats : Factor w/ 41 levels "AdminStorProcBlProd",..: 2 2 18 2 18 18 2 2 2 18 ... # $ AgeCat : Factor w/ 9 levels "[0-5]","[11-20]",..: 4 4 4 4 4 8 8 8 8 8 ... # $ ClaimLevelSavings: num 0 0 0 0 0 ... # - attr(*, ".internal.selfref")=<externalptr> head(appdf1DT2) ClaimServiceID LineNumber claimStatusId PatientGender PayorID ProviderID AppealID ZipCode TIN EditID 1: 51318639 1 3 M 000 149385 79765 33904 0 2: 51318640 2 3 M 000 149385 79765 33904 022 3: 51318642 4 3 M 000 149385 79765 33904 00504 4: 51318641 3 3 M 000 149385 79765 33904 022 5: 51318643 5 3 M 000 149385 79765 33904 00504 6: 85833537 7 2 F 000 3240182 116998 46635 00504 CurrentBilled ClaimLineSavings StatusChangeMo Grouping AppealOverturned PrimaryDX RevCodeCats 1: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 AmbSurgCare 2: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 AmbSurgCare 3: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 MedSurgSuppandDevs 4: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 AmbSurgCare 5: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 MedSurgSuppandDevs 6: 23472.92 0 2018-04 Ambulatory Health Care Facilities 1 M1712 MedSurgSuppandDevs AgeCat ClaimLevelSavings 1: [31-40] 0.00 2: [31-40] 0.00 3: [31-40] 0.00 4: [31-40] 0.00 5: [31-40] 0.00 6: [61-70] 296.25 Maybe I am in over my head in this pursuit given my novice status with R, however, any direction would be appreciated. Thank you. WHP Confidentiality Notice This message is sent from Zelis. ...{{dropped:15}}
Hi Bill, Am 18.07.18 um 18:33 schrieb Bill Poling:> Hi, > I worked through this excellent tutorial: > #Elegant regression results tables and plots in R: the finalfit package > https://www.r-bloggers.com/elegant-regression-results-tables-and-plots-in-r-the-finalfit-package/ > > > > Now I am applying it to my own data. > > In the tutorial there is mention of: > > # Tables can be knitted to PDF, Word or html documents. We do this in > # RStudio from a .Rmd document. Example chunk: > # ```{r, echo = FALSE, results='asis'} > # knitr::kable(example_table, row.names=FALSE, > # align=c("l", "l", "r", "r", "r", "r")) > # ``` > > I am having a difficult time understanding how this works? > > I have read through the help: > > ?knitr > #"This function takes an input file, extracts the R code in it according to a list of patterns, evaluates the code and writes the output in another file. > #It can also tangle R source code from the input document (purl() is a wrapper to knit(..., tangle = TRUE)). > #The knitr.purl.inline option can be used to also tangle the code of inline expressions (disabled by default)." > > install.packages("knitr") > library(knitr) > ?knit > ?stitch > install.packages("stitch")#package 'stitch' is not available (for R version 3.5.1) > ?spin > install.packages("spin") #package 'spin' is not available (for R version 3.5.1)Warning in install.packages : Perhaps you meant 'SPIn' ? > > I have also looked at the github and knitr author's links > > https://github.com/yihui/knitr > > https://yihui.name/knitr/demo/stitch/ > > https://github.com/yihui/knitr/blob/master/inst/examples/knitr-spin.Rmd > > > If I understand this correctly I have to have a template already in place as the input object, is that correct? How would I construct this it that is so? > > I also tried writing out directly to pdf and png with no success. > > #pdf("c:/WHP/Appeals/OutputPDFs/EX&DE V1.pdf") > #png("c:/WHP/Appeals/OutputPDFs/EX&DE V1.png") > #opts_chunk$set(fig.path = "c:/WHP/Appeals/OutputPDFs/EX&DE V1.pdf") <--I don't even understand what this does, poached it from one of the google sites I have been reviewing and tried to make it work? > > #This is the script I would like the output placed in PDF > explanatory = c("claimStatusId", "AgeCat", "PatientGender", "PayorID") > dependent = "AppealOverturned" # Appeals Status > appdf1DT2 %>% > summary_factorlist(dependent, explanatory, p=TRUE, add_dependent_label=TRUE) > > #dev.off() > > > str(appdf1DT2) > # Classes 'data.table' and 'data.frame': 3983 obs. of 21 variables: > # $ ClaimServiceID : Factor w/ 3983 levels "51318639","51318640",..: 1 2 4 3 5 12 6 8 7 9 ... > # $ LineNumber : Factor w/ 140 levels "1","2","3","4",..: 1 2 4 3 5 7 1 3 2 4 ... > # $ claimStatusId : Factor w/ 2 levels "2","3": 2 2 2 2 2 1 1 1 1 1 ... > # $ PatientGender : Factor w/ 3 levels "F","M","UNK": 2 2 2 2 2 1 1 1 1 1 ... > # $ PayorID : Factor w/ 19 levels "000","234","239",..: 1 1 1 1 1 1 1 1 1 1 ... > # $ AppealID : Factor w/ 512 levels "79765","116998",..: 1 1 1 1 1 2 2 2 2 2 ... > # $ ZipCode : Factor w/ 223 levels "2155","3037",..: 72 72 72 72 72 102 102 102 102 102 ... > # $ EditID : Factor w/ 21 levels "","0","001X",..: 2 12 8 12 8 8 2 8 12 8 ... > # $ CurrentBilled : num 14394 14394 14394 14394 14394 ... > # $ ClaimLineSavings : num 0 0 0 0 0 ... > # $ StatusChangeMo : Factor w/ 7 levels "2018-01","2018-02",..: 4 4 4 4 4 4 4 4 4 4 ... > # $ Grouping : Factor w/ 9 levels "","Agencies",..: 4 4 4 4 4 4 4 4 4 4 ... > # $ AppealOverturned : Factor w/ 2 levels "1","2": 2 2 2 2 2 1 1 1 1 1 ... > # $ PrimaryDX : Factor w/ 360 levels "","8442","912",..: 2 2 2 2 2 171 171 171 171 171 ... > # $ RevCodeCats : Factor w/ 41 levels "AdminStorProcBlProd",..: 2 2 18 2 18 18 2 2 2 18 ... > # $ AgeCat : Factor w/ 9 levels "[0-5]","[11-20]",..: 4 4 4 4 4 8 8 8 8 8 ... > # $ ClaimLevelSavings: num 0 0 0 0 0 ... > # - attr(*, ".internal.selfref")=<externalptr> > > head(appdf1DT2) > ClaimServiceID LineNumber claimStatusId PatientGender PayorID ProviderID AppealID ZipCode TIN EditID > 1: 51318639 1 3 M 000 149385 79765 33904 0 > 2: 51318640 2 3 M 000 149385 79765 33904 022 > 3: 51318642 4 3 M 000 149385 79765 33904 00504 > 4: 51318641 3 3 M 000 149385 79765 33904 022 > 5: 51318643 5 3 M 000 149385 79765 33904 00504 > 6: 85833537 7 2 F 000 3240182 116998 46635 00504 > CurrentBilled ClaimLineSavings StatusChangeMo Grouping AppealOverturned PrimaryDX RevCodeCats > 1: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 AmbSurgCare > 2: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 AmbSurgCare > 3: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 MedSurgSuppandDevs > 4: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 AmbSurgCare > 5: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 MedSurgSuppandDevs > 6: 23472.92 0 2018-04 Ambulatory Health Care Facilities 1 M1712 MedSurgSuppandDevs > AgeCat ClaimLevelSavings > 1: [31-40] 0.00 > 2: [31-40] 0.00 > 3: [31-40] 0.00 > 4: [31-40] 0.00 > 5: [31-40] 0.00 > 6: [61-70] 296.25 > > > Maybe I am in over my head in this pursuit given my novice status with R, however, any direction would be appreciated. > > Thank you. > > WHP > > Confidentiality Notice This message is sent from Zelis. ...{{dropped:15}} >Not sure, if I get you right. Seems, that you use knitr:: and code chunks without the necessary context? Please have a look at https://rmarkdown.rstudio.com/ to get a more general understanding about using knitr within RMarkdown context. HTH, Rainer Hurling
Dear Bill, It seems like you are looking at the wrong help files. The code in the tutorial uses the package::function() syntax. So knitr::kable() translates into use the function kable() from the knitr package. The help file you are looking for is ?kable (when knitr is loaded) or ?knitr::kable (when knitr is not loaded). Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance thierry.onkelinx at inbo.be Havenlaan 88 bus 73, 1000 Brussel www.inbo.be /////////////////////////////////////////////////////////////////////////////////////////// To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey /////////////////////////////////////////////////////////////////////////////////////////// 2018-07-18 18:33 GMT+02:00 Bill Poling <Bill.Poling at zelis.com>:> Hi, > I worked through this excellent tutorial: > #Elegant regression results tables and plots in R: the finalfit package > https://www.r-bloggers.com/elegant-regression-results-tables-and-plots-in-r-the-finalfit-package/ > > > > Now I am applying it to my own data. > > In the tutorial there is mention of: > > # Tables can be knitted to PDF, Word or html documents. We do this in > # RStudio from a .Rmd document. Example chunk: > # ```{r, echo = FALSE, results='asis'} > # knitr::kable(example_table, row.names=FALSE, > # align=c("l", "l", "r", "r", "r", "r")) > # ``` > > I am having a difficult time understanding how this works? > > I have read through the help: > > ?knitr > #"This function takes an input file, extracts the R code in it according to a list of patterns, evaluates the code and writes the output in another file. > #It can also tangle R source code from the input document (purl() is a wrapper to knit(..., tangle = TRUE)). > #The knitr.purl.inline option can be used to also tangle the code of inline expressions (disabled by default)." > > install.packages("knitr") > library(knitr) > ?knit > ?stitch > install.packages("stitch")#package 'stitch' is not available (for R version 3.5.1) > ?spin > install.packages("spin") #package 'spin' is not available (for R version 3.5.1)Warning in install.packages : Perhaps you meant 'SPIn' ? > > I have also looked at the github and knitr author's links > > https://github.com/yihui/knitr > > https://yihui.name/knitr/demo/stitch/ > > https://github.com/yihui/knitr/blob/master/inst/examples/knitr-spin.Rmd > > > If I understand this correctly I have to have a template already in place as the input object, is that correct? How would I construct this it that is so? > > I also tried writing out directly to pdf and png with no success. > > #pdf("c:/WHP/Appeals/OutputPDFs/EX&DE V1.pdf") > #png("c:/WHP/Appeals/OutputPDFs/EX&DE V1.png") > #opts_chunk$set(fig.path = "c:/WHP/Appeals/OutputPDFs/EX&DE V1.pdf") <--I don't even understand what this does, poached it from one of the google sites I have been reviewing and tried to make it work? > > #This is the script I would like the output placed in PDF > explanatory = c("claimStatusId", "AgeCat", "PatientGender", "PayorID") > dependent = "AppealOverturned" # Appeals Status > appdf1DT2 %>% > summary_factorlist(dependent, explanatory, p=TRUE, add_dependent_label=TRUE) > > #dev.off() > > > str(appdf1DT2) > # Classes 'data.table' and 'data.frame': 3983 obs. of 21 variables: > # $ ClaimServiceID : Factor w/ 3983 levels "51318639","51318640",..: 1 2 4 3 5 12 6 8 7 9 ... > # $ LineNumber : Factor w/ 140 levels "1","2","3","4",..: 1 2 4 3 5 7 1 3 2 4 ... > # $ claimStatusId : Factor w/ 2 levels "2","3": 2 2 2 2 2 1 1 1 1 1 ... > # $ PatientGender : Factor w/ 3 levels "F","M","UNK": 2 2 2 2 2 1 1 1 1 1 ... > # $ PayorID : Factor w/ 19 levels "000","234","239",..: 1 1 1 1 1 1 1 1 1 1 ... > # $ AppealID : Factor w/ 512 levels "79765","116998",..: 1 1 1 1 1 2 2 2 2 2 ... > # $ ZipCode : Factor w/ 223 levels "2155","3037",..: 72 72 72 72 72 102 102 102 102 102 ... > # $ EditID : Factor w/ 21 levels "","0","001X",..: 2 12 8 12 8 8 2 8 12 8 ... > # $ CurrentBilled : num 14394 14394 14394 14394 14394 ... > # $ ClaimLineSavings : num 0 0 0 0 0 ... > # $ StatusChangeMo : Factor w/ 7 levels "2018-01","2018-02",..: 4 4 4 4 4 4 4 4 4 4 ... > # $ Grouping : Factor w/ 9 levels "","Agencies",..: 4 4 4 4 4 4 4 4 4 4 ... > # $ AppealOverturned : Factor w/ 2 levels "1","2": 2 2 2 2 2 1 1 1 1 1 ... > # $ PrimaryDX : Factor w/ 360 levels "","8442","912",..: 2 2 2 2 2 171 171 171 171 171 ... > # $ RevCodeCats : Factor w/ 41 levels "AdminStorProcBlProd",..: 2 2 18 2 18 18 2 2 2 18 ... > # $ AgeCat : Factor w/ 9 levels "[0-5]","[11-20]",..: 4 4 4 4 4 8 8 8 8 8 ... > # $ ClaimLevelSavings: num 0 0 0 0 0 ... > # - attr(*, ".internal.selfref")=<externalptr> > > head(appdf1DT2) > ClaimServiceID LineNumber claimStatusId PatientGender PayorID ProviderID AppealID ZipCode TIN EditID > 1: 51318639 1 3 M 000 149385 79765 33904 0 > 2: 51318640 2 3 M 000 149385 79765 33904 022 > 3: 51318642 4 3 M 000 149385 79765 33904 00504 > 4: 51318641 3 3 M 000 149385 79765 33904 022 > 5: 51318643 5 3 M 000 149385 79765 33904 00504 > 6: 85833537 7 2 F 000 3240182 116998 46635 00504 > CurrentBilled ClaimLineSavings StatusChangeMo Grouping AppealOverturned PrimaryDX RevCodeCats > 1: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 AmbSurgCare > 2: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 AmbSurgCare > 3: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 MedSurgSuppandDevs > 4: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 AmbSurgCare > 5: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 MedSurgSuppandDevs > 6: 23472.92 0 2018-04 Ambulatory Health Care Facilities 1 M1712 MedSurgSuppandDevs > AgeCat ClaimLevelSavings > 1: [31-40] 0.00 > 2: [31-40] 0.00 > 3: [31-40] 0.00 > 4: [31-40] 0.00 > 5: [31-40] 0.00 > 6: [61-70] 296.25 > > > Maybe I am in over my head in this pursuit given my novice status with R, however, any direction would be appreciated. > > Thank you. > > WHP > > Confidentiality Notice This message is sent from Zelis. ...{{dropped:15}} > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.
Hi Rainer: Thank you I will have a look at the link you provide. As I mentioned, ?#opts_chunk$set(fig.path = "c:/WHP/Appeals/OutputPDFs/EX&DE V1.pdf") <--I don't even understand what this does, poached it from one of the google sites I have been reviewing and tried to make it work?? Hopefully your reference has an example I can follow, will let you know, cheers. WHP>>Not sure, if I get you right. Seems, that you use knitr:: and codechunks without the necessary context? Please have a look at https://rmarkdown.rstudio.com/<https://rmarkdown.rstudio.com/> to get a more general understanding about using knitr within RMarkdown context.<<<< From: Rainer Hurling <rhurlin at gwdg.de> Sent: Thursday, July 19, 2018 3:45 AM To: Bill Poling <Bill.Poling at zelis.com> Cc: r-help (r-help at r-project.org) <r-help at r-project.org> Subject: Re: [R] Help with knitr pkg Hi Bill, Am 18.07.18 um 18:33 schrieb Bill Poling:> Hi, > I worked through this excellent tutorial: > #Elegant regression results tables and plots in R: the finalfit package > https://www.r-bloggers.com/elegant-regression-results-tables-and-plots-in-r-the-finalfit-package/<https://www.r-bloggers.com/elegant-regression-results-tables-and-plots-in-r-the-finalfit-package/> > > > > Now I am applying it to my own data. > > In the tutorial there is mention of: > > # Tables can be knitted to PDF, Word or html documents. We do this in > # RStudio from a .Rmd document. Example chunk: > # ```{r, echo = FALSE, results='asis'} > # knitr::kable(example_table, row.names=FALSE, > # align=c("l", "l", "r", "r", "r", "r")) > # ``` > > I am having a difficult time understanding how this works? > > I have read through the help: > > ?knitr > #"This function takes an input file, extracts the R code in it according to a list of patterns, evaluates the code and writes the output in another file. > #It can also tangle R source code from the input document (purl() is a wrapper to knit(..., tangle = TRUE)). > #The knitr.purl.inline option can be used to also tangle the code of inline expressions (disabled by default)." > > install.packages("knitr") > library(knitr) > ?knit > ?stitch > install.packages("stitch")#package 'stitch' is not available (for R version 3.5.1) > ?spin > install.packages("spin") #package 'spin' is not available (for R version 3.5.1)Warning in install.packages : Perhaps you meant 'SPIn' ? > > I have also looked at the github and knitr author's links > > https://github.com/yihui/knitr<https://github.com/yihui/knitr> > > https://yihui.name/knitr/demo/stitch/<https://yihui.name/knitr/demo/stitch/> > > https://github.com/yihui/knitr/blob/master/inst/examples/knitr-spin.Rmd<https://github.com/yihui/knitr/blob/master/inst/examples/knitr-spin.Rmd> > > > If I understand this correctly I have to have a template already in place as the input object, is that correct? How would I construct this it that is so? > > I also tried writing out directly to pdf and png with no success. > > #pdf("c:/WHP/Appeals/OutputPDFs/EX&DE V1.pdf") > #png("c:/WHP/Appeals/OutputPDFs/EX&DE V1.png") > #opts_chunk$set(fig.path = "c:/WHP/Appeals/OutputPDFs/EX&DE V1.pdf") <--I don't even understand what this does, poached it from one of the google sites I have been reviewing and tried to make it work? > > #This is the script I would like the output placed in PDF > explanatory = c("claimStatusId", "AgeCat", "PatientGender", "PayorID") > dependent = "AppealOverturned" # Appeals Status > appdf1DT2 %>% > summary_factorlist(dependent, explanatory, p=TRUE, add_dependent_label=TRUE) > > #dev.off() > > > str(appdf1DT2) > # Classes 'data.table' and 'data.frame': 3983 obs. of 21 variables: > # $ ClaimServiceID : Factor w/ 3983 levels "51318639","51318640",..: 1 2 4 3 5 12 6 8 7 9 ... > # $ LineNumber : Factor w/ 140 levels "1","2","3","4",..: 1 2 4 3 5 7 1 3 2 4 ... > # $ claimStatusId : Factor w/ 2 levels "2","3": 2 2 2 2 2 1 1 1 1 1 ... > # $ PatientGender : Factor w/ 3 levels "F","M","UNK": 2 2 2 2 2 1 1 1 1 1 ... > # $ PayorID : Factor w/ 19 levels "000","234","239",..: 1 1 1 1 1 1 1 1 1 1 ... > # $ AppealID : Factor w/ 512 levels "79765","116998",..: 1 1 1 1 1 2 2 2 2 2 ... > # $ ZipCode : Factor w/ 223 levels "2155","3037",..: 72 72 72 72 72 102 102 102 102 102 ... > # $ EditID : Factor w/ 21 levels "","0","001X",..: 2 12 8 12 8 8 2 8 12 8 ... > # $ CurrentBilled : num 14394 14394 14394 14394 14394 ... > # $ ClaimLineSavings : num 0 0 0 0 0 ... > # $ StatusChangeMo : Factor w/ 7 levels "2018-01","2018-02",..: 4 4 4 4 4 4 4 4 4 4 ... > # $ Grouping : Factor w/ 9 levels "","Agencies",..: 4 4 4 4 4 4 4 4 4 4 ... > # $ AppealOverturned : Factor w/ 2 levels "1","2": 2 2 2 2 2 1 1 1 1 1 ... > # $ PrimaryDX : Factor w/ 360 levels "","8442","912",..: 2 2 2 2 2 171 171 171 171 171 ... > # $ RevCodeCats : Factor w/ 41 levels "AdminStorProcBlProd",..: 2 2 18 2 18 18 2 2 2 18 ... > # $ AgeCat : Factor w/ 9 levels "[0-5]","[11-20]",..: 4 4 4 4 4 8 8 8 8 8 ... > # $ ClaimLevelSavings: num 0 0 0 0 0 ... > # - attr(*, ".internal.selfref")=<externalptr> > > head(appdf1DT2) > ClaimServiceID LineNumber claimStatusId PatientGender PayorID ProviderID AppealID ZipCode TIN EditID > 1: 51318639 1 3 M 000 149385 79765 33904 0 > 2: 51318640 2 3 M 000 149385 79765 33904 022 > 3: 51318642 4 3 M 000 149385 79765 33904 00504 > 4: 51318641 3 3 M 000 149385 79765 33904 022 > 5: 51318643 5 3 M 000 149385 79765 33904 00504 > 6: 85833537 7 2 F 000 3240182 116998 46635 00504 > CurrentBilled ClaimLineSavings StatusChangeMo Grouping AppealOverturned PrimaryDX RevCodeCats > 1: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 AmbSurgCare > 2: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 AmbSurgCare > 3: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 MedSurgSuppandDevs > 4: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 AmbSurgCare > 5: 14394.08 0 2018-04 Ambulatory Health Care Facilities 2 8442 MedSurgSuppandDevs > 6: 23472.92 0 2018-04 Ambulatory Health Care Facilities 1 M1712 MedSurgSuppandDevs > AgeCat ClaimLevelSavings > 1: [31-40] 0.00 > 2: [31-40] 0.00 > 3: [31-40] 0.00 > 4: [31-40] 0.00 > 5: [31-40] 0.00 > 6: [61-70] 296.25 > > > Maybe I am in over my head in this pursuit given my novice status with R, however, any direction would be appreciated. > > Thank you. > > WHP > > Confidentiality Notice This message is sent from Zelis. ...{{dropped:15}} >Not sure, if I get you right. Seems, that you use knitr:: and code chunks without the necessary context? Please have a look at https://rmarkdown.rstudio.com/<https://rmarkdown.rstudio.com/> to get a more general understanding about using knitr within RMarkdown context. HTH, Rainer Hurling Confidentiality Notice This message is sent from Zelis. This transmission may contain information which is privileged and confidential and is intended for the personal and confidential use of the named recipient only. Such information may be protected by applicable State and Federal laws from this disclosure or unauthorized use. If the reader of this message is not the intended recipient, or the employee or agent responsible for delivering the message to the intended recipient, you are hereby notified that any disclosure, review, discussion, copying, or taking any action in reliance on the contents of this transmission is strictly prohibited. If you have received this transmission in error, please contact the sender immediately. Zelis, 2018. [[alternative HTML version deleted]]