README.md

In ivanhanigan/exploratoryanalysistemplate: eda

EDA template

This is designed to create code snippets. These can be used as standalone R scripts or incorporated into complicated workflows such as ProjectTemplate http://projecttemplate.net/ or http://cran.r-project.org/web/packages/makeProject/index.html

To install

library(devtools)
install_github(repo = "exploratoryanalysistemplate", username = "ivanhanigan")

To use

textdata <- exploratory_analysis_template(
  projdir = "~/path/to/project",
  packagedir =  "a_package_is_a_discrete_chunk_of_work",
  outfile = "this_is_the_result.csv",
  indir = "~/path/to/input/data",
  infile = "this_is_the_input_data.csv",
  titl = "Title of the code snippet",
  show_header = TRUE)
cat(textdata)
# check the codes, if ok sink to a r markdown script
sink("tests/test_taxo_review.Rmd")
cat(textdata)
sink()

Results

Title of the code snippet
---

```{r echo = T, results = "asis", eval = T}
projdir <- "~/path/to/project"
outdir <- file.path(projdir, "a_package_is_a_discrete_chunk_of_work")
# if(!file.exists(outdir)) dir.create(outdir)
outfile <- "this_is_the_result.csv"
file.path(outdir, outfile) 
setwd(outdir)
```
```{r, echo = TRUE, eval = FALSE}
library(gdata)
library(disentangle)
library(EML)
library(sqldf)
library(taxize)
indir <- "~/path/to/input/data"

dir(indir)
infile <- "this_is_the_input_data.csv"

#### load ####
print(file.path(indir,infile))
dat <- read.csv(file.path(indir,infile), stringsAsFactors = F)

#### check ####
str(dat)

head(dat) 
tail(dat)
```

```{r echo = T, results = "asis", eval = F}
#### Taxonomic review ####
tx <- as.data.frame(table(dat$species))
names(tx) <- c("species", "Frequency")
write.csv(tx, file.path(outdir, gsub(".csv","_taxonomic_coverage.csv", outfile)), row.names = F)  
# Test new version?
tx <- as.data.frame(table(dat$species))
names(tx) <- c("species", "Frequency")
splist <- tx$species
sources <- gnr_datasources()
sources

eol <- sources$id[sources$title == "EOL"]
gbif_backbone <- sources$id[sources$title == "GBIF Backbone Taxonomy"]
ipni <- sources$id[sources$title == "The International Plant Names Index"]
zk <- sources$id[sources$title == "ZooKeys"]
zb <- sources$id[sources$title == "ZooBank"]
c(eol, gbif_backbone, ipni, zk, zb)
out <- gnr_resolve(splist, data_source_ids=c(eol, gbif_backbone, ipni, zk, zb), stripauthority=TRUE)

out2 <- unique(out$results)
out3 <- sqldf('select submitted_name, matched_name2 as match_via_database, max(score) as max_database_score, "" as change_note, "" as update_to
  from out2
  group by submitted_name, matched_name2')
out3[which(out3$submitted_name == out3$match_via_database),"max_database_score"] <- ""
out3[which(out3$submitted_name == out3$match_via_database),"match_via_database"] <- ""
out3
write.csv(out3, file.path(outdir, gsub(".csv","_taxonomic_coverage.csv", outfile)), row.names = F)  
#### TODO: 
# you should go to this CSV file and edit the final columns, 
# take notes on decisions and create the updates list.  Save as new file with 2.csv at end.
####

# Post review merge fixed names and remove old names
dir(outdir)
tx_file <- "xxx_taxonomic_coverage2.csv"
tx <- read.csv(file.path(outdir, tx_file), stringsAsFactor = F)
nrow(tx)
head(tx)
tx[tx[,grep("change_note", names(tx))]!="",]                                          
str(dat)

# check that linking variable is identical
idx <- names(table(dat$species))
head(idx)
idy <- tx$submitted_name
head(idy)
idx[-which(idx in idy)]
idy[-which(idy in idx)]

# if all good then merge
dat <- merge(dat, tx, by.x = "species", by.y = "submitted_name", all.x = T)
str(dat)

# reorder cols
paste(names(dat), collapse = "','", sep = "")
namelist <- c("visitcode","surveyyear", "species")

dat <- dat[,namelist]
names(dat) <- gsub("update_to" , "species", names(dat))
str(dat)  
```

ivanhanigan/exploratoryanalysistemplate documentation built on May 18, 2019, 7:13 a.m.