https://github.com/nationalparkservice/imd-ccal

The goal of imdccal is to extract data from water chemistry lab deliverables and convert it to a machine readable format.
https://github.com/nationalparkservice/imd-ccal

Last synced: 1 day ago
JSON representation

The goal of imdccal is to extract data from water chemistry lab deliverables and convert it to a machine readable format.

• Host: GitHub
• URL: https://github.com/nationalparkservice/imd-ccal
• Owner: nationalparkservice
• Created: 2023-07-13T02:01:24.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-06-14T21:46:37.000Z (7 months ago)
• Last Synced: 2024-11-08T02:15:26.280Z (about 2 months ago)
• Language: R
• Homepage: https://nationalparkservice.github.io/imd-ccal/
• Size: 510 KB
• Stars: 0
• Watchers: 7
• Forks: 2
• Open Issues: 2
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        

# imdccal

The goal of imdccal is to extract data from water chemistry lab deliverables and convert it to a machine readable format.

## Installation

You can install the development version of imdccal from [its GitHub repository](https://github.com/nationalparkservice/nccn-climate) with:

``` r

# install.packages("remotes")

remotes::install_github("nationalparkservice/imd-ccal")

```

## Example

Read data from a single file of CCAL lab data and write a machine-readable version to an Excel file or set of CSV files:

``` r

library(imdccal)

# We'll assume that you have the CCAL file and a folder called "ccal_tidy" in your working directory

machineReadableCCAL("LVLD_101118.xlsx", destination_folder = "ccal_tidy")  # Write tidied data to a new .xlsx

machineReadableCCAL("LVLD_101118.xlsx", format = "csv", destination_folder = "ccal_tidy")  # Write tidied data to a folder of CSV files

```

Read data from *multiple* files of CCAL lab data and write a machine-readable version to an Excel files or sets of CSV files:

``` r

library(imdccal)

# We'll assume that you have a folder full of CCAL files in a folder called "ccal", and a folder called "ccal_tidy" in your working directory

all_files <- list.files("ccal", pattern = "*.xlsx$", full.names = TRUE)

machineReadableCCAL(all_files, destination_folder = "ccal_tidy")  # Write one file of tidied data per input file

machineReadableCCAL(all_files, format = "csv", destination_folder = "ccal_tidy")  # Write one folder of tidied CSV data per input file

```

Read and tidy the data and work with it in R, without writing the data to any files:

``` r

library(imdccal)

all_files <- list.files("ccal", pattern = "*.xlsx$", full.names = TRUE)

tidy_ccal <- getCCALData(all_files)

lvld_18_data <- tidy_ccal$`LVLD_101118.xlsx`$data  # Get the data for a single set of lab results

lvld_18_meta <- tidy_ccal$`LVLD_101118.xlsx`$metadata # Get the metadata for the same set of results

```