csv-helpers
v0.0.2
Published
This is a little helper library to complement [@jrc03c/js-math-tools](https://github.com/jrc03c/js-math-tools) and [@jrc03c/js-data-science-helpers](https://github.com/jrc03c/js-data-science-helpers). All it does is load CSV files as `DataFrame` objects a
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Intro
This is a little helper library to complement @jrc03c/js-math-tools and @jrc03c/js-data-science-helpers. All it does is load CSV files as DataFrame
objects and save DataFrame
objects as CSV files.
Installation
npm install --save https://github.com/jrc03c/js-csv-helpers
Usage
Node & bundlers:
const { loadCSV, saveCSV } = require("js-csv-helpers")
// load
loadCSV("path/to/my-data.csv").then(df => {
// save
saveCSV("path/to/other-data.csv", df).then(() => {
console.log("Done!")
})
})
Browser:
<script src="path/to/dist/js-csv-helpers"></script>
<script>
// load
loadCSV("path/to/my-data.csv").then(df => {
// save
saveCSV("other-data.csv", df).then(() => {
console.log("Done!")
})
})
</script>
NOTE: Usage in both environments is basically identical except for one thing: In the browser,
saveCSV
takes a filename and aDataFrame
; but in Node,saveCSV
takes a path and aDataFrame
. That's because the browser can only download files without specifying where to save them.
API
loadCSV
loadCSV(
path: string,
config: object || null,
callback: function || null,
)
Given a path
, this function returns a Promise
that resolves to a DataFrame
. It also accepts a optional callback function, if you prefer that style. See the section below for more information about the optional config
object.
saveCSV
saveCSV(
path: string,
data: DataFrame,
config: object || null,
callback: function || null,
)
Given a path
(either a URL or a filesystem path depending whether you're in a browser or Node environment, as described in the Usage section above) and a DataFrame
(data
), this function returns a Promise
that resolves to true
. (If something goes wrong during saving, an error will just be thrown instead of returning false
.) It also accepts an optional callback function, if you prefer that style. See the section below for more information about the optional config
object.
Configuration
This library is basically a thin wrapper around papaparse
. Any configuration object you could pass into this library's functions will be passed directly into papaparse
's functions. See their configuration documentation for more info. As of today, the default configuration values are:
{
delimiter: "", // auto-detect
newline: "", // auto-detect
quoteChar: '"',
escapeChar: '"',
header: false,
transformHeader: undefined,
dynamicTyping: false,
preview: 0,
encoding: "",
worker: false,
comments: false,
step: undefined,
complete: undefined,
error: undefined,
download: false,
downloadRequestHeaders: undefined,
downloadRequestBody: undefined,
skipEmptyLines: false,
chunk: undefined,
chunkSize: undefined,
fastMode: undefined,
beforeFirstChunk: undefined,
withCredentials: undefined,
transform: undefined,
delimitersToGuess: [',', '\t', '|', ';', Papa.RECORD_SEP, Papa.UNIT_SEP]
}
This library only adds one extra option to the configuration object in the loadCSV
function: setting "inferTypes"
to true
or false
enables or disables dynamic type inference. By default, papaparse
doesn't try to figure out what kinds of data your CSV file contains; it merely returns a matrix of strings. They provide an option called "dynamicTyping"
which I think asks papaparse
to try to infer data types, but I don't think it's quite as extensive as the one I've written here.
Here's an example of how to use it:
// use this library's type inference
loadCSV("path/to/my-data.csv", { inferTypes: true })
// use papaparse's type inference
loadCSV("path/to/my-data.csv", { dynamicTyping: true })