The DataWeave Analytics library provides a collection of simple functions intended to perform data analysis over datasets. DataWeave, which supports data transformations in multiple formats, is a fast analyzer for datasets. This library fills a gap in some commonly used functionalities.
The CSVSummary on analytics::summaries consumes a CSV file and produces
a summary of the values on the different columns present in it.
For example, assume the following CSV input:
id,time,age
1,234,18
2,333,24
3,108,15
4,444,44
The CSVSummary mapping produces the following JSON output from the CSV input:
{
"id": {
"mean": 2.5,
"modes": [
"1",
"2",
"3",
"4"
],
"median": 2.5,
"stdev": 1.118033988749895,
"quartiles": [
1.5,
2.5,
3.5
]
},
"time": {
"mean": 279.75,
"modes": [
"234",
"333",
"108",
"444"
],
"median": 283.5,
"stdev": 123.8999092009352523399554085511010,
"quartiles": [
171,
283.5,
388.5
]
},
"age": {
"mean": 25.25,
"modes": [
"18",
"24",
"15",
"44"
],
"median": 21,
"stdev": 11.29988937998952271159312403049506,
"quartiles": [
16.5,
21,
34
]
}
}Notice that the result provides a summary consisting of the mean, the modes, the median, the standard deviation, and the quartiles of the values of each column in the CSV file.
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