Data frames for Java
Java Other
Latest commit a11ebdf Oct 9, 2016 @cardillo update dependencies.

README.md

joinery

joinery [joi-nuh-ree]
1. In woodworking, the craft of joining together pieces of wood to produce more complex items.
2. In Java, a data analysis library for joining together pieces of data to produce insight.

quick start

Remember FizzBuzz (of course you do!), well imagine you have just solved the puzzle (well done!) and you have written the results to a comma-delimited file for further analysis. Now you want to know how many times are the strings Fizz, Buzz, and FizzBuzz printed out.

You could answer this question any number of ways, for example you could modify the original program, or reach for Python/pandas, or even (for the sadistic among us, you know who you are) type out a one-liner at the command prompt (probably including cut, sort, and uniq).

Well, now you have one more option. This option is especially good if you are 1) using Java already and 2) may need to integrate your solution with other Java applications in the future.

You can answer this question with joinery.

df.groupBy("value")
  .count()
  .sortBy("-number")
  .head(3)

Printing out the resulting data frame gives us the following table.

       value    number
 0  Fizz            27
 1  Buzz            14
 2  FizzBuzz         6

See FizzBuzz.java for the complete code.

next steps

Get the executable jar and try it for yourself.

$ java -jar joinery-dataframe-1.8-jar-with-dependencies.jar shell
# Joinery -- Data frames for Java, 1.8-5feda86
# Java HotSpot(TM) 64-Bit Server VM, Oracle Corporation, 1.8.0_91
# Rhino 1.7 release 2 2009 03 22
> df = new DataFrame()
[empty data frame]
> df.add("value")
[empty data frame]
> [10, 20, 30].forEach(function(val) {
      df.append([val])
  })
> df
        value
 0     10
 1     20
 2     30

>

maven

A maven repository for joinery is hosted on JCenter. For instructions on setting up your maven profile to use JCenter, visit https://bintray.com/bintray/jcenter.

<dependency>
  <groupId>joinery</groupId>
  <artifactId>joinery-dataframe</artifactId>
  <version>1.8</version>
</dependency>

download

JCenter also allows for direct download using the button below.

Download

utilities

joinery includes some tools to make working with data frames easier. These tools are available by running joinery.DataFrame as an application.

$ java joinery.DataFrame
usage: joinery.DataFrame [compare|plot|show|shell] [csv-file ...]

show

Show displays the tabular data of a data frame in a gui window.

$ java joinery.DataFrame show data.csv

Screenshot of show window

plot

Plot displays the numeric data of a data frame as a chart.

$ java joinery.DataFrame plot data.csv

Screenshot of plot window

shell

Launches an interactive JavaScript shell for working with data frames.

$ java joinery.DataFrame shell
# Joinery -- Data frames for Java, 1.8-5feda86
# Java HotSpot(TM) 64-Bit Server VM, Oracle Corporation, 1.8.0_91
# Rhino 1.7 release 2 2009 03 22
> df = DataFrame.readCsv("https://www.quandl.com/api/v1/datasets/GOOG/NASDAQ_AAPL.csv")
              Date    Open    High     Low          Close                Volume
    0   2015-03-20  128.25  128.4   125.16   125.90000000     68695136.00000000
    1   2015-03-19  128.75  129.25  127.4    127.50000000     45809490.00000000
    2   2015-03-18  127.0   129.16  126.37   128.47000000     65270945.00000000
    3   2015-03-17  125.9   127.32  125.65   127.04000000     51023104.00000000
    4   2015-03-16  123.88  124.95  122.87   124.95000000     35874300.00000000
    5   2015-03-13  124.4   125.4   122.58   123.59000000     51827283.00000000
    6   2015-03-12  122.31  124.9   121.63   124.45000000     48362719.00000000
    7   2015-03-11  124.75  124.77  122.11   122.24000000     68938974.00000000
    8   2015-03-10  126.41  127.22  123.8    124.51000000     68856582.00000000

... 8649 rows skipped ...

 8658   1980-12-12  0.0 4.12    4.11       4.11000000     14657300.00000000

> df.types()
[class java.util.Date, class java.lang.String, class java.lang.String, class java.lang.String, class java.lang.Double, class java.lang.Double]
> df.sortBy("Date")
              Date     Open     High     Low            Close                Volume
 8658   1980-12-12  0.0 4.12    4.11       4.11000000     14657300.00000000
 8657   1980-12-15  0.0 3.91    3.89       3.89000000      5496400.00000000
 8656   1980-12-16  0.0 3.62    3.61       3.61000000      3304000.00000000
 8655   1980-12-17  0.0 3.71    3.7        3.70000000      2701300.00000000
 8654   1980-12-18  0.0 3.82    3.8        3.80000000      2295300.00000000
 8653   1980-12-19  0.0 4.05    4.04       4.04000000      1519700.00000000
 8652   1980-12-22  0.0 4.25    4.23       4.23000000      1167600.00000000
 8651   1980-12-23  0.0 4.43    4.41       4.41000000      1467200.00000000
 8650   1980-12-24  0.0 4.66    4.64       4.64000000      1500100.00000000

... 8649 rows skipped ...

    0   2015-03-20  128.25  128.4   125.16   125.90000000     68695136.00000000

> .reindex("Date")
           Open High     Low            Close                Volume
1980-12-12  0.0 4.12    4.11       4.11000000     14657300.00000000
1980-12-15  0.0 3.91    3.89       3.89000000      5496400.00000000
1980-12-16  0.0 3.62    3.61       3.61000000      3304000.00000000
1980-12-17  0.0 3.71    3.7        3.70000000      2701300.00000000
1980-12-18  0.0 3.82    3.8        3.80000000      2295300.00000000
1980-12-19  0.0 4.05    4.04       4.04000000      1519700.00000000
1980-12-22  0.0 4.25    4.23       4.23000000      1167600.00000000
1980-12-23  0.0 4.43    4.41       4.41000000      1467200.00000000
1980-12-24  0.0 4.66    4.64       4.64000000      1500100.00000000

... 8649 rows skipped ...

2015-03-20  128.25  128.4   125.16   125.90000000     68695136.00000000

> .retain("Close")
                    Close
1980-12-12     4.11000000
1980-12-15     3.89000000
1980-12-16     3.61000000
1980-12-17     3.70000000
1980-12-18     3.80000000
1980-12-19     4.04000000
1980-12-22     4.23000000
1980-12-23     4.41000000
1980-12-24     4.64000000

... 8649 rows skipped ...

2015-03-20   125.90000000

> .plot(PlotType.AREA)

documentation

The complete api documentation for the DataFrame class is available at http://cardillo.github.io/joinery


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