Category

Category plots display data values from different discrete categories.

Data Sourcing

Category plots can be created using data from tables and arrays.

Creating a Category Plot using Data from a Table

When data is sourced from a table, the following syntax can be used to create a category:

.catPlot("SeriesName", source, "CategoryCol", "ValueCol").show()

  • catPlot is the method used to create a category plot.
  • "SeriesName" is the name (string) you want to use to identify the series on the plot itself.
  • source is the table that holds the data you want to plot.
  • "CategoryCol" is the name of the column (as a string) to be used for the categories.
  • "ValueCol" is the name of the column (as a string) to be used for the values.
  • show tells Deephaven to draw the plot in the console.
//source the data
t1c = db.t("LearnDeephaven", "StockTrades")
        .where("Date > `2017-08-20`", "USym = `MSFT`")
        .view("Date", "USym", "Last", "Size", "ExchangeTimestamp")

totalSharesByUSym = t1c.view("Date", "USym", "SharesTraded=Size")
        .sumBy("Date", "USym")

//build the plot
categoryPlot = catPlot("MSFT", totalSharesByUSym.where("USym = `MSFT`"), "Date", "SharesTraded")
        .chartTitle("Shares Traded")
        .show()

from deephaven import Plot
# source the data
t1c = db.t("LearnDeephaven", "StockTrades") \
    .where("Date > `2017-08-20`", "USym = `MSFT`") \
    .view("Date", "USym", "Last", "Size", "ExchangeTimestamp")

totalSharesByUSym = t1c.view("Date", "USym", "SharesTraded=Size") \
    .sumBy("Date", "USym")

# build the plot
categoryPlot = Plot.catPlot("MSFT", totalSharesByUSym.where("USym = `MSFT`"), "Date", "SharesTraded") \
    .chartTitle("Shares Traded") \
    .show()

img

Creating a Category Plot using Data from Arrays

When data is sourced from a array, the following syntax can be used to create a category:

.catPlot("SeriesName", [category], [values]).show()

  • catPlot is the method used to create a category plot.
  • "SeriesName" is the name (as a string) you want to use to identify the series on the chart itself.
  • [category] is the array containing the data to be used for the X values.
  • [values] is the array containing the data to be used for the Y values.
  • show tells Deephaven to draw the plot in the console.

Categories with Shared Axes

You can also compare multiple categories over the same period of time by creating a category plot with shared axes. In the following example, a second category plot has been added to the previous example, thereby creating bar graphs on the same chart:

t2c = db.t("LearnDeephaven", "StockTrades")
        .where("Date > `2017-08-20`", "USym in `AAPL`, `MSFT`")
        .view("Date", "USym", "Last", "Size", "ExchangeTimestamp")

totalSharesByUSym2 = t2c.view("Date", "USym", "SharesTraded=Size").sumBy("Date", "USym")

categoryPlot2 = catPlot("MSFT", totalSharesByUSym2.where("USym = `MSFT`"), "Date", "SharesTraded")
        .catPlot("AAPL", totalSharesByUSym2.where("USym = `AAPL`"), "Date", "SharesTraded")
        .chartTitle("Shares Traded")
        .show()

from deephaven import Plot

t2c = db.t("LearnDeephaven", "StockTrades") \
    .where("Date > `2017-08-20`", "USym in `AAPL`, `MSFT`") \
    .view("Date", "USym", "Last", "Size", "ExchangeTimestamp")

totalSharesByUSym2 = t2c.view("Date", "USym", "SharesTraded=Size").sumBy("Date", "USym")

categoryPlot2 = Plot.catPlot("MSFT", totalSharesByUSym2.where("USym = `MSFT`"), "Date", "SharesTraded") \
    .catPlot("AAPL", totalSharesByUSym2.where("USym = `AAPL`"), "Date", "SharesTraded") \
    .chartTitle("Shares Traded") \
    .show()

img

Subsequent categories can be added to the chart by adding additional catPlot() methods to the query. However, the plotBy() method can also be used to do this.

Note

See plotBy(./)

Plot Styles

By default, values are presented as vertical bars. However, by using Deephaven's plotStyle() method, the data can be represented as a bar, a stacked bar, a line, an area or a stacked area.

In any of the examples below, you can simply swap out the .plotStyle() argument with the appropriate name; e.g., ("Area"), ("stacked_area"), etc.

Note

See Plot Styles

Category Plot with Stacked Bar

t2c = db.t("LearnDeephaven", "StockTrades")
        .where("Date >`2017-08-20`", "USym in `AAPL`, `MSFT`")
        .view("Date", "USym", "Last", "Size", "ExchangeTimestamp")

totalSharesByUSym2 = t2c.view("Date", "USym", "SharesTraded=Size").sumBy("Date", "USym")

categoryPlotStacked = catPlot("MSFT", totalSharesByUSym2.where("USym = `MSFT`"), "Date", "SharesTraded")
        .catPlot("AAPL", totalSharesByUSym2.where("USym = `AAPL`"), "Date", "SharesTraded")
        .plotStyle("stacked_bar")
        .chartTitle("Shares Traded")
        .show()

from deephaven import Plot

t2c = db.t("LearnDeephaven", "StockTrades") \
    .where("Date >`2017-08-20`", "USym in `AAPL`, `MSFT`") \
    .view("Date", "USym", "Last", "Size", "ExchangeTimestamp")

totalSharesByUSym2 = t2c.view("Date", "USym", "SharesTraded=Size").sumBy("Date", "USym")

categoryPlotStacked = Plot.catPlot("MSFT", totalSharesByUSym2.where("USym = `MSFT`"), "Date", "SharesTraded") \
    .catPlot("AAPL", totalSharesByUSym2.where("USym = `AAPL`"), "Date", "SharesTraded") \
    .plotStyle("stacked_bar") \
    .chartTitle("Shares Traded") \
    .show()

img

Multiple Sets of Stacked Category Plots

Note

This feature is currently available in Deephaven Classic, and will be coming to the web soon.

Multiple sets of stacked category plots can be created by assigning each category to a group and then applying a plot style:

t3c = db.t("LearnDeephaven", "StockTrades")
        .where("Date > `2017-08-20`", "USym in `AAPL`, `MSFT`, `IBM`, `CSCO`")
        .view("Date", "USym", "Last", "Size", "ExchangeTimestamp")

totalSharesByUSym3 = t3c.view("Date", "USym", "SharesTraded=Size").sumBy("Date", "USym")

multiStackCatPlot = catPlot("MSFT", totalSharesByUSym3.where("USym = `MSFT`"), "Date", "SharesTraded")
        .group(1)
        .catPlot("AAPL", totalSharesByUSym3.where("USym = `AAPL`"), "Date", "SharesTraded")
        .group(1)
//the two series above are assigned to group 1

        .catPlot("IBM", totalSharesByUSym3.where("USym = `IBM`"), "Date", "SharesTraded")
        .group(2)
        .catPlot("CSCO", totalSharesByUSym3.where("USym = `CSCO`"), "Date", "SharesTraded")
        .group(2)
//the two series above are assigned to group 2

        .plotStyle("stacked_bar")
        .chartTitle("Shares Traded")
        .show()

from deephaven import Plot

t3c = db.t("LearnDeephaven", "StockTrades") \
    .where("Date > `2017-08-20`", "USym in `AAPL`, `MSFT`, `IBM`, `CSCO`") \
    .view("Date", "USym", "Last", "Size", "ExchangeTimestamp")

totalSharesByUSym3 = t3c.view("Date", "USym", "SharesTraded=Size").sumBy("Date", "USym")

multiStackCatPlot = Plot.catPlot("MSFT", totalSharesByUSym3.where("USym = `MSFT`"), "Date", "SharesTraded") \
    .group(1) \
    .catPlot("AAPL", totalSharesByUSym3.where("USym = `AAPL`"), "Date", "SharesTraded") \
    .group(1)\
    .catPlot("IBM", totalSharesByUSym3.where("USym = `IBM`"), "Date", "SharesTraded") \
    .group(2) \
    .catPlot("CSCO", totalSharesByUSym3.where("USym = `CSCO`"), "Date", "SharesTraded") \
    .group(2)\
    .plotStyle("stacked_bar") \
    .chartTitle("Shares Traded") \
    .show()

img

Additional Options