##  Deephaven - Category Plotting Notebook - Python  
##  https://docs.deephaven.io/


from deephaven import Plot
# See print(sorted(dir())) or help('deephaven') for full namespace contents.

# note that we are constraining the data to NYSE business time
import deephaven.Calendars as Calendars
cal = Calendars.calendar("USNYSE")
trades = db.t("LearnIris", "StockTrades").where("Date=`2017-08-25`")
trades = trades.where("cal.isBusinessTime(ExchangeTimestamp)")


#  CATEGORY PLOTTING - SINGLE

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")

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


# CATEGORY PLOTTING - MULTIPLE

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()


# CATEGORY PLOTTING - MULTIPLE WITH PLOTSTYLE - 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 = Plot.catPlot("MSFT", totalSharesByUSym2.where("USym = `MSFT`"), "Date", "SharesTraded")\
   .catPlot("AAPL", totalSharesByUSym2.where("USym = `AAPL`"), "Date", "SharesTraded")\
   .plotStyle("stacked_bar")\
   .chartTitle("Shares Traded")\
   .show()


# CATEGORY PLOTTING - MULTIPLE WITH PLOTSTYLE AND GROUPING - STACKED BAR

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()


# ERROR BAR on CATEGORY PLOT

# source the data
t_cat_EB = db.t("LearnDeephaven", "StockTrades")\
   .where("Date = `2017-08-23`", "USym = `GOOG`")\
   .updateView("TimeBin=upperBin(Timestamp, 20 * MINUTE)")\
   .where("isBusinessTime(TimeBin)")

# calculate standard deviations for the upper and lower error values
t_cat_EB_StdDev = t_cat_EB.by(caf.AggCombo(caf.AggAvg("AvgPrice = Last"), caf.AggStd("StdPrice = Last")), "TimeBin")

# plot the data
eb_CatTrades = Plot.catErrorBar("Trades: GOOG", t_cat_EB_StdDev.update("AvgPriceLow = AvgPrice - StdPrice",
                                                                      "AvgPriceHigh = AvgPrice + StdPrice"),
                               "TimeBin", "AvgPrice", "AvgPriceLow", "AvgPriceHigh")\
   .show()