Description Usage Arguments Details Value See Also Examples
Compute aggregates across category class represented by the table
column. Values are one or more SQL aggregates that are valid expressions
with GROUP BY <class column>
. Class column usually is of character
or other discrete type. Typical example is computing a bar chart for the
column using SQL COUNT(*) ... GROUP BY
- hence the name of the
function. Result is a data frame to visualize as bar charts or heatmaps
(see creating visualizations with createHistogram
and
createHeatmap
).
1 2 3 |
channel |
connection object as returned by |
tableName |
table name |
category |
column name or expression associated with categories. Name may be
valid SQL expression and can contain otional alias (e.g. |
aggregates |
SQL aggregates to compute. Each aggregate corresponds to category value.
Aggregates may have optional aliases like in |
where |
specifies criteria to satisfy by the table rows before applying
computation. The creteria are expressed in the form of SQL predicates (inside
|
orderBy |
list of column names, aliases, references or their combinations to use in SQL |
top |
if specified indicates number of bars to include in bar plot. In combination with |
by |
for optional grouping by one or more columns for faceting or alike (effectively these elements
will be part of |
withMelt |
logical if TRUE then uses reshape2 |
... |
additional arguments to be passed to |
test |
logical: if TRUE show what would be done, only (similar to parameter |
No columns returned as character and not excluded by as.is
are
converted to factors by default, i.e. stringsAsFactors = FALSE
when calling
sqlQuery
if not specified when calling this function.
Data frame to use for bar chart plots with createHistogram
.
computeHistogram
, createHistogram
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | if(interactive()){
# initialize connection to Lahman baseball database in Aster
conn = odbcDriverConnect(connection="driver={Aster ODBC Driver};
server=<dbhost>;port=2406;database=<dbname>;uid=<user>;pwd=<pw>")
# Compute average team season era, walks, and hits for each decade starting with 1980
computeBarchart(channel=conn, "teams_enh", "teamid team",
aggregates=c("avg(era) era", "avg(bb) bb", "avg(h) h"),
where="yearid >=1980", by=c("decadeid"))
# multipe aggregates in the same bar chart (with melt)
bc = computeBarchart(channel=conn, tableName="pitching_enh", category="teamid",
aggregates=c("AVG(era) era", "AVG(whip) whip"), withMelt=TRUE,
where="yearid >= 2000 and lgid='AL'")
# adding facets by decadeid
bc = computeBarchart(channel=conn, tablelName="pitching_enh", category="teamid",
aggregates=c("AVG(era) era", "AVG(whip) whip", "AVG(ktobb) ktobb"),
where="yearid >= 1990 and lgid='AL'", by="decadeid", withMelt=TRUE)
}
|
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