Take a Tabular object:

Aggregate all rows by computing the joined string of "col1" and the total of the values of column "col2":

Aggregate rows by first grouping those with common value of column "col1" and then totaling:

Use operator form to aggregate a list of associations by computing a function of the values of key "a":

Aggregate associations by first grouping those with common value of key "b":

Take a Tabular object with measurements of soil pH at three depth levels of 0, 30 and 80 meters:

Find mean pH for each depth:

Take measurements of various species of iris flower:

Compute the mean of the second column:

Compute the median of the "PetalLength" column:

Compute number of observations for each species:

Compute the mean of "SepalLength" for each species variety:

Old Faithful geyser data containing eruption times and next eruption waiting times in minutes:

Compute correlation between the columns:

Visualize the waiting time vs. duration:

Compute mean of the durations depending on the waiting time:

Convert into the normal form of the Tabular object:

Take a table of data about penguins in the Palmer Archipelago:

Extract column names:

Find the mean body weight for each sex:

Find the median body weight for each island location:

Find the body mass distribution for each species:

Plot the PDF for each estimated distribution:

Take a Tabular object with data of monthly ozone readings for Los Angeles:

Compute the mean for each column, each month:

Visualize the mean seasonality:

Take a Tabular object with data for a selection of car models:

Find the mean city and highway milage per each drive type and year:

Find the mean city and highway milage per each manufacturer for year 2008:

Using AggregateRows without grouping input may reduce a Tabular object too much:

Tally species varieties:

Use grouping: