Analyze Aggregated Sales Data

Find the market sector with the highest revenue in each region

Start with a table of sales information for a company. It tracks sales by date, geographic region, market sector, product type etc.:

In[1]:=

sales=Select[ResourceData["Sample Tabular Data: Sales Data"],#Date≥DateObject[{2015,7,1},"Day"]&]

Out[1]=

Simplify the table to show sales data by date, using Total to aggregate the values:

In[2]:=

salesByDate=AggregateRowssales,"Quantity"Function[Total[#Quantity]],

,"Date"

Out[2]=

Show the revenue and cost over time:

In[3]:=

ListLinePlotsalesByDate{{"Date","Revenue"},{"Date","Cost"}},





Out[3]=

	Revenue
	Cost

Create a scatter plot of revenue vs. cost to see that the company has a very tight pricing scheme for their products:

In[4]:=

ListPlotsales{"Cost","Revenue"},





Out[4]=

Plot a histogram of the quantity column. The sales are fairly evenly distributed in size:

In[5]:=

Histogram[sales"Quantity"]

Out[5]=

Pivot the data by region to effectively create multiple datasets:

In[6]:=

salesByRegion=PivotToColumns[sales,"Region""Quantity"]

Out[6]=

Show a histogram of the number of sales of given sizes in each region:

In[7]:=

HistogramsalesByRegion{"Midwest","Northeast","South","West"},



Out[7]=

Show all the regions together in a stacked histogram:

In[8]:=

HistogramsalesByRegion{"Midwest","Northeast","South","West"},



Out[8]=

	Midwest
	Northeast
	South
	West

Aggregate the data by region and product:

In[9]:=

salesByRegion2=SortByAggregateRowssales,"Quantity"Function[Total[#Quantity]],

,{"Region","Product"},"Region"

Out[9]=

Format labels in a readable form:

In[10]:=

labels=Row[#,":"]&/@

FromTabular[

]

;

Create a bar chart showing revenue by region and product:

In[11]:=

BarChartsalesByRegion2"Revenue",



Out[11]=

Get the total revenue for each region and market sector:

In[12]:=

salesBySector=AggregateRows[sales,{"TotalRevenue"Function[Total[#Revenue]]},{"Region","Sector"}]

Out[12]=

Get a list of all the regions in the sales data:

In[13]:=

regions=DeleteDuplicates[salesBySector〚All,"Region"〛]//Normal

Out[13]=

{Northeast,South,Midwest,West}

Select the data for each region:

In[14]:=

selectedDataByRegion=Map[regionNameSelect[salesBySector,#RegionregionName&],regions]

Out[14]=



Tabular

Row count: 4

Column count: 3



Tabular

Row count: 4

Column count: 3



Tabular

Row count: 3

Column count: 3



Tabular

Row count: 4

Column count: 3





Find the sector with the highest revenue in each region:

In[15]:=

Join@@Map[regionDataSelect[regionData,Function[record,record["TotalRevenue"]Max[regionData[All,"TotalRevenue"]]]],selectedDataByRegion]

Out[15]=

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Contributed by: Wolfram Research

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Analyze Aggregated Sales Data

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Analyze Aggregated Sales Data

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