Grouped norm dist

[Anonymous]

Hi all,

I'm trying to make a grouped norm.dist calculation but can't yet figure it out. Below an example of my dataset (item, price):

chair	30
couch	400
table	200
table	150
chair	11
desk	100
chair	60
couch	180
chair	100

If I would do a normal norm.dist calculation it wouldn't do any good since there are different products. That's why I want to group the calculation based on the product column. Each item should be calculated on it's own median and mean prices, and not on all the prices. It's btw big data with around 1K different items.

Any idea? Thanks in advance!

[FreemanZ]

hi @Anonymous 

try to plot a table visual with the product column and measures like:

mean = MEAN(TableName[Price])

median = MEDIAN(TableName[Price])

Or?

[Anonymous]

I would like to have the data in a calculated column, so that won't work. Besides that I dont want the distribution over all the prices but the distribution for each product within it's own prices.

[FreemanZ]

hi @Anonymous 

try to create a calculated table like:

Table =

ADDCOLUMNS(

    VALUES(TableName[Product]),

    "mean",

     CALCULATE(MEAN(TableName[Price])),

    "median",

    CALCULATE(MEDIAN(TableName[Price]))

)

[Anonymous]

The problem is that it calculates everything on all the data, while you want to know the mean/median/stddev based on the items prices. Example;

item	price	stddev
chair	30	A
couch	400	B
table	200	C
table	150	C
chair	11	A
desk	100	D
chair	60	A
couch	180	B
chair	100	A

[Anonymous]

The problem is that it calculates it over all the data ... I want to group the values based on the items. Example:

item	price	med	mean	std.dev
chair	30	45	50.25	33.62
couch	400	290	290	110
table	200	175	175	25
table	150	175	175	25
chair	11	45	50.25	33.62
desk	100	null	null	null
chair	60	45	50.25	33.62
couch	180	290	290	110
chair	100	45	50.25	33.62

The endgoal is to filter out outliers automatically within the report.

[FreemanZ · Accepted solution]

Aha, @Anonymous  try to add three columns like:

mean2 = 
VAR _table =
FILTER(
    TableName, 
    TableName[item] = EARLIER(TableName[item])
)
RETURN
AVERAGEX(
    _table,
    TableName[Price]
)

med2 = 
VAR _table =
FILTER(
    TableName,
    TableName[item] = EARLIER(TableName[item])
)
RETURN
CONVERT(
    MEDIANX(
        _table,
        TableName[Price]
    ), 
    INTEGER
)

std.dev2 = 
VAR _table =
FILTER(
    TableName,
    TableName[item] = EARLIER(TableName[item])
)
RETURN
STDEVX.P(
    _table,
    TableName[Price]
)

it worked like: