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jwhitlow
Regular Visitor

Logins Per Day

    I am hoping someone can guide me with how to take a table with individual logins data and create a summary table. This is an example of what my source table look like:

 

 Name  Timestamp
 Betty  2021-07-15 23:00 
 Betty  2021-07-15 23:00 
 Betty  2021-07-15 21:28 
 Hellen  2021-07-26 10:39 
 Hellen  2021-07-26 09:26 
 Milo  2021-07-26 09:40 
 Milo  2021-07-15 05:40 
 Patrick  2021-07-16 06:31 
 Patrick  2021-07-15 08:00 
 Patrick  2021-07-14 13:38 
 Patrick  2021-07-14 10:33 
 Patrick  2021-07-14 07:44 
 Robert  2021-07-26 04:14 
 Robert  2021-07-15 07:44 
 Robert  2021-07-15 04:15 
 Susan  2021-07-23 00:59 
 Susan  2021-07-22 01:01 
 Susan  2021-07-12 01:01 
 Will  2021-07-13 06:46 

 

  Below is the result I am trying to accomplish. I am able to do this in Excel using VBA. I am trying to replicate this in Power BI without using VBA.

 

 Name  Logins  Days  Average 
 Betty  3  1  3.00
 Hellen  2  1  2.00
 Milo  2  2  1.00
 Patrick  5  3  1.67
 Robert  3  2  1.50
 Susan  3  3  1.00
 Will  1  1  1.00

 

1 ACCEPTED SOLUTION
V-pazhen-msft
Community Support
Community Support

@jwhitlow 

You need to also remove time value to get distinctcount for days. Copy and paste the code to a blank query, and check the steps.

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("ndE9C8IwEAbgv3J0buEul37d6OQiiA4OpUOVDsVgocbBf2+ChVJtI7hkeR9e7i5VFcGmtfYZxRGAQkUJ5gmloFgQIarj/wGJKkawbY1pbzOhMiAULoMCS3HvW+w60y/kGtdyNwOmU75v7NBdrnPiKjJhChHXUkyrLhINxMLFD+K25TDBXLQeyaE/t4P9WlgLBYQfNtzhhetIR3F83JuPqzMgSlquAwVIgrQKaA5OnTHznP3Rtf/X+gU=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Name = _t, #"  Timestamp" = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"  Timestamp", type datetime}}),
    #"Split Column by Delimiter" = Table.SplitColumn(Table.TransformColumnTypes(#"Changed Type", {{"  Timestamp", type text}}, "zh-CN"), "  Timestamp", Splitter.SplitTextByDelimiter(" ", QuoteStyle.Csv), {"  Timestamp.1", "  Timestamp.2"}),
    #"Removed Columns" = Table.RemoveColumns(#"Split Column by Delimiter",{"  Timestamp.2"}),
    #"Grouped Rows" = Table.Group(#"Removed Columns", {"Name"}, {{"logins", each Table.RowCount(_), Int64.Type}, {"days", each Table.RowCount(Table.Distinct(_)), Int64.Type}}),
    #"Added Custom" = Table.AddColumn(#"Grouped Rows", "Average", each [logins]/[days])
in
    #"Added Custom"

Vpazhenmsft_2-1628130979461.png

 

 

Paul Zheng _ Community Support Team
If this post helps, please Accept it as the solution to help the other members find it more quickly.

View solution in original post

4 REPLIES 4
V-pazhen-msft
Community Support
Community Support

@jwhitlow 

You need to also remove time value to get distinctcount for days. Copy and paste the code to a blank query, and check the steps.

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("ndE9C8IwEAbgv3J0buEul37d6OQiiA4OpUOVDsVgocbBf2+ChVJtI7hkeR9e7i5VFcGmtfYZxRGAQkUJ5gmloFgQIarj/wGJKkawbY1pbzOhMiAULoMCS3HvW+w60y/kGtdyNwOmU75v7NBdrnPiKjJhChHXUkyrLhINxMLFD+K25TDBXLQeyaE/t4P9WlgLBYQfNtzhhetIR3F83JuPqzMgSlquAwVIgrQKaA5OnTHznP3Rtf/X+gU=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Name = _t, #"  Timestamp" = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"  Timestamp", type datetime}}),
    #"Split Column by Delimiter" = Table.SplitColumn(Table.TransformColumnTypes(#"Changed Type", {{"  Timestamp", type text}}, "zh-CN"), "  Timestamp", Splitter.SplitTextByDelimiter(" ", QuoteStyle.Csv), {"  Timestamp.1", "  Timestamp.2"}),
    #"Removed Columns" = Table.RemoveColumns(#"Split Column by Delimiter",{"  Timestamp.2"}),
    #"Grouped Rows" = Table.Group(#"Removed Columns", {"Name"}, {{"logins", each Table.RowCount(_), Int64.Type}, {"days", each Table.RowCount(Table.Distinct(_)), Int64.Type}}),
    #"Added Custom" = Table.AddColumn(#"Grouped Rows", "Average", each [logins]/[days])
in
    #"Added Custom"

Vpazhenmsft_2-1628130979461.png

 

 

Paul Zheng _ Community Support Team
If this post helps, please Accept it as the solution to help the other members find it more quickly.

Jakinta
Solution Sage
Solution Sage

You can group them like this

 

= Table.Group(PriorStepName, {"Name"}, {{"Logins", each Table.RowCount(_), Int64.Type} , {"Days", each Table.RowCount(Table.Distinct(_)), Int64.Type}})

 

then divide Logins/Days to get the Average.

Thanks for the quick reply! 😀 Can you please provide a little more detail?

 

In your example, what is 'PriorStepName'?

'PriorStepName' is the name of the last step in your existing query.

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