Yesterday while going through my feeds, I have landed on this post about the demographics and use-figures of various social networking (2.0) tools, et al (by businessweek) on think:lab blog. When I looked at the BusinessWeek’s graphical representation of demographics and usage figures of social networks, the first thought that came to me is, “well, this is something challenging to do in Excel“. So I started creating the chart in the most famous cell software :D, just to show you how the graph looked on BW site (click on it to see the bigger version),
(Download download the art of excel charting spreadsheet)
First up I tried creating a graphlet, a 10 by 10 cell grid that can be filled by ‘1’s based on a number between 1 and 100. The ‘1’s should be filled from left to right or right to left based on direction mentioned in a cell.
This task is simple, lets say the grid is from a1 to j10 and a11 has ‘the number of cells to be filled’ and a12 has the direction (either “R” or “L”)
The formula for any cell in the range of a1 to j10 would be,
= IF((ROW($a$10)-ROW())*10+11*(IF($a$12=”R”,0,1)) + (-1)^(IF($a$12=”R”,0,1))*((COLUMN($j$10)-COLUMN())+1)< =$a$11,1,"")
the above formula essentially means,
if direction is Left to Right,
if row of the cell * 10 + column of the cell is less than or equal to a11
return “1”
else return “”
else
if row of the cell * 10 + 10 – column of the cell is less than or equal to a11
return “1”
else return “”
Once I have the grid filled with required number of 1’s, I have applied conditional formatting (read: Creating cool dash-boards using excel conditional formatting) to change cell’s a ‘1’ in them to some color and blank ones to gray like this,
The output was something like this,
Now all I have to do is multiply this over the entire 7 columns and 6 rows like the BW’s graph and change the fill colors in conditional formatting. The final output looked something like this (click on it for a bigger version),
To end with, I have found out that doing this type of charts doesnt take much time although you need to have the creative juices to come-up with formats like this. What do you think?
For those of you who want to see how this is done and do a little bit of playing around, download the art of excel charting spreadsheet.
Also read:
- Say good-bye to default chart formats
- Creating cool dash-boards using excel conditional formatting
- PHD’s Excel posts
PS: the images are from BusinessWeek.
One Response to “SQL vs. Power Query – The Ultimate Comparison”
Enjoyed your SQL / Power Query podcast (A LOT). I've used SQL a little longer than Chandoo. Power Query not so much.
Today I still use SQL & VBA for my "go to" applications. While I don't pull billions of rows, I do pull millions. I agree with Chandoo about Power Query (PQ) lack of performance. I've tried to benchmark PQ to SQL and I find that a well written SQL will work much faster. Like mentioned in the podcast, my similar conclusion is that SQL is doing the filtering on the server while PQ is pulling data into the local computer and then filtering the data. I've heard about PQ query folding but I still prefer SQL.
My typical excel application will use SQL to pull data from an Enterprise DB. I load data into Structured Tables and/or Excel Power Pivot (especially if there's lot of data).
I like to have a Control Worksheet to enter parameters, display error messages and have user buttons to execute VBA. I use VBA to build/edit parameters used in the SQL. Sometimes I use parameter-based SQL. Sometimes I create a custom SQL String in a hidden worksheet that I then pull into VBA code (these may build a string of comma separated values that's used with a SQL include). Another SQL trick I like to do is tag my data with a YY-MM, YY-QTR, or YY-Week field constructed form a Transaction Date.
In an application, I like to create a dashboard(s) that may contain hyperlinks that allow the end-user to drill into data. Sometimes the hyperlink will point to worksheet and sometimes to a supporting workbook. In some cases, I use a double click VBA Macro that will pull additional data and direct the user to a supplemental worksheet or pivot table.
In recent years I like Dynamic Formulas & Lambda Functions. I find this preferable to pivot tales and slicers. I like to use a Lambda in conjunction with a cube formula to pull data from a power pivot data model. I.E. a Lambda using a cube formula to aggregate Accounting Data by a general ledger account and financial period. Rather than present info in a power pivot table, you can use this combination to easily build financial reports in a format that's familiar to Accounting Professionals.
One thing that PQ does very well is consolidating data from separate files. In the old days this was always a pain.
I've found that using SQL can be very trying (even for someone with experience). It's largely an iterative process. Start simple then use Xlookup (old days Match/Index). Once you get the relationships correct you can then use SQL joins to construct a well behaved SQL statement.
Most professional enterprise systems offer a schema that's very valuable for constructing SQL statements. For any given enterprise system there's often a community of users that will share SQL. I.E. MS Great Plains was a great source (but I haven't used them in years).
Hope this long reply has value - keep up the good work.