We have received a chart for chart busters that required some fixing. I thought, this will be a fun exercise for you. So here it goes,
…column chart that shows daily, weekly or monthly data depending on the user’s choice. In daily the columns are displayed properly, but in weekly & monthly mode the columns are a fraction of the width they should be – why, and how can this be avoided? Bonus points if you can describe how to use an INDIRECT formula on the x-axis labels which is another problem I ran into whilst creating this mockup!
You can download the workbook from here.
Here is how it is looking:
Thanks Gordon for asking this question.
Featured Answers:
There were several people who answered this correctly. I am featuring two answers for this problem.
By Jeff Weir:
One way to fix this is to select the ‘axis options/axis type/text axis’ option in the axis dialogue box (it’s current setting is “Automatically select based on data”.
Then it would be good if you set the ‘interval between tick marks as one, as well as the ‘interval between labels’ as 1 also.
Unfortunately then you run into the problem that your dates are now too wide for the space allowed for them on the graph. Easiest way to do that is to firstly make the graph a little wider, and secondly have an intermediate formula that formats your dates so they have a character return between the month and year, like this:
1 Jan
2009
instead of this:
1 Jan 2009
You can accomplish that with a formula along the lines of this:
=DAY(B6)&CHOOSE(MONTH(B6),” Jan”, ” Feb”, ” Mar”, ” Apr”, ” May”, ” Jun”, ” Jul”, ” Aug”, ” Sep”,” Oct”,” Nov”,” Dec”)&CHAR(10)&YEAR(B6)
Also, the y axis could do with a custom number format. No point of displaying all those zeros if say $250k or 250k (assuming not a currency) will do.
You can see it here
By Gerald Higgins
Well, here goes with the simple solution (in 2003).
Right click the chart, and select Chart Options.
On the AXES tab, there are 3 options under “Category (X) axis”.
I think the option for Time scale was originally selected.
The option for “Automatic” also does not work.
But the option for “Category” does work.
All the commenters with an answer will receive their discount codes by this weekend. Enjoy.
Lear more about making better charts using these chart busters examples:
- Asset Allocation Charts – Done the right way
- Calorie chart – How much you should exercise for what you eat – fixed properly
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.