Advanced Excel Power Query | How to Clean Financial Data? | Tutorialspoint
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Power Query is a powerful tool given by Microsoft. Power Query combines different software(SQL, Excel, VBA).
With our Trainer, You learn:
- Introduction to Advanced Excel Power Query
- Excel Installation
- Advanced Excel Power Query Text Functions
- Date Function- Calculate Age in 2 button clicks
- Merge Queries from two Excel Files
- Append 100 Excel Tables
- 99+ Excel functions can be replaced by button clicks
- M Function for Date
- 700 M functions to reduce tasks
- Merge Queries - No VLOOKUP.
- How to Clean Financial Data with Power Query.
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0:00
Hello everyone and welcome back
0:02
In this video we'll see one more case study related to finance department
0:07
How do I clean this kind of financial data when I get from the company
0:11
It becomes very tedious and very challenging part to create a pivot table or to do any ysis part
0:16
Or if I want to create a chart, report, anything. So you see on the screen I have some data, that's a financial data
0:23
And you see, I have June, July. This sells are merged. Then I have the second heading, actual budget and the variance
0:29
budget and the variance, same way actual budget and variance. On the left hand side, if you see
0:33
there's a revenue given and these are the empty rows, total revenues given, expenses, total
0:37
empty rows. And same way at the bottom, there are two empty rows or one single null row at the
0:42
bottom, the blank rows. How do I clean this data and convert into this format? So I can create a chart
0:50
pivot table, pivot report, anything with help of this data. So from coming this data, you know
0:55
unclean data to clean data, it takes only seven to eight. button clicks in Power Query. Seven, eight button clicks, no using function, no using any formula
1:04
no anything. Just using a few button clicks in Power Query, we'll see how to clean this data
1:08
Now, before going to Power Query, let me explain you what are the things we'll be doing here
1:13
First thing, I'll try to fill down this column so that I can get revenue, revenue, revenue
1:17
revenue, revenue, revenue, everywhere. Same way, I'll get expenses on all the places. Second thing, I don't want this total revenue, total expenses, net, loss and income
1:25
because this total values I can calculate later on. So I'll try to filter this values here
1:31
Third thing, if you see, there are two column headings into this data here
1:35
I cannot unpivoted two column headings. In the previous video of a scene, the case study, there was only one column heading Jan to December
1:42
It was easy to unpevote. But there are two column headings you cannot unpevote
1:47
So what you have to do is you have to merge these two records and then you have to unpevote
1:52
Okay that the thing But again there a challenge there is no merging rows in power query there is merging columns possible in Power Query So I have to do a transpose merge the columns etc etc and etc
2:04
And finally, I'll come back to that clean data. So start with the basic one. Let me show you how to pull this data and do it further
2:11
So right now, what I've done is I have created a name range and given the data as my data. The name range as my data
2:18
I have purposely selected this data here. I cannot convert this into a table and get it
2:22
because it doesn't look like a table format. Okay. Now, after giving this name range
2:27
click on data tab and click on from table. So ignore the warning which you're getting
2:32
Right. Now you can see I have got the data that is column one, column two, and so on
2:36
And carefully observe, when I had June, there were three cells which were merge. Now you see June, null, null
2:42
July, null, null, these are the values given. So I have to also fill right
2:46
There is no fill right option in power query. There's only fill down or fill up
2:50
So that thing also I have to work out. So first thing, select the column 1, transform and I'll just select the option fill down
2:57
So if I click on fill down, you can see all the places revenue, total revenues, expenses will come here
3:02
Now, I have to remove this total revenues and also total expense and net income loss
3:07
So click on this drop down and I can select the option from here as deselect total revenue expense and net income loss
3:15
Because this can be calculated later on. So in normal table, you don't need this aggregation value
3:20
So click on okay. that has been removed Next thing If I want to fill on the right there is no method Okay June fill right July fill right You see there is no fill right or fill left option So I have to transpose the table so then only I can fill down that option Okay So now I just click on this transform tab transpose and you can see this has been transpose Now it becomes very easy to fill down So select the column and now I can select the option as fill down Okay I got this data here After filling down when I again transpose back because I brought it for filling down This will be two column headings There is no method in Power Query to unpivot two column headings There is only one method
4:00
You can only combine these columns and make it as one column. So select those two columns
4:06
So I'll select these two columns, that is column one and column two. And I'll try to merge this columns using Transform
4:13
And there's an option given as merge columns. And the separator can be anything, comma, space, anything
4:19
because later on I'll just remove that delimiter. So I'll select the option as colon and I'll click on okay
4:25
Now, these two columns have become one. Okay, these two columns have become one
4:30
Now, why did I combine this columns? You can see right now. Again, if I click on transpose
4:35
now I have only one column heading. Previously, I had two column headings
4:40
Now, I have only one column heading. Now, the last thing, if I want to un-pivot
4:45
I have to promote this as headers. This row should be promoted as headers
4:49
So, transform, and you can see there are two options. Use first row as headers
4:54
So I'll select the option as use first row as headers. Now you can see all the headers are been given here, June, June budget, variance and so on
5:03
Now, the last thing is, I have to keep these two columns constant and I can unpivot the other columns
5:09
because you see this is June, June, and so on. So select those two columns, right click on any column heading, any selected column heading
5:17
and then you can select the option as un-pivot other columns. Click on un-pivot other columns and you can see the data is coming into a table format
5:25
It has still not come. We have to again clean the data. This attribute column has to be separated
5:31
The separator here is nothing but colon. So transform tab and I have the option as split column split by delimiter
5:38
So I'll select split by delimiter and automatically it will pick up the delimiter that is colon
5:43
I have to click on okay. And you can see these are two different columns I have
5:47
After doing that what I can do is I can just keep on renaming the columns here So I just double click here and type as month Second one I write as details or actual hyphen I can write as budget
6:04
And third one I can just write as product type. And fourth one I can write as revenue or expense
6:16
Okay, revenue and expense. Please ignore the spelling. So I've got this four columns
6:24
And I think this variance can be calculated later on. So I can just click on this drop down and I can select the option
6:29
De-select this variance. Click on okay. Okay. So this is a clean data which can be used for creating charts, reports and visualization
6:36
Anything. Now I can click on home, close and load. Okay. So see, that's a new data which I've got
6:42
And this is the unclean data which cannot be used for ysis purpose
6:46
Any point of time you want to go back and see what are the steps I've applied
6:50
So what you can do is you can just double click here, that is my data. And now you'll get this power query editor
6:55
What is the first step, second step, third step, this is a revision. So you can just click on the first step
7:01
This first two steps automatically come. Third step is, if you see, that is a fill down
7:05
Okay. So you see, that's a fill down. Keep on observing. If I keep on clicking here, the steps would be given here
7:10
So the filtered rows, and then I transpose the table, and then I fill down, and then I merge the columns
7:16
and transpose, etc., etc. So this can be notes for you. You can keep this notes with you
7:21
At any point of time, if you get similar case study, you can apply the steps
7:25
Yes, depending upon the logic, which is relevant to your example. So I can just click on close and that's it
7:31
So any changes made in this data will be reflected into your output data
7:36
And same if you create a pivot table or any pivot chart from this data
7:40
same story. Data source changes and the values will change here. So I hope you have understood
7:44
how to clean this financial data, by using Power Query in just few button clicks
7:49
That's all for this video
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