I have recently been working on a data table in Excel containing measurements of fossil specimens. In addition to containing things like the specimen number, species name, etc., the table also contains measurements from the fossils in question. However, because several specimens have data from both the left and right sides of the specimen, I often end up with situations where a single entry spans multiple rows, which means I cannot sort the data.
I have looked elsewhere on the Internet for a solution, and the only response I have gotten is that Excel doesn't really work well with entries spanning multiple rows, and I should reorganize my data. I understand that, and I have been looking for an alternate way of organizing the data. However, I have not been able to find an easy way to organize the data. I have tried reorganizing the information so each entry spans multiple rows, but when I do this it becomes very easy to make mistakes and to lose track of the data. It also becomes difficult to compare the data, since the measurements on the left and right side of the specimen are essentially the same thing and I cannot easily compare them if one specimen has a bone only preserved on the right side and the other specimen has the same bone preserved but only on the left side.
I have also tried organizing the measurements into a separate sheet which could be accessed by a hyperlink from the main sheet, but this has also posed problems. Because in this case the measurement data still cannot be sorted by specimen number of species name, if a specimen number or species name changes (which it has in the past), I have to manually reorganize all the hyperlinks by hand.
Finally, I have also tried adding an identifier to the multi-row entries, but this has a tendency to get screwed up if I sort the data, and it also mixes up any equations I use in the sheet. I might be doing it wrong somehow.
The good news is I am not interested in sorting the specimens by measurements, so if there is any way to organize the table so it is sortable but the measurements cannot be sorted, that is fine. At the same time, because all specimens technically have a left and right side (plus the average measurement between them), I could also work with a system wherein each "entry" spanned a set number of rows or subrows.
I was also wondering if it would be possible to write a macro to sort the data (especially since I am just sorting by the first five columns or so), or else do the database in some other program like Microsoft Access. Any help would be greatly appreciated.
Everything you describe really breaks down to: "Excel is great for analysis; but I really should have stored my source data in a database." Accountants I have worked with almost always come to this conclusion eventually, once their data and reporting needs get sufficiently complex.
I suggest you invest the moderate effort to upload your data to a proper database, and learn how to download I as appropriate to Excel for specific analyses. The time effort will be well spent, and simpler by far than coercing EXCEL into tasks for which it is ill-suited.
MS-Access, MySql, and SQL-Server Express are all suitable for this type of upgrade. MS-Access, if already available in your Office subscription, has the advantage of integrating even more easily with Excel than the other two, and also uses VBA as it's macro language. The other two offer more complete and powerful implementations of the SQL language. All told, use the one most easily available to you.
Related
I have a Dataset H3:J12 where components are classified based on Type. I have summed the count for similar components and sorted based on Count with Unique and Sort formulae and the result is L3:M7.
In my actual case, there are several thousands of such components which are sorted as in L:L and now I would like to add the Type column next to the Component with sorted Count as shown in P3:R12. Is it possible to extract them directly from L3:M7 or directly from H3:J12, as I will not be able to do them manually.
Screenshots/here refer:
Mechanical approaches include pivots, VB, etc. However, you could consider a more dynamic approach that doesn't require constant updating / refreshing (of code, pivots, etc.) whenever underlying data is appended/amended.
YES: you can retrieve directly from source data as follows:
=SORT(UNIQUE(C3:D20))
=SUMIFS(E3:E30,C3:C30,H3:H17,D3:D30,I3:I17)
Notes:
Could make this averageif(s), countif(s), percentile etc. etc. - another
significant advantage over alternative methods (VB, pivots, etc.), besides dynamic nature, is the flexibility re: measures; restrictions present in pivots are substantive in relation to Excel direct calculation
Disadvantage is inability to automatically chart data using pivot chart functionality that accompanies pivot tables
See linked sheet opening line for conditional formatting sample used to recreate 'look / feel' you might otherwise be losing out on with this approach
It seemed as though you were almost there! I'm not sure what relevance other tables have (ignored this in light of question).
I'm in the processing of creating a report for the company I work at that has a rather complicated survey export file that needs to have the data extracted in meaningful ways.
The table headers are as follow https://docs.google.com/spreadsheets/d/1Et9Pg6k9CJA3HTO0aHcnSnOWVU05bmHYUsPS0wB2Nr8/edit?usp=sharing
It has respondents listing there top 3 most important options and the rest are left blank.
If anyone can help me figure out a way to potentially summarize this in a pivot table that would be great.
You're data is in a crosstab. Pivot's don't like that kind of layout. You need to unpivot your data.
If you've got the PowerQuery add-in installed (or have Excel 2016 or Excel/Office 365 subscription) then you can use PowerQuery to do this. Google "PowerQuery" and "Unpivot" and you'll turn up a whole heap of videos.
Otherwise you can use VBA such as my Unpivot routine I've previously blogged about at http://dailydoseofexcel.com/archives/2013/11/21/unpivot-shootout/
As always it depends what questions you want to ask in your analysis. Here are two suggestions.
What are the commonest first/second/third choices?
This assumes that the ranking is important, i.e. the first choice is ranked significantly higher than the second choice, so you want to analyse them separately.
You could add three extra columns to your data using this formula to convert the first choice to a single variable with 11 categories
=IFERROR(MATCH(COLUMNS($A:A),$A3:$K3,0),"")
in L3 and likewise with the second and third choices in M3 and N3.
in the event that a respondent (row) has less than three choices, it will give a blank for the second and/or third choice.
What are the commonest choices regardless of ranking?
This assumes that the ranking isn't so important - you just want to know which columns have been picked overall.
=INDEX($L$3:$N$10,INT((ROWS($1:1)-1)/3)+1,MOD(INT(ROWS($1:1)-1),3)+1)
In N3. This would have to pulled down for 3N rows, where N is the number of rows in the original dataset.
Then it would be a simple case of setting up pivot tables or charts for the four new variables.
I'm trying to analyze a set of data across 3 excel tables in Tableau.
When I just use 1 table (transactions) the data is correct and works normally, however when I make a connection, it seems like Tableau takes the originally correct data and deletes/duplicated entries seemingly at random (I've looked for patterns to see what the problem is, can't find them).
Here are some screenshots to illustrate the problem. I'm using inner joins. The tables I'm joining should have no impact on the data that I'm currently talking about.
This is a large data set (> 400,000 rows)
Correct Data:
From Excel, ordered by date
Tableau's Data Set (notice the missing entries (PK field) and incorrect order despite order by date)
Looking at PK and Distribution Amount
This is my first time using stackexchange so I apologize if I breached any kind of etiquette requirements! Any suggestions as to how to correct the data set tableau is detecting would be extremely helpful!
EDIT: Also, going deeper into the bad data it seems as though even when sorted chronologically the data in tableau is not in the correct order
I am trying to figure out how to create the most useful PivotTable for a user to view data for BI purposes. Here are two options I was considerating:
(1) Traditional PivotTable, pivot values on top:
(2) Drill-down type PivotTable:
What are the pros and cons of each method? For example, one for each to start might be:
Drilldown
PRO: trivial to add additional drilldown variables.
Pivot:
PRO: can easily sort by the column headers in the table UI.
And, are there any other possible tabular displays of data, either another type of PivotTable or another type altogether?
I'll suggest to keep it simple. If the objective is to present a view of the revenue figures of each region summarized by gender then pivot table in option 1 is the most effective of both, as it shows everything relevant in one simple look, keeping similar data at the same level making easier to compare.
Bear in mind that management requested that view to be able to effectively see how each region is performing on that specific category.
If the focus is revenue by different gender. Option 1 shows that in same row continuously for each region. It can easily be seen that the best performer on revenue generated by females is US, while best performer on revenue generated by males is Canada. While is not easy to see that in option 2.
If the focus is revenue by same gender. Option 1 shows that in same column continuously, which is not the case with option two.
Option 2 will be useful if the primary focus is set on revenue by region then if there is a need to see additional details based on the performance of any region management can drilldown to see the details of what makes the primary number. Which in this case is not the objective as the request is to show both.
Also best advice is to always agree requirements with clients (internal and/or external) you might find that they might have requested only what they believe it is possible to achieve and after they have that they will apply some "manual steps" to achieve their ultimate goal, something you could have done entirely if only you would have known.
Pivot Tables are used to -
summarize data
analyze data
explore data
present summary data
Both ways (traditional and drill down) of Pivot table can do the above listed.
It depends on what you want to achieve in BI.
If detailed data is not required to show or sort then you can use drill down.
Mostly in BI, data used in summarised form. So Drill down method will be good for display of data. Anyways you can double click and see the detailed data. See how to get details of drill
Drill Down:
a. Pros
Summarise Easily
Add sub points for summary
"Get Details" of Pivot for more details
b. Cons
The way you are doing sorting by pivot is not possible. Instead I would suggest to use pivot to drill down. So you can sort (And will move to Pros section :P) and check pivot details in another form.
Traditional Way
This way you are making to use pivot tables of your data. You should explore more in given links below.
5 pivot tables you probably haven't seen before
pivot tables save your job
23 things you should know about Excel pivot tables
Generally every representation of data has a purpose and with this purpose there come certain advantages and disadvantages.
Obviously with any kind of report, the audience matters most. Which would put you in the classical Requirement Analysis situation where you need to figure out what your customer wants (What data is of interest? How should it be sliced? What medium is it consumed on?)
Is the Revenue by Gender an important KPI?
If it is not, why including it at all?
If it is, let's see what a potential reader would do to answer a question like "How does the womens sale for Mexico compare with Canada?"
Drill down table:
Understanding the table will take a couple of second since they have to understand the different levels and their representation, the meaning of the bold and regular lines and realize that the man and women values accumulate to the total value for a region
Find Mexico in the list
Find the row for women and the value of it on the right
Find Canada in the list
Find the row for women and the value of it on the right
Remember the the value for Mexico or look it up again
Important here is also that this process will be repeated more or less exactly for every follow up question.
Traditional table
Understanding the table will be faster, they see a country name on the left and male/female on the top. Generally people are used to these tables since primary school and won't need further explanation.
Find Mexico in the list, go to the right until they find the value for women (if you try it you will see that you automatically see the values and the heading)
Find Canada in the list, (realize that it is only one line above) go to the right and have both values on top of each other.
For all the following questions the structure is easy to remember and it's a find and match game between rows and columns
I know that might be a bit subjective, but I hope the general idea is understandable
If you know have a question like "In which region do we sell more to men than women?" the advantage of a traditional over a drill down table becomes even more obvious.
With the drill down you will have to juggle several rows and their values while with the traditional you just skim through one column and look for the biggest value.
Is the Revenue per Region the main KPI?
You should then rather use a drill down table, possibly with additional levels (ie. North America in case it's international data or US State since I would assume it would be of interest if your product sells better in Alaska than Florida).
Your audience can then decide which granularity they want to see and adjust it accordingly. The gender is on the bottom of the hierarchy so either you have curious people who are interested in just another figure or they don't care and just don't drill down that deep.
The assumption here is that you deliver the table on the highest aggregate level.
One could argue that the same problem of finding row etc. exists as well for this case but I would assume you wouldn't necessarily compare the sales for Yucatán with Alberta so you stay in one group of states for example and again just have to skim up or down to find the states of the same country so you can compare it.
Using drilldowns in pivot tables is, in my opinion, a tool to be used by analysts, and not managers. Pivot tables are not quite intuitive enough to be used on reports that are being sent on for BI review by management. Typically any report which is being circulated for review by the powers that be should be consistent from user to user. That means using drilldowns would display different numbers if different items are selected - which could lead to 2 people talking about different values without knowing it.
Many people in management level positions outside of the core analytical group will still print anything you e-mail them before they look at it. I suspect that this is more likely to be true in a less technologically advanced company (ie: one which uses Excel as its database analysis tool instead of a full ERP-type system). In either case, anything being submitted for high level review should already be formatted exactly as you want them to see it.
The key in Excel deliverables within the workbplace is to make review as easy as possible. That means all necessary information should be immediately visible on each tab, with a minimum of scrolling (maybe scrolling down if necessary, but never scrolling right), and absolutely no clicking required.
Conclusion - Do not force a reviewer to manipulate your Excel file to use it
You may like drilldowns because you see how powerful it is to adjust reports as you are analyzing data - but once you have made your own analytical conclusions, those conclusions should be immediately apperent from the visible workspace that you leave for review.
Therefore, in order to achieve simplicity in high level review documents, you should use the 'traditional' format as you have shown it, which shows all numbers next to eachother in an easy to read table.
I have several documents which contain statistical data of performance of companies. There are about 60 different excel sheets representing different months and I want to collect data into one big table. Original tables looks something like this, but are bigger:
Each company takes two rows which represent their profit from the sales of the product and cost to manufacture the product.I need both of these numbers.
As I said, there are ~60 these tables and I want to extract information about Product2. I want to put everything into one table where columns would represent months and rows - profit and costs of each company. It could be easily done (I think) with INDEX function as all sheets are named similarly. The problem I faced is that at some periods of time other companies enter the market:
Some of them stay, some of them fail. I would like to collect information on all companies that exist today or ever existed, but newly found companies distort the list (in second picture we see, that company BA is in 4th row, not BB). As row of a company changes from time to time, using INDEX becomes problematic, because in some cases results of different companies get into one row. Adjusting them one by one seems very painful.
Maybe there is some quick and efficient method to solve such problem?
Any help or ideas would be appreciated.
One think you may want to try is linking the Excel spreadsheets as tables in Access. From there you can create a query that ties the tables together. As data changes in the spreadsheets, the query will reflect those changes.