Tags: INDEX

Determine the most recent status after satisfying certain conditions

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Assume a three column dataset with Patient ID, Smoking Status and Review Date

PatientID SmokingStatus ReviewDate
P1 10-03-2018
P1 9 09-03-2018
P1 1 08-03-2018
P1 4 07-03-2018
P2 9 10-03-2018
P2 9 09-03-2018
P2 9 08-03-2018
P2 9 07-03-2018
P3 2 10-03-2018
P3 09-03-2018
P3 9 08-03-2018
P4 9 10-03-2018
P4 1 09-03-2018
P4 4 08-03-2018

The objective is the create another 3 column dataset with the following conditions:

  1. If the patient's latest smoking status is other than Blank or 9, then consider that as the smoking status of the patient; and
  2. If the patient's latest smoking status is blank or 9, then consider the previous smoking status that is not blank or 9; and
  3. If the patient's smoking status is blank or 9 on all dates, then consider the smoking status as 9

The expected result is:

PatientID Last date when the smoking status was other than 9 or Blank Smoking status on that date
P1 08-Mar-18 1
P2 10-Mar-18 9
P3 10-Mar-18 2
P4 09-Mar-18 1

I have solved this question using 3 methods - PowerPivot, Advanced Filters and formulas.  You may download my solution workbook from here.

Return the specific product which satisfies the user defined feature combination

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Here is a simple matrix like data layout which shows the features available in every product.  Let's assume that this data is in range A2:E8 (including the header row)

Functions Product A Product B Product C Product D
Function 1 x
Function 2 x x
Function 3 x x x
Function 4 x x
Function 5 x x
Function 6 x

Here is a user created input table of his/her requirements.  Let's assume that this data is in range A12:B18 (including the header row)

Functions Input
Function 1
Function 2 x
Function 3 x
Function 4
Function 5 x
Function 6

The expected result is the "Product" which meets the user defined function combinations. The result should be Product B. If there are different products which meet the user's requirements, only the first one will be returned as a result. If one would like all products to be returned, the one can use Power Query to resolve this problem.

=IFERROR(INDEX($B$2:$E$2,1,MATCH(COUNTA($A$13:$A$18),MMULT(1*(TRANSPOSE(B3:E8=B13:B18)),1*(ISNUMBER(ROW(INDIRECT("1:"&COUNTA($A$3:$A$8)))))),0)),"No such product")

Please note that this is an array formula so please confirm the formula with Ctrl+Shift+Enter.

Return best possible fit, to manually entered dimensions, with the intent to minimise wastage

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Refer to a simple 5 column representative inventory dataset of a Glass manufacturer:

Model Length (MM) Wide (MM) Thk (MM) CAT
HX9-G-ARD 1071 273 3.5 A
MYP-G-3RD 580 535 3.2 B
EPO-G-3RD 580 535 3.2 A
MYG-G-3R 966 350 3.2 A
MYN-G-3RD 649 530 3.2 A
GM SPIN-G-3FD 882 395 3.2 A
MY8-G-AR 880 400 3.5 B
GM2-G-AR 880 400 3.5 A

From this inventory data, one has to furnish customer orders based on specific dimensions demanded by them.  A typical Customer request would be to supply glass sheets as per the following dimensions

Length (MM) Wide (MM) Thk (MM) CAT
780 542 3.5 A

The firm may or may not have glass sheets of this specific size.  The objective is to identify glass sheets, from the inventory on hand, which match customer specifications.  If there is no exact match, then one must be able to obtain all inventory items which have the same Thk (MM) and CAT as the customer specified dimensions but the Length and thickness should be more than equal to the customer specified dimensions.  The length and width can then be trimmed to match the exact customer dimensions.  Furthermore, the result returned should:

  1. List only the Top 30 glass sheets available in inventory; and
  2. List those Top 30 glass sheets in ascending order of wastage (wastage caused when the glass sheet is trimmed to match the customer specified dimensions)

You may refer to my solution in this workbook.  I have shared two solutions - one using Excel formulas and the other using Power Query a.k.a. Get and Transform in Excel 2016.  Please read the Comments in cells F1, J9 and J16 of the "Solutions" worksheet.  The difference between the 2 solutions is:

  1. Formula driven solution - This is in range J10:AM14 of the Solutions worksheet.  This is a semi dynamic solution (as compared to the Power Query solution).  To get the models in ascending order of wastage, one will have to create an Area column in the base data and sort that column in ascending order.
  2. Power Query solution - This is in range J17:AM21 of the Solutions worksheet.  This is a dynamic solution.  Just change the customer specified dimensions in range G2:J2 of the Data and Query worksheet.  Thereafter just right click on any cell in the range below and select refresh.

Compute potential Sales of a retail outlet

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The objective is to assist a Store Manager with computing potential sales across different products and colours.  To start with let's assume two datasets:

1. Customer-Colour dataset - a two column table which lists down the colour preference of each customer; and
2. Colour-Product-Price dataset - a three column table which lists down the multiple products associated with each colour and the associated prices

My objective is to compute the "Potential Sales" if each customer buys one unit of each colour of each product.  While this can be resolved by using formulas (see Formula solution worksheet of the workbook), I'd like to resolve this problem with the help of the Power Query and PowerPivot tools.

The initial challenge will be to establish a relationship between the two tables because one cannot establish Many to Many relationships in a PowerPivot.  The two tables above are a perfect example of Many to Many relationships because each customer likes multiple colours and each colour is associated with multiple products.

You may download my solution workbook from this link.

You may also view a short video of my solution here:

Auto detect sum range when copying and pasting

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Assume a simple two column data range as follows:

Product Amount
A 1
S 2
D 3
E 4
Product A
F 5
G 6
R 7
Product B
q 8
w 9
s 10
d 11
c 12
v 13
b 14
Product C

In the table above, one may want to compute the Product wise revenue.  Since the number of items falling in every product is different, one cannot copy and paste the SUM function from one product to another.  So one can adopt any one of the following two approaches:

1. Write the SUM function thrice; or
2. Use the short cut key for adding.  Here is the process (please note that this process will only work when there are no blank cells in the second column.  If there are blank cells, then the process mentioned below can be modified to still get the desired result):

a. Select range B2:B18
b. Press Ctrl+G > Special > Blanks > OK
c. Press Alt+= (this is the short cut key to generate the SUM function)

Now consider a different scenario.  Assume that the two column data range has the summarization row at the top of each Product block (rather than at the bottom as in the table above)

Product Amount
Product A
A 1
S 2
D 3
E 4
Product B
F 5
G 6
R 7
Product C
q 8
w 9
s 10
d 11
c 12
v 13
b 14

The second method described above will not work in this case because the Alt+= shortcut key only identifies thr range above or to the left.  To solve this problem, we need to write a formula for Product A which when copied down will auto adjust the range height.

You may refer to my solution in this workbook.  I have discussed two variants of the table above.

Extract City, State and Pin code from an address string

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For a lot of Excel users, a common problem is to extract City, State and Pin Code from an address string.  What compounds the issue is that there is no standardisation in an address string.  For e.g., one may end the address with a Pin code, while others may end it with a State and Country.  Some other variations could be:

1. End the address with Contact Numbers
2. There are no spaces between City, State and Pin code

There are of course many other variations which are possible and the sheer number of these variations makes it difficult to list down all of them.

Here is an example of address strings from where the State, City and Pin code need to extracted in three columns:

1. F-45, Pocket 1, Sector 198, Noida - 201303, Uttar Pradesh, India
2. S-45/B, Pocket 1-C, Phase II, Sector 189, Gurgaon, Haryana - 122002
3. RR-45/B, Pocket II-S, Cross 2, Noida - 201303, India
4. T-45, Sector 198, Lucknow - 226001, Uttar Pradesh, India
5. V-45(A), Sector 193C,Allahabad-211002 Uttar Pradesh India
6. V-45(A), Sector 193C,Allahabad-211002Uttar PradeshIndia

You may refer to my solution in this workbook.

Prioritise investment liquidation to minimise Capital Gains

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Assume a five column dataset with the Fund Name in column A, Market Value in column B, Gain/Loss in column C, Gain/Loss % in column D [column C/column B] and Type of investment in column E (Short term or Long term).  Since multiple investments can be made in one fund, there can be multiple line items for with the same Fund Name (with different market values).  Let's call this dataset the Investment schedule.

The objective is to determine the following:

a. Minimum total gain realised from sale of one/multiple funds; and
b. Short term gain present in a above; and
c. Total Long term gain realised from sale of one/multiple funds; and
d. If Long term investments fall for liquidating the particular fund, then how much is the gain/loss by forcible liquidating the short term investments.

You may refer to my solution in this workbook.

Consider a Pivot Table Value field column as a criteria for computing another Value Field column

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Assume a simple three column dataset showing hours worked by different machine on different dates.  So column A is Date, column B is Machine Name and column C is hours worked.  There are duplicates appearing in column A and B .  Blanks in column C depict machine idle time.

The task is to create a simple three column dataset showing all unique Machine names in the first column, Last day on which the machine worked in the second column and hours worked on the last day in the third column.

This problem can be solved by using formulas (Refer first worksheet of the workbook) but if one has to use a Pivot Table, then there would be a few problems.

1. The Grand Total for the Date Field should be blank because on cannot determine the Last day on which the machine worked across different machine types.  A conventional Pivot Table shows the Maximum of all dates appearing in the Date Field.

2. The Grand Total for the Hours worked Field should be a summation of the total hours worked on last day across all machine types.  A conventional Pivot Table shows the Maximum of all hours worked appearing in the Hours worked Field.

3. The biggest problem of them all is that there is no way to give a criteria as the Last day for that machine for computing another Field in the Pivot Table.  Please refer the file for a better understanding.

This problem can be solved using the PowerPivot.  You may refer to my solution in this workbook.

Compute configuration count using Set Theory and Venn Diagrams

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Assume a table which lists attendees for a Company's Annual day function.  In this Table, data for every attendee is shown on a separate row so if an employee attends the function with his/her spouse and three children, then there will be 5 rows for that employee.

The question is to determine the count of the following family configuration:

1. Employees only (those who attended without spouse and children); and
2. Employees, spouse and children (Family); and
3. Employees and spouse (no children); and
4. Employees and children (no spouse)

You may refer to my solution in this workbook.  I have solved this problem using:

1. MS Excel Formulas based on Set Theory and Venn Diagram; and
2. PowerPivot

Create a Pivot Table from multiple individual ranges without using ancillary columns

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Assume that there are three separate tables showing the following information:

1. Date of visit data for visitors to a certain recreation facility.  The same visitor may visit the facility multiple times
2. Fee per visit in different cites
3. Region in which each city lies

The question is to analyse the three tables above via a Pivot Table to generate the following:

1. Region wise and visitor wise:
a.  Fee per visit
b.  Frequency of visit
c.  Revenue
2. Revenue collected by month wise and by visitor

In this workbook, I have shared two solutions:

1. PowerPivot solution - This solution answers both questions above without using any calculated/ancillary columns in the base data.  By establishing simple relationships in the PowerPivot window and by writing two calculated Field formulas, both questions above have been answered.  To use this PowerPivot solution, you need to be using the PowerPivot add-in for MS Excel.  This add-in is only available for Excel 2010 and higher versions.

2. Pivot Table solution - This solution answers both questions above by using calculated/ancillary columns in the base data.

Here's another example.  Assume a four column table showing Date of session, Client, Location and Participant Name.  Assume another four column table showing Client, Date of session, Date of invoice and Amount Billed.  The task is to determine the Amount billed per location.  You may refer to my PowerPivot and Pivot Table solution in this workbook.