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Advanced excel 01 (2)

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Advanced excel 01 (2)

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Advanced excel 01 (2)

  1. 1. Part: 01 Microsoft Advanced Excel References References (Relative, Absolute, Mixed) Naming Referring Other Sheets Useful Functions Various Functions Conditional Sum, Count, Average If – Testing Condition Lookups (HLookUp, VLookUp, Index, Match) Database Functions Data Analysis Sorting (by Characters, by Color, Custom List) Filtering (incl. Advance Filtering) Conditional Formatting Tips & Tricks Muhammad Faisal Shafi m_faisal_shafi@yahoo.com 0333-3054495 Associate member of Institute of Cost and Management Accountant of Pakistan (ICMAP), has over 10 years of experience in Audit, Accounts and CA firms. Currently he has been working with Pakistan Paper Products Limited as Head of Internal Audit since January 2011. I have delivered different courses of MS Office (incl. MS Excel upto advance level & MS Access) at Audit & Accounts Training Institute of AGPR. Conducted two workshops of two days each at ICMAP H.O. on Financial Modeling using MS Excel. With the coordination of KBC I will conduct another two days workshop on Dashboard using Excel at ICMAP H.O. in the next month. I’ve been invited as guest speaker at Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology (SZABIST) regarding a session on the topic of “Finance and Financial Analysis using MS Excel” scheduled in the next month. Join me at Xlab (Excel Lab) a facebook group at https://www.facebook.com/groups/318201971676974/ Your Trainer
  2. 2. Part: 02 Microsoft Advanced Excel Your Trainer Creating Reports Sub-Total Scenario Manager Goal Seek Data Table (One & Two Variables) Consolidation (3-D, Internal, External) Improve Visualization of Data Charts (Popular Types, Adding/ Deleting Data, Sub-chart, Secondary Axis) Pivot Tables (Basics, Filtering, Options, Grouping, Slicer) Facilitating & Restricting Users Data Validation (incl. Depended Lists) Controls (Combo Box, List Box, Check Box, Option Button, Spin Button, Scroll Bar) Automating Your Repetitive Tasks Macro (Intro, Developer Tab, Record, Run, View Code, Sort to get top 3, Methods to Call) Questions & Answers Muhammad Faisal Shafi m_faisal_shafi@yahoo.com 0333-3054495 Associate member of Institute of Cost and Management Accountant of Pakistan (ICMAP), has over 10 years of experience in Audit, Accounts and CA firms. Currently he has been working with Pakistan Paper Products Limited as Head of Internal Audit since January 2011. I have delivered different courses of MS Office (incl. MS Excel upto advance level & MS Access) at Audit & Accounts Training Institute of AGPR. Conducted two workshops of two days each at ICMAP H.O. on Financial Modeling using MS Excel. With the coordination of KBC I will conduct another two days workshop on Dashboard using Excel at ICMAP H.O. in the next month. I’ve been invited as guest speaker at Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology (SZABIST) regarding a session on the topic of “Finance and Financial Analysis using MS Excel” scheduled in the next month. Join me at Xlab (Excel Lab) a facebook group at https://www.facebook.com/groups/318201971676974/
  3. 3. References (Relative, Absolute, Mixed) Naming Referring Other Sheets References
  4. 4. Unit Price 25 OrderDate Packets Units @ Packet Total Units Total 6-Jan-13 95 10 950 23,750 23-Jan-13 50 60 3000 75,000 9-Feb-13 36 100 3600 90,000 26-Feb-13 27 12 324 8,100 15-Mar-13 56 100 5600 140,000 1-Apr-13 60 12 720 18,000 18-Apr-13 75 12 900 22,500 5-May-13 90 12 1080 27,000 22-May-13 32 100 3200 80,000 8-Jun-13 60 10 600 15,000 25-Jun-13 90 60 5400 135,000 12-Jul-13 29 10 290 7,250 29-Jul-13 81 100 8100 202,500 15-Aug-13 35 12 420 10,500 1-Sep-13 2 12 24 600 18-Sep-13 16 60 960 24,000 5-Oct-13 28 10 280 7,000 22-Oct-13 64 100 6400 160,000 8-Nov-13 15 10 150 3,750 25-Nov-13 96 10 960 24,000 12-Dec-13 67 60 4020 100,500 29-Dec-13 74 100 7400 185,000 15-Jan-14 46 12 552 13,800 1-Feb-14 87 60 5220 130,500 18-Feb-14 4 10 40 1,000 7-Mar-14 7 100 700 17,500 24-Mar-14 50 10 500 12,500 10-Apr-14 66 60 3960 99,000 27-Apr-14 96 10 960 24,000 14-May-14 53 100 5300 132,500 31-May-14 80 12 960 24,000 17-Jun-14 5 10 50 1,250 4-Jul-14 62 10 620 15,500 21-Jul-14 55 60 3300 82,500 7-Aug-14 42 100 4200 105,000 24-Aug-14 3 12 36 900 10-Sep-14 7 60 420 10,500 27-Sep-14 76 10 760 19,000 14-Oct-14 57 100 5700 142,500 31-Oct-14 14 10 140 3,500 17-Nov-14 11 60 660 16,500 4-Dec-14 94 10 940 23,500 21-Dec-14 28 100 2800 70,000 Rel. Ref. =B3*C3 Abs. Ref. =B3*C3*$G$1 Estimates of sales (quantity) for the year of 2015 Estimated contribution rate 20% 30% 10% 40% Month Units Sold Doug Dave Brian Larry January 720 144 216 72 288 February 900 180 270 90 360 March 1,080 216 324 108 432 April 3,200 640 960 320 1,280 May 600 120 180 60 240 June 5,400 1,080 1,620 540 2,160 July 552 110 166 55 221 August 5,220 1,044 1,566 522 2,088 September 40 8 12 4 16 October 700 140 210 70 280 November 500 100 150 50 200 December 3,960 792 1,188 396 1,584 Total 22,872 4,574 6,862 2,287 9,149 Mixed Ref. =$J4*K$2 References (Relative, Absolute, Mixed)
  5. 5. Naming Name Rules: • Names Must Not Exceed 255 Characters • Cell Names Are Not Allowed To Contain Spaces • Excel Does Not Distinguish Between Capital Letter and Lower Case • Cell Names Must Be Unique and Must Not Resemble a Number, Cell Address Or Reserve Word • A Cell Name must start with a Letter, or an Underscore
  6. 6. ='Jul-Dec'!D2+'Jan- Jun'!D2 Sheet to be summarized by taking data from other two sheets =SUM('Jul-Dec'!D2,'Jan- Jun'!D2) Referring Other Sheets
  7. 7. External Link: (Link to another excel workbook) Source file: Module 3 - Inter Ex Data Target file: Module 3 When source file is open ='[Module 3 - Inter Ex Data.xlsx]Jul-Dec'!$C$4 When source file is close ='D:HOIAInternal AuditAll About ExcelExcel PracticeDeliverablesBasics to Inter[Module 3 - Inter Ex Data.xlsx]Jul-Dec'!$C$4 Edit Links: Referring Other Sheets
  8. 8. Hyper Link: (Internet type link) Shortcut key to call this dialogue box is Ctrl + K Referring Other Sheets
  9. 9. Useful Functions Various Functions Conditional Sum, Count, Average If – Testing Condition Lookups (HLookUp, VLookUp, Index, Match) Database Functions
  10. 10. Various Functions Days
  11. 11. 1 2 3 4 5 6 1 2 3 4 5 6 Various Functions
  12. 12. Various Functions
  13. 13. =LEFT(B80,FIND("- ",B80)-1) =RIGHT(B80,LEN(B80)-FIND("-",B80)) Concatenate function may be replaced with “&”, however be careful that this symbol is to be placed at each join as well as take care of using “” around adding string value w/o any reference. =CONCATENATE(D80,"-",E80) OR =D80&"-"&E80 Various Functions
  14. 14. Today Now Day Month Year =CHOOSE(WEEKDAY(B99),"Sunday","Monday","T uesday","Wednesday","Thursday","Friday","Saturda y") =SUMPRODUCT (D103:D107,E103 :E107) =REPLACE(B113,7,5,"Fres h") =SUBSTITUTE(B113,"Leave","Fre sh") Various Functions
  15. 15. Depreciation Methods SLN : Straight Line Method SYD : Sum of Years Digits Method DB : Declining Balance Method =SLN($D$121,$D$123,$D$12 2) =SYD($D$121,$D$123,$D$122,E127 ) =DB($D$121,$D$123,$D$122,E127) Various Functions
  16. 16. Syntax: • Abs(Number) Abs = Absolute • Round(No., No. of Digits) • RoundDown(No., No. of Digits) • RoundUp(No., No. of Digits) • Ceiling(No., Significance) • Floor(No., Significance) • Choose(Index No., Value1, Value2,…) • Indirect(Ref) • Large(Array, K) • Small(Array, K) • Rank(No., Ref., [Order]) Order 1 for Ascending • Left(Text, [No. of Characters]) • Right(Text, [No. of Characters]) • Mid(Text, Start No., [No. of Characters]) • Len(Text) Lentgh • Rept(Text, No. of Times) Repeat • Find(Find What, Where, [Start No.]) • Search(Find What, Where, [Start No.]) Various Functions
  17. 17. Syntax: • Concatenate(Text1, Text2,…) • Upper(Text) • Lower(Text) • Proper(Text) • Today() • Now() • Day(Serial No.) • Month(Serial No.) • Year(Serial No.) • Date(Year, Month, Day) • Weekday(Serial No.) • SumProduct(Array1, Array2, …) • RandBetween(Bottom, Top) Random Between • Replace(Old Text, Start No., No. of Characters, New Text) • Substitute(Text, Old Text, New Text) • =SLN(Cost, Salvage Value, Life) • =SYD(Cost, Salvage Value, Life, Per[iod]) • =DB(Cost, Salvage Value, Life, Period, [Month]) Various Functions
  18. 18. Conditional Sum, Count, Average
  19. 19. Syntax: SumIf(Range, Criteria, [Sum Range]) CountIf(Range, Criteria) AverageIf(Range, Criteria, [Average Range]) Lets sum of transactions of “Pear” in terms of amount: 2,965 =SUMIF(A5:A26,B36,E5:E26) Lets sum of transactions of “Pear” in terms of quantity: 37 =SUMIF(A5:A26,B36,C5:C26) Lets count number of entries of “Pear”: 3 =COUNTIF(A5:A25,B31) Lets average of transactions of “Pear” in terms of amount: 988.33 =AVERAGEIF(A5:A26,B31,E5:E26) Lets average of transactions of “Pear” in terms of rate: 81.67 =AVERAGEIF(A5:A26,B31,D5:D26) Criteria may also be as “Pear” Conditional Sum, Count, Average
  20. 20. Lets Sum of quantity where quantity is 12: 36 =SUMIF(C5:C25,12) Lets Sum of amount where amount is greater than 2000: 13,040 =SUMIF(E5:E25,">2000") Lets Sum of amount where quantity is more than 10: 22,266 =SUMIF(C5:C25,">10",E5:E25) ? ? ? ? 6,310 3 2,875 155 Conditional Sum, Count, Average
  21. 21. Copy(abovedataofCol.A) PasteSpecialValues Selectanycell(e.g.A57) DataRemoveDuplicates Now we are going to make a list of items because in our database there are some items entered more than once. Conditional Sum, Count, Average
  22. 22. Listofonlyunique entries Listaftersorting (Asc.) Be careful about referencing; match total of summary with original database. =SUMIF($A$5:$A$25,$A57,$E$5:$E$25) =SUMIF($A$5:$A$25,$A57,$C$5:$C$25) Conditional Sum, Count, Average
  23. 23. =SUMIF($D$4:$D$17,A2 1,$C$4:$C$17) =COUNTIF($D$4:$D$17,A21) =SUMIF($B$4:$B$17,A2 7,$C$4:$C$17) =COUNTIF(B4:B17,A27) Conditional Sum, Count, Average
  24. 24. =D4*Norma l =SUMIF(B$4:B4,B4,E$4: E4) Running Total of Order 16,956,238 =SUMIF(A2:A7,"<4-1-13",B2:B7) 17,344,335 =SUMIF(A2:A7,">4-1-13",B2:B7) Go to better Conditional Sum, Count, Average
  25. 25. =SUMIF(E137:E149,">0") =ABS(SUMIF(E137:E149,"<0")) =SUMIF(B120:B132,"<>Punj ab",C120:C132) Conditional Sum, Count, Average
  26. 26. =MONTH(B171) =B$168&"-"&F171&"- "&COUNTIF(F$171:F171,F1 71) 1 2 =SMALL(D171:D183,COUNTIF(C171:C183,"" )+1) 3 =SMALL(D171:D183,COUNTIF(D171:D183,0) +1) 4 Conditional Sum, Count, Average
  27. 27. If – Testing Condition =IF(B2>C2, "Yes", "No") Alternatively: =IF(E2>1, "Yes", "No") Syntax: IF(logical_test, [value_if_true], [value_if_false]) =IF(E19>0,C19*0.01, 0) Alternatively =IF(C19>D19,C19*0.01, 0)
  28. 28. =IF(E39<=35,E39 *D39,35*D39) =IF(E39<=35,0,(E3 9-35)*D39*1.5) =IF(B39>C39,(B39- C39)*5%,0) Alternatively: =MIN(E39,35)*D3 9 Alternatively: =IF(E39>35,(E39- 35)*D39*150%,0) Alternatively: =MAX(B39- C39,0)*5% If – Testing Condition
  29. 29. =IF(C55<=DATE(2000,1, 1),"AWARD","NO AWARD") Alternatively: =IF(C55<=36526,"AWAR D","NO AWARD") If – Testing Condition
  30. 30. =IF(F5>=60,"Pass","Fail") =IF(AND(G5="Pass",L5="Pass",Q5="Pass"),"OK","Not OK") =IF(OR(B5>80,R5="OK"),"ALLOWED", "NOT ALLOWED") If – Testing Condition
  31. 31. If – Testing Condition
  32. 32. =IF(C109>=15,10%*B109,IF(C109>17,13 %*B109,IF(C109>19,20%*B109,8%*B109 ))) =IF(C109>=15,12%*B109,IF(C109>17,15 %*B109,IF(C109>19,22%*B109,10%*B1 09))) =IF(AND(C109>=15,D109="F",OR(E109="KORANGI",E109="LANDH I",E109="STEEL TOWN")),30%*B109,IF(C109>19,35%*B109,20%*B109)) =IF(C109>=19,"MANAGER",IF(C109>=17,"DEP.MAN AGER","CLERK")) If – Testing Condition
  33. 33. If – Testing Condition
  34. 34. =IF(F140>=30000,"A",IF(F140>=20000 ,"B",IF(F140>=10000,"C","D"))) =IF(F140>=25000,"Good",IF(F140>=150 00,"Fair","Poor")) =IF(AND(B140>=5000,C140>=5000,D140>= 5000,E140>=5000),"A","B") =IF(OR(B140>=5000,C140>=5000,D140>=5 000,E140>=5000),"A","B") If – Testing Condition
  35. 35. If – Testing Condition
  36. 36. =IF(AND($C167>=1,$C167<31),$D167,0) =IF(AND($C167>30,$C167<91),$D167,0) =IF(AND($C167>90,$C167<181),$D167,0) =IF($C167>180,$D167,0) =SUM(F167:H167) If – Testing Condition
  37. 37. =IF(J196>=$B$214,$C$214,IF(J196>=$B$213,$C$213,IF(J196>=$B$212, $C$212,IF(J196>=$B$211,$C$211,IF(J196>=$B$210,$C$210,$C$209))))) =IF(K196=$C$214,$F$209,IF(K196=$C$213,$F$210,IF(K196=$C$212 ,$F$211,$F$212))) Go to better If – Testing Condition
  38. 38. =IF(J196>=$B$214,$C$214,IF(J196>=$B$213,$C$213,IF(J196>=$B$212, $C$212,IF(J196>=$B$211,$C$211,IF(J196>=$B$210,$C$210,$C$209))))) =IF(MIN(C196,D196,E196,F196,G196)>=40,IF(J196>=$B$214,$C$214,IF( J196>=$B$213,$C$213,IF(J196>=$B$212,$C$212,IF(J196>=$B$211,$C$211, IF(J196>=$B$210,$C$210,$C$209))))),"Fail") If – Testing Condition
  39. 39. =IF(ISBLANK(B2 19),"",COUNTA(B $219:B219)) =IF(AND(ISBLANK(F220),ISBLANK(G220)),"",H219+F220-G220) =IFERROR(K219 /L219,0) If – Testing Condition
  40. 40. =IF(ISBLANK(D235),"Enter your name please: ","Welcome: "&D235) Spac e =IF(ISTEXT(H235),"","Enter a valid class Name:") =IF(ISNUMBER(H237),"","Enter a valid Roll No.") =IF(H239=H235&"."&H237,"","Enter a valid Code:") If – Testing Condition
  41. 41. =IF(AND(ISBLANK(M235),ISBLANK( M237)),"",M235&"_"&M237) =IF(OR(M235=T235,M235=T236,M235=T237,M235=T238,M235=T239,M 235=U235,M235=U236,M235=U237,M235=U238,M235=U239),"","Enter a valid Class Name:") =IF(AND(M237>0,M237<100),"" ,"Enter a valid Roll No.") =IF(OR(ISBLANK(M235),ISBLANK( M237)),"Enter valid Class Name and Roll No.",IF(EXACT(M239,U240),"","Enter a valid Code:")) If – Testing Condition
  42. 42. =IF(COUNTIF(A$245:A245,A245)<2, SUMIF(A$245:A245,A245,D$245:D245),0) =IF(COUNTIF(B$245:B245,B245)>1,"",1+MAX(G$244:G244)) Back to simple If – Testing Condition
  43. 43. Lookups (HLookUp, VLookUp, Index, Match) =VLOOKUP(J3,$B$16:$C$21,2) =VLOOKUP(J3,$B$16:$D$21,3) =IF(MIN(C3,D3,E3,F3,G3)>=40,VLOOKUP(J3,$B$16:$C$21,2), "Fail") Back to simple
  44. 44. Lookups (HLookUp, VLookUp, Index, Match) Dept =VLOOKUP(A28,Dept,2,FAL SE)
  45. 45. Lookups (HLookUp, VLookUp, Index, Match) Stoc k =VLOOKUP(A51,Stock,2,FALSE) =VLOOKUP(A51,Stock,5,FALSE)
  46. 46. Lookups (HLookUp, VLookUp, Index, Match) =VLOOKUP(B59,$E$ 59:$H$67,4)*B59
  47. 47. Lookups (HLookUp, VLookUp, Index, Match) =VLOOKUP(B90,$B$74:$D$86,3) =LOOKUP(B90,$B$74:$C$86,$D$74:$D$86) Syntax: Vlookup(Lookup Value, Table Array, Column No., [Range Lookup]) Lookup(Lookup Value, Lookup Vector, [Result Vector])
  48. 48. Lookups (HLookUp, VLookUp, Index, Match) =HLOOKUP(C102,$B$98:$N$100,3) =LOOKUP(C102,$B$98:$N$99,$B$100:$N$100) Syntax: Hlookup(Lookup Value, Table Array, Row No., [Range Lookup]) Lookup(Lookup Value, Lookup Vector, [Result Vector])
  49. 49. Lookups (HLookUp, VLookUp, Index, Match) Look horizontally (row) =MATCH("Product",L2:O2) 2 Look vertically (column) =MATCH("Plum",M3:M7) 2 =MATCH("Plum",M2:M7) 3 Arranged Ascending =MATCH(10573,L3:L7) It took Match Type as Exact =MATCH(10572,L3:L7) It took Match Type as Less Than =MATCH(10572,L3:L7,1) Match Type Less Than given by user =MATCH("Orange",M3:M7) It took Match Type as Exact =MATCH("Peach",M3:M7) Wrong result because it is neither ascending nor descending =MATCH("Peach",M3:M7,0) Match Type Exact given by user Match =MATCH("*ple",M3:M7,0)  1 =MATCH(MAX(N3:N7),N3:N7,0)  2 Right result, by using Match Type to Exact =MATCH(LARGE(N3:N7,2),N3:N7,0)  3 Right result, by using Match Type to Exact
  50. 50. Lookups (HLookUp, VLookUp, Index, Match) =INDEX(V3:V7,3) Single Column therefore only Array and Row No. are enough =INDEX(V3:Y7,3,0) Error because row number is not right =INDEX(V3:Y7,3,1) All arguments given =INDEX(V3:Y3,,2) Single Row therefore row reference may be skipped =INDEX(V3:Y7,,2) Product got from the row where function applied while we wish to get first row’s product =INDEX(V3:Y7,1,2) All arguments given =INDEX(V3:Y7,MATCH(W13,W3:W7,0),4) Match will give row No. according to what has been entered at W13 (exact match) in turn index will return respective quantity being 4th column =INDEX(V3:Y7,MATCH(W17,W3:W7,0),3) List of Data Validation has been applied at W17 to restrict user to select between available list; index will return unit price being 3rd column Index
  51. 51. Database Functions Type Date Invoice Name Amount Level 1 28-Jan-11 595 Poole 8,000.00 Level 1 3-Feb-11 600 Davis 6,000.00 Level 1 17-Feb-11 602 Crowther 7,000.00 Level 1 17-Feb-11 603 Maze 4,000.00 Level 1 18-Feb-11 605 Park 1,000.00 Level 1 24-Feb-11 606 Waterson 6,000.00 Level 1 24-Feb-11 607 Dune 6,000.00 Level 2 19-Jan-11 591 Bryant 34,970.00 Level 2 21-Jan-11 596 Carver 34,545.45 Level 2 25-Feb-11 592 Blythe 25,196.36 Level 2 28-Feb-11 569 Porter 24,913.64 Level 2 28-Feb-11 594 Blair 7,000.00 Level 2 10-Mar-11 611 Boyden 14,545.45 Level 2 21-Mar-11 614 Hayden 17,943.64 Level 2 31-Mar-11 546 Wilson 32,036.36 Level 3 9-Mar-11 610 Dune 84,200.00 Level 4 10-Mar-11 611 Bryant 77,258.18 Level 8 14-Feb-11 575 Constable 8,015.91 Level 8 4-Mar-11 608 Constable 27,272.73 Level 1 6-Apr-11 616 Stuart 6,000.00 Level 2 6-Apr-11 611 Bryant 14,545.45 Level 3 14-Apr-11 618 Hayden 36,533.64 Level 3 24-Apr-11 621 Polter 46,845.45 Level 4 6-Apr-11 611 Blair 77,258.18 Level 4 7-Apr-11 617 Dune 20,719.09 Level 4 12-Apr-11 612 Carver 12,869.09 Level 7 24-May-11 630 Atkins 1,000.00 Level 7 30-May-11 630 Atkins 1,000.00 Level 7 30-May-11 632 Norris 1,000.00 Level 1 10-May-11 623 Arthur 7,000.00 Level 1 11-May-11 623 Arthur 7,000.00 Level 1 24-May-11 630 Atkins 5,000.00 Type Date Invoice Name Amount Level 1 30-May-11 630 Atkins 5,000.00 Level 2 9-May-11 611 Blair 14,545.45 Level 4 9-May-11 611 Blair 77,258.18 Level 4 19-May-11 627 Hayden 10,023.64 Level 4 20-May-11 627 Hayden 10,023.64 Level 4 24-May-11 626 Wilson 11,909.09 Level 4 27-May-11 625 Blythe 18,946.36 Level 6 23-May-11 628 Craig 707.27 Level 6 23-May-11 629 Polter 126.00 Level 8 2-May-11 608 Craig 27,272.73 Level 8 18-May-11 586 Howard 18,181.82 Level 8 19-May-11 586 Howard 18,181.82 Level 8 23-May-11 608 Craig 27,272.73 Level 8 24-May-11 631 Soul 5,000.00 Level 8 26-May-11 586 Simpson 18,181.82 Level 1 12-Jul-11 653 Roberts 6,000.00 Level 1 22-Jul-11 658 Murray 6,000.00 Level 1 25-Jul-11 658 Murray 6,000.00 Level 4 20-Jul-11 654 Peterson 9,711.82 Level 6 5-Jul-11 646 Barney 2,660.00 Level 6 20-Jul-11 657 Boyden 2,516.36 Level 6 20-Jul-11 657 Boyden 649.09 Level 9 20-Jul-11 652 Soul 35,201.82 Level 9 22-Jul-11 652 Soul 35,201.82 Level 9 26-Jul-11 652 Soul 35,201.82 Level 5 6-Jul-11 648 Simpson 18,181.82 Level 5 25-Jul-11 659 Davis 10,909.09 Level 7 8-Jun-11 630 Atkins 1,000.00 Level 1 8-Jun-11 630 Atkins 5,000.00 Level 1 17-Jun-11 636 Martin 4,000.00 Level 1 20-Jun-11 642 Carter 2,000.00 Level 1 23-Jun-11 643 Carter 5,000.00 Level 6 9-Jun-11 633 Garrison 655.00 Level 5 15-Jun-11 635 Simpson 20,909.09
  52. 52. Extract from Database data of “Atkins” to prove results Syntax of DFunctions (Database, Field, Criteria) Criteria Type Date Date Name Amount Level 1 >=01/01/2011 <=03/31/2011 Level 2 >=01/01/2011 <=03/31/2011 DSUM DCOUNT DAVERAGE DMAX DMIN 229,151 15 15,277 34,970 1,000 Field: “Amount” Name Total Sales No. of Transactions Average Sale Maximum Sale Minimum Sale Atkins 18,000 6 3,000 5,000 1,000 DSUM DCOUNT DAVERAGE DMAX DMIN # Data Remove Duplicates # Validation List Type Date Invoice Name Amount Level 7 24-May-11 630 Atkins 1,000. Level 1 24-May-11 630 Atkins 5,000 Level 7 30-May-11 630 Atkins 1,000 Level 1 30-May-11 630 Atkins 5,000 Level 7 8-Jun-11 630 Atkins 1,000 Level 1 8-Jun-11 630 Atkins 5,000 Database Functions
  53. 53. Data Analysis Sorting (by Characters, by Color, Custom List) Filtering (incl. Advance Filtering) Conditional Formatting
  54. 54. Date Region Sales Rep Customer Product Sales COGS 22-Apr-11 MidWest Vivien R Yahoo WFJ Item 1,087 489 20-Jul-11 North Michael G Yahoo ZCN Item 459 430 22-Jun-11 North Hassan M Yahoo YUZ Item 143 97 29-Jul-11 NorthEast Hassan M Yahoo YCR Item 4,578 1,694 5-Dec-11 SouthEast Donald Wayne Yahoo WZQ Item 5,060 2,176 13-Oct-11 NorthEast Sarabeth L Yahoo ZBJ Item 3,296 3,082 14-Dec-11 NorthEast Anastasiya A Yahoo XLN Item 3,122 1,155 16-Jul-11 MidWest Vivien R Yahoo VGE Item 903 845 1-Feb-12 SouthEast Cherry M Yahoo ZUL Item 6,205 3,599 19-Dec-12 NorthEast Toni M Yahoo ZHN Item 3,214 1,382 12-Feb-11 West Hassan M Yahoo ZBJ Item 6,336 2,851 20-Nov-11 SouthEast Daniil N Yahoo YYC Item 5,673 3,290 9-Feb-11 West Vivien R Yahoo YRA Item 6,514 3,843 2-Apr-11 North Cherry M Yahoo YLH Item 8,135 3,498 26-Nov-11 West Barbara C Yahoo XWY Item 4,863 3,647 13-Aug-11 North Abdisamad A Yahoo XKA Item 8,088 5,500 26-Apr-11 NorthEast Dan Yahoo XDA Item 9,527 4,096 19-Aug-11 MidWest Cherry M Yahoo XAQ Item 5,932 2,669 30-Jul-11 NorthEast Abdisamad A Yahoo WYM Item 7,546 2,792 26-Oct-11 West Abdisamad A Yahoo WSV Item 9,099 6,187 27-Jun-11 NorthEast Nikol M Yahoo WPE Item 9,300 5,394 22-Oct-11 MidWest Shuting Yahoo WOW Item 3,907 1,446 5-Apr-11 MidWest Barbara C Yahoo WLI Item 4,092 2,373 18-Apr-11 North Tonya J Yahoo WKL Item 9,195 8,597 9-Sep-11 MidWest Vivien R Yahoo WIP Item 5,592 3,076 25-Jul-11 West Suzanne M Yahoo VVA Item 8,389 4,950 7-Apr-11 NorthEast Abdisamad A Yahoo VTW Item 4,899 2,204 8-Mar-11 SouthEast Barbara C Yahoo VSH Item 6,510 5,729 17-Sep-11 SouthEast Tonya J Yahoo VPC Item 6,253 3,689 18-May-11 SouthEast Tonya J Yahoo VOO Item 1,818 1,054 17-Sep-11 North Anastasiya A Yahoo VNQ Item 1,762 969 30-Aug-11 SouthEast Nikol M Yahoo UYS Item 8,209 4,844 18-Jul-11 MidWest Michael G Yahoo UXX Item 6,786 4,615 13-Jan-11 SouthEast Suzanne M Yahoo UWC Item 9,416 4,049 30-Jan-11 MidWest Daniil N Yahoo UNF Item 1,334 1,000 24-Aug-11 NorthEast Dan Yahoo UMJ Item 6,951 6,499 28-Jul-11 SouthEast Catherine W Yahoo UJQ Item 8,290 4,808 27-Apr-11 West Analyssa C Yahoo UER Item 1,283 872 12-Feb-11 West Sarabeth L Yahoo UCA Item 2,304 1,267 22-Sep-11 North Cherry M Yahoo UAL Item 9,929 5,858 Custom List: MS Office Button Excel Options Popular Edit Custom Lists Applying Custom List at Sorting: Data Sort Column; Sort On; Order (Custom List) Sorted by Font Color then by Cell Color Getting unique values Column-wise (one by one Col.) Sorting
  55. 55. Date Region Sales Rep Customer Product Sales COGS 1-Feb-12 SouthEast Cherry M Yahoo ZUL Item 6,205 3,599 12-Feb-11 West Hassan M Yahoo ZBJ Item 6,336 2,851 20-Nov-11 SouthEast Daniil N Yahoo YYC Item 5,673 3,290 9-Feb-11 West Vivien R Yahoo YRA Item 6,514 3,843 26-Nov-11 West Barbara C Yahoo XWY Item 4,863 3,647 5-Dec-11 SouthEast Donald Wayne Yahoo WZQ Item 5,060 2,176 26-Oct-11 West Abdisamad A Yahoo WSV Item 9,099 6,187 25-Jul-11 West Suzanne M Yahoo VVA Item 8,389 4,950 8-Mar-11 SouthEast Barbara C Yahoo VSH Item 6,510 5,729 17-Sep-11 SouthEast Tonya J Yahoo VPC Item 6,253 3,689 18-May-11 SouthEast Tonya J Yahoo VOO Item 1,818 1,054 Custom Filter Region Greater than “S” Date Region Sales Rep Customer Product Sales COGS MidWest >5000 Date Region Sales Rep Customer Product Sales COGS MidWest >5000 And Or Data Filter Advanced Filter List Range Criteria Range Copy to Date Region Sales Rep Customer Product Sales COGS Sales >10-31-2011 >3999 <5001 Date >10-31-2011 A valid criteria for such data Filtering
  56. 56. Customer *Mart* Wild Card (*) Product c?ke Wild Card (?) To display data where Customer name consists of “Mart” at any position To display data where Product name starts with “C” and ends with “ke” A B C D E F G OrderDate Product OrderID Shipped Customer Invoice Paid 1-Jan-02Coke 10456 1-Aug-02MegaMart 278 278 3-Jan-02Good*Eats 10457 2-Aug-02MiniMart 789 500 3-Jan-02 10458 3-Aug-02SuperMart 1,365 1,365 3-Jan-02Produce 10459 4-Aug-02Mart-o-rama 240 240 4-Jan-02Coke 10460 5-Aug-02MegaMart 1,348 1,348 11-Jan-02Produce 10461 6-Aug-02Mart-o-rama 2,023 2,023 11-Jan-02Produce 10462 7-Aug-02MegaMart 293 293 18-Jan-02Produce 10463 8-Aug-02MiniMart 1,803 1,803 20-Jan-02Coke 10464 9-Aug-02MegaMart 1,668 1,668 20-Jan-02Cake 10465 10-Aug-02MegaMart 566 566 21-Jan-02Good*Eats 10466 11-Aug-02MegaMart 422 422 21-Jan-02Produce 10467 12-Aug-02Mart-o-rama 1,336 1,336 25-Jan-02Coke 10468 13-Aug-02MegaMart 176 176 25-Jan-02Cake 10469 14-Aug-02MiniMart 870 870 26-Jan-02Cake 10470 15-Aug-02MiniMart 1,682 1,682 26-Jan-02Produce 10471 16-Aug-02MiniMart 1,704 1,704 3-Feb-02 10472 17-Aug-02SuperMart 460 460 3-Feb-02Cake 10473 18-Aug-02MiniMart 1,607 1,607 4-Feb-02Cake 10474 19-Aug-02MiniMart 1,205 1,205 7-Feb-02Coke 10475 20-Aug-02MiniMart 2,192 2,192 8-Feb-02Cake 10476 21-Aug-02MiniMart 455 455 17-Feb-02Good*Eats 10477 22-Aug-02MegaMart 1,800 1,800 17-Feb-02 10478 23-Aug-02MiniMart 2,207 2,207 22-Feb-02Good*Eats 10479 24-Aug-02MegaMart 122 122 23-Feb-02Coke 10480 25-Aug-02MiniMart 2,374 2,374 23-Feb-03Cake 10481 26-Aug-02MegaMart 1,348 1,348 28-Feb-02Coke 10482 27-Aug-02MegaMart 616 616 Filtering (Advance)
  57. 57. A B C D E F G OrderDate Product OrderID Shipped Customer Invoice Paid 1-Jan-02Coke 10456 1-Aug-02MegaMart 278 278 3-Jan-02Good*Eats 10457 2-Aug-02MiniMart 789 500 3-Jan-02 10458 3-Aug-02SuperMart 1,365 1,365 3-Jan-02Produce 10459 4-Aug-02Mart-o-rama 240 240 4-Jan-02Coke 10460 5-Aug-02MegaMart 1,348 1,348 11-Jan-02Produce 10461 6-Aug-02Mart-o-rama 2,023 2,023 11-Jan-02Produce 10462 7-Aug-02MegaMart 293 293 18-Jan-02Produce 10463 8-Aug-02MiniMart 1,803 1,803 20-Jan-02Coke 10464 9-Aug-02MegaMart 1,668 1,668 20-Jan-02Cake 10465 10-Aug-02MegaMart 566 566 21-Jan-02Good*Eats 10466 11-Aug-02MegaMart 422 422 21-Jan-02Produce 10467 12-Aug-02Mart-o-rama 1,336 1,336 25-Jan-02Coke 10468 13-Aug-02MegaMart 176 176 25-Jan-02Cake 10469 14-Aug-02MiniMart 870 870 26-Jan-02Cake 10470 15-Aug-02MiniMart 1,682 1,682 26-Jan-02Produce 10471 16-Aug-02MiniMart 1,704 1,704 3-Feb-02 10472 17-Aug-02SuperMart 460 460 3-Feb-02Cake 10473 18-Aug-02MiniMart 1,607 1,607 4-Feb-02Cake 10474 19-Aug-02MiniMart 1,205 1,205 7-Feb-02Coke 10475 20-Aug-02MiniMart 2,192 2,192 8-Feb-02Cake 10476 21-Aug-02MiniMart 455 455 17-Feb-02Good*Eats 10477 22-Aug-02MegaMart 1,800 1,800 17-Feb-02 10478 23-Aug-02MiniMart 2,207 2,207 22-Feb-02Good*Eats 10479 24-Aug-02MegaMart 122 122 23-Feb-02Coke 10480 25-Aug-02MiniMart 2,374 2,374 23-Feb-03Cake 10481 26-Aug-02MegaMart 1,348 1,348 28-Feb-02Coke 10482 27-Aug-02MegaMart 616 616 To display data where Product name is blank =ISBLANK(B2) FALSE Find Blank Top/ Bottom 10…, Above Average, and Below Average are available as built-in facility. FALSE Unmatched To display data where Paid amount differs with Invoice amount =F2<>G2 #VALUE! Find No. To display data where Order ID consists of “8” at any position =FIND(8,C2) Filtering (Advance)
  58. 58. G.R. No. Student Math English Urdu Islamiat Total %age Grade 1005 Hashim 74 42 34 96 246 62%B 1030 Bilal 47 55 99 80 281 70%A 1021 Basheer 42 40 52 91 225 56%C 1054 Javaria 78 36 66 27 207 52%Fail 1074 Bushra 42 61 51 58 212 53%C 1084 Saqib 37 31 39 107 27%Fail 1005 Rehana 73 36 54 62 225 56%C 1065 Mubashir 42 47 52 40 181 45%D 1036 Waqar 41 61 91 78 271 68%B 1043 Khalid 78 76 83 99 336 84%A+ 1024 Junaid 36 75 90 82 283 71%A 1027 Chaman 34 36 38 33 141 35%Pass Duplicat es Lower than 33 Grading Criteria 33% Pass 40% D 50% C 60% B 70% A 80% A+ Greater than 79 Top 3 Bottom 3 Containing “a” Blan k Conditional Formatting
  59. 59. Conditional Formatting Sales by Builder Date Builder Total 11 Feb 13 Doug 4,640 17 Jan 13 Morgan 2,328 31 Jan 13 Dave 3,850 19 Aug 10 Gill 3,810 23 Jun 10 Dave 2,313 02 Feb 13 Brian 1,565 15 Apr 10 Larry 5,740 20 Mar 10 Rob 5,840 05 Feb 10 Morgan 1,884 14 Feb 13 Jones 548 11 Jan 10 Brian 4,128 14 Nov 09 Rob 4,640 12 Nov 09 Jones 2,125 03 Nov 09 Doug 639 04 Nov 09 Richard 4,110 05 Nov 09 Sime 969 12 Dec 09 Mandis 802 25 Jan 10 Rogger 3,420 19 Mar 10 Dave 3,560 03 May 10 Dave 1,636 24 May 10 Dave 3,888 02 Jun 10 Larry 6,630 03 Jun 10 Brian 3,800 23 Jul 10 Larry 1,605 01 Aug 10 Rob 1,989 03 Sep 10 Rob 3,040 17 Sep 10 Brian 2,760 12 Oct 10 Dave 2,448 24 Nov 10 Larry 2,223 Highlight other than “Larry” Highligh t Below AverageHighlight Dates Occurring This Month Hide Error Sales by Builder Date Builder Total 11 Feb 13 Doug 4,640 17 Jan 13 Morgan 2,328 31 Jan 13 Dave 3,850 19 Aug 10 Gill 3,810 23 Jun 10 Dave 2,313 02 Feb 13 Brian 1,565 15 Apr 10 Larry 5,740 20 Mar 10 Rob 5,840 05 Feb 10 Morgan 1,884 14 Feb 13 Jones 548 11 Jan 10 Brian 4,128 14 Nov 09 Rob 4,640 12 Nov 09 Jones 2,125 03 Nov 09 Doug 639 04 Nov 09 Richard 4,110 05 Nov 09 Sime 969 12 Dec 09 Mandis 802 25 Jan 10 Rogger 19 Mar 10 Dave 3,560 03 May 10 Dave 1,636 24 May 10 Dave 3,888 02 Jun 10 Larry 6,630 03 Jun 10 Brian 3,800 23 Jul 10 Larry 1,605 01 Aug 10 Rob 1,989 03 Sep 10 Rob 3,040 17 Sep 10 Brian 2,760 12 Oct 10 Dave 2,448 24 Nov 10 Larry 2,223 Icon Sets Data Bars
  60. 60. Tips & Tricks
  61. 61. Tips & Tricks F6 to move b/w open files Ctrl + Pg Up/ Pg Dn to move b/w sheets Drag & Drop (to cut/ paste or copy/ paste or to make place for cut/ paste) Shift + Space to select entire row Ctrl + Space to select entire column F4 to repeat last command Shift + F2 to edit comments Insert a Sheet Right-click on sheet tab Delete a Sheet Rename a Sheet Hide a Sheet Move or Copy a Sheet
  62. 62. Desired Location of Sheet We can move or copy to the same book or any open book or a new book Desired Order of Sheet Copy of Sheet Check it to make a copy otherwise Excel will move the sheet Move means Cut & Paste Copy means Copy & Paste Tips & Tricks
  63. 63. Tips & Tricks
  64. 64. Tips & Tricks 2 1 3 4 5 6 7 8 Requirement: From the ledger of repair of vehicles (given below), we have to extract entries of vehicle # “AB-0131”
  65. 65. Tips & Tricks
  66. 66. Tips & Tricks
  67. 67. Tips & Tricks Alternatively: Sorted for “KDN-9779” from the following list =IF(ISERROR(FIND(9779,C73)),"","KDN-9779")
  68. 68. Tips & Tricks
  69. 69. Tips & Tricks Go To Special Constants, Formulas, Blanks, Row Differences, Column Differences, Visible Cells Only Paste Special Formulas, Values, Formats, Comments, Validation, Column Widths, Operation, Transpose, Paste Link Link a picture Hide functions from view Custom Formatting (Symbols e.g. Kg, Rounding e.g. in thousands)
  70. 70. Sub-Total Scenario Manager Goal Seek Data Table (One & Two Variables) Consolidation (3-D, Internal, External) CreatingReports
  71. 71. Sub-Total Sort by Region then by Sale Rep; Sub-Total at each change in Region; again Sub-Total at each change in Sales Rep (uncheck replace current sub-totals). Apply formatting to only sub-totals of any level expand or collapse accordingly then ^G Special Visible Cells Only; Sub-Total Remove All Date Region Sales Rep Customer Product Sales COGS Abdisamad A Total 105,487 71,869 Analyssa C Total 43,768 26,289 Anastasiya A Total 58,381 35,444 Barbara C Total 69,882 48,002 Catherine W Total 47,563 28,338 Cherry M Total 126,926 74,191 Dan Total 56,677 38,142 Dana L Total 99,612 64,527 Daniil N Total 57,301 32,180 Desiree A Total 63,582 46,800 Dina Total 70,651 40,473 Donald Wayne Total 63,125 33,664 Hassan M Total 103,656 70,381 Michael G Total 56,431 30,055 Nikol M Total 97,765 62,610 Sarabeth L Total 105,861 63,141 Shannon L Total 71,010 39,335 Shuting Total 106,369 57,344 Suzanne M Total 79,980 48,651 Toni M Total 75,657 42,140 Tonya J Total 100,052 67,262 Vivien R Total 46,682 23,305 North Total 1,706,418 1,044,143 Abdisamad A Total 72,645 47,760 Analyssa C Total 82,114 58,072 Anastasiya A Total 65,258 42,246 Barbara C Total 97,979 57,088
  72. 72. Sales Person Area Monthly Sales (Dec. 2012) Region 1 Hashim Gulshan 110,000 Basheer Liaquatabad 90,000 Javaria F.B. Area 120,000 320,000 320,000 Region 2 Khalid Nazimabad 125,000 Rehana Hyderi 95,000 Chaman North Karachi 75,000 Waqar Orangi 120,000 Saqib Golimar 75,000 490,000 490,000 Region 3 Bushra Saddar 85,000 Mubashir Shahra-e-Faisal 105,000 Bilal Malir 125,000 Junaid Super Highway 150,000 465,000 465,000 1,275,000 1,275,000 Sales Person Area Monthly Sales (Dec. 2012) Region 1 Hashim Gulshan 110,000 Javaria F.B. Area 120,000 320,000 230,000 Region 2 Khalid Nazimabad 125,000 Waqar Orangi 120,000 490,000 245,000 Region 3 Mubashir Shahra-e-Faisal 105,000 Bilal Malir 125,000 Junaid Super Highway 150,000 465,000 380,000 1,275,000 855,000 9 9 =SUBTOTAL(A$20,C2:C20) =SUBTOTAL(100+A$20,C2:C20) Onlyrecordsgreaterthan99,999(belowfigurerecordshavebeenhidden). Sub-Total
  73. 73. If Sub-Total used on filtered data then it accounts for only visible cells Advantages of Sub-Total  If any range of total is wrong but grand total range is correct then grand total will be correct.  In case of hidden data as a result of filtering then it will calculate only unhidden data Disadvantages of Sub-Total  We have to know function number of the function  In case of hidden data as a result of filtering then it will calculate only unhidden data Sub-Total
  74. 74. Scenario Manager Changing Cells Resulting Cells Units Sold 15000 Total Revenue 1,500,000 S.P./ Unit 100 Total Costs 1,050,000 V.C./ Unit 40 Profit 450,000 Fixed Costs 450,000 1) Data-->What-If Analysis-->Scenario Manager Add-->Scenario Name: Pessimistic Approach-->Changing Cells: B4:B7 [Rel. Ref.] (1000;100;50;400,000)-->OK-->OK 2) Data-->What-If Analysis-->Scenario Manager Add-->Scenario Name: Optimistic Approach-->Changing Cells: B4:B7 [Rel. Ref.] (20000;150;60;1,000,000)-->OK-->OK 3) Data-->What-If Analysis-->Scenario Manager Add-->Scenario Name: Normal Approach-->Changing Cells: B4:B7 [Rel. Ref.] (10000;110;55;500,000)-->OK-->OK 4) Data-->What-If Analysis-->Scenario Manager-->Summary Result Cells-->F4:F6 [Rel. Ref.]-->OK B4:B7 F4:F6
  75. 75. Scenario Summary Current Values: Pessimistic Approach Optimistic Approach Normal Approach Changing Cells: Units_Sold 15000 1000 20000 10000 S.P.__Unit 100 100 150 110 V.C.__Unit 40 50 60 55 Fixed_Costs 450,000 400,000 1,000,000 500,000 Result Cells: Total_Revenue 1,500,000 100,000 3,000,000 1,100,000 Total_Costs 1,050,000 450,000 2,200,000 1,050,000 Profit 450,000 (350,000) 800,000 50,000 Notes: Current Values column represents values of changing cells at time Scenario Summary Report was created. Changing cells for each scenario are highlighted in gray. Scenario Manager
  76. 76. Sales 145,769 Variable Costs 66,519 Contribution Margin 79,250 Fixed Costs 79,250 Net Income - Assumptions Units Sold 4,859 Price per Unit 30.00 Variable Cost per Unit 13.69 Fixed Costs 79,250 Sales 170,769 Variable Costs 66,519 Contribution Margin 104,250 Fixed Costs 79,250 Net Income 25,000 Assumptions Units Sold 4,859 Price per Unit 35.15 Variable Cost per Unit 13.69 Fixed Costs 79,250 Sales 237,738 Variable Costs 108,488 Contribution Margin 129,250 Fixed Costs 79,250 Net Income 50,000 Assumptions Units Sold 7,925 Price per Unit 30.00 Variable Cost per Unit 13.69 Fixed Costs 79,250 Original – Break Even Point We may come to this situation applying on any other situation by setting value to 0 (“zero”) Price Per Unit changed to earn a profit of Rs.25,000 Units Sold changed to earn a profit of Rs.50,000 Data  What-If Analysis  Goal Seek  Set Cell (having a formula/ function)  To Value  By Changing Cell (without any formula/ function) Goal Seek
  77. 77. One Variable Interest Rate Monthly Repayment Total Repayment Total Interest 10.00% 1,718 206,155 76,155 1% 3% 5% 7% 10% 12% 15% 20% 25% 30% Interest Rate Monthly Repayment Total Repayment Total Interest 10.00% 1,718 206,155 76,155 1% 3% 5% 7% 10% 12% 15% 20% 25% 30% Step 2 Step 3 Select Table Area Tractor Loan Amount of loan 130,000 Interest Rate 10.00% Term of Loan (Years) 10 Number of Payments (per Year) 12 Amount of Payment 1,718 Total Paid 206,155 Interest Paid 76,155 To be Repaid by June 2023 Step 1 =K4 =K8 =K10 =K11 Data Table
  78. 78. One Variable Step 4 Data  What-If Analysis  Data Table Keep Row Input Cell blank In Column Input Cell ref. to original cell containing Interest Rate i.e. K4 Interest Rate Monthly Repayment Total Repayment Total Interest 10.00% 396 47,574 17,574 1% 1,139 136,662 6,662 3% 1,255 150,635 20,635 5% 1,379 165,462 35,462 7% 1,509 181,129 51,129 10% 1,718 206,155 76,155 12% 1,865 223,815 93,815 15% 2,097 251,683 121,683 20% 2,512 301,479 171,479 25% 2,957 354,889 224,889 30% 3,427 411,244 281,244 Final Output Value generated by Data Table Now we may make this row invisible by changing font color to white Data Table
  79. 79. Two Variables Select Table Area Tractor Loan Amount of loan 130,000 Interest Rate 10.00% Term of Loan (Years) 10 Number of Payments (per Year) 12 Amount of Payment 1,718 Total Paid 206,155 Interest Paid 76,155 To be Repaid by June 2023 Step 1 T e r m o f L o a n 1,718 5 10 12 15 1% 3% 5% 7% 10% 12% 15% 20% 25% 30% Step 3 =K8 T e r m o f L o a n 1,718 5 10 12 15 1% 3% 5% 7% 10% 12% 15% 20% 25% 30% Step 2 Data Table
  80. 80. Two Variables Step 4 Data  What-If Analysis  Data Table In Row Input Cell ref. to original cell containing Term of Loan i.e. K5 In Column Input Cell ref. to original cell containing Interest Rate i.e. K4 Final Output Value generated by Data Table Now we may make this cell invisible by changing font color similar to fill color of the row. Term of Loan 396 5 10 12 15 1% 2,222 1,139 958 778 3% 2,336 1,255 1,076 898 5% 2,453 1,379 1,202 1,028 7% 2,574 1,509 1,337 1,168 10% 2,762 1,718 1,554 1,397 12% 2,892 1,865 1,707 1,560 15% 3,093 2,097 1,951 1,819 20% 3,444 2,512 2,388 2,283 25% 3,816 2,957 2,855 2,776 30% 4,206 3,427 3,346 3,289 Data Table
  81. 81. Consolidation Product/Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total Carlota 71 158 114 96 142 62 112 103 114 140 115 115 1342 Yanaki 109 161 147 79 97 109 184 114 110 168 146 132 1556 Aspen 143 181 96 138 115 88 111 155 135 179 156 89 1586 Sunset 134 155 89 101 98 72 106 120 141 171 131 142 1460 Delicate Arch 139 139 123 140 115 74 142 150 111 189 128 124 1574 Bellen 156 114 77 148 110 122 181 143 162 119 113 164 1609 Total 752 908 646 702 677 527 836 785 773 966 789 766 9127 There may be lot of sheets excluding such sheets to be incorporated here. It may give wrong results if any sheet moved from the range sheets. Similar spaces should be used in all sheets. =SUM('Store(1):Store(5)'!B3) Type “=Sum(“Go to Store(1)  Select relevant cell  Shift + Go to Store(5) Enter We may also put simply =sum('sto*'!B3) then it will converted itself to such 3D Ref. A more reliable method to select the same cell from all sheet one by one instead of 3- D referencing.
  82. 82. Consolidation Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec TOTAL Sales Software 28,175 50,244 52,910 55,480 54,890 54,800 56,380 52,910 52,910 57,360 52,910 24,000 592,969 Books 47,700 74,550 78,000 82,500 81,250 81,420 56,500 78,220 78,220 84,780 78,220 54,700 876,060 Videos 26,500 49,750 51,850 55,850 55,400 53,500 55,500 53,750 53,750 56,500 53,750 25,250 285,600 CD-ROMs 49,532 48,720 51,258 53,998 54,810 54,303 26,460 51,258 51,258 56,840 51,258 26,513 576,205 SALES TOTAL 151,907 223,264 234,018 247,828 246,350 244,023 194,840 236,138 236,138 255,480 236,138 130,463 2,636,584 Expenses Cost of Goods 12,153 17,861 18,721 19,826 19,708 19,522 15,587 18,891 18,891 20,438 18,891 10,437 210,927 Advertising 8,878 12,306 15,236 14,650 16,115 15,383 10,450 15,236 15,236 13,185 15,236 10,556 162,467 Rent 4,053 6,153 6,153 6,153 6,153 6,153 3,990 6,153 6,153 6,153 6,153 4,263 67,683 Supplies 2,509 3,516 4,102 3,809 3,663 4,102 2,470 4,102 4,102 3,663 3,956 2,842 42,835 Salaries 30,880 46,880 48,345 48,345 48,345 49,810 32,300 49,810 49,810 49,810 51,275 35,525 541,135 Shipping 27,503 40,288 42,485 43,950 42,485 43,218 28,500 42,485 42,485 46,148 44,683 29,435 473,663 Utilities 965 1,758 1,758 1,612 1,758 1,905 1,235 1,758 1,758 1,905 1,758 1,218 19,387 EXPENSES TOTAL 86,940 128,762 136,800 138,345 138,227 140,091 94,532 138,435 138,435 141,301 141,951 94,276 1,518,095 GROSS PROFIT 64,967 94,502 97,217 109,483 108,124 103,931 100,308 97,703 97,703 114,179 94,187 36,187 1,118,489 Consolidated data from three sheets (Div-A, Div-B, and Div-C) all sheets use similar labels for rows and columns, however, there was different patterns in the sheets (e.g. number of columns and rows are different even order of rows were different but consolidation made according to labels used therein. Created a new sheet (i.e. Div-A2C)  Data  Consolidate  Added (addresses)  Use Labels in: Top Row & Left Column  Create Links to Source Data
  83. 83. Consolidation January February March April May June July August September October November December Revenue Branch A 16,498 16,549 15,524 15,356 17,657 15,216 15,926 15,621 16,517 18,315 15,613 15,643 Branch B 17,861 15,205 16,090 18,372 18,351 16,799 16,749 18,312 15,097 17,943 17,509 15,869 Branch C 18,807 17,256 17,893 17,686 18,344 15,190 15,377 18,592 15,696 15,641 16,344 18,537 Sale of Shirts 53,166 49,010 49,507 51,414 54,352 47,205 48,052 52,525 47,310 51,899 49,466 50,049 Branch A 12,057 10,078 11,695 12,056 11,525 11,907 10,076 12,054 11,357 13,882 10,376 11,903 Branch B 10,795 13,444 12,355 10,811 10,475 13,834 12,197 11,425 11,290 12,812 10,089 10,996 Branch C 11,401 10,122 12,127 11,534 11,593 13,154 10,739 13,650 13,364 10,038 12,237 13,950 Sale of Pants 34,253 33,644 36,177 34,401 33,593 38,895 33,012 37,129 36,011 36,732 32,702 36,849 Branch A 8,618 8,940 8,142 7,043 7,346 8,911 8,084 8,535 8,682 7,656 8,479 8,092 Branch B 7,670 8,920 8,147 8,631 8,657 8,183 8,062 7,810 8,653 7,964 7,883 7,496 Branch C 8,296 7,047 7,545 8,180 7,989 8,781 7,956 8,050 8,803 7,271 7,376 7,277 Sale of Shoes 24,584 24,907 23,834 23,854 23,992 25,875 24,102 24,395 26,138 22,891 23,738 22,865 Consolidated data from three workbooks(Br-A, Br-B, and Br-C). For convenience in referring ranges have been given name. Created a new sheet (i.e. Br-A2C)  Data  Consolidate  Browse to file  Edit name of range  Added (addresses)  Use Labels in: Top Row & Left Column  Create Links to Source Data Consolidation with other workbooks (external data)
  84. 84. Improve Visualization of Data Charts (Popular Types, Adding/ Deleting Data, Sub-chart, Secondary Axis) Pivot Tables (Basics, Filtering, Options, Grouping, Slicer)
  85. 85. Year Sales Expense Profit 2005 4,689 2,326 2,363 2006 4,946 2,152 2,794 2007 3,383 2,493 890 2008 4,978 2,065 2,913 2009 2,696 2,005 691 2010 3,339 2,190 1,149 Rs. in Thousands Charts Sample Data
  86. 86. Charts - 1,000 2,000 3,000 4,000 5,000 6,000 2005 2006 2007 2008 2009 2010 Sales Expense Profit Column Chart Line Chart 4,689 4,946 3,383 4,978 2,696 Expense Expense Expense Expense Expense 2005 2006 2007 2008 2009 - 1,000 2,000 3,000 4,000 5,000 6,000 2005 2006 2007 2008 2009 2010 Sales Expense Profit Axis Data Series Data Label Data Point Legend Gridlines Axis Popular Types
  87. 87. Charts Pie Chart Bar Chart Sales 4,689 Expense 2,326 Profit 2,363 Financial Year 2005 - 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 2005 2006 2007 2008 2009 2010 Profit Expense Sales Format Data LabelsLabel OptionsCategory Name, Value, Separator Popular Types
  88. 88. Charts - 1,000 2,000 3,000 4,000 5,000 6,000 2005 2006 2007 2008 2009 2010 Sales Expense Profit Doughnut Chart Financial Year 2005 Sales Expense Profit It may be used for more than one data categories but distinction may not be maintained. Area Chart Popular Types
  89. 89. Charts Year Sales Expense Profit 2005 4,689 2,326 2,363 2006 4,946 2,152 2,794 2007 3,383 2,493 890 2008 4,978 2,065 2,913 2009 2,696 2,005 691 2010 3,339 2,190 1,149 - 1,000 2,000 3,000 4,000 5,000 6,000 2005 2006 2007 2008 2009 2010 Sales Rs. in Thousands To add another series select chart then apply Chart Tools Design Tab Data Select Data Add (Series) Alternatively select cells containing Expense data Copy Paste Special after selecting chart Add Cells as: New Series Values (Y) in: Columns Series Names in the First Row: Check it. Adding a Series
  90. 90. Charts Expenses Amount Administrative Expenses 2,843,916,990 Financial Charges 944,943,570 Selling and Distribution Exp. 1,791,012,930 Sales Promotion 560,828,520 Staff Salaries and Benefits 538,637,000 Depreciation 331,181,000 Vehicle Expenses 174,699,000 Cartage and Forwarding 161,624,000 Other Selling Expenses 23,868,410 Tender Fees 175,000 Administrative Expenses Financial Charges Sales Promotion Staff Salaries and Benefits Depreciation Vehicle Expenses Cartage and Forwarding Other Selling Expenses Selling & Distribution Expenses Expenses BreakupofSales andDistribution expenses Select Data excl. Selling and Distribution Exp.; Format Data Series Series Options Split Series by: Sub-Chart
  91. 91. Product Sales 2008 Productgroup A 3,216,546 Product B 987,987 Product C 256,446 Product D 565,467 Product E 466,361 Product F 426,450 Product G 386,539 Product H 346,628 3,216,546 987,987 256,446 565,467 466,361 426,450 386,539 346,628 3,435,878 Sales by Productgroup in 2009 Productgroup A Product B Product C Product D Product E Product F Product G Product H Sub-ChartCharts
  92. 92. Year Production Capacity 2001 36,641 48,215 2002 47,761 48,215 2003 41,006 58,632 2004 40,432 58,632 2005 34,622 58,632 2006 38,478 58,632 2007 43,539 58,632 2008 48,439 58,632 2009 54,419 58,632 2010 45,122 58,632 2011 45,690 58,632 2012 53,230 58,632 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 - 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Capacity Production Area Chart Column Chart Secondary AxisCharts
  93. 93. Pivot Tables Basics A pivot table is a great reporting tool that sorts and sums independent of the original data layout in the spreadsheet. It can automatically sort, count, and total spreadsheet data and then create a second table to display the summarized data. Once you have finished looking at the summarized data, you can quickly re-sort your data and look at it from a totally different perspective, and all of this can be done without using functions or formulas. Introduction
  94. 94. Pivot Tables Filtering Field Filtering Year 2006 Qtr Q 3 & Q 4 Column Labels Direct Sales, Internet, Retail We may apply filtering on any one filter or more filters as below:
  95. 95. Pivot Tables Options Applying different options by right-click or Options Pivot Table Options
  96. 96. Pivot Tables Options
  97. 97. Pivot Tables Options
  98. 98. Pivot Tables Options
  99. 99. Pivot Tables Options
  100. 100. Pivot Tables Options
  101. 101. Pivot Tables Options For instance Catering of Jan divided by Feb (72,000/75,990) X 100.
  102. 102. Pivot Tables Grouping
  103. 103. Pivot Tables Grouping
  104. 104. Pivot Tables Grouping
  105. 105. Pivot Tables Slicer
  106. 106. Facilitating & Restricting Users Data Validation (incl. Depended Lists) Controls (Combo Box, List Box, Check Box, Option Button, Spin Button, Scroll Bar)
  107. 107. G.R. No. Student Math English Urdu Islamiat Total %age Grade Whole number between (minimum:) 0 & (maximum:) 100 To avoid duplicate entries: =COUNTIF($K$2: $K$13,K2)<2 Prepared by: Name: CNIC#: Date: Custom: =ISTEXT(L6) Text Length: equal to 15 Date: Between 1-Jan-2011 to Today() List Invoice Amount Paid Amount Custom: <=Paid_Amt Data Validation
  108. 108. Data Validation Data Country Pakistani Cities Indian Cities Bangladeshi Cities Pakistan Faisalabad Agra Barisal India Hyderabad Ahmedabad Chittagong Bangladesh Islamabad Chanai Comilla Karachi Colcata Dhaka Lahore Goa Gazipur Lodhran Jaipur Khulna Peshawar Mumbai Rangpur Quetta New Dehli Sadiqabad Puna Sukkur Secondary lists Primary list Pakistan India Bangladesh Name of Cell(s) containing cities of a country must be same as Country in Primary List (e.g. G4:G13 must be named as "Pakistan" instead of "Pak" because in the Primary List this is "Pakistan")
  109. 109. Data Validation To be applied at City e.g. B4
  110. 110. Controls
  111. 111. Controls =IF(M$38=TRUE,M18,"") =IF($Q$50=5,M18,"")
  112. 112. Controls =K60/100 =L63*M$60 =K72/100 =L75*M$72
  113. 113. Automating Your Repetitive Tasks Macro (Intro, Developer Tab, Record, Run, View Code, Sort to get top 3, Methods to Call)
  114. 114. Macro What is an Excel Macro? An excel macro is a series of keystrokes, mouse clicks, and other commands that you can record and reuse to save time. The next time you want to perform those steps, you can run the macro and then sit back while Microsoft Excel does the work for you. Suggestions before creating a macro • Plan your macro • Initially you may use the copy of original work • Before record a macro - once perform desired tasks (as rehearsal) • Initially it is advisable to use more than one small macros instead of a single for all your tasks Uses of Excel Macro Everyday users use the macro recorder to automate simple tasks Application developers create completely custom applications Introduction
  115. 115. Macro Developer Tab Adding the Developer Tab in Excel 2007  Click on the Excel Options button  Click on the Popular option  Click on the Show Developer Tab in the ribbon  Click on OK
  116. 116. Macro Record – Dialogue Box Macro Name: Use naming conventions; invalid name if starts with digit or having space, “.”, punctuation marks Shortcut Key: Assign a shortcut without conflict of built-in commands (may be any small/ capital letter or digit) Store Macro in: 1. This workbook (The macro is available only in this file.) 2. New workbook (This option opens a new Excel file. The macro is available only in this new file.) 3. Personal macro workbook(This option creates a hidden file Personal.xls which stores your
  117. 117. Macro Record – First Example 1. Click on the Home tab of the ribbon. 2. Select cells A1 to F1. 3. Click on the Merge and Center icon to center the title b/w A1 and F1. 4. Click on the Fill Color icon. 5. Choose Blue to turn the background color to blue. 6. Click on the Font Color icon. 7. Choose White to turn the text to white. 8. Click on the Font Size icon. 9. Choose 16 to change the size of text. 10. Click on the Developer tab of the ribbon. 11. Click the Stop Recording button on the ribbon.
  118. 118. Macro Run – First Example 1. Click on the Sheet2 tab. 2. Click on cell A1. 3. Type the title: Profit & Loss Statement of April 2013. 4. Click on the Developer tab of the ribbon. 5. Click Macros button on the ribbon to bring up Macro dialog box. Alternatively a short cut to call this dialogue box by applying Alt + F8. 6. Click on the format_titles macro in the Macro name window. 7. Click the Run button. 8. The steps of the macro should run automatically and apply the same formatting steps applied to the title on sheet 1.
  119. 119. Macro View Code – First Example Unnecessary portion of code may be deleted instantly or after making them comments to read it conformably as well as to speed up it execution. Shortcut to view code is Alt +F11
  120. 120. Macro Sort to get top 3 G.R. No. Student Math English Urdu Islamiat Total %age Grade 1021 Basheer 42 40 52 91 225 56% C 1030 Bilal 47 55 99 80 281 70% A 1074 Bushra 42 61 51 58 212 53% C 1027 Chaman 34 36 38 33 141 35% Pass 1017 Fawad 88 52 65 87 292 73% A 1005 Hashim 74 42 34 96 246 62% B 1004 Jamshed 81 54 - 25 160 40% Fail 1054 Javaria 78 36 66 27 207 52% Fail 1024 Junaid 36 75 90 82 283 71% A 1043 Khalid 78 76 83 99 336 84% A+ 1046 Mehmood 5 27 43 81 156 39% Fail 1065 Mubashir 42 47 52 40 181 45% D 1053 Nasir 37 20 20 38 115 29% Fail 1032 Rais 13 28 52 76 169 42% Fail 1050 Rehana 73 36 54 62 225 56% C 1084 Sikandar 37 31 - 39 107 27% Fail 1036 Waqar 41 61 91 78 271 68% B 1039 Zeeshan 67 29 79 99 274 69% B This is our original data which is sorted by student name. Requirements  We need to extract top 3 students particulars in the following manner: Position G.R. No. Name Total Grade 1st 1043 Khalid 336A+ 2nd 1017 Fawad 292A 3rd 1024 Junaid 283A
  121. 121. Macro Sort to get top 3 1. Select Columns A to I 2. Data Sort Total  Values Largest to Smallest 3. Select A2:B4; Copy and Paste to L2:M4 4. Select G2:G4; Copy and Paste Special to N2:N4 5. Select I2:I4; Copy and Paste Special to O2:O4 6. Select Columns A to I 7. Data Sort G.R. No.  Values Smallest to Largest Add a Button to Run Macro  Developer Insert Form Controls Button  Draw the Button  Right-Click  Edit Text: Top 3 Students  Right-Click  Assign Macro…  Select Macro Name OK Macro Name: Top_3
  122. 122. Macro Methods to Call Macro Adding graphical aids to run macro: Insert Clip Art  Select any image Draw the image & place at a suitable place Right-Click Assign Macro… Select Macro Name Adding Button to Run Macro  Developer Insert Form Controls Button  Draw the Button & place at a suitable place  Right-Click  Edit Text  Right-Click  Assign Macro…  Select Macro Name  OK Now due to relative references we may apply these macros at any column where similar kind of data (irrespective of size) with similar error may be available there. So reach at respective columns heading and apply the respective macro.
  123. 123. Questions & Answers

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