YearMth Region Employee Item Units Unit Cost Total
--------------------------------------------------------------------
2006-12 DC Jones Pen Set 700 1.99 1,393
2006-12 NY Peterson Binder 85 19.99 1,699
2006-12 DC Howard Pen Set 62 4.99 309
2006-12 DC Gill Pen 58 19.99 1,159
2006-12 NY Anderson Binder 10 4.99 50
2006-12 NY Anderson Pen Set 19 2.99 57
Using this data how would I create a Dynamic Range using a Macro.
Thanks
Depends what you want to do! But here's an example
ActiveWorkbook.Names.Add Name:="MyDynamicRange",
RefersToR1C1:= "=OFFSET(Sheet1!R2C2,0,0,COUNTA(Sheet1!R2C2:R200C2),1)"
This range will contain all your Regions.
Related
So I have two DataFrames: Historic and Applet.
Historic contains a list of all courses my school offered in the past and Applet is all courses that my school currently offers
I want to merge the two DataFrames so that any items in my Applet DataFrame that don't exist in Historic are added and any that do exist overwrite their copies in Historic (Some courses may have updated information and should overwrite their historic entries with that information..)
I'm currently using Historic.combine_first(Applet) to merge the two by on their Indexes. However, I want the duplicate entries to overwrite their Historic entries not just make a duplicate entry.
Code:
def update2(self):
historic = pd.read_csv('course_history.txt', header=None, sep='"', encoding = 'ISO-8859-1',
names=['Course_ID', 'Course_Title', 'Professor_Name','Meeting_Time','Enrollment','Room','Year','Term','Credit'],index_col=[0,6,7])
winnet = pd.DataFrame(self.data, columns =['Course_ID', 'Course_Title', 'Professor_Name','Meeting_Time','Enrollment','Room','Year','Term','Credit'] )
winnet.set_index(['Course_ID','Year','Term'], inplace=True)
historic3 = historic.combine_first(winnet)
Historic DataFrame:
Course_ID Year Term ...
AC 230 01 2020-21 May Accounting Systems Crouse, Justin D. ... ROOM NULL 1.00
AC 429 01 2020-21 May CPA Review Sommermeyer, Eric ... ROOM NULL 1.00
ART 150 01 2020-21 May 20th-Century Art, Media, & Design Fedeler, Barbara J. ... ROOM NULL 1.00
ART 208 01 2020-21 May Photography I Payne, Thomas R. ... ROOM NULL 1.00
PSY 222 01 2018-19 FA Cognitive Psychology Eslick Watkins, A ... ROOM NULL 1.00
Applet DataFrame:
Course_ID Year Term
PSY 101 01 2018-19 FA Introduction to Psychology Bane, C T H 9:35AM-11:15AM 40/44/0 LH 330 1.00
PSY 101 02 2018-19 FA Introduction to Psychology Eslick Watkins, A T H 1:00PM-2:40PM 40/43/0 SC 134 1.00
PSY 210 10 2018-19 FA Child Development Munir, S T H 9:35AM-11:15AM 30/10/0 LH 327 0.50
PSY 211 20 2018-19 FA Adolescent Development Munir, S T H 1:00PM-2:40PM 30/6/0 LH 330 0.50
PSY 222 01 2018-19 FA Cognitive Psychology Eslick Watkins, A T H 9:35AM-11:15AM 30/24/0 LH 324 1.00
You can use concat then drop_duplicates
cols = [columns_to_judge_duplicates]
combined = pd.concat([Applet, Historic])
combined = combined.drop_duplicates(subset=cols, method='first')
Hi I have excel sheet named 'master'
Start Customer Country Parent group Issue
2 Jaguar USA TATA HW
3 Suzuki Japan Suzuki Motors HW
6 GM USA General Motors SW
7 Hyundai Japan Hyundai Motrs HW
8 Google USA Google corporations SW
12 TCS India TATA Consultancy Services HW
14 Jaguar USA TATA HW
19 AT & T USA AT & T Corporation SW
28 Oracle USA Oracle Services SW
30 Benz Germany Mercedez Benz SW
31 Suzuki Japan Suzuki Motors SW
49 Honda Japan HONDA motors HW
90 GM USA General Motors SW
91 Hyundai Japan Hyundai motors HW
96 Jaguar USA TATA SW
98 Suzuki Japan Suzuki Motors HW
100 TCS India TATA Consultancy Services HW
114 Hyundai Japan Hyundai motors HW
119 AT & T USA AT & T Corporation SW
125 Suzuki Japan Suzuki Motors SW
where I want to colour cells of customer column where customer is Honda, TCS, Jaguar and Suzuki using for loop over list of these four customers.
List = ['Honda', 'TCS', 'Jaguar', 'Suzuki']
and write colored data frame in excel sheet
You tagged this question with StyleFrame so I suppose you want a solution using it.
from StyleFrame import StyleFrame, Styler
sf = StyleFrame.read_excel('path/to/excel.xlsx', sheetname='master')
yellow_bg = Styler(bg_color='yellow')
sf.apply_style_by_indexes(sf[sf['Customer'].isin(('Honda', 'TCS', 'Jaguar', 'Suzuki'))],
styler_obj=yellow_bg,
cols_to_style='Customer')
sf.to_excel('path/to/excel.xlsx').save()
You may provide sheet_name (note underscore) to to_excel if you don't want to use Excel's default sheet name ('Sheet1')
When extracting and moving data, the first column of the criteria is working but the second criteria is not engaging. It is returning the movement for all stores if they had sold that item.
List of column headers.
R2=Left Len,
S2=Store
A2=Left Len,
B2=UPC,
C2=Store,
D2=Movement,
The file is just short of 900k rows of data in total.
I believe it to be an issue with Current Region.
Also need for this to return zero if there is no movement for that store. This will be repeated 39 more times to the right in order to get results for each location.
Ultimate goal is to find the Zero Movers that need to be addressed. So the rows of upc's would need to stay aligned with the criteria.
Any help would be greatly appreciated.
Using Windows 7,
Office 2016
Sub Find_Fill_Data()
Range("u2:x" & Range("x" & Rows.Count).End(xlUp).Row).ClearContents
Range("a2:D" & Range("D" & Rows.Count).End(xlUp).Row).AdvancedFilter Action:=xlFilterCopy, criteriarange:=Range("r2").CurrentRegion, copytorange:=Range("u2"), unique:=False
Range("q4").Select
End Sub
**Left Len Item 5 7 8 9**
1070002152 MILK DUDS THEATER BOX 123 254 181 196
1070002385 WHOPPERS MALT BALLS 19 0 28 42
1070002440 WHOPPERS MALT BALLS 92 188 79 133
1070002660 WHOPPERS MALT BALLS 22 21 11 22
1070006080 CANDY BAR 575 463 446 303
1070006611 WHOPPER ROBIN EGGS 22 28 25 0
1070008807 CANDY 132 57 59 0
1070008813 THEATER BOX 331 127 101 171
1070013272 J/RANCHER CRNCH CHEW ASST 61 0 0 0
1070050180 WHOPPERS MALT BALLS CARTN 119 24 99 99
Dataset Sample
I have data set like the attached picture where I want only the observations that have same numsecur every year.
How do I do this in SAS proc sql function? Will this be easier to do in STATA? If so what procedure can I use?
You look like a new user to stackoverflow. Welcome. Your question is getting down voted for at least three reasons:
1) It's not really clear what you want from your description of the problem and the data
you're providing
2) You haven't shown any attempts at what you've tried
3) Providing your data as a picture is not great. It's most helpful if you're going
to provide data to provide it so it's easy for others to consume in their program.
After all, you're asking for our help make it easier for us to help you. If You
included something like the following we just have to copy and paste to create your
dataset to work with:
DATA test;
INPUT ID YEAR EXEC SUM;
DATALINES;
1573 1997 50 1080
1581 1997 51 300
1598 1996 54 80
1598 1998 54 80
1598 1999 54 80
1602 1996 55 112.6
1602 1997 55 335.965
;
RUN;
That being said the following MAY give you what you're looking for but it's only a guess as I'm not sure if this is really what you're asking:
proc sql no print;
create table testout as
select *,count(*) as cnt
from test
group by sum
having cnt > 1;
quit;
Are you asking: show all rows where the same SUM is used or something else?
Assuming I understand your question correctly, you would like to keep the observations from the same company/individual only if the company has the same numsecur every year. So, here is what I would try using STATA:
input ID YEAR EXEC SUM
1573 1997 50 1080 //
1581 1997 51 300 //
1598 1996 54 80 //
1598 1998 54 80 //
1598 1999 54 80 //
1602 1996 55 112.6 //
1602 1997 55 335.965 //
1575 1997 50 1080 //
1575 1998 51 1080 //
1595 1996 54 80 //
1595 1998 54 30 //
1595 1999 54 80 //
1605 1996 55 112.6 //
1605 1997 55 335.965 //
end
bysort ID SUM: gen drop=cond(_N==1, 0,_n)
drop if drop==0
The results show ( based on my data):
ID YEAR EXEC SUM drop
1. 1575 1997 50 1080 1
2. 1575 1998 51 1080 2
3. 1595 1999 54 80 1
4. 1595 1996 54 80 2
5. 1598 1996 54 80 1
6. 1598 1998 54 80 2
7. 1598 1999 54 80 3
My dataset looks like this...
State Close Date Probability Highest Prob/State
WA 12/31/2016 50% FALSE
WA 12/19/2016 80% FALSE
WA 10/15/2016 80% TRUE
My objective is to build a formula to populate the right-most column. The formula should assess Close Dates and Probabilities within each state. First, it should select the highest probability, then it should select the nearest close date if there is a tie on probability (as in the example). For that record, it should read "TRUE".
I assume this would include a MAX IF statement but haven't been able to get it to work.
Here is a more robust set of data I'm working with. It may actually be easier to first find the highest probability within each Region then select the minimum (oldest) date if there is a tie on probability. This too will serve my purposes.
Region Forecast Close Date Probability (%)
Okeechobee FL 6/27/2016 90
Okeechobee West FL 7/1/2016 40
Albany GA 3/11/2016 100
Emerald Coast FL 6/30/2016 60
Emerald Coast FL 10/1/2016 40
Cullman_Hartselle TN 4/30/2016 10
North MS 10/1/2016 25
Roanoke VA 8/31/2016 25
Roanoke VA 8/1/2016 40
Gardena CA 6/1/2016 80
Gardena CA 6/1/2016 80
Lomita-Harbor City 6/30/2016 60
Lomita-Harbor City 6/30/2016 0
Lomita-Harbor City 6/30/2016 40
Eastern NC 6/30/2016 60
Northwest NC 9/16/2016 10
Fort Collins_Greeley CO 3/1/2016 100
Northwest OK 6/30/2016 100
Southwest MO 7/29/2016 90
Northern NH-VT 3/1/2016 20
South DE 12/1/2016 0
South DE 12/1/2016 20
Kingston NY 12/30/2016 5
Longview WA 11/30/2016 5
North DE 12/1/2016 20
North DE 12/1/2016 0
Salt Lake City UT 8/31/2016 20
Idaho Panhandle 8/26/2016 0
Bridgeton_Salem NJ 7/1/2016 25
Bridgeton_Salem NJ 7/1/2016 65
Layton_Ogden UT 3/25/2016 5
Central OR 6/30/2016 10
The following Array formula should work:
=(ABS(B2-$F$2)=MIN(IF(($A$2:$A$33=A2)*(C2=MAX(IF($A$2:$A$33=A2,$C$2:$C$33))),ABS($B$2:$B$33-$F$2))))*(C2=MAX(IF($A$2:$A$33=A2,$C$2:$C$33)))>0
Being an array formula use Ctrl-Shift-Enter when exiting Edit mode. If done properly Excel will put {} around the formula.
Edit
Added #tigeravatar suggestion to avoid volatile functions.
I think this is OK now but needs to be checked against the more complete set of data provided by OP.
It counts:-
(1) Any rows with same state but higher probability
(2) Any rows with same state and probability, in the future (or present) and nearer to today's date
(3) Any rows with same state and probability, in the past and nearer to today's date.
If all these are zero, you should have the right one.
=COUNTIFS($A$2:$A$100,$A2,$C$2:$C$100,">"&$C2)
+COUNTIFS($A$2:$A$100,$A2,$C$2:$C$100,$C2,$B$2:$B$100,"<"&$G$2+IF ($B2>=$G$2,DATEDIF($G$2,$B2,"d"),DATEDIF($B2,$G$2,"d")),$B$2:$B$100,">="&$G$2)
+COUNTIFS($A$2:$A$100,$A2,$C$2:$C$100,$C2,$B$2:$B$100,">"&$G$2-IF($B2>=$G$2,DATEDIF($G$2,$B2,"d"),DATEDIF($B2,$G$2,"d")),$B$2:$B$100,"<"&$G$2)
=0
If the dates are all in the future, it can be simplified a lot:-
=COUNTIFS($A$2:$A$100,$A2,$C$2:$C$100,">"&$C2)
+COUNTIFS($A$2:$A$100,$A2,$C$2:$C$100,$C2,$B$2:$B$100,"<"&$G$2+DATEDIF($G$2,$B2,"d"))
=0