I have a pivot table segmented by years, quarters and months. If I try
to expand a quarter for 2015, however, the corresponding quarter in
all other years are shown as well. How can I expand only one quarter
for one year?
- https://superuser.com/questions/1049881/expanding-specific-sections-of-a-pivot-table-in-excel
This question got no answer there, but that wasn't a programming forum. I have a similar question. Is there a VBA solution?
Alternatively, is there a VBA code to "catch" expansion clicks and then jump into the original cell on which plus was clicked?
Sample code (I want this true just for 2016):
ActiveSheet.PivotTables(1).PivotFields("Month").PivotItems("3").ShowDetail = True
Year
Month
Text
2015
1
Dummy1
2015
2
Dummy1
2015
3
Dummy1
2015
4
Dummy1
2015
5
Dummy1
2016
1
Dummy1
2016
2
Dummy1
2016
3
Dummy1
2016
4
Dummy1
2016
5
Dummy1
2017
1
Dummy1
2017
2
Dummy1
2017
3
Dummy1
2017
4
Dummy1
2017
5
Dummy1
2015
1
Dummy2
2015
2
Dummy2
2015
3
Dummy2
2015
4
Dummy2
2015
5
Dummy2
2016
1
Dummy2
2016
2
Dummy2
2016
3
Dummy2
2016
4
Dummy2
2016
5
Dummy2
2017
1
Dummy2
2017
2
Dummy2
2017
3
Dummy2
2017
4
Dummy2
2017
5
Dummy2
You can use something like this? This will be a good starting point for you, you'll have to create an IF THEN for each month
Private Sub Worksheet_PivotTableUpdate(ByVal Target As PivotTable)
If (ActiveSheet.PivotTables(1).PivotFields("Month").PivotItems("3").ShowDetail) Then
ActiveSheet.PivotTables(1).PivotFields("Month").PivotItems("3").ShowDetail = False
Sheets(2).Activate
'''' Change filter options here? or have a cell selected?
End If
End Sub
Related
I am using sumproduct formula to get the first four month, then the second four month, third four month of net sales until one month before today. This is my formula that I used:
=IFERROR(SUMPRODUCT($B3:$Y3*(COLUMN($B3:$Y3)>=AGGREGATE(15,6,COLUMN($B3:$Y3)/($B3:$Y3<>0),1)+4*(COLUMNS(B3)-1))*(COLUMN($B3:$Y3)<AGGREGATE(15,6,COLUMN($B3:$Y3)/($B3:$Y3<>0),1)+4*(COLUMNS(B3)))*($B$1:$Y$1<EOMONTH(TODAY(),-1)+1)),0)
However, I need to capture the same range as I have it for the net sales as for other measures like COGS in my example. I cannot use the formula above for the other measures like COGS as sometimes they are zero in the same range as in the Net Sales.But I need to capture the zeros here as well.
Example 1
Example 2
Net Sales
Jan
Feb
Mar
Apr
May
June
July
Aug
Sept
Oct
Nov
Dec
0
0
2
3
4
5
2
3
2
3
2
4
---> 1st period= 14 2nd period= 10
COGS (follows the same date range as Net Sales)
Jan
Feb
Mar
Apr
May
June
July
Aug
Sept
Oct
Nov
Dec
0
0
0
0
0
2
1
4
2
3
2
4
---> 1st period= 2 2nd Period= 11
You can leave the entire range check logic from the first formula and change just the value range, i.e first formula in my sample:
=IFERROR(SUMPRODUCT($A3:$L3*(COLUMN($A3:$L3)>=AGGREGATE(15,6,COLUMN($A3:$L3)/($A3:$L3<>0),1)+4*(COLUMN(A3)-1))*(COLUMN($A3:$L3)<AGGREGATE(15,6,COLUMN($A3:$L3)/($A3:$L3<>0),1)+4*(COLUMN(A3)))*($A$2:$L$2<EOMONTH(TODAY(),-1)+1)),0)
second formula for COGS:
=IFERROR(SUMPRODUCT($O3:$Z3*(COLUMN($A3:$L3)>=AGGREGATE(15,6,COLUMN($A3:$L3)/($A3:$L3<>0),1)+4*(COLUMN(A3)-1))*(COLUMN($A3:$L3)<AGGREGATE(15,6,COLUMN($A3:$L3)/($A3:$L3<>0),1)+4*(COLUMN(A3)))*($A$2:$L$2<EOMONTH(TODAY(),-1)+1)),0)
This question already has answers here:
How do I get a list of all the duplicate items using pandas in python?
(13 answers)
Closed 2 years ago.
Given a dataset as follows:
name month year
0 Joe December 2017
1 James January 2018
2 Bob April 2018
3 Joe December 2017
4 Jack February 2018
5 Jack April 2018
I need to filter and display all duplicated rows based on columns month and year in Pandas.
With code below, I get:
df = df[df.duplicated(subset = ['month', 'year'])]
df = df.sort_values(by=['name', 'month', 'year'], ascending = False)
Out:
name month year
3 Joe December 2017
5 Jack April 2018
But I want the result as follows:
name month year
0 Joe December 2017
1 Joe December 2017
2 Bob April 2018
3 Jack April 2018
How could I do that in Pandas?
The following code works, by adding keep = False:
df = df[df.duplicated(subset = ['month', 'year'], keep = False)]
df = df.sort_values(by=['name', 'month', 'year'], ascending = False)
I'm wanting to add formula to locate the Policy Year in each cell in column B (starting in B2) which is determined from interrogating the date shown in the corresponding cell in Column A and then checking whether it sits in a range (inception date and expiry date) D2:E5 The Policy Year sits in C2:C5 I've shown the values I'd expect the formula in the cells in column B to draw from Column C.
COLUMN A COLUMN B EXPECTED VALUE COLUMN C COLUMN D COLUMN E
2 April 2017 2016 2016 5 December 2016 4 December 2017
5 June 2017 2016 2017 5 December 2017 4 December 2018
6 December 2017 2017 2018 5 December 2018 4 December 2019
4 January 2018 2017 2019 5 December 2019 4 December 2020
6 August 2018 2017
4 December 2018 2017
29 December 2018 2018
6 March 2020 2019
I have a DataFrame that contains data similar to this:
Name Date A B C
John 19/04/2018 10 11 8
John 20/04/2018 9 7 9
John 21/04/2018 22 15 22
… … … … …
John 16/04/2019 8 8 9
John 17/04/2019 10 11 18
John 18/04/2019 8 9 11
Rich 19/04/2018 18 7 6
… … … … …
Rich 18/04/2019 19 11 17
The data can start on any day and contains at least 365 days of data, sometimes more. What I want to end up with is a DataFrame like this:
Name Date Sum
John April 356
John May 276
John June 209
Rich April 452
I need to sum up all of the months to get a year’s worth of data (April - March) but I need to be able to handle taking part of April’s total (in this example) from 2018 and part from 2019. What I would also like to do is shift the days so they are consecutive and follow on in sequence so rather than:
John 16/04/2019 8 8 9 Tuesday
John 17/04/2019 10 11 18 Wednesday
John 18/04/2019 8 9 11 Thursday
John 19/04/2019 10 11 8 Thursday (was 19/04/2018)
John 20/04/2019 9 7 9 Friday (was 20/04/2018)
It becomes
John 16/04/2019 8 8 9 Tuesday
John 17/04/2019 10 11 18 Wednesday
John 18/04/2019 8 9 11 Thursday
John 19/04/2019 9 7 9 Friday (was 20/04/2018)
Prior to summing to get the final DataFrame. Is this possible?
Additional information requested in comments
Here is a link to the initial data set https://github.com/stottp/exampledata/blob/master/SOExample.csv and the required output would be:
Name Month Total
John March 11634
John April 11470
John May 11757
John June 10968
John July 11682
John August 11631
John September 11085
John October 11924
John November 11593
John December 11714
John January 11320
John February 10167
Rich March 11594
Rich April 12383
Rich May 12506
Rich June 11112
Rich July 11636
Rich August 11303
Rich September 10667
Rich October 10992
Rich November 11721
Rich December 11627
Rich January 11669
Rich February 10335
Let's see if I understood correctly. If you want to sum, I suppose you mean sum the values of columns ['A', 'B', 'C'] for each day and get the total value monthly.
If that's right, the first thing to to is set the ['Date'] column as the index so that the data frame is easier to work with:
df.set_index(df['Date'], inplace=True, drop=True)
del df['Date']
Next, you will want to add the new column ['Sum'] by re-sampling your data frame (from days to months) whilst summing the values of ['A', 'B', 'C']:
df['Sum'] = df['A'].resample('M').sum() + df['B'].resample('M').sum() + df['C'].resample('M').sum()
df['Sum'].head()
Out[37]:
Date
2012-11-30 1956265
2012-12-31 2972076
2013-01-31 2972565
2013-02-28 2696121
2013-03-31 2970687
Freq: M, dtype: int64
The last part about squashing February of 2018 and 2019 together as if they were a single month might yield from:
df['2019-02'].merge(df['2018-02'], how='outer', on=['Date', 'A', 'B', 'C'])
Test this last step and see if it works for you.
Cheers
I have a chronological list of Product, Year, Month, Profit (like below).
Summary Table
Product Year Month Profit
TV 2018 1 10
TV 2018 2 20
TV 2018 3 30
TV 2018 4 50
TV 2018 5 35
TV 2018 6 60
TV 2018 7 90
Heater 2018 1 20
Heater 2018 2 3
Heater 2018 3 8
Heater 2018 4 4
Heater 2018 5 6
Heater 2018 6 11
Heater 2018 7 1
What I wanted to do is lookup another sheet that has all of the price changes within by month and year as well as the table below shows.
Sale Price
Product Year Month Price
TV 2018 1 $1,000.00
TV 2018 4 $800.00
TV 2018 7 $950.00
Heater 2018 1 $20.00
Heater 2018 2 $60.00
Heater 2018 5 $45.00
So the end result for example, TV Month = 2 and Year = 2018, I want it to pull in $1,000 to be part of my profit calculation.
to get the correct Price, use:
=INDEX(J:J,AGGREGATE(14,6,ROW($I$2:$I$7)/(($G$2:$G$7=A2)*($H$2:$H$7=B2)*($I$2:$I$7<=C2)),1))