I have a data as below. I have created column "difference in values" manually, the calculation is value at 8:15 AM - value at 8:00 AM which is 2 in second row and so on for all values of column Tushar and Lohit respectively. How can i do this calculation in Spotfire i believe over and previous function can help but i am unable find anything on this. Please help
Name Time Values Difference in values
Tushar 08:00 AM 2 0
Tushar 08:15 AM 4 2
Tushar 08:30 AM 5 1
Tushar 08:45 AM 6 1
Tushar 09:00 AM 7 1
Lohit 08:00 AM 2 0
Lohit 08:15 AM 4 2
Lohit 08:30 AM 5 1
Lohit 08:45 AM 6 1
This should work
SN([Values] - Max([Values]) over (Intersect(Previous([Time]),[Name])),0)
where Max(..) is just to have an aggregation, since it is only looking at the previous Time row for each value of Name. [so Min would work just as well].
SN(...) is there to set the result to 0 when it is empty (as in the first row of each Name).
Related
i want to add +2 days to column based on other column i use this table :
Company Type Joinning Date Starting day
1 1 19/01/2019
2 0 19/01/2019
3 0 19/01/2019
4 1 20/01/2019
5 0 20/01/2019
6 1 21/01/2019
i want to add +2 DAYS in column Starting day which is Joining day + 2 days if the company have type 1 how can i do it ?
What i've tried ?
pic
Desired Results
Company Type Joinning Date Starting day
1 1 19/01/2019 21/01/2019
2 0 19/01/2019
3 0 19/01/2019
4 1 20/01/2019 22/01/2019
5 0 20/01/2019
6 1 21/01/2019 23/01/2019
Just to show my comment of:
=IF(B2=1,C2+2,"")
Works. The output cell must be formatted in the desired method:
Hello I have to count how many people were scheduled on each hour in excel so I transformed starting and ending data/time to only contain time and basing on it I tried to substract these two information but I only get an hour then but what I need is the hours to be like this:
instead
starting on 9:00
ending on 17:00
this
9:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
to count every hour that employee was at work. But I don't know how :(
Or is there a better way of doing that?
Assuming your table looks something like this:
Person
Start
End
09:00
10:00
11:00
12:00
13:00
14:00
15:00
Alice
08:35
16:35
1
1
1
1
1
1
1
Bob
09:35
17:35
0
1
1
1
1
1
1
Carl
10:35
18:35
0
0
1
1
1
1
1
Dan
11:35
19:35
0
0
0
1
1
1
1
Ed
12:35
20:35
0
0
0
0
1
1
1
Total present
1
2
3
4
5
5
5
You can compute the entries 0 or 1 in each cell under the times using the formula
=IF(AND((E$4>$C6);(E$4<=$D6));1;0)
In the formula, E$4 is a reference to the column header, e.g. "9:00", $C6 and $D6 are references to the start and end times of the person. They are defined using partial absolute references ($) so the same formula can be copied and pasted in all the cells.
The result will be 1 if the person was present at that time and 0 if not.
The "Total present" formulas just sum up the 1's and 0's in the column.
I have the following Excel spreadsheet
A B C D
1 Product ID Time of Event
2 27152 01.04.2017 08:45:00 27152 70 Min.
3 27152 01.04.2017 09:00:00 29297 108 Min.
4 27152 01.04.2017 09:55:00 28802 28 Min.
5 29297 02.04.2017 11:02:00
6 29297 02.04.2017 12:50:00
7 28802 18.04.2017 11:48:00
8 28802 18.04.2017 12:00:00
9 28802 18.04.2017 12:13:00
10 28802 18.04.2017 12:16:00
In Column A you can find different Product IDs.
In Column B the time when an event happens in the Product ID.
Each event is listed in the table; therefore, a ProductID can appear
several times in Column A.
In Column D I want to show now the difference in minutes between
the first and the last event which happens in a product ID.
D2 = 9:55:00 - 8:45:00 = 70 Min.
D3 = 12:50:00 - 11:02:00 = 108 Min.
D4 = 12:16:00 - 11:48:00 = 28 Min.
Therefore, I would need something like a DIFFERENCE-IF-Formula.
One of my ideas so far was going by the LARGE and SMALL function.
=LARGE(B2:B4;1)-SMALL(B2:B4;1)
However, this way I would have to find each array (B2:B4, B5:B6, B7:B10) seperatly; therefore, I would prefer to have the productID as a criteria in the formula.
Summarized:
Do you have any idea how I could calculate the difference in minutes between the last and the first event of a certain ProdcutID in the list?
I would prefer to avoid any kind of array formula.
=ROUND(MMULT(AGGREGATE({14,15},6,B$2:B$10/(A$2:A$10=C2),1),{1;-1})*1440,1)&" Min"
and copied down.
I've a feeling the separators for horizontal and vertical arrays in German versions of Excel are the period (.) and semicolon (;) respectively, so I believe you'll need:
=RUNDEN(MMULT(AGGREGAT({14.15};6;B$2:B$10/(A$2:A$10=C2);1);{1;-1})*1440;1)&" Min"
though please let me know if that doesn't give the required results.
Regards
With some conditions,
1. assuming that you convert column B into 2 columns
2. times is in ascending order
A B C
Product ID Time of Event TIMES
27152 01.04.2017 8:45:00
27152 01.04.2017 9:00:00
27152 01.04.2017 9:55:00
29297 02.04.2017 11:02:00
29297 02.04.2017 12:50:00
28802 18.04.2017 11:48:00
28802 18.04.2017 12:00:00
28802 18.04.2017 12:13:00
28802 18.04.2017 12:16:00
This will work without using array
=(INDEX($C$2:$C$10,SUMPRODUCT(MAX(ROW($A$2:$A$10)*(D2=$A$2:$A$10))-1))-INDEX($C$2:$C$10,MATCH(D2,$A$2:$A$10,0)))*1440
Convert time into minutes
=(time*1440)
Look for first matching value
=INDEX($C$2:$C$10,MATCH(D2,$A$2:$A$10,0))
Look for last matching value
=INDEX($C$2:$C$10,SUMPRODUCT(MAX(ROW($A$2:$A$10)*(D2=$A$2:$A$10))-1)
NOTE If last value is SMALLER then first value, you will receive an error.
I have an Excel file looks like below in Excel:
2016-1-1 2016-1-2 2016-1-3 2016-1-4
300100 am 1 3 5 1
pm 3 2 4 5
300200 am 2 5 2 6
pm 5 1 3 7
300300 am 1 6 3 2
pm 3 7 2 3
300400 am 3 1 1 3
pm 2 5 5 2
300500 am 1 6 6 1
pm 5 7 7 5
But after I imported it by pd.read_excel and printed it, it was displayed like below in Python:
2016-1-1 2016-1-2 2016-1-3 2016-1-4
300100 am 1 3 5 1
NaN pm 3 2 4 5
300200 am 2 5 2 6
NaN pm 5 1 3 7
300300 am 1 6 3 2
NaN pm 3 7 2 3
300400 am 3 1 1 3
NaN pm 2 5 5 2
300500 am 1 6 6 1
NaN pm 5 7 7 5
How can I solve this to make the Dataframe look like the format in Excel, without so many "NaN"? Thanks!
Most of the time when Excel looks like what you have in your example, it does actually have blanks where those spaces are. But, the cells are merged, so it looks pretty. When you import it into pandas, it reads them as empty or NaN.
To fix it, forward fill the empty cells, then set as the index.
df.ffill()
Without access to the Excel files or knowledge of the versions it's impossible to be sure, but it just looks like you have a column of numbers (the first column) with every other row blank. Pandas expects uniformly filled columns, so while in Excel you have a sort of "structure" of the information for both AM and PM for each first-column number (id?), Pandas just sees two rows, one with an invalid first column. Depending on how you actually want to access this data, an easy fix would be to replace every NaN with the number directly above it, so each row contains either the AM or PM information for the "id". Another fix would be to change your column structure to have 2016-1-1-am and 2016-1-1-pm fields.
You're looking for the fillna method:
df = df.fillna('')
I have the following data set with 2 columns - Period, Score
Period Score
3/1/2016 2
3/1/2017 3
12/1/2018 3
3/1/2016 3
3/1/2017 3
12/1/2018 3
3/1/2016 2
3/1/2017 3
12/1/2018 4
3/1/2016 2
3/1/2017 3
12/1/2018 4
3/1/2016 2
3/1/2017 2
I am looking for an expression which finds out the Difference of average scores between the first and last period. In the above example,
Average Score in first period = Avg(score) in 3/1/2016 = (2+3+2+2)/4 = 2.25
Average Score in last period = Avg(score) in 12/1/2018 = (3+3+4+4)/4 = 3.5
Difference in average score change between first and last period = 3.5 - 2.25 = 1.25
Calculated column 1: Average Score Over Period
Avg([Score]) OVER ([Period])
Calculated column 2: Difference
Max([Average Score Over Period]) - Min([Average Score Over Period])