As an athlete I want to keep track of my progression in Excel.
I need a formula that looks for the fastest time ran in a given season. (The lowest value in E for a given year. For 2017, for example, this is 13.32, for 2018 12 and so on.
Can you help me further?
Instead of formula you can use PIVOT
Keep the Year in Report Filter and Time into Value. Then on value field setting select min as summarize value by.
So every you change the year in the Filter the min value will show up.
=AGGREGATE(15,6,E3:E6/(B3:B6=2017),1)
15 tell aggregate to sort the results in ascending order
6 tells aggregate to ignore any errors such as when you divide by 0
E3:E6 is your time range
B3:B6 is you Year as an integer.
B3:B6=2017 when true will be 1 and false will be 0 (provide it goes through a math operation like divide.
1 tells aggregate to return the 1st value in the sorted list of results
Related
I'm creating an excel spreadsheet to track when an item is received as well as when a response to the item having been received has been made (ie: my mail was delivered at 1:00pm (item received) but I didn't check the mail until 5:00pm (response to item having been received)).
I need to track both the date and time of the item being received and want to separate these in two separate columns. At the moment this translates to:
Column A: Date item received
Column B: Time item received
Column L: Date item was responded to having been received
Column M: Time item was responded to having been received
In essence I'm looking to run calculations on the response time between when the item is received and when it has been responded to (ie: average response time, number of responses in less than an hour, and even things like the number of responses that took between 2 and 3 hours where Bob was the person who responded).
The per-line pseudo code would look something like:
(Lr + Mr) - (Ar + Br) ' where L,M,A,B are the columns and 'r' is the row number.
An example, with the following data:
1. A B L M
2. 1/5/19 10:00 1/5/19 12:00
3. 1/5/19 21:00 1/6/19 1:00
4. 1/5/19 22:00 1/5/19 23:00
5. 1/6/19 3:00 1/6/19 4:00
The outcome for the average response time would be 2 hours (average(rows 2-5) = average(2, 4, 1, 1) = 2)
The number of items with an average response times would be as follows:
(<=1 hour) = 2
(>1 & <=2) = 2
(>2 & <=3) = 0
(>3) = 1
I don't know (or can find) a function that will perform this and then let me use it within something like a countifs() or averageifs() function.
While I could do this (fairly easily) in VBA, the practical implementation of this spreadsheet limits me to standard Excel. I suspect that sumproduct() will be fundamental to make this work, but I feel that I need something like a sumsum() function (which doesn't exist) and I'm not familiar with sumproduct() to better understand what to even look for to set something like this up.
If you are not so familiar with SUMPRODUCT() or the likes I would suggest one helper column. Like so:
You can see the formula used is:
=((C2+D2)-(A2+B2))
You can probably do all type of calculations on this helper column. Note, column is formatted hh:mm. However, if you want to look into SUMPRODUCT() you could think about these:
Formula in H2:
=SUMPRODUCT(--(ROUND((((A2:A5+B2:B5)-(C2:C5+D2:D5))*-24),2)<=1))
Formula in H3:
=SUMPRODUCT((ROUND((((A2:A5+B2:B5)-(C2:C5+D2:D5))*-24),2)>1)*(ROUND((((A2:A5+B2:B5)-(C2:C5+D2:D5))*-24),2)<=2))
Formula in H4:
=SUMPRODUCT((ROUND((((A2:A5+B2:B5)-(C2:C5+D2:D5))*-24),2)>2)*(ROUND((((A2:A5+B2:B5)-(C2:C5+D2:D5))*-24),2)<3))
Formula in H5:
=SUMPRODUCT(--(ROUND((((A2:A5+B2:B5)-(C2:C5+D2:D5))*-24),2)>3))
The helper column is the easiest approach. It gives you the time differences that you can then easily analyse however you want. Analysis without the helper column is possible, but the approach differs depending on what type of analysis you want to do.
For the example you provided, which is counting the number of time differences grouped into ranges, you would use the FREQUENCY function:
=FREQUENCY(C2:C5+D2:D5-A2:A5-B2:B5,F2:F4)
In F2:F4 (called the "bins"), enter the upper limit of each range you want to count. The Frequency function counts up to and including the first value, then counts from there up to and including the second value, and so on. Enter the bins as times, e.g. 1:00 for 1 hour.
Note that Frequency is an array-entered and an array-returning function. This you means you need to first select the range that will contain all output values, G2:G5 in this example, then enter the function, then press CTRL+SHIFT+ENTER
Also note that Frequency returns an array that is one element larger than the number of bins specified. The extra element is the count of all values greater than the largest bin specified.
I'm looking to perform data analysis on 100-years of climatological data for select U.S. locations (8 in particular), for each day spanning the 100-years. I have a pandas dataFrame set up with columns for Max temperature, Min temperature, Avg temperature, Snowfall, Precip Total, and then Day, Year, and Month values (then, I have an index also based on a date-time value). Right now, I want to set up a for loop to print the first Maximum temperature of 90 degrees F or greater from each year, but ONLY the first. Eventually, I want to narrow this down to each of my 8 locations, but first I just want to get the for loop to work.
Experimented with various iterations of a for loop.
for year in range(len(climate['Year'])):
if (climate['Max'][year] >=90).all():
print (climate.index[year])
break
Unsurprisingly, the output of the loop I provided prints the first 90 degree day period (from the year 1919, the beginning of my data frame) and breaks.
for year in range(len(climate['Year'])):
if (climate['Max'][year] >=90).all():
print (climate.index[year])
break
1919-06-12 00:00:00
That's fine. If I take out the break statement, all of the 90 degree days print, including multiple in the same year. I just want the first value from each year to print. Do I need to set up a second for loop to increment through the year? If I explicitly state the year, ala below, while trying to loop through a counter, the loop still begins in 1919 and eventually reaches an out of bounds index. I know this logic is incorrect.
count = 1919
while count < 2019:
for year in range(len(climate['Year'])):
if (climate[climate['Year']==count]['Max'][year] >=90).all():
print (climate.index[year])
count = count+1
Any input is sincerely appreciated.
You can achieve this without having a second for loop. Assuming the climate dataframe is ordered chronologically, this should do what you want:
current_year = None
for i in range(climate.shape[0]):
if climate['Max'][i] >= 90 and climate['Year'][i] != current_year:
print(climate.index[i])
current_year = climate['Year'][i]
Notice that we're using the current_year variable to keep track of the latest year that we've already printed the result for. Then, in the if check, we're checking if we've already printed a result for the year of the current row in the loop.
That's one way to do it, but I would suggest taking a look at pandas.DataFrame.groupby because I think it fits your use case well. You could get a dataframe that contains the first >=90 max days per year with the following (again assuming climate is ordered chronologically):
climate[climate.Max >= 90].groupby('Year').first()
This just filters the dataframe to only contain the >=90 max days, groups rows from the same year together, and retains only the first row from each group. If you had an additional column Location, you could extend this to get the same except per location per year:
climate[climate.Max >= 90].groupby(['Location', 'Year']).first()
I have a rather big (long) table and need to do something quite simple but I'm currently with a sort of blackout...
Imagine that you have:
Date 1 Value 1 Date 2 Value 2 Date 3 Value 3 Date of MAX
... ... ... ... ... ... ????
I want to deploy in ???? a formula that will result in the date at which the maximal value (between Value 1...3) was registered. For instance:
Date 1 Value 1 Date 2 Value 2 Date 3 Value 3 Date of MAX
20160501 10 20160722 47 20161002 9 20160722
meaning, the Date of MAX is of Date 2 because that was the date at which the MAX was measured.
Thanks in advance.
You could do a more general solution using offset:-
=MAX(N(OFFSET(D2,0,COLUMN(A:D)*3)))
to find the largest value - put this in (say) R2.
Then find a match for it and pick out the corresponding date:-
=OFFSET(C2,0,MATCH(R2,N(OFFSET(D2,0,COLUMN(A:D)*3)),0)*3)
assuming the dates and values are every third column.
These are array formulae and must be entered with CtrlShiftEnter
If the last value really was in P21 you would have to give a row offset as well as a column offset.
OK, I found a dirty but simple solution (don't know why I didn't think of it at first):
=IF(G2>=MAX(G2,J2,M2,P21),F2,IF(J2>=MAX(G2,J2,M2,P21),I2,IF(M2>=MAX(G2,J2,M2,P21),L2,O2)))
where the pairs (4 of them) are at FG, IJ, LM, OP. Not elegant but does the job.
I am starting with DAX.
I have a standard date table and a table with sales. When I try to show the running total with the below formula the month filter is ignored, as shown:
The formula is:
Prov YTD VJ 2:=CALCULATE(FIRMPROV[SumProv];
All(Kalender[Jahr]);
DATESBETWEEN(Kalender[Datum];
Min(START_YTD[start_ytd]);
MIN(END_YTD[end_ytd])))
A good way to calculate running totals is by using the FILTER and EARLIER functions, but a prerequisite to that is that you need to create a Month Number column (ie. Jan = 1, Feb = 2, Mar = 3, etc.)
Then, you can use the following DAX:
CALCULATE(SUM([SumProv]),ALL(FirmProv),FILTER(FirmProv,[Month Number]<=EARLIER([Month Number])))
EARLIER basically is DAX's way of interpreting the current row. You're telling DAX to sum ALL of the rows in the FirmProv table where the month number is less than or equal to the current row (AKA running total).
Here's the result (note the numbers aren't exactly like yours, I just quickly mocked it up to show the example):
Ive spent the last 2 days trying to get this, and I really just need a few pointers. Im using Excel 2010 w/ Power Pivot and calculating inventories. I am trying to get the amount sold between 2 dates. I recorded the quantity on hand if the item was in stock.
Item # Day Date Qty
Black Thursday 11/6/2014 2
Blue Thursday 11/6/2014 3
Green Thursday 11/6/2014 3
Black Friday 11/7/2014 2
Green Friday 11/7/2014 2
Black Monday 11/10/2014 3
Blue Monday 11/10/2014 4
Green Monday 11/10/2014 3
Is there a way to do this in dax? I may have to go back and calculate the differences for each record in excel, but Id like to avoid that if possible.
Somethings that have made this hard for me.
1) I only record the inventory Mon-Fri. I am not sure this will always be the case so i'd like to avoid a dependency on this being only weekdays.
2) When there is none in stock, I dont have a record for that day
Ive tried, CALCULATE with dateadd and it gave me results nearly right, but it ended up filtering out some of the results. Really was odd, but almost right.
Any Help is appreciated.
Bryan, this may not totally answer your question as there are a couple of things that aren't totally clear to me but it should give you a start and I'm happy to expand my answer if you provide further info.
One 'pattern' you can use involves the TOPN function which when used with the parameter n=1 can return the earliest or latest value from a table that it sorts by dates and can be filtered to be earlier/later than dates specified.
For this example I am using a 'disconnected' date table from which the user would select the two dates required in a slicer or report filter:
=
CALCULATE (
SUM ( inventory[Qty] ),
TOPN (
1,
FILTER ( inventory, inventory[Date] <= MAX ( dates[Date] ) ),
inventory[Date],
0
)
)
In this case the TOPN returns a single row table of the latest date earlier than or equal to the latest date provided. The 1st argument in the TOPN specifies the number of rows, the second the table to use, the 3rd the column to sort on and the 4th says to sort descending.
From here it is straightforward to adapt this for a second measure that finds the value for the latest date before or equal to the earliest date selected (i.e. swap MIN for MAX in MAX(dates[Date])).
Hope this helps.
Jacob
*prettified using daxformatter.com