I have unique number of items and invoices, but one invoice can have multiple items.
A B C D
1 Invoice Items
2 1 10
3 2 20
4 1 30
idea is sort it to horizontaly via this formula
=IFERROR(INDEX($B$2:$B$8;SMALL(IF($D$2=$A$2:$A$8;ROW($A$2:$A$8)-ROW($A$2)+1);COLUMN(A1)));"")
result:
A B C D E F
1 Invoice Items Invoice Item1 Item2
2 1 10 1 10 30
3 2 20
4 1 30
But my geal is setup results horizontaly:
A B
1 Invoice Items
2 1 10
3 1 30
4 2 20
Is that even possible ?
Is your goal actually to sort on Invoice first and then on Items? If so, why just not using sort on two levels using the build in option?
Input:
Sort:
Output:
It's in Dutch but you'll get the idea :)
Related
I have the following DataFrame:
Segments Airline_pct_tesco Airline_pct_asda food_pct_tesco food_pct_asda Airline_diff food_diff
A 1 2 4 2 -1 2
B 2 2 4 4 0 0
c 10 5 12 10 5 2
I want to convert it to this format:
Segments Category Asda% Tesco% Diff%
A Airline 2 1 -1
b Food 4 4 0
c Airline 5 10 5
A Food 2 4 2
(only partially showing). Note
category is the col name without the '_pct_tesco' or '_diff' or '_pct_asda'
I am unsure how to go about this - I have tried transform but I just don't know how I can get it in a way which is easy for any user to use. I am doing this in pandas and am not sure how to even begin! The Asda% are related to '_pct_asda' columns and same for diff and tesco columns respectively..
Let's try set_index to save columns, then create a MultiIndex.from_frame using str.extract on the columns to create a MultiIndex based on the values before a list of suffixes, then stack to go to long-form.
new_df = df.set_index('Segments')
# Define allowed suffixes here
suffixes = ['_pct_asda', '_pct_tesco', '_diff']
# Extract Values
new_df.columns = (
pd.MultiIndex.from_frame(
new_df.columns.str.extract(rf'(.*?)({"|".join(suffixes)})'),
names=['Category', None]
)
)
new_df = new_df.stack(0)
new_df:
_diff _pct_asda _pct_tesco
Segments Category
A Airline -1 2 1
food 2 2 4
B Airline 0 2 2
food 0 4 4
c Airline 5 5 10
food 2 10 12
To get cleaner output add reset_index + rename to fix column names and index and also re-order columns.
new_df = new_df.reset_index().rename(columns={
'_pct_asda': 'Asda%',
'_pct_tesco': 'Tesco%',
'_diff': 'Diff%'
})[['Segments', 'Category', 'Asda%', 'Tesco%', 'Diff%']]
new_df:
Segments Category Asda% Tesco% Diff%
0 A Airline 2 1 -1
1 A food 2 4 2
2 B Airline 2 2 0
3 B food 4 4 0
4 c Airline 5 10 5
5 c food 10 12 2
Hope someone can help me out with what is probably quite a simple thing in Excel but I just can't seem to be able to work it out. I have a table of numbers which correspond to colour codes:
A
B
C
D
E
F
2
2
2
2
2
24
36
36
2
2
2
24
2
2
2
2
2
2
36
2
36
2
2
24
2
2
36
2
2
2
2
36
2
2
2
24
2
2
2
2
36
2
What I would like to able to have is some way of having a total based on the criteria:
Count the total number of times '36' appears in the table only if the row has '24' in column F
I've tried using COUNTIF and COUNTIFS but that only works for matching sized columns of data.
Any help would be really appreciated.
Use SUMPRODUCT:
=SUMPRODUCT((A1:E7=36)*(F1:F7=24))
I have an Excel file like this, where column A and B are given. I want to add column C and D that represent days. D is pretty easy, because it is always one day. C is tricky, because I want to count only "unique" days, where a branch can be one day maximum, where D counts all days.
A B C D
Row Name Branch Unique Overall
1 Jack Health 1 1
2 Jack Health 0 1
3 Jack Food 1 1
4 Jolie Tech 1 1
5 Jolie Food 1 1
6 Jolie Tech 0 1
7 Jolie Health 1 1
I need column C and D for a pivot table like this:
Branch Unique Overall
Health 2 3
Food 2 2
Tech 1 2
I also could add names as a sub position.
Branch Unique Overall
Health 2 3
-Jack 1 2
-Jolie 1 1
Food 2 2
-Jack 1 1
-Jolie 1 1
Tech 1 2
-Jolie 1 2
But that´s something, that can be done after preparing the data and what comes with the program anyway. So how can I design a formula that counts only unique branches for a data set of hundreds of rows?
Thank you!
In C2 put:
=--(COUNTIFS($A$2:A2,A2,$B$2:B2,B2)=1)
Then copy down
I have a couple of columns as shown below:
A B C D E
1 12 4 1
2 3 2 2
3 7
4 3 0 6
How would I be able to return a count of each column above so for example receive the result:
A B C D E
1 12 4 1
2 3 2 2
3 7
4 3 0 6
5 count:3 4 2 1
for each of the column. Im looking for a formula that would be able to do that in one cell(B5) returning a count for each of the columns, and avoid using fill handling as the data set is quite large
It's pretty easy, using Google Spreadsheet's functions:
=ArrayFormula(MMULT(TRANSPOSE(row(A1:A4)^0),--(len(A1:E4)>0)))
Or, if you want join them all:
=JOIN(", ",ArrayFormula(MMULT(TRANSPOSE(row(A1:A4)^0),--(len(A1:E4)>0))))
I need to determine the range to apply the Frequency function. Here's what the problem is. On the given sheet, I have subtotals for my data and there is a column which has "Stop" Values.
The data would look something like:
Route1
Order# Stop# Qty
001016 1 5
008912 1 5
062232 2 6
062232 3 2
069930 4 1
1000 4 3
1001 4 4
1001 5 8
1003 8 1
Route 1 Subtotal 6 35
Route2
Order# Stop# Qty
10065 1 5
10076 1 5
10077 2 6
10079 3 2
10087 4 1
10098 4 3
10109 4 4
10171 5 8
10175 8 1
Route 2 Subtotal 6 35
How do I write VBA code for calculating the distinct stop values. I need the distinct count of the stop#. Hence in the example above you can see that the total stops are 6 because 1 stop can have multiple orders and 1 route can have multiple orders/stop. Hope I am making sense here. Let me know how I would write my VBA code for this. Thanks for your help.
For the Stop Subtotal unique count, try this formula (adjust ranges as required):
=COUNT(1/FREQUENCY(B2:B10,B2:B10))