I have a spreadsheet where dates are being recorded in regards to individuals, with additional data, as such:
Tom | xyz | 5/2/2012
Dick | foo | 5/2/2012
Tom | bar | 6/1/2012
On another sheet there is a line in which I want to be able to put in the name, such as Tom, and retrieve on the following cell through a formula the data for the LAST (most recent by date) entry in the first sheet. So the first sheet is a log, and the second sheet displays the most recent one. In the following example, the first cell is entered and the remaining are formulas displaying data from the first sheet:
Tom | bar | 6/1/2012
and so on, showing the latest dated entry in the log.
I'm stumped, any ideas?
If you only need to do a single lookup, you can do that by adding two new columns in your log sheet:
Sheet1
| A | B | C | D | E | F
1 | Tom | xyz | 6/2/2012 | | * | *
2 | Dick | foo | 5/2/2012 | | * | *
3 | Tom | bar | 6/1/2012 | | * | *
Sheet2
| A | B | C
1 | Tom | =Sheet1.E1 | =Sheet1.F1
*(E1) = =IF(AND($A1=Sheet2.$A$1;E2=0);B1;E2)
(i.e. paste the formula above in E1, then copy/paste it in the other cells with *)
Explanation: if A is not what you're looking for, go for the next; if it is, but there is a non-empty next, go for the next; otherwise, get it. This way you're selecting the last one corresponding to your search. I'm assuming you want the last entry, not "the one with the most recent date", since that's what you asked in your example. If I interpreted your question wrong, please update it and I can try to provide a better answer.
Update: If the log dates can be out of order, here's how you get the last entry:
*(F1) = =IF(AND($A1=Sheet2.$A$1;C1>=F2);C1;F2)
*(E1) = =IF(C1=F1;B1;E2)
Here I just replaced the test F2=0 (select next if non-empty) for C1>=F2 (select next if more recent) and, for the other column, select next if the first test also did so.
Disclaimer: I'm very inexperienced with spreadsheets, the solution above is ugly but gets the job done. For instance, if you wanted a 2nd row in Sheet2 to do another lookup, you'd need to add two more columns to Sheet1, etc.
Related
I have two dataframes. One is a set of ≈4000 entries that looks similar to this:
| grade_col1 | grade_col2 |
| --- | --- |
| A-| A-|
| B | 86|
| C+| C+|
| B-| D |
| A | A |
| C-| 72|
| F | 96|
| B+| B+|
| B | B |
| A-| A-|
The other is a set of ≈700 entries that look similar to this:
| grade | scale |
| --- | --- |
| A+|100|
| A+| 99|
| A+| 98|
| A+| 97|
| A | 96|
| A | 95|
| A | 94|
| A | 93|
| A-| 92|
| A-| 91|
| A-| 90|
| B+| 89|
| B+| 88|
...and so on.
What I'm trying to do is create a new column that shows whether grade_col2 matches grade_col1 with a binary, 0-1 output (0 = no match, 1 = match). Most of grade_col2 is shown by letter grade. But every once in awhile an entry in grade_col2 was accidentally entered as a numeric grade instead. I want this match column to give me a "1" even when grade_col2 is a numeric grade instead of a letter grade. In other words, if grade_col1 is B and grade_col2 is 86, I want this to still be read as a match. Only when grade_col1 is F and grade_col2 is 96 would this not be a match (similar to when grade_col1 is B- and grade_col2 is D = not a match).
The second data frame gives me the information I need to translate between one and the other (entries between 97-100 are A+, between 93-96 are A, and so on). I just don't know how to run a script that uses this information to find matches through all ≈4000 entries. Theoretically, I could do this manually, but the real dataset is so lengthy that this isn't realistic.
I had been thinking of using nested if_else statements with dplyr. But once I got past the first "if" statement, I got stuck. I'd appreciate any help with this people can offer.
You can do this using a join.
Let your first dataframe be grades_df and your second dataframe be lookup_df, then you want something like the following:
output = grades_df %>%
# join on look up, keeping everything grades table
left_join(lookup_df, by = c(grade_col2 = "scale")) %>%
# combine grade_col2 from grades_df and grade from lookup_df
mutate(grade_col2b = ifelse(is.na(grade), grade_col2, grade)) %>%
# indicator column
mutate(indicator = ifelse(grade_col1 == grade_col2b, 1, 0))
I'm looking to get the count of query param usage from the query string from page views stored in app insights using KQL. My query currently looks like:
pageViews
| project parsed=parseurl(url)
| project keys=bag_keys(parsed["Query Parameters"])
and the results look like
with each row looking like
I'm looking to get the count of each value in the list when it is contained in the url in order to anwser the question "How many times does page appear in the querystring". So the results might look like:
Page | From | ...
1000 | 67 | ...
Thanks in advance
you could try something along the following lines:
datatable(url:string)
[
"https://a.b.c/d?p1=hello&p2=world",
"https://a.b.c/d?p2=world&p3=foo&p4=bar"
]
| project parsed = parseurl(url)
| project keys = bag_keys(parsed["Query Parameters"])
| mv-expand key = ['keys'] to typeof(string)
| summarize count() by key
which returns:
| key | count_ |
|-----|--------|
| p1 | 1 |
| p2 | 2 |
| p3 | 1 |
| p4 | 1 |
I'm trying to update a table column from another table with the code below.
Now the editor says '39 rows affected' and I can see something happened because some cells changed from null to empty (nothing shows).
While orhers are still null
What could be wrong here?
Why does it not update properly....
PS: I checked manually that the values are not empty in the column to check for.
UPDATE CANZ_CONC
SET EAN = (SELECT t1.EAN_nummer FROM ArtLev_CONC t1 WHERE t1.Artikelcode_leverancier = Artikelcode_leverancier)
WHERE ARTNMR IN (SELECT t1.Artikelcode_leverancier FROM Artlev_CONC t1 WHERE t1.Artikelcode_leverancier = ARTNMR);
Edit:
The tabel2 is like:
NMR | EAN | CUSTOM
-------------------------------
1 | 987 | A
2 | 654 | B
3 | 321 | C
Tabel 1 is like
NMR | EAN | CUSTOM
-------------------------------
1 | null | null
2 | null | null
5 | null | null
After the UPDATE table1 is like
NMR | EAN | CUSTOM
-------------------------------
1 | | null
2 | | null
5 | null | null
I've got this working.
I guess my data was corrupted after all.
Since it is about 330.000 rows it was not very easy to spot.
But it came to me when the loading of the data took about 10 minutes!
It used to be about 40 - 60 seconds.
So I ended up back at the drawing board for the initial csv file.
I also saw the columns had not been given a DATA type, so I altered that as well.
Thanx for the help!
Maybe this is related to math.stacexhange, but I am affraid, that I will get a formula in answer what I won't undersand.
I have products in our database, and I have products from different suppliers in another table.
What I want is to pair, these supplieres products to our products if it is possible, or show for me at least show me a list, where the matching is high.
I did iterate throught all the suppliers products, and explodes the product name by spaces, and store it in a table, and the count of the occurence.
The table seems like this.
+--------+-------------+---------------+-------+
| id | word | originalWord | count |
+--------+-------------+---------------+-------+
| 220950 | Tracer | Tracer | 493 |
| 220951 | Destroyer | Destroyer | 3 |
| 220952 | Avago5050 | Avago5050 | 4 |
| 220953 | mouse | mouse | 2535 |
| 220954 | TRAMYS44916 | /TRAMYS44916/ | 2 |
| 220955 | GameZone | GameZone | 16 |
| 220956 | Enduro | Enduro | 3 |
| 220957 | AVAGO | AVAGO | 10 |
| 220958 | 5050 | 5050 | 4 |
| 220959 | optical | optical | 2370 |
| 220960 | USB | USB | 6160 |
+--------+-------------+---------------+-------+
and so on. Of course, in another table I stored, what is the product id for each word.
So what I want is to determine the weight of a word by occurence.
As you see, the word TRAMYS44916 is occured only twice, almost certain that is a partnumber, so this is the most heavy word. It weight should be 1.
Let's say the most occured is USB with 6160 occurence, so it weight should be like 0.01 or something like that, I think.
What is the best way to get all the weights of the words?
There are other tables for other suppliers so dispersion is always change.
This reminds me of Naive Bayes text classification, so to determine which product should it belongs to, you can calculate tf-idf of all the words.
Then if you want to pair it from another product name, you can decompose it to words again and select the product id based on the highest term value, however maybe you should specify some threshold for this, because in some cases it would not be that clear.
tf-idf = ("number of word matches in product name"/"word count of product name") * log ("number of products" / "number of products that contains the word")
You can see how it is done in the example here (In your case the document will be the product full name): https://en.wikipedia.org/wiki/Tf–idf#Example_of_tf.E2.80.93idf
Example implementation in Java: https://guendouz.wordpress.com/2015/02/17/implementation-of-tf-idf-in-java/
I have two tables
Names
id | name
---------
5 | bill
15 | bob
10 | nancy
Entries
id | name_id | added | description
----------------------------------
2 | 5 | 20140908 | i added this
4 | 5 | 20140910 | added later on
9 | 10 | 20140908 | i also added this
1 | 15 | 20140805 | added early on
6 | 5 | 20141015 | late to the party
I'd like to order Names by the first of the numerically-lowest added values in the Entries table, and display the rows from both tables ordered by the added column overall, so the results will be something like:
names.id | names.name | entries.added | entries.description
-----------------------------------------------------------
15 | bob | 20140805 | added early on
5 | bill | 20140908 | i added this
10 | nancy | 20140908 | i also added this
I looked into joins on the first item (e.g. SQL Server: How to Join to first row) but wasn't able to get it to work.
Any tips?
Give this query a try:
SELECT Names.id, Names.name, Entries.added, Entries.description
FROM Names
INNER JOIN Entries
ON Names.id = Entries.name_id
ORDER BY Entries.added
Add DESC if you want it in reverse order i.e.: ORDER BY Entries.added DESC.
This should do it:
SELECT n.id, n.name, e.added, e.description
FROM Names n INNER JOIN
(SELECT name_id, description, Min(added) FROM Entries GROUP BY name_id, description) e
ON n.id = e.name_id
ORDER BY e.added