For example I have 3 different entities
#action = eat,run,walk
#person = Michael, John, Fred
#emotion = angry,sad,happy
I want to count user entered action and person entities
If bot recognizes
entities['action'].size() + entities['person'].size() > 2
Any other way to achieve this?
To account for one of the entities not being recognized, you can use ternary operator <Expression> ? <what_to_do_when_true> : <what_to_do_when_false>.
So, in your example the condition would look like this:
((entities['action'] != null ? entities['action'].size() : 0) + (entities['action'] != null ? entities['person'].size() : 0)) > 2
When one of the entity is not recognized (null), the value counted will be 0.
Related
Here is my data set.
Data in
I'd like to check if the gender with "Potential Original" matched the gender with "Potential Duplicate'. There is no specified group but 1 duplicate + 1 or more original acted like a group.
Here is the output I want (for duplicate it's NA because it's comparing to itself).
Data out
Appreciate your help. Thanks.
Thanks Rahul for looking into this. This is what I tried and I think it worked. The logic is to create the seq # first for each block of Duplicate and Original and then pull the lag value with corresponding distance.
library(data.table)
setDT(df)[, counter := seq_len(.N), by = list(cumsum(Status == "Potential
Duplicate"))]
for (i in 1:nrow(df)) {
if (df$Status[i]=="Potential Duplicate") {
df$Gender_LAG[i] <-df2$Gender[i]
}
else {
df$Gender_LAG[i]<-df2$Gender[i-df2$counter[i]+1]
}
}
Thanks.
Looking forwards to seeing other options.
My model:
class User(ndb.Model):
name = ndb.StringProperty()
Is there any difference in terms of efficiency/cost/speed between the following two queries?
u = User.query(User.name==name).get()
u = User.query().filter(User.name==name).get()
Should I use one of them over the other? I assume the 2nd one is worse because it firsts get the entire User class queryset and then applies the filter?
There is no difference in functionality between the two so you can choose whatever you like best. On the google documentation, they show these two examples:
query = Account.query(Account.userid >= 40, Account.userid < 50)
and
query1 = Account.query() # Retrieve all Account entitites
query2 = query1.filter(Account.userid >= 40) # Filter on userid >= 40
query3 = query2.filter(Account.userid < 50) # Filter on userid < 50 too
and state:
query3 is equivalent to the query variable from the previous example.
I want to select data as per below criteria in Netezza.
can someone help me to write the sql.
Case 1: Unique ID has 2 "."s
Deal ID = Parse from UNIQ_ID. Pos 1 to first "."
E.g.
Unique ID = 0000149844.FXFWD.COIBI_I
Deal ID = 0000149844
Case 2: Unique ID has 1 "."s
Deal ID = Parse from UNIQ_ID. First "." to end
E.g
Unique ID = 25808.1234140AT`enter code here`
Deal ID = 1234140AT
Use "position" function of Netezza to determine the position of ".", Make use of this output in "substr" function to extract required fields.
For Case 1 :
select substr('0000149844.FXFWD.COIBI_I',1,(position('.' in '0000149844.FXFWD.COIBI_I') - 1));
For Case 2 :
select substr('25808.1234140AT',(position('.' in '25808.1234140AT') + 1));
I'm building an application that needs to allow the user to filter a data table according to different filters. So, the user will have three different filter posibilites but he might use only one, or two or the three of them at the same tame.
So, let's say I have the following columns on the table:
ID (int) PK
Sede (int)
Programa (int)
Estado (int)
All of those columns will store numbers, integers. The "ID" column is the primary key, "Sede" stores 1 or 2, "Programa" is any number between 1 and 15, and "Estado" will store numbers between 1 and 13.
The user may filter the data stored in the table using any of those filters (Sede, Programa or Estado). But the might, as well, use two filters, or the three of them at the same time.
The idea is that this application works like the data filters on Excel. I created a simulated table on excel to show what I want to achieve:
This first image shows the whole table, without applying any filter.
Here, the user selected a filter for "Sede" and "Programa" but leaved the "Estado" filter empty. So the query returns the values that are equal to the filter, but leaves the "Estado" filter open, and brings all the records, filering only by "Sede" (1) and "Programa" (6).
In this image, the user only selected the "Estado" filter (5), so it brings all the records that match this criteria, it doesn't matter if "Sede" or "Programa" are empty.
If I use a SELECT clasuse with a WHERE on it, it will work, but only if the three filters have a value:
DECLARE #sede int
DECLARE #programa int
DECLARE #estado int
SET #sede = '1'
SET #programa = '5'
SET #estado = '12'
SELECT * FROM [dbo].[Inscripciones]
WHERE
([dbo].[Inscripciones].[Sede] = #sede)
AND
([dbo].[Inscripciones].[Programa] = #programa)
AND
([dbo].[Inscripciones].[Estado] = #estado)
I also tryed changing the "AND" for a "OR", but I can't get the desired result.
Any help will be highly appreciated!! Thanks!
common problem: try using coalesce on the variable and for the 2nd value use the field name you're comparing to. Be careful though; Ensure it's NULL and not empty string being passed!
What this does is take the first non-null value of the variable passed in or the value you're comparing to.. Thus if the value passed in is null the comparison will always return true.
WHERE
[dbo].[Inscripciones].[Sede] = coalesce(#sede, [dbo].[Inscripciones].[Sede])
AND
[dbo].[Inscripciones].[Programa] = coalesce(#programa, [dbo].[Inscripciones].[Programa])
AND
[dbo].[Inscripciones].[Estado] = coalesce(#estado, [dbo].[Inscripciones].[Estado])
If sede is null and programa and estado are populated the compare would look like...
?=? (or 1=1)
?=programa variable passed in
?=Estado variable passed in
Boa Sorte!
Thank you all for your anwers. After reading the article posted in the comments by #SeanLange I was finally able to achieve what was needed. Using a CASE clause in the WHERE statement solves the deal. Here's the code:
SELECT
*
FROM [dbo].[Inscripciones]
WHERE
([dbo].[Inscripciones].[Sede] = (CASE WHEN #sede = '' THEN [dbo].[Inscripciones].[Sede] ELSE #sede END))
AND
([dbo].[Inscripciones].[Programa] = (CASE WHEN #programa = '' THEN [dbo].[Inscripciones].[Programa] ELSE #programa END))
AND
([dbo].[Inscripciones].[Estado] = (CASE WHEN #estado = '' THEN [dbo].[Inscripciones].[Estado] ELSE #estado END))
AND
([dbo].[Inscripciones].[TipoIngreso] = (CASE WHEN #tipoingreso = '' THEN [dbo].[Inscripciones].[TipoIngreso] ELSE #tipoingreso END))
Thanks again!!
Please let me know if there is any query where in I remove the repeating entries in a row.
For eg: I have a table which has name with 9 telephone numbers:
Name Tel0 Tel1 Tel2 Tel3 Tel4 Tel5 Tel6 Tel7 Tel8
John 1 2 2 2 3 3 4 5 1
The final result should be as shown below:
Name Tel0 Tel1 Tel2 Tel3 Tel4 Tel5 Tel6 Tel7 Tel8
John 1 2 3 4 5
regards
Maddy
I fear that it will be more complicated to keep this format than to split the table in two as I suggested. If you insist on keeping the current schema then I would suggest that you query the row, organise the fields in application code and then perform an update on the database.
You could also try to use SQL UNION operator to give you a list of the numbers, a UNION by default will remove all duplicate rows:
SELECT Name, Tel FROM
(SELECT Name, Tel0 AS Tel FROM Person UNION
SELECT Name, Tel1 FROM Person UNION
SELECT Name, Tel2 FROM Person) ORDER BY Name ;
Which should give you a result set like this:
John|1
John|2
You will then have to step through the result set and saving each number into a separate variable (skipping those variables that do not exist) until the "Name" field changes.
Tel1 := Null; Tel2 := Null;
Name := ResultSet['Name'];
Tel0 := ResultSet['Tel'];
ResultSet.Next();
if (Name == ResultSet['Name']) {
Tel1 := ResultSet['Tel'];
} else {
UPDATE here.
StartAgain;
}
ResultSet.Next();
if (Name == ResultSet['Name']) {
Tel2 := ResultSet['Tel'];
} else {
UPDATE here.
StartAgain;
}
I am not recommending you do this, it is very bad use of a relational database but once implemented in a real language and debugged that should work.