I have the following:
[{"result":"SUCCESS"}, {"result":"FAILURE"}, {"result":"SUCCESS"}]
I would like to transform with jsonata that into:
[1,0,1]
BR,
$.(result = "SUCCESS" ? 1 : 0)
See https://try.jsonata.org/g_qF8wPAw
Related
How can i filter 12 random objects from a model in django .
I tried to do this but It does not work and It just returned me 1 object.
max = product.objects.aggregate(id = Max('id'))
max_p = int(max['id'])
l = []
for s in range(1 , 13):
l.append(random.randint(1 , max_p))
for i in l:
great_proposal = product.objects.filter(id=i)
products = product.objects.all().order_by('-id')[:50]
great_proposal1 = random.sample(list(products) , 12)
Hi . It worked with this code !
Try this:
product.objects.order_by('?')[:12]
The '?' will "sort" randomly and "[:12]" will get only 12 objects.
I'm pretty sure the code is correct, but maybe you did not realize that you're just using great_proposal as variable to save the output, which is not an array, and therefore only returns one output.
Try:
result_array = []
for i in l:
result_array.append(product.objects.filter(index=i))
I have a membership model, and I want to search OR on two columns....not sure how to do it.
I tried this:
u1.all_memberships.where(inviter: u2, invited: u2)
Membership Load (6.8ms) SELECT "memberships".* FROM "memberships" WHERE (memberships.user_id = 1 OR memberships.invited_id = 1) AND "memberships"."user_id" = 3 AND "memberships"."invited_id" = 3
=> []
But note the 2 AND on both queries, when ideally what I would like to do is literally just replace all the ANDs with ORs.
So I would love if the query looked something like this:
Membership Load (6.8ms) SELECT "memberships".* FROM "memberships" WHERE (memberships.user_id = 1 OR memberships.invited_id = 1) OR (memberships.user_id = 3 OR memberships.invited_id = 3)
Assuming that my modification is syntactically correct SQL ofcourse.
How do I do that with a where clause? Is that possible?
I expect It can help
where("inviter_id = ? OR invited_id = ? ", u2.id, u2.id)
DRYer solution
where("inviter_id = :uid OR invited_id = :uid ", uid: u2.id)
I have three lists that look like this:
age = ['51+', '21-30', '41-50', '31-40', '<21']
cluster = ['notarget', 'cluster3', 'allclusters', 'cluster1', 'cluster2']
device = ['htc_one_2gb','iphone_6/6+_at&t','iphone_6/6+_vzn','iphone_6/6+_all_other_devices','htc_one_2gb_limited_time_offer','nokia_lumia_v3','iphone5s','htc_one_1gb','nokia_lumia_v3_more_everything']
I also have column in a df that looks like this:
campaign_name
0 notarget_<21_nokia_lumia_v3
1 htc_one_1gb_21-30_notarget
2 41-50_htc_one_2gb_cluster3
3 <21_htc_one_2gb_limited_time_offer_notarget
4 51+_cluster3_iphone_6/6+_all_other_devices
I want to split the column into three separate columns based on the values in the above lists. Like so:
age cluster device
0 <21 notarget nokia_lumia_v3
1 21-30 notarget htc_one_1gb
2 41-50 cluster3 htc_one_2gb
3 <21 notarget htc_one_2gb_limited_time_offer
4 51+ cluster3 iphone_6/6+_all_other_devices
First thought was to do a simple test like this:
ages_list = []
for i in ages:
if i in df['campaign_name'][0]:
ages_list.append(i)
print ages_list
>>> ['<21']
I was then going to convert ages_list to a series and combine it with the remaining two to get the end result above but i assume there is a more pythonic way of doing it?
the idea behind this is that you'll create a regular expression based on the values you already have , for example if you want to build a regular expressions that capture any value from your age list you may do something like this '|'.join(age) and so on for all the values you already have cluster & device.
a special case for device list becuase it contains + sign that will conflict with the regex ( because + means one or more when it comes to regex ) so we can fix this issue by replacing any value of + with \+ , so this mean I want to capture literally +
df = pd.DataFrame({'campaign_name' : ['notarget_<21_nokia_lumia_v3' , 'htc_one_1gb_21-30_notarget' , '41-50_htc_one_2gb_cluster3' , '<21_htc_one_2gb_limited_time_offer_notarget' , '51+_cluster3_iphone_6/6+_all_other_devices'] })
def split_df(df):
campaign_name = df['campaign_name']
df['age'] = re.findall('|'.join(age) , campaign_name)[0]
df['cluster'] = re.findall('|'.join(cluster) , campaign_name)[0]
df['device'] = re.findall('|'.join([x.replace('+' , '\+') for x in device ]) , campaign_name)[0]
return df
df.apply(split_df, axis = 1 )
if you want to drop the original column you can do this
df.apply(split_df, axis = 1 ).drop( 'campaign_name', axis = 1)
Here I'm assuming that a value must be matched by regex but if this is not the case you can do your checks , you got the idea
Just wondering does the filter turn the data into tuples? For example
val filesLines = sc.textFile("file.txt")
val split_lines = filesLines.map(_.split(";"))
val filteredData = split_lines.filter(x => x(4)=="Blue")
//from here if we wanted to map the data would it be using tuple format ie. x._3 OR x(3)
val blueRecords = filteredData.map(x => x._1, x._2)
OR
val blueRecords = filteredData.map(x => x(0), x(1))
No, all filter does is take a predicate function and uses it such that any of the datapoints in the set that return a false when passed through that predicate, then they are not passed back out to the resultant set. So, the data remians the same:
filesLines //RDD[String] (lines of the file)
split_lines //RDD[Array[String]] (lines delimited by semicolon)
filteredData //RDD[Array[String]] (lines delimited by semicolon where the 5th item is Blue
So, to use filteredData, you will have to access the data as an array using parentheses with the appropriate index
filter will not change the RDD - filtered data would still be RDD(Array[String])
hi i have below code working fine:
if getattr(hotel_main, "X", 1):
hotels1 = hotels.filter(Q(X=True))
for hotel in hotels1:
if models.CalendarDay.objects.filter(hotel=hotel, date=date).count() == 0:
similar_venues.append(hotel)
I reused above code again and again to check different conditions like Q(Y=True),Q(Y=True),Q(Z=True)
if i can filter a list based on the condition i can get rid of repeating code... i want something like this: similar_venues.filter(Q(X=True)) Any help please...
If i understood correctly what you asked:
filter_on_x = [obj for obj in similar_venues if obj.X]
filter_on_y = [obj for obj in similar_venues if obj.Y]
and so on for all the X, Y, Z
You can write conditions in a list:
conditions = [ Q(Y=True),Q(Y=True),Q(Z=True) ]
if getattr(hotel_main, "X", 1):
q_date = Q( calendarday__date = date )
for q in conditions:
for hotel in hotels.filter( q_date & q).distinct():
similar_venues.append(hotel)