CouchDB unable to Reduce Function - mapreduce

Hi all im starting to work with couchdb
im trying to rereduce this reduce function
function(key,values,rereduce){
if(rereduce === true){
//HELP HERE
return results;
}
values.forEach(function(doc){
if(results[(doc.id-1)]){
results[(doc.id-1)].valori.push(doc.valore);
}else{
results[(doc.id-1)] = {
id:doc.id,
nome:doc.nome,
unita:doc.unita,
valori:[doc.valore]
};
}
});
return results;
}
someone can help me to rereduce this?
this is my Map output data
[2015, 7, 6, 0, 0, 26]
ID: bfc53ce117b53ec023c528e0c3039fc7
{nome: "COT ist.INGRESSO ", valore: 309.6, id: 1, unita: "mg/Nm", ora: "00:00:26"}
[2015, 7, 6, 0, 0, 26]
ID: bfc53ce117b53ec023c528e0c303a032
{nome: "COT ist. USCITA ", valore: 5.4, id: 2, unita: "mg/Nm", ora: "00:00:26"}
[2015, 7, 6, 0, 0, 26]
ID: bfc53ce117b53ec023c528e0c303adf4
{nome: "Media TOC NIRA ", valore: 6.8, id: 3, unita: "mg/Nm", ora: "00:00:26"}
[2015, 7, 6, 0, 0, 26]
ID: bfc53ce117b53ec023c528e0c303b6a7
{nome: "Media TOC Giorn. ", valore: 7.3, id: 4, unita: "mg/Nm", ora: "00:00:26"}
[2015, 7, 6, 0, 1, 26]
ID: bfc53ce117b53ec023c528e0c303c3ee
{nome: "COT ist.INGRESSO ", valore: 410.9, id: 1, unita: "mg/Nm", ora: "00:01:26"}
[2015, 7, 6, 0, 1, 26]
ID: bfc53ce117b53ec023c528e0c303c7e6
{nome: "COT ist. USCITA ", valore: 7, id: 2, unita: "mg/Nm", ora: "00:01:26"}
[2015, 7, 6, 0, 1, 26]
ID: bfc53ce117b53ec023c528e0c303cb60
{nome: "Media TOC NIRA ", valore: 6.4, id: 3, unita: "mg/Nm", ora: "00:01:26"}
[2015, 7, 6, 0, 1, 26]
ID: bfc53ce117b53ec023c528e0c303d729
{nome: "Media TOC Giorn. ", valore: 6.9, id: 4, unita: "mg/Nm", ora: "00:01:26"}
[2015, 7, 6, 0, 2, 26]
ID: bfc53ce117b53ec023c528e0c303df8e
{nome: "COT ist.INGRESSO ", valore: 306.7, id: 1, unita: "mg/Nm", ora: "00:02:26"}
etc....
What i need after the reduce is:
[{nome:"COT ist.Ingresso", id:1, unita:"mg/Nm",valori:[309.6,5.4,.....]}
{name:"thename",id:2, unita:"mg/Nm",valori:[6.8,3.5,......]}...]
this is an array of 4 object (one each id) with valori field is the concat of the various valore field, ( ordered by key or ora property)

Related

How add 0 when TruncWeek's week no result in Django Query?

I want query the issue's count of group by weekly.
query1 = MyModel.object.filter(issue_creator__in=group.user_set.all()).\
annotate(week=TruncWeek('issue_creat_date')).values('week').annotate(count=Count('id')).order_by('week'))
the query result is OK. the queryset result:
[
{'week': datetime.datetime(2022, 1, 3, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 9},
{'week': datetime.datetime(2022, 1, 10, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 12},
{'week': datetime.datetime(2022, 1, 17, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 10},
{'week': datetime.datetime(2022, 2, 7, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 1},
{'week': datetime.datetime(2022, 2, 14, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 6},
{'week': datetime.datetime(2022, 2, 21, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 11},
{'week': datetime.datetime(2022, 2, 28, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 1}
]
but 20220101-20220301 has 9 weeks:
[
datetime.datetime(2022, 1, 3, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 1, 10, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 1, 17, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 1, 24, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 1, 31, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 2, 7, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 2, 14, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 2, 21, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 2, 28, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>)
]
I want add zero when that week no result as this result:
[
{'week': datetime.datetime(2022, 1, 3, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 9},
{'week': datetime.datetime(2022, 1, 10, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 12},
{'week': datetime.datetime(2022, 1, 17, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 10},
{'week': datetime.datetime(2022, 1, 24, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 0},
{'week': datetime.datetime(2022, 1, 31, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 0},
{'week': datetime.datetime(2022, 2, 7, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 1},
{'week': datetime.datetime(2022, 2, 14, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 6},
{'week': datetime.datetime(2022, 2, 21, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 11},
{'week': datetime.datetime(2022, 2, 28, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 1}
]
how to write the right queryset?
Thanks.

Django method for None value Coalesce.
from django.db.models.functions import Coalesce
query1 = MyModel.object.filter(issue_creator__in=group.user_set.all()).\
annotate(week=TruncWeek('issue_creat_date')).values('week').annotate(count=Count('id')).order_by('week'))

Django ORM queryset equivalent to group by year-month?

I have an Django app and need some datavisualization and I am blocked with ORM.
I have a models Orders with a field created_at and I want to present data with a diagram bar (number / year-month) in a dashboard template.
So I need to aggregate/annotate data from my model but did find a complete solution.
I find partial answer with TruncMonth and read about serializers but wonder if there is a simpliest solution with Django ORM possibilities...
In Postgresql it would be:
SELECT date_trunc('month',created_at), count(order_id) FROM "Orders" GROUP BY date_trunc('month',created_at) ORDER BY date_trunc('month',created_at);
"2021-01-01 00:00:00+01" "2"
"2021-02-01 00:00:00+01" "3"
"2021-03-01 00:00:00+01" "3"
...
example
1 "2021-01-04 07:42:03+01"
2 "2021-01-24 13:59:44+01"
3 "2021-02-06 03:29:11+01"
4 "2021-02-06 08:21:15+01"
5 "2021-02-13 10:38:36+01"
6 "2021-03-01 12:52:22+01"
7 "2021-03-06 08:04:28+01"
8 "2021-03-11 16:58:56+01"
9 "2022-03-25 21:40:10+01"
10 "2022-04-04 02:12:29+02"
11 "2022-04-13 08:24:23+02"
12 "2022-05-08 06:48:25+02"
13 "2022-05-19 15:40:12+02"
14 "2022-06-01 11:29:36+02"
15 "2022-06-05 02:15:05+02"
16 "2022-06-05 03:08:22+02"
expected result
[
{
"year-month": "2021-01",
"number" : 2
},
{
"year-month": "2021-03",
"number" : 3
},
{
"year-month": "2021-03",
"number" : 3
},
{
"year-month": "2021-03",
"number" : 1
},
{
"year-month": "2021-04",
"number" : 2
},
{
"year-month": "2021-05",
"number" : 3
},
{
"year-month": "2021-06",
"number" : 3
},
]
I have done this but I am not able to order by date:
Orders.objects.annotate(month=TruncMonth('created_at')).values('month').annotate(number=Count('order_id')).values('month', 'number').order_by()
<SafeDeleteQueryset [
{'month': datetime.datetime(2022, 3, 1, 0, 0, tzinfo=<UTC>), 'number': 4},
{'month': datetime.datetime(2022, 6, 1, 0, 0, tzinfo=<UTC>), 'number': 2},
{'month': datetime.datetime(2022, 5, 1, 0, 0, tzinfo=<UTC>), 'number': 1},
{'month': datetime.datetime(2022, 1, 1, 0, 0, tzinfo=<UTC>), 'number': 5},
{'month': datetime.datetime(2021, 12, 1, 0, 0, tzinfo=<UTC>), 'number': 1},
{'month': datetime.datetime(2022, 7, 1, 0, 0, tzinfo=<UTC>), 'number': 1},
{'month': datetime.datetime(2021, 9, 1, 0, 0, tzinfo=<UTC>), 'number': 2},
'...(remaining elements truncated)...'
]>

Try adding the order_by on the original field if you have multi-year data.
from django.db.models import Sum
from django.db.models.functions import TruncMonth
Orders.objects.values(month=TruncMonth('created_at')).
order_by("created_at").annotate(Sum('number')

Access Pandas MultiIndex column by name

I have a spreadsheet imported with pandas like this:
df = pd.read_excel('my_spreadsheet.xlsx',header = [0,1],index_col=0,sheetname='Sheet1')
The output of df.columns is:
MultiIndex(levels=[[u'MR 1', u'MR 10', u'MR 11', u'MR 12', u'MR 13', u'MR 14', u'MR 15', u'MR 16', u'MR 17', u'MR 18', u'MR 19', u'MR 2', u'MR 20', u'MR 21', u'MR 22', u'MR 3', u'MR 4', u'MR 5', u'MR 6', u'MR 7', u'MR 8', u'MR 9'], [u'BIRADS', u'ExamDesc', u'completedDTTM']],
labels=[[0, 0, 0, 11, 11, 11, 15, 15, 15, 16, 16, 16, 17, 17, 17, 18, 18, 18, 19, 19, 19, 20, 20, 20, 21, 21, 21, 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 12, 12, 12, 13, 13, 13, 14, 14, 14], [1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0]],
names=[None, u'De-Identified MRN'])
I have been trying to access the values of column named 'De-Identified MRN', but can't seem to find the way to do this.
What I have tried (based on similar posts):
[in] df.index.get_level_values('De-Identified MRN')
[out] KeyError: 'Level De-Identified MRN must be same as name (None)'
and
[in] df.index.unique(level='De-Identified MRN')
[out] KeyError: 'Level De-Identified MRN must be same as name (None)'
UPDATE:
The following did the trick for some reason. I really do not understand the format of the MultiIndex Pandas Dataframe:
pd.Series(df.index)

By using your data
s="MultiIndex(levels=[[u'MR 1', u'MR 10', u'MR 11', u'MR 12', u'MR 13', u'MR 14', u'MR 15', u'MR 16', u'MR 17', u'MR 18', u'MR 19', u'MR 2', u'MR 20', u'MR 21', u'MR 22', u'MR 3', u'MR 4', u'MR 5', u'MR 6', u'MR 7', u'MR 8', u'MR 9'], [u'BIRADS', u'ExamDesc', u'completedDTTM']],labels=[[0, 0, 0, 11, 11, 11, 15, 15, 15, 16, 16, 16, 17, 17, 17, 18, 18, 18, 19, 19, 19, 20, 20, 20, 21, 21, 21, 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 12, 12, 12, 13, 13, 13, 14, 14, 14], [1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0]],names=[None, u'De-Identified MRN'])"
idx=eval(s, {}, {'MultiIndex': pd.MultiIndex})
df=pd.DataFrame(index=idx)
df.index.get_level_values(level=1) # df.index.get_level_values('De-Identified MRN')
Out[336]:
Index(['ExamDesc', 'completedDTTM', 'BIRADS', 'ExamDesc', 'completedDTTM',
'BIRADS', 'ExamDesc', 'completedDTTM', 'BIRADS', 'ExamDesc',...
Also if all above still does not work , try
df.reset_index()['De-Identified MRN']

Try the following:
midx = pd.MultiIndex(
levels=[[u'MR 1', u'MR 10', u'MR 11', u'MR 12', u'MR 13', u'MR 14', u'MR 15', u'MR 16', u'MR 17', u'MR 18', u'MR 19', u'MR 2', u'MR 20', u'MR 21', u'MR 22', u'MR 3', u'MR 4', u'MR 5', u'MR 6', u'MR 7', u'MR 8', u'MR 9'], [u'BIRADS', u'ExamDesc', u'completedDTTM']],
labels=[[0, 0, 0, 11, 11, 11, 15, 15, 15, 16, 16, 16, 17, 17, 17, 18, 18, 18, 19, 19, 19, 20, 20, 20, 21, 21, 21, 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 12, 12, 12, 13, 13, 13, 14, 14, 14], [1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0]],
names=[None, u'De-Identified MRN']
)
midx.levels[1] # returns the following
Index(['BIRADS', 'ExamDesc', 'completedDTTM'], dtype='object', name='De-Identified MRN')
midx.levels[1].values # returns the following
array(['BIRADS', 'ExamDesc', 'completedDTTM'], dtype=object)

RethinkDB group and merge into single doc with sub-array

Is it the best way to group and merge each reduction into a single document with sub-array?
r.expr([
{id: 1, foo: 1, bar: 2, date: r.time(2016, 1, 1, 'Z')},
{id: 1, foo: 4, bar: 1, date: r.time(2016, 1, 3, 'Z')},
{id: 1, foo: 10, bar: 0, date: r.time(2016, 1, 2, 'Z')},
{id: 2, foo: 5, bar: 3, date: r.time(2016, 1, 1, 'Z')},
{id: 2, foo: 3, bar: 6, date: r.time(2016, 1, 2, 'Z')}
]).group('id').orderBy('date').map(function(d){
return d
.without('foo', 'bar', 'date')
.merge({stats: [d.pluck('foo', 'bar', 'date')]})
}).reduce(function(left, right){
return left .without('stats').merge({
stats: left('stats').append(right('stats')(0))
})
}).ungroup().map(function(g){
return g('reduction')
})
Output:
[
{
"id": 1 ,
"stats": [
{
"foo": 1, "bar": 2 , "date": Fri Jan 01 2016 00:00:00 GMT+00:00
},
{
"foo": 10, "bar": 0 , "date": Sat Jan 02 2016 00:00:00 GMT+00:00
} ,
{
"foo": 4, "bar": 1 , "date": Sun Jan 03 2016 00:00:00 GMT+00:00
}
]
},
{
"id": 2 ,
"stats": [
{
"foo": 5, "bar": 3, "date": Fri Jan 01 2016 00:00:00 GMT+00:00
} ,
{
"foo": 3, "bar": 6, "date": Sat Jan 02 2016 00:00:00 GMT+00:00
}
]
}
]

This should work:
r.expr([
{id: 1, foo: 1, bar: 2, date: r.time(2016, 1, 1, 'Z')},
{id: 1, foo: 4, bar: 1, date: r.time(2016, 1, 3, 'Z')},
{id: 1, foo: 10, bar: 0, date: r.time(2016, 1, 2, 'Z')},
{id: 2, foo: 5, bar: 3, date: r.time(2016, 1, 1, 'Z')},
{id: 2, foo: 3, bar: 6, date: r.time(2016, 1, 2, 'Z')}
]).group('id')
.orderBy('date')
.without('id')
.ungroup()
.map(rec => { return { id : rec('group'), stats : rec('reduction') }; } )

Wrong position of annotations in a stacked bar chart (Google Chart API)

I have a stacked bar chart with annotations which sums the values. The annotations are always at the end of the bar, but when there isn't a value for the last data row (I) the annotation is at the beginning and I don't know how to fix it.
var dataArray = [
["Date", "A", "B", "C", "D", "E", "F", "G", "H", "I", {role: 'annotation'}],
["7.08.2015", 0, 0, 0, 3, 6, 1, 0, 0, 0, 10],
["6.08.2015", 0, 0, 0, 0, 4, 6, 1, 0, 7, 18],
["5.08.2015", 0, 0, 0, 2, 4, 0, 0, 0, 5, 11]
];
Demo and code at JSFiddle

Found a workaround ... added a new data column, with the name Total, is has the same value as the annotation:
var dataArray = [
["Date", "A", "B", "C", "D", "E", "F", "G", "H", "I", "Total", {role: 'annotation'}],
["7.08.2015", 0, 0, 0, 3, 6, 1, 0, 0, 0, 10, 10],
["6.08.2015", 0, 0, 0, 0, 4, 6, 1, 0, 7, 18, 18],
["5.08.2015", 0, 0, 0, 2, 4, 0, 0, 0, 5, 11, 11]
];
And added this to the options:
var options = {
...
series: {
9: {
color: 'transparent',
type: "bar",
targetAxisIndex: 1,
visibleInLegend: false
}
}
};
Demo and code at JSFiddle
This makes the Total bar transparent, hide it in the legends and let it start from the zero point.
Dynamic version which takes the last data row for the annotations:
var series = {};
series[data.getNumberOfColumns() - 3] = {
color: 'transparent',
type: "bar",
targetAxisIndex: 1,
visibleInLegend: false
};
options["series"] = series;
Demo and code at JSFiddle