Group and count in Mongo DB - mongodb

Question

I have many tweets object like this:
{
"_id" : ObjectId("5a2f4a381cb29b482553e2c9"),
"user_id" : 21898942,
"created_at" : ISODate("2009-03-09T19:48:50Z"),
"id" : 1301923516,
"place" : "",
"retweet_count" : 0,
"tweet" : "Save the Date! March 28th Vietnamese Cooking Class! Call to Reserve 312.255.0088",
"favorite_count" : 0
"type": A
}
I'm using this code to qroup the tweets by date and by type:
pipeline = [
{
"$group": {
"_id": {
"date": {
"$dateToString": {
"format": "%Y-%m-%d",
"date": "$created_at"
}
},
"type": "$type"
},
"count": {
"$sum": 1
}
}
}
]
results = mongo.db.tweets.aggregate(pipeline)
Here is the result I get:
{
"_id": {
"date": "2009-03-17",
"type": A
},
"count": 4
,
{
"_id": {
"date": "2009-03-17",
"type": B
},
"count": 6
}
But now I want to have the result in this format:
{date: "2009-03-17", A: 4, B: 6, C: 9}
Is there anyway I can achieve this through aggregate directly?
Note: I'm using MongoDB and PyMongo

Answer 1

You can try the below aggregation query in 3.6 version.
Added the second group to create array of type and count value pairs followed by $mergeObjects to merge date key value with $arrayToObject, which produces create a type value key and count value pairs, to generate the expected response.
$replaceRoot to promote the document to the top level.
pipeline = [
{
"$group": {
"_id": {
"date": {
"$dateToString": {
"format": "%Y-%m-%d",
"date": "$created_at"
}
},
"type": "$type"
},
"count": {
"$sum": 1
}
}
},
{
"$group": {
"_id": "$_id.date",
"typeandcount": {
"$push": {
"k": "$_id.type",
"v": "$count"
}
}
}
},
{
"$replaceRoot": {
"newRoot": {
"$mergeObjects": [
{
"date": "$_id"
},
{
"$arrayToObject": "$typeandcount"
}
]
}
}
}
]
Mongo 3.4 version:
Replace the last stage with below
{
"$replaceRoot": {
"newRoot": {
"$arrayToObject": {
"$concatArrays": [
[
{
"k": "date",
"v": "$_id"
}
],
"$typeandcount"
]
}
}
}
}