5

Ok… so I put this together in response… hope you find it helpful.

https://github.com/mrlynn/mongodb-community-forums-316436

1. Seed Sample Data (Python Script)

Make sure you’ve got a MongoDB Atlas cluster and pymongo + python-dotenv installed.

requirements.txt

pymongo
python-dotenv

.env

MONGODB_URI=mongodb+srv://<username>:<password>@<cluster-url>/test?retryWrites=true&w=majority

seed_data.py

import os
from pymongo import MongoClient
from datetime import datetime
from dotenv import load_dotenv

# Load credentials
load_dotenv()
mongo_uri = os.getenv("MONGODB_URI")
client = MongoClient(mongo_uri)

# Set database and collection
db = client["charts_demo"]
collection = db["status_log"]
collection.delete_many({})  # Clear collection for repeatability

# Sample data (with gaps in dates)
raw_data = [
    {"date": "3/5/25", "status": "passed"},
    {"date": "3/5/25", "status": "passed"},
    {"date": "3/10/25", "status": "passed"},
    {"date": "3/10/25", "status": "passed"},
    {"date": "3/12/25", "status": "failed"},
    {"date": "3/12/25", "status": "failed"},
    {"date": "3/12/25", "status": "passed"},
    {"date": "3/12/25", "status": "passed"},
    {"date": "3/12/25", "status": "passed"},
    {"date": "3/12/25", "status": "passed"},
    {"date": "3/12/25", "status": "failed"},
    {"date": "3/13/25", "status": "passed"},
    {"date": "3/13/25", "status": "passed"},
    {"date": "3/13/25", "status": "passed"},
]

# Format and insert
docs = [
    {"date": datetime.strptime(entry["date"], "%m/%d/%y"), "status": entry["status"]}
    for entry in raw_data
]
collection.insert_many(docs)
print("✅ Data inserted into charts_demo.status_log")

2. Create the Chart in MongoDB Charts

Step-by-Step:

  1. Go to MongoDB Charts and log in
  2. Create a new Dashboard
  3. Add a data source: choose the charts_demo.status_log collection
  4. Click “Add Chart” → Select Line Chart or Discrete Line
  5. Switch to Library mode in the top bar
  6. Paste in the following aggregation pipeline:
[
  {
    $group: {
      _id: { date: "$date", status: "$status" },
      count: { $sum: 1 }
    }
  },
  {
    $group: {
      _id: "$_id.date",
      counts: {
        $push: {
          k: "$_id.status",
          v: "$count"
        }
      }
    }
  },
  {
    $project: {
      _id: 0,
      date: "$_id",
      counts: { $arrayToObject: "$counts" }
    }
  },
  {
    $densify: {
      field: "date",
      range: {
        step: 1,
        unit: "day",
        bounds: "full"
      }
    }
  },
  {
    $addFields: {
      "counts.passed": { $ifNull: ["$counts.passed", 0] },
      "counts.failed": { $ifNull: ["$counts.failed", 0] }
    }
  }
]

Click Apply.

3. Configure the Chart Layout

  • X-Axis: date
  • Y-Axis:
    • Add counts.passed (Aggregate: Sum)
    • Add counts.failed (Aggregate: Sum)
  • Leave Series blank
  • Customize title: “Test Results per Day with Missing Dates Shown”

Final Result

You’ll see a line chart showing:

  • Test result counts (passed/failed)
  • All days between March 5 and 13, including zero-count days