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assignments/ assignments/assingment_3.md

+# Assignment 3
+
+
+
+## Task 1: Working with Mongo - Advanced
+
+
+## Areas covered:
+- Working with NoSQL
+- Working with Pandas
+
+## Description:
+You are given with a semester deatils in a JSON format, write FAST APIs for the below  : 
+
+1. To accept the semester details JSON and insert it in a collection
+2. To get sum and average of all marks filerter by any of "student_id", "batch_id", "semster_id", "subject_id"
+3. Generate excel report with "Student name", "Sememter name", "Subject 1", "Subject 2" ...., "Total"
+
+Sample Document:
+```json
+{
+  "semester_name": "Semester 3",
+  "semester_id": 299,
+  "semester_start_date": "2019-05-18",
+  "semester_end_date": "2019-06-04",
+  "student_details":[{
+  "student_name": "Student 1",
+  "student_id": 14500,
+  "batch_id": 43,
+  "subject_details": [
+    {
+      "subject_name": "Subject 1",
+      "subject_id": 12,
+      "score": 74
+    },
+    {
+      "subject_name": "Subject 2",
+      "subject_id": 14,
+      "score": 88
+    },
+    {
+      "subject_name": "Subject 3",
+      "subject_id": 15,
+      "score": 75
+    },
+    {
+      "subject_name": "Subject 4",
+      "subject_id": 5,
+      "score": 85
+    }
+  ]
+},
+{
+  "student_name": "Student 2",
+  "student_id": 14523,
+  "batch_id": 44,
+  "subject_details": [
+    {
+      "subject_name": "Subject 1",
+      "subject_id": 12,
+      "score": 83
+    },
+    {
+      "subject_name": "Subject 2",
+      "subject_id": 14,
+      "score": 98
+    },
+    {
+      "subject_name": "Subject 3",
+      "subject_id": 15,
+      "score": 68
+    },
+    {
+      "subject_name": "Subject 4",
+      "subject_id": 5,
+      "score": 71
+    }
+  ]
+}]
+}
+```
+
+Note: Perform all filter operations on Mongo itself
+
+### Tools to use: 
+1. Pycharm / VSCode
+2. Robo3T / Studio3T / MongoDB Compass
+3. PyMongo
+
+
+### Reference:
+https://www.mongodb.com/docs/manual/tutorial/query-documents/
+https://www.mongodb.com/docs/manual/reference/operator/aggregation-pipeline/
+https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_excel.html
+https://fastapi.tiangolo.com/advanced/custom-response/#fileresponse
+https://pymongo.readthedocs.io/en/stable/
+
+
+________________________________________________________
+## Task 2: Working with Timeseries
+
+
+## Areas covered:
+- Timeseries Operation
+- Working with Timeseries
+- Working with Pandas
+
+## Description:
+You are given with a dataset of temperature in the form of a CSV file. The end goal of the project is to create an API interface that will provide the following: 
+
+1. Get daily, weekly and monthly aggregate (min, max, and average) of the data filter by "good" data points and generate report in Excel format.
+
+Sample Document:
+
+
+Datetime,Temperature, Data quality
+20019-04-03 00:00:00.000, 112.4, good
+20019-04-03 01:00:00.000, 111.32, good
+20019-04-03 02:00:00.000, 114.98, bad
+
+### Tools to use: 
+1. Pycharm / VSCode
+2. Pandas 
+
+### Reference:
+https://kairosdb.github.io/docs/restapi/QueryMetrics.html
+https://pypi.org/project/kairosdb-python/
+
+