Gramoday-Assignment

This assignment deals with the scrapping of data from the Agricultutal Marketing website.

Overviwew

There are over 4,000 agriculture markets (commonly known as mandis) in the country. Everyday prices fluctuate in the markets basis supply and demand of the crop. Prediction of crop prices is one of the most important task to ensure efficient crop planning and food safety in the country.

Problem Statement

The problem statement revolves around prediction of prices for the crop Potato in District “Agra” in the state of Uttar Pradesh across year 2020 and to fetch data of prices for the year 2020 (date wise from 1st Jan’2020 to 31st Dec’2020) for district “Agra” of Uttar Pradesh from the data sources mentioned in the data section

Data Extraction (PART-A)

Follow the below steps to scrape the data.

!git clone https://github.com/hrsht-13/Gramoday.git

%cd Gramoday/

pip install -r requirements.txt

!python scrape_data.py (enter the path of the current directory. eg if you are using colab then your path will be /content/Gramoday)

Data will be extracted in the same directory as data.csv

PART B and PART C

The answers to the questions given in the doc file are provided in Gramoday-answers.docx

Notebook

A demo notebook has been provided for all the work done in assignment_Gramoday.ipynb