Assume this data is representative of all micro-irrigation use in Gujarat. What crops account for the most total area under each drip and sprinkler irrigation?

Cleaning

For this section, use the “MIS Beneficiary List” data included in this repo. This spreadsheet gives a list of recipients of government subsidies for micro-irrigation systems (MIS) in Gujarat, India, during 2014-15. I downloaded it a few years ago from a publicly accessible government website. For the following questions, focus on the “MIS Subsidy” column and ignore the “Tribal Subsidy” column.

1. Import this data into R and clean it, following our data cleaning checklist. (Use reasonable effort — aim to get about 90% of the way and skip, but mention, any remaining tasks that would be extremely time-consuming.) Comment your code following the best practices we discussed.

2. Assume this data is representative of all micro-irrigation use in Gujarat. What crops account for the most total area under each of drip and sprinkler irrigation?

3. Each farmer was only supposed to receive a subsidy once. Give your best estimate of the percentage of total subsidies disbursed that went to fraudulent claims. (Think carefully about how to define duplicate farmers in the data, and how to distinguish true duplicate claims from data entry errors.)