1. Download the file into your present working directory

  2. Read the content of the file into an object.

  3. Examine the Afghan Disaster Data. Suggest pre-processing steps that can be taken to improve this dataset.

  4. Change the data types of the columns in the AfghanDisaster csv into more suitable data types

  5. How many rows are there in the dataset? How many rows are there without Nas? List the rows with Nas?

  6. Discuss a viable strategy to replace the data that is missing.

  7. Implement the strategy you suggested : remove all rows with NA, zerofy all NAs, replace NA with mean

  8. Calculate the average value of HOUSES DESTROYED after you have normalized the data. What can you say about the data?

  9. What type of disaster caused the most number of injuries?

  10. What type of disaster caused the most number of deaths?

  11. Assuming each house costs USD 1000, insert a new column to the dataframe you have been using which shows the economic loss.

  12. Plot a graph to show the ordered list of natural disasters which causes the most deaths and the most economic damaga