Today’s dataset is a sample from the training data, for all the people who have donated to "Healthcare for All".
Instead of having all the features from the training data, we have a subset of only a few features. The objective of this sample dataset is to teach students some important steps in data blending, cleaning, and using linear regression to predict the target variable, here TARGET_D, using MS Excel and Python.
Data is provided to the analyst in four different Excel files named file1, file2, file3, and file4. Data is downloaded from a server at some frequent intervals and stored into different files. All the files have the same data recorder, ie. the same headers.
We will need to merge all this data together into one file before we start with any other operation on the data.
There is another file that contains other data such as date of birth, domain, and TARGET_D.
Use the Date of birth column to find the age.
Use vlook_up from the file vlookup_table.csv, using the column CONTROLN to add the column TARGET_D to the previous merged data
As an exercise, split the column Domain and use vlook_up from the file vlookup_table.csv to check which kind of neighborhood they live in (ie. urban, city, town, rural, etc.).
After merging all the data together, start with the data cleaning operations as mentioned in the lesson.