$S$&$P500$ Constituents

For the following questions, the file sp$500-$constituents.csv is provided, which contains a list of stocks in the S&P $500$ and certain data about each. Use pandas read$\_$csv$()$ to load the file into a DataFrame, and for each part below, develop statements to further refine the data.

a$)$ SEC filings: Use the drop$()$ method to take out the SEC filings column from the DataFrame.

b$)$ Headquarters location: Use the split$()$ method to create two new fields, one for city and one for state.

c$)$ Date first added missing values: Create a DataFrame that has the symbols with those stocks where the Date first added field is missing a value.

d$)$ Date first added $($multivalued$)$: Find rows where "Date first added" is different from a single date, then use statements to create a new column that determines and populates the date in first position if more than one date is indicated for this field.

e$)$ Founded $($missing values$)$: Create a DataFrame that has the symbols with those stocks where the Founded column is missing a value.

f$)$ Founded $($multivalued$)$: Find rows where "Date first added" is different from a single date, then use statements to create a new column that determines and populates the date in first position if more than one date is indicated for this field.