Prepare the string data type columns as follows. a. Use web search and find the countries that belong to OECD and BRICS groups. Then, using the map() function, create a new column that indicates which of the two groups a country belongs. b. In the Continent column change the values of South America and North America into “America”. c. With a for loop generate relative frequency of all the string data type columns and examine whether there are infrequent values in each of the string variables that can be combined. d. Generate and save full-rank dummy variables for the string variables
Prepare the string data type columns as follows. a. Use web search and find the countries that belong to OECD and BRICS groups. Then, using the map() function, create a new column that indicates which of the two groups a country belongs. b. In the Continent column change the values of South America and North America into “America”. c. With a for loop generate relative frequency of all the string data type columns and examine whether there are infrequent values in each of the string variables that can be combined. d. Generate and save full-rank dummy variables for the string variables
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Prepare the string data type columns as follows.
a. Use web search and find the countries that belong to OECD and BRICS groups. Then, using the map() function, create a new column that indicates which of the two groups a country belongs.
b. In the Continent column change the values of South America and North America into “America”.
c. With a for loop generate relative frequency of all the string data type columns and examine whether there are infrequent values in each of the string variables that can be combined.
d. Generate and save full-rank dummy variables for the string variables
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