Data
Americas-Top-College-Rankings-2019-(Forbes)

Americas-Top-College-Rankings-2019-(Forbes)

active ARFF CC0: Public Domain Visibility: public Uploaded 23-03-2022 by Onur Yildirim
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  • Computer Systems Machine Learning
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Context Starting in 2008, every year Forbes Magazine publishes a list of America's best colleges. Schools are ranked based on alumni salary (20), student satisfaction (20), debt (20), American leaders (15), on time graduation rate (12.5), and academic success (12.5). To learn more about the methodology, go to https://www.forbes.com/top-colleges/1208425d1987. Content The data set contains the rankings of 650 Unites States colleges along with various other statistics pertaining to each school. Acknowledgements Data collected from https://www.forbes.com/top-colleges/1208425d1987. Source was edited by Justin Conklin, Carter Coudriet, and Caroline Howard, and reported by Maria Clara Cobo, Julie Coleman, Madison Fernandez, Grace Kay, and Derek Saul. Inspiration Choosing where to go to college is one of the most prevalent issues facing teenagers across the country. With this data, I hope interesting findings will emerge pertaining to which schools are worth attending most.

16 features

Ranknumeric650 unique values
0 missing
Namestring650 unique values
0 missing
Citystring468 unique values
3 missing
Statestring51 unique values
0 missing
Public/Privatestring2 unique values
0 missing
Undergraduate_Populationnumeric623 unique values
0 missing
Student_Populationnumeric639 unique values
0 missing
Net_Pricenumeric638 unique values
2 missing
Average_Grant_Aidnumeric639 unique values
4 missing
Total_Annual_Costnumeric644 unique values
0 missing
Alumni_Salarynumeric354 unique values
15 missing
Acceptance_Ratenumeric93 unique values
2 missing
SAT_Lowernumeric97 unique values
99 missing
SAT_Uppernumeric90 unique values
99 missing
ACT_Lowernumeric20 unique values
97 missing
ACT_Uppernumeric16 unique values
97 missing
Website (ignore)string645 unique values
5 missing

19 properties

650
Number of instances (rows) of the dataset.
16
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
418
Number of missing values in the dataset.
127
Number of instances with at least one value missing.
12
Number of numeric attributes.
0
Number of nominal attributes.
0.02
Number of attributes divided by the number of instances.
75
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
19.54
Percentage of instances having missing values.
Average class difference between consecutive instances.
4.02
Percentage of missing values.

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