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Total Stats Share & Export ▼ Glossary Тeam Opponent Rk Тeam G MP FG FGA FG% 3P 3PA 3P% 2P 2PA 2P% FT FTA FT% ORB DRB TRB AST STL BLK TOV PF PTS 1 Charlotte Homets 9 2185 383 850 .451 127 321 .396 256 529 9 2210 376 809 .465 121 336 .484 139 192 .724 108 301 409 237 84 47 122 165 1032 89 320 409 225 64 57 150 192 1001 .332 260 535 .486 134 173 .775 124 305 429 179 100 32 123 173 948 99 308 407 224 72 36 146 142 938 9 2160 348 816 .426 103 305 338 245 511 .479 130 160 .813 111 315 426 205 66 45 148 175 929 9 2160 323 766 .422 123 351 .350 200 415 .482 141 185 .762 90 318 408 187 50 40 151 190 910 8 1945 354 735 .482 92 254 .362 262 481 .545 107 149 .718 77 274 351 196 74 50 134 167 907 79 284 363 186 56 48 109 154 904 2 Indiana Pacers .360 255 473 .539 128 164 .780 9 2160 358 830 .431 98 295 3 Toronto Ragtors 4 Cleveland Cavaliers 5 New Orleans Pelicans 9 2160 349 771 .453 90 278 .324 259 493 .525 150 197 .761 6 Orlando Magis 7 Los Angeles Lakers 8 New York Knicks 8 1970 325 709 .458 121 308 .393 204 401 .509 133 180 .739 Create a csv file from the data. Click to learn how to share information from Sports Reference. Compose a program that reads in the sports data (create an instance of InStream). Produce at least 2 output files (2 instances of OutStream) with filtered data (you choose how you want to filter the data). Create some sort of graph/histogram of your filtered data. Include a comment in your code that demonstrates how to run the program. Example: >>> python myprog.py data.csv

Total Stats Share & Export ▼ Glossary Тeam Opponent Rk Тeam G MP FG FGA FG% 3P 3PA 3P% 2P 2PA 2P% FT FTA FT% ORB DRB TRB AST STL BLK TOV PF PTS 1 Charlotte Homets 9 2185 383 850 .451 127 321 .396 256 529 9 2210 376 809 .465 121 336 .484 139 192 .724 108 301 409 237 84 47 122 165 1032 89 320 409 225 64 57 150 192 1001 .332 260 535 .486 134 173 .775 124 305 429 179 100 32 123 173 948 99 308 407 224 72 36 146 142 938 9 2160 348 816 .426 103 305 338 245 511 .479 130 160 .813 111 315 426 205 66 45 148 175 929 9 2160 323 766 .422 123 351 .350 200 415 .482 141 185 .762 90 318 408 187 50 40 151 190 910 8 1945 354 735 .482 92 254 .362 262 481 .545 107 149 .718 77 274 351 196 74 50 134 167 907 79 284 363 186 56 48 109 154 904 2 Indiana Pacers .360 255 473 .539 128 164 .780 9 2160 358 830 .431 98 295 3 Toronto Ragtors 4 Cleveland Cavaliers 5 New Orleans Pelicans 9 2160 349 771 .453 90 278 .324 259 493 .525 150 197 .761 6 Orlando Magis 7 Los Angeles Lakers 8 New York Knicks 8 1970 325 709 .458 121 308 .393 204 401 .509 133 180 .739 Create a csv file from the data. Click to learn how to share information from Sports Reference. Compose a program that reads in the sports data (create an instance of InStream). Produce at least 2 output files (2 instances of OutStream) with filtered data (you choose how you want to filter the data). Create some sort of graph/histogram of your filtered data. Include a comment in your code that demonstrates how to run the program. Example: >>> python myprog.py data.csv

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Total Stats Share & Export Glossary Team Opponent Rk Team G MP FG FGA FG% 3P 3PA 3P% 2P 2PA 2P% FT FTA FT% ORB DRB TRB AST STL BLK TOV PF PTS 1 Charlotte Hornets 2 Indiana Pacers 3 Toronto Raptors 9 2185 383 850 .451 127 321 .396 256 529 .484 139 192 .724 108 301 409 237 84 47 122 165 1032 9 2210 376 809 .465 121 336 .360 255 473 .539 128 164 .780 89 320 409 225 64 57 150 192 1001 9 2160 358 830 .431 98 295 .332 260 535 .486 134 173 .775 124 305 429 179 100 32 123 173 948 4 Cleveland Cavaliers 9 2160 349 771 .453 90 278 .324 259 493 .525 150 197 .761 99 308 407 224 72 36 146 142 938 5 New Orleans Pelicans 6 Orlando Magic 9 2160 348 816 .426 103 305 .338 245 511 .479 130 160 .813 111 315 426 205 66 45 148 175 929 9 2160 323 766 .422 123 351 .350 200 415 .482 141 185 .762 90 318 408 187 50 40 151 190 910 7 Los Angeles Lakers 8 New York Knicks 8 1945 354 735 .482 92 254 .362 262 481 .545 107 149 .718 77 274 351 196 74 50 134 167 907 8 1970 325 709 .458 121 308 .393 204 401 .509 133 180 .739 79 284 363 186 56 48 109 154 904 Create a csv file from the data. Click to learn how to share information from Sports Reference. Compose a program that reads in the sports data (create an instance of InStream). Produce at least 2 output files (2 instances of OutStream) with filtered data (you choose how you want to filter the data). Create some sort of graph/histogram of your filtered data. Include a comment in your code that demonstrates how to run the program. Example: >>> python myprog.py data.csv
Transcribed Image Text:Total Stats Share & Export Glossary Team Opponent Rk Team G MP FG FGA FG% 3P 3PA 3P% 2P 2PA 2P% FT FTA FT% ORB DRB TRB AST STL BLK TOV PF PTS 1 Charlotte Hornets 2 Indiana Pacers 3 Toronto Raptors 9 2185 383 850 .451 127 321 .396 256 529 .484 139 192 .724 108 301 409 237 84 47 122 165 1032 9 2210 376 809 .465 121 336 .360 255 473 .539 128 164 .780 89 320 409 225 64 57 150 192 1001 9 2160 358 830 .431 98 295 .332 260 535 .486 134 173 .775 124 305 429 179 100 32 123 173 948 4 Cleveland Cavaliers 9 2160 349 771 .453 90 278 .324 259 493 .525 150 197 .761 99 308 407 224 72 36 146 142 938 5 New Orleans Pelicans 6 Orlando Magic 9 2160 348 816 .426 103 305 .338 245 511 .479 130 160 .813 111 315 426 205 66 45 148 175 929 9 2160 323 766 .422 123 351 .350 200 415 .482 141 185 .762 90 318 408 187 50 40 151 190 910 7 Los Angeles Lakers 8 New York Knicks 8 1945 354 735 .482 92 254 .362 262 481 .545 107 149 .718 77 274 351 196 74 50 134 167 907 8 1970 325 709 .458 121 308 .393 204 401 .509 133 180 .739 79 284 363 186 56 48 109 154 904 Create a csv file from the data. Click to learn how to share information from Sports Reference. Compose a program that reads in the sports data (create an instance of InStream). Produce at least 2 output files (2 instances of OutStream) with filtered data (you choose how you want to filter the data). Create some sort of graph/histogram of your filtered data. Include a comment in your code that demonstrates how to run the program. Example: >>> python myprog.py data.csv
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