imported>lyuha |
imported>lyuha |
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| == 팀명 ==
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| '''eval'''
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| == 팀원 ==
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| [[권영기]], [[이원준]]
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| == 코드 ==
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| === phase1 ===
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| number = []
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| for i range(5):
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| number.append(input())
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| max(number)
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| === phase2 ===
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| number = []
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|
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| input = open("input.txt", encoding="utf-8").read().split("\n");
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| input.pop(0)
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|
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| for x in input[0].split():
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| number.append(int(x))
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|
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| print(max(number))
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| === phase3 ===
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| number = []
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|
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| input = open("input.txt", encoding="utf-8").read().split("\n");
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| input.pop(0)
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|
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| for x in input[0].split():
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| try:
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| number.append(int(x))
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| except ValueError:
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| continue
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|
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| try:
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| print(max(number))
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| except ValueError:
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| print("NaN")
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| finally:
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| pass
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| === phase4 ===
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| import math
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|
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| matrix = []
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|
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| input = open("input_matrix.txt", encoding="utf-8").read().split("\n");
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| row_length, col_length = map(int, input.pop(0).split())
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|
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| for x in input:
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| row = []
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| for number in x.split():
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| try:
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| row.append(int(number))
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| except ValueError:
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| row.append('NaN')
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| matrix.append(row)
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|
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| column_max = []
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| row_max = []
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|
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| for i in range(row_length):
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| row = []
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| for j in range(col_length):
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| if(type(matrix[i][j]) is int):
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| row.append(matrix[i][j])
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| if(len(row) > 0):
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| row_max.append(max(row))
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| else:
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| row_max.append("NaN")
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|
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| for i in range(col_length):
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| column = []
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| for j in range(row_length):
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| if(type(matrix[j][i]) is int):
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| column.append(matrix[j][i])
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| if(len(column) > 0):
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| column_max.append(max(column))
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| else:
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| column_max.append("NaN")
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|
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| print(column_max)
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| print(row_max)
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| for i in range(len(column_max)):
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| print("column ", i, " : ", column_max[i])
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| for i in range(len(row_max)):
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| print("row", i, " : ", row_max[i])
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| print(max([max([x for x in column_max if type(x) is int]), max([x for x in row_max if type(x) is int])]))
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| === phase final ===
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| import math
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|
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| del __builtins__.exit
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|
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| matrix = []
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|
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| input = open("input final.txt", encoding="utf-8").read().split("\n");
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| row_length, col_length = map(int, input.pop(0).split())
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|
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| for x in input:
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| row = []
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| for number in x.split():
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| try:
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| row.append(eval(number))
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| except NameError:
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| row.append('NaN')
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| except SyntaxError:
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| row.append('NaN')
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| except ValueError:
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| row.append('NaN')
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| matrix.append(row)
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|
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| column_max = []
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| row_max = []
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|
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| for i in range(row_length):
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| row = []
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| for j in range(col_length):
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| if(type(matrix[i][j]) is int):
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| row.append(matrix[i][j])
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| if(len(row) > 0):
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| row_max.append(max(row))
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| else:
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| row_max.append("NaN")
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|
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| for i in range(col_length):
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| column = []
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| for j in range(row_length):
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| if(type(matrix[j][i]) is int):
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| column.append(matrix[j][i])
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| if(len(column) > 0):
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| column_max.append(max(column))
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| else:
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| column_max.append("NaN")
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|
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| print(column_max)
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| print(row_max)
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| for i in range(len(column_max)):
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| print("column ", i, " : ", column_max[i])
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| for i in range(len(row_max)):
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| print("row", i, " : ", row_max[i])
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| print(max([max([x for x in column_max if type(x) is int]), max([x for x in row_max if type(x) is int])]))
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|
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|
