데이터 자료구조
□ 튜플 ○ 데이터 구조 : 리스트, 튜플, 딕셔너리, 집합 ○ ( )를 이용해 선언할 수 있음 ○ 삭제나 추가가 불가능함 ○ 더하거나 반복하는 것은 가능함 #튜플 선언 tuple_data = (1,2,3,4,5,6,7,8,9,10) tuple_data_copy = (1,2,3,4,5,6,7,8,9,10) #튜플 조회 print(tuple_data) print(tuple_data_copy) print(tuple_data[0]) print(tuple_data[1]) print(tuple_data_copy[0]) print(tuple_data_copy[1]) #형번환 list_data = list(tuple_data) list_data_copy = list(tuple_data_copy) print(type(..
2023. 12. 5.
딕셔너리 ↔ 자료구조 형변환
#json.dumps(dict,indent) #json.dump(dict, file_pointer) #json으로 형변환 d = {"group1":[ {'name':'Park', 'age':'32', 'sex':'Male'}, {'name':'Cho', 'age':'44', 'sex':'Female'}, {'name':'Kang', 'age':'39', 'sex':'Female', 'married':'No'} ], "group2":[ {'name':'Kim', 'age':'23', 'sex':'Male', 'married':'Yes'}, {'name':'Lee', 'age':'37', 'sex':'Male', 'married':'No'} ], "type": {'a':'employee', 'b':'offi..
2023. 11. 7.
딕셔너리 값 추출 예제2
#아래 딕셔너리에 group1에 {'name':'Park', 'age':'32', 'sex':'Male','married':'Yes'} 추가, type에 {'f':'engineer'} 추가 d = {"group1":[ {'name':'Park', 'age':'32', 'sex':'Male'}, {'name':'Cho', 'age':'44', 'sex':'Female'}, {'name':'Kang', 'age':'39', 'sex':'Female', 'married':'No'} ], "group2":[ {'name':'Kim', 'age':'23', 'sex':'Male', 'married':'Yes'}, {'name':'Lee', 'age':'37', 'sex':'Male', 'married':'No'}..
2023. 11. 7.
딕셔너리 값 추출 예제1
#아래 딕셔너리에서 출력결과와 같이 값 추출 #Name : Kim, Age : 23, Type : office' d = {"group1":[ {'name':'Park', 'age':'32', 'sex':'Male'}, {'name':'Cho', 'age':'44', 'sex':'Female'}, {'name':'Kang', 'age':'39', 'sex':'Female', 'married':'No'} ], "group2":[ {'name':'Kim', 'age':'23', 'sex':'Male', 'married':'Yes'}, {'name':'Lee', 'age':'37', 'sex':'Male', 'married':'No'} ], "type": {'a':'employee', 'b':'office', ..
2023. 11. 7.