기록하는 습관

[SQL] (해커랭크) Weather Observation Station 1

Avalla — Sat, 19 Aug 2023 00:47:34 +0900

Problem

HackerRank > Prepare > SQL > Basic Select > Weather Observation Station 1

Query a list of CITY and STATE from the STATION table.
The STATION table is described as follows:

where LAT_N is the northern latitude and LONG_W is the western longitude.

Solution

SELECT DISTINCT CITY, STATE
FROM STATION
;

[SQL] (해커랭크) Japanese Cities' Names

Avalla — Fri, 18 Aug 2023 18:38:58 +0900

Problem

HackerRank > Prepare > SQL > Basic Select > Japanese Cities' Names

Query the names of all the Japanese cities in the CITY table. The COUNTRYCODE for Japan is JPN.
The CITY table is described as follows:

Solution

SELECT NAME
FROM CITY
WHERE 1=1
and COUNTRYCODE = 'JPN'
;

[SQL] (해커랭크) Japanese Cities' Attributes

Avalla — Thu, 17 Aug 2023 23:35:30 +0900

Problem

HackerRank > Prepare > SQL > Basic Select > Japanese Cities' Attributes

Query all attributes of every Japanese city in the CITY table. The COUNTRYCODE for Japan is JPN.

The CITY table is described as follows:

Solution

SELECT *
FROM CITY
WHERE 1=1
and COUNTRYCODE = 'JPN'
;

[Python] 예외처리 : try ~ excpet 구문

Avalla — Wed, 16 Aug 2023 17:54:06 +0900

try ~ except

for i in [2,0,'-2'] :
    try :
        print(4/i)
    except :
        print('Error')

2.0
Error
Error

try ~ except ~ as

에러 구문을 확인하고 싶을 떄

for i in [2,0,'-2'] :
    try :
        print(4/i)
    except Exception as e:
        print(e)

2.0
division by zero
unsupported operand type(s) for /: 'int' and 'str'

try ~ except ~ else

에러가 나지 않았을 때 else 구문을 실행

List = [2,0,'-2','A']
for i in range(5) :
    print(f"_____{i} START_____")
    try :
        result = 4/int(List[i])
        print("▶ result 업데이트")
    except Exception as e:
        print('에러 :', e)
    else :
        print(f"현재 i : {i}, result : {result}")

_____0 START_____
▶ result 업데이트
현재 i : 0, result : 2.0
_____1 START_____
에러 : division by zero
_____2 START_____
▶ result 업데이트
현재 i : 2, result : -2.0
_____3 START_____
에러 : invalid literal for int() with base 10: 'A'
_____4 START_____
에러 : list index out of range

위 예시와 비교

List = [2,0,'-2','A']
for i in range(5) :
    print(f"_____{i} START_____")
    try :
        result = 4/int(List[i])
        print("▶ result 업데이트")
    except Exception as e:
        print('에러 :', e)
    print(f"현재 i : {i}, result : {result}")

_____0 START_____
▶ result 업데이트
현재 i : 0, result : 2.0
_____1 START_____
에러 : division by zero
현재 i : 1, result : 2.0
_____2 START_____
▶ result 업데이트
현재 i : 2, result : -2.0
_____3 START_____
에러 : invalid literal for int() with base 10: 'A'
현재 i : 3, result : -2.0
_____4 START_____
에러 : list index out of range
현재 i : 4, result : -2.0

try ~ except ~ finally

finally는 없어도 위와 결과가 같음

List = [2,0,'-2','A']
for i in range(5) :
    print(f"_____{i} START_____")
    try :
        result = 4/int(List[i])
        print("▶ result 업데이트")
    except Exception as e:
        print('에러 :', e)
    finally :
        print(f"현재 i : {i}, result : {result}")

_____0 START_____
▶ result 업데이트
현재 i : 0, result : 2.0
_____1 START_____
에러 : division by zero
현재 i : 1, result : 2.0
_____2 START_____
▶ result 업데이트
현재 i : 2, result : -2.0
_____3 START_____
에러 : invalid literal for int() with base 10: 'A'
현재 i : 3, result : -2.0
_____4 START_____
에러 : list index out of range
현재 i : 4, result : -2.0

Built-in Exception

IndexError : Index 범위 에러

NameError : 존재하지 않는 변수일 경우

ZeroDivisionError : 0으로 수를 나눌 때

ValueError : 타입에 관한 에러

FileNotFoundError : 존재하지 않는 파일 호출

for i in [2,0,'-2'] :
    try :
        print(4/i)
    except ZeroDivisionError :
        print('ZeroDivisionError')
    except :
        print('Error : 미리 분류해두지 않은 에러')

2.0
ZeroDivisionError
Error : 미리 분류해두지 않은 에러

List = [2,0,'-2','A']
for i in range(5) :
    print(f"_____{i} START_____")
    try :
        result = 4/int(List[i])
        print("▶ result 업데이트")
        print(f"현재 i : {i}, result : {result}")
    except ZeroDivisionError as z:
        print('ZeroDivisionError :', z)
    except ValueError as v:
        print('ValueError :', v)
    except IndexError as I :
        print('IndexError :', I)
    except Exception as e:
        print('미리 분류해두지 않은 에러 :', e)

_____0 START_____
▶ result 업데이트
현재 i : 0, result : 2.0
_____1 START_____
ZeroDivisionError : division by zero
_____2 START_____
▶ result 업데이트
현재 i : 2, result : -2.0
_____3 START_____
ValueError : invalid literal for int() with base 10: 'A'
_____4 START_____
IndexError : list index out of range

[SQL] (해커랭크) Select By ID

Avalla — Tue, 15 Aug 2023 16:38:07 +0900

Problem

HackerRank > Prepare > SQL > Basic Select > Select By ID

Query all columns for a city in CITY with the ID 1661.

The CITY table is described as follows:

Solution

SELECT *
FROM CITY
WHERE 1=1
and ID = 1661
;

[SQL] (해커랭크) Select All

Avalla — Mon, 14 Aug 2023 16:25:34 +0900

Problem

HackerRank > Prepare > SQL > Basic Select > Select All

Query all columns (attributes) for every row in the CITY table.

The CITY table is described as follows:

Solution

SELECT *
FROM CITY
;

[SQL] (해커랭크) Revising the Select Query II

Avalla — Sun, 13 Aug 2023 16:17:46 +0900

Problem

HackerRank > Prepare > SQL > Basic Select > Revising the Select Query II

Query the NAME field for all American cities in the CITY table with populations larger than 120000. The CountryCode for America is USA.

The CITY table is described as follows:

Solution

SELECT NAME
FROM CITY
WHERE 1=1
and COUNTRYCODE = 'USA'
and POPULATION > 120000

[SQL] (해커랭크) Revising the Select Query I

Avalla — Sat, 12 Aug 2023 15:04:23 +0900

Problem

HackerRank > Prepare > SQL > Basic Select > Revising the Select Query I

Query all columns for all American cities in the CITY table with populations larger than 100000. The CountryCode for America is USA.

The CITY table is described as follows:

Solution

SELECT *
FROM CITY
WHERE 1=1
and COUNTRYCODE = 'USA'
and POPULATION > 100000
;

[Numpy] 011. 파일 읽기&쓰기 (I/O)

Avalla — Fri, 11 Aug 2023 18:29:27 +0900

Numpy Data i/o

import numpy as np

txt 파일 저장

np.savetxt(파일명, 배열, fmt=문자열형식, delimiter=구분자)

아래 예시 배열을 저장해보자.

array_save = np.arange(20).reshape(4,5)
print( array_save )

[[ 0  1  2  3  4]
 [ 5  6  7  8  9]
 [10 11 12 13 14]
 [15 16 17 18 19]]

fmt 값을 '%d'(정수)로 주지 않으면 실수 값으로 저장이 된다.

np.savetxt("./sample_tab.txt", array_save, fmt='%d', delimiter="\t")

아래와 같이 잘 저장됨을 확인하였다.

txt 파일 로드

np.loadtxt(파일명, dtype=데이터타입, delimiter=구분자)

array_load = np.loadtxt("./sample_tab.txt", dtype=int, delimiter="\t")
print(array_load)

[[ 0  1  2  3  4]
 [ 5  6  7  8  9]
 [10 11 12 13 14]
 [15 16 17 18 19]]

npy 파일 저장

np.save(파일명, 배열)

.npy 파일은 Numpy 전용 저장 형식이라 .txt파일처럼 메모장으로 열어서 데이터를 직접 확인할 수는 없다. 속도와 용량 측면에서 유리할 수 있다.

아래와 같이 배열을 저장하면 './sample_npy.npy' 파일이 생성된다.

array_save = np.arange(20).reshape(4,5)
print( array_save )
np.save("sample_npy", array_save)

[[ 0  1  2  3  4]
 [ 5  6  7  8  9]
 [10 11 12 13 14]
 [15 16 17 18 19]]

array_load = np.load("sample_npy.npy")
print( array_load )
print( type(array_load) )

[[ 0  1  2  3  4]
 [ 5  6  7  8  9]
 [10 11 12 13 14]
 [15 16 17 18 19]]
<class 'numpy.ndarray'>

위와 같이 배열 형식이 잘 로드된다.

[Numpy] 010. 랜덤 표본 추출 (Random Sampling)

Avalla — Thu, 10 Aug 2023 18:00:41 +0900

샘플링 함수들

import numpy as np

np.random.uniform(하한, 상한, 형태)

Docstring:

uniform(low=0.0, high=1.0, size=None)

Draw samples from a uniform distribution.

Samples are uniformly distributed over the half-open interval
[low, high) (includes low, but excludes high). In other words,
any value within the given interval is equally likely to be drawn
by uniform.

print( np.random.uniform(0, 1, 5) )
print( np.random.uniform(0, 1, (2,3)) )

[0.71029172 0.00673713 0.42074585 0.53413197 0.62083628]
[[0.46548593 0.62558901 0.2386203 ]
 [0.49704519 0.06470508 0.0865601 ]]

np.random.normal(평균, 표준편차, 형태)

print( np.random.normal(0, 1, 4) )
print( np.random.normal(50, 10, (2,2)) )
print( np.random.normal(0, 1, 1000000).mean() )

[ 0.77727106  0.91040219 -0.70066303  1.31100763]
[[42.03442125 54.90997165]
 [57.27299351 60.1309165 ]]
0.0004011744654032617

import pandas as pd
pd.DataFrame({"sample":np.random.normal(0, 1, 1000)}).hist()

np.random.randint(상한, 하한, 형태)

Docstring:

randint(low, high=None, size=None, dtype=int)

Return random integers from low (inclusive) to high (exclusive).

Return random integers from the "discrete uniform" distribution of
the specified dtype in the "half-open" interval [low, high). If
high is None (the default), then results are from [0, low).

print( np.random.randint(0, 10, (3,4)) )
print( np.random.randint(0, 10, (3,1,1)) )

[[4 5 5 5]
 [9 4 5 8]
 [0 3 0 3]]
[[[8]]

 [[3]]

 [[6]]]

np.random.choice(1차원배열, 형태)

Docstring:

choice(a, size=None, replace=True, p=None)

Generates a random sample from a given 1-D array

print( np.random.choice(['가위', '바위', '보']) )
print( np.random.choice(['가위', '바위', '보'], size=0) )
print( np.random.choice(['가위', '바위', '보'], size=1) )
print( np.random.choice(['가위', '바위', '보'], size=(2,2)) )

보
[]
['바위']
[['바위' '바위']
 ['보' '가위']]