Overview

Dataset statistics

Number of variables6
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory55.1 B

Variable types

Text4
Numeric2

Dataset

Description대구광역시 동구 관내 시장 및 대형마트에서 조사한 장바구니 대표생필품의 물가정보 데이터입니다. (각 품목에 대한 시장 및 대형마트 가격 정보가 포함되어있습니다.)
Author대구광역시 동구
URLhttps://www.data.go.kr/data/3076626/fileData.do

Alerts

방촌시장 가격 is highly overall correlated with 동촌 홈플러스 가격High correlation
동촌 홈플러스 가격 is highly overall correlated with 방촌시장 가격High correlation
품목 has unique valuesUnique

Reproduction

Analysis started2024-03-14 14:55:38.773510
Analysis finished2024-03-14 14:55:40.481218
Duration1.71 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
2024-03-14T23:55:41.091349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.28
Min length1

Characters and Unicode

Total characters57
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row햅쌀
2nd row고구마
3rd row콩
4th row쇠고기
5th row돼지고기
ValueCountFrequency (%)
햅쌀 1
 
4.0%
명태 1
 
4.0%
소주 1
 
4.0%
맥주 1
 
4.0%
두부 1
 
4.0%
참기름 1
 
4.0%
식용유 1
 
4.0%
참치캔 1
 
4.0%
당면 1
 
4.0%
밀가루 1
 
4.0%
Other values (15) 15
60.0%
2024-03-14T23:55:42.025876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
고 6
 
10.5%
기 5
 
8.8%
주 3
 
5.3%
추 2
 
3.5%
마 2
 
3.5%
참 2
 
3.5%
햅 1
 
1.8%
가 1
 
1.8%
루 1
 
1.8%
당 1
 
1.8%
Other values (33) 33
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 6
 
10.5%
기 5
 
8.8%
주 3
 
5.3%
추 2
 
3.5%
마 2
 
3.5%
참 2
 
3.5%
햅 1
 
1.8%
가 1
 
1.8%
루 1
 
1.8%
당 1
 
1.8%
Other values (33) 33
57.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 6
 
10.5%
기 5
 
8.8%
주 3
 
5.3%
추 2
 
3.5%
마 2
 
3.5%
참 2
 
3.5%
햅 1
 
1.8%
가 1
 
1.8%
루 1
 
1.8%
당 1
 
1.8%
Other values (33) 33
57.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
고 6
 
10.5%
기 5
 
8.8%
주 3
 
5.3%
추 2
 
3.5%
마 2
 
3.5%
참 2
 
3.5%
햅 1
 
1.8%
가 1
 
1.8%
루 1
 
1.8%
당 1
 
1.8%
Other values (33) 33
57.9%

용량
Text

Distinct21
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
2024-03-14T23:55:42.703674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length6.6
Min length2

Characters and Unicode

Total characters165
Distinct characters49
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)72.0%

Sample

1st row20kg
2nd row1kg
3rd row500g(백태)
4th row600g
5th row600g
ValueCountFrequency (%)
1마리 3
 
12.0%
600g 2
 
8.0%
1봉 2
 
8.0%
500g(자른당면/1봉 1
 
4.0%
20kg 1
 
4.0%
1kg(중력분 1
 
4.0%
360ml(16.9도/1병 1
 
4.0%
640ml(1병 1
 
4.0%
380g(1모 1
 
4.0%
320ml(병용기/1병 1
 
4.0%
Other values (11) 11
44.0%
2024-03-14T23:55:43.793593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23
 
13.9%
0 17
 
10.3%
( 13
 
7.9%
) 13
 
7.9%
g 11
 
6.7%
병 6
 
3.6%
마 5
 
3.0%
/ 5
 
3.0%
k 5
 
3.0%
6 5
 
3.0%
Other values (39) 62
37.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
36.4%
Other Letter 47
28.5%
Lowercase Letter 24
 
14.5%
Open Punctuation 13
 
7.9%
Close Punctuation 13
 
7.9%
Other Punctuation 7
 
4.2%
Uppercase Letter 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
병 6
 
12.8%
마 5
 
10.6%
리 4
 
8.5%
봉 3
 
6.4%
수 2
 
4.3%
기 2
 
4.3%
개 2
 
4.3%
용 1
 
2.1%
옥 1
 
2.1%
도 1
 
2.1%
Other values (20) 20
42.6%
Decimal Number
ValueCountFrequency (%)
1 23
38.3%
0 17
28.3%
6 5
 
8.3%
5 4
 
6.7%
3 3
 
5.0%
2 3
 
5.0%
8 2
 
3.3%
4 1
 
1.7%
9 1
 
1.7%
7 1
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
g 11
45.8%
k 5
20.8%
l 4
 
16.7%
m 4
 
16.7%
Other Punctuation
ValueCountFrequency (%)
/ 5
71.4%
. 2
 
28.6%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 93
56.4%
Hangul 47
28.5%
Latin 25
 
15.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
병 6
 
12.8%
마 5
 
10.6%
리 4
 
8.5%
봉 3
 
6.4%
수 2
 
4.3%
기 2
 
4.3%
개 2
 
4.3%
용 1
 
2.1%
옥 1
 
2.1%
도 1
 
2.1%
Other values (20) 20
42.6%
Common
ValueCountFrequency (%)
1 23
24.7%
0 17
18.3%
( 13
14.0%
) 13
14.0%
/ 5
 
5.4%
6 5
 
5.4%
5 4
 
4.3%
3 3
 
3.2%
2 3
 
3.2%
. 2
 
2.2%
Other values (4) 5
 
5.4%
Latin
ValueCountFrequency (%)
g 11
44.0%
k 5
20.0%
l 4
 
16.0%
m 4
 
16.0%
L 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118
71.5%
Hangul 47
 
28.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23
19.5%
0 17
14.4%
( 13
11.0%
) 13
11.0%
g 11
9.3%
/ 5
 
4.2%
k 5
 
4.2%
6 5
 
4.2%
l 4
 
3.4%
5 4
 
3.4%
Other values (9) 18
15.3%
Hangul
ValueCountFrequency (%)
병 6
 
12.8%
마 5
 
10.6%
리 4
 
8.5%
봉 3
 
6.4%
수 2
 
4.3%
기 2
 
4.3%
개 2
 
4.3%
용 1
 
2.1%
옥 1
 
2.1%
도 1
 
2.1%
Other values (20) 20
42.6%

방촌시장 가격
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9852
Minimum1500
Maximum62900
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size353.0 B
2024-03-14T23:55:43.999815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1500
5-th percentile1680
Q12950
median5000
Q38000
95-th percentile50200
Maximum62900
Range61400
Interquartile range (IQR)5050

Descriptive statistics

Standard deviation15732.891
Coefficient of variation (CV)1.5969235
Kurtosis8.6303952
Mean9852
Median Absolute Deviation (MAD)2800
Skewness3.0638762
Sum246300
Variance2.4752385 × 108
MonotonicityNot monotonic
2024-03-14T23:55:44.207176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
2200 3
 
12.0%
62900 1
 
4.0%
5000 1
 
4.0%
9500 1
 
4.0%
1550 1
 
4.0%
2950 1
 
4.0%
8500 1
 
4.0%
7500 1
 
4.0%
7800 1
 
4.0%
5800 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
1500 1
 
4.0%
1550 1
 
4.0%
2200 3
12.0%
2500 1
 
4.0%
2950 1
 
4.0%
3300 1
 
4.0%
3500 1
 
4.0%
3650 1
 
4.0%
4000 1
 
4.0%
4050 1
 
4.0%
ValueCountFrequency (%)
62900 1
4.0%
59000 1
4.0%
15000 1
4.0%
10700 1
4.0%
9500 1
4.0%
8500 1
4.0%
8000 1
4.0%
7800 1
4.0%
7500 1
4.0%
7000 1
4.0%

비고1
Text

Distinct17
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
2024-03-14T23:55:44.699365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length4.76
Min length2

Characters and Unicode

Total characters119
Distinct characters63
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)64.0%

Sample

1st row안계쌀
2nd row국산
3rd row국산
4th row한우
5th row국산
ValueCountFrequency (%)
국산 9
33.3%
안계쌀 1
 
3.7%
오뚜기 1
 
3.7%
참소주 1
 
3.7%
카스 1
 
3.7%
180g 1
 
3.7%
풀무원 1
 
3.7%
옛날참기름 1
 
3.7%
해표식용유 1
 
3.7%
동원(135g*4개 1
 
3.7%
Other values (9) 9
33.3%
2024-03-14T23:55:45.691930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
21.0%
국 10
 
8.4%
산 10
 
8.4%
주 3
 
2.5%
0 3
 
2.5%
오 2
 
1.7%
g 2
 
1.7%
1 2
 
1.7%
( 2
 
1.7%
원 2
 
1.7%
Other values (53) 58
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74
62.2%
Space Separator 25
 
21.0%
Decimal Number 10
 
8.4%
Lowercase Letter 4
 
3.4%
Open Punctuation 2
 
1.7%
Close Punctuation 2
 
1.7%
Other Punctuation 2
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 10
 
13.5%
산 10
 
13.5%
주 3
 
4.1%
오 2
 
2.7%
원 2
 
2.7%
표 2
 
2.7%
해 2
 
2.7%
참 2
 
2.7%
기 2
 
2.7%
무 1
 
1.4%
Other values (38) 38
51.4%
Decimal Number
ValueCountFrequency (%)
0 3
30.0%
1 2
20.0%
7 1
 
10.0%
8 1
 
10.0%
3 1
 
10.0%
4 1
 
10.0%
5 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
g 2
50.0%
m 1
25.0%
l 1
25.0%
Other Punctuation
ValueCountFrequency (%)
* 1
50.0%
/ 1
50.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74
62.2%
Common 41
34.5%
Latin 4
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 10
 
13.5%
산 10
 
13.5%
주 3
 
4.1%
오 2
 
2.7%
원 2
 
2.7%
표 2
 
2.7%
해 2
 
2.7%
참 2
 
2.7%
기 2
 
2.7%
무 1
 
1.4%
Other values (38) 38
51.4%
Common
ValueCountFrequency (%)
25
61.0%
0 3
 
7.3%
1 2
 
4.9%
( 2
 
4.9%
) 2
 
4.9%
7 1
 
2.4%
8 1
 
2.4%
3 1
 
2.4%
4 1
 
2.4%
* 1
 
2.4%
Other values (2) 2
 
4.9%
Latin
ValueCountFrequency (%)
g 2
50.0%
m 1
25.0%
l 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74
62.2%
ASCII 45
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
55.6%
0 3
 
6.7%
g 2
 
4.4%
1 2
 
4.4%
( 2
 
4.4%
) 2
 
4.4%
m 1
 
2.2%
7 1
 
2.2%
8 1
 
2.2%
3 1
 
2.2%
Other values (5) 5
 
11.1%
Hangul
ValueCountFrequency (%)
국 10
 
13.5%
산 10
 
13.5%
주 3
 
4.1%
오 2
 
2.7%
원 2
 
2.7%
표 2
 
2.7%
해 2
 
2.7%
참 2
 
2.7%
기 2
 
2.7%
무 1
 
1.4%
Other values (38) 38
51.4%

동촌 홈플러스 가격
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10559.2
Minimum1550
Maximum63840
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size353.0 B
2024-03-14T23:55:46.058001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1550
5-th percentile1966
Q13490
median5980
Q38390
95-th percentile51788
Maximum63840
Range62290
Interquartile range (IQR)4900

Descriptive statistics

Standard deviation15928.633
Coefficient of variation (CV)1.5085075
Kurtosis8.2131219
Mean10559.2
Median Absolute Deviation (MAD)2490
Skewness2.9820802
Sum263980
Variance2.5372134 × 108
MonotonicityNot monotonic
2024-03-14T23:55:46.440758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
6990 2
 
8.0%
59800 1
 
4.0%
3500 1
 
4.0%
8390 1
 
4.0%
1550 1
 
4.0%
1960 1
 
4.0%
3200 1
 
4.0%
7690 1
 
4.0%
7480 1
 
4.0%
7990 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
1550 1
4.0%
1960 1
4.0%
1990 1
4.0%
2550 1
4.0%
2690 1
4.0%
3200 1
4.0%
3490 1
4.0%
3500 1
4.0%
3990 1
4.0%
4000 1
4.0%
ValueCountFrequency (%)
63840 1
4.0%
59800 1
4.0%
19740 1
4.0%
11900 1
4.0%
9990 1
4.0%
8490 1
4.0%
8390 1
4.0%
7990 1
4.0%
7690 1
4.0%
7480 1
4.0%

비고2
Text

Distinct16
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
2024-03-14T23:55:47.006562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length3
Mean length4.88
Min length2

Characters and Unicode

Total characters122
Distinct characters62
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)60.0%

Sample

1st row경기미
2nd row국산
3rd row국산
4th row한우
5th row국산
ValueCountFrequency (%)
국산 10
35.7%
오뚜기 1
 
3.6%
참소주 1
 
3.6%
카스 1
 
3.6%
210g 1
 
3.6%
풀무원 1
 
3.6%
옛날참기름 1
 
3.6%
해표식용유 1
 
3.6%
동원(135g*4개 1
 
3.6%
백설 1
 
3.6%
Other values (9) 9
32.1%
2024-03-14T23:55:47.729430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28
23.0%
국 10
 
8.2%
산 10
 
8.2%
0 3
 
2.5%
기 3
 
2.5%
주 3
 
2.5%
( 2
 
1.6%
원 2
 
1.6%
g 2
 
1.6%
) 2
 
1.6%
Other values (52) 57
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 75
61.5%
Space Separator 28
 
23.0%
Decimal Number 10
 
8.2%
Lowercase Letter 4
 
3.3%
Open Punctuation 2
 
1.6%
Close Punctuation 2
 
1.6%
Other Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 10
 
13.3%
산 10
 
13.3%
기 3
 
4.0%
주 3
 
4.0%
원 2
 
2.7%
래 2
 
2.7%
유 2
 
2.7%
참 2
 
2.7%
경 2
 
2.7%
무 1
 
1.3%
Other values (38) 38
50.7%
Decimal Number
ValueCountFrequency (%)
0 3
30.0%
1 2
20.0%
7 1
 
10.0%
4 1
 
10.0%
2 1
 
10.0%
5 1
 
10.0%
3 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
g 2
50.0%
m 1
25.0%
l 1
25.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
* 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 75
61.5%
Common 43
35.2%
Latin 4
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 10
 
13.3%
산 10
 
13.3%
기 3
 
4.0%
주 3
 
4.0%
원 2
 
2.7%
래 2
 
2.7%
유 2
 
2.7%
참 2
 
2.7%
경 2
 
2.7%
무 1
 
1.3%
Other values (38) 38
50.7%
Common
ValueCountFrequency (%)
28
65.1%
0 3
 
7.0%
( 2
 
4.7%
) 2
 
4.7%
1 2
 
4.7%
7 1
 
2.3%
* 1
 
2.3%
4 1
 
2.3%
2 1
 
2.3%
5 1
 
2.3%
Latin
ValueCountFrequency (%)
g 2
50.0%
m 1
25.0%
l 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 75
61.5%
ASCII 47
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28
59.6%
0 3
 
6.4%
( 2
 
4.3%
g 2
 
4.3%
) 2
 
4.3%
1 2
 
4.3%
m 1
 
2.1%
7 1
 
2.1%
* 1
 
2.1%
4 1
 
2.1%
Other values (4) 4
 
8.5%
Hangul
ValueCountFrequency (%)
국 10
 
13.3%
산 10
 
13.3%
기 3
 
4.0%
주 3
 
4.0%
원 2
 
2.7%
래 2
 
2.7%
유 2
 
2.7%
참 2
 
2.7%
경 2
 
2.7%
무 1
 
1.3%
Other values (38) 38
50.7%

Interactions

2024-03-14T23:55:39.839813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:55:39.141055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:55:40.027655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:55:39.589808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:55:47.989125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목용량방촌시장 가격비고1동촌 홈플러스 가격비고2
품목1.0001.0001.0001.0001.0001.000
용량1.0001.0000.0000.6770.0000.816
방촌시장 가격1.0000.0001.0000.0000.9950.000
비고11.0000.6770.0001.0000.0001.000
동촌 홈플러스 가격1.0000.0000.9950.0001.0000.000
비고21.0000.8160.0001.0000.0001.000
2024-03-14T23:55:48.251307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
방촌시장 가격동촌 홈플러스 가격
방촌시장 가격1.0000.934
동촌 홈플러스 가격0.9341.000

Missing values

2024-03-14T23:55:40.224340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:55:40.405052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

품목용량방촌시장 가격비고1동촌 홈플러스 가격비고2
0햅쌀20kg62900안계쌀59800경기미
1고구마1kg4000국산6990국산
2콩500g(백태)7000국산9990국산
3쇠고기600g59000한우63840한우
4돼지고기600g15000국산19740국산
5닭고기1마리(생닭)8000국산8490국산
6달걀10개4050신선알찬란3990신선란
7배추1단(2통)2500국산2690국산
8무1개2200국산1990국산
9양파5kg3300국산4290국산
품목용량방촌시장 가격비고1동촌 홈플러스 가격비고2
15김1봉3650해표 재래김6990올리브유에 구운 파래재래김
16밀가루1kg(중력분)2200백설2550백설
17당면500g(자른당면/1봉)5800오뚜기5980오뚜기
18참치캔150g(살코기/1캔)7800동원(135g*4개)7990동원(135g*4개)
19식용유1.8L(옥수수유/1병)7500해표식용유7480해표식용유
20참기름320ml(병용기/1병)8500옛날참기름7690옛날참기름
21두부380g(1모)2950풀무원 180g3200풀무원 210g
22맥주640ml(1병)2200카스1960카스
23소주360ml(16.9도/1병)1550참소주1550참소주
24청주700ml(1병)9500경주법주(700ml)8390경주법주(700ml)