Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells76
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory126.0 B

Variable types

Numeric5
Text4
Categorical5

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-1170/S/1/datasetView.do

Alerts

년도-월 is highly overall correlated with 일련번호 and 1 other fieldsHigh correlation
점검일자 is highly overall correlated with 일련번호 and 1 other fieldsHigh correlation
시장유형 구분(시장/마트) 코드 is highly overall correlated with 시장유형 구분(시장/마트) 이름High correlation
시장유형 구분(시장/마트) 이름 is highly overall correlated with 시장유형 구분(시장/마트) 코드High correlation
일련번호 is highly overall correlated with 년도-월 and 1 other fieldsHigh correlation
시장/마트 번호 is highly overall correlated with 자치구 코드 and 1 other fieldsHigh correlation
자치구 코드 is highly overall correlated with 시장/마트 번호 and 1 other fieldsHigh correlation
자치구 이름 is highly overall correlated with 시장/마트 번호 and 1 other fieldsHigh correlation
일련번호 has unique valuesUnique

Reproduction

Analysis started2024-05-11 06:35:22.702334
Analysis finished2024-05-11 06:35:30.177099
Duration7.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1662166.2
Minimum1631293
Maximum1692959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:35:30.341755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1631293
5-th percentile1634423.9
Q11646907.2
median1661851
Q31677754.2
95-th percentile1689881.1
Maximum1692959
Range61666
Interquartile range (IQR)30847

Descriptive statistics

Standard deviation17834.556
Coefficient of variation (CV)0.010729707
Kurtosis-1.2077593
Mean1662166.2
Median Absolute Deviation (MAD)15423.5
Skewness0.0061855869
Sum1.6621662 × 1010
Variance3.180714 × 108
MonotonicityNot monotonic
2024-05-11T15:35:30.690749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1646077 1
 
< 0.1%
1650409 1
 
< 0.1%
1661888 1
 
< 0.1%
1669867 1
 
< 0.1%
1645980 1
 
< 0.1%
1663903 1
 
< 0.1%
1659156 1
 
< 0.1%
1675804 1
 
< 0.1%
1634283 1
 
< 0.1%
1676759 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1631293 1
< 0.1%
1631300 1
< 0.1%
1631306 1
< 0.1%
1631307 1
< 0.1%
1631311 1
< 0.1%
1631314 1
< 0.1%
1631324 1
< 0.1%
1631332 1
< 0.1%
1631340 1
< 0.1%
1631342 1
< 0.1%
ValueCountFrequency (%)
1692959 1
< 0.1%
1692952 1
< 0.1%
1692947 1
< 0.1%
1692930 1
< 0.1%
1692929 1
< 0.1%
1692924 1
< 0.1%
1692923 1
< 0.1%
1692922 1
< 0.1%
1692906 1
< 0.1%
1692893 1
< 0.1%

시장/마트 번호
Real number (ℝ)

HIGH CORRELATION 

Distinct102
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.7191
Minimum1
Maximum228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:35:30.921025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q145
median94
Q3147
95-th percentile222
Maximum228
Range227
Interquartile range (IQR)102

Descriptive statistics

Standard deviation69.005953
Coefficient of variation (CV)0.65896244
Kurtosis-1.0040402
Mean104.7191
Median Absolute Deviation (MAD)51
Skewness0.37945558
Sum1047191
Variance4761.8216
MonotonicityNot monotonic
2024-05-11T15:35:31.154928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
214 136
 
1.4%
223 134
 
1.3%
103 127
 
1.3%
73 121
 
1.2%
88 120
 
1.2%
100 117
 
1.2%
133 116
 
1.2%
220 115
 
1.1%
91 115
 
1.1%
2 114
 
1.1%
Other values (92) 8785
87.8%
ValueCountFrequency (%)
1 93
0.9%
2 114
1.1%
6 93
0.9%
8 101
1.0%
10 102
1.0%
11 106
1.1%
13 90
0.9%
14 102
1.0%
15 104
1.0%
16 102
1.0%
ValueCountFrequency (%)
228 95
0.9%
227 86
0.9%
226 3
 
< 0.1%
225 1
 
< 0.1%
224 106
1.1%
223 134
1.3%
222 81
0.8%
221 101
1.0%
220 115
1.1%
219 103
1.0%

시장/마트 이름
Text

Distinct102
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:35:31.492951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.7607
Min length4

Characters and Unicode

Total characters67607
Distinct characters141
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row청담삼익시장
2nd row광장시장
3rd row숭인시장
4th row숭인시장
5th row이마트 왕십리점
ValueCountFrequency (%)
이마트 1492
 
10.0%
홈플러스 1180
 
7.9%
롯데백화점 814
 
5.5%
미아점 407
 
2.7%
강남점 288
 
1.9%
목동점 270
 
1.8%
롯데마트 213
 
1.4%
하나로클럽 198
 
1.3%
잠실점 198
 
1.3%
신세계백화점 194
 
1.3%
Other values (94) 9599
64.6%
2024-05-11T15:35:32.101327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 6051
 
9.0%
장 5129
 
7.6%
시 4991
 
7.4%
4853
 
7.2%
마 2207
 
3.3%
트 2004
 
3.0%
이 1706
 
2.5%
화 1676
 
2.5%
백 1486
 
2.2%
동 1355
 
2.0%
Other values (131) 36149
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61629
91.2%
Space Separator 4853
 
7.2%
Uppercase Letter 380
 
0.6%
Decimal Number 323
 
0.5%
Close Punctuation 211
 
0.3%
Open Punctuation 211
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 6051
 
9.8%
장 5129
 
8.3%
시 4991
 
8.1%
마 2207
 
3.6%
트 2004
 
3.3%
이 1706
 
2.8%
화 1676
 
2.7%
백 1486
 
2.4%
동 1355
 
2.2%
신 1232
 
2.0%
Other values (123) 33792
54.8%
Decimal Number
ValueCountFrequency (%)
4 112
34.7%
3 112
34.7%
1 99
30.7%
Uppercase Letter
ValueCountFrequency (%)
C 190
50.0%
N 190
50.0%
Space Separator
ValueCountFrequency (%)
4853
100.0%
Close Punctuation
ValueCountFrequency (%)
) 211
100.0%
Open Punctuation
ValueCountFrequency (%)
( 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61629
91.2%
Common 5598
 
8.3%
Latin 380
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 6051
 
9.8%
장 5129
 
8.3%
시 4991
 
8.1%
마 2207
 
3.6%
트 2004
 
3.3%
이 1706
 
2.8%
화 1676
 
2.7%
백 1486
 
2.4%
동 1355
 
2.2%
신 1232
 
2.0%
Other values (123) 33792
54.8%
Common
ValueCountFrequency (%)
4853
86.7%
) 211
 
3.8%
( 211
 
3.8%
4 112
 
2.0%
3 112
 
2.0%
1 99
 
1.8%
Latin
ValueCountFrequency (%)
C 190
50.0%
N 190
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61629
91.2%
ASCII 5978
 
8.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 6051
 
9.8%
장 5129
 
8.3%
시 4991
 
8.1%
마 2207
 
3.6%
트 2004
 
3.3%
이 1706
 
2.8%
화 1676
 
2.7%
백 1486
 
2.4%
동 1355
 
2.2%
신 1232
 
2.0%
Other values (123) 33792
54.8%
ASCII
ValueCountFrequency (%)
4853
81.2%
) 211
 
3.5%
( 211
 
3.5%
C 190
 
3.2%
N 190
 
3.2%
4 112
 
1.9%
3 112
 
1.9%
1 99
 
1.7%

품목 번호
Real number (ℝ)

Distinct80
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201.0683
Minimum13
Maximum321
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:35:32.319821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile22
Q158
median260
Q3306
95-th percentile320
Maximum321
Range308
Interquartile range (IQR)248

Descriptive statistics

Standard deviation116.05515
Coefficient of variation (CV)0.57719265
Kurtosis-1.3978169
Mean201.0683
Median Absolute Deviation (MAD)52
Skewness-0.54135582
Sum2010683
Variance13468.797
MonotonicityNot monotonic
2024-05-11T15:35:32.529587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
171 572
 
5.7%
320 565
 
5.7%
311 393
 
3.9%
58 378
 
3.8%
312 332
 
3.3%
309 329
 
3.3%
307 322
 
3.2%
23 314
 
3.1%
306 311
 
3.1%
24 299
 
3.0%
Other values (70) 6185
61.9%
ValueCountFrequency (%)
13 158
1.6%
17 13
 
0.1%
18 270
2.7%
22 176
1.8%
23 314
3.1%
24 299
3.0%
25 296
3.0%
26 201
2.0%
27 153
1.5%
28 200
2.0%
ValueCountFrequency (%)
321 3
 
< 0.1%
320 565
5.7%
318 13
 
0.1%
316 1
 
< 0.1%
315 11
 
0.1%
314 10
 
0.1%
313 16
 
0.2%
312 332
3.3%
311 393
3.9%
310 215
 
2.1%

품목 이름
Text

Distinct75
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:35:32.902529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length6.6014
Min length1

Characters and Unicode

Total characters66014
Distinct characters87
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row돼지고기
2nd row닭고기(육계)
3rd row양파(1.5kg망)
4th row오징어(생물,국산)
5th row달걀(10개)
ValueCountFrequency (%)
달걀(10개 572
 
5.4%
달걀(30개 565
 
5.3%
오이(다다기 393
 
3.7%
배(신고 390
 
3.7%
쇠고기(한우,불고기 378
 
3.6%
돼지고기(생삼겹살 368
 
3.5%
사과(부사 337
 
3.2%
애호박 332
 
3.1%
양파(1.5kg망 329
 
3.1%
배추(2.5~3kg 322
 
3.0%
Other values (65) 6631
62.5%
2024-05-11T15:35:33.446533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 6460
 
9.8%
) 6460
 
9.8%
기 3235
 
4.9%
고 3205
 
4.9%
0 2823
 
4.3%
, 2548
 
3.9%
g 1714
 
2.6%
1 1401
 
2.1%
산 1249
 
1.9%
3 1198
 
1.8%
Other values (77) 35721
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39492
59.8%
Decimal Number 6757
 
10.2%
Open Punctuation 6460
 
9.8%
Close Punctuation 6460
 
9.8%
Other Punctuation 3199
 
4.8%
Lowercase Letter 2707
 
4.1%
Space Separator 617
 
0.9%
Math Symbol 322
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 3235
 
8.2%
고 3205
 
8.1%
산 1249
 
3.2%
배 1176
 
3.0%
어 1168
 
3.0%
오 1163
 
2.9%
달 1153
 
2.9%
걀 1153
 
2.9%
개 1140
 
2.9%
추 1112
 
2.8%
Other values (60) 23738
60.1%
Decimal Number
ValueCountFrequency (%)
0 2823
41.8%
1 1401
20.7%
3 1198
17.7%
5 665
 
9.8%
2 348
 
5.2%
6 311
 
4.6%
4 11
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
g 1714
63.3%
k 891
32.9%
m 51
 
1.9%
c 51
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 2548
79.6%
. 651
 
20.4%
Open Punctuation
ValueCountFrequency (%)
( 6460
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6460
100.0%
Space Separator
ValueCountFrequency (%)
617
100.0%
Math Symbol
ValueCountFrequency (%)
~ 322
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39492
59.8%
Common 23815
36.1%
Latin 2707
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 3235
 
8.2%
고 3205
 
8.1%
산 1249
 
3.2%
배 1176
 
3.0%
어 1168
 
3.0%
오 1163
 
2.9%
달 1153
 
2.9%
걀 1153
 
2.9%
개 1140
 
2.9%
추 1112
 
2.8%
Other values (60) 23738
60.1%
Common
ValueCountFrequency (%)
( 6460
27.1%
) 6460
27.1%
0 2823
11.9%
, 2548
 
10.7%
1 1401
 
5.9%
3 1198
 
5.0%
5 665
 
2.8%
. 651
 
2.7%
617
 
2.6%
2 348
 
1.5%
Other values (3) 644
 
2.7%
Latin
ValueCountFrequency (%)
g 1714
63.3%
k 891
32.9%
m 51
 
1.9%
c 51
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39492
59.8%
ASCII 26522
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 6460
24.4%
) 6460
24.4%
0 2823
10.6%
, 2548
 
9.6%
g 1714
 
6.5%
1 1401
 
5.3%
3 1198
 
4.5%
k 891
 
3.4%
5 665
 
2.5%
. 651
 
2.5%
Other values (7) 1711
 
6.5%
Hangul
ValueCountFrequency (%)
기 3235
 
8.2%
고 3205
 
8.1%
산 1249
 
3.2%
배 1176
 
3.0%
어 1168
 
3.0%
오 1163
 
2.9%
달 1153
 
2.9%
걀 1153
 
2.9%
개 1140
 
2.9%
추 1112
 
2.8%
Other values (60) 23738
60.1%

실판매규격
Text

Distinct1251
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:35:33.888569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length21
Mean length5.7122
Min length1

Characters and Unicode

Total characters57122
Distinct characters102
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique726 ?
Unique (%)7.3%

Sample

1st row2580
2nd row1마리(1130g)
3rd row1.5kg
4th row1마리410g
5th row10개
ValueCountFrequency (%)
1개 1586
 
14.6%
1마리 1024
 
9.4%
600g 809
 
7.4%
100g 558
 
5.1%
30개 279
 
2.6%
10개 270
 
2.5%
1포기 183
 
1.7%
1망 170
 
1.6%
1마리(1kg 137
 
1.3%
1kg 130
 
1.2%
Other values (1090) 5728
52.7%
2024-05-11T15:35:34.550103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9870
17.3%
0 8393
14.7%
g 5448
 
9.5%
개 3726
 
6.5%
( 3498
 
6.1%
) 3492
 
6.1%
리 2755
 
4.8%
마 2741
 
4.8%
3 1731
 
3.0%
5 1661
 
2.9%
Other values (92) 13807
24.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26650
46.7%
Other Letter 12560
22.0%
Lowercase Letter 8396
 
14.7%
Open Punctuation 3519
 
6.2%
Close Punctuation 3513
 
6.1%
Space Separator 1174
 
2.1%
Other Punctuation 1138
 
2.0%
Math Symbol 133
 
0.2%
Dash Punctuation 27
 
< 0.1%
Uppercase Letter 9
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 3726
29.7%
리 2755
21.9%
마 2741
21.8%
망 545
 
4.3%
기 451
 
3.6%
포 436
 
3.5%
봉 330
 
2.6%
팩 225
 
1.8%
란 170
 
1.4%
원 143
 
1.1%
Other values (53) 1038
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 9870
37.0%
0 8393
31.5%
3 1731
 
6.5%
5 1661
 
6.2%
2 1645
 
6.2%
6 1613
 
6.1%
8 699
 
2.6%
4 553
 
2.1%
9 243
 
0.9%
7 242
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
g 5448
64.9%
k 1392
 
16.6%
m 773
 
9.2%
c 771
 
9.2%
r 4
 
< 0.1%
f 2
 
< 0.1%
o 2
 
< 0.1%
v 2
 
< 0.1%
n 1
 
< 0.1%
p 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 793
69.7%
, 343
30.1%
/ 1
 
0.1%
; 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
K 4
44.4%
G 3
33.3%
M 1
 
11.1%
C 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 3498
99.4%
[ 21
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 3492
99.4%
] 21
 
0.6%
Math Symbol
ValueCountFrequency (%)
+ 100
75.2%
~ 33
 
24.8%
Space Separator
ValueCountFrequency (%)
1174
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36157
63.3%
Hangul 12560
 
22.0%
Latin 8405
 
14.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 3726
29.7%
리 2755
21.9%
마 2741
21.8%
망 545
 
4.3%
기 451
 
3.6%
포 436
 
3.5%
봉 330
 
2.6%
팩 225
 
1.8%
란 170
 
1.4%
원 143
 
1.1%
Other values (53) 1038
 
8.3%
Common
ValueCountFrequency (%)
1 9870
27.3%
0 8393
23.2%
( 3498
 
9.7%
) 3492
 
9.7%
3 1731
 
4.8%
5 1661
 
4.6%
2 1645
 
4.5%
6 1613
 
4.5%
1174
 
3.2%
. 793
 
2.2%
Other values (15) 2287
 
6.3%
Latin
ValueCountFrequency (%)
g 5448
64.8%
k 1392
 
16.6%
m 773
 
9.2%
c 771
 
9.2%
r 4
 
< 0.1%
K 4
 
< 0.1%
G 3
 
< 0.1%
f 2
 
< 0.1%
o 2
 
< 0.1%
v 2
 
< 0.1%
Other values (4) 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44562
78.0%
Hangul 12556
 
22.0%
Compat Jamo 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9870
22.1%
0 8393
18.8%
g 5448
12.2%
( 3498
 
7.8%
) 3492
 
7.8%
3 1731
 
3.9%
5 1661
 
3.7%
2 1645
 
3.7%
6 1613
 
3.6%
k 1392
 
3.1%
Other values (29) 5819
13.1%
Hangul
ValueCountFrequency (%)
개 3726
29.7%
리 2755
21.9%
마 2741
21.8%
망 545
 
4.3%
기 451
 
3.6%
포 436
 
3.5%
봉 330
 
2.6%
팩 225
 
1.8%
란 170
 
1.4%
원 143
 
1.1%
Other values (50) 1034
 
8.2%
Compat Jamo
ValueCountFrequency (%)
ㅣ 2
50.0%
ㄹ 1
25.0%
ㅎ 1
25.0%

가격(원)
Real number (ℝ)

Distinct900
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6263.5969
Minimum0
Maximum88000
Zeros98
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:35:34.765917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile800
Q12300
median3980
Q36800
95-th percentile24000
Maximum88000
Range88000
Interquartile range (IQR)4500

Descriptive statistics

Standard deviation7523.6078
Coefficient of variation (CV)1.2011641
Kurtosis10.870439
Mean6263.5969
Median Absolute Deviation (MAD)2000
Skewness2.9972176
Sum62635969
Variance56604675
MonotonicityNot monotonic
2024-05-11T15:35:34.994439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4000 502
 
5.0%
3000 443
 
4.4%
5000 376
 
3.8%
2500 376
 
3.8%
2000 283
 
2.8%
3500 278
 
2.8%
1000 253
 
2.5%
1500 242
 
2.4%
6000 177
 
1.8%
4980 149
 
1.5%
Other values (890) 6921
69.2%
ValueCountFrequency (%)
0 98
1.0%
100 2
 
< 0.1%
182 3
 
< 0.1%
200 1
 
< 0.1%
250 1
 
< 0.1%
300 1
 
< 0.1%
330 6
 
0.1%
333 3
 
< 0.1%
350 1
 
< 0.1%
370 1
 
< 0.1%
ValueCountFrequency (%)
88000 1
 
< 0.1%
59400 1
 
< 0.1%
57000 3
< 0.1%
55800 3
< 0.1%
55700 1
 
< 0.1%
54000 2
< 0.1%
53340 1
 
< 0.1%
52200 1
 
< 0.1%
51960 2
< 0.1%
51000 4
< 0.1%

년도-월
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-04
1418 
2021-07
1412 
2021-08
1150 
2021-03
1147 
2021-06
1138 
Other values (4)
3735 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-03
2nd row2021-02
3rd row2021-03
4th row2021-02
5th row2021-07

Common Values

ValueCountFrequency (%)
2021-04 1418
14.2%
2021-07 1412
14.1%
2021-08 1150
11.5%
2021-03 1147
11.5%
2021-06 1138
11.4%
2021-05 1110
11.1%
2021-02 1096
11.0%
2021-01 1094
10.9%
2021-09 435
 
4.3%

Length

2024-05-11T15:35:35.171628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:35.363481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-04 1418
14.2%
2021-07 1412
14.1%
2021-08 1150
11.5%
2021-03 1147
11.5%
2021-06 1138
11.4%
2021-05 1110
11.1%
2021-02 1096
11.0%
2021-01 1094
10.9%
2021-09 435
 
4.3%

비고
Text

Distinct1976
Distinct (%)19.9%
Missing76
Missing (%)0.8%
Memory size156.2 KiB
2024-05-11T15:35:35.754469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length5.8672914
Min length2

Characters and Unicode

Total characters58227
Distinct characters380
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1198 ?
Unique (%)12.1%

Sample

1st row국내산
2nd row국내산,하림
3rd row국내산
4th row국내산
5th row국내산1등급
ValueCountFrequency (%)
국내산 3666
29.2%
국산 379
 
3.0%
국내 369
 
2.9%
생물 269
 
2.1%
러시아 161
 
1.3%
특란 148
 
1.2%
냉동 142
 
1.1%
국내산,생물 140
 
1.1%
신고 112
 
0.9%
부사 111
 
0.9%
Other values (1705) 7054
56.2%
2024-05-11T15:35:36.745231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 7753
 
13.3%
산 7564
 
13.0%
내 7022
 
12.1%
3269
 
5.6%
, 2142
 
3.7%
생 1030
 
1.8%
0 968
 
1.7%
란 927
 
1.6%
입 775
 
1.3%
물 718
 
1.2%
Other values (370) 26059
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46759
80.3%
Space Separator 3269
 
5.6%
Other Punctuation 3200
 
5.5%
Decimal Number 3168
 
5.4%
Open Punctuation 605
 
1.0%
Close Punctuation 603
 
1.0%
Lowercase Letter 367
 
0.6%
Math Symbol 163
 
0.3%
Dash Punctuation 53
 
0.1%
Uppercase Letter 38
 
0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 7753
16.6%
산 7564
 
16.2%
내 7022
 
15.0%
생 1030
 
2.2%
란 927
 
2.0%
입 775
 
1.7%
물 718
 
1.5%
동 680
 
1.5%
수 571
 
1.2%
부 554
 
1.2%
Other values (335) 19165
41.0%
Decimal Number
ValueCountFrequency (%)
0 968
30.6%
1 658
20.8%
5 282
 
8.9%
2 272
 
8.6%
9 225
 
7.1%
3 219
 
6.9%
8 169
 
5.3%
4 169
 
5.3%
6 133
 
4.2%
7 73
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
g 189
51.5%
c 59
 
16.1%
k 52
 
14.2%
m 51
 
13.9%
l 8
 
2.2%
p 8
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
G 12
31.6%
P 11
28.9%
A 11
28.9%
L 2
 
5.3%
K 1
 
2.6%
F 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 2142
66.9%
. 603
 
18.8%
/ 448
 
14.0%
% 5
 
0.2%
？ 2
 
0.1%
Math Symbol
ValueCountFrequency (%)
+ 124
76.1%
~ 39
 
23.9%
Space Separator
ValueCountFrequency (%)
3269
100.0%
Open Punctuation
ValueCountFrequency (%)
( 605
100.0%
Close Punctuation
ValueCountFrequency (%)
) 603
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46758
80.3%
Common 11063
 
19.0%
Latin 405
 
0.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 7753
16.6%
산 7564
 
16.2%
내 7022
 
15.0%
생 1030
 
2.2%
란 927
 
2.0%
입 775
 
1.7%
물 718
 
1.5%
동 680
 
1.5%
수 571
 
1.2%
부 554
 
1.2%
Other values (334) 19164
41.0%
Common
ValueCountFrequency (%)
3269
29.5%
, 2142
19.4%
0 968
 
8.7%
1 658
 
5.9%
( 605
 
5.5%
. 603
 
5.5%
) 603
 
5.5%
/ 448
 
4.0%
5 282
 
2.5%
2 272
 
2.5%
Other values (13) 1213
 
11.0%
Latin
ValueCountFrequency (%)
g 189
46.7%
c 59
 
14.6%
k 52
 
12.8%
m 51
 
12.6%
G 12
 
3.0%
P 11
 
2.7%
A 11
 
2.7%
l 8
 
2.0%
p 8
 
2.0%
L 2
 
0.5%
Other values (2) 2
 
0.5%
Han
ValueCountFrequency (%)
大 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46755
80.3%
ASCII 11466
 
19.7%
Compat Jamo 3
 
< 0.1%
None 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 7753
16.6%
산 7564
 
16.2%
내 7022
 
15.0%
생 1030
 
2.2%
란 927
 
2.0%
입 775
 
1.7%
물 718
 
1.5%
동 680
 
1.5%
수 571
 
1.2%
부 554
 
1.2%
Other values (331) 19161
41.0%
ASCII
ValueCountFrequency (%)
3269
28.5%
, 2142
18.7%
0 968
 
8.4%
1 658
 
5.7%
( 605
 
5.3%
. 603
 
5.3%
) 603
 
5.3%
/ 448
 
3.9%
5 282
 
2.5%
2 272
 
2.4%
Other values (24) 1616
14.1%
None
ValueCountFrequency (%)
？ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
33.3%
ㄱ 1
33.3%
ㅂ 1
33.3%
CJK
ValueCountFrequency (%)
大 1
100.0%

시장유형 구분(시장/마트) 코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
5084 
1
4916 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 5084
50.8%
1 4916
49.2%

Length

2024-05-11T15:35:36.914832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:37.026041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5084
50.8%
1 4916
49.2%

시장유형 구분(시장/마트) 이름
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대형마트
5084 
전통시장
4916 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전통시장
2nd row전통시장
3rd row전통시장
4th row전통시장
5th row대형마트

Common Values

ValueCountFrequency (%)
대형마트 5084
50.8%
전통시장 4916
49.2%

Length

2024-05-11T15:35:37.169841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:37.324540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대형마트 5084
50.8%
전통시장 4916
49.2%

자치구 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean416262.5
Minimum110000
Maximum740000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:35:37.447695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110000
5-th percentile140000
Q1260000
median410000
Q3560000
95-th percentile710000
Maximum740000
Range630000
Interquartile range (IQR)300000

Descriptive statistics

Standard deviation185831.74
Coefficient of variation (CV)0.44642922
Kurtosis-1.2116664
Mean416262.5
Median Absolute Deviation (MAD)150000
Skewness0.10086455
Sum4.162625 × 109
Variance3.4533437 × 1010
MonotonicityNot monotonic
2024-05-11T15:35:37.606804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
140000 621
 
6.2%
620000 540
 
5.4%
470000 509
 
5.1%
560000 442
 
4.4%
230000 429
 
4.3%
710000 422
 
4.2%
350000 421
 
4.2%
215000 419
 
4.2%
680000 412
 
4.1%
440000 409
 
4.1%
Other values (15) 5376
53.8%
ValueCountFrequency (%)
110000 204
 
2.0%
140000 621
6.2%
170000 386
3.9%
200000 407
4.1%
215000 419
4.2%
230000 429
4.3%
260000 366
3.7%
290000 398
4.0%
305000 379
3.8%
320000 368
3.7%
ValueCountFrequency (%)
740000 386
3.9%
710000 422
4.2%
680000 412
4.1%
650000 375
3.8%
620000 540
5.4%
590000 204
 
2.0%
560000 442
4.4%
545000 331
3.3%
530000 391
3.9%
500000 391
3.9%

자치구 이름
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
중구
 
621
관악구
 
540
양천구
 
509
영등포구
 
442
동대문구
 
429
Other values (20)
7459 

Length

Max length4
Median length3
Mean length3.0644
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강남구
2nd row종로구
3rd row강북구
4th row강북구
5th row성동구

Common Values

ValueCountFrequency (%)
중구 621
 
6.2%
관악구 540
 
5.4%
양천구 509
 
5.1%
영등포구 442
 
4.4%
동대문구 429
 
4.3%
송파구 422
 
4.2%
노원구 421
 
4.2%
광진구 419
 
4.2%
강남구 412
 
4.1%
마포구 409
 
4.1%
Other values (15) 5376
53.8%

Length

2024-05-11T15:35:37.771372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
중구 621
 
6.2%
관악구 540
 
5.4%
양천구 509
 
5.1%
영등포구 442
 
4.4%
동대문구 429
 
4.3%
송파구 422
 
4.2%
노원구 421
 
4.2%
광진구 419
 
4.2%
강남구 412
 
4.1%
마포구 409
 
4.1%
Other values (15) 5376
53.8%

점검일자
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-04-29
1414 
2021-07-29
1400 
2021-06-24
1138 
2021-03-25
1125 
2021-05-27
1101 
Other values (12)
3822 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-03-25
2nd row2021-02-25
3rd row2021-03-25
4th row2021-02-25
5th row2021-07-29

Common Values

ValueCountFrequency (%)
2021-04-29 1414
14.1%
2021-07-29 1400
14.0%
2021-06-24 1138
11.4%
2021-03-25 1125
11.2%
2021-05-27 1101
11.0%
2021-01-28 1091
10.9%
2021-08-26 1084
10.8%
2021-02-25 1038
10.4%
2021-09-30 435
 
4.3%
2021-02-18 58
 
0.6%
Other values (7) 116
 
1.2%

Length

2024-05-11T15:35:37.938425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-04-29 1414
14.1%
2021-07-29 1400
14.0%
2021-06-24 1138
11.4%
2021-03-25 1125
11.2%
2021-05-27 1101
11.0%
2021-01-28 1091
10.9%
2021-08-26 1084
10.8%
2021-02-25 1038
10.4%
2021-09-30 435
 
4.3%
2021-02-18 58
 
0.6%
Other values (7) 116
 
1.2%

Interactions

2024-05-11T15:35:28.460692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:25.309006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:26.038175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:26.861132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:27.628091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:28.628795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:25.493093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:26.190724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:27.038219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:27.848852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:28.770482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:25.614402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:26.335118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:27.166641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:27.982687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:28.932932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:25.775235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:26.483315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:27.320033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:28.144233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:29.163588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:25.903742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:26.663261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:27.464182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:28.317984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:35:38.054619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호시장/마트 번호품목 번호품목 이름가격(원)년도-월시장유형 구분(시장/마트) 코드시장유형 구분(시장/마트) 이름자치구 코드자치구 이름점검일자
일련번호1.0000.0570.0450.1210.0060.9400.0000.0000.1620.1590.940
시장/마트 번호0.0571.0000.2160.5340.0620.0400.1290.1290.8240.9490.239
품목 번호0.0450.2161.0000.9960.5460.0210.0880.0880.3470.4980.061
품목 이름0.1210.5340.9961.0000.7620.0900.1840.1840.6060.7980.000
가격(원)0.0060.0620.5460.7621.0000.0140.1530.1530.1250.2300.067
년도-월0.9400.0400.0210.0900.0141.0000.0000.0000.0490.0601.000
시장유형 구분(시장/마트) 코드0.0000.1290.0880.1840.1530.0001.0001.0000.0790.2330.067
시장유형 구분(시장/마트) 이름0.0000.1290.0880.1840.1530.0001.0001.0000.0790.2330.067
자치구 코드0.1620.8240.3470.6060.1250.0490.0790.0791.0001.0000.285
자치구 이름0.1590.9490.4980.7980.2300.0600.2330.2331.0001.0000.451
점검일자0.9400.2390.0610.0000.0671.0000.0670.0670.2850.4511.000
2024-05-11T15:35:38.210256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도-월점검일자자치구 이름시장유형 구분(시장/마트) 코드시장유형 구분(시장/마트) 이름
년도-월1.0001.0000.0230.0000.000
점검일자1.0001.0000.1460.0600.060
자치구 이름0.0230.1461.0000.2010.201
시장유형 구분(시장/마트) 코드0.0000.0600.2011.0001.000
시장유형 구분(시장/마트) 이름0.0000.0600.2011.0001.000
2024-05-11T15:35:38.356305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호시장/마트 번호품목 번호가격(원)자치구 코드년도-월시장유형 구분(시장/마트) 코드시장유형 구분(시장/마트) 이름자치구 이름점검일자
일련번호1.0000.0030.009-0.031-0.0030.7980.0000.0000.0560.752
시장/마트 번호0.0031.000-0.0130.0100.5100.0130.1290.1290.7640.097
품목 번호0.009-0.0131.000-0.061-0.0560.0090.0670.0670.1990.024
가격(원)-0.0310.010-0.0611.0000.0420.0070.1150.1150.0930.028
자치구 코드-0.0030.510-0.0560.0421.0000.0220.0270.0270.9990.115
년도-월0.7980.0130.0090.0070.0221.0000.0000.0000.0231.000
시장유형 구분(시장/마트) 코드0.0000.1290.0670.1150.0270.0001.0001.0000.2010.060
시장유형 구분(시장/마트) 이름0.0000.1290.0670.1150.0270.0001.0001.0000.2010.060
자치구 이름0.0560.7640.1990.0930.9990.0230.2010.2011.0000.146
점검일자0.7520.0970.0240.0280.1151.0000.0600.0600.1461.000

Missing values

2024-05-11T15:35:29.459251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:35:29.972768image/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

일련번호시장/마트 번호시장/마트 이름품목 번호품목 이름실판매규격가격(원)년도-월비고시장유형 구분(시장/마트) 코드시장유형 구분(시장/마트) 이름자치구 코드자치구 이름점검일자
150431646077215청담삼익시장285돼지고기2580154802021-03국내산1전통시장680000강남구2021-03-25
8904163982755광장시장283닭고기(육계)1마리(1130g)70002021-02국내산,하림1전통시장110000종로구2021-02-25
198951651048221숭인시장309양파(1.5kg망)1.5kg35002021-03국내산1전통시장305000강북구2021-03-25
77801638635221숭인시장254오징어(생물,국산)1마리410g49502021-02국내산1전통시장305000강북구2021-02-25
48280168059174이마트 왕십리점171달걀(10개)10개46802021-07국내산1등급2대형마트200000성동구2021-07-29
524641684795154홈플러스 강동점52돼지고기(삼겹살)600g148802021-08국내산100g 2,4802대형마트740000강동구2021-08-26
2565716567081통인시장256오징어(냉동,국산)1마리50002021-04국내산,동해안1전통시장110000종로구2021-04-29
53286168570231인왕시장26배추1포기(2.2kg)50002021-08강원도1전통시장410000서대문구2021-08-26
520163179268롯데백화점 미아점264명태(냉동,수입산)1마리490g32502021-01러시아2대형마트305000강북구2021-01-28
471361679430121마포농수산물시장306배(신고, 600g)1개(350g)60002021-07국내산,신고배,세일1전통시장440000마포구2021-07-29
일련번호시장/마트 번호시장/마트 이름품목 번호품목 이름실판매규격가격(원)년도-월비고시장유형 구분(시장/마트) 코드시장유형 구분(시장/마트) 이름자치구 코드자치구 이름점검일자
228791653913219대조시장27배1개(500g)40002021-04<NA>1전통시장380000은평구2021-04-29
81641639019214이마트 목동점24양파한망59802021-02국내산2대형마트470000양천구2021-02-25
32224166328844이마트 역삼점320달걀(30개)30개69002021-05국내산2대형마트680000강남구2021-05-27
496811682009224농협하나로마트 신촌점306배(신고, 600g)1개(350g)38802021-07국내산,세일2대형마트440000마포구2021-07-29
29116166013027이마트 창동점307배추(2.5~3kg)2.7kg32002021-05국내산2대형마트320000도봉구2021-05-27
28040165917310용문시장23상추1망 130g10002021-04국내산1전통시장170000용산구2021-04-29
28079165921262후암시장283닭고기(육계)1마리 1,1k55002021-04동우1전통시장170000용산구2021-04-29
103281641383134신원시장(신림1동)305사과(부사, 300g)1개25002021-02국산 청송부사1전통시장620000관악구2021-02-25
38062166907573뚝도시장320달걀(30개)30개85002021-06국내산1전통시장200000성동구2021-06-24
21250165225062후암시장58쇠고기(한우,불고기)100g (1+)50002021-04음성축산물1전통시장170000용산구2021-04-29