Overview

Dataset statistics

Number of variables31
Number of observations10000
Missing cells2692
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 MiB
Average record size in memory274.0 B

Variable types

Numeric15
Categorical9
Text7

Dataset

Description농수산식품유통공사, 농협중앙회, 수협중앙회, 축산물품질평가원에서 농수축산물 유통정보 조사요령에 의거 유통단계(산지, 경락/도매, 소매)별 지역별로 대표품목을 조사하여 일별 제공하는 정보로 도매시장경락가격, 산지공판장 가격 등과 융복합할 수 있도록 조사가격코드를 농수축산물표준코드로 변환하여 제공
Author농림수산식품교육문화정보원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220208000000001720

Alerts

BFRT_PRIC has 2692 (26.9%) missing valuesMissing
EXAMIN_SPCIES_CODE has 4398 (44.0%) zerosZeros
IMP_TRADE has 9447 (94.5%) zerosZeros
TRADE_AMT has 9447 (94.5%) zerosZeros

Reproduction

Analysis started2023-12-11 03:50:43.403149
Analysis finished2023-12-11 03:50:44.243098
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

EXAMIN_DE
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20220205
Minimum20220201
Maximum20220207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:44.281480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20220201
5-th percentile20220204
Q120220204
median20220205
Q320220207
95-th percentile20220207
Maximum20220207
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.2588732
Coefficient of variation (CV)6.2258179 × 10-8
Kurtosis-0.011089239
Mean20220205
Median Absolute Deviation (MAD)1
Skewness-0.43566784
Sum2.0220205 × 1011
Variance1.5847617
MonotonicityNot monotonic
2023-12-11T12:50:44.373842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20220204 2555
25.6%
20220207 2518
25.2%
20220205 2342
23.4%
20220206 2331
23.3%
20220201 95
 
0.9%
20220203 86
 
0.9%
20220202 73
 
0.7%
ValueCountFrequency (%)
20220201 95
 
0.9%
20220202 73
 
0.7%
20220203 86
 
0.9%
20220204 2555
25.6%
20220205 2342
23.4%
20220206 2331
23.3%
20220207 2518
25.2%
ValueCountFrequency (%)
20220207 2518
25.2%
20220206 2331
23.3%
20220205 2342
23.4%
20220204 2555
25.6%
20220203 86
 
0.9%
20220202 73
 
0.7%
20220201 95
 
0.9%

EXAMIN_SE_NM
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
소비자가격
7866 
도매가격
1581 
축산물산지가격(농협)
 
553

Length

Max length11
Median length5
Mean length5.1737
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row소비자가격
2nd row소비자가격
3rd row도매가격
4th row도매가격
5th row소비자가격

Common Values

ValueCountFrequency (%)
소비자가격 7866
78.7%
도매가격 1581
 
15.8%
축산물산지가격(농협) 553
 
5.5%

Length

2023-12-11T12:50:44.489344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:50:44.615235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소비자가격 7866
78.7%
도매가격 1581
 
15.8%
축산물산지가격(농협 553
 
5.5%

EXAMIN_SE_CODE
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
7
7866 
6
1581 
3
 
553

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7
2nd row7
3rd row6
4th row6
5th row7

Common Values

ValueCountFrequency (%)
7 7866
78.7%
6 1581
 
15.8%
3 553
 
5.5%

Length

2023-12-11T12:50:44.733796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:50:44.822401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7 7866
78.7%
6 1581
 
15.8%
3 553
 
5.5%

EXAMIN_AREA_NAME
Text

Distinct61
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:50:45.011144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.779
Min length2

Characters and Unicode

Total characters27790
Distinct characters62
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row충북청주
2nd row서울서부
3rd row서울서부
4th row서울서부
5th row충북청주
ValueCountFrequency (%)
대구 1029
 
10.3%
대전 1027
 
10.3%
부산 994
 
9.9%
서울서부 926
 
9.3%
서울 847
 
8.5%
광주 688
 
6.9%
인천 410
 
4.1%
제주 367
 
3.7%
경남창원 357
 
3.6%
경기수원 263
 
2.6%
Other values (51) 3092
30.9%
2023-12-11T12:50:45.344013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 2712
 
9.8%
부 2116
 
7.6%
대 2056
 
7.4%
울 1976
 
7.1%
전 1945
 
7.0%
주 1890
 
6.8%
경 1770
 
6.4%
원 1240
 
4.5%
산 1216
 
4.4%
북 1155
 
4.2%
Other values (52) 9714
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27790
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 2712
 
9.8%
부 2116
 
7.6%
대 2056
 
7.4%
울 1976
 
7.1%
전 1945
 
7.0%
주 1890
 
6.8%
경 1770
 
6.4%
원 1240
 
4.5%
산 1216
 
4.4%
북 1155
 
4.2%
Other values (52) 9714
35.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27790
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 2712
 
9.8%
부 2116
 
7.6%
대 2056
 
7.4%
울 1976
 
7.1%
전 1945
 
7.0%
주 1890
 
6.8%
경 1770
 
6.4%
원 1240
 
4.5%
산 1216
 
4.4%
북 1155
 
4.2%
Other values (52) 9714
35.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27790
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 2712
 
9.8%
부 2116
 
7.6%
대 2056
 
7.4%
울 1976
 
7.1%
전 1945
 
7.0%
주 1890
 
6.8%
경 1770
 
6.4%
원 1240
 
4.5%
산 1216
 
4.4%
북 1155
 
4.2%
Other values (52) 9714
35.0%

EXAMIN_AREA_CODE
Real number (ℝ)

Distinct72
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2554.9237
Minimum1102
Maximum3904
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:45.516289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1102
5-th percentile1102
Q12104
median2501
Q33300
95-th percentile3804
Maximum3904
Range2802
Interquartile range (IQR)1196

Descriptive statistics

Standard deviation884.80221
Coefficient of variation (CV)0.34631258
Kurtosis-0.95488015
Mean2554.9237
Median Absolute Deviation (MAD)699
Skewness-0.22252502
Sum25549237
Variance782874.95
MonotonicityNot monotonic
2023-12-11T12:50:45.673193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1102 926
 
9.3%
1104 847
 
8.5%
2501 679
 
6.8%
2200 670
 
6.7%
2100 650
 
6.5%
2404 364
 
3.6%
2204 359
 
3.6%
2504 348
 
3.5%
2104 344
 
3.4%
2401 324
 
3.2%
Other values (62) 4489
44.9%
ValueCountFrequency (%)
1102 926
9.3%
1104 847
8.5%
2100 650
6.5%
2104 344
 
3.4%
2200 670
6.7%
2204 359
 
3.6%
2300 266
 
2.7%
2304 144
 
1.4%
2401 324
 
3.2%
2404 364
 
3.6%
ValueCountFrequency (%)
3904 178
1.8%
3900 189
1.9%
3849 22
 
0.2%
3848 6
 
0.1%
3845 1
 
< 0.1%
3834 12
 
0.1%
3833 14
 
0.1%
3813 16
 
0.2%
3812 14
 
0.1%
3804 173
1.7%

EXAMIN_MRKT_NM
Text

Distinct74
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:50:45.897445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length4.7331
Min length2

Characters and Unicode

Total characters47331
Distinct characters97
Distinct categories4 ?
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 row육거리시장
2nd row복조리시장
3rd row서울가락동도매시장
4th row서울가락동도매시장
5th row육거리시장
ValueCountFrequency (%)
c-유통 1437
 
14.4%
a-유통 1293
 
12.9%
e-유통 785
 
7.8%
b-유통 498
 
5.0%
부전시장 360
 
3.6%
서울가락동도매시장 344
 
3.4%
칠성시장 332
 
3.3%
양동시장 324
 
3.2%
역전시장 315
 
3.1%
대전오정농수산물도매 310
 
3.1%
Other values (65) 4003
40.0%
2023-12-11T12:50:46.241419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 4602
 
9.7%
시 4570
 
9.7%
유 4314
 
9.1%
통 4314
 
9.1%
- 4314
 
9.1%
동 1488
 
3.1%
도 1478
 
3.1%
C 1437
 
3.0%
A 1293
 
2.7%
매 1270
 
2.7%
Other values (87) 18251
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38702
81.8%
Dash Punctuation 4314
 
9.1%
Uppercase Letter 4314
 
9.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 4602
 
11.9%
시 4570
 
11.8%
유 4314
 
11.1%
통 4314
 
11.1%
동 1488
 
3.8%
도 1478
 
3.8%
매 1270
 
3.3%
전 1182
 
3.1%
부 1112
 
2.9%
산 909
 
2.3%
Other values (79) 13463
34.8%
Uppercase Letter
ValueCountFrequency (%)
C 1437
33.3%
A 1293
30.0%
E 785
18.2%
B 498
 
11.5%
D 160
 
3.7%
F 141
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 4314
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38702
81.8%
Common 4315
 
9.1%
Latin 4314
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 4602
 
11.9%
시 4570
 
11.8%
유 4314
 
11.1%
통 4314
 
11.1%
동 1488
 
3.8%
도 1478
 
3.8%
매 1270
 
3.3%
전 1182
 
3.1%
부 1112
 
2.9%
산 909
 
2.3%
Other values (79) 13463
34.8%
Latin
ValueCountFrequency (%)
C 1437
33.3%
A 1293
30.0%
E 785
18.2%
B 498
 
11.5%
D 160
 
3.7%
F 141
 
3.3%
Common
ValueCountFrequency (%)
- 4314
> 99.9%
1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38702
81.8%
ASCII 8629
 
18.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 4602
 
11.9%
시 4570
 
11.8%
유 4314
 
11.1%
통 4314
 
11.1%
동 1488
 
3.8%
도 1478
 
3.8%
매 1270
 
3.3%
전 1182
 
3.1%
부 1112
 
2.9%
산 909
 
2.3%
Other values (79) 13463
34.8%
ASCII
ValueCountFrequency (%)
- 4314
50.0%
C 1437
 
16.7%
A 1293
 
15.0%
E 785
 
9.1%
B 498
 
5.8%
D 160
 
1.9%
F 141
 
1.6%
1
 
< 0.1%

EXAMIN_MRKT_CODE
Real number (ℝ)

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3799
Minimum0
Maximum53
Zeros11
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:46.370845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q313
95-th percentile36
Maximum53
Range53
Interquartile range (IQR)12

Descriptive statistics

Standard deviation11.007547
Coefficient of variation (CV)1.3135654
Kurtosis2.3172663
Mean8.3799
Median Absolute Deviation (MAD)1
Skewness1.6676858
Sum83799
Variance121.16609
MonotonicityNot monotonic
2023-12-11T12:50:46.490011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 4617
46.2%
2 970
 
9.7%
21 617
 
6.2%
12 611
 
6.1%
13 559
 
5.6%
3 532
 
5.3%
22 360
 
3.6%
11 344
 
3.4%
24 332
 
3.3%
42 269
 
2.7%
Other values (11) 789
 
7.9%
ValueCountFrequency (%)
0 11
 
0.1%
1 4617
46.2%
2 970
 
9.7%
3 532
 
5.3%
4 16
 
0.2%
6 182
 
1.8%
8 141
 
1.4%
11 344
 
3.4%
12 611
 
6.1%
13 559
 
5.6%
ValueCountFrequency (%)
53 53
 
0.5%
42 269
2.7%
36 266
2.7%
32 1
 
< 0.1%
31 20
 
0.2%
24 332
3.3%
23 45
 
0.4%
22 360
3.6%
21 617
6.2%
16 4
 
< 0.1%

STD_MRKT_NM
Text

Distinct74
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:50:46.749126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length4
Mean length5.0382
Min length4

Characters and Unicode

Total characters50382
Distinct characters103
Distinct categories3 ?
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 row청주육거리종합시장
2nd row복조리시장
3rd row서울가락도매
4th row서울가락도매
5th row청주육거리종합시장
ValueCountFrequency (%)
c-유통 1437
 
14.4%
a-유통 1293
 
12.9%
e-유통 785
 
7.8%
b-유통 498
 
5.0%
부산부전시장 360
 
3.6%
서울가락도매 344
 
3.4%
대구칠성시장 332
 
3.3%
광주양동시장 324
 
3.2%
대전역전시장 315
 
3.1%
대전농수산도매 310
 
3.1%
Other values (64) 4002
40.0%
2023-12-11T12:50:47.162849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 4314
 
8.6%
통 4314
 
8.6%
- 4314
 
8.6%
장 3814
 
7.6%
시 3750
 
7.4%
대 1615
 
3.2%
전 1540
 
3.1%
부 1493
 
3.0%
도 1477
 
2.9%
C 1437
 
2.9%
Other values (93) 22314
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41754
82.9%
Dash Punctuation 4314
 
8.6%
Uppercase Letter 4314
 
8.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 4314
 
10.3%
통 4314
 
10.3%
장 3814
 
9.1%
시 3750
 
9.0%
대 1615
 
3.9%
전 1540
 
3.7%
부 1493
 
3.6%
도 1477
 
3.5%
산 1320
 
3.2%
매 1269
 
3.0%
Other values (86) 16848
40.4%
Uppercase Letter
ValueCountFrequency (%)
C 1437
33.3%
A 1293
30.0%
E 785
18.2%
B 498
 
11.5%
D 160
 
3.7%
F 141
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 4314
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41754
82.9%
Common 4314
 
8.6%
Latin 4314
 
8.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 4314
 
10.3%
통 4314
 
10.3%
장 3814
 
9.1%
시 3750
 
9.0%
대 1615
 
3.9%
전 1540
 
3.7%
부 1493
 
3.6%
도 1477
 
3.5%
산 1320
 
3.2%
매 1269
 
3.0%
Other values (86) 16848
40.4%
Latin
ValueCountFrequency (%)
C 1437
33.3%
A 1293
30.0%
E 785
18.2%
B 498
 
11.5%
D 160
 
3.7%
F 141
 
3.3%
Common
ValueCountFrequency (%)
- 4314
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41754
82.9%
ASCII 8628
 
17.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 4314
 
10.3%
통 4314
 
10.3%
장 3814
 
9.1%
시 3750
 
9.0%
대 1615
 
3.9%
전 1540
 
3.7%
부 1493
 
3.6%
도 1477
 
3.5%
산 1320
 
3.2%
매 1269
 
3.0%
Other values (86) 16848
40.4%
ASCII
ValueCountFrequency (%)
- 4314
50.0%
C 1437
 
16.7%
A 1293
 
15.0%
E 785
 
9.1%
B 498
 
5.8%
D 160
 
1.9%
F 141
 
1.6%

STD_MRKT_CODE
Real number (ℝ)

Distinct93
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean255584.87
Minimum110001
Maximum391182
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:47.348674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110001
5-th percentile110081
Q1210097
median250084
Q3330401
95-th percentile381402
Maximum391182
Range281181
Interquartile range (IQR)120304

Descriptive statistics

Standard deviation88646.307
Coefficient of variation (CV)0.34683707
Kurtosis-0.95685959
Mean255584.87
Median Absolute Deviation (MAD)70100
Skewness-0.21991683
Sum2.5558487 × 109
Variance7.8581678 × 109
MonotonicityNot monotonic
2023-12-11T12:50:47.547184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
210089 360
 
3.6%
110001 344
 
3.4%
220089 332
 
3.3%
240087 324
 
3.2%
250084 315
 
3.1%
250089 310
 
3.1%
110212 296
 
3.0%
220001 293
 
2.9%
210093 269
 
2.7%
230036 266
 
2.7%
Other values (83) 6891
68.9%
ValueCountFrequency (%)
110001 344
3.4%
110005 53
 
0.5%
110081 174
1.7%
110212 296
3.0%
110213 233
2.3%
110382 166
1.7%
110403 184
1.8%
110406 182
1.8%
110408 141
1.4%
210087 20
 
0.2%
ValueCountFrequency (%)
391182 189
1.9%
390401 178
1.8%
384981 22
 
0.2%
384881 6
 
0.1%
384582 1
 
< 0.1%
383481 12
 
0.1%
383381 14
 
0.1%
381402 184
1.8%
381383 16
 
0.2%
381282 3
 
< 0.1%

EXAMIN_PRDLST_NM
Text

Distinct65
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:50:47.811257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.6418
Min length1

Characters and Unicode

Total characters26418
Distinct characters106
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row새송이버섯
2nd row양배추
3rd row양배추
4th row생강
5th row돼지고기
ValueCountFrequency (%)
한우 553
 
5.5%
풋고추 477
 
4.8%
쇠고기 405
 
4.0%
상추 327
 
3.3%
파 312
 
3.1%
오이 304
 
3.0%
돼지고기 274
 
2.7%
호박 265
 
2.6%
땅콩 231
 
2.3%
무 212
 
2.1%
Other values (55) 6640
66.4%
2023-12-11T12:50:48.244529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
고 1968
 
7.4%
추 1573
 
6.0%
기 884
 
3.3%
파 809
 
3.1%
이 737
 
2.8%
배 645
 
2.4%
우 634
 
2.4%
한 553
 
2.1%
풋 477
 
1.8%
건 467
 
1.8%
Other values (96) 17671
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25716
97.3%
Open Punctuation 351
 
1.3%
Close Punctuation 351
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 1968
 
7.7%
추 1573
 
6.1%
기 884
 
3.4%
파 809
 
3.1%
이 737
 
2.9%
배 645
 
2.5%
우 634
 
2.5%
한 553
 
2.2%
풋 477
 
1.9%
건 467
 
1.8%
Other values (94) 16969
66.0%
Open Punctuation
ValueCountFrequency (%)
( 351
100.0%
Close Punctuation
ValueCountFrequency (%)
) 351
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25716
97.3%
Common 702
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 1968
 
7.7%
추 1573
 
6.1%
기 884
 
3.4%
파 809
 
3.1%
이 737
 
2.9%
배 645
 
2.5%
우 634
 
2.5%
한 553
 
2.2%
풋 477
 
1.9%
건 467
 
1.8%
Other values (94) 16969
66.0%
Common
ValueCountFrequency (%)
( 351
50.0%
) 351
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25716
97.3%
ASCII 702
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
고 1968
 
7.7%
추 1573
 
6.1%
기 884
 
3.4%
파 809
 
3.1%
이 737
 
2.9%
배 645
 
2.5%
우 634
 
2.5%
한 553
 
2.2%
풋 477
 
1.9%
건 467
 
1.8%
Other values (94) 16969
66.0%
ASCII
ValueCountFrequency (%)
( 351
50.0%
) 351
50.0%

EXAMIN_PRDLST_CODE
Real number (ℝ)

Distinct65
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean313.5008
Minimum111
Maximum638
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:48.406866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum111
5-th percentile142
Q1224
median248
Q3419
95-th percentile535
Maximum638
Range527
Interquartile range (IQR)195

Descriptive statistics

Standard deviation132.98209
Coefficient of variation (CV)0.42418421
Kurtosis-0.53037254
Mean313.5008
Median Absolute Deviation (MAD)66
Skewness0.71026342
Sum3135008
Variance17684.236
MonotonicityNot monotonic
2023-12-11T12:50:48.568323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
511 553
 
5.5%
242 477
 
4.8%
512 405
 
4.0%
214 327
 
3.3%
246 312
 
3.1%
223 304
 
3.0%
514 274
 
2.7%
224 265
 
2.6%
314 231
 
2.3%
231 212
 
2.1%
Other values (55) 6640
66.4%
ValueCountFrequency (%)
111 168
1.7%
112 160
1.6%
141 171
1.7%
142 170
1.7%
143 67
 
0.7%
151 181
1.8%
152 168
1.7%
211 194
1.9%
212 190
1.9%
213 86
0.9%
ValueCountFrequency (%)
638 151
 
1.5%
619 75
 
0.8%
615 76
 
0.8%
613 64
 
0.6%
611 60
 
0.6%
535 81
 
0.8%
516 51
 
0.5%
515 29
 
0.3%
514 274
2.7%
512 405
4.0%

EXAMIN_SPCIES_NM
Text

Distinct59
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:50:48.804829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length2
Mean length3.1048
Min length1

Characters and Unicode

Total characters31048
Distinct characters91
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반
2nd row일반
3rd row일반
4th row수입
5th row앞다리살
ValueCountFrequency (%)
일반 2791
27.0%
수입 752
 
7.3%
국산 683
 
6.6%
월동 406
 
3.9%
6~7월 324
 
3.1%
청양고추 192
 
1.9%
냉동 189
 
1.8%
꽈리고추 188
 
1.8%
대파 186
 
1.8%
적 185
 
1.8%
Other values (50) 4438
42.9%
2023-12-11T12:50:49.190842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
일 3578
 
11.5%
반 3578
 
11.5%
수 1313
 
4.2%
( 1233
 
4.0%
산 1199
 
3.9%
) 1193
 
3.8%
국 1098
 
3.5%
입 961
 
3.1%
고 808
 
2.6%
월 740
 
2.4%
Other values (81) 15347
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26105
84.1%
Decimal Number 1325
 
4.3%
Open Punctuation 1233
 
4.0%
Close Punctuation 1233
 
4.0%
Uppercase Letter 484
 
1.6%
Math Symbol 334
 
1.1%
Space Separator 334
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 3578
 
13.7%
반 3578
 
13.7%
수 1313
 
5.0%
산 1199
 
4.6%
국 1098
 
4.2%
입 961
 
3.7%
고 808
 
3.1%
월 740
 
2.8%
지 685
 
2.6%
동 643
 
2.5%
Other values (68) 11502
44.1%
Decimal Number
ValueCountFrequency (%)
6 476
35.9%
0 371
28.0%
7 324
24.5%
5 77
 
5.8%
3 67
 
5.1%
4 10
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 1193
96.8%
） 40
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
G 242
50.0%
K 242
50.0%
Open Punctuation
ValueCountFrequency (%)
( 1233
100.0%
Math Symbol
ValueCountFrequency (%)
~ 334
100.0%
Space Separator
ValueCountFrequency (%)
334
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26105
84.1%
Common 4459
 
14.4%
Latin 484
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 3578
 
13.7%
반 3578
 
13.7%
수 1313
 
5.0%
산 1199
 
4.6%
국 1098
 
4.2%
입 961
 
3.7%
고 808
 
3.1%
월 740
 
2.8%
지 685
 
2.6%
동 643
 
2.5%
Other values (68) 11502
44.1%
Common
ValueCountFrequency (%)
( 1233
27.7%
) 1193
26.8%
6 476
 
10.7%
0 371
 
8.3%
~ 334
 
7.5%
334
 
7.5%
7 324
 
7.3%
5 77
 
1.7%
3 67
 
1.5%
） 40
 
0.9%
Latin
ValueCountFrequency (%)
G 242
50.0%
K 242
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26105
84.1%
ASCII 4903
 
15.8%
None 40
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
일 3578
 
13.7%
반 3578
 
13.7%
수 1313
 
5.0%
산 1199
 
4.6%
국 1098
 
4.2%
입 961
 
3.7%
고 808
 
3.1%
월 740
 
2.8%
지 685
 
2.6%
동 643
 
2.5%
Other values (68) 11502
44.1%
ASCII
ValueCountFrequency (%)
( 1233
25.1%
) 1193
24.3%
6 476
 
9.7%
0 371
 
7.6%
~ 334
 
6.8%
334
 
6.8%
7 324
 
6.6%
G 242
 
4.9%
K 242
 
4.9%
5 77
 
1.6%
Other values (2) 77
 
1.6%
None
ValueCountFrequency (%)
） 40
100.0%

EXAMIN_SPCIES_CODE
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0997
Minimum0
Maximum31
Zeros4398
Zeros (%)44.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:49.352483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile10
Maximum31
Range31
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.7636387
Coefficient of variation (CV)1.792465
Kurtosis15.074932
Mean2.0997
Median Absolute Deviation (MAD)1
Skewness3.3381614
Sum20997
Variance14.164976
MonotonicityNot monotonic
2023-12-11T12:50:49.473071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 4398
44.0%
1 2052
20.5%
2 1541
 
15.4%
6 419
 
4.2%
3 406
 
4.1%
5 230
 
2.3%
10 180
 
1.8%
9 158
 
1.6%
12 134
 
1.3%
7 132
 
1.3%
Other values (7) 350
 
3.5%
ValueCountFrequency (%)
0 4398
44.0%
1 2052
20.5%
2 1541
 
15.4%
3 406
 
4.1%
4 59
 
0.6%
5 230
 
2.3%
6 419
 
4.2%
7 132
 
1.3%
8 20
 
0.2%
9 158
 
1.6%
ValueCountFrequency (%)
31 30
 
0.3%
22 26
 
0.3%
21 34
 
0.3%
15 81
0.8%
14 100
1.0%
12 134
1.3%
10 180
1.8%
9 158
1.6%
8 20
 
0.2%
7 132
1.3%

STD_LCLAS_NM
Categorical

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
조미채소류
1444 
과실류
1331 
엽경채류
1164 
국내산육류
570 
과일과채류
569 
Other values (17)
4922 

Length

Max length8
Median length7
Mean length4.0826
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row버섯류
2nd row엽경채류
3rd row엽경채류
4th row조미채소류
5th row국내산육류

Common Values

ValueCountFrequency (%)
조미채소류 1444
14.4%
과실류 1331
13.3%
엽경채류 1164
11.6%
국내산육류 570
 
5.7%
과일과채류 569
 
5.7%
과채류 569
 
5.7%
생축(가축)류 553
 
5.5%
특용작물류 433
 
4.3%
버섯류 419
 
4.2%
근채류 409
 
4.1%
Other values (12) 2539
25.4%

Length

2023-12-11T12:50:49.601914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조미채소류 1444
14.1%
과실류 1331
13.0%
엽경채류 1164
11.3%
국내산육류 570
 
5.5%
과일과채류 569
 
5.5%
과채류 569
 
5.5%
생축(가축)류 553
 
5.4%
특용작물류 433
 
4.2%
버섯류 419
 
4.1%
근채류 409
 
4.0%
Other values (13) 2814
27.4%

STD_LCLAS_CO
Real number (ℝ)

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.7044
Minimum1
Maximum91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:49.725406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q17
median11
Q317
95-th percentile81
Maximum91
Range90
Interquartile range (IQR)10

Descriptive statistics

Standard deviation22.275934
Coefficient of variation (CV)1.1305056
Kurtosis3.2059894
Mean19.7044
Median Absolute Deviation (MAD)5
Skewness2.0105909
Sum197044
Variance496.21724
MonotonicityNot monotonic
2023-12-11T12:50:50.213419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
12 1444
14.4%
6 1331
13.3%
10 1164
11.6%
43 570
 
5.7%
8 569
 
5.7%
9 569
 
5.7%
41 553
 
5.5%
16 433
 
4.3%
17 419
 
4.2%
11 409
 
4.1%
Other values (12) 2539
25.4%
ValueCountFrequency (%)
1 328
 
3.3%
3 408
 
4.1%
5 349
 
3.5%
6 1331
13.3%
7 124
 
1.2%
8 569
 
5.7%
9 569
 
5.7%
10 1164
11.6%
11 409
 
4.1%
12 1444
14.4%
ValueCountFrequency (%)
91 334
3.3%
89 151
 
1.5%
81 76
 
0.8%
74 75
 
0.8%
71 124
 
1.2%
47 132
 
1.3%
44 138
 
1.4%
43 570
5.7%
41 553
5.5%
17 419
4.2%

STD_PRDLST_NM
Text

Distinct68
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:50:50.466040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.5005
Min length1

Characters and Unicode

Total characters25005
Distinct characters107
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row새송이
2nd row양배추
3rd row양배추
4th row생강
5th row돈육
ValueCountFrequency (%)
한우 868
 
8.7%
상추 327
 
3.3%
오이 304
 
3.0%
풋고추 289
 
2.9%
돈육 274
 
2.7%
호박 265
 
2.6%
땅콩 231
 
2.3%
무 212
 
2.1%
조미제품 205
 
2.1%
당근 197
 
2.0%
Other values (58) 6828
68.3%
2023-12-11T12:50:50.871285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
추 1687
 
6.7%
고 1288
 
5.2%
우 949
 
3.8%
한 868
 
3.5%
파 809
 
3.2%
이 737
 
2.9%
배 645
 
2.6%
리 610
 
2.4%
토 430
 
1.7%
마 419
 
1.7%
Other values (97) 16563
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24567
98.2%
Open Punctuation 219
 
0.9%
Close Punctuation 219
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 1687
 
6.9%
고 1288
 
5.2%
우 949
 
3.9%
한 868
 
3.5%
파 809
 
3.3%
이 737
 
3.0%
배 645
 
2.6%
리 610
 
2.5%
토 430
 
1.8%
마 419
 
1.7%
Other values (95) 16125
65.6%
Open Punctuation
ValueCountFrequency (%)
( 219
100.0%
Close Punctuation
ValueCountFrequency (%)
) 219
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24567
98.2%
Common 438
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 1687
 
6.9%
고 1288
 
5.2%
우 949
 
3.9%
한 868
 
3.5%
파 809
 
3.3%
이 737
 
3.0%
배 645
 
2.6%
리 610
 
2.5%
토 430
 
1.8%
마 419
 
1.7%
Other values (95) 16125
65.6%
Common
ValueCountFrequency (%)
( 219
50.0%
) 219
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24567
98.2%
ASCII 438
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
추 1687
 
6.9%
고 1288
 
5.2%
우 949
 
3.9%
한 868
 
3.5%
파 809
 
3.3%
이 737
 
3.0%
배 645
 
2.6%
리 610
 
2.5%
토 430
 
1.8%
마 419
 
1.7%
Other values (95) 16125
65.6%
ASCII
ValueCountFrequency (%)
( 219
50.0%
) 219
50.0%

STD_PRDLST_CODE
Real number (ℝ)

Distinct69
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1977.5607
Minimum101
Maximum9117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:51.024161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile302
Q1704
median1101
Q31701
95-th percentile8132
Maximum9117
Range9016
Interquartile range (IQR)997

Descriptive statistics

Standard deviation2229.1648
Coefficient of variation (CV)1.1272295
Kurtosis3.2056544
Mean1977.5607
Median Absolute Deviation (MAD)484
Skewness2.0105517
Sum19775607
Variance4969175.8
MonotonicityNot monotonic
2023-12-11T12:50:51.165846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4121 553
 
5.5%
1005 327
 
3.3%
4301 315
 
3.1%
901 304
 
3.0%
1205 289
 
2.9%
902 265
 
2.6%
1603 231
 
2.3%
4304 226
 
2.3%
1101 212
 
2.1%
9108 205
 
2.1%
Other values (59) 7073
70.7%
ValueCountFrequency (%)
101 168
1.7%
104 160
1.6%
301 171
1.7%
302 170
1.7%
303 67
 
0.7%
501 168
1.7%
502 181
1.8%
601 176
1.8%
602 150
1.5%
605 122
1.2%
ValueCountFrequency (%)
9117 129
1.3%
9108 205
2.1%
8910 151
1.5%
8132 76
 
0.8%
7403 75
 
0.8%
7106 60
 
0.6%
7104 64
 
0.6%
4705 81
 
0.8%
4702 51
 
0.5%
4402 48
 
0.5%

STD_SPCIES_NM
Text

Distinct95
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:50:51.459079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length4.9752
Min length2

Characters and Unicode

Total characters49752
Distinct characters151
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

Unique0 ?
Unique (%)0.0%

Sample

1st row새송이(일반)
2nd row양배추(일반)
3rd row양배추(일반)
4th row생강(수입)
5th row앞다리살
ValueCountFrequency (%)
월동무 212
 
2.1%
고추가루 205
 
2.0%
월동배추 194
 
1.9%
청양 192
 
1.9%
양배추(일반 190
 
1.8%
꽈리고추(일반 188
 
1.8%
파프리카(일반 186
 
1.8%
대파(일반 186
 
1.8%
적상추 185
 
1.8%
흙당근 183
 
1.8%
Other values (89) 8388
81.4%
2023-12-11T12:50:51.958694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 4572
 
9.2%
) 4572
 
9.2%
반 3168
 
6.4%
일 3168
 
6.4%
수 1563
 
3.1%
추 1380
 
2.8%
입 1133
 
2.3%
고 1012
 
2.0%
파 809
 
1.6%
월 740
 
1.5%
Other values (141) 27635
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38054
76.5%
Open Punctuation 4572
 
9.2%
Close Punctuation 4572
 
9.2%
Decimal Number 1473
 
3.0%
Lowercase Letter 438
 
0.9%
Math Symbol 334
 
0.7%
Space Separator 309
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
반 3168
 
8.3%
일 3168
 
8.3%
수 1563
 
4.1%
추 1380
 
3.6%
입 1133
 
3.0%
고 1012
 
2.7%
파 809
 
2.1%
월 740
 
1.9%
양 717
 
1.9%
리 669
 
1.8%
Other values (128) 23695
62.3%
Decimal Number
ValueCountFrequency (%)
6 476
32.3%
0 371
25.2%
7 324
22.0%
1 148
 
10.0%
5 77
 
5.2%
3 67
 
4.5%
4 10
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
k 219
50.0%
g 219
50.0%
Open Punctuation
ValueCountFrequency (%)
( 4572
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4572
100.0%
Math Symbol
ValueCountFrequency (%)
~ 334
100.0%
Space Separator
ValueCountFrequency (%)
309
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38054
76.5%
Common 11260
 
22.6%
Latin 438
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
반 3168
 
8.3%
일 3168
 
8.3%
수 1563
 
4.1%
추 1380
 
3.6%
입 1133
 
3.0%
고 1012
 
2.7%
파 809
 
2.1%
월 740
 
1.9%
양 717
 
1.9%
리 669
 
1.8%
Other values (128) 23695
62.3%
Common
ValueCountFrequency (%)
( 4572
40.6%
) 4572
40.6%
6 476
 
4.2%
0 371
 
3.3%
~ 334
 
3.0%
7 324
 
2.9%
309
 
2.7%
1 148
 
1.3%
5 77
 
0.7%
3 67
 
0.6%
Latin
ValueCountFrequency (%)
k 219
50.0%
g 219
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38054
76.5%
ASCII 11698
 
23.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 4572
39.1%
) 4572
39.1%
6 476
 
4.1%
0 371
 
3.2%
~ 334
 
2.9%
7 324
 
2.8%
309
 
2.6%
k 219
 
1.9%
g 219
 
1.9%
1 148
 
1.3%
Other values (3) 154
 
1.3%
Hangul
ValueCountFrequency (%)
반 3168
 
8.3%
일 3168
 
8.3%
수 1563
 
4.1%
추 1380
 
3.6%
입 1133
 
3.0%
고 1012
 
2.7%
파 809
 
2.1%
월 740
 
1.9%
양 717
 
1.9%
리 669
 
1.8%
Other values (128) 23695
62.3%

STD_SPCIES_CODE
Real number (ℝ)

Distinct97
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean197772.19
Minimum10101
Maximum911718
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:52.138636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile30206
Q170401
median110112
Q3170101
95-th percentile813201
Maximum911718
Range901617
Interquartile range (IQR)99700

Descriptive statistics

Standard deviation222915.88
Coefficient of variation (CV)1.1271346
Kurtosis3.2053818
Mean197772.19
Median Absolute Deviation (MAD)48314
Skewness2.0105049
Sum1.9777219 × 109
Variance4.969149 × 1010
MonotonicityNot monotonic
2023-12-11T12:50:52.353417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110112 212
 
2.1%
910801 205
 
2.1%
100104 194
 
1.9%
120501 192
 
1.9%
100401 190
 
1.9%
120601 188
 
1.9%
132601 186
 
1.9%
120201 186
 
1.9%
100502 185
 
1.8%
110304 183
 
1.8%
Other values (87) 8079
80.8%
ValueCountFrequency (%)
10101 168
1.7%
10401 160
1.6%
30118 154
1.5%
30197 17
 
0.2%
30206 157
1.6%
30297 13
 
0.1%
30301 53
 
0.5%
30398 14
 
0.1%
50101 143
1.4%
50103 25
 
0.2%
ValueCountFrequency (%)
911718 129
1.3%
910801 205
2.1%
891002 151
1.5%
813201 76
 
0.8%
740314 75
 
0.8%
710603 60
 
0.6%
710402 64
 
0.6%
470501 81
 
0.8%
470214 51
 
0.5%
440227 48
 
0.5%

EXAMIN_UNIT_NM
Categorical

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
100G
3246 
1KG
1906 
10개
881 
1개
700 
1마리
520 
Other values (24)
2747 

Length

Max length7
Median length4
Mean length3.4822
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100G
2nd row1포기
3rd row10KG
4th row10KG
5th row100G

Common Values

ValueCountFrequency (%)
100G 3246
32.5%
1KG 1906
19.1%
10개 881
 
8.8%
1개 700
 
7.0%
1마리 520
 
5.2%
500G 429
 
4.3%
10KG 384
 
3.8%
20KG 359
 
3.6%
1포기 331
 
3.3%
200G 160
 
1.6%
Other values (19) 1084
 
10.8%

Length

2023-12-11T12:50:52.495579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
100g 3246
32.5%
1kg 1906
19.1%
10개 881
 
8.8%
1개 700
 
7.0%
1마리 520
 
5.2%
500g 429
 
4.3%
10kg 384
 
3.8%
20kg 359
 
3.6%
1포기 331
 
3.3%
200g 160
 
1.6%
Other values (19) 1084
 
10.8%

EXAMIN_UNIT
Real number (ℝ)

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.865552
Minimum1
Maximum600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:52.635053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median10
Q3100
95-th percentile100
Maximum600
Range599
Interquartile range (IQR)99

Descriptive statistics

Standard deviation81.024864
Coefficient of variation (CV)1.7665734
Kurtosis22.423083
Mean45.865552
Median Absolute Deviation (MAD)9
Skewness4.1146816
Sum458655.52
Variance6565.0285
MonotonicityNot monotonic
2023-12-11T12:50:52.763387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1.0 4074
40.7%
100.0 3014
30.1%
10.0 1390
 
13.9%
20.0 350
 
3.5%
1.86 132
 
1.3%
500.0 113
 
1.1%
200.0 111
 
1.1%
4.0 105
 
1.1%
15.0 103
 
1.0%
2.0 90
 
0.9%
Other values (11) 518
 
5.2%
ValueCountFrequency (%)
1.0 4074
40.7%
1.86 132
 
1.3%
2.0 90
 
0.9%
4.0 105
 
1.1%
5.0 83
 
0.8%
8.0 42
 
0.4%
10.0 1390
 
13.9%
12.0 25
 
0.2%
15.0 103
 
1.0%
17.0 20
 
0.2%
ValueCountFrequency (%)
600.0 64
 
0.6%
500.0 113
 
1.1%
200.0 111
 
1.1%
100.0 3014
30.1%
60.0 45
 
0.4%
45.0 35
 
0.4%
40.0 90
 
0.9%
35.0 33
 
0.3%
30.0 76
 
0.8%
20.0 350
 
3.5%

STD_UNIT_NM
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
kg
3915 
g
3302 
개
1963 
미(마리)
 
367
kg
 
219
Other values (2)
 
234

Length

Max length9
Median length7
Mean length3.9649
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowg
2nd row개
3rd rowkg
4th rowkg
5th rowg

Common Values

ValueCountFrequency (%)
kg 3915
39.1%
g 3302
33.0%
개 1963
19.6%
미(마리) 367
 
3.7%
kg 219
 
2.2%
kg 미(마리) 153
 
1.5%
l 81
 
0.8%

Length

2023-12-11T12:50:52.914822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:50:53.058673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kg 4287
42.2%
g 3302
32.5%
개 1963
19.3%
미(마리 520
 
5.1%
l 81
 
0.8%

STD_UNIT_CODE
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158457.96
Minimum101200
Maximum721200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:53.170978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101200
5-th percentile101200
Q1110000
median110000
Q3120000
95-th percentile701200
Maximum721200
Range620000
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation157572.15
Coefficient of variation (CV)0.9944098
Kurtosis8.2158048
Mean158457.96
Median Absolute Deviation (MAD)8800
Skewness3.1764361
Sum1.5845796 × 109
Variance2.4828982 × 1010
MonotonicityNot monotonic
2023-12-11T12:50:53.294195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
120000 3915
39.1%
110000 3302
33.0%
101200 1963
19.6%
701200 367
 
3.7%
720000 219
 
2.2%
721200 153
 
1.5%
340000 81
 
0.8%
ValueCountFrequency (%)
101200 1963
19.6%
110000 3302
33.0%
120000 3915
39.1%
340000 81
 
0.8%
701200 367
 
3.7%
720000 219
 
2.2%
721200 153
 
1.5%
ValueCountFrequency (%)
721200 153
 
1.5%
720000 219
 
2.2%
701200 367
 
3.7%
340000 81
 
0.8%
120000 3915
39.1%
110000 3302
33.0%
101200 1963
19.6%

EXAMIN_GRAD_NM
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상(1등급)
5744 
중(2등급)
4192 
하(3등급)
 
64

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중(2등급)
2nd row상(1등급)
3rd row상(1등급)
4th row중(2등급)
5th row중(2등급)

Common Values

ValueCountFrequency (%)
상(1등급) 5744
57.4%
중(2등급) 4192
41.9%
하(3등급) 64
 
0.6%

Length

2023-12-11T12:50:53.430469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:50:53.541280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상(1등급 5744
57.4%
중(2등급 4192
41.9%
하(3등급 64
 
0.6%

EXAMIN_GRAD_CODE
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
5744 
2
4192 
3
 
64

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 5744
57.4%
2 4192
41.9%
3 64
 
0.6%

Length

2023-12-11T12:50:53.678051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:50:53.782300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5744
57.4%
2 4192
41.9%
3 64
 
0.6%

STD_GRAD_NM
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상
5744 
보통
3766 
자연산 보통
 
426
4등
 
64

Length

Max length6
Median length1
Mean length1.596
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row보통
2nd row상
3rd row상
4th row보통
5th row보통

Common Values

ValueCountFrequency (%)
상 5744
57.4%
보통 3766
37.7%
자연산 보통 426
 
4.3%
4등 64
 
0.6%

Length

2023-12-11T12:50:53.908400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:50:54.025954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상 5744
55.1%
보통 4192
40.2%
자연산 426
 
4.1%
4등 64
 
0.6%

STD_GRAD_CODE
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
12
5744 
13
3766 
73
 
426
14
 
64

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row12
3rd row12
4th row13
5th row13

Common Values

ValueCountFrequency (%)
12 5744
57.4%
13 3766
37.7%
73 426
 
4.3%
14 64
 
0.6%

Length

2023-12-11T12:50:54.169836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:50:54.301124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
12 5744
57.4%
13 3766
37.7%
73 426
 
4.3%
14 64
 
0.6%

TODAY_PRIC
Real number (ℝ)

Distinct972
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean130740.7
Minimum200
Maximum4300000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:54.454500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200
5-th percentile699
Q11980
median5000
Q314600
95-th percentile258000
Maximum4300000
Range4299800
Interquartile range (IQR)12620

Descriptive statistics

Standard deviation599290.02
Coefficient of variation (CV)4.583806
Kurtosis27.474638
Mean130740.7
Median Absolute Deviation (MAD)3800
Skewness5.3200752
Sum1.307407 × 109
Variance3.5914852 × 1011
MonotonicityNot monotonic
2023-12-11T12:50:54.645491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 186
 
1.9%
2500 173
 
1.7%
5000 141
 
1.4%
1000 109
 
1.1%
1990 107
 
1.1%
1500 96
 
1.0%
2980 88
 
0.9%
10000 88
 
0.9%
700 85
 
0.9%
4000 83
 
0.8%
Other values (962) 8844
88.4%
ValueCountFrequency (%)
200 4
 
< 0.1%
210 4
 
< 0.1%
220 4
 
< 0.1%
230 4
 
< 0.1%
240 10
0.1%
250 23
0.2%
260 16
0.2%
270 18
0.2%
279 4
 
< 0.1%
280 23
0.2%
ValueCountFrequency (%)
4300000 6
0.1%
4281000 7
0.1%
4110000 9
0.1%
4040000 4
< 0.1%
4036333 6
0.1%
4000000 2
 
< 0.1%
3950000 2
 
< 0.1%
3939859 5
0.1%
3920000 3
 
< 0.1%
3916000 5
0.1%

BFRT_PRIC
Real number (ℝ)

MISSING 

Distinct874
Distinct (%)12.0%
Missing2692
Missing (%)26.9%
Infinite0
Infinite (%)0.0%
Mean164127.97
Minimum200
Maximum4300000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:54.799360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200
5-th percentile673.5
Q11997.5
median5470
Q315972.5
95-th percentile630200
Maximum4300000
Range4299800
Interquartile range (IQR)13975

Descriptive statistics

Standard deviation678640.87
Coefficient of variation (CV)4.1348277
Kurtosis20.157342
Mean164127.97
Median Absolute Deviation (MAD)4220
Skewness4.6150984
Sum1.1994472 × 109
Variance4.6055342 × 1011
MonotonicityNot monotonic
2023-12-11T12:50:54.942453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 138
 
1.4%
2500 124
 
1.2%
5000 99
 
1.0%
1990 82
 
0.8%
1000 75
 
0.8%
1500 73
 
0.7%
10000 65
 
0.7%
2980 65
 
0.7%
700 63
 
0.6%
4000 63
 
0.6%
Other values (864) 6461
64.6%
(Missing) 2692
26.9%
ValueCountFrequency (%)
200 3
 
< 0.1%
210 3
 
< 0.1%
220 3
 
< 0.1%
230 2
 
< 0.1%
240 8
0.1%
250 18
0.2%
260 13
0.1%
270 12
0.1%
279 3
 
< 0.1%
280 17
0.2%
ValueCountFrequency (%)
4300000 6
0.1%
4281000 7
0.1%
4110000 8
0.1%
4040000 3
 
< 0.1%
4036333 6
0.1%
4000000 1
 
< 0.1%
3950000 2
 
< 0.1%
3939859 5
0.1%
3920000 3
 
< 0.1%
3916000 5
0.1%

IMP_TRADE
Real number (ℝ)

ZEROS 

Distinct76
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3108
Minimum0
Maximum311
Zeros9447
Zeros (%)94.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:55.061064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.05
Maximum311
Range311
Interquartile range (IQR)0

Descriptive statistics

Standard deviation15.845312
Coefficient of variation (CV)6.8570677
Kurtosis144.97715
Mean2.3108
Median Absolute Deviation (MAD)0
Skewness10.664255
Sum23108
Variance251.07391
MonotonicityNot monotonic
2023-12-11T12:50:55.192945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9447
94.5%
2 37
 
0.4%
6 30
 
0.3%
3 27
 
0.3%
4 25
 
0.2%
18 20
 
0.2%
8 19
 
0.2%
5 19
 
0.2%
17 17
 
0.2%
1 16
 
0.2%
Other values (66) 343
 
3.4%
ValueCountFrequency (%)
0 9447
94.5%
1 16
 
0.2%
2 37
 
0.4%
3 27
 
0.3%
4 25
 
0.2%
5 19
 
0.2%
6 30
 
0.3%
7 16
 
0.2%
8 19
 
0.2%
9 11
 
0.1%
ValueCountFrequency (%)
311 3
< 0.1%
295 3
< 0.1%
242 7
0.1%
195 5
0.1%
146 5
0.1%
142 3
< 0.1%
139 3
< 0.1%
134 4
< 0.1%
131 7
0.1%
121 1
 
< 0.1%

TRADE_AMT
Real number (ℝ)

ZEROS 

Distinct73
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2283
Minimum0
Maximum294
Zeros9447
Zeros (%)94.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:50:55.332693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum294
Range294
Interquartile range (IQR)0

Descriptive statistics

Standard deviation15.467705
Coefficient of variation (CV)6.9414824
Kurtosis144.90569
Mean2.2283
Median Absolute Deviation (MAD)0
Skewness10.706572
Sum22283
Variance239.2499
MonotonicityNot monotonic
2023-12-11T12:50:55.455198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9447
94.5%
3 39
 
0.4%
2 37
 
0.4%
6 30
 
0.3%
4 24
 
0.2%
8 23
 
0.2%
1 23
 
0.2%
7 17
 
0.2%
16 15
 
0.1%
5 14
 
0.1%
Other values (63) 331
 
3.3%
ValueCountFrequency (%)
0 9447
94.5%
1 23
 
0.2%
2 37
 
0.4%
3 39
 
0.4%
4 24
 
0.2%
5 14
 
0.1%
6 30
 
0.3%
7 17
 
0.2%
8 23
 
0.2%
9 9
 
0.1%
ValueCountFrequency (%)
294 3
< 0.1%
289 3
< 0.1%
242 7
0.1%
195 5
0.1%
141 5
0.1%
139 1
 
< 0.1%
134 4
< 0.1%
132 2
 
< 0.1%
131 7
0.1%
128 3
< 0.1%

Sample

EXAMIN_DEEXAMIN_SE_NMEXAMIN_SE_CODEEXAMIN_AREA_NAMEEXAMIN_AREA_CODEEXAMIN_MRKT_NMEXAMIN_MRKT_CODESTD_MRKT_NMSTD_MRKT_CODEEXAMIN_PRDLST_NMEXAMIN_PRDLST_CODEEXAMIN_SPCIES_NMEXAMIN_SPCIES_CODESTD_LCLAS_NMSTD_LCLAS_COSTD_PRDLST_NMSTD_PRDLST_CODESTD_SPCIES_NMSTD_SPCIES_CODEEXAMIN_UNIT_NMEXAMIN_UNITSTD_UNIT_NMSTD_UNIT_CODEEXAMIN_GRAD_NMEXAMIN_GRAD_CODESTD_GRAD_NMSTD_GRAD_CODETODAY_PRICBFRT_PRICIMP_TRADETRADE_AMT
707220220205소비자가격7충북청주3300육거리시장1청주육거리종합시장331108새송이버섯317일반0버섯류17새송이1711새송이(일반)171101100G100.0g110000중(2등급)2보통1375075000
347220220204소비자가격7서울서부1102복조리시장13복조리시장110213양배추212일반0엽경채류10양배추1004양배추(일반)1004011포기1.0개101200상(1등급)1상123330<NA>00
369120220206도매가격6서울서부1102서울가락동도매시장11서울가락도매110001양배추212일반0엽경채류10양배추1004양배추(일반)10040110KG10.0kg120000상(1등급)1상127000700000
932420220206도매가격6서울서부1102서울가락동도매시장11서울가락도매110001생강247수입1조미채소류12생강1210생강(수입)12109810KG20.0kg120000중(2등급)2보통13450004500000
1006820220204소비자가격7충북청주3300육거리시장1청주육거리종합시장331108돼지고기514앞다리살4국내산육류43돈육4304앞다리살430470100G100.0g110000중(2등급)2보통131420<NA>00
833220220207소비자가격7경기의정부3124A-유통1A-유통312401건멸치638일반0건제품89멸치8910중멸치891002100G100.0g110000중(2등급)2자연산 보통734360436000
1174620220207소비자가격7대전2504E-유통2E-유통250093건블루베리427수입0과실류6블루베리659건블루베리(수입)65997100G100.0g110000중(2등급)2보통133330333000
119820220205소비자가격7전남순천3604A-유통1A-유통360401배412신고1과실류6배602신고6020110개10.0개101200상(1등급)1상12359803598000
869720220206축산물산지가격(농협)3경남진주3813진주시장4진주진주381383한우511350KG(수)6생축(가축)류41한우4121한육우 350kg 수4121341KG1.0kg720000중(2등급)2보통13835583555454
940120220207소비자가격7경북안동3724C-유통1C-유통372401물오징어619생선1신선 해면연체류74오징어7403팔완향오징어7403141마리1.0kg 미(마리)721200중(2등급)2자연산 보통736780678000
EXAMIN_DEEXAMIN_SE_NMEXAMIN_SE_CODEEXAMIN_AREA_NAMEEXAMIN_AREA_CODEEXAMIN_MRKT_NMEXAMIN_MRKT_CODESTD_MRKT_NMSTD_MRKT_CODEEXAMIN_PRDLST_NMEXAMIN_PRDLST_CODEEXAMIN_SPCIES_NMEXAMIN_SPCIES_CODESTD_LCLAS_NMSTD_LCLAS_COSTD_PRDLST_NMSTD_PRDLST_CODESTD_SPCIES_NMSTD_SPCIES_CODEEXAMIN_UNIT_NMEXAMIN_UNITSTD_UNIT_NMSTD_UNIT_CODEEXAMIN_GRAD_NMEXAMIN_GRAD_CODESTD_GRAD_NMSTD_GRAD_CODETODAY_PRICBFRT_PRICIMP_TRADETRADE_AMT
1087220220204소비자가격7경기수원3100수원지동시장1수원지동시장311108당근232무세척1근채류11당근1103흙당근1103041KG1.0kg120000상(1등급)1상122830<NA>00
97220220205소비자가격7충북청주3300육거리시장1청주육거리종합시장331108사과411후지5과실류6사과601후지6010310개10.0개101200상(1등급)1상12266002660000
459420220205소비자가격7부산2104D-유통2D-유통210098양파245양파(일반)0조미채소류12양파1201양파(일반)1201011KG1.0kg120000상(1등급)1상121600160000
560220220205소비자가격7경남창원3800창원상남시장1창원상남시장381402풋고추242꽈리고추2조미채소류12꽈리고추1206꽈리고추(일반)120601100G100.0g110000상(1등급)1상121200120000
247220220204소비자가격7광주2404A-유통1A-유통240094오이223다다기계통2과채류9오이901백다다기9010210개10.0개101200상(1등급)1상1211630<NA>00
830920220207소비자가격7서울서부1102복조리시장13복조리시장110213건멸치638일반0건제품89멸치8910중멸치891002100G100.0g110000중(2등급)2자연산 보통731860186000
609120220204소비자가격7부산2100부전시장22부산부전시장210089생강247국산0조미채소류12생강1210생강(일반)1210011KG1.0kg120000중(2등급)2보통135500<NA>00
1071720220205소비자가격7광주2401양동시장21광주양동시장240087팥(적두)142국산0두류3팥302붉은팥30206500G1.0kg120000상(1등급)1상124750475000
459020220205소비자가격7서울1104B-유통6B-유통110406양파245양파(일반)0조미채소류12양파1201양파(일반)1201011KG1.0kg120000상(1등급)1상121430143000
358620220206소비자가격7경남창원3800창원상남시장1창원상남시장381402양배추212일반0엽경채류10양배추1004양배추(일반)1004011포기1.0개101200상(1등급)1상123500350000