Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory145.0 B

Variable types

DateTime1
Categorical4
Text2
Numeric9

Dataset

Description거래일,시장,품목명,품목코드,등급,거래수량,거래단위수량,평균가격,전일평균가격,전년가격,전일대비등락율,검색일전년대비등락율,등급,거래단위,등급단위,중량단위
Author서울시농수산식품공사
URLhttps://data.seoul.go.kr/dataList/OA-20949/S/1/datasetView.do

Alerts

등급.1 is highly overall correlated with 등급단위 and 1 other fieldsHigh correlation
등급 is highly overall correlated with 등급단위 and 1 other fieldsHigh correlation
거래수량 is highly overall correlated with 거래단위High correlation
평균가격 is highly overall correlated with 전일평균가격 and 2 other fieldsHigh correlation
전일평균가격 is highly overall correlated with 평균가격 and 2 other fieldsHigh correlation
전일대비등락율 is highly overall correlated with 평균가격 and 2 other fieldsHigh correlation
검색일전년대비등락율 is highly overall correlated with 평균가격 and 2 other fieldsHigh correlation
등급단위 is highly overall correlated with 등급 and 1 other fieldsHigh correlation
중량단위 is highly overall correlated with 거래단위High correlation
거래단위 is highly overall correlated with 거래수량 and 1 other fieldsHigh correlation
거래단위 is highly imbalanced (62.6%)Imbalance
평균가격 has 3251 (32.5%) zerosZeros
전일평균가격 has 3162 (31.6%) zerosZeros
전년가격 has 2141 (21.4%) zerosZeros
전일대비등락율 has 4473 (44.7%) zerosZeros
검색일전년대비등락율 has 5017 (50.2%) zerosZeros
등급단위 has 1614 (16.1%) zerosZeros
중량단위 has 1184 (11.8%) zerosZeros

Reproduction

Analysis started2024-05-11 06:24:50.227829
Analysis finished2024-05-11 06:25:15.827254
Duration25.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct50
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-03-22 00:00:00
Maximum2024-05-10 00:00:00
2024-05-11T15:25:16.009666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:16.310175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시장
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
가락시장
5246 
강서시장(경매)
2540 
강서시장(시장도메인)
2214 

Length

Max length11
Median length4
Mean length6.5658
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가락시장
2nd row가락시장
3rd row가락시장
4th row강서시장(경매)
5th row강서시장(시장도메인)

Common Values

ValueCountFrequency (%)
가락시장 5246
52.5%
강서시장(경매) 2540
25.4%
강서시장(시장도메인) 2214
22.1%

Length

2024-05-11T15:25:16.586516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:16.862329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가락시장 5246
52.5%
강서시장(경매 2540
25.4%
강서시장(시장도메인 2214
22.1%
Distinct265
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:25:17.497658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length4.6706
Min length1

Characters and Unicode

Total characters46706
Distinct characters273
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.1%

Sample

1st row수박(일반)
2nd row딸기 금실
3rd row열무
4th row사과 시나노레드
5th row토마토
ValueCountFrequency (%)
수입 741
 
5.2%
사과 629
 
4.4%
딸기 400
 
2.8%
감귤 387
 
2.7%
시금치 267
 
1.9%
양파 247
 
1.7%
감자 241
 
1.7%
고구마 218
 
1.5%
214
 
1.5%
국산 200
 
1.4%
Other values (264) 10611
75.0%
2024-05-11T15:25:18.336594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4155
 
8.9%
1448
 
3.1%
1154
 
2.5%
) 1114
 
2.4%
( 1114
 
2.4%
1027
 
2.2%
1009
 
2.2%
986
 
2.1%
874
 
1.9%
840
 
1.8%
Other values (263) 32985
70.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40320
86.3%
Space Separator 4155
 
8.9%
Close Punctuation 1114
 
2.4%
Open Punctuation 1114
 
2.4%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1448
 
3.6%
1154
 
2.9%
1027
 
2.5%
1009
 
2.5%
986
 
2.4%
874
 
2.2%
840
 
2.1%
824
 
2.0%
803
 
2.0%
759
 
1.9%
Other values (257) 30596
75.9%
Uppercase Letter
ValueCountFrequency (%)
M 1
33.3%
B 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
4155
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1114
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 40320
86.3%
Common 6383
 
13.7%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1448
 
3.6%
1154
 
2.9%
1027
 
2.5%
1009
 
2.5%
986
 
2.4%
874
 
2.2%
840
 
2.1%
824
 
2.0%
803
 
2.0%
759
 
1.9%
Other values (257) 30596
75.9%
Common
ValueCountFrequency (%)
4155
65.1%
) 1114
 
17.5%
( 1114
 
17.5%
Latin
ValueCountFrequency (%)
M 1
33.3%
B 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 40320
86.3%
ASCII 6386
 
13.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4155
65.1%
) 1114
 
17.4%
( 1114
 
17.4%
M 1
 
< 0.1%
B 1
 
< 0.1%
A 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
1448
 
3.6%
1154
 
2.9%
1027
 
2.5%
1009
 
2.5%
986
 
2.4%
874
 
2.2%
840
 
2.1%
824
 
2.0%
803
 
2.0%
759
 
1.9%
Other values (257) 30596
75.9%

품목코드
Real number (ℝ)

Distinct265
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31523.17
Minimum15100
Maximum81802
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:25:18.643896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15100
5-th percentile21100
Q122402
median25101
Q341131
95-th percentile67134
Maximum81802
Range66702
Interquartile range (IQR)18729

Descriptive statistics

Standard deviation14327.904
Coefficient of variation (CV)0.45451976
Kurtosis2.6459117
Mean31523.17
Median Absolute Deviation (MAD)3697
Skewness1.7116525
Sum3.152317 × 108
Variance2.0528883 × 108
MonotonicityNot monotonic
2024-05-11T15:25:18.898053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24400 170
 
1.7%
41507 157
 
1.6%
21300 145
 
1.5%
22500 144
 
1.4%
22101 138
 
1.4%
32103 134
 
1.3%
41500 133
 
1.3%
22302 125
 
1.2%
32104 122
 
1.2%
22100 122
 
1.2%
Other values (255) 8610
86.1%
ValueCountFrequency (%)
15100 75
0.8%
15102 22
 
0.2%
15103 50
0.5%
15111 52
0.5%
15115 19
 
0.2%
15200 59
0.6%
15202 6
 
0.1%
15203 39
0.4%
15205 75
0.8%
15207 26
 
0.3%
ValueCountFrequency (%)
81802 26
0.3%
81207 23
0.2%
81204 26
0.3%
81203 20
0.2%
81202 22
0.2%
81201 21
0.2%
81101 19
0.2%
77202 17
0.2%
77201 13
0.1%
77101 5
 
0.1%

등급
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2960 
2720 
2587 
1614 
 
75

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
2960
29.6%
2720
27.2%
2587
25.9%
1614
16.1%
75
 
0.8%
44
 
0.4%

Length

2024-05-11T15:25:19.132877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:19.361295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2960
29.6%
2720
27.2%
2587
25.9%
1614
16.1%
75
 
0.8%
44
 
0.4%

거래수량
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.578855
Minimum0.05
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:25:19.637443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.05
5-th percentile1
Q14
median8
Q310
95-th percentile20
Maximum500
Range499.95
Interquartile range (IQR)6

Descriptive statistics

Standard deviation58.613977
Coefficient of variation (CV)3.762406
Kurtosis59.244133
Mean15.578855
Median Absolute Deviation (MAD)4
Skewness7.6897135
Sum155788.55
Variance3435.5983
MonotonicityNot monotonic
2024-05-11T15:25:19.866021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
10.0 2694
26.9%
4.0 1302
13.0%
5.0 921
 
9.2%
1.0 899
 
9.0%
2.0 886
 
8.9%
8.0 810
 
8.1%
20.0 553
 
5.5%
3.0 341
 
3.4%
15.0 298
 
3.0%
12.0 216
 
2.2%
Other values (19) 1080
10.8%
ValueCountFrequency (%)
0.05 25
 
0.2%
0.2 22
 
0.2%
0.5 13
 
0.1%
1.0 899
9.0%
1.5 179
 
1.8%
2.0 886
8.9%
2.5 18
 
0.2%
3.0 341
 
3.4%
3.6 24
 
0.2%
4.0 1302
13.0%
ValueCountFrequency (%)
500.0 125
 
1.2%
400.0 20
 
0.2%
200.0 15
 
0.1%
100.0 81
 
0.8%
50.0 60
 
0.6%
20.0 553
5.5%
18.0 98
 
1.0%
17.0 16
 
0.2%
16.0 59
 
0.6%
15.0 298
3.0%
Distinct59
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:25:20.276578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.1683
Min length2

Characters and Unicode

Total characters51683
Distinct characters25
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row9키로개
2nd row1키로상자
3rd row1.5키로단
4th row10키로상자
5th row5키로상자
ValueCountFrequency (%)
10키로상자 2434
24.3%
4키로상자 1181
11.8%
5키로상자 917
 
9.2%
2키로상자 860
 
8.6%
1키로 608
 
6.1%
8키로상자 587
 
5.9%
20키로상자 388
 
3.9%
3키로상자 338
 
3.4%
10키로망대 237
 
2.4%
15키로상자 194
 
1.9%
Other values (47) 2256
22.6%
2024-05-11T15:25:20.906184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9602
18.6%
9602
18.6%
7707
14.9%
7707
14.9%
1 4608
8.9%
0 3814
 
7.4%
5 1740
 
3.4%
2 1710
 
3.3%
4 1322
 
2.6%
8 908
 
1.8%
Other values (15) 2963
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36410
70.4%
Decimal Number 14891
28.8%
Other Punctuation 382
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9602
26.4%
9602
26.4%
7707
21.2%
7707
21.2%
363
 
1.0%
360
 
1.0%
349
 
1.0%
314
 
0.9%
160
 
0.4%
160
 
0.4%
Other values (4) 86
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 4608
30.9%
0 3814
25.6%
5 1740
 
11.7%
2 1710
 
11.5%
4 1322
 
8.9%
8 908
 
6.1%
3 433
 
2.9%
6 163
 
1.1%
7 146
 
1.0%
9 47
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 382
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36410
70.4%
Common 15273
29.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9602
26.4%
9602
26.4%
7707
21.2%
7707
21.2%
363
 
1.0%
360
 
1.0%
349
 
1.0%
314
 
0.9%
160
 
0.4%
160
 
0.4%
Other values (4) 86
 
0.2%
Common
ValueCountFrequency (%)
1 4608
30.2%
0 3814
25.0%
5 1740
 
11.4%
2 1710
 
11.2%
4 1322
 
8.7%
8 908
 
5.9%
3 433
 
2.8%
. 382
 
2.5%
6 163
 
1.1%
7 146
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36410
70.4%
ASCII 15273
29.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
9602
26.4%
9602
26.4%
7707
21.2%
7707
21.2%
363
 
1.0%
360
 
1.0%
349
 
1.0%
314
 
0.9%
160
 
0.4%
160
 
0.4%
Other values (4) 86
 
0.2%
ASCII
ValueCountFrequency (%)
1 4608
30.2%
0 3814
25.0%
5 1740
 
11.4%
2 1710
 
11.2%
4 1322
 
8.7%
8 908
 
5.9%
3 433
 
2.8%
. 382
 
2.5%
6 163
 
1.1%
7 146
 
1.0%

평균가격
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5538
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19388.847
Minimum0
Maximum380000
Zeros3251
Zeros (%)32.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:25:21.178816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median9915.5
Q324937.25
95-th percentile72363
Maximum380000
Range380000
Interquartile range (IQR)24937.25

Descriptive statistics

Standard deviation30029.7
Coefficient of variation (CV)1.5488131
Kurtosis17.092109
Mean19388.847
Median Absolute Deviation (MAD)9915.5
Skewness3.394724
Sum1.9388848 × 108
Variance9.017829 × 108
MonotonicityNot monotonic
2024-05-11T15:25:21.443355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3251
32.5%
20000 33
 
0.3%
18000 30
 
0.3%
16000 19
 
0.2%
19000 18
 
0.2%
14000 17
 
0.2%
30000 17
 
0.2%
15000 17
 
0.2%
10000 15
 
0.1%
38000 15
 
0.1%
Other values (5528) 6568
65.7%
ValueCountFrequency (%)
0 3251
32.5%
100 1
 
< 0.1%
250 3
 
< 0.1%
252 2
 
< 0.1%
254 1
 
< 0.1%
261 1
 
< 0.1%
309 1
 
< 0.1%
316 1
 
< 0.1%
317 1
 
< 0.1%
322 1
 
< 0.1%
ValueCountFrequency (%)
380000 1
< 0.1%
323243 1
< 0.1%
288000 1
< 0.1%
272381 1
< 0.1%
267750 1
< 0.1%
260000 1
< 0.1%
256860 1
< 0.1%
247800 2
< 0.1%
245700 1
< 0.1%
245647 1
< 0.1%

전일평균가격
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct5638
Distinct (%)56.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19766.786
Minimum0
Maximum441667
Zeros3162
Zeros (%)31.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:25:21.709157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10400
Q325533.75
95-th percentile74932
Maximum441667
Range441667
Interquartile range (IQR)25533.75

Descriptive statistics

Standard deviation30106.251
Coefficient of variation (CV)1.5230726
Kurtosis20.050862
Mean19766.786
Median Absolute Deviation (MAD)10400
Skewness3.4776671
Sum1.9766786 × 108
Variance9.0638637 × 108
MonotonicityNot monotonic
2024-05-11T15:25:22.379569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3162
31.6%
18000 33
 
0.3%
20000 26
 
0.3%
10000 21
 
0.2%
15000 17
 
0.2%
16000 17
 
0.2%
33000 17
 
0.2%
11000 17
 
0.2%
19000 16
 
0.2%
13143 13
 
0.1%
Other values (5628) 6661
66.6%
ValueCountFrequency (%)
0 3162
31.6%
100 1
 
< 0.1%
250 5
 
0.1%
259 1
 
< 0.1%
261 1
 
< 0.1%
262 1
 
< 0.1%
267 1
 
< 0.1%
268 1
 
< 0.1%
269 1
 
< 0.1%
297 1
 
< 0.1%
ValueCountFrequency (%)
441667 1
< 0.1%
382000 1
< 0.1%
380000 1
< 0.1%
286667 1
< 0.1%
281440 1
< 0.1%
258571 1
< 0.1%
254100 1
< 0.1%
249370 1
< 0.1%
248554 1
< 0.1%
245700 1
< 0.1%

전년가격
Real number (ℝ)

ZEROS 

Distinct5741
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18885.406
Minimum0
Maximum369793
Zeros2141
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:25:22.620343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12076.5
median12500
Q325250
95-th percentile58015.55
Maximum369793
Range369793
Interquartile range (IQR)23173.5

Descriptive statistics

Standard deviation25473.687
Coefficient of variation (CV)1.3488557
Kurtosis24.9783
Mean18885.406
Median Absolute Deviation (MAD)11296.5
Skewness3.9359753
Sum1.8885406 × 108
Variance6.4890873 × 108
MonotonicityNot monotonic
2024-05-11T15:25:22.949075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2141
 
21.4%
20000 57
 
0.6%
16000 44
 
0.4%
15000 43
 
0.4%
8500 43
 
0.4%
10000 41
 
0.4%
40000 36
 
0.4%
35000 34
 
0.3%
22000 34
 
0.3%
25000 29
 
0.3%
Other values (5731) 7498
75.0%
ValueCountFrequency (%)
0 2141
21.4%
350 13
 
0.1%
376 1
 
< 0.1%
460 1
 
< 0.1%
484 1
 
< 0.1%
551 1
 
< 0.1%
616 1
 
< 0.1%
631 1
 
< 0.1%
653 1
 
< 0.1%
664 1
 
< 0.1%
ValueCountFrequency (%)
369793 1
< 0.1%
276667 1
< 0.1%
273334 2
< 0.1%
264600 1
< 0.1%
260000 1
< 0.1%
251224 1
< 0.1%
243850 1
< 0.1%
243750 1
< 0.1%
243636 1
< 0.1%
241500 1
< 0.1%

전일대비등락율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4675
Distinct (%)46.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.080502
Minimum0
Maximum1900
Zeros4473
Zeros (%)44.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:25:23.193849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median81.408784
Q3100
95-th percentile119.6846
Maximum1900
Range1900
Interquartile range (IQR)100

Descriptive statistics

Standard deviation58.037444
Coefficient of variation (CV)1.0348952
Kurtosis127.67674
Mean56.080502
Median Absolute Deviation (MAD)38.06495
Skewness4.7820522
Sum560805.02
Variance3368.3449
MonotonicityNot monotonic
2024-05-11T15:25:23.465547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4473
44.7%
100.0 816
 
8.2%
105.555555555555 4
 
< 0.1%
94.4444444444444 4
 
< 0.1%
75.0 3
 
< 0.1%
83.3333333333333 3
 
< 0.1%
95.2380952380952 3
 
< 0.1%
111.111111111111 3
 
< 0.1%
95.4545454545454 3
 
< 0.1%
104.0 2
 
< 0.1%
Other values (4665) 4686
46.9%
ValueCountFrequency (%)
0.0 4473
44.7%
1.05831304899989 1
 
< 0.1%
10.0396551724137 1
 
< 0.1%
21.1819595645412 1
 
< 0.1%
23.8395560040363 1
 
< 0.1%
24.6904588492352 1
 
< 0.1%
26.7642127724432 1
 
< 0.1%
29.1666666666666 1
 
< 0.1%
29.5794461720716 1
 
< 0.1%
31.811371342954 1
 
< 0.1%
ValueCountFrequency (%)
1900.0 1
< 0.1%
1303.75093773443 1
< 0.1%
830.578379249234 1
< 0.1%
719.6 1
< 0.1%
637.546468401486 1
< 0.1%
412.080244221543 1
< 0.1%
392.295454545454 1
< 0.1%
373.415045515456 1
< 0.1%
368.170173833485 1
< 0.1%
303.186022610483 1
< 0.1%

검색일전년대비등락율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4835
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.033119
Minimum0
Maximum1091.6194
Zeros5017
Zeros (%)50.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:25:23.751750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3112.96765
95-th percentile200.50059
Maximum1091.6194
Range1091.6194
Interquartile range (IQR)112.96765

Descriptive statistics

Standard deviation79.71992
Coefficient of variation (CV)1.2449795
Kurtosis6.2152446
Mean64.033119
Median Absolute Deviation (MAD)0
Skewness1.660733
Sum640331.19
Variance6355.2657
MonotonicityNot monotonic
2024-05-11T15:25:24.037858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 5017
50.2%
100.0 19
 
0.2%
211.764705882352 8
 
0.1%
165.466448445171 6
 
0.1%
195.741176470588 6
 
0.1%
169.682352941176 6
 
0.1%
51.0340370529943 5
 
0.1%
133.333333333333 5
 
0.1%
105.882352941176 5
 
0.1%
312.021085111853 5
 
0.1%
Other values (4825) 4918
49.2%
ValueCountFrequency (%)
0.0 5017
50.2%
2.27634873662645 1
 
< 0.1%
12.1731289449954 1
 
< 0.1%
14.0113229828765 1
 
< 0.1%
17.1844868223698 1
 
< 0.1%
17.2296015180265 1
 
< 0.1%
19.1451917033312 1
 
< 0.1%
19.1711100339311 1
 
< 0.1%
21.0318489121113 1
 
< 0.1%
21.4145116405348 1
 
< 0.1%
ValueCountFrequency (%)
1091.61942699555 1
< 0.1%
639.82496633968 1
< 0.1%
638.265351461832 1
< 0.1%
625.173726009265 1
< 0.1%
616.964285714285 1
< 0.1%
600.0 1
< 0.1%
557.617817947062 1
< 0.1%
535.172 1
< 0.1%
534.293186355839 1
< 0.1%
532.666666666666 1
< 0.1%

등급.1
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2960 
2720 
2587 
1614 
 
75

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
2960
29.6%
2720
27.2%
2587
25.9%
1614
16.1%
75
 
0.8%
44
 
0.4%

Length

2024-05-11T15:25:24.356107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:25:24.557019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2960
29.6%
2720
27.2%
2587
25.9%
1614
16.1%
75
 
0.8%
44
 
0.4%

거래단위
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
키로상자
7707 
키로
1184 
키로망대
 
349
 
196
키로개
 
164
Other values (6)
 
400

Length

Max length4
Median length4
Mean length3.641
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row키로개
2nd row키로상자
3rd row키로단
4th row키로상자
5th row키로상자

Common Values

ValueCountFrequency (%)
키로상자 7707
77.1%
키로 1184
 
11.8%
키로망대 349
 
3.5%
196
 
2.0%
키로개 164
 
1.6%
그람단 160
 
1.6%
키로단 154
 
1.5%
42
 
0.4%
키로펜 17
 
0.2%
키로포대 14
 
0.1%

Length

2024-05-11T15:25:24.756350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
키로상자 7707
77.1%
키로 1184
 
11.8%
키로망대 349
 
3.5%
196
 
2.0%
키로개 164
 
1.6%
그람단 160
 
1.6%
키로단 154
 
1.5%
42
 
0.4%
키로펜 17
 
0.2%
키로포대 14
 
0.1%

등급단위
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6905
Minimum0
Maximum6
Zeros1614
Zeros (%)16.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:25:24.936523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile3
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.1220676
Coefficient of variation (CV)0.66374894
Kurtosis-0.097383637
Mean1.6905
Median Absolute Deviation (MAD)1
Skewness0.26456487
Sum16905
Variance1.2590357
MonotonicityNot monotonic
2024-05-11T15:25:25.130502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 2960
29.6%
2 2660
26.6%
3 2587
25.9%
0 1614
16.1%
4 75
 
0.8%
5 60
 
0.6%
6 44
 
0.4%
ValueCountFrequency (%)
0 1614
16.1%
1 2960
29.6%
2 2660
26.6%
3 2587
25.9%
4 75
 
0.8%
5 60
 
0.6%
6 44
 
0.4%
ValueCountFrequency (%)
6 44
 
0.4%
5 60
 
0.6%
4 75
 
0.8%
3 2587
25.9%
2 2660
26.6%
1 2960
29.6%
0 1614
16.1%

중량단위
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0482
Minimum0
Maximum88
Zeros1184
Zeros (%)11.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:25:25.361523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile29
Maximum88
Range88
Interquartile range (IQR)0

Descriptive statistics

Standard deviation12.709698
Coefficient of variation (CV)3.1395925
Kurtosis20.144642
Mean4.0482
Median Absolute Deviation (MAD)0
Skewness4.4968411
Sum40482
Variance161.53643
MonotonicityNot monotonic
2024-05-11T15:25:25.571769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 7707
77.1%
0 1184
 
11.8%
4 349
 
3.5%
68 196
 
2.0%
8 164
 
1.6%
48 160
 
1.6%
29 154
 
1.5%
88 42
 
0.4%
32 17
 
0.2%
2 14
 
0.1%
ValueCountFrequency (%)
0 1184
 
11.8%
1 7707
77.1%
2 14
 
0.1%
4 349
 
3.5%
8 164
 
1.6%
25 13
 
0.1%
29 154
 
1.5%
32 17
 
0.2%
48 160
 
1.6%
68 196
 
2.0%
ValueCountFrequency (%)
88 42
 
0.4%
68 196
 
2.0%
48 160
 
1.6%
32 17
 
0.2%
29 154
 
1.5%
25 13
 
0.1%
8 164
 
1.6%
4 349
 
3.5%
2 14
 
0.1%
1 7707
77.1%

Interactions

2024-05-11T15:25:13.297240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:57.176011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:59.233515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:01.314045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:03.462967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:05.208209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:07.179723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:09.584116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:11.528905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:13.504291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:57.391093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:59.468235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:01.542848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:03.658657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:05.401348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:07.405647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:09.809696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:11.724658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:13.693775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:57.597121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:59.651304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:01.779675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:03.894569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:05.596192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:07.582911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:10.004109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:11.914316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:13.947183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:57.860501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:59.899193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:02.010928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:04.133026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:05.819456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:07.771925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:10.213853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:12.141965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:14.152718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:58.069390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:00.192715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:02.241407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:04.300019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:06.008575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:07.954911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:10.439730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:12.366396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:14.380520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:58.307059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:00.433235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:02.502966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:04.490013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:06.226392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:08.172911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:10.640297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:12.578873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:14.580122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:58.528059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:00.664855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:02.820053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:04.678154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:06.491403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:08.382852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:10.853918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:12.739064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:14.723405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:58.736847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:00.881562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:03.038988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:04.865824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:06.756058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:09.140311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:11.062607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:12.908963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:14.906180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:24:58.972664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:01.108409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:03.265594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:05.057173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:06.983554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:09.341014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:11.293112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:25:13.090742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:25:25.746483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
거래일시장품목코드등급거래수량거래단위수량평균가격전일평균가격전년가격전일대비등락율검색일전년대비등락율등급.1거래단위등급단위중량단위
거래일1.0000.1300.0760.0000.0000.0000.1930.1350.1470.0210.3600.0000.0000.0000.000
시장0.1301.0000.5290.2030.0710.5720.0420.0410.1380.0000.0890.2030.3450.1460.184
품목코드0.0760.5291.0000.4950.2390.8820.2120.2660.3170.0930.1920.4950.5430.5080.367
등급0.0000.2030.4951.0000.0000.4730.1500.1500.1990.0890.0401.0000.3161.0000.088
거래수량0.0000.0710.2390.0001.0001.0000.1120.0820.0440.0000.0000.0000.7850.0000.716
거래단위수량0.0000.5720.8820.4731.0001.0000.5480.5320.5860.0000.3180.4731.0000.5301.000
평균가격0.1930.0420.2120.1500.1120.5481.0000.7760.5680.6630.3160.1500.1650.1430.069
전일평균가격0.1350.0410.2660.1500.0820.5320.7761.0000.7840.0000.2350.1500.1440.1300.058
전년가격0.1470.1380.3170.1990.0440.5860.5680.7841.0000.0000.0020.1990.2200.1720.035
전일대비등락율0.0210.0000.0930.0890.0000.0000.6630.0000.0001.0000.2570.0890.0000.1340.000
검색일전년대비등락율0.3600.0890.1920.0400.0000.3180.3160.2350.0020.2571.0000.0400.1350.0580.060
등급.10.0000.2030.4951.0000.0000.4730.1500.1500.1990.0890.0401.0000.3161.0000.088
거래단위0.0000.3450.5430.3160.7851.0000.1650.1440.2200.0000.1350.3161.0000.3621.000
등급단위0.0000.1460.5081.0000.0000.5300.1430.1300.1720.1340.0581.0000.3621.0000.065
중량단위0.0000.1840.3670.0880.7161.0000.0690.0580.0350.0000.0600.0881.0000.0651.000
2024-05-11T15:25:25.973758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
거래단위등급.1등급시장
거래단위1.0000.1680.1680.215
등급.10.1681.0001.0000.086
등급0.1681.0001.0000.086
시장0.2150.0860.0861.000
2024-05-11T15:25:26.164577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목코드거래수량평균가격전일평균가격전년가격전일대비등락율검색일전년대비등락율등급단위중량단위시장등급등급.1거래단위
품목코드1.000-0.203-0.134-0.1210.116-0.131-0.1480.020-0.2660.2730.2720.2720.281
거래수량-0.2031.0000.1630.1630.326-0.077-0.026-0.0630.2650.0530.0000.0000.583
평균가격-0.1340.1631.0000.5310.1190.5910.583-0.115-0.0160.0250.0790.0790.071
전일평균가격-0.1210.1630.5311.0000.4650.5410.535-0.113-0.0170.0180.0750.0750.065
전년가격0.1160.3260.1190.4651.0000.1570.289-0.185-0.0190.0610.1000.1000.101
전일대비등락율-0.131-0.0770.5910.5410.1571.0000.7490.010-0.0120.0000.0530.0530.000
검색일전년대비등락율-0.148-0.0260.5830.5350.2890.7491.0000.0110.0220.0590.0230.0230.067
등급단위0.020-0.063-0.115-0.113-0.1850.0100.0111.000-0.0460.0981.0001.0000.188
중량단위-0.2660.265-0.016-0.017-0.019-0.0120.022-0.0461.0000.0770.0320.0321.000
시장0.2730.0530.0250.0180.0610.0000.0590.0980.0771.0000.0860.0860.215
등급0.2720.0000.0790.0750.1000.0530.0231.0000.0320.0861.0001.0000.168
등급.10.2720.0000.0790.0750.1000.0530.0231.0000.0320.0861.0001.0000.168
거래단위0.2810.5830.0710.0650.1010.0000.0670.1881.0000.2150.1680.1681.000

Missing values

2024-05-11T15:25:15.175687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:25:15.633198image/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

거래일시장품목명품목코드등급거래수량거래단위수량평균가격전일평균가격전년가격전일대비등락율검색일전년대비등락율등급.1거래단위등급단위중량단위
328242024-04-18가락시장수박(일반)221019.09키로개42050420500100.00.0키로개28
166402024-04-29가락시장딸기 금실226121.01키로상자3048000.00.0키로상자31
631062024-03-29가락시장열무231061.51.5키로단253425222523100.475813100.435989키로단129
10662024-05-10강서시장(경매)사과 시나노레드4113410.010키로상자00200000.00.0키로상자01
550292024-04-04강서시장(시장도메인)토마토225005.05키로상자287142800016000102.55179.4625키로상자21
503902024-04-07강서시장(시장도메인)열무231064.04키로상자0850025390.00.0키로상자31
588212024-04-01가락시장브로콜리 국산258018.08키로상자19458000.00.0키로상자31
501952024-04-07강서시장(경매)치커리(일반)268202.02키로상자0353500.00.0키로상자21
577342024-04-02강서시장(경매)상추 적포기214054.04키로상자9390854818507109.85025750.737559키로상자11
585262024-04-01가락시장부추(일반)21601500.0500그람단2918000.00.0그람단148
거래일시장품목명품목코드등급거래수량거래단위수량평균가격전일평균가격전년가격전일대비등락율검색일전년대비등락율등급.1거래단위등급단위중량단위
140182024-05-01가락시장(선)명태 수입6125110.010키로상자487782451941667198.939598117.066263키로상자21
26852024-05-09강서시장(시장도메인)양배추212008.08키로망대1175675507303155.708609160.974942키로망대24
722992024-03-23강서시장(경매)알배기배추211118.08키로상자400003370325692118.683797155.690487키로상자11
442392024-04-11강서시장(경매)양상추 수입252508.08키로상자14500145000100.00.0키로상자31
75722024-05-05가락시장롱그린고추2420910.010키로상자020753135220.00.0키로상자31
413062024-04-13강서시장(경매)감 대봉시4161215.015키로상자0041500.00.0키로상자31
231052024-04-25강서시장(경매)청양고추2420310.010키로상자523915870013758789.25212938.078452키로상자01
730372024-03-23강서시장(시장도메인)골드파인애플 수입4275112.012키로상자215002025328000106.15711376.785714키로상자21
26662024-05-09강서시장(시장도메인)감자1520020.020키로상자51554620746690830.578379110.417648키로상자31
457372024-04-10강서시장(경매)가지228008.08키로상자00247880.00.0키로상자21