Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows1681
Duplicate rows (%)16.8%
Total size in memory722.7 KiB
Average record size in memory74.0 B

Variable types

DateTime1
Categorical2
Text3
Numeric2

Dataset

Description삼산농산물도매시장의 실시간 농산물 경락가격을 제공함으로써 시장 투명성 확보에 기여<br/>삼산농산물도매시장 실시간 경락정보(경매일자,법인명,품목,품종,거래물량(kg),경락단가(원), 산지,비고)등의 데이터 입니다.<br/>
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3044829&srcSe=7661IVAWM27C61E190

Alerts

Dataset has 1681 (16.8%) duplicate rowsDuplicates
거래물량(kg) is highly overall correlated with 경락단가(원)High correlation
경락단가(원) is highly overall correlated with 거래물량(kg)High correlation
비고 is highly imbalanced (53.4%)Imbalance

Reproduction

Analysis started2024-04-29 13:44:27.360440
Analysis finished2024-04-29 13:44:28.422880
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

경매일자
Date

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-10-02 00:00:00
Maximum2023-10-09 00:00:00
2024-04-29T22:44:28.462451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:44:28.550364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

법인명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
(주)부평농산
6048 
(주)경인농산
2040 
인천원예농협
1912 

Length

Max length7
Median length7
Mean length6.8088
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천원예농협
2nd row(주)부평농산
3rd row(주)경인농산
4th row(주)부평농산
5th row(주)부평농산

Common Values

ValueCountFrequency (%)
(주)부평농산 6048
60.5%
(주)경인농산 2040
 
20.4%
인천원예농협 1912
 
19.1%

Length

2024-04-29T22:44:28.655279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:44:28.737241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주)부평농산 6048
60.5%
주)경인농산 2040
 
20.4%
인천원예농협 1912
 
19.1%

품목
Text

Distinct140
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-29T22:44:28.961851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length2
Mean length2.836
Min length1

Characters and Unicode

Total characters28360
Distinct characters185
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)0.2%

Sample

1st row무
2nd row깻잎
3rd row느타리버섯
4th row호박
5th row청경채
ValueCountFrequency (%)
포도 818
 
8.1%
떫은감 438
 
4.3%
풋고추 437
 
4.3%
단감 425
 
4.2%
고구마 386
 
3.8%
깻잎 385
 
3.8%
오이 377
 
3.7%
호박 321
 
3.2%
느타리버섯 267
 
2.6%
바나나 251
 
2.5%
Other values (132) 5995
59.4%
2024-04-29T22:44:29.325346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
추 2038
 
7.2%
고 1393
 
4.9%
감 1272
 
4.5%
이 1015
 
3.6%
섯 939
 
3.3%
버 939
 
3.3%
도 829
 
2.9%
포 818
 
2.9%
리 817
 
2.9%
나 756
 
2.7%
Other values (175) 17544
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27854
98.2%
Close Punctuation 194
 
0.7%
Open Punctuation 194
 
0.7%
Space Separator 100
 
0.4%
Other Punctuation 18
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 2038
 
7.3%
고 1393
 
5.0%
감 1272
 
4.6%
이 1015
 
3.6%
섯 939
 
3.4%
버 939
 
3.4%
도 829
 
3.0%
포 818
 
2.9%
리 817
 
2.9%
나 756
 
2.7%
Other values (171) 17038
61.2%
Close Punctuation
ValueCountFrequency (%)
) 194
100.0%
Open Punctuation
ValueCountFrequency (%)
( 194
100.0%
Space Separator
ValueCountFrequency (%)
100
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27854
98.2%
Common 506
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 2038
 
7.3%
고 1393
 
5.0%
감 1272
 
4.6%
이 1015
 
3.6%
섯 939
 
3.4%
버 939
 
3.4%
도 829
 
3.0%
포 818
 
2.9%
리 817
 
2.9%
나 756
 
2.7%
Other values (171) 17038
61.2%
Common
ValueCountFrequency (%)
) 194
38.3%
( 194
38.3%
100
19.8%
, 18
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27854
98.2%
ASCII 506
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
추 2038
 
7.3%
고 1393
 
5.0%
감 1272
 
4.6%
이 1015
 
3.6%
섯 939
 
3.4%
버 939
 
3.4%
도 829
 
3.0%
포 818
 
2.9%
리 817
 
2.9%
나 756
 
2.7%
Other values (171) 17038
61.2%
ASCII
ValueCountFrequency (%)
) 194
38.3%
( 194
38.3%
100
19.8%
, 18
 
3.6%

품종
Text

Distinct247
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-29T22:44:29.595226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length4.7015
Min length2

Characters and Unicode

Total characters47015
Distinct characters256
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)0.4%

Sample

1st row가을무
2nd row깻잎(일반)
3rd row애느타리
4th row애호박
5th row청경채(일반)
ValueCountFrequency (%)
기타 1053
 
10.5%
샤인마스캇 565
 
5.6%
백다다기 328
 
3.3%
약시 322
 
3.2%
송본 306
 
3.1%
깻잎(일반 273
 
2.7%
청양 261
 
2.6%
바나나(수입 251
 
2.5%
새송이버섯(일반 244
 
2.4%
애호박 220
 
2.2%
Other values (239) 6207
61.9%
2024-04-29T22:44:29.991846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 3897
 
8.3%
) 3897
 
8.3%
반 3283
 
7.0%
일 3182
 
6.8%
기 1589
 
3.4%
타 1378
 
2.9%
추 1219
 
2.6%
마 1096
 
2.3%
수 970
 
2.1%
리 897
 
1.9%
Other values (246) 25607
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39002
83.0%
Open Punctuation 3897
 
8.3%
Close Punctuation 3897
 
8.3%
Decimal Number 187
 
0.4%
Space Separator 30
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
반 3283
 
8.4%
일 3182
 
8.2%
기 1589
 
4.1%
타 1378
 
3.5%
추 1219
 
3.1%
마 1096
 
2.8%
수 970
 
2.5%
리 897
 
2.3%
입 836
 
2.1%
고 832
 
2.1%
Other values (240) 23720
60.8%
Decimal Number
ValueCountFrequency (%)
1 186
99.5%
3 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 3897
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3897
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39002
83.0%
Common 8013
 
17.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
반 3283
 
8.4%
일 3182
 
8.2%
기 1589
 
4.1%
타 1378
 
3.5%
추 1219
 
3.1%
마 1096
 
2.8%
수 970
 
2.5%
리 897
 
2.3%
입 836
 
2.1%
고 832
 
2.1%
Other values (240) 23720
60.8%
Common
ValueCountFrequency (%)
( 3897
48.6%
) 3897
48.6%
1 186
 
2.3%
30
 
0.4%
, 2
 
< 0.1%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39002
83.0%
ASCII 8013
 
17.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 3897
48.6%
) 3897
48.6%
1 186
 
2.3%
30
 
0.4%
, 2
 
< 0.1%
3 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
반 3283
 
8.4%
일 3182
 
8.2%
기 1589
 
4.1%
타 1378
 
3.5%
추 1219
 
3.1%
마 1096
 
2.8%
수 970
 
2.5%
리 897
 
2.3%
입 836
 
2.1%
고 832
 
2.1%
Other values (240) 23720
60.8%

거래물량(kg)
Real number (ℝ)

HIGH CORRELATION 

Distinct206
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.8786
Minimum1
Maximum700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-29T22:44:30.117345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median9
Q321
95-th percentile120
Maximum700
Range699
Interquartile range (IQR)18

Descriptive statistics

Standard deviation64.047467
Coefficient of variation (CV)2.2973703
Kurtosis33.497233
Mean27.8786
Median Absolute Deviation (MAD)7
Skewness5.2521535
Sum278786
Variance4102.0781
MonotonicityNot monotonic
2024-04-29T22:44:30.246505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1028
 
10.3%
5 957
 
9.6%
10 926
 
9.3%
2 844
 
8.4%
3 666
 
6.7%
4 505
 
5.1%
6 356
 
3.6%
20 329
 
3.3%
8 315
 
3.1%
7 290
 
2.9%
Other values (196) 3784
37.8%
ValueCountFrequency (%)
1 1028
10.3%
2 844
8.4%
3 666
6.7%
4 505
5.1%
5 957
9.6%
6 356
 
3.6%
7 290
 
2.9%
8 315
 
3.1%
9 208
 
2.1%
10 926
9.3%
ValueCountFrequency (%)
700 1
 
< 0.1%
690 1
 
< 0.1%
604 1
 
< 0.1%
600 3
 
< 0.1%
560 1
 
< 0.1%
550 26
0.3%
530 3
 
< 0.1%
520 1
 
< 0.1%
510 1
 
< 0.1%
503 1
 
< 0.1%

경락단가(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct963
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean244823.82
Minimum1000
Maximum7000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-29T22:44:30.382400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile13000
Q150000
median125000
Q3282000
95-th percentile880000
Maximum7000000
Range6999000
Interquartile range (IQR)232000

Descriptive statistics

Standard deviation383364.79
Coefficient of variation (CV)1.5658803
Kurtosis48.992
Mean244823.82
Median Absolute Deviation (MAD)90000
Skewness5.2629685
Sum2.4482382 × 109
Variance1.4696857 × 1011
MonotonicityNot monotonic
2024-04-29T22:44:30.532743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
120000 155
 
1.6%
60000 151
 
1.5%
180000 133
 
1.3%
24000 129
 
1.3%
100000 128
 
1.3%
150000 119
 
1.2%
90000 115
 
1.1%
70000 111
 
1.1%
80000 107
 
1.1%
12000 101
 
1.0%
Other values (953) 8751
87.5%
ValueCountFrequency (%)
1000 1
 
< 0.1%
1500 2
 
< 0.1%
2000 4
 
< 0.1%
2500 2
 
< 0.1%
3000 6
 
0.1%
3500 4
 
< 0.1%
4000 11
 
0.1%
4300 1
 
< 0.1%
4500 5
 
0.1%
5000 36
0.4%
ValueCountFrequency (%)
7000000 1
< 0.1%
6783000 1
< 0.1%
5910000 1
< 0.1%
5760000 1
< 0.1%
5280000 1
< 0.1%
5250000 1
< 0.1%
4200000 1
< 0.1%
4024000 1
< 0.1%
3639500 1
< 0.1%
3536000 1
< 0.1%

산지
Text

Distinct135
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-29T22:44:30.807143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length5.5899
Min length2

Characters and Unicode

Total characters55899
Distinct characters108
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)0.1%

Sample

1st row강원 평창군
2nd row충남 논산시
3rd row충남 천안시
4th row경기 양주시
5th row경기 용인시 처인구
ValueCountFrequency (%)
경기 1916
 
10.1%
충남 1708
 
9.0%
경북 1625
 
8.6%
강원 1386
 
7.3%
국외 912
 
4.8%
논산시 776
 
4.1%
청도군 622
 
3.3%
경남 498
 
2.6%
인천 497
 
2.6%
평창군 445
 
2.4%
Other values (127) 8527
45.1%
2024-04-29T22:44:31.183392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8912
15.9%
시 4500
 
8.1%
경 4429
 
7.9%
군 3761
 
6.7%
남 2720
 
4.9%
충 2167
 
3.9%
북 2139
 
3.8%
기 1966
 
3.5%
원 1894
 
3.4%
천 1742
 
3.1%
Other values (98) 21669
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46987
84.1%
Space Separator 8912
 
15.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4500
 
9.6%
경 4429
 
9.4%
군 3761
 
8.0%
남 2720
 
5.8%
충 2167
 
4.6%
북 2139
 
4.6%
기 1966
 
4.2%
원 1894
 
4.0%
천 1742
 
3.7%
산 1570
 
3.3%
Other values (97) 20099
42.8%
Space Separator
ValueCountFrequency (%)
8912
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46987
84.1%
Common 8912
 
15.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4500
 
9.6%
경 4429
 
9.4%
군 3761
 
8.0%
남 2720
 
5.8%
충 2167
 
4.6%
북 2139
 
4.6%
기 1966
 
4.2%
원 1894
 
4.0%
천 1742
 
3.7%
산 1570
 
3.3%
Other values (97) 20099
42.8%
Common
ValueCountFrequency (%)
8912
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46987
84.1%
ASCII 8912
 
15.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8912
100.0%
Hangul
ValueCountFrequency (%)
시 4500
 
9.6%
경 4429
 
9.4%
군 3761
 
8.0%
남 2720
 
5.8%
충 2167
 
4.6%
북 2139
 
4.6%
기 1966
 
4.2%
원 1894
 
4.0%
천 1742
 
3.7%
산 1570
 
3.3%
Other values (97) 20099
42.8%

비고
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경매
9008 
정가수의
992 

Length

Max length4
Median length2
Mean length2.1984
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경매 9008
90.1%
정가수의 992
 
9.9%

Length

2024-04-29T22:44:31.306512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:44:31.402550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경매 9008
90.1%
정가수의 992
 
9.9%

Interactions

2024-04-29T22:44:28.022510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:44:27.845143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:44:28.114461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:44:27.936479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-29T22:44:31.456630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경매일자법인명거래물량(kg)경락단가(원)비고
경매일자1.0000.1300.0570.0250.055
법인명0.1301.0000.0740.0770.161
거래물량(kg)0.0570.0741.0000.5860.064
경락단가(원)0.0250.0770.5861.0000.037
비고0.0550.1610.0640.0371.000
2024-04-29T22:44:31.544328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법인명비고
법인명1.0000.265
비고0.2651.000
2024-04-29T22:44:31.611228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
거래물량(kg)경락단가(원)법인명비고
거래물량(kg)1.0000.7510.0440.049
경락단가(원)0.7511.0000.0340.037
법인명0.0440.0341.0000.265
비고0.0490.0370.2651.000

Missing values

2024-04-29T22:44:28.262859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-29T22:44:28.370474image/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

경매일자법인명품목품종거래물량(kg)경락단가(원)산지비고
832412023-10-07인천원예농협무가을무13117000강원 평창군경매
142282023-10-03(주)부평농산깻잎깻잎(일반)351000충남 논산시경매
216082023-10-03(주)경인농산느타리버섯애느타리30240000충남 천안시경매
14142023-10-02(주)부평농산호박애호박25262500경기 양주시경매
563372023-10-06(주)부평농산청경채청경채(일반)1080000경기 용인시 처인구경매
304982023-10-04(주)부평농산참다래(키위)키위(수입)3168000국외정가수의
664252023-10-06(주)경인농산고구마밤고구마111000전북 김제시경매
260322023-10-04(주)부평농산적채적채(일반)327000강원 평창군경매
607652023-10-06(주)부평농산배추기타5060000강원 정선군경매
295832023-10-04(주)부평농산알타리무알타리무(일반)18036000경기 화성시경매
경매일자법인명품목품종거래물량(kg)경락단가(원)산지비고
152092023-10-03(주)부평농산배추우거지330000인천 부평구정가수의
533662023-10-05인천원예농협팥팥(일반)343500충남 당진군경매
883882023-10-09(주)부평농산오이백다다기116000충남 부여군경매
411562023-10-05(주)부평농산쌈채모듬쌈채2066000경기 이천시경매
860792023-10-09(주)부평농산깻잎깻잎(일반)6180000충남 논산시경매
77572023-10-02(주)경인농산깻잎깻잎(일반)5145000충남 논산시경매
506412023-10-05(주)경인농산양배추양배추(일반)20270000전남 해남군경매
656962023-10-06(주)경인농산새송이버섯새송이버섯(일반)672000충북 음성군경매
786552023-10-07(주)부평농산파인애플파인애플(수입)3126000국외정가수의
829142023-10-07인천원예농협호박애호박19000경기 연천군경매

Duplicate rows

Most frequently occurring

경매일자법인명품목품종거래물량(kg)경락단가(원)산지비고# duplicates
4752023-10-04(주)부평농산느타리버섯느타리버섯(일반)535000경기 양평군경매13
5362023-10-04(주)부평농산브로코리(녹색꽃양배추)브로코리(수입)234000국외경매13
8682023-10-05(주)부평농산표고버섯표고버섯(수입)211000국외경매13
1492023-10-02(주)부평농산팽이버섯팽이1호10240000경북 청도군경매11
10992023-10-06(주)부평농산팽이버섯팽이1호10170000경북 청도군경매11
16352023-10-09(주)부평농산포도샤인마스캇40340000경북 경산시경매11
472023-10-02(주)부평농산느타리버섯느타리버섯(일반)557500경기 양평군경매10
2492023-10-03(주)부평농산느타리버섯느타리버섯(일반)545000경기 양평군경매10
5532023-10-04(주)부평농산양상추양상추(일반)5195000경남 하동군경매10
6712023-10-05(주)경인농산미나리돌미나리384000경기 시흥시경매10