Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows1658
Duplicate rows (%)16.6%
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 1658 (16.6%) 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 (50.5%)Imbalance

Reproduction

Analysis started2024-04-29 13:44:33.403649
Analysis finished2024-04-29 13:44:34.433865
Duration1.03 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
2024-04-29T22:44:34.478730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:44:34.564312image/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
6083 
(주)경인농산
1994 
인천원예농협
1923 

Length

Max length7
Median length7
Mean length6.8077
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
(주)부평농산 6083
60.8%
(주)경인농산 1994
 
19.9%
인천원예농협 1923
 
19.2%

Length

2024-04-29T22:44:34.670237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:44:34.747732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주)부평농산 6083
60.8%
주)경인농산 1994
 
19.9%
인천원예농협 1923
 
19.2%

품목
Text

Distinct137
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-29T22:44:34.962867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length2
Mean length2.8661
Min length1

Characters and Unicode

Total characters28661
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

Unique11 ?
Unique (%)0.1%

Sample

1st row바나나
2nd row감자
3rd row양배추
4th row무순
5th row레몬
ValueCountFrequency (%)
포도 734
 
7.3%
풋고추 477
 
4.7%
깻잎 430
 
4.3%
떫은감 426
 
4.2%
단감 390
 
3.9%
고구마 389
 
3.9%
오이 380
 
3.8%
호박 339
 
3.4%
느타리버섯 273
 
2.7%
표고버섯 262
 
2.6%
Other values (129) 5994
59.4%
2024-04-29T22:44:35.318384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
추 2045
 
7.1%
고 1480
 
5.2%
감 1216
 
4.2%
이 956
 
3.3%
섯 929
 
3.2%
버 929
 
3.2%
리 873
 
3.0%
도 751
 
2.6%
포 734
 
2.6%
마 721
 
2.5%
Other values (175) 18027
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28093
98.0%
Close Punctuation 223
 
0.8%
Open Punctuation 223
 
0.8%
Space Separator 94
 
0.3%
Other Punctuation 28
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 2045
 
7.3%
고 1480
 
5.3%
감 1216
 
4.3%
이 956
 
3.4%
섯 929
 
3.3%
버 929
 
3.3%
리 873
 
3.1%
도 751
 
2.7%
포 734
 
2.6%
마 721
 
2.6%
Other values (171) 17459
62.1%
Close Punctuation
ValueCountFrequency (%)
) 223
100.0%
Open Punctuation
ValueCountFrequency (%)
( 223
100.0%
Space Separator
ValueCountFrequency (%)
94
100.0%
Other Punctuation
ValueCountFrequency (%)
, 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28093
98.0%
Common 568
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 2045
 
7.3%
고 1480
 
5.3%
감 1216
 
4.3%
이 956
 
3.4%
섯 929
 
3.3%
버 929
 
3.3%
리 873
 
3.1%
도 751
 
2.7%
포 734
 
2.6%
마 721
 
2.6%
Other values (171) 17459
62.1%
Common
ValueCountFrequency (%)
) 223
39.3%
( 223
39.3%
94
16.5%
, 28
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28093
98.0%
ASCII 568
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
추 2045
 
7.3%
고 1480
 
5.3%
감 1216
 
4.3%
이 956
 
3.4%
섯 929
 
3.3%
버 929
 
3.3%
리 873
 
3.1%
도 751
 
2.7%
포 734
 
2.6%
마 721
 
2.6%
Other values (171) 17459
62.1%
ASCII
ValueCountFrequency (%)
) 223
39.3%
( 223
39.3%
94
16.5%
, 28
 
4.9%

품종
Text

Distinct239
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-29T22:44:35.553458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length4.7111
Min length2

Characters and Unicode

Total characters47111
Distinct characters241
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

Unique31 ?
Unique (%)0.3%

Sample

1st row바나나(수입)
2nd row기타
3rd row양배추(일반)
4th row무순(일반)
5th row레몬(수입)
ValueCountFrequency (%)
기타 1106
 
11.0%
샤인마스캇 502
 
5.0%
백다다기 331
 
3.3%
약시 313
 
3.1%
깻잎(일반 301
 
3.0%
송본 292
 
2.9%
청양 286
 
2.9%
바나나(수입 248
 
2.5%
새송이버섯(일반 225
 
2.2%
애호박 215
 
2.1%
Other values (230) 6206
61.9%
2024-04-29T22:44:35.914578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 3977
 
8.4%
( 3977
 
8.4%
반 3297
 
7.0%
일 3205
 
6.8%
기 1642
 
3.5%
타 1442
 
3.1%
추 1166
 
2.5%
수 1022
 
2.2%
마 1010
 
2.1%
리 935
 
2.0%
Other values (231) 25438
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38956
82.7%
Close Punctuation 3977
 
8.4%
Open Punctuation 3977
 
8.4%
Decimal Number 172
 
0.4%
Space Separator 25
 
0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
반 3297
 
8.5%
일 3205
 
8.2%
기 1642
 
4.2%
타 1442
 
3.7%
추 1166
 
3.0%
수 1022
 
2.6%
마 1010
 
2.6%
리 935
 
2.4%
입 887
 
2.3%
고 879
 
2.3%
Other values (225) 23471
60.3%
Decimal Number
ValueCountFrequency (%)
1 171
99.4%
3 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 3977
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3977
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38956
82.7%
Common 8155
 
17.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
반 3297
 
8.5%
일 3205
 
8.2%
기 1642
 
4.2%
타 1442
 
3.7%
추 1166
 
3.0%
수 1022
 
2.6%
마 1010
 
2.6%
리 935
 
2.4%
입 887
 
2.3%
고 879
 
2.3%
Other values (225) 23471
60.3%
Common
ValueCountFrequency (%)
) 3977
48.8%
( 3977
48.8%
1 171
 
2.1%
25
 
0.3%
, 4
 
< 0.1%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38956
82.7%
ASCII 8155
 
17.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 3977
48.8%
( 3977
48.8%
1 171
 
2.1%
25
 
0.3%
, 4
 
< 0.1%
3 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
반 3297
 
8.5%
일 3205
 
8.2%
기 1642
 
4.2%
타 1442
 
3.7%
추 1166
 
3.0%
수 1022
 
2.6%
마 1010
 
2.6%
리 935
 
2.4%
입 887
 
2.3%
고 879
 
2.3%
Other values (225) 23471
60.3%

거래물량(kg)
Real number (ℝ)

HIGH CORRELATION 

Distinct198
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.3961
Minimum1
Maximum750
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-29T22:44:36.038872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median8
Q320
95-th percentile120
Maximum750
Range749
Interquartile range (IQR)17

Descriptive statistics

Standard deviation63.896869
Coefficient of variation (CV)2.3323345
Kurtosis34.760996
Mean27.3961
Median Absolute Deviation (MAD)6
Skewness5.3284026
Sum273961
Variance4082.8099
MonotonicityNot monotonic
2024-04-29T22:44:36.368267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1004
 
10.0%
5 970
 
9.7%
10 919
 
9.2%
2 814
 
8.1%
3 694
 
6.9%
4 533
 
5.3%
8 359
 
3.6%
6 352
 
3.5%
20 325
 
3.2%
7 288
 
2.9%
Other values (188) 3742
37.4%
ValueCountFrequency (%)
1 1004
10.0%
2 814
8.1%
3 694
6.9%
4 533
5.3%
5 970
9.7%
6 352
 
3.5%
7 288
 
2.9%
8 359
 
3.6%
9 205
 
2.1%
10 919
9.2%
ValueCountFrequency (%)
750 1
 
< 0.1%
700 1
 
< 0.1%
690 1
 
< 0.1%
604 1
 
< 0.1%
600 6
 
0.1%
576 1
 
< 0.1%
560 4
 
< 0.1%
550 22
0.2%
540 2
 
< 0.1%
530 2
 
< 0.1%

경락단가(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct1004
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean244466.71
Minimum500
Maximum9128000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-29T22:44:36.505705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile14000
Q150000
median122750
Q3280000
95-th percentile900050
Maximum9128000
Range9127500
Interquartile range (IQR)230000

Descriptive statistics

Standard deviation382316.25
Coefficient of variation (CV)1.5638786
Kurtosis66.82565
Mean244466.71
Median Absolute Deviation (MAD)87250
Skewness5.7152267
Sum2.4446671 × 109
Variance1.4616572 × 1011
MonotonicityNot monotonic
2024-04-29T22:44:36.656329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
120000 156
 
1.6%
60000 143
 
1.4%
90000 130
 
1.3%
80000 128
 
1.3%
40000 127
 
1.3%
180000 116
 
1.2%
140000 115
 
1.1%
24000 115
 
1.1%
70000 110
 
1.1%
150000 109
 
1.1%
Other values (994) 8751
87.5%
ValueCountFrequency (%)
500 1
 
< 0.1%
1000 2
 
< 0.1%
1500 4
 
< 0.1%
2000 5
 
0.1%
2500 6
0.1%
3000 7
0.1%
3600 1
 
< 0.1%
4000 14
0.1%
4200 1
 
< 0.1%
4250 1
 
< 0.1%
ValueCountFrequency (%)
9128000 1
< 0.1%
7000000 1
< 0.1%
5910000 2
< 0.1%
5400000 1
< 0.1%
4320000 1
< 0.1%
4200000 2
< 0.1%
3500000 1
< 0.1%
3450000 1
< 0.1%
3406000 1
< 0.1%
3360000 1
< 0.1%

산지
Text

Distinct133
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-29T22:44:36.927332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length5.5492
Min length2

Characters and Unicode

Total characters55492
Distinct characters102
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

Unique12 ?
Unique (%)0.1%

Sample

1st row국외
2nd row강원 양구군
3rd row전남 해남군
4th row경기도 수원시 장안구
5th row국외
ValueCountFrequency (%)
경기 1898
 
10.1%
충남 1779
 
9.5%
경북 1485
 
7.9%
강원 1388
 
7.4%
국외 977
 
5.2%
논산시 838
 
4.5%
청도군 579
 
3.1%
인천 505
 
2.7%
경남 460
 
2.4%
평창군 439
 
2.3%
Other values (126) 8467
45.0%
2024-04-29T22:44:37.304660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8815
15.9%
시 4428
 
8.0%
경 4208
 
7.6%
군 3704
 
6.7%
남 2751
 
5.0%
충 2332
 
4.2%
북 2060
 
3.7%
기 1952
 
3.5%
원 1872
 
3.4%
천 1727
 
3.1%
Other values (92) 21643
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46677
84.1%
Space Separator 8815
 
15.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4428
 
9.5%
경 4208
 
9.0%
군 3704
 
7.9%
남 2751
 
5.9%
충 2332
 
5.0%
북 2060
 
4.4%
기 1952
 
4.2%
원 1872
 
4.0%
천 1727
 
3.7%
산 1620
 
3.5%
Other values (91) 20023
42.9%
Space Separator
ValueCountFrequency (%)
8815
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46677
84.1%
Common 8815
 
15.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4428
 
9.5%
경 4208
 
9.0%
군 3704
 
7.9%
남 2751
 
5.9%
충 2332
 
5.0%
북 2060
 
4.4%
기 1952
 
4.2%
원 1872
 
4.0%
천 1727
 
3.7%
산 1620
 
3.5%
Other values (91) 20023
42.9%
Common
ValueCountFrequency (%)
8815
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46677
84.1%
ASCII 8815
 
15.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8815
100.0%
Hangul
ValueCountFrequency (%)
시 4428
 
9.5%
경 4208
 
9.0%
군 3704
 
7.9%
남 2751
 
5.9%
충 2332
 
5.0%
북 2060
 
4.4%
기 1952
 
4.2%
원 1872
 
4.0%
천 1727
 
3.7%
산 1620
 
3.5%
Other values (91) 20023
42.9%

비고
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경매
8917 
정가수의
1083 

Length

Max length4
Median length2
Mean length2.2166
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경매 8917
89.2%
정가수의 1083
 
10.8%

Length

2024-04-29T22:44:37.462124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:44:37.562361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경매 8917
89.2%
정가수의 1083
 
10.8%

Interactions

2024-04-29T22:44:34.076679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:44:33.900370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:44:34.167615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:44:33.986089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-29T22:44:37.632554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경매일자법인명거래물량(kg)경락단가(원)비고
경매일자1.0000.1140.0430.0290.061
법인명0.1141.0000.0800.0750.172
거래물량(kg)0.0430.0801.0000.5580.059
경락단가(원)0.0290.0750.5581.0000.044
비고0.0610.1720.0590.0441.000
2024-04-29T22:44:37.740662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법인명비고
법인명1.0000.283
비고0.2831.000
2024-04-29T22:44:37.817157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
거래물량(kg)경락단가(원)법인명비고
거래물량(kg)1.0000.7540.0480.045
경락단가(원)0.7541.0000.0330.044
법인명0.0480.0331.0000.283
비고0.0450.0440.2831.000

Missing values

2024-04-29T22:44:34.264189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-29T22:44:34.372856image/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
300262023-10-04(주)부평농산바나나바나나(수입)5165000국외정가수의
567592023-10-06(주)부평농산감자기타4164000강원 양구군경매
363222023-10-04(주)경인농산양배추양배추(일반)36360000전남 해남군경매
455812023-10-05(주)부평농산무순무순(일반)2017000경기도 수원시 장안구경매
202512023-10-03(주)부평농산레몬레몬(수입)3195000국외정가수의
949652023-10-09(주)부평농산떫은감약시210000경북 청도군경매
104652023-10-02인천원예농협꽈리고추꽈리고추(일반)14308000강원 평창군경매
973322023-10-09(주)경인농산양배추양배추(일반)110000강원 평창군경매
6312023-10-02(주)부평농산깻잎깻잎(일반)3100500충남 논산시경매
495612023-10-05(주)경인농산표고버섯표고버섯(일반)254000국외경매
경매일자법인명품목품종거래물량(kg)경락단가(원)산지비고
607002023-10-06(주)부평농산떫은감약시14168000경북 청도군경매
406672023-10-05(주)부평농산청경채청경채(일반)10120000서울 송파구경매
406462023-10-05(주)부평농산쑥갓쑥갓(일반)10120000인천 계양구경매
238132023-10-03인천원예농협풋고추청양126000전남 나주시경매
440102023-10-05(주)부평농산포도샤인마스캇20140000경북 경산시경매
132182023-10-03(주)부평농산풋고추청양8456000광주 남구경매
539582023-10-05인천원예농협양파양파(일반)751500000전남 무안군정가수의
996322023-10-09인천원예농협고구마호박고구마230000충남 당진군경매
163632023-10-03(주)부평농산포도샤인마스캇18450000경북 김천시경매
983242023-10-09(주)경인농산깻잎깻잎(일반)114000충남 논산시경매

Duplicate rows

Most frequently occurring

경매일자법인명품목품종거래물량(kg)경락단가(원)산지비고# duplicates
5042023-10-04(주)부평농산느타리버섯느타리버섯(일반)535000경기 양평군경매13
2772023-10-03(주)부평농산느타리버섯느타리버섯(일반)545000경기 양평군경매11
5232023-10-04(주)부평농산대파대파(일반)5501375000강원 강릉시경매11
3292023-10-03(주)부평농산바나나바나나(수입)10310000국외정가수의10
6162023-10-04(주)부평농산팽이버섯팽이1호575000경북 청도군경매10
562023-10-02(주)부평농산느타리버섯느타리버섯(일반)557500경기 양평군경매9
5472023-10-04(주)부평농산바나나바나나(수입)137000국외정가수의9
7712023-10-05(주)부평농산미나리미나리(일반)5130000충남 부여군경매9
7802023-10-05(주)부평농산브로코리(녹색꽃양배추)브로코리(수입)235000국외경매9
8772023-10-05(주)부평농산표고버섯표고버섯(일반)829600충남 부여군경매9