Overview

Dataset statistics

Number of variables8
Number of observations311
Missing cells79
Missing cells (%)3.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.9 KiB
Average record size in memory65.4 B

Variable types

Categorical4
Numeric1
Text3

Dataset

Description대구광역시_도매시장 중도매인 현황_20220630
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15086032&dataSetDetailId=150860321cc5fdd73f015&provdMethod=FILE

Alerts

법인 is highly overall correlated with 거래법인High correlation
거래법인 is highly overall correlated with 법인High correlation
사무실번호 has 79 (25.4%) missing valuesMissing

Reproduction

Analysis started2024-04-19 05:43:08.480706
Analysis finished2024-04-19 05:43:09.089820
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

법인
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
효성청과㈜
77 
대양청과㈜
73 
대구중앙청과㈜
57 
농협북대구공판장
47 
대구경북원예농협공판장
37 
Other values (2)
20 

Length

Max length12
Median length11
Mean length6.9517685
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
효성청과㈜ 77
24.8%
대양청과㈜ 73
23.5%
대구중앙청과㈜ 57
18.3%
농협북대구공판장 47
15.1%
대구경북원예농협공판장 37
11.9%
축산부류 (신흥산업㈜) 19
 
6.1%
법인 1
 
0.3%

Length

2024-04-19T14:43:09.157702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:43:09.268109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
효성청과㈜ 77
23.3%
대양청과㈜ 73
22.1%
대구중앙청과㈜ 57
17.3%
농협북대구공판장 47
14.2%
대구경북원예농협공판장 37
11.2%
축산부류 19
 
5.8%
신흥산업㈜ 19
 
5.8%
법인 1
 
0.3%

순번
Real number (ℝ)

Distinct77
Distinct (%)24.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.276527
Minimum1
Maximum77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-19T14:43:09.401895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q113.5
median28
Q344.5
95-th percentile67.5
Maximum77
Range76
Interquartile range (IQR)31

Descriptive statistics

Standard deviation19.918723
Coefficient of variation (CV)0.65789327
Kurtosis-0.76354243
Mean30.276527
Median Absolute Deviation (MAD)15
Skewness0.45212142
Sum9416
Variance396.75554
MonotonicityNot monotonic
2024-04-19T14:43:09.567137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 6
 
1.9%
11 6
 
1.9%
2 6
 
1.9%
19 6
 
1.9%
18 6
 
1.9%
17 6
 
1.9%
16 6
 
1.9%
14 6
 
1.9%
13 6
 
1.9%
12 6
 
1.9%
Other values (67) 251
80.7%
ValueCountFrequency (%)
1 6
1.9%
2 6
1.9%
3 6
1.9%
4 6
1.9%
5 6
1.9%
6 6
1.9%
7 6
1.9%
8 6
1.9%
9 6
1.9%
10 6
1.9%
ValueCountFrequency (%)
77 1
0.3%
76 1
0.3%
75 1
0.3%
74 1
0.3%
73 2
0.6%
72 2
0.6%
71 2
0.6%
70 2
0.6%
69 2
0.6%
68 2
0.6%

허가번호
Text

Distinct310
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-04-19T14:43:09.843257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.938907
Min length10

Characters and Unicode

Total characters3402
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique309 ?
Unique (%)99.4%

Sample

1st row1996-1-0277
2nd row1996-1-0296
3rd row2000-1-0757
4th row2000-1-0761
5th row2003-1-0795
ValueCountFrequency (%)
2021-1-1137 2
 
0.6%
1996-1-0277 1
 
0.3%
2021-1-1136 1
 
0.3%
2021-1-1135 1
 
0.3%
2021-1-1131 1
 
0.3%
2020-1-1127 1
 
0.3%
2020-1-1125 1
 
0.3%
2020-1-1124 1
 
0.3%
2017-1-1074 1
 
0.3%
2019-1-1113 1
 
0.3%
Other values (300) 300
96.5%
2024-04-19T14:43:10.215691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 768
22.6%
1 736
21.6%
- 622
18.3%
2 433
12.7%
9 217
 
6.4%
8 146
 
4.3%
7 134
 
3.9%
6 103
 
3.0%
3 88
 
2.6%
4 83
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2780
81.7%
Dash Punctuation 622
 
18.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 768
27.6%
1 736
26.5%
2 433
15.6%
9 217
 
7.8%
8 146
 
5.3%
7 134
 
4.8%
6 103
 
3.7%
3 88
 
3.2%
4 83
 
3.0%
5 72
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 622
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3402
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 768
22.6%
1 736
21.6%
- 622
18.3%
2 433
12.7%
9 217
 
6.4%
8 146
 
4.3%
7 134
 
3.9%
6 103
 
3.0%
3 88
 
2.6%
4 83
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3402
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 768
22.6%
1 736
21.6%
- 622
18.3%
2 433
12.7%
9 217
 
6.4%
8 146
 
4.3%
7 134
 
3.9%
6 103
 
3.0%
3 88
 
2.6%
4 83
 
2.4%

중도매인
Categorical

Distinct47
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
김**
69 
이**
39 
박**
31 
정**
19 
서**
15 
Other values (42)
138 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique16 ?
Unique (%)5.1%

Sample

1st row전**
2nd row배**
3rd row허**
4th row경**
5th row여**

Common Values

ValueCountFrequency (%)
김** 69
22.2%
이** 39
12.5%
박** 31
 
10.0%
정** 19
 
6.1%
서** 15
 
4.8%
최** 14
 
4.5%
배** 9
 
2.9%
조** 8
 
2.6%
홍** 8
 
2.6%
장** 7
 
2.3%
Other values (37) 92
29.6%

Length

2024-04-19T14:43:10.356792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
김 69
22.2%
이 39
12.5%
박 31
 
10.0%
정 19
 
6.1%
서 15
 
4.8%
최 14
 
4.5%
배 9
 
2.9%
조 8
 
2.6%
홍 8
 
2.6%
장 7
 
2.3%
Other values (37) 92
29.6%

상호
Text

Distinct307
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-04-19T14:43:10.655123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length4.8424437
Min length2

Characters and Unicode

Total characters1506
Distinct characters202
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique303 ?
Unique (%)97.4%

Sample

1st row대교상회
2nd row만평상회
3rd row경북상회
4th row우리상회
5th row성주상회
ValueCountFrequency (%)
농업회사법인 4
 
1.2%
㈜창성뿌리 2
 
0.6%
창녕상회 2
 
0.6%
2
 
0.6%
성보상회 2
 
0.6%
경북상회 2
 
0.6%
19번 1
 
0.3%
대교상회 1
 
0.3%
㈜대한청과 1
 
0.3%
㈜청우농산 1
 
0.3%
Other values (303) 303
94.4%
2024-04-19T14:43:11.439575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 154
 
10.2%
회 106
 
7.0%
상 103
 
6.8%
농 76
 
5.0%
청 76
 
5.0%
과 68
 
4.5%
산 65
 
4.3%
대 32
 
2.1%
주 31
 
2.1%
성 30
 
2.0%
Other values (192) 765
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1256
83.4%
Other Symbol 154
 
10.2%
Decimal Number 47
 
3.1%
Open Punctuation 18
 
1.2%
Close Punctuation 18
 
1.2%
Space Separator 11
 
0.7%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 106
 
8.4%
상 103
 
8.2%
농 76
 
6.1%
청 76
 
6.1%
과 68
 
5.4%
산 65
 
5.2%
대 32
 
2.5%
주 31
 
2.5%
성 30
 
2.4%
유 30
 
2.4%
Other values (178) 639
50.9%
Decimal Number
ValueCountFrequency (%)
1 18
38.3%
0 8
17.0%
5 6
 
12.8%
2 5
 
10.6%
4 3
 
6.4%
7 2
 
4.3%
9 2
 
4.3%
3 2
 
4.3%
8 1
 
2.1%
Other Symbol
ValueCountFrequency (%)
㈜ 154
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1410
93.6%
Common 96
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 154
 
10.9%
회 106
 
7.5%
상 103
 
7.3%
농 76
 
5.4%
청 76
 
5.4%
과 68
 
4.8%
산 65
 
4.6%
대 32
 
2.3%
주 31
 
2.2%
성 30
 
2.1%
Other values (179) 669
47.4%
Common
ValueCountFrequency (%)
( 18
18.8%
1 18
18.8%
) 18
18.8%
11
11.5%
0 8
8.3%
5 6
 
6.2%
2 5
 
5.2%
4 3
 
3.1%
7 2
 
2.1%
9 2
 
2.1%
Other values (3) 5
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1256
83.4%
None 154
 
10.2%
ASCII 96
 
6.4%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 154
100.0%
Hangul
ValueCountFrequency (%)
회 106
 
8.4%
상 103
 
8.2%
농 76
 
6.1%
청 76
 
6.1%
과 68
 
5.4%
산 65
 
5.2%
대 32
 
2.5%
주 31
 
2.5%
성 30
 
2.4%
유 30
 
2.4%
Other values (178) 639
50.9%
ASCII
ValueCountFrequency (%)
( 18
18.8%
1 18
18.8%
) 18
18.8%
11
11.5%
0 8
8.3%
5 6
 
6.2%
2 5
 
5.2%
4 3
 
3.1%
7 2
 
2.1%
9 2
 
2.1%
Other values (3) 5
 
5.2%

사무실번호
Text

MISSING 

Distinct228
Distinct (%)98.3%
Missing79
Missing (%)25.4%
Memory size2.6 KiB
2024-04-19T14:43:11.703451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.931034
Min length2

Characters and Unicode

Total characters2768
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)96.6%

Sample

1st row053-311-2008
2nd row053-311-2233
3rd row053-312-6742
4th row053-313-0761
5th row053-313-0270
ValueCountFrequency (%)
053-312-7787 2
 
0.9%
053-326-5061 2
 
0.9%
053-311-1245 2
 
0.9%
053-311-8785 1
 
0.4%
053-311-8877 1
 
0.4%
053-312-3754 1
 
0.4%
053-311-0074 1
 
0.4%
053-314-8935 1
 
0.4%
053-314-8212 1
 
0.4%
053-254-5089 1
 
0.4%
Other values (217) 217
94.3%
2024-04-19T14:43:12.066932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 535
19.3%
- 460
16.6%
1 367
13.3%
0 352
12.7%
5 349
12.6%
2 185
 
6.7%
7 125
 
4.5%
8 111
 
4.0%
4 110
 
4.0%
6 88
 
3.2%
Other values (3) 86
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2303
83.2%
Dash Punctuation 460
 
16.6%
Space Separator 5
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 535
23.2%
1 367
15.9%
0 352
15.3%
5 349
15.2%
2 185
 
8.0%
7 125
 
5.4%
8 111
 
4.8%
4 110
 
4.8%
6 88
 
3.8%
9 81
 
3.5%
Space Separator
ValueCountFrequency (%)
3
60.0%
　 2
40.0%
Dash Punctuation
ValueCountFrequency (%)
- 460
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2768
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 535
19.3%
- 460
16.6%
1 367
13.3%
0 352
12.7%
5 349
12.6%
2 185
 
6.7%
7 125
 
4.5%
8 111
 
4.0%
4 110
 
4.0%
6 88
 
3.2%
Other values (3) 86
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2766
99.9%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 535
19.3%
- 460
16.6%
1 367
13.3%
0 352
12.7%
5 349
12.6%
2 185
 
6.7%
7 125
 
4.5%
8 111
 
4.0%
4 110
 
4.0%
6 88
 
3.2%
Other values (2) 84
 
3.0%
None
ValueCountFrequency (%)
　 2
100.0%

거래법인
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
효성청과
77 
대양청과
73 
중앙청과
57 
북대구농협
47 
원예농협
38 

Length

Max length7
Median length4
Mean length4.3344051
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
효성청과 77
24.8%
대양청과 73
23.5%
중앙청과 57
18.3%
북대구농협 47
15.1%
원예농협 38
12.2%
신흥산업(주) 19
 
6.1%

Length

2024-04-19T14:43:12.200618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:43:12.321456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
효성청과 77
24.8%
대양청과 73
23.5%
중앙청과 57
18.3%
북대구농협 47
15.1%
원예농협 38
12.2%
신흥산업(주 19
 
6.1%

취급부류
Categorical

Distinct6
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
과채
142 
과일
86 
엽채
51 
축산
19 
서류
 
11

Length

Max length3
Median length2
Mean length2.0064309
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row과일
2nd row과일
3rd row과일
4th row과일
5th row과채

Common Values

ValueCountFrequency (%)
과채 142
45.7%
과일 86
27.7%
엽채 51
 
16.4%
축산 19
 
6.1%
서류 11
 
3.5%
과채 2
 
0.6%

Length

2024-04-19T14:43:12.459033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:43:12.569210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
과채 144
46.3%
과일 86
27.7%
엽채 51
 
16.4%
축산 19
 
6.1%
서류 11
 
3.5%

Interactions

2024-04-19T14:43:08.800255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T14:43:12.653898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법인순번중도매인거래법인취급부류
법인1.0000.3170.0841.0000.658
순번0.3171.0000.0000.3400.307
중도매인0.0840.0001.0000.0000.000
거래법인1.0000.3400.0001.0000.849
취급부류0.6580.3070.0000.8491.000
2024-04-19T14:43:12.750206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
중도매인법인거래법인취급부류
중도매인1.0000.0230.0000.000
법인0.0231.0000.9980.467
거래법인0.0000.9981.0000.469
취급부류0.0000.4670.4691.000
2024-04-19T14:43:12.839697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번법인중도매인거래법인취급부류
순번1.0000.1650.0000.1850.165
법인0.1651.0000.0230.9980.467
중도매인0.0000.0231.0000.0000.000
거래법인0.1850.9980.0001.0000.469
취급부류0.1650.4670.0000.4691.000

Missing values

2024-04-19T14:43:08.925230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:43:09.046974image/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

법인순번허가번호중도매인상호사무실번호거래법인취급부류
0농협북대구공판장11996-1-0277전**대교상회053-311-2008북대구농협과일
1농협북대구공판장21996-1-0296배**만평상회053-311-2233북대구농협과일
2농협북대구공판장32000-1-0757허**경북상회053-312-6742북대구농협과일
3농협북대구공판장42000-1-0761경**우리상회053-313-0761북대구농협과일
4농협북대구공판장52003-1-0795여**성주상회053-313-0270북대구농협과채
5농협북대구공판장62004-1-0808김**㈜비케이푸드시스템053-311-9666북대구농협과채
6농협북대구공판장72004-1-0810권**㈜세운청과053-311-4466북대구농협과채
7농협북대구공판장82005-1-0824이**영남농산053-312-1387북대구농협과일
8농협북대구공판장92007-1-0842최**㈜한국농산푸드053-311-3695북대구농협과일
9농협북대구공판장102007-1-0869공**㈜진주농산 농업회사법인053-312-2772북대구농협과채
법인순번허가번호중도매인상호사무실번호거래법인취급부류
301축산부류 (신흥산업㈜)102022-03-09정**9번<NA>신흥산업(주)축산
302축산부류 (신흥산업㈜)112022-03-10김**20번<NA>신흥산업(주)축산
303축산부류 (신흥산업㈜)122022-03-11김**101번<NA>신흥산업(주)축산
304축산부류 (신흥산업㈜)132022-03-12배**107번<NA>신흥산업(주)축산
305축산부류 (신흥산업㈜)142022-03-13정**104번<NA>신흥산업(주)축산
306축산부류 (신흥산업㈜)152020-03-01이**112번<NA>신흥산업(주)축산
307축산부류 (신흥산업㈜)162020-03-02윤**10번<NA>신흥산업(주)축산
308축산부류 (신흥산업㈜)172020-03-03박**45번<NA>신흥산업(주)축산
309축산부류 (신흥산업㈜)182020-03-04황**3번<NA>신흥산업(주)축산
310축산부류 (신흥산업㈜)192020-03-05배**117번<NA>신흥산업(주)축산