Overview

Dataset statistics

Number of variables11
Number of observations36
Missing cells14
Missing cells (%)3.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory93.7 B

Variable types

Categorical5
Text4
Numeric2

Dataset

Description강원도 삼척시의 골재 및 토석 채취 현황(허가 업체, 연락처, 주소, 용도, 허가면적, 허가량, 허가기간)을 제공합니다.
Author강원특별자치도 삼척시
URLhttps://www.data.go.kr/data/15069516/fileData.do

Alerts

소재 시군 has constant value ""Constant
소재 읍면동 is highly overall correlated with 소재 리High correlation
소재 리 is highly overall correlated with 허가면적(제곱미터) and 1 other fieldsHigh correlation
허가면적(제곱미터) is highly overall correlated with 허가량(천 세제곱미터) and 1 other fieldsHigh correlation
허가량(천 세제곱미터) is highly overall correlated with 허가면적(제곱미터)High correlation
연락처 has 14 (38.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 20:34:33.349380
Analysis finished2023-12-12 20:34:34.353355
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종류
Categorical

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
골재
14 
석재
12 
토석
10 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
골재 14
38.9%
석재 12
33.3%
토석 10
27.8%

Length

2023-12-13T05:34:34.415419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:34:34.524890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
골재 14
38.9%
석재 12
33.3%
토석 10
27.8%

수허가자 상호
Text

Distinct22
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-13T05:34:34.696222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.0277778
Min length3

Characters and Unicode

Total characters289
Distinct characters63
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)38.9%

Sample

1st row㈜다성실업 대표 신용석
2nd row삼표자원개발㈜
3rd row주식회사 가곡
4th row서평산업
5th row한서개발
ValueCountFrequency (%)
대표 10
16.4%
㈜다성실업 6
 
9.8%
신용석 6
 
9.8%
쌍용씨앤이㈜ 4
 
6.6%
삼표자원개발㈜ 4
 
6.6%
서평산업 2
 
3.3%
가곡 2
 
3.3%
주식회사 2
 
3.3%
㈜석용산업개발 2
 
3.3%
김태진 2
 
3.3%
Other values (18) 21
34.4%
2023-12-13T05:34:35.012860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 27
 
9.3%
25
 
8.7%
업 16
 
5.5%
표 14
 
4.8%
용 12
 
4.2%
개 12
 
4.2%
발 12
 
4.2%
대 12
 
4.2%
석 9
 
3.1%
성 8
 
2.8%
Other values (53) 142
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 233
80.6%
Other Symbol 27
 
9.3%
Space Separator 25
 
8.7%
Close Punctuation 2
 
0.7%
Open Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 16
 
6.9%
표 14
 
6.0%
용 12
 
5.2%
개 12
 
5.2%
발 12
 
5.2%
대 12
 
5.2%
석 9
 
3.9%
성 8
 
3.4%
산 8
 
3.4%
신 6
 
2.6%
Other values (49) 124
53.2%
Other Symbol
ValueCountFrequency (%)
㈜ 27
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 260
90.0%
Common 29
 
10.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 27
 
10.4%
업 16
 
6.2%
표 14
 
5.4%
용 12
 
4.6%
개 12
 
4.6%
발 12
 
4.6%
대 12
 
4.6%
석 9
 
3.5%
성 8
 
3.1%
산 8
 
3.1%
Other values (50) 130
50.0%
Common
ValueCountFrequency (%)
25
86.2%
) 2
 
6.9%
( 2
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 233
80.6%
ASCII 29
 
10.0%
None 27
 
9.3%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 27
100.0%
ASCII
ValueCountFrequency (%)
25
86.2%
) 2
 
6.9%
( 2
 
6.9%
Hangul
ValueCountFrequency (%)
업 16
 
6.9%
표 14
 
6.0%
용 12
 
5.2%
개 12
 
5.2%
발 12
 
5.2%
대 12
 
5.2%
석 9
 
3.9%
성 8
 
3.4%
산 8
 
3.4%
신 6
 
2.6%
Other values (49) 124
53.2%

연락처
Text

MISSING 

Distinct15
Distinct (%)68.2%
Missing14
Missing (%)38.9%
Memory size420.0 B
2023-12-13T05:34:35.183271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters264
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

Unique10 ?
Unique (%)45.5%

Sample

1st row033-572-6441
2nd row033-571-7219
3rd row033-576-9991
4th row033-572-8456
5th row033-521-2003
ValueCountFrequency (%)
033-572-6441 4
18.2%
033-571-7219 2
 
9.1%
033-576-9991 2
 
9.1%
033-572-8456 2
 
9.1%
033-521-2003 2
 
9.1%
033-572-3665 1
 
4.5%
033-572-8641 1
 
4.5%
033-572-7600 1
 
4.5%
033-575-2123 1
 
4.5%
033-552-2788 1
 
4.5%
Other values (5) 5
22.7%
2023-12-13T05:34:35.468564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 50
18.9%
- 44
16.7%
0 35
13.3%
5 29
11.0%
7 23
8.7%
2 22
8.3%
1 19
 
7.2%
4 14
 
5.3%
6 13
 
4.9%
9 8
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 220
83.3%
Dash Punctuation 44
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 50
22.7%
0 35
15.9%
5 29
13.2%
7 23
10.5%
2 22
10.0%
1 19
 
8.6%
4 14
 
6.4%
6 13
 
5.9%
9 8
 
3.6%
8 7
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 264
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 50
18.9%
- 44
16.7%
0 35
13.3%
5 29
11.0%
7 23
8.7%
2 22
8.3%
1 19
 
7.2%
4 14
 
5.3%
6 13
 
4.9%
9 8
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 264
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 50
18.9%
- 44
16.7%
0 35
13.3%
5 29
11.0%
7 23
8.7%
2 22
8.3%
1 19
 
7.2%
4 14
 
5.3%
6 13
 
4.9%
9 8
 
3.0%

소재 시군
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
삼척
36 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
삼척 36
100.0%

Length

2023-12-13T05:34:35.599195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:34:35.699033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
삼척 36
100.0%

소재 읍면동
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size420.0 B
원덕
15 
조비동
7 
근덕
7 
미로
4 
하장
2 

Length

Max length3
Median length2
Mean length2.2222222
Min length2

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row원덕
2nd row조비동
3rd row원덕
4th row원덕
5th row미로

Common Values

ValueCountFrequency (%)
원덕 15
41.7%
조비동 7
19.4%
근덕 7
19.4%
미로 4
 
11.1%
하장 2
 
5.6%
적노동 1
 
2.8%

Length

2023-12-13T05:34:35.797820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:34:35.927221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원덕 15
41.7%
조비동 7
19.4%
근덕 7
19.4%
미로 4
 
11.1%
하장 2
 
5.6%
적노동 1
 
2.8%

소재 리
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
산양
13 
<NA>
8 
하맹방리
4 
상거노리
2 
동막
2 
Other values (4)
7 

Length

Max length4
Median length2
Mean length2.7777778
Min length2

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row산양
2nd row<NA>
3rd row산양
4th row산양
5th row상거노리

Common Values

ValueCountFrequency (%)
산양 13
36.1%
<NA> 8
22.2%
하맹방리 4
 
11.1%
상거노리 2
 
5.6%
동막 2
 
5.6%
노경 2
 
5.6%
활기 2
 
5.6%
추동 2
 
5.6%
매원 1
 
2.8%

Length

2023-12-13T05:34:36.068477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:34:36.236090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
산양 13
36.1%
na 8
22.2%
하맹방리 4
 
11.1%
상거노리 2
 
5.6%
동막 2
 
5.6%
노경 2
 
5.6%
활기 2
 
5.6%
추동 2
 
5.6%
매원 1
 
2.8%

소재 지번
Text

Distinct24
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-13T05:34:36.483679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length8.3888889
Min length3

Characters and Unicode

Total characters302
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)38.9%

Sample

1st row산201번지외5필
2nd row산36외3필
3rd row741-1
4th row698
5th row395-1번지외21필
ValueCountFrequency (%)
외 4
 
7.1%
산201번지외5필 3
 
5.4%
산36외3필 3
 
5.4%
1필 3
 
5.4%
395-1번지외21필 2
 
3.6%
13필 2
 
3.6%
5필 2
 
3.6%
741-1 2
 
3.6%
698 2
 
3.6%
2필 2
 
3.6%
Other values (25) 31
55.4%
2023-12-13T05:34:36.963315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 40
13.2%
3 32
10.6%
필 30
9.9%
외 29
9.6%
산 26
8.6%
2 22
 
7.3%
21
 
7.0%
지 19
 
6.3%
번 17
 
5.6%
5 10
 
3.3%
Other values (8) 56
18.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 149
49.3%
Other Letter 122
40.4%
Space Separator 21
 
7.0%
Dash Punctuation 10
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 40
26.8%
3 32
21.5%
2 22
14.8%
5 10
 
6.7%
0 10
 
6.7%
6 10
 
6.7%
8 9
 
6.0%
7 6
 
4.0%
9 6
 
4.0%
4 4
 
2.7%
Other Letter
ValueCountFrequency (%)
필 30
24.6%
외 29
23.8%
산 26
21.3%
지 19
15.6%
번 17
13.9%
회 1
 
0.8%
Space Separator
ValueCountFrequency (%)
21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 180
59.6%
Hangul 122
40.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 40
22.2%
3 32
17.8%
2 22
12.2%
21
11.7%
5 10
 
5.6%
0 10
 
5.6%
6 10
 
5.6%
- 10
 
5.6%
8 9
 
5.0%
7 6
 
3.3%
Other values (2) 10
 
5.6%
Hangul
ValueCountFrequency (%)
필 30
24.6%
외 29
23.8%
산 26
21.3%
지 19
15.6%
번 17
13.9%
회 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 180
59.6%
Hangul 122
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 40
22.2%
3 32
17.8%
2 22
12.2%
21
11.7%
5 10
 
5.6%
0 10
 
5.6%
6 10
 
5.6%
- 10
 
5.6%
8 9
 
5.0%
7 6
 
3.3%
Other values (2) 10
 
5.6%
Hangul
ValueCountFrequency (%)
필 30
24.6%
외 29
23.8%
산 26
21.3%
지 19
15.6%
번 17
13.9%
회 1
 
0.8%

용도
Categorical

Distinct4
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
토목용
16 
쇄골재용 토목용
11 
토목용 쇄골재용
5 
토목용 쇄골재용 조경용
4 

Length

Max length12
Median length8
Mean length6.2222222
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row쇄골재용 토목용
2nd row쇄골재용 토목용
3rd row쇄골재용 토목용
4th row쇄골재용 토목용
5th row토목용

Common Values

ValueCountFrequency (%)
토목용 16
44.4%
쇄골재용 토목용 11
30.6%
토목용 쇄골재용 5
 
13.9%
토목용 쇄골재용 조경용 4
 
11.1%

Length

2023-12-13T05:34:37.140265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:34:37.273983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토목용 36
60.0%
쇄골재용 20
33.3%
조경용 4
 
6.7%

허가면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60373.917
Minimum2876
Maximum437015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-13T05:34:37.427435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2876
5-th percentile4083
Q15200
median18733
Q371766
95-th percentile241800.5
Maximum437015
Range434139
Interquartile range (IQR)66566

Descriptive statistics

Standard deviation103190.34
Coefficient of variation (CV)1.7091874
Kurtosis8.9211125
Mean60373.917
Median Absolute Deviation (MAD)14036.5
Skewness2.9534823
Sum2173461
Variance1.0648246 × 1010
MonotonicityNot monotonic
2023-12-13T05:34:37.600584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
5000 2
 
5.6%
176729 2
 
5.6%
7781 2
 
5.6%
437015 2
 
5.6%
5200 2
 
5.6%
4978 2
 
5.6%
13366 2
 
5.6%
71766 2
 
5.6%
94604 2
 
5.6%
94329 2
 
5.6%
Other values (12) 16
44.4%
ValueCountFrequency (%)
2876 1
2.8%
4083 2
5.6%
4415 1
2.8%
4978 2
5.6%
5000 2
5.6%
5200 2
5.6%
7781 2
5.6%
9054 1
2.8%
9990 1
2.8%
13366 2
5.6%
ValueCountFrequency (%)
437015 2
5.6%
176729 2
5.6%
94604 2
5.6%
94329 2
5.6%
71766 2
5.6%
71471 1
2.8%
41428 2
5.6%
33670 1
2.8%
30311 1
2.8%
24184 1
2.8%

허가량(천 세제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean731.47222
Minimum7
Maximum4446
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-13T05:34:37.728811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile33.25
Q185
median170.5
Q31229.5
95-th percentile2317
Maximum4446
Range4439
Interquartile range (IQR)1144.5

Descriptive statistics

Standard deviation971.87905
Coefficient of variation (CV)1.3286616
Kurtosis4.8217289
Mean731.47222
Median Absolute Deviation (MAD)128.5
Skewness1.9513069
Sum26333
Variance944548.88
MonotonicityNot monotonic
2023-12-13T05:34:37.852405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1499 2
 
5.6%
996 2
 
5.6%
100 2
 
5.6%
108 2
 
5.6%
185 2
 
5.6%
65 2
 
5.6%
95 2
 
5.6%
73 2
 
5.6%
2413 1
 
2.8%
1629 1
 
2.8%
Other values (18) 18
50.0%
ValueCountFrequency (%)
7 1
2.8%
22 1
2.8%
37 1
2.8%
47 1
2.8%
54 1
2.8%
65 2
5.6%
73 2
5.6%
89 1
2.8%
95 2
5.6%
99 1
2.8%
ValueCountFrequency (%)
4446 1
2.8%
2413 1
2.8%
2285 1
2.8%
2048 1
2.8%
1630 1
2.8%
1629 1
2.8%
1499 2
5.6%
1306 1
2.8%
1204 1
2.8%
1083 1
2.8%

허가기간(최초허가일-종료일)
Text

Distinct31
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-13T05:34:38.063698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length21.666667
Min length21

Characters and Unicode

Total characters780
Distinct characters15
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

Unique26 ?
Unique (%)72.2%

Sample

1st row2013-05-01-2021-05-31
2nd row2017-03-05-2022-12-31
3rd row2017-01-02-2021-12-31
4th row2020-12-21-2022-07-31
5th row2021-06-17-2024-05-31(연장)
ValueCountFrequency (%)
2018-11-08-2024-04-30 2
 
5.6%
2011-07-01-2024-05-31 2
 
5.6%
2019-08-02-2023-07-31 2
 
5.6%
2001-07-05-2024-05-31 2
 
5.6%
2016-12-09-2024-11-30 2
 
5.6%
2012-08-21-2030-06-30 1
 
2.8%
2020-12-21-2022-07-31(연장 1
 
2.8%
2021-06-17-2023-05-31 1
 
2.8%
2020-11-03-2022-09-30 1
 
2.8%
2022-02-14-2022-12-31 1
 
2.8%
Other values (21) 21
58.3%
2023-12-13T05:34:38.449075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 180
23.1%
0 165
21.2%
2 155
19.9%
1 116
14.9%
3 45
 
5.8%
5 23
 
2.9%
4 22
 
2.8%
7 20
 
2.6%
8 11
 
1.4%
6 11
 
1.4%
Other values (5) 32
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 576
73.8%
Dash Punctuation 180
 
23.1%
Other Letter 12
 
1.5%
Open Punctuation 6
 
0.8%
Close Punctuation 6
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 165
28.6%
2 155
26.9%
1 116
20.1%
3 45
 
7.8%
5 23
 
4.0%
4 22
 
3.8%
7 20
 
3.5%
8 11
 
1.9%
6 11
 
1.9%
9 8
 
1.4%
Other Letter
ValueCountFrequency (%)
연 6
50.0%
장 6
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 180
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 768
98.5%
Hangul 12
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
- 180
23.4%
0 165
21.5%
2 155
20.2%
1 116
15.1%
3 45
 
5.9%
5 23
 
3.0%
4 22
 
2.9%
7 20
 
2.6%
8 11
 
1.4%
6 11
 
1.4%
Other values (3) 20
 
2.6%
Hangul
ValueCountFrequency (%)
연 6
50.0%
장 6
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 768
98.5%
Hangul 12
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 180
23.4%
0 165
21.5%
2 155
20.2%
1 116
15.1%
3 45
 
5.9%
5 23
 
3.0%
4 22
 
2.9%
7 20
 
2.6%
8 11
 
1.4%
6 11
 
1.4%
Other values (3) 20
 
2.6%
Hangul
ValueCountFrequency (%)
연 6
50.0%
장 6
50.0%

Interactions

2023-12-13T05:34:33.952820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:34:33.794241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:34:34.031642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:34:33.871722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:34:38.552891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종류수허가자 상호연락처소재 읍면동소재 리소재 지번용도허가면적(제곱미터)허가량(천 세제곱미터)허가기간(최초허가일-종료일)
종류1.0000.3670.7510.0000.3510.4300.4030.2250.3620.000
수허가자 상호0.3671.0000.9980.9761.0000.9820.8970.9680.3050.989
연락처0.7510.9981.0001.0001.0000.9980.8360.9870.0001.000
소재 읍면동0.0000.9761.0001.0001.0001.0000.3700.5380.0000.838
소재 리0.3511.0001.0001.0001.0001.0000.6230.9120.0001.000
소재 지번0.4300.9820.9981.0001.0001.0000.9641.0000.9420.939
용도0.4030.8970.8360.3700.6230.9641.0000.4060.6300.958
허가면적(제곱미터)0.2250.9680.9870.5380.9121.0000.4061.0000.8231.000
허가량(천 세제곱미터)0.3620.3050.0000.0000.0000.9420.6300.8231.0000.000
허가기간(최초허가일-종료일)0.0000.9891.0000.8381.0000.9390.9581.0000.0001.000
2023-12-13T05:34:38.662546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종류용도소재 읍면동소재 리
종류1.0000.3860.0000.190
용도0.3861.0000.2300.274
소재 읍면동0.0000.2301.0000.913
소재 리0.1900.2740.9131.000
2023-12-13T05:34:38.749895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가면적(제곱미터)허가량(천 세제곱미터)종류소재 읍면동소재 리용도
허가면적(제곱미터)1.0000.7040.1820.3800.5710.338
허가량(천 세제곱미터)0.7041.0000.2350.0000.0000.462
종류0.1820.2351.0000.0000.1900.386
소재 읍면동0.3800.0000.0001.0000.9130.230
소재 리0.5710.0000.1900.9131.0000.274
용도0.3380.4620.3860.2300.2741.000

Missing values

2023-12-13T05:34:34.137003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:34:34.294573image/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

종류수허가자 상호연락처소재 시군소재 읍면동소재 리소재 지번용도허가면적(제곱미터)허가량(천 세제곱미터)허가기간(최초허가일-종료일)
0골재㈜다성실업 대표 신용석033-572-6441삼척원덕산양산201번지외5필쇄골재용 토목용500014992013-05-01-2021-05-31
1골재삼표자원개발㈜033-571-7219삼척조비동<NA>산36외3필쇄골재용 토목용13366952017-03-05-2022-12-31
2골재주식회사 가곡033-576-9991삼척원덕산양741-1쇄골재용 토목용40831002017-01-02-2021-12-31
3골재서평산업033-572-8456삼척원덕산양698쇄골재용 토목용212541082020-12-21-2022-07-31
4골재한서개발033-521-2003삼척미로상거노리395-1번지외21필토목용162121852021-06-17-2024-05-31(연장)
5골재㈜월드산업033-572-3665삼척근덕하맹방리355-5번지 외 5필토목용44151562020-07-03-2021-06-30
6골재㈜나눔033-572-8641삼척근덕하맹방리323번지 외 8필토목용9054372019-06-10-2021-05-15
7토석㈜다성실업 대표 신용석033-572-6441삼척원덕산양산201번지외5필토목용 쇄골재용 조경용414288732001-07-05-2024-05-31
8토석㈜다성실업 대표 신용석033-572-6441삼척원덕산양산203번지외2필토목용 쇄골재용 조경용9432922852011-07-01-2024-05-31
9토석동막개발㈜ 김종환033-572-7600삼척근덕동막산130번지외12필토목용 쇄골재용17672920482012-09-01-2030-06-30
종류수허가자 상호연락처소재 시군소재 읍면동소재 리소재 지번용도허가면적(제곱미터)허가량(천 세제곱미터)허가기간(최초허가일-종료일)
26석재㈜다성실업 대표 신용석<NA>삼척원덕산양산201번지외 5필토목용 쇄골재용 조경용4142814992001-07-05-2024-05-31
27석재㈜다성실업 대표 신용석<NA>삼척원덕산양산203번지외 2필토목용 쇄골재용 조경용9432944462011-07-01-2024-05-31
28석재대득산업주식회사 대표 이성철<NA>삼척원덕산양산267번지외2필토목용 쇄골재용7176612042011-12-14-2024-12-31
29석재㈜석용산업개발 대표 윤종현<NA>삼척원덕노경산183외 11필토목용946049962016-12-08-2024-12-31
30석재쌍용씨앤이㈜<NA>삼척조비동<NA>산133번지외1필토목용4978892012-05-07-2024-11-07
31석재쌍용씨앤이㈜<NA>삼척미로활기산178외 1필토목용5200732016-12-09-2024-11-30
32석재삼표자원개발㈜ 김태진<NA>삼척조비동<NA>산36외2필쇄골재용 토목용24184992015-07-15-2023-12-31
33석재㈜청암개발<NA>삼척원덕산양산321외 2필토목용7147113062015-05-04-2022-05-31(연장)
34석재태원광업㈜<NA>삼척하장추동산108-1토목용7781652019-08-02-2023-07-31
35석재삼광산업개발㈜<NA>삼척근덕매원산64 외 1필토목용30311472022-04-08-2024-06-30