Overview

Dataset statistics

Number of variables10
Number of observations146
Missing cells8
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.7 KiB
Average record size in memory81.9 B

Variable types

Text8
DateTime1
Numeric1

Dataset

Description강원특별자치도 속초시 건축업체 현황에 관한 데이터입니다.건축업체명, 대표자 이름, 업체등록일자, 업종, 등록번호, 등록일, 주력사업, 우편번호, 영업소재지, 전화번호를 제공하며공공데이터 제공 신청에 의해 개방하는 데이터입니다.
Author강원특별자치도 속초시
URLhttps://www.data.go.kr/data/15126756/fileData.do

Alerts

전화번호 has 8 (5.5%) missing valuesMissing
업체명 has unique valuesUnique
등록번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 15:09:41.294564
Analysis finished2024-03-14 15:09:43.081669
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

UNIQUE 

Distinct146
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-15T00:09:43.942968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length6.6917808
Min length3

Characters and Unicode

Total characters977
Distinct characters174
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

Unique146 ?
Unique (%)100.0%

Sample

1st row(주)고원
2nd row(주)국제산업
3rd row(주)국토조경
4th row(주)금강엔지니어링
5th row(주)녹색라인
ValueCountFrequency (%)
주)고원 1
 
0.7%
유일설비 1
 
0.7%
속초린나이 1
 
0.7%
영동건축설비 1
 
0.7%
수리종합설비 1
 
0.7%
수복종합설비 1
 
0.7%
신아건설(주 1
 
0.7%
안전가스설비 1
 
0.7%
에스에이치(sh)종합설비(주 1
 
0.7%
에스제이건설(주 1
 
0.7%
Other values (136) 136
93.2%
2024-03-15T00:09:45.423373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 80
 
8.2%
설 73
 
7.5%
( 72
 
7.4%
) 72
 
7.4%
건 43
 
4.4%
비 38
 
3.9%
이 19
 
1.9%
스 18
 
1.8%
대 18
 
1.8%
합 16
 
1.6%
Other values (164) 528
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 825
84.4%
Open Punctuation 72
 
7.4%
Close Punctuation 72
 
7.4%
Uppercase Letter 5
 
0.5%
Decimal Number 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 80
 
9.7%
설 73
 
8.8%
건 43
 
5.2%
비 38
 
4.6%
이 19
 
2.3%
스 18
 
2.2%
대 18
 
2.2%
합 16
 
1.9%
사 16
 
1.9%
종 14
 
1.7%
Other values (155) 490
59.4%
Uppercase Letter
ValueCountFrequency (%)
S 1
20.0%
H 1
20.0%
E 1
20.0%
N 1
20.0%
G 1
20.0%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 825
84.4%
Common 147
 
15.0%
Latin 5
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 80
 
9.7%
설 73
 
8.8%
건 43
 
5.2%
비 38
 
4.6%
이 19
 
2.3%
스 18
 
2.2%
대 18
 
2.2%
합 16
 
1.9%
사 16
 
1.9%
종 14
 
1.7%
Other values (155) 490
59.4%
Latin
ValueCountFrequency (%)
S 1
20.0%
H 1
20.0%
E 1
20.0%
N 1
20.0%
G 1
20.0%
Common
ValueCountFrequency (%)
( 72
49.0%
) 72
49.0%
1 2
 
1.4%
9 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 825
84.4%
ASCII 152
 
15.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 80
 
9.7%
설 73
 
8.8%
건 43
 
5.2%
비 38
 
4.6%
이 19
 
2.3%
스 18
 
2.2%
대 18
 
2.2%
합 16
 
1.9%
사 16
 
1.9%
종 14
 
1.7%
Other values (155) 490
59.4%
ASCII
ValueCountFrequency (%)
( 72
47.4%
) 72
47.4%
1 2
 
1.3%
S 1
 
0.7%
H 1
 
0.7%
E 1
 
0.7%
N 1
 
0.7%
G 1
 
0.7%
9 1
 
0.7%

대표자
Text

Distinct142
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-15T00:09:46.856832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9863014
Min length2

Characters and Unicode

Total characters436
Distinct characters120
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique138 ?
Unique (%)94.5%

Sample

1st row김청재
2nd row최규동
3rd row조주현
4th row김수자
5th row김주연
ValueCountFrequency (%)
최현숙 2
 
1.4%
이종균 2
 
1.4%
박복자 2
 
1.4%
이승준 2
 
1.4%
주재웅 1
 
0.7%
김성민 1
 
0.7%
유정인 1
 
0.7%
유상호 1
 
0.7%
추봉현 1
 
0.7%
원정용 1
 
0.7%
Other values (132) 132
90.4%
2024-03-15T00:09:48.711055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 29
 
6.7%
이 25
 
5.7%
박 17
 
3.9%
정 13
 
3.0%
최 13
 
3.0%
영 12
 
2.8%
용 11
 
2.5%
진 9
 
2.1%
종 9
 
2.1%
주 8
 
1.8%
Other values (110) 290
66.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 436
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 29
 
6.7%
이 25
 
5.7%
박 17
 
3.9%
정 13
 
3.0%
최 13
 
3.0%
영 12
 
2.8%
용 11
 
2.5%
진 9
 
2.1%
종 9
 
2.1%
주 8
 
1.8%
Other values (110) 290
66.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 436
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 29
 
6.7%
이 25
 
5.7%
박 17
 
3.9%
정 13
 
3.0%
최 13
 
3.0%
영 12
 
2.8%
용 11
 
2.5%
진 9
 
2.1%
종 9
 
2.1%
주 8
 
1.8%
Other values (110) 290
66.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 436
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 29
 
6.7%
이 25
 
5.7%
박 17
 
3.9%
정 13
 
3.0%
최 13
 
3.0%
영 12
 
2.8%
용 11
 
2.5%
진 9
 
2.1%
종 9
 
2.1%
주 8
 
1.8%
Other values (110) 290
66.5%

업체등록일자
Date

Distinct136
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1986-04-29 00:00:00
Maximum2024-02-23 00:00:00
2024-03-15T00:09:49.125704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:09:49.562202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업종
Text

Distinct69
Distinct (%)47.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-15T00:09:50.375291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length158
Median length101
Mean length40.993151
Min length7

Characters and Unicode

Total characters5985
Distinct characters89
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

Unique47 ?
Unique (%)32.2%

Sample

1st row금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업 금속구조물ㆍ창호ㆍ온실공사업(대업종전환)
2nd row금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업 금속구조물ㆍ창호ㆍ온실공사업(대업종전환)
3rd row조경식재ㆍ시설물공사업 조경식재공사업(대업종전환)
4th row승강기ㆍ삭도공사업 승강기설치공사업(대업종전환)
5th row도장ㆍ습식ㆍ방수ㆍ석공사업 지반조성ㆍ포장공사업 도장공사업(대업종전환) 포장공사업(대업종전환)
ValueCountFrequency (%)
가스ㆍ난방공사업 62
 
12.0%
제2종(대업종전환 61
 
11.8%
가스시설시공업 49
 
9.5%
난방시공업 45
 
8.7%
금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업 22
 
4.3%
금속구조물ㆍ창호ㆍ온실공사업(대업종전환 19
 
3.7%
철근ㆍ콘크리트공사업(대업종전환 18
 
3.5%
철근ㆍ콘크리트공사업 18
 
3.5%
제3종(대업종전환 18
 
3.5%
상ㆍ하수도설비공사업 16
 
3.1%
Other values (41) 187
36.3%
2024-03-15T00:09:51.669298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 638
 
10.7%
공 411
 
6.9%
369
 
6.2%
ㆍ 332
 
5.5%
사 317
 
5.3%
종 287
 
4.8%
) 236
 
3.9%
( 236
 
3.9%
환 193
 
3.2%
전 193
 
3.2%
Other values (79) 2773
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5050
84.4%
Space Separator 369
 
6.2%
Close Punctuation 236
 
3.9%
Open Punctuation 236
 
3.9%
Decimal Number 94
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 638
 
12.6%
공 411
 
8.1%
ㆍ 332
 
6.6%
사 317
 
6.3%
종 287
 
5.7%
환 193
 
3.8%
전 193
 
3.8%
대 193
 
3.8%
시 167
 
3.3%
설 142
 
2.8%
Other values (73) 2177
43.1%
Decimal Number
ValueCountFrequency (%)
2 70
74.5%
3 19
 
20.2%
1 5
 
5.3%
Space Separator
ValueCountFrequency (%)
369
100.0%
Close Punctuation
ValueCountFrequency (%)
) 236
100.0%
Open Punctuation
ValueCountFrequency (%)
( 236
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5050
84.4%
Common 935
 
15.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 638
 
12.6%
공 411
 
8.1%
ㆍ 332
 
6.6%
사 317
 
6.3%
종 287
 
5.7%
환 193
 
3.8%
전 193
 
3.8%
대 193
 
3.8%
시 167
 
3.3%
설 142
 
2.8%
Other values (73) 2177
43.1%
Common
ValueCountFrequency (%)
369
39.5%
) 236
25.2%
( 236
25.2%
2 70
 
7.5%
3 19
 
2.0%
1 5
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4718
78.8%
ASCII 935
 
15.6%
Compat Jamo 332
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 638
 
13.5%
공 411
 
8.7%
사 317
 
6.7%
종 287
 
6.1%
환 193
 
4.1%
전 193
 
4.1%
대 193
 
4.1%
시 167
 
3.5%
설 142
 
3.0%
스 125
 
2.6%
Other values (72) 2052
43.5%
ASCII
ValueCountFrequency (%)
369
39.5%
) 236
25.2%
( 236
25.2%
2 70
 
7.5%
3 19
 
2.0%
1 5
 
0.5%
Compat Jamo
ValueCountFrequency (%)
ㆍ 332
100.0%

등록번호
Text

UNIQUE 

Distinct146
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-15T00:09:52.569607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length148
Median length108
Mean length36.5
Min length11

Characters and Unicode

Total characters5329
Distinct characters63
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

Unique146 ?
Unique (%)100.0%

Sample

1st row속초2006-08-04 속초2006-08-04
2nd row광주북2017-07-06 광주북2017-07-06
3rd row속초2020-16-01 속초2020-16-01
4th row속초2014-22-01 속초2014-22-01
5th row춘천2017-05-03 춘천2017-14-02 춘천2017-05-03 춘천2017-14-02
ValueCountFrequency (%)
속초2006-08-04 2
 
0.5%
속초2017-27-07 2
 
0.5%
속초2019-09-01 2
 
0.5%
강원고성2015-11-01 2
 
0.5%
속초2021-07-02 2
 
0.5%
속초2012-27-02 2
 
0.5%
속초2021-27-01 2
 
0.5%
강원95-17-01 2
 
0.5%
속초2007-01-01 2
 
0.5%
속초2007-27-02 2
 
0.5%
Other values (252) 409
95.3%
2024-03-15T00:09:53.942838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1137
21.3%
- 867
16.3%
2 754
14.1%
1 591
11.1%
속 302
 
5.7%
초 302
 
5.7%
283
 
5.3%
7 166
 
3.1%
9 125
 
2.3%
3 111
 
2.1%
Other values (53) 691
13.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3243
60.9%
Other Letter 936
 
17.6%
Dash Punctuation 867
 
16.3%
Space Separator 283
 
5.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
속 302
32.3%
초 302
32.3%
강 74
 
7.9%
원 73
 
7.8%
양 32
 
3.4%
고 10
 
1.1%
가 9
 
1.0%
성 8
 
0.9%
스 8
 
0.9%
주 7
 
0.7%
Other values (41) 111
 
11.9%
Decimal Number
ValueCountFrequency (%)
0 1137
35.1%
2 754
23.3%
1 591
18.2%
7 166
 
5.1%
9 125
 
3.9%
3 111
 
3.4%
4 99
 
3.1%
6 91
 
2.8%
8 85
 
2.6%
5 84
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 867
100.0%
Space Separator
ValueCountFrequency (%)
283
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4393
82.4%
Hangul 936
 
17.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
속 302
32.3%
초 302
32.3%
강 74
 
7.9%
원 73
 
7.8%
양 32
 
3.4%
고 10
 
1.1%
가 9
 
1.0%
성 8
 
0.9%
스 8
 
0.9%
주 7
 
0.7%
Other values (41) 111
 
11.9%
Common
ValueCountFrequency (%)
0 1137
25.9%
- 867
19.7%
2 754
17.2%
1 591
13.5%
283
 
6.4%
7 166
 
3.8%
9 125
 
2.8%
3 111
 
2.5%
4 99
 
2.3%
6 91
 
2.1%
Other values (2) 169
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4393
82.4%
Hangul 936
 
17.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1137
25.9%
- 867
19.7%
2 754
17.2%
1 591
13.5%
283
 
6.4%
7 166
 
3.8%
9 125
 
2.8%
3 111
 
2.5%
4 99
 
2.3%
6 91
 
2.1%
Other values (2) 169
 
3.8%
Hangul
ValueCountFrequency (%)
속 302
32.3%
초 302
32.3%
강 74
 
7.9%
원 73
 
7.8%
양 32
 
3.4%
고 10
 
1.1%
가 9
 
1.0%
성 8
 
0.9%
스 8
 
0.9%
주 7
 
0.7%
Other values (41) 111
 
11.9%

등록일
Text

Distinct140
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-15T00:09:55.063379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length131
Median length98
Mean length30.719178
Min length10

Characters and Unicode

Total characters4485
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)91.8%

Sample

1st row2006-03-27 2006-03-27
2nd row2017-09-19 2017-09-19
3rd row2020-10-30 2020-10-30
4th row2014-01-20 2014-01-20
5th row2017-07-20 2017-07-20 2017-07-20 2017-07-20
ValueCountFrequency (%)
1994-12-15 8
 
1.9%
2017-07-20 6
 
1.4%
2017-02-13 5
 
1.2%
1995-11-15 5
 
1.2%
2004-06-21 5
 
1.2%
2020-08-14 5
 
1.2%
2020-03-02 5
 
1.2%
2005-02-21 5
 
1.2%
1997-05-27 4
 
1.0%
2009-03-16 4
 
1.0%
Other values (201) 369
87.6%
2024-03-15T00:09:56.602724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1044
23.3%
- 842
18.8%
2 776
17.3%
1 644
14.4%
275
 
6.1%
9 202
 
4.5%
3 166
 
3.7%
5 118
 
2.6%
7 111
 
2.5%
8 109
 
2.4%
Other values (2) 198
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3368
75.1%
Dash Punctuation 842
 
18.8%
Space Separator 275
 
6.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1044
31.0%
2 776
23.0%
1 644
19.1%
9 202
 
6.0%
3 166
 
4.9%
5 118
 
3.5%
7 111
 
3.3%
8 109
 
3.2%
4 106
 
3.1%
6 92
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 842
100.0%
Space Separator
ValueCountFrequency (%)
275
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4485
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1044
23.3%
- 842
18.8%
2 776
17.3%
1 644
14.4%
275
 
6.1%
9 202
 
4.5%
3 166
 
3.7%
5 118
 
2.6%
7 111
 
2.5%
8 109
 
2.4%
Other values (2) 198
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4485
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1044
23.3%
- 842
18.8%
2 776
17.3%
1 644
14.4%
275
 
6.1%
9 202
 
4.5%
3 166
 
3.7%
5 118
 
2.6%
7 111
 
2.5%
8 109
 
2.4%
Other values (2) 198
 
4.4%

주력사업
Text

Distinct144
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-15T00:09:57.448276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length123
Median length71
Mean length34.390411
Min length16

Characters and Unicode

Total characters5021
Distinct characters77
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

Unique142 ?
Unique (%)97.3%

Sample

1st row금속구조물ㆍ창호ㆍ온실공사(2006-03-27)
2nd row금속구조물ㆍ창호ㆍ온실공사(2017-09-19)
3rd row조경식재공사(2020-10-30)
4th row승강기설치공사(2014-01-20)
5th row도장공사(2017-07-20) 포장공사(2017-07-20)
ValueCountFrequency (%)
난방공사(제2종)(2020-08-14 2
 
1.1%
금속구조물ㆍ창호ㆍ온실공사(1994-12-15 2
 
1.1%
난방공사(제2종)(2017-02-13 2
 
1.1%
가스시설공사(제2종)(2012-01-16),난방공사(제2종)(2011-11-29 1
 
0.5%
난방공사(제2종)(2023-04-27 1
 
0.5%
난방공사(제2종)(2012-08-06 1
 
0.5%
가스시설공사(제2종)(2020-01-16),난방공사(제2종)(2020-08-14 1
 
0.5%
가스시설공사(제3종)(2020-03-06),난방공사(제2종)(2013-01-29 1
 
0.5%
가스시설공사(제3종)(2014-01-20),난방공사(제2종)(2005-09-27 1
 
0.5%
기계설비공사(2018-03-30 1
 
0.5%
Other values (172) 172
93.0%
2024-03-15T00:09:58.743018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 562
 
11.2%
2 535
 
10.7%
- 462
 
9.2%
1 351
 
7.0%
( 325
 
6.5%
) 325
 
6.5%
공 231
 
4.6%
사 231
 
4.6%
170
 
3.4%
3 118
 
2.4%
Other values (67) 1711
34.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1942
38.7%
Other Letter 1751
34.9%
Dash Punctuation 462
 
9.2%
Open Punctuation 325
 
6.5%
Close Punctuation 325
 
6.5%
Space Separator 170
 
3.4%
Other Punctuation 46
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 231
 
13.2%
사 231
 
13.2%
ㆍ 95
 
5.4%
제 94
 
5.4%
종 94
 
5.4%
설 92
 
5.3%
시 54
 
3.1%
방 52
 
3.0%
조 51
 
2.9%
난 48
 
2.7%
Other values (52) 709
40.5%
Decimal Number
ValueCountFrequency (%)
0 562
28.9%
2 535
27.5%
1 351
18.1%
3 118
 
6.1%
9 100
 
5.1%
8 60
 
3.1%
4 57
 
2.9%
5 56
 
2.9%
7 54
 
2.8%
6 49
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 462
100.0%
Open Punctuation
ValueCountFrequency (%)
( 325
100.0%
Close Punctuation
ValueCountFrequency (%)
) 325
100.0%
Space Separator
ValueCountFrequency (%)
170
100.0%
Other Punctuation
ValueCountFrequency (%)
, 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3270
65.1%
Hangul 1751
34.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 231
 
13.2%
사 231
 
13.2%
ㆍ 95
 
5.4%
제 94
 
5.4%
종 94
 
5.4%
설 92
 
5.3%
시 54
 
3.1%
방 52
 
3.0%
조 51
 
2.9%
난 48
 
2.7%
Other values (52) 709
40.5%
Common
ValueCountFrequency (%)
0 562
17.2%
2 535
16.4%
- 462
14.1%
1 351
10.7%
( 325
9.9%
) 325
9.9%
170
 
5.2%
3 118
 
3.6%
9 100
 
3.1%
8 60
 
1.8%
Other values (5) 262
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3270
65.1%
Hangul 1656
33.0%
Compat Jamo 95
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 562
17.2%
2 535
16.4%
- 462
14.1%
1 351
10.7%
( 325
9.9%
) 325
9.9%
170
 
5.2%
3 118
 
3.6%
9 100
 
3.1%
8 60
 
1.8%
Other values (5) 262
8.0%
Hangul
ValueCountFrequency (%)
공 231
 
13.9%
사 231
 
13.9%
제 94
 
5.7%
종 94
 
5.7%
설 92
 
5.6%
시 54
 
3.3%
방 52
 
3.1%
조 51
 
3.1%
난 48
 
2.9%
가 46
 
2.8%
Other values (51) 663
40.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 95
100.0%

우편번호
Real number (ℝ)

Distinct50
Distinct (%)34.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24859.137
Minimum24800
Maximum24904
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-03-15T00:09:59.178223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24800
5-th percentile24803.25
Q124842
median24862
Q324885
95-th percentile24899
Maximum24904
Range104
Interquartile range (IQR)43

Descriptive statistics

Standard deviation29.619339
Coefficient of variation (CV)0.001191487
Kurtosis-0.77617477
Mean24859.137
Median Absolute Deviation (MAD)23
Skewness-0.28681523
Sum3629434
Variance877.30524
MonotonicityNot monotonic
2024-03-15T00:09:59.630445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24899 19
 
13.0%
24864 12
 
8.2%
24862 10
 
6.8%
24868 10
 
6.8%
24842 7
 
4.8%
24847 6
 
4.1%
24803 5
 
3.4%
24839 5
 
3.4%
24867 4
 
2.7%
24894 4
 
2.7%
Other values (40) 64
43.8%
ValueCountFrequency (%)
24800 1
 
0.7%
24802 2
 
1.4%
24803 5
3.4%
24804 1
 
0.7%
24807 3
2.1%
24808 1
 
0.7%
24809 1
 
0.7%
24810 1
 
0.7%
24813 1
 
0.7%
24815 2
 
1.4%
ValueCountFrequency (%)
24904 3
 
2.1%
24902 1
 
0.7%
24900 1
 
0.7%
24899 19
13.0%
24897 1
 
0.7%
24896 1
 
0.7%
24894 4
 
2.7%
24892 1
 
0.7%
24891 1
 
0.7%
24890 2
 
1.4%

영업소재지
Text

Distinct137
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-15T00:10:01.175298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length39.5
Mean length28.541096
Min length20

Characters and Unicode

Total characters4167
Distinct characters128
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique128 ?
Unique (%)87.7%

Sample

1st row강원특별자치도 속초시 농공단지2길 33-4(대포동)
2nd row강원특별자치도 속초시 번영로72번길 16-3 (금호동)
3rd row강원특별자치도 속초시 척산양지말길 34 1층 (노학동)
4th row강원특별자치도 속초시 농공단지2길 14 (대포동)
5th row강원특별자치도 속초시 조양로 49 (조양동)
ValueCountFrequency (%)
강원특별자치도 146
18.3%
속초시 146
18.3%
교동 40
 
5.0%
노학동 23
 
2.9%
조양동 20
 
2.5%
대포동 19
 
2.4%
1층 17
 
2.1%
동해대로 16
 
2.0%
2층 11
 
1.4%
영랑동 10
 
1.3%
Other values (224) 351
43.9%
2024-03-15T00:10:02.928802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
653
 
15.7%
동 182
 
4.4%
원 153
 
3.7%
시 152
 
3.6%
도 151
 
3.6%
( 149
 
3.6%
) 149
 
3.6%
치 147
 
3.5%
초 147
 
3.5%
자 147
 
3.5%
Other values (118) 2137
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2580
61.9%
Space Separator 653
 
15.7%
Decimal Number 576
 
13.8%
Open Punctuation 149
 
3.6%
Close Punctuation 149
 
3.6%
Dash Punctuation 41
 
1.0%
Other Punctuation 18
 
0.4%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 182
 
7.1%
원 153
 
5.9%
시 152
 
5.9%
도 151
 
5.9%
치 147
 
5.7%
초 147
 
5.7%
자 147
 
5.7%
강 147
 
5.7%
속 146
 
5.7%
별 146
 
5.7%
Other values (102) 1062
41.2%
Decimal Number
ValueCountFrequency (%)
1 109
18.9%
2 99
17.2%
3 83
14.4%
4 74
12.8%
5 50
8.7%
0 38
 
6.6%
7 34
 
5.9%
9 33
 
5.7%
8 32
 
5.6%
6 24
 
4.2%
Space Separator
ValueCountFrequency (%)
653
100.0%
Open Punctuation
ValueCountFrequency (%)
( 149
100.0%
Close Punctuation
ValueCountFrequency (%)
) 149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2581
61.9%
Common 1586
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 182
 
7.1%
원 153
 
5.9%
시 152
 
5.9%
도 151
 
5.9%
치 147
 
5.7%
초 147
 
5.7%
자 147
 
5.7%
강 147
 
5.7%
속 146
 
5.7%
별 146
 
5.7%
Other values (103) 1063
41.2%
Common
ValueCountFrequency (%)
653
41.2%
( 149
 
9.4%
) 149
 
9.4%
1 109
 
6.9%
2 99
 
6.2%
3 83
 
5.2%
4 74
 
4.7%
5 50
 
3.2%
- 41
 
2.6%
0 38
 
2.4%
Other values (5) 141
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2580
61.9%
ASCII 1586
38.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
653
41.2%
( 149
 
9.4%
) 149
 
9.4%
1 109
 
6.9%
2 99
 
6.2%
3 83
 
5.2%
4 74
 
4.7%
5 50
 
3.2%
- 41
 
2.6%
0 38
 
2.4%
Other values (5) 141
 
8.9%
Hangul
ValueCountFrequency (%)
동 182
 
7.1%
원 153
 
5.9%
시 152
 
5.9%
도 151
 
5.9%
치 147
 
5.7%
초 147
 
5.7%
자 147
 
5.7%
강 147
 
5.7%
속 146
 
5.7%
별 146
 
5.7%
Other values (102) 1062
41.2%
None
ValueCountFrequency (%)
㈜ 1
100.0%

전화번호
Text

MISSING 

Distinct133
Distinct (%)96.4%
Missing8
Missing (%)5.5%
Memory size1.3 KiB
2024-03-15T00:10:04.003930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.014493
Min length12

Characters and Unicode

Total characters1658
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

Unique128 ?
Unique (%)92.8%

Sample

1st row033-633-6644
2nd row033-636-3647
3rd row033-632-2253
4th row033-638-4585
5th row033-244-7426
ValueCountFrequency (%)
033-636-9990 2
 
1.4%
033-638-1177 2
 
1.4%
033-633-4052 2
 
1.4%
033-632-1178 2
 
1.4%
033-638-4585 2
 
1.4%
033-637-3651 1
 
0.7%
033-638-2793 1
 
0.7%
033-633-0695 1
 
0.7%
033-637-2826 1
 
0.7%
033-632-1824 1
 
0.7%
Other values (123) 123
89.1%
2024-03-15T00:10:05.176324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 466
28.1%
- 276
16.6%
0 226
13.6%
6 192
11.6%
2 85
 
5.1%
7 83
 
5.0%
8 81
 
4.9%
5 77
 
4.6%
1 66
 
4.0%
9 60
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1382
83.4%
Dash Punctuation 276
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 466
33.7%
0 226
16.4%
6 192
13.9%
2 85
 
6.2%
7 83
 
6.0%
8 81
 
5.9%
5 77
 
5.6%
1 66
 
4.8%
9 60
 
4.3%
4 46
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 276
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1658
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 466
28.1%
- 276
16.6%
0 226
13.6%
6 192
11.6%
2 85
 
5.1%
7 83
 
5.0%
8 81
 
4.9%
5 77
 
4.6%
1 66
 
4.0%
9 60
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1658
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 466
28.1%
- 276
16.6%
0 226
13.6%
6 192
11.6%
2 85
 
5.1%
7 83
 
5.0%
8 81
 
4.9%
5 77
 
4.6%
1 66
 
4.0%
9 60
 
3.6%

Interactions

2024-03-15T00:09:42.059517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:10:05.433560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종우편번호
업종1.0000.000
우편번호0.0001.000

Missing values

2024-03-15T00:09:42.413113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:09:42.895937image/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

업체명대표자업체등록일자업종등록번호등록일주력사업우편번호영업소재지전화번호
0(주)고원김청재2006-03-27금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업 금속구조물ㆍ창호ㆍ온실공사업(대업종전환)속초2006-08-04 속초2006-08-042006-03-27 2006-03-27금속구조물ㆍ창호ㆍ온실공사(2006-03-27)24899강원특별자치도 속초시 농공단지2길 33-4(대포동)033-633-6644
1(주)국제산업최규동2017-09-19금속ㆍ창호ㆍ지붕ㆍ건축물조립공사업 금속구조물ㆍ창호ㆍ온실공사업(대업종전환)광주북2017-07-06 광주북2017-07-062017-09-19 2017-09-19금속구조물ㆍ창호ㆍ온실공사(2017-09-19)24831강원특별자치도 속초시 번영로72번길 16-3 (금호동)033-636-3647
2(주)국토조경조주현2020-10-30조경식재ㆍ시설물공사업 조경식재공사업(대업종전환)속초2020-16-01 속초2020-16-012020-10-30 2020-10-30조경식재공사(2020-10-30)24867강원특별자치도 속초시 척산양지말길 34 1층 (노학동)033-632-2253
3(주)금강엔지니어링김수자2014-01-20승강기ㆍ삭도공사업 승강기설치공사업(대업종전환)속초2014-22-01 속초2014-22-012014-01-20 2014-01-20승강기설치공사(2014-01-20)24899강원특별자치도 속초시 농공단지2길 14 (대포동)033-638-4585
4(주)녹색라인김주연2017-07-20도장ㆍ습식ㆍ방수ㆍ석공사업 지반조성ㆍ포장공사업 도장공사업(대업종전환) 포장공사업(대업종전환)춘천2017-05-03 춘천2017-14-02 춘천2017-05-03 춘천2017-14-022017-07-20 2017-07-20 2017-07-20 2017-07-20도장공사(2017-07-20) 포장공사(2017-07-20)24894강원특별자치도 속초시 조양로 49 (조양동)033-244-7426
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