Overview

Dataset statistics

Number of variables7
Number of observations722
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory40.3 KiB
Average record size in memory57.2 B

Variable types

Numeric1
Text4
DateTime1
Categorical1

Dataset

Description경기도 안산시 소재 전문건설업 등록현황입니다. 상호,업체등록일자,업종,대표자,영업소재지(도로명주소),데이터기준일자를 제공합니다.
URLhttps://www.data.go.kr/data/15068573/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:47:48.901418
Analysis finished2023-12-12 02:47:49.608211
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct722
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean361.5
Minimum1
Maximum722
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2023-12-12T11:47:49.676353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile37.05
Q1181.25
median361.5
Q3541.75
95-th percentile685.95
Maximum722
Range721
Interquartile range (IQR)360.5

Descriptive statistics

Standard deviation208.56773
Coefficient of variation (CV)0.57695086
Kurtosis-1.2
Mean361.5
Median Absolute Deviation (MAD)180.5
Skewness0
Sum261003
Variance43500.5
MonotonicityStrictly increasing
2023-12-12T11:47:49.803614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
476 1
 
0.1%
478 1
 
0.1%
479 1
 
0.1%
480 1
 
0.1%
481 1
 
0.1%
482 1
 
0.1%
483 1
 
0.1%
484 1
 
0.1%
485 1
 
0.1%
Other values (712) 712
98.6%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
722 1
0.1%
721 1
0.1%
720 1
0.1%
719 1
0.1%
718 1
0.1%
717 1
0.1%
716 1
0.1%
715 1
0.1%
714 1
0.1%
713 1
0.1%

상호
Text

Distinct719
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-12T11:47:50.058764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length7.3864266
Min length2

Characters and Unicode

Total characters5333
Distinct characters340
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique717 ?
Unique (%)99.3%

Sample

1st row(유)성우이앤씨
2nd row(유)에스디건설
3rd row(유)태종건설
4th row(유)통나무인터내셔널
5th row(주)1급현대정비
ValueCountFrequency (%)
경동eng 3
 
0.4%
대한난방시설관리 2
 
0.3%
효자건축설비 1
 
0.1%
삼천리엔지니어링(주 1
 
0.1%
본오이엠씨 1
 
0.1%
상록보일러프라자 1
 
0.1%
산호건설(주 1
 
0.1%
유)성우이앤씨 1
 
0.1%
산호건축설비 1
 
0.1%
봉림조경 1
 
0.1%
Other values (709) 709
98.2%
2023-12-12T11:47:50.419242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 545
 
10.2%
) 524
 
9.8%
( 524
 
9.8%
설 176
 
3.3%
이 167
 
3.1%
건 149
 
2.8%
스 101
 
1.9%
엔 98
 
1.8%
지 98
 
1.8%
산 81
 
1.5%
Other values (330) 2870
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4187
78.5%
Close Punctuation 525
 
9.8%
Open Punctuation 525
 
9.8%
Uppercase Letter 81
 
1.5%
Other Punctuation 9
 
0.2%
Decimal Number 4
 
0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 545
 
13.0%
설 176
 
4.2%
이 167
 
4.0%
건 149
 
3.6%
스 101
 
2.4%
엔 98
 
2.3%
지 98
 
2.3%
산 81
 
1.9%
에 79
 
1.9%
비 76
 
1.8%
Other values (299) 2617
62.5%
Uppercase Letter
ValueCountFrequency (%)
E 20
24.7%
G 19
23.5%
N 18
22.2%
S 4
 
4.9%
M 3
 
3.7%
C 3
 
3.7%
L 2
 
2.5%
I 2
 
2.5%
T 1
 
1.2%
F 1
 
1.2%
Other values (8) 8
 
9.9%
Other Punctuation
ValueCountFrequency (%)
. 6
66.7%
& 1
 
11.1%
, 1
 
11.1%
， 1
 
11.1%
Decimal Number
ValueCountFrequency (%)
1 1
25.0%
4 1
25.0%
2 1
25.0%
3 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 524
99.8%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 524
99.8%
[ 1
 
0.2%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4187
78.5%
Common 1063
 
19.9%
Latin 81
 
1.5%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 545
 
13.0%
설 176
 
4.2%
이 167
 
4.0%
건 149
 
3.6%
스 101
 
2.4%
엔 98
 
2.3%
지 98
 
2.3%
산 81
 
1.9%
에 79
 
1.9%
비 76
 
1.8%
Other values (298) 2617
62.5%
Latin
ValueCountFrequency (%)
E 20
24.7%
G 19
23.5%
N 18
22.2%
S 4
 
4.9%
M 3
 
3.7%
C 3
 
3.7%
L 2
 
2.5%
I 2
 
2.5%
T 1
 
1.2%
F 1
 
1.2%
Other values (8) 8
 
9.9%
Common
ValueCountFrequency (%)
) 524
49.3%
( 524
49.3%
. 6
 
0.6%
& 1
 
0.1%
[ 1
 
0.1%
] 1
 
0.1%
, 1
 
0.1%
1 1
 
0.1%
， 1
 
0.1%
4 1
 
0.1%
Other values (2) 2
 
0.2%
Han
ValueCountFrequency (%)
到 1
50.0%
我 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4185
78.5%
ASCII 1143
 
21.4%
None 3
 
0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 545
 
13.0%
설 176
 
4.2%
이 167
 
4.0%
건 149
 
3.6%
스 101
 
2.4%
엔 98
 
2.3%
지 98
 
2.3%
산 81
 
1.9%
에 79
 
1.9%
비 76
 
1.8%
Other values (297) 2615
62.5%
ASCII
ValueCountFrequency (%)
) 524
45.8%
( 524
45.8%
E 20
 
1.7%
G 19
 
1.7%
N 18
 
1.6%
. 6
 
0.5%
S 4
 
0.3%
M 3
 
0.3%
C 3
 
0.3%
L 2
 
0.2%
Other values (19) 20
 
1.7%
None
ValueCountFrequency (%)
㈜ 2
66.7%
， 1
33.3%
CJK
ValueCountFrequency (%)
到 1
50.0%
我 1
50.0%

업체등록일자
Date

Distinct644
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
Minimum1978-08-04 00:00:00
Maximum2023-05-15 00:00:00
2023-12-12T11:47:50.559626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:47:50.700947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업종
Text

Distinct159
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-12T11:47:50.898955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length149
Median length109
Mean length33.850416
Min length7

Characters and Unicode

Total characters24440
Distinct characters87
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

Unique103 ?
Unique (%)14.3%

Sample

1st row상ㆍ하수도설비공사업 지반조성ㆍ포장공사업 구조물해체ㆍ비계공사업 비계ㆍ구조물해체공사업(대업종전환) 상ㆍ하수도설비공사업(대업종전환) 보링ㆍ그라우팅공사업(대업종전환) 토공사업(대업종전환)
2nd row상ㆍ하수도설비공사업 지반조성ㆍ포장공사업 조경식재ㆍ시설물공사업 포장공사업(대업종전환) 조경식재공사업(대업종전환) 상ㆍ하수도설비공사업(대업종전환)
3rd row시설물유지관리업
4th row실내건축공사업 실내건축공사업(대업종전환)
5th row가스ㆍ난방공사업 가스시설시공업 제2종(대업종전환)
ValueCountFrequency (%)
가스ㆍ난방공사업 176
 
8.5%
가스시설시공업 165
 
8.0%
기계설비ㆍ가스공사업 146
 
7.0%
제2종(대업종전환 138
 
6.7%
기계설비공사업(대업종전환 123
 
5.9%
난방시공업 118
 
5.7%
금속창호ㆍ지붕건축물조립공사업 96
 
4.6%
제3종(대업종전환 93
 
4.5%
금속구조물ㆍ창호ㆍ온실공사업(대업종전환 81
 
3.9%
도장ㆍ습식ㆍ방수ㆍ석공사업 78
 
3.8%
Other values (50) 858
41.4%
2023-12-12T11:47:51.286880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 2706
 
11.1%
공 1744
 
7.1%
사 1461
 
6.0%
1353
 
5.5%
ㆍ 1227
 
5.0%
종 1169
 
4.8%
) 921
 
3.8%
( 921
 
3.8%
대 886
 
3.6%
환 886
 
3.6%
Other values (77) 11166
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20962
85.8%
Space Separator 1353
 
5.5%
Close Punctuation 921
 
3.8%
Open Punctuation 921
 
3.8%
Decimal Number 283
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 2706
 
12.9%
공 1744
 
8.3%
사 1461
 
7.0%
ㆍ 1227
 
5.9%
종 1169
 
5.6%
대 886
 
4.2%
환 886
 
4.2%
전 886
 
4.2%
설 680
 
3.2%
시 594
 
2.8%
Other values (71) 8723
41.6%
Decimal Number
ValueCountFrequency (%)
2 141
49.8%
3 93
32.9%
1 49
 
17.3%
Space Separator
ValueCountFrequency (%)
1353
100.0%
Close Punctuation
ValueCountFrequency (%)
) 921
100.0%
Open Punctuation
ValueCountFrequency (%)
( 921
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20962
85.8%
Common 3478
 
14.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 2706
 
12.9%
공 1744
 
8.3%
사 1461
 
7.0%
ㆍ 1227
 
5.9%
종 1169
 
5.6%
대 886
 
4.2%
환 886
 
4.2%
전 886
 
4.2%
설 680
 
3.2%
시 594
 
2.8%
Other values (71) 8723
41.6%
Common
ValueCountFrequency (%)
1353
38.9%
) 921
26.5%
( 921
26.5%
2 141
 
4.1%
3 93
 
2.7%
1 49
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19735
80.7%
ASCII 3478
 
14.2%
Compat Jamo 1227
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 2706
 
13.7%
공 1744
 
8.8%
사 1461
 
7.4%
종 1169
 
5.9%
대 886
 
4.5%
환 886
 
4.5%
전 886
 
4.5%
설 680
 
3.4%
시 594
 
3.0%
조 499
 
2.5%
Other values (70) 8224
41.7%
ASCII
ValueCountFrequency (%)
1353
38.9%
) 921
26.5%
( 921
26.5%
2 141
 
4.1%
3 93
 
2.7%
1 49
 
1.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1227
100.0%

대표자
Text

Distinct716
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-12T11:47:51.727888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.1717452
Min length2

Characters and Unicode

Total characters2290
Distinct characters208
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique710 ?
Unique (%)98.3%

Sample

1st row김기원
2nd row김진옥
3rd row김종순
4th row김세영
5th row최경종
ValueCountFrequency (%)
이은숙 2
 
0.3%
김영호 2
 
0.3%
김진태 2
 
0.3%
송석환 2
 
0.3%
김재호 2
 
0.3%
구지민 2
 
0.3%
우상갑 1
 
0.1%
인선학,이종배 1
 
0.1%
김기원 1
 
0.1%
김재형 1
 
0.1%
Other values (706) 706
97.8%
2023-12-12T11:47:52.177299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 149
 
6.5%
이 120
 
5.2%
정 71
 
3.1%
영 60
 
2.6%
성 51
 
2.2%
박 49
 
2.1%
호 45
 
2.0%
상 43
 
1.9%
수 42
 
1.8%
종 42
 
1.8%
Other values (198) 1618
70.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2249
98.2%
Other Punctuation 32
 
1.4%
Uppercase Letter 9
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 149
 
6.6%
이 120
 
5.3%
정 71
 
3.2%
영 60
 
2.7%
성 51
 
2.3%
박 49
 
2.2%
호 45
 
2.0%
상 43
 
1.9%
수 42
 
1.9%
종 42
 
1.9%
Other values (188) 1577
70.1%
Uppercase Letter
ValueCountFrequency (%)
I 2
22.2%
P 1
11.1%
R 1
11.1%
A 1
11.1%
O 1
11.1%
J 1
11.1%
U 1
11.1%
N 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 31
96.9%
， 1
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2249
98.2%
Common 32
 
1.4%
Latin 9
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 149
 
6.6%
이 120
 
5.3%
정 71
 
3.2%
영 60
 
2.7%
성 51
 
2.3%
박 49
 
2.2%
호 45
 
2.0%
상 43
 
1.9%
수 42
 
1.9%
종 42
 
1.9%
Other values (188) 1577
70.1%
Latin
ValueCountFrequency (%)
I 2
22.2%
P 1
11.1%
R 1
11.1%
A 1
11.1%
O 1
11.1%
J 1
11.1%
U 1
11.1%
N 1
11.1%
Common
ValueCountFrequency (%)
, 31
96.9%
， 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2249
98.2%
ASCII 40
 
1.7%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 149
 
6.6%
이 120
 
5.3%
정 71
 
3.2%
영 60
 
2.7%
성 51
 
2.3%
박 49
 
2.2%
호 45
 
2.0%
상 43
 
1.9%
수 42
 
1.9%
종 42
 
1.9%
Other values (188) 1577
70.1%
ASCII
ValueCountFrequency (%)
, 31
77.5%
I 2
 
5.0%
P 1
 
2.5%
R 1
 
2.5%
A 1
 
2.5%
O 1
 
2.5%
J 1
 
2.5%
U 1
 
2.5%
N 1
 
2.5%
None
ValueCountFrequency (%)
， 1
100.0%

영업소재지(도로명주소)
Text

Distinct719
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-12T11:47:52.557607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length47
Mean length32.850416
Min length17

Characters and Unicode

Total characters23718
Distinct characters272
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique716 ?
Unique (%)99.2%

Sample

1st row경기도 안산시 단원구 광덕2로 186-5, 302호 (고잔동, 성진빌딩)
2nd row경기도 안산시 단원구 동산로 63, 427호 (원시동)
3rd row경기도 안산시 상록구 광덕1로 358 205호 (이동,에이스프라자)
4th row경기도 안산시 단원구 이삭4길 15-4 1층 (고잔동)
5th row경기도 안산시 단원구 선이로 43 (선부동)
ValueCountFrequency (%)
경기도 722
 
13.8%
안산시 722
 
13.8%
단원구 438
 
8.4%
상록구 284
 
5.4%
고잔동 114
 
2.2%
1층 57
 
1.1%
본오동 55
 
1.1%
사동 54
 
1.0%
원곡동 49
 
0.9%
이동 48
 
0.9%
Other values (1108) 2679
51.3%
2023-12-12T11:47:53.168141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4500
 
19.0%
1 946
 
4.0%
동 862
 
3.6%
산 793
 
3.3%
시 776
 
3.3%
안 770
 
3.2%
구 731
 
3.1%
기 730
 
3.1%
( 728
 
3.1%
) 728
 
3.1%
Other values (262) 12154
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13187
55.6%
Space Separator 4500
 
19.0%
Decimal Number 3912
 
16.5%
Open Punctuation 728
 
3.1%
Close Punctuation 728
 
3.1%
Other Punctuation 511
 
2.2%
Dash Punctuation 144
 
0.6%
Uppercase Letter 7
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 862
 
6.5%
산 793
 
6.0%
시 776
 
5.9%
안 770
 
5.8%
구 731
 
5.5%
기 730
 
5.5%
도 728
 
5.5%
경 727
 
5.5%
원 599
 
4.5%
로 588
 
4.5%
Other values (240) 5883
44.6%
Decimal Number
ValueCountFrequency (%)
1 946
24.2%
2 605
15.5%
0 541
13.8%
3 490
12.5%
4 317
 
8.1%
5 291
 
7.4%
6 224
 
5.7%
7 183
 
4.7%
9 163
 
4.2%
8 152
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
A 3
42.9%
B 2
28.6%
L 1
 
14.3%
C 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
, 415
81.2%
， 95
 
18.6%
. 1
 
0.2%
Space Separator
ValueCountFrequency (%)
4500
100.0%
Open Punctuation
ValueCountFrequency (%)
( 728
100.0%
Close Punctuation
ValueCountFrequency (%)
) 728
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13187
55.6%
Common 10524
44.4%
Latin 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 862
 
6.5%
산 793
 
6.0%
시 776
 
5.9%
안 770
 
5.8%
구 731
 
5.5%
기 730
 
5.5%
도 728
 
5.5%
경 727
 
5.5%
원 599
 
4.5%
로 588
 
4.5%
Other values (240) 5883
44.6%
Common
ValueCountFrequency (%)
4500
42.8%
1 946
 
9.0%
( 728
 
6.9%
) 728
 
6.9%
2 605
 
5.7%
0 541
 
5.1%
3 490
 
4.7%
, 415
 
3.9%
4 317
 
3.0%
5 291
 
2.8%
Other values (8) 963
 
9.2%
Latin
ValueCountFrequency (%)
A 3
42.9%
B 2
28.6%
L 1
 
14.3%
C 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13187
55.6%
ASCII 10436
44.0%
None 95
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4500
43.1%
1 946
 
9.1%
( 728
 
7.0%
) 728
 
7.0%
2 605
 
5.8%
0 541
 
5.2%
3 490
 
4.7%
, 415
 
4.0%
4 317
 
3.0%
5 291
 
2.8%
Other values (11) 875
 
8.4%
Hangul
ValueCountFrequency (%)
동 862
 
6.5%
산 793
 
6.0%
시 776
 
5.9%
안 770
 
5.8%
구 731
 
5.5%
기 730
 
5.5%
도 728
 
5.5%
경 727
 
5.5%
원 599
 
4.5%
로 588
 
4.5%
Other values (240) 5883
44.6%
None
ValueCountFrequency (%)
， 95
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-08-04
722 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-04
2nd row2023-08-04
3rd row2023-08-04
4th row2023-08-04
5th row2023-08-04

Common Values

ValueCountFrequency (%)
2023-08-04 722
100.0%

Length

2023-12-12T11:47:53.326445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:47:53.426347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-04 722
100.0%

Interactions

2023-12-12T11:47:49.345126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T11:47:49.464116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:47:49.567130image/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

순번상호업체등록일자업종대표자영업소재지(도로명주소)데이터기준일자
01(유)성우이앤씨2005-11-18상ㆍ하수도설비공사업 지반조성ㆍ포장공사업 구조물해체ㆍ비계공사업 비계ㆍ구조물해체공사업(대업종전환) 상ㆍ하수도설비공사업(대업종전환) 보링ㆍ그라우팅공사업(대업종전환) 토공사업(대업종전환)김기원경기도 안산시 단원구 광덕2로 186-5, 302호 (고잔동, 성진빌딩)2023-08-04
12(유)에스디건설2004-03-10상ㆍ하수도설비공사업 지반조성ㆍ포장공사업 조경식재ㆍ시설물공사업 포장공사업(대업종전환) 조경식재공사업(대업종전환) 상ㆍ하수도설비공사업(대업종전환)김진옥경기도 안산시 단원구 동산로 63, 427호 (원시동)2023-08-04
23(유)태종건설2015-03-03시설물유지관리업김종순경기도 안산시 상록구 광덕1로 358 205호 (이동,에이스프라자)2023-08-04
34(유)통나무인터내셔널2004-04-13실내건축공사업 실내건축공사업(대업종전환)김세영경기도 안산시 단원구 이삭4길 15-4 1층 (고잔동)2023-08-04
45(주)1급현대정비2006-09-18가스ㆍ난방공사업 가스시설시공업 제2종(대업종전환)최경종경기도 안산시 단원구 선이로 43 (선부동)2023-08-04
56(주)가가종합철거환경2007-07-31구조물해체ㆍ비계공사업 비계ㆍ구조물해체공사업(대업종전환)양해명경기도 안산시 단원구 시흥대로 84-6 (선부동)2023-08-04
67(주)가나로드건설2013-08-09시설물유지관리업 도장ㆍ습식ㆍ방수ㆍ석공사업 도장공사업(대업종전환)김세연경기도 안산시 상록구 각골로 120, 102호 (본오동)2023-08-04
78(주)가든포유2010-03-04조경식재ㆍ시설물공사업 조경식재공사업(대업종전환) 조경시설물설치공사업(대업종전환)방성원경기도 안산시 상록구 담원2길 20， 3층 (팔곡이동)2023-08-04
89(주)가림엔지니어링2011-03-10조경식재ㆍ시설물공사업 조경시설물설치공사업(대업종전환) 조경식재공사업(대업종전환)권오찬경기도 안산시 단원구 초지2로 43， 상가동 204호 (초지동)2023-08-04
910(주)가원산업2005-05-16시설물유지관리업 금속창호ㆍ지붕건축물조립공사업 기계설비공사업(폐업) 금속구조물ㆍ창호ㆍ온실공사업(대업종전환)고기철경기도 안산시 단원구 별망로 336, 2층 (성곡동)2023-08-04
순번상호업체등록일자업종대표자영업소재지(도로명주소)데이터기준일자
712713현우알루미늄공업(주)2021-05-06금속창호ㆍ지붕건축물조립공사업 금속구조물ㆍ창호ㆍ온실공사업(대업종전환)최호경기도 안산시 단원구 별망로 167 (성곡동)2023-08-04
713714호남기업(주)2003-03-24금속창호ㆍ지붕건축물조립공사업 철물공사업(폐업) 금속구조물ㆍ창호ㆍ온실공사업(대업종전환)서양원경기도 안산시 상록구 노리울길 19 (장상동)2023-08-04
714715호수기획(주)2022-01-19도장ㆍ습식ㆍ방수ㆍ석공사업신호균경기도 안산시 단원구 고잔로 18 15층 (고잔동)2023-08-04
715716홍민건업(주)2004-11-04금속창호ㆍ지붕건축물조립공사업 도장ㆍ습식ㆍ방수ㆍ석공사업 지반조성ㆍ포장공사업 습식ㆍ방수공사업(대업종전환) 석공사업(대업종전환) 포장공사업(대업종전환) 금속구조물ㆍ창호ㆍ온실공사업(대업종전환)박승우경기도 안산시 단원구 고잔로 55, 1202호 (고잔동， 중앙오피스텔)2023-08-04
716717홍성종합설비2001-11-20가스ㆍ난방공사업 가스시설시공업 제3종(대업종전환) 난방시공업 제2종(대업종전환)김인수경기도 안산시 상록구 도매시장로5길 3 1층 상가B호 (일동)2023-08-04
717718효상디엔씨(주)2020-12-15도장ㆍ습식ㆍ방수ㆍ석공사업 석공사업(대업종전환)신장선경기도 안산시 상록구 각골서로 21, 1층 103호 (본오동)2023-08-04
718719효성보일러설비2013-02-01가스ㆍ난방공사업 가스시설시공업 제2종(대업종전환)이효영경기도 안산시 상록구 장화3길 20 (사동,103호)2023-08-04
719720효자건축설비1997-01-23가스ㆍ난방공사업 난방시공업 제2종(대업종전환) 가스시설시공업 제3종(대업종전환)김재호경기도 안산시 단원구 선이로1길 9 (선부동)2023-08-04
720721흥국공업(주)1992-07-21가스ㆍ난방공사업 난방시공업 제1종(대업종전환) 가스시설시공업 제2종(대업종전환)서원석경기도 안산시 상록구 광덕1로 341, 5층 (이동,제스트프라자)2023-08-04
721722흥진정공(주)2017-11-01기계설비ㆍ가스공사업 기계설비공사업(대업종전환)이중근,이원익경기도 안산시 단원구 범지기로141번길 27 (원시동)2023-08-04