Overview

Dataset statistics

Number of variables26
Number of observations163
Missing cells1808
Missing cells (%)42.7%
Duplicate rows1
Duplicate rows (%)0.6%
Total size in memory35.5 KiB
Average record size in memory222.8 B

Variable types

Categorical8
Text8
DateTime1
Unsupported6
Numeric3

Dataset

Description배출가스 전문정비 사업자 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=640035A392KPQI9NC05N1097696&infSeq=1

Alerts

Dataset has 1 (0.6%) duplicate rowsDuplicates
영업상태구분코드 is highly imbalanced (80.5%)Imbalance
영업상태명 is highly imbalanced (52.8%)Imbalance
X좌표값 is highly imbalanced (89.6%)Imbalance
Y좌표값 is highly imbalanced (89.6%)Imbalance
환경업무구분명 is highly imbalanced (80.5%)Imbalance
배출시설연간가동일수 is highly imbalanced (71.8%)Imbalance
방지시설연간가동일수 is highly imbalanced (71.8%)Imbalance
인허가취소일자 has 163 (100.0%) missing valuesMissing
폐업일자 has 136 (83.4%) missing valuesMissing
소재지시설전화번호 has 155 (95.1%) missing valuesMissing
소재지면적정보 has 163 (100.0%) missing valuesMissing
도로명우편번호 has 157 (96.3%) missing valuesMissing
소재지도로명주소 has 27 (16.6%) missing valuesMissing
소재지우편번호 has 10 (6.1%) missing valuesMissing
WGS84위도 has 14 (8.6%) missing valuesMissing
WGS84경도 has 14 (8.6%) missing valuesMissing
업태구분명정보 has 158 (96.9%) missing valuesMissing
업종구분명정보 has 158 (96.9%) missing valuesMissing
종별명 has 163 (100.0%) missing valuesMissing
주생산품명정보 has 163 (100.0%) missing valuesMissing
배출시설조업시간 has 163 (100.0%) missing valuesMissing
방지시설조업시간 has 163 (100.0%) missing valuesMissing
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported
종별명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주생산품명정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported
배출시설조업시간 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방지시설조업시간 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 21:13:21.878226
Analysis finished2023-12-10 21:13:22.351431
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct26
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
안산시
18 
의정부시
17 
안양시
16 
광주시
14 
부천시
14 
Other values (21)
84 

Length

Max length4
Median length3
Mean length3.1226994
Min length3

Unique

Unique4 ?
Unique (%)2.5%

Sample

1st row가평군
2nd row고양시
3rd row고양시
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
안산시 18
 
11.0%
의정부시 17
 
10.4%
안양시 16
 
9.8%
광주시 14
 
8.6%
부천시 14
 
8.6%
고양시 12
 
7.4%
오산시 7
 
4.3%
수원시 7
 
4.3%
시흥시 6
 
3.7%
의왕시 6
 
3.7%
Other values (16) 46
28.2%

Length

2023-12-11T06:13:22.402858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안산시 18
 
11.0%
의정부시 17
 
10.4%
안양시 16
 
9.8%
광주시 14
 
8.6%
부천시 14
 
8.6%
고양시 12
 
7.4%
오산시 7
 
4.3%
수원시 7
 
4.3%
시흥시 6
 
3.7%
의왕시 6
 
3.7%
Other values (16) 46
28.2%

사업장명
Text

Distinct150
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-11T06:13:22.594032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length9.7177914
Min length4

Characters and Unicode

Total characters1584
Distinct characters151
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique138 ?
Unique (%)84.7%

Sample

1st row테크원모터스(주)
2nd row대한통운(주)서울지사
3rd row명진공업사
4th row현대일산중부서비스(주)
5th row고양현대자동차공업사
ValueCountFrequency (%)
주식회사 4
 
2.2%
현대자동차정비공업사(주 3
 
1.7%
경안자동차정비공업(주 2
 
1.1%
교통안전공단 2
 
1.1%
금성자동차공업사 2
 
1.1%
세봉자동차정비(주 2
 
1.1%
부광모터스(주 2
 
1.1%
주)북의정부자동차 2
 
1.1%
만안현대서비스 2
 
1.1%
교통안전공단(안산자동차검사소 2
 
1.1%
Other values (153) 157
87.2%
2023-12-11T06:13:22.951668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 102
 
6.4%
주 100
 
6.3%
자 92
 
5.8%
차 92
 
5.8%
( 92
 
5.8%
) 92
 
5.8%
비 63
 
4.0%
공 58
 
3.7%
사 58
 
3.7%
업 53
 
3.3%
Other values (141) 782
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1373
86.7%
Open Punctuation 92
 
5.8%
Close Punctuation 92
 
5.8%
Space Separator 17
 
1.1%
Decimal Number 8
 
0.5%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 102
 
7.4%
주 100
 
7.3%
자 92
 
6.7%
차 92
 
6.7%
비 63
 
4.6%
공 58
 
4.2%
사 58
 
4.2%
업 53
 
3.9%
스 49
 
3.6%
정 43
 
3.1%
Other values (133) 663
48.3%
Decimal Number
ValueCountFrequency (%)
1 6
75.0%
5 1
 
12.5%
2 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
D 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 92
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1373
86.7%
Common 209
 
13.2%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 102
 
7.4%
주 100
 
7.3%
자 92
 
6.7%
차 92
 
6.7%
비 63
 
4.6%
공 58
 
4.2%
사 58
 
4.2%
업 53
 
3.9%
스 49
 
3.6%
정 43
 
3.1%
Other values (133) 663
48.3%
Common
ValueCountFrequency (%)
( 92
44.0%
) 92
44.0%
17
 
8.1%
1 6
 
2.9%
5 1
 
0.5%
2 1
 
0.5%
Latin
ValueCountFrequency (%)
K 1
50.0%
D 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1373
86.7%
ASCII 211
 
13.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 102
 
7.4%
주 100
 
7.3%
자 92
 
6.7%
차 92
 
6.7%
비 63
 
4.6%
공 58
 
4.2%
사 58
 
4.2%
업 53
 
3.9%
스 49
 
3.6%
정 43
 
3.1%
Other values (133) 663
48.3%
ASCII
ValueCountFrequency (%)
( 92
43.6%
) 92
43.6%
17
 
8.1%
1 6
 
2.8%
5 1
 
0.5%
2 1
 
0.5%
K 1
 
0.5%
D 1
 
0.5%

인허가일자
Date

Distinct141
Distinct (%)87.0%
Missing1
Missing (%)0.6%
Memory size1.4 KiB
Minimum1991-12-30 00:00:00
Maximum2023-05-10 00:00:00
2023-12-11T06:13:23.065048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:13:23.169245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing163
Missing (%)100.0%
Memory size1.6 KiB

영업상태구분코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
155 
11
 
7
3
 
1

Length

Max length4
Median length4
Mean length3.8957055
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 155
95.1%
11 7
 
4.3%
3 1
 
0.6%

Length

2023-12-11T06:13:23.295309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:13:23.398791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 155
95.1%
11 7
 
4.3%
3 1
 
0.6%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
운영중
128 
폐업 등
27 
영업
 
7
재개업
 
1

Length

Max length4
Median length3
Mean length3.1226994
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 128
78.5%
폐업 등 27
 
16.6%
영업 7
 
4.3%
재개업 1
 
0.6%

Length

2023-12-11T06:13:23.501934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:13:23.609283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 128
67.4%
폐업 27
 
14.2%
등 27
 
14.2%
영업 7
 
3.7%
재개업 1
 
0.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)81.5%
Missing136
Missing (%)83.4%
Infinite0
Infinite (%)0.0%
Mean20125128
Minimum20010110
Maximum20180112
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T06:13:23.704389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010110
5-th percentile20080526
Q120111164
median20130228
Q320135907
95-th percentile20170839
Maximum20180112
Range170002
Interquartile range (IQR)24742.5

Descriptive statistics

Standard deviation33429.813
Coefficient of variation (CV)0.0016610981
Kurtosis4.5490636
Mean20125128
Median Absolute Deviation (MAD)19000
Skewness-1.3859433
Sum5.4337846 × 108
Variance1.1175524 × 109
MonotonicityNot monotonic
2023-12-11T06:13:23.808682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
20130701 2
 
1.2%
20130620 2
 
1.2%
20111027 2
 
1.2%
20120920 2
 
1.2%
20160229 2
 
1.2%
20110216 1
 
0.6%
20151102 1
 
0.6%
20141113 1
 
0.6%
20170420 1
 
0.6%
20111101 1
 
0.6%
Other values (12) 12
 
7.4%
(Missing) 136
83.4%
ValueCountFrequency (%)
20010110 1
0.6%
20080227 1
0.6%
20081224 1
0.6%
20110216 1
0.6%
20111027 2
1.2%
20111101 1
0.6%
20111228 1
0.6%
20120521 1
0.6%
20120813 1
0.6%
20120920 2
1.2%
ValueCountFrequency (%)
20180112 1
0.6%
20171019 1
0.6%
20170420 1
0.6%
20160229 2
1.2%
20151102 1
0.6%
20141113 1
0.6%
20130701 2
1.2%
20130620 2
1.2%
20130610 1
0.6%
20130412 1
0.6%

소재지시설전화번호
Text

MISSING 

Distinct7
Distinct (%)87.5%
Missing155
Missing (%)95.1%
Memory size1.4 KiB
2023-12-11T06:13:23.961377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.625
Min length8

Characters and Unicode

Total characters93
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

Unique6 ?
Unique (%)75.0%

Sample

1st row666-9997
2nd row031-296-7100
3rd row031 447 8400
4th row031 447 8400
5th row031-375-6613
ValueCountFrequency (%)
031 2
16.7%
447 2
16.7%
8400 2
16.7%
666-9997 1
8.3%
031-296-7100 1
8.3%
031-375-6613 1
8.3%
031-206-78501 1
8.3%
031-453-2777 1
8.3%
031-878-8400 1
8.3%
2023-12-11T06:13:24.235938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17
18.3%
- 11
11.8%
3 10
10.8%
1 10
10.8%
7 10
10.8%
4 8
8.6%
6 7
7.5%
8 6
 
6.5%
4
 
4.3%
9 4
 
4.3%
Other values (2) 6
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
83.9%
Dash Punctuation 11
 
11.8%
Space Separator 4
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17
21.8%
3 10
12.8%
1 10
12.8%
7 10
12.8%
4 8
10.3%
6 7
9.0%
8 6
 
7.7%
9 4
 
5.1%
2 3
 
3.8%
5 3
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 93
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17
18.3%
- 11
11.8%
3 10
10.8%
1 10
10.8%
7 10
10.8%
4 8
8.6%
6 7
7.5%
8 6
 
6.5%
4
 
4.3%
9 4
 
4.3%
Other values (2) 6
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17
18.3%
- 11
11.8%
3 10
10.8%
1 10
10.8%
7 10
10.8%
4 8
8.6%
6 7
7.5%
8 6
 
6.5%
4
 
4.3%
9 4
 
4.3%
Other values (2) 6
 
6.5%

소재지면적정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing163
Missing (%)100.0%
Memory size1.6 KiB

도로명우편번호
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing157
Missing (%)96.3%
Memory size1.4 KiB
2023-12-11T06:13:24.418103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.6666667
Min length5

Characters and Unicode

Total characters34
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

Unique6 ?
Unique (%)100.0%

Sample

1st row420-837
2nd row16601
3rd row18144
4th row17095
5th row16071
ValueCountFrequency (%)
420-837 1
16.7%
16601 1
16.7%
18144 1
16.7%
17095 1
16.7%
16071 1
16.7%
480-810 1
16.7%
2023-12-11T06:13:24.727591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8
23.5%
0 6
17.6%
4 4
11.8%
8 4
11.8%
7 3
 
8.8%
6 3
 
8.8%
- 2
 
5.9%
2 1
 
2.9%
3 1
 
2.9%
9 1
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32
94.1%
Dash Punctuation 2
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
25.0%
0 6
18.8%
4 4
12.5%
8 4
12.5%
7 3
 
9.4%
6 3
 
9.4%
2 1
 
3.1%
3 1
 
3.1%
9 1
 
3.1%
5 1
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
23.5%
0 6
17.6%
4 4
11.8%
8 4
11.8%
7 3
 
8.8%
6 3
 
8.8%
- 2
 
5.9%
2 1
 
2.9%
3 1
 
2.9%
9 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8
23.5%
0 6
17.6%
4 4
11.8%
8 4
11.8%
7 3
 
8.8%
6 3
 
8.8%
- 2
 
5.9%
2 1
 
2.9%
3 1
 
2.9%
9 1
 
2.9%

소재지도로명주소
Text

MISSING 

Distinct121
Distinct (%)89.0%
Missing27
Missing (%)16.6%
Memory size1.4 KiB
2023-12-11T06:13:25.004667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28
Mean length22.801471
Min length14

Characters and Unicode

Total characters3101
Distinct characters182
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)80.9%

Sample

1st row경기도 고양시 일산동구 성현로 615
2nd row경기도 고양시 일산동구 고봉로 618-18
3rd row경기도 고양시 일산동구 성현로 363 (문봉동)
4th row경기도 고양시 일산서구 경의로 848 (덕이동)
5th row경기도 고양시 덕양구 통일로1031번길 494
ValueCountFrequency (%)
경기도 136
 
19.3%
의정부시 16
 
2.3%
안산시 15
 
2.1%
안양시 13
 
1.8%
상록구 13
 
1.8%
부천시 12
 
1.7%
광주시 12
 
1.7%
고양시 10
 
1.4%
오산시 7
 
1.0%
동안구 7
 
1.0%
Other values (295) 463
65.8%
2023-12-11T06:13:25.462903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
570
 
18.4%
경 149
 
4.8%
시 145
 
4.7%
기 142
 
4.6%
도 137
 
4.4%
로 124
 
4.0%
동 110
 
3.5%
1 92
 
3.0%
( 88
 
2.8%
) 88
 
2.8%
Other values (172) 1456
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1870
60.3%
Space Separator 570
 
18.4%
Decimal Number 463
 
14.9%
Open Punctuation 88
 
2.8%
Close Punctuation 88
 
2.8%
Dash Punctuation 17
 
0.5%
Other Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 149
 
8.0%
시 145
 
7.8%
기 142
 
7.6%
도 137
 
7.3%
로 124
 
6.6%
동 110
 
5.9%
구 59
 
3.2%
안 55
 
2.9%
산 52
 
2.8%
길 46
 
2.5%
Other values (157) 851
45.5%
Decimal Number
ValueCountFrequency (%)
1 92
19.9%
3 72
15.6%
2 56
12.1%
4 44
9.5%
8 43
9.3%
7 40
8.6%
6 33
 
7.1%
0 33
 
7.1%
5 26
 
5.6%
9 24
 
5.2%
Space Separator
ValueCountFrequency (%)
570
100.0%
Open Punctuation
ValueCountFrequency (%)
( 88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 88
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1870
60.3%
Common 1231
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 149
 
8.0%
시 145
 
7.8%
기 142
 
7.6%
도 137
 
7.3%
로 124
 
6.6%
동 110
 
5.9%
구 59
 
3.2%
안 55
 
2.9%
산 52
 
2.8%
길 46
 
2.5%
Other values (157) 851
45.5%
Common
ValueCountFrequency (%)
570
46.3%
1 92
 
7.5%
( 88
 
7.1%
) 88
 
7.1%
3 72
 
5.8%
2 56
 
4.5%
4 44
 
3.6%
8 43
 
3.5%
7 40
 
3.2%
6 33
 
2.7%
Other values (5) 105
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1870
60.3%
ASCII 1231
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
570
46.3%
1 92
 
7.5%
( 88
 
7.1%
) 88
 
7.1%
3 72
 
5.8%
2 56
 
4.5%
4 44
 
3.6%
8 43
 
3.5%
7 40
 
3.2%
6 33
 
2.7%
Other values (5) 105
 
8.5%
Hangul
ValueCountFrequency (%)
경 149
 
8.0%
시 145
 
7.8%
기 142
 
7.6%
도 137
 
7.3%
로 124
 
6.6%
동 110
 
5.9%
구 59
 
3.2%
안 55
 
2.9%
산 52
 
2.8%
길 46
 
2.5%
Other values (157) 851
45.5%

소재지지번주소
Text

Distinct145
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-11T06:13:25.794721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length20.840491
Min length11

Characters and Unicode

Total characters3397
Distinct characters157
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique128 ?
Unique (%)78.5%

Sample

1st row경기도 가평군 가평읍 상색리 171-4번지 ,171-14
2nd row경기도 고양시 일산동구 사리현동 137번지
3rd row경기도 고양시 일산동구 문봉동
4th row경기도 고양시 일산동구 성석동 1229-11번지
5th row경기도 고양시 덕양구 벽제동 264-5번지
ValueCountFrequency (%)
경기도 163
 
21.9%
안산시 18
 
2.4%
의정부시 17
 
2.3%
안양시 16
 
2.1%
상록구 15
 
2.0%
부천시 14
 
1.9%
광주시 14
 
1.9%
고양시 12
 
1.6%
박달동 8
 
1.1%
동안구 8
 
1.1%
Other values (296) 460
61.7%
2023-12-11T06:13:26.231002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
591
17.4%
시 173
 
5.1%
기 168
 
4.9%
경 164
 
4.8%
도 163
 
4.8%
동 160
 
4.7%
지 139
 
4.1%
번 134
 
3.9%
1 121
 
3.6%
- 113
 
3.3%
Other values (147) 1471
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2104
61.9%
Space Separator 591
 
17.4%
Decimal Number 578
 
17.0%
Dash Punctuation 113
 
3.3%
Other Punctuation 9
 
0.3%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 173
 
8.2%
기 168
 
8.0%
경 164
 
7.8%
도 163
 
7.7%
동 160
 
7.6%
지 139
 
6.6%
번 134
 
6.4%
구 69
 
3.3%
안 53
 
2.5%
산 50
 
2.4%
Other values (132) 831
39.5%
Decimal Number
ValueCountFrequency (%)
1 121
20.9%
2 79
13.7%
4 65
11.2%
3 60
10.4%
5 52
9.0%
7 49
8.5%
8 42
 
7.3%
0 40
 
6.9%
6 38
 
6.6%
9 32
 
5.5%
Space Separator
ValueCountFrequency (%)
591
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 113
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2104
61.9%
Common 1293
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 173
 
8.2%
기 168
 
8.0%
경 164
 
7.8%
도 163
 
7.7%
동 160
 
7.6%
지 139
 
6.6%
번 134
 
6.4%
구 69
 
3.3%
안 53
 
2.5%
산 50
 
2.4%
Other values (132) 831
39.5%
Common
ValueCountFrequency (%)
591
45.7%
1 121
 
9.4%
- 113
 
8.7%
2 79
 
6.1%
4 65
 
5.0%
3 60
 
4.6%
5 52
 
4.0%
7 49
 
3.8%
8 42
 
3.2%
0 40
 
3.1%
Other values (5) 81
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2104
61.9%
ASCII 1293
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
591
45.7%
1 121
 
9.4%
- 113
 
8.7%
2 79
 
6.1%
4 65
 
5.0%
3 60
 
4.6%
5 52
 
4.0%
7 49
 
3.8%
8 42
 
3.2%
0 40
 
3.1%
Other values (5) 81
 
6.3%
Hangul
ValueCountFrequency (%)
시 173
 
8.2%
기 168
 
8.0%
경 164
 
7.8%
도 163
 
7.7%
동 160
 
7.6%
지 139
 
6.6%
번 134
 
6.4%
구 69
 
3.3%
안 53
 
2.5%
산 50
 
2.4%
Other values (132) 831
39.5%

소재지우편번호
Text

MISSING 

Distinct128
Distinct (%)83.7%
Missing10
Missing (%)6.1%
Memory size1.4 KiB
2023-12-11T06:13:26.570266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2679739
Min length5

Characters and Unicode

Total characters806
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

Unique111 ?
Unique (%)72.5%

Sample

1st row12426
2nd row10261
3rd row10250
4th row10274
5th row10257
ValueCountFrequency (%)
13982 4
 
2.6%
15633 3
 
2.0%
14567 3
 
2.0%
12791 3
 
2.0%
15257 3
 
2.0%
15558 3
 
2.0%
446908 3
 
2.0%
12739 2
 
1.3%
426855 2
 
1.3%
15119 2
 
1.3%
Other values (118) 125
81.7%
2023-12-11T06:13:27.043807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 187
23.2%
4 110
13.6%
0 80
9.9%
2 74
 
9.2%
5 73
 
9.1%
8 68
 
8.4%
7 61
 
7.6%
3 56
 
6.9%
6 51
 
6.3%
9 45
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 805
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 187
23.2%
4 110
13.7%
0 80
9.9%
2 74
 
9.2%
5 73
 
9.1%
8 68
 
8.4%
7 61
 
7.6%
3 56
 
7.0%
6 51
 
6.3%
9 45
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 806
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 187
23.2%
4 110
13.6%
0 80
9.9%
2 74
 
9.2%
5 73
 
9.1%
8 68
 
8.4%
7 61
 
7.6%
3 56
 
6.9%
6 51
 
6.3%
9 45
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 806
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 187
23.2%
4 110
13.6%
0 80
9.9%
2 74
 
9.2%
5 73
 
9.1%
8 68
 
8.4%
7 61
 
7.6%
3 56
 
6.9%
6 51
 
6.3%
9 45
 
5.6%

WGS84위도
Real number (ℝ)

MISSING 

Distinct127
Distinct (%)85.2%
Missing14
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean37.477621
Minimum37.019556
Maximum38.077549
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T06:13:27.217933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.019556
5-th percentile37.169395
Q137.333193
median37.404175
Q337.692857
95-th percentile37.832996
Maximum38.077549
Range1.0579923
Interquartile range (IQR)0.35966399

Descriptive statistics

Standard deviation0.21360929
Coefficient of variation (CV)0.0056996492
Kurtosis-0.69883508
Mean37.477621
Median Absolute Deviation (MAD)0.12478078
Skewness0.36911767
Sum5584.1655
Variance0.04562893
MonotonicityNot monotonic
2023-12-11T06:13:27.391397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4027737811 4
 
2.5%
37.7551816851 3
 
1.8%
37.4969635676 3
 
1.8%
37.3587958925 2
 
1.2%
37.2916053362 2
 
1.2%
37.1385016516 2
 
1.2%
37.1639148744 2
 
1.2%
37.2342688059 2
 
1.2%
37.7440107663 2
 
1.2%
37.333193187 2
 
1.2%
Other values (117) 125
76.7%
(Missing) 14
 
8.6%
ValueCountFrequency (%)
37.019556391 1
0.6%
37.0236533363 1
0.6%
37.1385016516 2
1.2%
37.1420229502 1
0.6%
37.1615651515 1
0.6%
37.1639148744 2
1.2%
37.1776163913 1
0.6%
37.2024179067 1
0.6%
37.2127818531 1
0.6%
37.2177058898 1
0.6%
ValueCountFrequency (%)
38.0775487177 1
0.6%
37.9207113728 1
0.6%
37.8991089744 1
0.6%
37.8586342343 1
0.6%
37.857925557 1
0.6%
37.8489789646 1
0.6%
37.842155819 1
0.6%
37.8336379791 1
0.6%
37.8320321835 1
0.6%
37.8163789663 1
0.6%

WGS84경도
Real number (ℝ)

MISSING 

Distinct127
Distinct (%)85.2%
Missing14
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean127.00305
Minimum126.71176
Maximum127.64296
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T06:13:27.541555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.71176
5-th percentile126.7721
Q1126.84928
median126.97475
Q3127.09707
95-th percentile127.27481
Maximum127.64296
Range0.93119781
Interquartile range (IQR)0.24779351

Descriptive statistics

Standard deviation0.18338945
Coefficient of variation (CV)0.0014439767
Kurtosis0.49090587
Mean127.00305
Median Absolute Deviation (MAD)0.12547117
Skewness0.72541987
Sum18923.455
Variance0.033631689
MonotonicityNot monotonic
2023-12-11T06:13:27.674254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.904948723 4
 
2.5%
127.0198133637 3
 
1.8%
126.7917525394 3
 
1.8%
126.9633714423 2
 
1.2%
126.8766162145 2
 
1.2%
127.0662765679 2
 
1.2%
127.0669310803 2
 
1.2%
126.9692720669 2
 
1.2%
127.0532119838 2
 
1.2%
127.3743598935 2
 
1.2%
Other values (117) 125
76.7%
(Missing) 14
 
8.6%
ValueCountFrequency (%)
126.7117594756 1
0.6%
126.7290116378 1
0.6%
126.7292051976 1
0.6%
126.7579610253 1
0.6%
126.7597891682 1
0.6%
126.7605276909 1
0.6%
126.7654009573 1
0.6%
126.7717838398 1
0.6%
126.7725721198 1
0.6%
126.7747085721 1
0.6%
ValueCountFrequency (%)
127.6429572813 1
0.6%
127.5482906364 1
0.6%
127.4869817348 1
0.6%
127.4854750733 1
0.6%
127.3743598935 2
1.2%
127.2858270004 1
0.6%
127.2757022795 1
0.6%
127.2734661807 1
0.6%
127.2703072685 1
0.6%
127.2678558573 1
0.6%

업태구분명정보
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing158
Missing (%)96.9%
Memory size1.4 KiB
2023-12-11T06:13:27.817267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.4
Min length7

Characters and Unicode

Total characters47
Distinct characters11
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

Unique1 ?
Unique (%)20.0%

Sample

1st row자동차 수리업
2nd row자동차 전문 수리업
3rd row자동차 전문 수리업
4th row자동차 종합 수리업
5th row자동차 종합 수리업
ValueCountFrequency (%)
자동차 5
35.7%
수리업 5
35.7%
전문 2
 
14.3%
종합 2
 
14.3%
2023-12-11T06:13:28.094622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
19.1%
자 5
10.6%
동 5
10.6%
차 5
10.6%
수 5
10.6%
리 5
10.6%
업 5
10.6%
전 2
 
4.3%
문 2
 
4.3%
종 2
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38
80.9%
Space Separator 9
 
19.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 5
13.2%
동 5
13.2%
차 5
13.2%
수 5
13.2%
리 5
13.2%
업 5
13.2%
전 2
 
5.3%
문 2
 
5.3%
종 2
 
5.3%
합 2
 
5.3%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38
80.9%
Common 9
 
19.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 5
13.2%
동 5
13.2%
차 5
13.2%
수 5
13.2%
리 5
13.2%
업 5
13.2%
전 2
 
5.3%
문 2
 
5.3%
종 2
 
5.3%
합 2
 
5.3%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38
80.9%
ASCII 9
 
19.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
100.0%
Hangul
ValueCountFrequency (%)
자 5
13.2%
동 5
13.2%
차 5
13.2%
수 5
13.2%
리 5
13.2%
업 5
13.2%
전 2
 
5.3%
문 2
 
5.3%
종 2
 
5.3%
합 2
 
5.3%

X좌표값
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
158 
181509.590513338
 
1
198990.707488238
 
1
206848.197051265
 
1
208531.266826059
 
1

Length

Max length16
Median length4
Mean length4.3680982
Min length4

Unique

Unique5 ?
Unique (%)3.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 158
96.9%
181509.590513338 1
 
0.6%
198990.707488238 1
 
0.6%
206848.197051265 1
 
0.6%
208531.266826059 1
 
0.6%
201692.062462624 1
 
0.6%

Length

2023-12-11T06:13:28.259599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:13:28.405972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 158
96.9%
181509.590513338 1
 
0.6%
198990.707488238 1
 
0.6%
206848.197051265 1
 
0.6%
208531.266826059 1
 
0.6%
201692.062462624 1
 
0.6%

Y좌표값
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
158 
443879.247256587
 
1
416854.455598343
 
1
404473.950883458
 
1
418634.243950235
 
1

Length

Max length16
Median length4
Mean length4.3680982
Min length4

Unique

Unique5 ?
Unique (%)3.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 158
96.9%
443879.247256587 1
 
0.6%
416854.455598343 1
 
0.6%
404473.950883458 1
 
0.6%
418634.243950235 1
 
0.6%
472529.291626898 1
 
0.6%

Length

2023-12-11T06:13:28.553733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:13:28.685625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 158
96.9%
443879.247256587 1
 
0.6%
416854.455598343 1
 
0.6%
404473.950883458 1
 
0.6%
418634.243950235 1
 
0.6%
472529.291626898 1
 
0.6%

환경업무구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
155 
배출가스전문정비사업자
 
7
확인검사대행자
 
1

Length

Max length11
Median length4
Mean length4.3190184
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 155
95.1%
배출가스전문정비사업자 7
 
4.3%
확인검사대행자 1
 
0.6%

Length

2023-12-11T06:13:28.810844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:13:28.931780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 155
95.1%
배출가스전문정비사업자 7
 
4.3%
확인검사대행자 1
 
0.6%

업종구분명정보
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing158
Missing (%)96.9%
Memory size1.4 KiB
2023-12-11T06:13:29.072783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.4
Min length7

Characters and Unicode

Total characters47
Distinct characters11
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

Unique1 ?
Unique (%)20.0%

Sample

1st row자동차 수리업
2nd row자동차 전문 수리업
3rd row자동차 전문 수리업
4th row자동차 종합 수리업
5th row자동차 종합 수리업
ValueCountFrequency (%)
자동차 5
35.7%
수리업 5
35.7%
전문 2
 
14.3%
종합 2
 
14.3%
2023-12-11T06:13:29.375682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
19.1%
자 5
10.6%
동 5
10.6%
차 5
10.6%
수 5
10.6%
리 5
10.6%
업 5
10.6%
전 2
 
4.3%
문 2
 
4.3%
종 2
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38
80.9%
Space Separator 9
 
19.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 5
13.2%
동 5
13.2%
차 5
13.2%
수 5
13.2%
리 5
13.2%
업 5
13.2%
전 2
 
5.3%
문 2
 
5.3%
종 2
 
5.3%
합 2
 
5.3%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38
80.9%
Common 9
 
19.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 5
13.2%
동 5
13.2%
차 5
13.2%
수 5
13.2%
리 5
13.2%
업 5
13.2%
전 2
 
5.3%
문 2
 
5.3%
종 2
 
5.3%
합 2
 
5.3%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38
80.9%
ASCII 9
 
19.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
100.0%
Hangul
ValueCountFrequency (%)
자 5
13.2%
동 5
13.2%
차 5
13.2%
수 5
13.2%
리 5
13.2%
업 5
13.2%
전 2
 
5.3%
문 2
 
5.3%
종 2
 
5.3%
합 2
 
5.3%

종별명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing163
Missing (%)100.0%
Memory size1.6 KiB

주생산품명정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing163
Missing (%)100.0%
Memory size1.6 KiB

배출시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing163
Missing (%)100.0%
Memory size1.6 KiB

배출시설연간가동일수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
155 
0
 
8

Length

Max length4
Median length4
Mean length3.8527607
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 155
95.1%
0 8
 
4.9%

Length

2023-12-11T06:13:29.522778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:13:29.625990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 155
95.1%
0 8
 
4.9%

방지시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing163
Missing (%)100.0%
Memory size1.6 KiB

방지시설연간가동일수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
155 
0
 
8

Length

Max length4
Median length4
Mean length3.8527607
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 155
95.1%
0 8
 
4.9%

Length

2023-12-11T06:13:29.738333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:13:29.835369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 155
95.1%
0 8
 
4.9%

Sample

시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값환경업무구분명업종구분명정보종별명주생산품명정보배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
0가평군테크원모터스(주)20060501<NA><NA>운영중<NA><NA><NA><NA><NA>경기도 가평군 가평읍 상색리 171-4번지 ,171-141242637.804452127.486982<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1고양시대한통운(주)서울지사20091130<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산동구 성현로 615경기도 고양시 일산동구 사리현동 137번지1026137.696408126.84915<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2고양시명진공업사20090701<NA><NA>운영중<NA><NA><NA><NA><NA>경기도 고양시 일산동구 문봉동<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3고양시현대일산중부서비스(주)20080521<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산동구 고봉로 618-18경기도 고양시 일산동구 성석동 1229-11번지1025037.711838126.789633<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4고양시고양현대자동차공업사20030122<NA><NA>운영중<NA><NA><NA><NA><NA>경기도 고양시 덕양구 벽제동 264-5번지10274<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5고양시(주)명진자동차20130813<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산동구 성현로 363 (문봉동)경기도 고양시 일산동구 문봉동 168-56번지1025737.702657126.824036<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6고양시대우일산서비스(주)19961025<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산서구 경의로 848 (덕이동)경기도 고양시 일산서구 덕이동1023237.692857126.760528<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7고양시북부자동차공업사19981002<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 덕양구 통일로1031번길 494경기도 고양시 덕양구 내유동 400-8번지1026237.718146126.847121<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8고양시일산제일자동차20090421<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산서구 경의로789번길 26 (덕이동)경기도 고양시 일산서구 덕이동1022537.688632126.757961<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9고양시(주)현대일산자동차정비센타20130618<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산동구 성석로 40 (중산동)경기도 고양시 일산동구 중산동 10-2번지1031937.683493126.7914<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값환경업무구분명업종구분명정보종별명주생산품명정보배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
153파주시금촌자동차정비검사소20120824<NA><NA>운영중<NA><NA><NA><NA>경기도 파주시 강천길 58-7 (금촌동)경기도 파주시 금촌동 735번지1091237.76219126.765401<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
154포천시한양자동차공업(주)19961001<NA><NA>운영중<NA><NA><NA><NA>경기도 포천시 소흘읍 호국로 483경기도 포천시 소흘읍 이동교리 118-1번지48782037.816379127.134793<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
155포천시포천자동차공업사19920211<NA><NA>운영중<NA><NA><NA><NA>경기도 포천시 신북면 중앙로 409경기도 포천시 신북면 가채리 337-2번지48791137.920711127.215423<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
156포천시삼성공업사19980908<NA><NA>운영중<NA><NA><NA><NA>경기도 포천시 영북면 영북로 36경기도 포천시 영북면 운천리 259-5번지1110438.077549127.275702<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
157포천시고려자동차정비공장19960912<NA><NA>운영중<NA><NA><NA><NA>경기도 포천시 내촌면 금강로 2008경기도 포천시 내촌면 음현리 520번지48783237.759175127.221799<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
158하남시에이스자동차종합20161223<NA><NA>운영중<NA><NA><NA><NA>경기도 하남시 대성로 171 (춘궁동)경기도 하남시 춘궁동 180-1번지1301737.525552127.197997<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
159하남시(주)정림이앤씨<NA><NA><NA>운영중<NA><NA><NA><NA>경기도 하남시 하남대로622번길 33경기도 하남시 창우동 323번지 외 2필지46512037.530082127.222165<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
160화성시(주)화성현대서비스19990611<NA><NA>운영중<NA><NA><NA><NA>경기도 화성시 송산면 송산로 84경기도 화성시 송산면 사강리 300번지1854737.217706126.729012<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
161화성시(주)중앙고속20040315<NA><NA>운영중<NA><NA><NA><NA><NA>경기도 화성시 동탄면 중리 423-1번지18465<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
162화성시(주)남양공업사20130827<NA><NA>운영중<NA><NA><NA><NA>경기도 화성시 남양읍 주석로 370-17경기도 화성시 남양읍 북양리 565-19번지1825537.202418126.862352<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군명사업장명인허가일자영업상태구분코드영업상태명폐업일자소재지시설전화번호도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값환경업무구분명업종구분명정보배출시설연간가동일수방지시설연간가동일수# duplicates
0안양시세봉자동차정비(주)19980730<NA>폐업 등20160229<NA><NA>경기도 안양시 동안구 부림로188번길 31 (관양동)경기도 안양시 동안구 관양동 736-10번지43181037.401078126.961048<NA><NA><NA><NA><NA><NA><NA>2