Overview

Dataset statistics

Number of variables7
Number of observations76
Missing cells33
Missing cells (%)6.2%
Duplicate rows1
Duplicate rows (%)1.3%
Total size in memory4.3 KiB
Average record size in memory57.7 B

Variable types

Categorical3
Text4

Dataset

Description전라북도 정읍시 소재한 폐기물처리업 현황중( 업종, 업체명, 소재지도로명주소, 소재지지번주소, 전화번호, 담당부서)의 정보를 제공합니다.
Author전라북도 정읍시
URLhttps://www.data.go.kr/data/15034701/fileData.do

Alerts

담당부서 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 1 (1.3%) duplicate rowsDuplicates
소재지도로명주소 has 10 (13.2%) missing valuesMissing
전화번호 has 23 (30.3%) missing valuesMissing

Reproduction

Analysis started2023-12-16 16:00:43.374128
Analysis finished2023-12-16 16:00:46.846028
Duration3.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

Distinct6
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size740.0 B
종합재활용업
43 
수집운반업
21 
중간처리업
5 
중간재활용업
 
3
최종재활용업
 
3

Length

Max length6
Median length6
Mean length5.6447368
Min length5

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row중간처분업
2nd row중간재활용업
3rd row중간재활용업
4th row중간재활용업
5th row최종재활용업

Common Values

ValueCountFrequency (%)
종합재활용업 43
56.6%
수집운반업 21
27.6%
중간처리업 5
 
6.6%
중간재활용업 3
 
3.9%
최종재활용업 3
 
3.9%
중간처분업 1
 
1.3%

Length

2023-12-16T16:00:47.192350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T16:00:47.623211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종합재활용업 43
56.6%
수집운반업 21
27.6%
중간처리업 5
 
6.6%
중간재활용업 3
 
3.9%
최종재활용업 3
 
3.9%
중간처분업 1
 
1.3%

업체명
Text

Distinct68
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-16T16:00:48.281137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length6.3947368
Min length2

Characters and Unicode

Total characters486
Distinct characters122
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)82.9%

Sample

1st row동원페이퍼㈜정읍공장
2nd row제이에스산업
3rd row㈜수미자원
4th row㈜와이에스2공장
5th row㈜새한리싸이클
ValueCountFrequency (%)
유)현영 4
 
5.0%
유)숲으로 3
 
3.8%
태영자원 2
 
2.5%
㈜칠보환경개발 2
 
2.5%
주)그린환경 2
 
2.5%
농업회사법인 2
 
2.5%
유)현대환경 1
 
1.2%
정토농장 1
 
1.2%
원천농장 1
 
1.2%
하늘농장 1
 
1.2%
Other values (61) 61
76.2%
2023-12-16T16:00:49.869666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 25
 
5.1%
( 24
 
4.9%
) 24
 
4.9%
유 20
 
4.1%
업 16
 
3.3%
경 15
 
3.1%
농 15
 
3.1%
원 14
 
2.9%
이 13
 
2.7%
환 13
 
2.7%
Other values (112) 307
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 404
83.1%
Other Symbol 25
 
5.1%
Open Punctuation 24
 
4.9%
Close Punctuation 24
 
4.9%
Space Separator 4
 
0.8%
Uppercase Letter 4
 
0.8%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 20
 
5.0%
업 16
 
4.0%
경 15
 
3.7%
농 15
 
3.7%
원 14
 
3.5%
이 13
 
3.2%
환 13
 
3.2%
정 12
 
3.0%
산 11
 
2.7%
장 10
 
2.5%
Other values (104) 265
65.6%
Uppercase Letter
ValueCountFrequency (%)
S 2
50.0%
N 1
25.0%
M 1
25.0%
Other Symbol
ValueCountFrequency (%)
㈜ 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 429
88.3%
Common 53
 
10.9%
Latin 4
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 25
 
5.8%
유 20
 
4.7%
업 16
 
3.7%
경 15
 
3.5%
농 15
 
3.5%
원 14
 
3.3%
이 13
 
3.0%
환 13
 
3.0%
정 12
 
2.8%
산 11
 
2.6%
Other values (105) 275
64.1%
Common
ValueCountFrequency (%)
( 24
45.3%
) 24
45.3%
4
 
7.5%
2 1
 
1.9%
Latin
ValueCountFrequency (%)
S 2
50.0%
N 1
25.0%
M 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 404
83.1%
ASCII 57
 
11.7%
None 25
 
5.1%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 25
100.0%
ASCII
ValueCountFrequency (%)
( 24
42.1%
) 24
42.1%
4
 
7.0%
S 2
 
3.5%
2 1
 
1.8%
N 1
 
1.8%
M 1
 
1.8%
Hangul
ValueCountFrequency (%)
유 20
 
5.0%
업 16
 
4.0%
경 15
 
3.7%
농 15
 
3.7%
원 14
 
3.5%
이 13
 
3.2%
환 13
 
3.2%
정 12
 
3.0%
산 11
 
2.7%
장 10
 
2.5%
Other values (104) 265
65.6%

소재지도로명주소
Text

MISSING 

Distinct58
Distinct (%)87.9%
Missing10
Missing (%)13.2%
Memory size740.0 B
2023-12-16T16:00:50.781906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length23
Mean length18.409091
Min length14

Characters and Unicode

Total characters1215
Distinct characters89
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

Unique53 ?
Unique (%)80.3%

Sample

1st row전라북도 정읍시 공단1길 50
2nd row전라북도 정읍시 칠북로 345
3rd row전라북도 정읍시 구다리길 27-29(망제동)
4th row전라북도 정읍시 감곡면 백산감산로 553
5th row전라북도 정읍시 3산단3길 112
ValueCountFrequency (%)
전라북도 66
23.7%
정읍시 65
23.3%
천월길 5
 
1.8%
흥방길 4
 
1.4%
북면 4
 
1.4%
3산단4길 4
 
1.4%
연정길 3
 
1.1%
35 3
 
1.1%
167 3
 
1.1%
정신로 3
 
1.1%
Other values (103) 119
42.7%
2023-12-16T16:00:52.111362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
213
17.5%
북 77
 
6.3%
정 77
 
6.3%
도 70
 
5.8%
읍 69
 
5.7%
전 66
 
5.4%
라 66
 
5.4%
시 66
 
5.4%
1 45
 
3.7%
길 43
 
3.5%
Other values (79) 423
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 750
61.7%
Decimal Number 224
 
18.4%
Space Separator 213
 
17.5%
Dash Punctuation 18
 
1.5%
Close Punctuation 4
 
0.3%
Open Punctuation 4
 
0.3%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 77
10.3%
정 77
10.3%
도 70
 
9.3%
읍 69
 
9.2%
전 66
 
8.8%
라 66
 
8.8%
시 66
 
8.8%
길 43
 
5.7%
로 22
 
2.9%
산 19
 
2.5%
Other values (64) 175
23.3%
Decimal Number
ValueCountFrequency (%)
1 45
20.1%
3 29
12.9%
7 26
11.6%
2 25
11.2%
5 22
9.8%
9 19
8.5%
4 16
 
7.1%
6 15
 
6.7%
0 14
 
6.2%
8 13
 
5.8%
Space Separator
ValueCountFrequency (%)
213
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 750
61.7%
Common 465
38.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 77
10.3%
정 77
10.3%
도 70
 
9.3%
읍 69
 
9.2%
전 66
 
8.8%
라 66
 
8.8%
시 66
 
8.8%
길 43
 
5.7%
로 22
 
2.9%
산 19
 
2.5%
Other values (64) 175
23.3%
Common
ValueCountFrequency (%)
213
45.8%
1 45
 
9.7%
3 29
 
6.2%
7 26
 
5.6%
2 25
 
5.4%
5 22
 
4.7%
9 19
 
4.1%
- 18
 
3.9%
4 16
 
3.4%
6 15
 
3.2%
Other values (5) 37
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 750
61.7%
ASCII 465
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
213
45.8%
1 45
 
9.7%
3 29
 
6.2%
7 26
 
5.6%
2 25
 
5.4%
5 22
 
4.7%
9 19
 
4.1%
- 18
 
3.9%
4 16
 
3.4%
6 15
 
3.2%
Other values (5) 37
 
8.0%
Hangul
ValueCountFrequency (%)
북 77
10.3%
정 77
10.3%
도 70
 
9.3%
읍 69
 
9.2%
전 66
 
8.8%
라 66
 
8.8%
시 66
 
8.8%
길 43
 
5.7%
로 22
 
2.9%
산 19
 
2.5%
Other values (64) 175
23.3%

소재지지번주소
Text

Distinct67
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-16T16:00:53.027592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length26
Mean length21.131579
Min length16

Characters and Unicode

Total characters1606
Distinct characters87
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

Unique60 ?
Unique (%)78.9%

Sample

1st row전라북도 정읍시 영파동 500-12
2nd row전라북도 정읍시 북면 태곡리 150-25
3rd row전라북도 정읍시 망제동 309-3
4th row전라북도 정읍시 감곡면 대신리 61-1
5th row전라북도 정읍시 북면 태곡리 927
ValueCountFrequency (%)
전라북도 76
20.8%
정읍시 76
20.8%
북면 14
 
3.8%
태곡리 10
 
2.7%
감곡면 8
 
2.2%
정우면 7
 
1.9%
오주리 7
 
1.9%
신태인읍 6
 
1.6%
덕천면 6
 
1.6%
영파동 6
 
1.6%
Other values (115) 150
41.0%
2023-12-16T16:00:58.015559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
290
18.1%
북 96
 
6.0%
정 86
 
5.4%
읍 82
 
5.1%
전 76
 
4.7%
도 76
 
4.7%
시 76
 
4.7%
라 76
 
4.7%
- 60
 
3.7%
리 57
 
3.5%
Other values (77) 631
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 932
58.0%
Decimal Number 316
 
19.7%
Space Separator 290
 
18.1%
Dash Punctuation 60
 
3.7%
Other Punctuation 6
 
0.4%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 96
10.3%
정 86
 
9.2%
읍 82
 
8.8%
전 76
 
8.2%
도 76
 
8.2%
시 76
 
8.2%
라 76
 
8.2%
리 57
 
6.1%
면 53
 
5.7%
동 22
 
2.4%
Other values (62) 232
24.9%
Decimal Number
ValueCountFrequency (%)
2 48
15.2%
1 47
14.9%
5 40
12.7%
3 38
12.0%
8 30
9.5%
4 28
8.9%
9 25
7.9%
7 22
7.0%
0 21
6.6%
6 17
 
5.4%
Space Separator
ValueCountFrequency (%)
290
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 932
58.0%
Common 674
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 96
10.3%
정 86
 
9.2%
읍 82
 
8.8%
전 76
 
8.2%
도 76
 
8.2%
시 76
 
8.2%
라 76
 
8.2%
리 57
 
6.1%
면 53
 
5.7%
동 22
 
2.4%
Other values (62) 232
24.9%
Common
ValueCountFrequency (%)
290
43.0%
- 60
 
8.9%
2 48
 
7.1%
1 47
 
7.0%
5 40
 
5.9%
3 38
 
5.6%
8 30
 
4.5%
4 28
 
4.2%
9 25
 
3.7%
7 22
 
3.3%
Other values (5) 46
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 932
58.0%
ASCII 674
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
290
43.0%
- 60
 
8.9%
2 48
 
7.1%
1 47
 
7.0%
5 40
 
5.9%
3 38
 
5.6%
8 30
 
4.5%
4 28
 
4.2%
9 25
 
3.7%
7 22
 
3.3%
Other values (5) 46
 
6.8%
Hangul
ValueCountFrequency (%)
북 96
10.3%
정 86
 
9.2%
읍 82
 
8.8%
전 76
 
8.2%
도 76
 
8.2%
시 76
 
8.2%
라 76
 
8.2%
리 57
 
6.1%
면 53
 
5.7%
동 22
 
2.4%
Other values (62) 232
24.9%

전화번호
Text

MISSING 

Distinct43
Distinct (%)81.1%
Missing23
Missing (%)30.3%
Memory size740.0 B
2023-12-16T16:00:59.562395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.018868
Min length12

Characters and Unicode

Total characters637
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

Unique37 ?
Unique (%)69.8%

Sample

1st row063-536-8811
2nd row063-535-0746
3rd row063-571-7711
4th row063-532-1277
5th row063-535-7956
ValueCountFrequency (%)
063-571-2215 4
 
7.5%
063-571-6705 3
 
5.7%
063-536-5541 3
 
5.7%
063-536-7532 2
 
3.8%
063-537-4700 2
 
3.8%
063-531-3662 2
 
3.8%
063-531-3057 1
 
1.9%
063-536-3314 1
 
1.9%
063-530-2921 1
 
1.9%
063-532-9185 1
 
1.9%
Other values (33) 33
62.3%
2023-12-16T16:01:00.857801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 112
17.6%
- 106
16.6%
5 85
13.3%
0 81
12.7%
6 79
12.4%
7 50
7.8%
1 45
7.1%
2 27
 
4.2%
4 21
 
3.3%
8 19
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 531
83.4%
Dash Punctuation 106
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 112
21.1%
5 85
16.0%
0 81
15.3%
6 79
14.9%
7 50
9.4%
1 45
8.5%
2 27
 
5.1%
4 21
 
4.0%
8 19
 
3.6%
9 12
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 637
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 112
17.6%
- 106
16.6%
5 85
13.3%
0 81
12.7%
6 79
12.4%
7 50
7.8%
1 45
7.1%
2 27
 
4.2%
4 21
 
3.3%
8 19
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 637
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 112
17.6%
- 106
16.6%
5 85
13.3%
0 81
12.7%
6 79
12.4%
7 50
7.8%
1 45
7.1%
2 27
 
4.2%
4 21
 
3.3%
8 19
 
3.0%

담당부서
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
정읍시 자원순환과
76 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정읍시 자원순환과
2nd row정읍시 자원순환과
3rd row정읍시 자원순환과
4th row정읍시 자원순환과
5th row정읍시 자원순환과

Common Values

ValueCountFrequency (%)
정읍시 자원순환과 76
100.0%

Length

2023-12-16T16:01:01.362655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T16:01:01.844158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정읍시 76
50.0%
자원순환과 76
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-15
76 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12-15
2nd row2023-12-15
3rd row2023-12-15
4th row2023-12-15
5th row2023-12-15

Common Values

ValueCountFrequency (%)
2023-12-15 76
100.0%

Length

2023-12-16T16:01:02.399687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T16:01:02.961292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-15 76
100.0%

Correlations

2023-12-16T16:01:03.360865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종업체명소재지도로명주소소재지지번주소전화번호
업종1.0000.1300.6820.8380.632
업체명0.1301.0001.0000.9981.000
소재지도로명주소0.6821.0001.0001.0000.998
소재지지번주소0.8380.9981.0001.0000.998
전화번호0.6321.0000.9980.9981.000

Missing values

2023-12-16T16:00:45.635096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T16:00:46.175730image/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.
2023-12-16T16:00:46.612012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업종업체명소재지도로명주소소재지지번주소전화번호담당부서데이터기준일자
0중간처분업동원페이퍼㈜정읍공장전라북도 정읍시 공단1길 50전라북도 정읍시 영파동 500-12063-536-8811정읍시 자원순환과2023-12-15
1중간재활용업제이에스산업전라북도 정읍시 칠북로 345전라북도 정읍시 북면 태곡리 150-25<NA>정읍시 자원순환과2023-12-15
2중간재활용업㈜수미자원전라북도 정읍시 구다리길 27-29(망제동)전라북도 정읍시 망제동 309-3<NA>정읍시 자원순환과2023-12-15
3중간재활용업㈜와이에스2공장전라북도 정읍시 감곡면 백산감산로 553전라북도 정읍시 감곡면 대신리 61-1<NA>정읍시 자원순환과2023-12-15
4최종재활용업㈜새한리싸이클전라북도 정읍시 3산단3길 112전라북도 정읍시 북면 태곡리 927063-535-0746정읍시 자원순환과2023-12-15
5최종재활용업농업회사법인(유)친환경대현그린전라북도 정읍시 신태인읍 신태인북길 585전라북도 정읍시 신태인읍 연정리 581063-571-7711정읍시 자원순환과2023-12-15
6최종재활용업정읍정애영농조합법인전라북도 정읍시 이평면 청량리 163-2전라북도 정읍시 이평면 궁동길 241-19063-532-1277정읍시 자원순환과2023-12-15
7종합재활용업㈜리엔캠전라북도 정읍시 천월길 174전라북도 정읍시 덕천면 신월리 219063-535-7956정읍시 자원순환과2023-12-15
8종합재활용업태인산업(주)전라북도 정읍시 2산단6길 11전라북도 정읍시 하북동 853-3063-537-5727정읍시 자원순환과2023-12-15
9종합재활용업(유)정읍대원산업전라북도 정읍시 3산단4길 98-8전라북도 정읍시 북면 태곡리 932-6063-536-7277정읍시 자원순환과2023-12-15
업종업체명소재지도로명주소소재지지번주소전화번호담당부서데이터기준일자
66중간처리업㈜신성이엔티전라북도 정읍시 소성상평로 195전라북도 정읍시 소성면 등계리 202-3063-538-6041정읍시 자원순환과2023-12-15
67중간처리업(유)숲으로전라북도 정읍시 연정길 25전라북도 정읍시 신태인읍 신태인리 390-2063-571-6705정읍시 자원순환과2023-12-15
68중간처리업(주)정원산업개발전라북도 정읍시 소성상평로 195전라북도 정읍시 소성면 등계리 202-3063-537-0492정읍시 자원순환과2023-12-15
69수집운반업(유)현영전라북도 정읍시 흥방길 35전라북도 정읍시 감곡면 오주리 58-25063-571-2215정읍시 자원순환과2023-12-15
70수집운반업(주)그린환경전라북도 정읍시 천월길 167전라북도 정읍시 덕천면 달천리 817-5063-536-5541정읍시 자원순환과2023-12-15
71수집운반업(유)숲으로전라북도 정읍시 연정길 25전라북도 정읍시 신태인읍 신태인리 390-2063-571-6705정읍시 자원순환과2023-12-15
72수집운반업반석건설건기전라북도 정읍시 서부로 10전라북도 정읍시 연지동 252-117063-533-1174정읍시 자원순환과2023-12-15
73수집운반업남일유지<NA>전라북도 정읍시 북면 태곡리 928-2<NA>정읍시 자원순환과2023-12-15
74수집운반업대광<NA>전라북도 정읍시 신태인읍 우령리 438-2<NA>정읍시 자원순환과2023-12-15
75수집운반업SM로지스<NA>전라북도 정읍시 칠보면 와우리 822-7<NA>정읍시 자원순환과2023-12-15

Duplicate rows

Most frequently occurring

업종업체명소재지도로명주소소재지지번주소전화번호담당부서데이터기준일자# duplicates
0수집운반업(유)현영전라북도 정읍시 흥방길 35전라북도 정읍시 감곡면 오주리 58-25063-571-2215정읍시 자원순환과2023-12-152