Overview

Dataset statistics

Number of variables7
Number of observations22
Missing cells6
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory63.8 B

Variable types

Text4
Numeric2
Categorical1

Dataset

Description전북특별자치도 전주시 내 농기계수리업소를 제공하며, 업소명, 도로명주소, 지번주소, 위도, 경도, 전화번호 등을 제공합니다.항목 : 업소명, 도로명주소, 지번주소, 위도, 경도, 업소전화번호제공부서 : 농업정책과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15083304/fileData.do

Alerts

위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
데이터기준일자 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
데이터기준일자 is highly imbalanced (73.3%)Imbalance
업소명 has 1 (4.5%) missing valuesMissing
도로명주소 has 1 (4.5%) missing valuesMissing
지번주소 has 1 (4.5%) missing valuesMissing
위도 has 1 (4.5%) missing valuesMissing
경도 has 1 (4.5%) missing valuesMissing
업소전화번호 has 1 (4.5%) missing valuesMissing

Reproduction

Analysis started2024-03-14 20:23:23.504831
Analysis finished2024-03-14 20:23:25.770411
Duration2.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing1
Missing (%)4.5%
Memory size304.0 B
2024-03-15T05:23:26.360607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.7619048
Min length3

Characters and Unicode

Total characters184
Distinct characters73
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

Unique21 ?
Unique (%)100.0%

Sample

1st row(유)원일농기계
2nd row국제종합기계(주)전북영업소
3rd row농업회사법인 주식회사 이지팜
4th row대동농업기계
5th row대림농기계
ValueCountFrequency (%)
주식회사 2
 
6.5%
한성티앤아이 2
 
6.5%
전주농협 2
 
6.5%
유)원일농기계 1
 
3.2%
우주무인 1
 
3.2%
한아에스에스 1
 
3.2%
전주대리점 1
 
3.2%
북전주대리점 1
 
3.2%
하늘항공 1
 
3.2%
㈜씨앤씨테크 1
 
3.2%
Other values (18) 18
58.1%
2024-03-15T05:23:27.640155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 11
 
6.0%
주 11
 
6.0%
기 10
 
5.4%
10
 
5.4%
계 9
 
4.9%
전 9
 
4.9%
대 8
 
4.3%
리 5
 
2.7%
업 5
 
2.7%
아 5
 
2.7%
Other values (63) 101
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 169
91.8%
Space Separator 10
 
5.4%
Open Punctuation 2
 
1.1%
Close Punctuation 2
 
1.1%
Other Symbol 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 11
 
6.5%
주 11
 
6.5%
기 10
 
5.9%
계 9
 
5.3%
전 9
 
5.3%
대 8
 
4.7%
리 5
 
3.0%
업 5
 
3.0%
아 5
 
3.0%
사 4
 
2.4%
Other values (59) 92
54.4%
Space Separator
ValueCountFrequency (%)
10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 170
92.4%
Common 14
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 11
 
6.5%
주 11
 
6.5%
기 10
 
5.9%
계 9
 
5.3%
전 9
 
5.3%
대 8
 
4.7%
리 5
 
2.9%
업 5
 
2.9%
아 5
 
2.9%
사 4
 
2.4%
Other values (60) 93
54.7%
Common
ValueCountFrequency (%)
10
71.4%
( 2
 
14.3%
) 2
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 169
91.8%
ASCII 14
 
7.6%
None 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 11
 
6.5%
주 11
 
6.5%
기 10
 
5.9%
계 9
 
5.3%
전 9
 
5.3%
대 8
 
4.7%
리 5
 
3.0%
업 5
 
3.0%
아 5
 
3.0%
사 4
 
2.4%
Other values (59) 92
54.4%
ASCII
ValueCountFrequency (%)
10
71.4%
( 2
 
14.3%
) 2
 
14.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명주소
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing1
Missing (%)4.5%
Memory size304.0 B
2024-03-15T05:23:28.483213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length25.047619
Min length21

Characters and Unicode

Total characters526
Distinct characters68
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row전북특별자치도 전주시 덕진구 호남로 2519-11
2nd row전북특별자치도 전주시 덕진구 신복로 132
3rd row전북특별자치도 전주시 덕진구 번영로 264, 제2동
4th row전북특별자치도 전주시 덕진구 기린대로 916
5th row전북특별자치도 전주시 덕진구 도당산2길 7
ValueCountFrequency (%)
전북특별자치도 21
18.9%
전주시 21
18.9%
덕진구 15
 
13.5%
완산구 6
 
5.4%
우림로 2
 
1.8%
대동로 2
 
1.8%
7 2
 
1.8%
212호 1
 
0.9%
106 1
 
0.9%
235 1
 
0.9%
Other values (39) 39
35.1%
2024-03-15T05:23:29.743855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
93
17.7%
전 42
 
8.0%
도 22
 
4.2%
구 22
 
4.2%
특 21
 
4.0%
별 21
 
4.0%
자 21
 
4.0%
치 21
 
4.0%
주 21
 
4.0%
시 21
 
4.0%
Other values (58) 221
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 352
66.9%
Space Separator 93
 
17.7%
Decimal Number 72
 
13.7%
Other Punctuation 5
 
1.0%
Dash Punctuation 4
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 42
 
11.9%
도 22
 
6.2%
구 22
 
6.2%
특 21
 
6.0%
별 21
 
6.0%
자 21
 
6.0%
치 21
 
6.0%
주 21
 
6.0%
시 21
 
6.0%
북 21
 
6.0%
Other values (45) 119
33.8%
Decimal Number
ValueCountFrequency (%)
2 15
20.8%
1 15
20.8%
6 7
9.7%
5 7
9.7%
9 6
 
8.3%
0 6
 
8.3%
7 6
 
8.3%
3 5
 
6.9%
8 3
 
4.2%
4 2
 
2.8%
Space Separator
ValueCountFrequency (%)
93
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 352
66.9%
Common 174
33.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 42
 
11.9%
도 22
 
6.2%
구 22
 
6.2%
특 21
 
6.0%
별 21
 
6.0%
자 21
 
6.0%
치 21
 
6.0%
주 21
 
6.0%
시 21
 
6.0%
북 21
 
6.0%
Other values (45) 119
33.8%
Common
ValueCountFrequency (%)
93
53.4%
2 15
 
8.6%
1 15
 
8.6%
6 7
 
4.0%
5 7
 
4.0%
9 6
 
3.4%
0 6
 
3.4%
7 6
 
3.4%
, 5
 
2.9%
3 5
 
2.9%
Other values (3) 9
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 352
66.9%
ASCII 174
33.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
93
53.4%
2 15
 
8.6%
1 15
 
8.6%
6 7
 
4.0%
5 7
 
4.0%
9 6
 
3.4%
0 6
 
3.4%
7 6
 
3.4%
, 5
 
2.9%
3 5
 
2.9%
Other values (3) 9
 
5.2%
Hangul
ValueCountFrequency (%)
전 42
 
11.9%
도 22
 
6.2%
구 22
 
6.2%
특 21
 
6.0%
별 21
 
6.0%
자 21
 
6.0%
치 21
 
6.0%
주 21
 
6.0%
시 21
 
6.0%
북 21
 
6.0%
Other values (45) 119
33.8%

지번주소
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing1
Missing (%)4.5%
Memory size304.0 B
2024-03-15T05:23:30.421553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length25.428571
Min length23

Characters and Unicode

Total characters534
Distinct characters51
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

Unique21 ?
Unique (%)100.0%

Sample

1st row전북특별자치도 전주시 덕진구 성덕동 75-2
2nd row전북특별자치도 전주시 덕진구 팔복동4가 202-3
3rd row전북특별자치도 전주시 덕진구 성덕동 368-4
4th row전북특별자치도 전주시 덕진구 동산동 476-14
5th row전북특별자치도 전주시 덕진구 우아동3가 748-57
ValueCountFrequency (%)
전북특별자치도 21
20.0%
전주시 21
20.0%
덕진구 15
14.3%
완산구 6
 
5.7%
반월동 3
 
2.9%
중인동 2
 
1.9%
태평동 2
 
1.9%
팔복동2가 2
 
1.9%
성덕동 2
 
1.9%
304-7 1
 
1.0%
Other values (30) 30
28.6%
2024-03-15T05:23:31.741438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84
 
15.7%
전 43
 
8.1%
동 22
 
4.1%
자 22
 
4.1%
북 21
 
3.9%
구 21
 
3.9%
시 21
 
3.9%
주 21
 
3.9%
도 21
 
3.9%
치 21
 
3.9%
Other values (41) 237
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 344
64.4%
Decimal Number 89
 
16.7%
Space Separator 84
 
15.7%
Dash Punctuation 17
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 43
 
12.5%
동 22
 
6.4%
자 22
 
6.4%
북 21
 
6.1%
구 21
 
6.1%
시 21
 
6.1%
주 21
 
6.1%
도 21
 
6.1%
치 21
 
6.1%
별 21
 
6.1%
Other values (29) 110
32.0%
Decimal Number
ValueCountFrequency (%)
2 15
16.9%
4 13
14.6%
6 11
12.4%
5 10
11.2%
7 10
11.2%
3 10
11.2%
1 10
11.2%
0 5
 
5.6%
8 4
 
4.5%
9 1
 
1.1%
Space Separator
ValueCountFrequency (%)
84
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 344
64.4%
Common 190
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 43
 
12.5%
동 22
 
6.4%
자 22
 
6.4%
북 21
 
6.1%
구 21
 
6.1%
시 21
 
6.1%
주 21
 
6.1%
도 21
 
6.1%
치 21
 
6.1%
별 21
 
6.1%
Other values (29) 110
32.0%
Common
ValueCountFrequency (%)
84
44.2%
- 17
 
8.9%
2 15
 
7.9%
4 13
 
6.8%
6 11
 
5.8%
5 10
 
5.3%
7 10
 
5.3%
3 10
 
5.3%
1 10
 
5.3%
0 5
 
2.6%
Other values (2) 5
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 344
64.4%
ASCII 190
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
84
44.2%
- 17
 
8.9%
2 15
 
7.9%
4 13
 
6.8%
6 11
 
5.8%
5 10
 
5.3%
7 10
 
5.3%
3 10
 
5.3%
1 10
 
5.3%
0 5
 
2.6%
Other values (2) 5
 
2.6%
Hangul
ValueCountFrequency (%)
전 43
 
12.5%
동 22
 
6.4%
자 22
 
6.4%
북 21
 
6.1%
구 21
 
6.1%
시 21
 
6.1%
주 21
 
6.1%
도 21
 
6.1%
치 21
 
6.1%
별 21
 
6.1%
Other values (29) 110
32.0%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct21
Distinct (%)100.0%
Missing1
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean35.849983
Minimum35.772169
Maximum35.887287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size326.0 B
2024-03-15T05:23:32.035053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.772169
5-th percentile35.777869
Q135.823059
median35.86117
Q335.875037
95-th percentile35.87727
Maximum35.887287
Range0.11511786
Interquartile range (IQR)0.05197828

Descriptive statistics

Standard deviation0.032824902
Coefficient of variation (CV)0.00091561833
Kurtosis0.71749746
Mean35.849983
Median Absolute Deviation (MAD)0.01459898
Skewness-1.2371345
Sum752.84964
Variance0.0010774742
MonotonicityNot monotonic
2024-03-15T05:23:32.441347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
35.87551871 1
 
4.5%
35.86116977 1
 
4.5%
35.77216948 1
 
4.5%
35.87726963 1
 
4.5%
35.87579749 1
 
4.5%
35.85795902 1
 
4.5%
35.87192464 1
 
4.5%
35.86233607 1
 
4.5%
35.88728734 1
 
4.5%
35.77786946 1
 
4.5%
Other values (11) 11
50.0%
ValueCountFrequency (%)
35.77216948 1
4.5%
35.77786946 1
4.5%
35.81087689 1
4.5%
35.82242729 1
4.5%
35.82303397 1
4.5%
35.82305912 1
4.5%
35.84657079 1
4.5%
35.85414484 1
4.5%
35.85795902 1
4.5%
35.85980912 1
4.5%
ValueCountFrequency (%)
35.88728734 1
4.5%
35.87726963 1
4.5%
35.87671 1
4.5%
35.87579749 1
4.5%
35.87551871 1
4.5%
35.8750374 1
4.5%
35.87482706 1
4.5%
35.87192464 1
4.5%
35.86384655 1
4.5%
35.86233607 1
4.5%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct21
Distinct (%)100.0%
Missing1
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean127.09424
Minimum127.03612
Maximum127.15515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size326.0 B
2024-03-15T05:23:32.811669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.03612
5-th percentile127.04474
Q1127.06546
median127.08936
Q3127.12742
95-th percentile127.14453
Maximum127.15515
Range0.1190235
Interquartile range (IQR)0.0619599

Descriptive statistics

Standard deviation0.034860777
Coefficient of variation (CV)0.00027429077
Kurtosis-0.92645624
Mean127.09424
Median Absolute Deviation (MAD)0.025058
Skewness0.27363967
Sum2668.979
Variance0.0012152738
MonotonicityNot monotonic
2024-03-15T05:23:33.420644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
127.0447351 1
 
4.5%
127.1027408 1
 
4.5%
127.0920129 1
 
4.5%
127.0654573 1
 
4.5%
127.0583399 1
 
4.5%
127.0893644 1
 
4.5%
127.0851822 1
 
4.5%
127.0810734 1
 
4.5%
127.1301638 1
 
4.5%
127.1044652 1
 
4.5%
Other values (11) 11
50.0%
ValueCountFrequency (%)
127.0361231 1
4.5%
127.0447351 1
4.5%
127.0583399 1
4.5%
127.0615228 1
4.5%
127.0643064 1
4.5%
127.0654573 1
4.5%
127.0735048 1
4.5%
127.0810734 1
4.5%
127.0851822 1
4.5%
127.0856558 1
4.5%
ValueCountFrequency (%)
127.1551466 1
4.5%
127.1445341 1
4.5%
127.1439391 1
4.5%
127.1423836 1
4.5%
127.1301638 1
4.5%
127.1274172 1
4.5%
127.1044652 1
4.5%
127.1027408 1
4.5%
127.0920129 1
4.5%
127.0909663 1
4.5%

업소전화번호
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing1
Missing (%)4.5%
Memory size304.0 B
2024-03-15T05:23:34.204805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters252
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

Unique21 ?
Unique (%)100.0%

Sample

1st row063-211-0030
2nd row063-212-8334
3rd row063-214-9112
4th row063-213-2626
5th row063-251-0201
ValueCountFrequency (%)
063-211-0030 1
 
4.8%
063-285-4848 1
 
4.8%
063-211-8573 1
 
4.8%
063-212-0400 1
 
4.8%
063-224-5396 1
 
4.8%
063-212-2105 1
 
4.8%
063-714-2070 1
 
4.8%
063-253-0052 1
 
4.8%
063-221-9917 1
 
4.8%
063-227-1577 1
 
4.8%
Other values (11) 11
52.4%
2024-03-15T05:23:35.366902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 42
16.7%
0 37
14.7%
2 36
14.3%
3 31
12.3%
6 29
11.5%
1 23
9.1%
5 15
 
6.0%
7 15
 
6.0%
4 11
 
4.4%
8 8
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 210
83.3%
Dash Punctuation 42
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37
17.6%
2 36
17.1%
3 31
14.8%
6 29
13.8%
1 23
11.0%
5 15
7.1%
7 15
7.1%
4 11
 
5.2%
8 8
 
3.8%
9 5
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 42
16.7%
0 37
14.7%
2 36
14.3%
3 31
12.3%
6 29
11.5%
1 23
9.1%
5 15
 
6.0%
7 15
 
6.0%
4 11
 
4.4%
8 8
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 42
16.7%
0 37
14.7%
2 36
14.3%
3 31
12.3%
6 29
11.5%
1 23
9.1%
5 15
 
6.0%
7 15
 
6.0%
4 11
 
4.4%
8 8
 
3.2%

데이터기준일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size304.0 B
2024-01-17
21 
<NA>
 
1

Length

Max length10
Median length10
Mean length9.7272727
Min length4

Unique

Unique1 ?
Unique (%)4.5%

Sample

1st row2024-01-17
2nd row2024-01-17
3rd row2024-01-17
4th row2024-01-17
5th row2024-01-17

Common Values

ValueCountFrequency (%)
2024-01-17 21
95.5%
<NA> 1
 
4.5%

Length

2024-03-15T05:23:35.789626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:23:36.116357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-17 21
95.5%
na 1
 
4.5%

Interactions

2024-03-15T05:23:24.393516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:23:23.888968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:23:24.648555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:23:24.133335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:23:36.321153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명도로명주소지번주소위도경도업소전화번호
업소명1.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.000
위도1.0001.0001.0001.0000.3031.000
경도1.0001.0001.0000.3031.0001.000
업소전화번호1.0001.0001.0001.0001.0001.000
2024-03-15T05:23:36.593031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도데이터기준일자
위도1.000-0.6271.000
경도-0.6271.0001.000
데이터기준일자1.0001.0001.000

Missing values

2024-03-15T05:23:24.998225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:23:25.381798image/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.
2024-03-15T05:23:25.626250image/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

업소명도로명주소지번주소위도경도업소전화번호데이터기준일자
0(유)원일농기계전북특별자치도 전주시 덕진구 호남로 2519-11전북특별자치도 전주시 덕진구 성덕동 75-235.875519127.044735063-211-00302024-01-17
1국제종합기계(주)전북영업소전북특별자치도 전주시 덕진구 신복로 132전북특별자치도 전주시 덕진구 팔복동4가 202-335.86117127.102741063-212-83342024-01-17
2농업회사법인 주식회사 이지팜전북특별자치도 전주시 덕진구 번영로 264, 제2동전북특별자치도 전주시 덕진구 성덕동 368-435.87671127.036123063-214-91122024-01-17
3대동농업기계전북특별자치도 전주시 덕진구 기린대로 916전북특별자치도 전주시 덕진구 동산동 476-1435.863847127.085656063-213-26262024-01-17
4대림농기계전북특별자치도 전주시 덕진구 도당산2길 7전북특별자치도 전주시 덕진구 우아동3가 748-5735.846571127.155147063-251-02012024-01-17
5대우농기계전북특별자치도 전주시 완산구 대동로 81전북특별자치도 전주시 완산구 서노송동 637-535.823059127.144534063-274-15002024-01-17
6대청중기전북특별자치도 전주시 덕진구 쪽구름로 190전북특별자치도 전주시 덕진구 반월동 626-1435.875037127.064306063-214-66872024-01-17
7대흥기계전북특별자치도 전주시 완산구 대동로 61전북특별자치도 전주시 완산구 태평동 52-335.822427127.142384063-275-55252024-01-17
8동양농기계 전주완주대리점전북특별자치도 전주시 덕진구 온고을로 520전북특별자치도 전주시 덕진구 여의동 87235.854145127.073505063-212-37342024-01-17
9빛드론전북특별자치도 전주시 덕진구 오송로 9, 203호전북특별자치도 전주시 덕진구 송천동1가 143-3135.859809127.127417063-271-70892024-01-17
업소명도로명주소지번주소위도경도업소전화번호데이터기준일자
12우주무인 항공산업전북특별자치도 전주시 완산구 천잠로 235, 실습동 4209호전북특별자치도 전주시 완산구 효자동2가 107035.810877127.090966063-227-15772024-01-17
13전주농협 모악농기계수리센터전북특별자치도 전주시 완산구 우림로 1016전북특별자치도 전주시 완산구 중인동 14335.777869127.104465063-221-99172024-01-17
14전주농협 전미농기계수리센터전북특별자치도 전주시 덕진구 과학로 212전북특별자치도 전주시 덕진구 전미동1가 56-535.887287127.130164063-253-00522024-01-17
15주식회사 헬셀전북특별자치도 전주시 덕진구 유상로 67, 7동전북특별자치도 전주시 덕진구 팔복동2가 750-135.862336127.081073063-714-20702024-01-17
16㈜씨앤씨테크전북특별자치도 전주시 덕진구 원고랑1길 35전북특별자치도 전주시 덕진구 고랑동 304-735.871925127.085182063-212-21052024-01-17
17하늘항공전북특별자치도 전주시 덕진구 원만성로 106, 212호전북특별자치도 전주시 덕진구 팔복동2가 836-235.857959127.089364063-224-53962024-01-17
18한성티앤아이 북전주대리점전북특별자치도 전주시 덕진구 서당안길 15-8전북특별자치도 전주시 덕진구 용정동 69-135.875797127.05834063-212-04002024-01-17
19한성티앤아이 전주대리점전북특별자치도 전주시 덕진구 암실길 37-9전북특별자치도 전주시 덕진구 반월동 624-535.87727127.065457063-211-85732024-01-17
20한아에스에스 전북영업소전북특별자치도 전주시 완산구 우림로 872-25전북특별자치도 전주시 완산구 중인동 74435.772169127.092013063-223-86662024-01-17
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