Overview

Dataset statistics

Number of variables6
Number of observations186
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.4 KiB
Average record size in memory51.7 B

Variable types

Numeric3
Text3

Dataset

Description전북특별자치도 전주시 버스카드충전소를 제공하며, 가맹점명, 도로명주소, 지번주소, 위도, 경도 등을 제공합니다.항목 : 연번, 가맹점명, 도로명주소, 지번주소, 위도, 경도
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15112820/fileData.do

Alerts

연번 has unique valuesUnique
가맹점명 has unique valuesUnique
도로명주소 has unique valuesUnique
지번주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-03-14 13:50:08.230042
Analysis finished2024-03-14 13:50:11.703620
Duration3.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct186
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.5
Minimum1
Maximum186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-14T22:50:12.062949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.25
Q147.25
median93.5
Q3139.75
95-th percentile176.75
Maximum186
Range185
Interquartile range (IQR)92.5

Descriptive statistics

Standard deviation53.837719
Coefficient of variation (CV)0.57580448
Kurtosis-1.2
Mean93.5
Median Absolute Deviation (MAD)46.5
Skewness0
Sum17391
Variance2898.5
MonotonicityStrictly increasing
2024-03-14T22:50:12.316190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
129 1
 
0.5%
120 1
 
0.5%
121 1
 
0.5%
122 1
 
0.5%
123 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
Other values (176) 176
94.6%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
186 1
0.5%
185 1
0.5%
184 1
0.5%
183 1
0.5%
182 1
0.5%
181 1
0.5%
180 1
0.5%
179 1
0.5%
178 1
0.5%
177 1
0.5%

가맹점명
Text

UNIQUE 

Distinct186
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-14T22:50:13.154236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length9.6021505
Min length8

Characters and Unicode

Total characters1786
Distinct characters192
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)100.0%

Sample

1st rowGS25금암나래점
2nd rowGS25금암스위트점
3rd rowGS25기전여고점
4th rowGS25나노중앙점
5th rowGS25뉴금암파크점
ValueCountFrequency (%)
gs25금암나래점 1
 
0.5%
gs25전주아영점 1
 
0.5%
gs25전주서부로점 1
 
0.5%
gs25전주제1공단점 1
 
0.5%
gs25전주서신대로점 1
 
0.5%
gs25전주서호점 1
 
0.5%
gs25전주세무서점 1
 
0.5%
gs25전주송천점 1
 
0.5%
gs25전주슈퍼스타점 1
 
0.5%
gs25전주신일점 1
 
0.5%
Other values (176) 176
94.6%
2024-03-14T22:50:14.203087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 186
 
10.4%
2 186
 
10.4%
5 186
 
10.4%
점 186
 
10.4%
S 186
 
10.4%
전 93
 
5.2%
주 79
 
4.4%
중 23
 
1.3%
대 20
 
1.1%
천 18
 
1.0%
Other values (182) 623
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1037
58.1%
Uppercase Letter 376
 
21.1%
Decimal Number 373
 
20.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 186
 
17.9%
전 93
 
9.0%
주 79
 
7.6%
중 23
 
2.2%
대 20
 
1.9%
천 18
 
1.7%
서 18
 
1.7%
효 17
 
1.6%
스 16
 
1.5%
아 16
 
1.5%
Other values (175) 551
53.1%
Uppercase Letter
ValueCountFrequency (%)
G 186
49.5%
S 186
49.5%
I 2
 
0.5%
C 2
 
0.5%
Decimal Number
ValueCountFrequency (%)
2 186
49.9%
5 186
49.9%
1 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1037
58.1%
Latin 376
 
21.1%
Common 373
 
20.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 186
 
17.9%
전 93
 
9.0%
주 79
 
7.6%
중 23
 
2.2%
대 20
 
1.9%
천 18
 
1.7%
서 18
 
1.7%
효 17
 
1.6%
스 16
 
1.5%
아 16
 
1.5%
Other values (175) 551
53.1%
Latin
ValueCountFrequency (%)
G 186
49.5%
S 186
49.5%
I 2
 
0.5%
C 2
 
0.5%
Common
ValueCountFrequency (%)
2 186
49.9%
5 186
49.9%
1 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1037
58.1%
ASCII 749
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
G 186
24.8%
2 186
24.8%
5 186
24.8%
S 186
24.8%
I 2
 
0.3%
C 2
 
0.3%
1 1
 
0.1%
Hangul
ValueCountFrequency (%)
점 186
 
17.9%
전 93
 
9.0%
주 79
 
7.6%
중 23
 
2.2%
대 20
 
1.9%
천 18
 
1.7%
서 18
 
1.7%
효 17
 
1.6%
스 16
 
1.5%
아 16
 
1.5%
Other values (175) 551
53.1%

도로명주소
Text

UNIQUE 

Distinct186
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-14T22:50:15.378599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length59.5
Mean length42.317204
Min length31

Characters and Unicode

Total characters7871
Distinct characters250
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)100.0%

Sample

1st row전북특별자치도 전주시 덕진구 거북바우3길15, 상가 103호,104호 (금암동 1564, 중앙하이츠아파트)
2nd row전북특별자치도 전주시 덕진구 떡전4길12 (금암동 750-9)
3rd row전북특별자치도 전주시 완산구 황강서원4길15(효자동3가 1604-9)
4th row전북특별자치도 전주시 덕진구 비석날로141 (팔복동2가 616-26)
5th row전북특별자치도 전주시 덕진구 용산2길6 (금암동 761-8)
ValueCountFrequency (%)
전북특별자치도 186
 
14.6%
전주시 186
 
14.6%
덕진구 93
 
7.3%
완산구 93
 
7.3%
1층 47
 
3.7%
상가 17
 
1.3%
효자동3가 17
 
1.3%
101호 15
 
1.2%
상가동 12
 
0.9%
서신동 11
 
0.9%
Other values (491) 600
47.0%
2024-03-14T22:50:16.830583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1091
 
13.9%
1 495
 
6.3%
전 388
 
4.9%
2 255
 
3.2%
자 228
 
2.9%
동 227
 
2.9%
주 197
 
2.5%
시 195
 
2.5%
북 194
 
2.5%
구 191
 
2.4%
Other values (240) 4410
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4342
55.2%
Decimal Number 1718
 
21.8%
Space Separator 1091
 
13.9%
Close Punctuation 190
 
2.4%
Open Punctuation 190
 
2.4%
Dash Punctuation 179
 
2.3%
Other Punctuation 151
 
1.9%
Uppercase Letter 8
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 388
 
8.9%
자 228
 
5.3%
동 227
 
5.2%
주 197
 
4.5%
시 195
 
4.5%
북 194
 
4.5%
구 191
 
4.4%
도 191
 
4.4%
치 188
 
4.3%
별 188
 
4.3%
Other values (218) 2155
49.6%
Decimal Number
ValueCountFrequency (%)
1 495
28.8%
2 255
14.8%
3 168
 
9.8%
0 136
 
7.9%
6 134
 
7.8%
7 120
 
7.0%
4 114
 
6.6%
8 114
 
6.6%
5 102
 
5.9%
9 80
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
G 2
25.0%
A 2
25.0%
I 1
12.5%
L 1
12.5%
S 1
12.5%
B 1
12.5%
Space Separator
ValueCountFrequency (%)
1091
100.0%
Close Punctuation
ValueCountFrequency (%)
) 190
100.0%
Open Punctuation
ValueCountFrequency (%)
( 190
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 179
100.0%
Other Punctuation
ValueCountFrequency (%)
, 151
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4342
55.2%
Common 3519
44.7%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 388
 
8.9%
자 228
 
5.3%
동 227
 
5.2%
주 197
 
4.5%
시 195
 
4.5%
북 194
 
4.5%
구 191
 
4.4%
도 191
 
4.4%
치 188
 
4.3%
별 188
 
4.3%
Other values (218) 2155
49.6%
Common
ValueCountFrequency (%)
1091
31.0%
1 495
14.1%
2 255
 
7.2%
) 190
 
5.4%
( 190
 
5.4%
- 179
 
5.1%
3 168
 
4.8%
, 151
 
4.3%
0 136
 
3.9%
6 134
 
3.8%
Other values (5) 530
15.1%
Latin
ValueCountFrequency (%)
G 2
20.0%
e 2
20.0%
A 2
20.0%
I 1
10.0%
L 1
10.0%
S 1
10.0%
B 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4342
55.2%
ASCII 3529
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1091
30.9%
1 495
14.0%
2 255
 
7.2%
) 190
 
5.4%
( 190
 
5.4%
- 179
 
5.1%
3 168
 
4.8%
, 151
 
4.3%
0 136
 
3.9%
6 134
 
3.8%
Other values (12) 540
15.3%
Hangul
ValueCountFrequency (%)
전 388
 
8.9%
자 228
 
5.3%
동 227
 
5.2%
주 197
 
4.5%
시 195
 
4.5%
북 194
 
4.5%
구 191
 
4.4%
도 191
 
4.4%
치 188
 
4.3%
별 188
 
4.3%
Other values (218) 2155
49.6%

지번주소
Text

UNIQUE 

Distinct186
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-14T22:50:18.315571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length29
Mean length26.639785
Min length22

Characters and Unicode

Total characters4955
Distinct characters62
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

Unique186 ?
Unique (%)100.0%

Sample

1st row전북특별자치도 전주시 덕진구 금암동 1564
2nd row전북특별자치도 전주시 덕진구 금암동 750-9
3rd row전북특별자치도 전주시 완산구 효자동3가 1604-9
4th row전북특별자치도 전주시 덕진구 팔복동2가 616-26
5th row전북특별자치도 전주시 덕진구 금암동 761-8
ValueCountFrequency (%)
전북특별자치도 186
20.0%
전주시 186
20.0%
덕진구 93
 
10.0%
완산구 93
 
10.0%
효자동3가 22
 
2.4%
서신동 12
 
1.3%
인후동1가 12
 
1.3%
삼천동1가 11
 
1.2%
송천동2가 10
 
1.1%
금암동 9
 
1.0%
Other values (219) 297
31.9%
2024-03-14T22:50:20.041349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
745
 
15.0%
전 373
 
7.5%
1 227
 
4.6%
자 222
 
4.5%
북 189
 
3.8%
동 189
 
3.8%
별 186
 
3.8%
치 186
 
3.8%
도 186
 
3.8%
특 186
 
3.8%
Other values (52) 2266
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3125
63.1%
Decimal Number 930
 
18.8%
Space Separator 745
 
15.0%
Dash Punctuation 155
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 373
 
11.9%
자 222
 
7.1%
북 189
 
6.0%
동 189
 
6.0%
별 186
 
6.0%
치 186
 
6.0%
도 186
 
6.0%
특 186
 
6.0%
시 186
 
6.0%
구 186
 
6.0%
Other values (40) 1036
33.2%
Decimal Number
ValueCountFrequency (%)
1 227
24.4%
2 135
14.5%
3 106
11.4%
6 96
10.3%
8 77
 
8.3%
7 72
 
7.7%
4 62
 
6.7%
5 56
 
6.0%
9 51
 
5.5%
0 48
 
5.2%
Space Separator
ValueCountFrequency (%)
745
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 155
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3125
63.1%
Common 1830
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 373
 
11.9%
자 222
 
7.1%
북 189
 
6.0%
동 189
 
6.0%
별 186
 
6.0%
치 186
 
6.0%
도 186
 
6.0%
특 186
 
6.0%
시 186
 
6.0%
구 186
 
6.0%
Other values (40) 1036
33.2%
Common
ValueCountFrequency (%)
745
40.7%
1 227
 
12.4%
- 155
 
8.5%
2 135
 
7.4%
3 106
 
5.8%
6 96
 
5.2%
8 77
 
4.2%
7 72
 
3.9%
4 62
 
3.4%
5 56
 
3.1%
Other values (2) 99
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3125
63.1%
ASCII 1830
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
745
40.7%
1 227
 
12.4%
- 155
 
8.5%
2 135
 
7.4%
3 106
 
5.8%
6 96
 
5.2%
8 77
 
4.2%
7 72
 
3.9%
4 62
 
3.4%
5 56
 
3.1%
Other values (2) 99
 
5.4%
Hangul
ValueCountFrequency (%)
전 373
 
11.9%
자 222
 
7.1%
북 189
 
6.0%
동 189
 
6.0%
별 186
 
6.0%
치 186
 
6.0%
도 186
 
6.0%
특 186
 
6.0%
시 186
 
6.0%
구 186
 
6.0%
Other values (40) 1036
33.2%

위도
Real number (ℝ)

UNIQUE 

Distinct186
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.830491
Minimum35.783049
Maximum35.879883
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-14T22:50:20.291460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.783049
5-th percentile35.794338
Q135.81436
median35.831201
Q335.844435
95-th percentile35.870566
Maximum35.879883
Range0.09683427
Interquartile range (IQR)0.03007524

Descriptive statistics

Standard deviation0.022522767
Coefficient of variation (CV)0.00062859219
Kurtosis-0.5785865
Mean35.830491
Median Absolute Deviation (MAD)0.015466395
Skewness0.058412296
Sum6664.4713
Variance0.00050727501
MonotonicityNot monotonic
2024-03-14T22:50:20.683883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.83725553 1
 
0.5%
35.81518573 1
 
0.5%
35.85654095 1
 
0.5%
35.83767538 1
 
0.5%
35.86099941 1
 
0.5%
35.81195461 1
 
0.5%
35.83249005 1
 
0.5%
35.80109866 1
 
0.5%
35.84156743 1
 
0.5%
35.83411933 1
 
0.5%
Other values (176) 176
94.6%
ValueCountFrequency (%)
35.7830491 1
0.5%
35.78399198 1
0.5%
35.78510176 1
0.5%
35.78759034 1
0.5%
35.7889208 1
0.5%
35.79188673 1
0.5%
35.79374145 1
0.5%
35.79393477 1
0.5%
35.79394568 1
0.5%
35.79414025 1
0.5%
ValueCountFrequency (%)
35.87988337 1
0.5%
35.87633602 1
0.5%
35.8761465 1
0.5%
35.8751547 1
0.5%
35.87431119 1
0.5%
35.87333293 1
0.5%
35.87320756 1
0.5%
35.87320591 1
0.5%
35.87250053 1
0.5%
35.87141761 1
0.5%

경도
Real number (ℝ)

UNIQUE 

Distinct186
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.12307
Minimum127.05776
Maximum127.17416
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-14T22:50:21.097066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.05776
5-th percentile127.0773
Q1127.10721
median127.1225
Q3127.13743
95-th percentile127.16885
Maximum127.17416
Range0.1164006
Interquartile range (IQR)0.030221425

Descriptive statistics

Standard deviation0.026155289
Coefficient of variation (CV)0.00020574778
Kurtosis-0.22451935
Mean127.12307
Median Absolute Deviation (MAD)0.01526
Skewness-0.073202316
Sum23644.891
Variance0.00068409915
MonotonicityNot monotonic
2024-03-14T22:50:21.541998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1393008 1
 
0.5%
127.1235057 1
 
0.5%
127.1189359 1
 
0.5%
127.1013554 1
 
0.5%
127.1224758 1
 
0.5%
127.0944864 1
 
0.5%
127.1100031 1
 
0.5%
127.1265207 1
 
0.5%
127.1731207 1
 
0.5%
127.1674089 1
 
0.5%
Other values (176) 176
94.6%
ValueCountFrequency (%)
127.0577638 1
0.5%
127.0609008 1
0.5%
127.061329 1
0.5%
127.0624036 1
0.5%
127.0698238 1
0.5%
127.0720075 1
0.5%
127.0728635 1
0.5%
127.0768407 1
0.5%
127.077133 1
0.5%
127.0772836 1
0.5%
ValueCountFrequency (%)
127.1741644 1
0.5%
127.1736287 1
0.5%
127.1731207 1
0.5%
127.1728605 1
0.5%
127.1728133 1
0.5%
127.171291 1
0.5%
127.1708426 1
0.5%
127.1707745 1
0.5%
127.1697881 1
0.5%
127.1689167 1
0.5%

Interactions

2024-03-14T22:50:10.238440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:50:08.701758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:50:09.470276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:50:10.552414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:50:08.962130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:50:09.726746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:50:10.808481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:50:09.213496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:50:09.972752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T22:50:21.805903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.5690.647
위도0.5691.0000.562
경도0.6470.5621.000
2024-03-14T22:50:22.043433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.000-0.348-0.005
위도-0.3481.000-0.067
경도-0.005-0.0671.000

Missing values

2024-03-14T22:50:11.227921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:50:11.566049image/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

연번가맹점명도로명주소지번주소위도경도
01GS25금암나래점전북특별자치도 전주시 덕진구 거북바우3길15, 상가 103호,104호 (금암동 1564, 중앙하이츠아파트)전북특별자치도 전주시 덕진구 금암동 156435.837256127.139301
12GS25금암스위트점전북특별자치도 전주시 덕진구 떡전4길12 (금암동 750-9)전북특별자치도 전주시 덕진구 금암동 750-935.838113127.128879
23GS25기전여고점전북특별자치도 전주시 완산구 황강서원4길15(효자동3가 1604-9)전북특별자치도 전주시 완산구 효자동3가 1604-935.82731127.100386
34GS25나노중앙점전북특별자치도 전주시 덕진구 비석날로141 (팔복동2가 616-26)전북특별자치도 전주시 덕진구 팔복동2가 616-2635.862913127.085363
45GS25뉴금암파크점전북특별자치도 전주시 덕진구 용산2길6 (금암동 761-8)전북특별자치도 전주시 덕진구 금암동 761-835.836255127.13087
56GS25뉴전북대병원점전북특별자치도 전주시 덕진구 건지2길10, 1층 (금암동 1594-8)전북특별자치도 전주시 덕진구 금암동 1594-835.84422127.141432
67GS25뉴전북대점전북특별자치도 전주시 덕진구 삼송3길47, 1층 (금암동 631-319)전북특별자치도 전주시 덕진구 금암동 631-31935.843862127.137681
78GS25뉴전주남중점전북특별자치도 전주시 완산구 덕적골2길6(평화동1가 445-9)전북특별자치도 전주시 완산구 평화동1가 445-935.79785127.140523
89GS25뉴전주덕진점전북특별자치도 전주시 덕진구 우아3길13, 1층 (우아동3가 747-48, 별장모텔)전북특별자치도 전주시 덕진구 우아동3가 747-4835.848725127.155546
910GS25뉴전주탄소점전북특별자치도 전주시 덕진구 팔복로195, 주1동 소매점1호 (팔복동3가 518-2)전북특별자치도 전주시 덕진구 팔복동3가 518-235.855522127.086677
연번가맹점명도로명주소지번주소위도경도
176177GS25효자센터점전북특별자치도 전주시 완산구 오두정길4 (효자동1가 296-2)전북특별자치도 전주시 완산구 효자동1가 296-235.806503127.120076
177178GS25효자시티점전북특별자치도 전주시 완산구 척동10길2, 1층 (효자동3가 1636-1)전북특별자치도 전주시 완산구 효자동3가 1636-135.824623127.100105
178179GS25효자원룸점전북특별자치도 전주시 완산구 서곡2길13, 1층 (효자동3가 1440-7)전북특별자치도 전주시 완산구 효자동3가 1440-735.834254127.102099
179180GS25효자중앙점전북특별자치도 전주시 완산구 구룡1길33-16 (효자동2가 1264-1)전북특별자치도 전주시 완산구 효자동2가 1264-135.812714127.105566
180181GS25효자파크점전북특별자치도 전주시 완산구 홍산북로45-12 (효자동3가 1529-2)전북특별자치도 전주시 완산구 효자동3가 1529-235.817863127.107161
181182GS25효자한강점전북특별자치도 전주시 완산구 강변로120-1 (효자동1가 660-1, 한강아파트)전북특별자치도 전주시 완산구 효자동1가 660-135.802075127.114154
182183GS25효자행복점전북특별자치도 전주시 완산구 척동4길14(효자동3가 1666-2)전북특별자치도 전주시 완산구 효자동3가 1666-235.822116127.101351
183184GS25효자효녀점전북특별자치도 전주시 완산구 안행5길20, 1층 (효자동1가 683-15)전북특별자치도 전주시 완산구 효자동1가 683-1535.802773127.132175
184185GS25효자휴먼시아점전북특별자치도 전주시 완산구 호암로88, 상가동 102호,103호 (효자동2가 1320-1, 효자휴먼시아6단지아파트)전북특별자치도 전주시 완산구 효자동2가 1320-135.807829127.102713
185186GS25효천우미린점전북특별자치도 전주시 완산구 효천중앙로17, 2동 101호 (효자동2가 282, 효천우미린더퍼스트상가)전북특별자치도 전주시 완산구 효자동2가 136335.798795127.103532