Overview

Dataset statistics

Number of variables6
Number of observations122
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory51.1 B

Variable types

Text4
Numeric2

Dataset

Description강릉시 금융기관정보에 대한 데이터로 금융기관명칭, 도로명주소, 지번주소, 전화번호, 위치정보 등의 항목을 제공합니다.
Author강원도 강릉시
URLhttps://www.data.go.kr/data/15042981/fileData.do

Alerts

명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:56:12.084989
Analysis finished2023-12-12 08:56:12.943194
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

명칭
Text

UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T17:56:13.209847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length9.9918033
Min length4

Characters and Unicode

Total characters1219
Distinct characters139
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

Unique122 ?
Unique (%)100.0%

Sample

1st rowCK저축은행 강릉지점
2nd rowIBK기업은행 강릉지점
3rd rowKB국민은행 강릉지점
4th rowKB국민은행 포남동출장소
5th rowNH농협은행 강릉과학산업진흥원출장소
ValueCountFrequency (%)
강릉지점 15
 
7.7%
강릉농협 14
 
7.2%
nh농협은행 11
 
5.7%
강릉축산농협 6
 
3.1%
강원양돈농협 5
 
2.6%
북강릉농협 4
 
2.1%
강릉원예농협 4
 
2.1%
주문진지점 3
 
1.5%
신한은행 3
 
1.5%
남부지점 2
 
1.0%
Other values (116) 127
65.5%
2023-12-12T17:56:13.680014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
강 96
 
7.9%
릉 87
 
7.1%
72
 
5.9%
지 64
 
5.3%
점 59
 
4.8%
협 55
 
4.5%
농 48
 
3.9%
금 31
 
2.5%
은 27
 
2.2%
행 27
 
2.2%
Other values (129) 653
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1101
90.3%
Space Separator 72
 
5.9%
Uppercase Letter 46
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 96
 
8.7%
릉 87
 
7.9%
지 64
 
5.8%
점 59
 
5.4%
협 55
 
5.0%
농 48
 
4.4%
금 31
 
2.8%
은 27
 
2.5%
행 27
 
2.5%
동 24
 
2.2%
Other values (116) 583
53.0%
Uppercase Letter
ValueCountFrequency (%)
H 13
28.3%
N 12
26.1%
S 4
 
8.7%
K 4
 
8.7%
C 3
 
6.5%
B 3
 
6.5%
I 2
 
4.3%
Ｍ 1
 
2.2%
Ｗ 1
 
2.2%
G 1
 
2.2%
Other values (2) 2
 
4.3%
Space Separator
ValueCountFrequency (%)
72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1101
90.3%
Common 72
 
5.9%
Latin 46
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
강 96
 
8.7%
릉 87
 
7.9%
지 64
 
5.8%
점 59
 
5.4%
협 55
 
5.0%
농 48
 
4.4%
금 31
 
2.8%
은 27
 
2.5%
행 27
 
2.5%
동 24
 
2.2%
Other values (116) 583
53.0%
Latin
ValueCountFrequency (%)
H 13
28.3%
N 12
26.1%
S 4
 
8.7%
K 4
 
8.7%
C 3
 
6.5%
B 3
 
6.5%
I 2
 
4.3%
Ｍ 1
 
2.2%
Ｗ 1
 
2.2%
G 1
 
2.2%
Other values (2) 2
 
4.3%
Common
ValueCountFrequency (%)
72
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1101
90.3%
ASCII 116
 
9.5%
None 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
강 96
 
8.7%
릉 87
 
7.9%
지 64
 
5.8%
점 59
 
5.4%
협 55
 
5.0%
농 48
 
4.4%
금 31
 
2.8%
은 27
 
2.5%
행 27
 
2.5%
동 24
 
2.2%
Other values (116) 583
53.0%
ASCII
ValueCountFrequency (%)
72
62.1%
H 13
 
11.2%
N 12
 
10.3%
S 4
 
3.4%
K 4
 
3.4%
C 3
 
2.6%
B 3
 
2.6%
I 2
 
1.7%
G 1
 
0.9%
M 1
 
0.9%
None
ValueCountFrequency (%)
Ｍ 1
50.0%
Ｗ 1
50.0%

주소
Text

Distinct119
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T17:56:14.010090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length39
Mean length22.319672
Min length13

Characters and Unicode

Total characters2723
Distinct characters138
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)95.1%

Sample

1st row강원도 강릉시 경강로 2156
2nd row강원도 강릉시 경강로 2087　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　
3rd row강원도 강릉시 금성로 48
4th row강원도 강릉시 경강로 2352 (포남동)
5th row강원도 강릉시 과학단지로 106-11 (대전동)
ValueCountFrequency (%)
강원도 122
21.9%
강릉시 122
21.9%
경강로 21
 
3.8%
강릉대로 15
 
2.7%
주문진읍 10
 
1.8%
율곡로 5
 
0.9%
주문로 5
 
0.9%
4 4
 
0.7%
왕산면 4
 
0.7%
2109 4
 
0.7%
Other values (187) 244
43.9%
2023-12-12T17:56:14.523844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
436
16.0%
강 293
 
10.8%
　 173
 
6.4%
릉 142
 
5.2%
시 130
 
4.8%
원 126
 
4.6%
도 122
 
4.5%
로 98
 
3.6%
2 79
 
2.9%
1 74
 
2.7%
Other values (128) 1050
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1555
57.1%
Space Separator 609
 
22.4%
Decimal Number 404
 
14.8%
Open Punctuation 57
 
2.1%
Close Punctuation 57
 
2.1%
Other Punctuation 30
 
1.1%
Dash Punctuation 11
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 293
18.8%
릉 142
 
9.1%
시 130
 
8.4%
원 126
 
8.1%
도 122
 
7.8%
로 98
 
6.3%
동 71
 
4.6%
길 34
 
2.2%
경 25
 
1.6%
대 23
 
1.5%
Other values (112) 491
31.6%
Decimal Number
ValueCountFrequency (%)
2 79
19.6%
1 74
18.3%
4 46
11.4%
0 36
8.9%
7 35
8.7%
3 34
8.4%
8 31
 
7.7%
9 27
 
6.7%
6 25
 
6.2%
5 17
 
4.2%
Space Separator
ValueCountFrequency (%)
436
71.6%
　 173
 
28.4%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Other Punctuation
ValueCountFrequency (%)
, 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1555
57.1%
Common 1168
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
강 293
18.8%
릉 142
 
9.1%
시 130
 
8.4%
원 126
 
8.1%
도 122
 
7.8%
로 98
 
6.3%
동 71
 
4.6%
길 34
 
2.2%
경 25
 
1.6%
대 23
 
1.5%
Other values (112) 491
31.6%
Common
ValueCountFrequency (%)
436
37.3%
　 173
 
14.8%
2 79
 
6.8%
1 74
 
6.3%
( 57
 
4.9%
) 57
 
4.9%
4 46
 
3.9%
0 36
 
3.1%
7 35
 
3.0%
3 34
 
2.9%
Other values (6) 141
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1555
57.1%
ASCII 995
36.5%
None 173
 
6.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
436
43.8%
2 79
 
7.9%
1 74
 
7.4%
( 57
 
5.7%
) 57
 
5.7%
4 46
 
4.6%
0 36
 
3.6%
7 35
 
3.5%
3 34
 
3.4%
8 31
 
3.1%
Other values (5) 110
 
11.1%
Hangul
ValueCountFrequency (%)
강 293
18.8%
릉 142
 
9.1%
시 130
 
8.4%
원 126
 
8.1%
도 122
 
7.8%
로 98
 
6.3%
동 71
 
4.6%
길 34
 
2.2%
경 25
 
1.6%
대 23
 
1.5%
Other values (112) 491
31.6%
None
ValueCountFrequency (%)
　 173
100.0%

지번주소
Text

Distinct110
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T17:56:14.969748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length17.713115
Min length13

Characters and Unicode

Total characters2161
Distinct characters69
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

Unique101 ?
Unique (%)82.8%

Sample

1st row강원도 강릉시 옥천동 139
2nd row강원도 강릉시 임당동 82-1
3rd row강원도 강릉시 금학동 61
4th row강원도 강릉시 포남동 1272
5th row강원도 강릉시 대전동 897-2
ValueCountFrequency (%)
강원도 122
23.6%
강릉시 122
23.6%
포남동 17
 
3.3%
임당동 13
 
2.5%
교동 12
 
2.3%
주문진읍 10
 
1.9%
옥천동 9
 
1.7%
성남동 5
 
1.0%
교항리 5
 
1.0%
노암동 5
 
1.0%
Other values (141) 198
38.2%
2023-12-12T17:56:15.638172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
397
18.4%
강 247
 
11.4%
도 124
 
5.7%
시 123
 
5.7%
릉 122
 
5.6%
원 122
 
5.6%
1 122
 
5.6%
동 101
 
4.7%
- 93
 
4.3%
2 84
 
3.9%
Other values (59) 626
29.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1190
55.1%
Decimal Number 481
22.3%
Space Separator 397
 
18.4%
Dash Punctuation 93
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 247
20.8%
도 124
10.4%
시 123
10.3%
릉 122
10.3%
원 122
10.3%
동 101
 
8.5%
리 30
 
2.5%
남 22
 
1.8%
면 20
 
1.7%
주 17
 
1.4%
Other values (47) 262
22.0%
Decimal Number
ValueCountFrequency (%)
1 122
25.4%
2 84
17.5%
3 61
12.7%
8 50
10.4%
4 42
 
8.7%
9 30
 
6.2%
0 25
 
5.2%
7 25
 
5.2%
6 23
 
4.8%
5 19
 
4.0%
Space Separator
ValueCountFrequency (%)
397
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1190
55.1%
Common 971
44.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
강 247
20.8%
도 124
10.4%
시 123
10.3%
릉 122
10.3%
원 122
10.3%
동 101
 
8.5%
리 30
 
2.5%
남 22
 
1.8%
면 20
 
1.7%
주 17
 
1.4%
Other values (47) 262
22.0%
Common
ValueCountFrequency (%)
397
40.9%
1 122
 
12.6%
- 93
 
9.6%
2 84
 
8.7%
3 61
 
6.3%
8 50
 
5.1%
4 42
 
4.3%
9 30
 
3.1%
0 25
 
2.6%
7 25
 
2.6%
Other values (2) 42
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1190
55.1%
ASCII 971
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
397
40.9%
1 122
 
12.6%
- 93
 
9.6%
2 84
 
8.7%
3 61
 
6.3%
8 50
 
5.1%
4 42
 
4.3%
9 30
 
3.1%
0 25
 
2.6%
7 25
 
2.6%
Other values (2) 42
 
4.3%
Hangul
ValueCountFrequency (%)
강 247
20.8%
도 124
10.4%
시 123
10.3%
릉 122
10.3%
원 122
10.3%
동 101
 
8.5%
리 30
 
2.5%
남 22
 
1.8%
면 20
 
1.7%
주 17
 
1.4%
Other values (47) 262
22.0%

위도
Real number (ℝ)

Distinct110
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.763826
Minimum37.521187
Maximum37.895171
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T17:56:15.841508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.521187
5-th percentile37.673119
Q137.753237
median37.757433
Q337.770238
95-th percentile37.889431
Maximum37.895171
Range0.37398368
Interquartile range (IQR)0.017001175

Descriptive statistics

Standard deviation0.057052045
Coefficient of variation (CV)0.0015107591
Kurtosis4.09474
Mean37.763826
Median Absolute Deviation (MAD)0.00816827
Skewness-0.43136636
Sum4607.1868
Variance0.0032549358
MonotonicityNot monotonic
2023-12-12T17:56:16.030299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.75567058 4
 
3.3%
37.75533369 3
 
2.5%
37.77168124 2
 
1.6%
37.75324012 2
 
1.6%
37.75369442 2
 
1.6%
37.7516651 2
 
1.6%
37.76565832 2
 
1.6%
37.77023825 2
 
1.6%
37.76063788 2
 
1.6%
37.87717828 1
 
0.8%
Other values (100) 100
82.0%
ValueCountFrequency (%)
37.5211869 1
0.8%
37.58842412 1
0.8%
37.60752517 1
0.8%
37.61052473 1
0.8%
37.63733343 1
0.8%
37.67209326 1
0.8%
37.67232791 1
0.8%
37.6881576 1
0.8%
37.68979929 1
0.8%
37.71789002 1
0.8%
ValueCountFrequency (%)
37.89517058 1
0.8%
37.8942585 1
0.8%
37.89298318 1
0.8%
37.89132386 1
0.8%
37.89118914 1
0.8%
37.89055025 1
0.8%
37.88952322 1
0.8%
37.88767757 1
0.8%
37.88095347 1
0.8%
37.87717828 1
0.8%

경도
Real number (ℝ)

Distinct110
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.89142
Minimum128.77883
Maximum129.04327
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T17:56:16.236849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.77883
5-th percentile128.82758
Q1128.87534
median128.89609
Q3128.90457
95-th percentile128.93066
Maximum129.04327
Range0.264442
Interquartile range (IQR)0.02923645

Descriptive statistics

Standard deviation0.041586406
Coefficient of variation (CV)0.00032264682
Kurtosis4.4849151
Mean128.89142
Median Absolute Deviation (MAD)0.0140407
Skewness1.1824484
Sum15724.753
Variance0.0017294292
MonotonicityNot monotonic
2023-12-12T17:56:16.466167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8971787 4
 
3.3%
128.8976399 3
 
2.5%
128.9113113 2
 
1.6%
128.8753382 2
 
1.6%
128.8940113 2
 
1.6%
128.8954621 2
 
1.6%
128.8701957 2
 
1.6%
128.9079905 2
 
1.6%
128.8980105 2
 
1.6%
128.8275741 1
 
0.8%
Other values (100) 100
82.0%
ValueCountFrequency (%)
128.7788311 1
0.8%
128.8259297 1
0.8%
128.8262646 1
0.8%
128.8262978 1
0.8%
128.8273989 1
0.8%
128.8274284 1
0.8%
128.8275741 1
0.8%
128.8276076 1
0.8%
128.8279816 1
0.8%
128.8286903 1
0.8%
ValueCountFrequency (%)
129.0432731 1
0.8%
129.0364647 1
0.8%
129.0333619 1
0.8%
129.0332858 1
0.8%
129.0321261 1
0.8%
128.9535406 1
0.8%
128.9309836 1
0.8%
128.924558 1
0.8%
128.9232563 1
0.8%
128.919478 1
0.8%

전화번호
Text

Distinct120
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T17:56:16.802433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.016393
Min length12

Characters and Unicode

Total characters1466
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

Unique118 ?
Unique (%)96.7%

Sample

1st row0507-1343-8991
2nd row033-641-1793
3rd row033-645-3502
4th row033-646-1151
5th row033-655-3810
ValueCountFrequency (%)
033-652-2005 2
 
1.6%
033-645-6671 2
 
1.6%
033-640-8700 1
 
0.8%
033-642-1777 1
 
0.8%
033-650-8023 1
 
0.8%
033-652-9966 1
 
0.8%
033-646-8764 1
 
0.8%
033-644-0135 1
 
0.8%
033-641-8251 1
 
0.8%
033-662-5044 1
 
0.8%
Other values (110) 110
90.2%
2023-12-12T17:56:17.325843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 302
20.6%
- 244
16.6%
0 221
15.1%
6 173
11.8%
4 131
8.9%
1 100
 
6.8%
5 95
 
6.5%
2 80
 
5.5%
8 48
 
3.3%
7 41
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1222
83.4%
Dash Punctuation 244
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 302
24.7%
0 221
18.1%
6 173
14.2%
4 131
10.7%
1 100
 
8.2%
5 95
 
7.8%
2 80
 
6.5%
8 48
 
3.9%
7 41
 
3.4%
9 31
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 244
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1466
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 302
20.6%
- 244
16.6%
0 221
15.1%
6 173
11.8%
4 131
8.9%
1 100
 
6.8%
5 95
 
6.5%
2 80
 
5.5%
8 48
 
3.3%
7 41
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1466
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 302
20.6%
- 244
16.6%
0 221
15.1%
6 173
11.8%
4 131
8.9%
1 100
 
6.8%
5 95
 
6.5%
2 80
 
5.5%
8 48
 
3.3%
7 41
 
2.8%

Interactions

2023-12-12T17:56:12.564131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:56:12.357402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:56:12.664275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:56:12.449548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:56:17.458799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.801
경도0.8011.000
2023-12-12T17:56:17.577626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.108
경도-0.1081.000

Missing values

2023-12-12T17:56:12.799928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:56:12.899586image/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

명칭주소지번주소위도경도전화번호
0CK저축은행 강릉지점강원도 강릉시 경강로 2156강원도 강릉시 옥천동 13937.758161128.9014650507-1343-8991
1IBK기업은행 강릉지점강원도 강릉시 경강로 2087강원도 강릉시 임당동 82-137.754469128.895269033-641-1793
2KB국민은행 강릉지점강원도 강릉시 금성로 48강원도 강릉시 금학동 6137.752618128.895746033-645-3502
3KB국민은행 포남동출장소강원도 강릉시 경강로 2352 (포남동)강원도 강릉시 포남동 127237.769305128.917911033-646-1151
4NH농협은행 강릉과학산업진흥원출장소강원도 강릉시 과학단지로 106-11 (대전동)강원도 강릉시 대전동 897-237.803271128.854876033-655-3810
5NH농협은행 강릉교동지점강원도 강릉시 강릉대로 258 (교동)강원도 강릉시 교동 139-437.760638128.89801033-641-3811
6NH농협은행 강릉권역보증센터강원도 강릉시 강릉대로 258 (교동)강원도 강릉시 교동 139-437.760638128.89801033-649-1540
7NH농협은행 강릉동부지점강원도 강릉시 하평길 56 (포남동)강원도 강릉시 포남동 1193-137.769736128.914704033-653-2251
8NH농협은행 강릉시지부강원도 강릉시 임영로 123 (성내동)강원도 강릉시 성내동 23-137.752278128.893052033-641-3801
9NH농협은행 강릉시청출장소강원도 강릉시 강릉대로 33 (홍제동)강원도 강릉시 홍제동 100137.75324128.875338033-643-2948
명칭주소지번주소위도경도전화번호
112하나금융투자 강릉지점강원도 강릉시 경강로 2071(임당동)강원도 강릉시 임당동 13937.753694128.894011033-646-5111
113하나은행 강릉중앙출장소강원도 강릉시 경강로 2071, 1층(임당동)강원도 강릉시 임당동 13937.753694128.894011033-645-2501
114하나은행 강릉지점강원도 강릉시 경강로 2110, 1층(임당동,동아빌딩)강원도 강릉시 임당동 114-237.755334128.89764033-644-1111
115한국투자증권 강릉지점강원도 강릉시 경강로 2109, 1층 (임당동,문선빌딩)강원도 강릉시 임당동 112-137.755671128.897179033-641-1414
116홍제새마을금고강원도 강릉시 토성로 116 (홍제동)강원도 강릉시 홍제동 48-737.753529128.889629033-643-4821
117홍제새마을금고남문지점강원도 강릉시 경강로 2044 (명주동)강원도 강릉시 명주동 30-737.751366128.892168033-642-4866
118홍제새마을금고유천지점강원도 강릉시 선수촌로 64-3, 105호(홍제동,유천이스턴빌딩)강원도 강릉시 홍제동 1031-437.75687128.870694033-644-4821
119우리은행 강릉지점강원도 강릉시 경강로 2097 (임당동)강원도 강릉시 임당동 8637.754958128.896103033-647-5101
120우리은행 가톨릭관동대학교출장소강원도 강릉시 범일로579번길 24, 제2학생회관내 (내곡동,가톨릭관동대학교)강원도 강릉시 내곡동 52237.737278128.872641033-641-6691
121한국은행 강릉본부강원도 강릉시 경강로 2063 (성내동)강원도 강릉시 성내동 337.753269128.893019033-640-0100