Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells28266
Missing cells (%)23.6%
Duplicate rows6
Duplicate rows (%)0.1%
Total size in memory1.0 MiB
Average record size in memory105.0 B

Variable types

Text6
Categorical4
DateTime1
Numeric1

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실) 전국, 전체 데이터의 경우 API 서비스를 이용하여 주시기 바랍니다.
Author지방자치단체
URLhttps://www.data.go.kr/data/15100062/standard.do

Alerts

Dataset has 6 (0.1%) duplicate rowsDuplicates
시군구명 is highly overall correlated with 제공기관코드 and 3 other fieldsHigh correlation
사용가능지역화폐 is highly overall correlated with 제공기관코드 and 3 other fieldsHigh correlation
제공기관명 is highly overall correlated with 제공기관코드 and 3 other fieldsHigh correlation
시도명 is highly overall correlated with 제공기관코드 and 3 other fieldsHigh correlation
제공기관코드 is highly overall correlated with 사용가능지역화폐 and 3 other fieldsHigh correlation
소재지도로명주소 has 1406 (14.1%) missing valuesMissing
소재지지번주소 has 8360 (83.6%) missing valuesMissing
업종명 has 559 (5.6%) missing valuesMissing
주요상품 has 9496 (95.0%) missing valuesMissing
전화번호 has 8445 (84.5%) missing valuesMissing

Reproduction

Analysis started2024-05-04 08:03:42.262128
Analysis finished2024-05-04 08:03:49.661937
Duration7.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가맹점명
Text

Distinct9765
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T08:03:50.373069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length28
Mean length6.8523
Min length1

Characters and Unicode

Total characters68523
Distinct characters1075
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9593 ?
Unique (%)95.9%

Sample

1st row아소비 작동 동도센트리움점
2nd row유니베라 부천상동
3rd row금강가구점(파로마가구)
4th row세븐일레븐 경산신대부영점
5th row하얀섬 금강민물
ValueCountFrequency (%)
세븐일레븐 55
 
0.4%
주식회사 52
 
0.4%
47
 
0.4%
지에스25 46
 
0.4%
이마트24 46
 
0.4%
씨유 30
 
0.2%
경산점 30
 
0.2%
유한회사 24
 
0.2%
카페 21
 
0.2%
씨유(cu 20
 
0.2%
Other values (10709) 12001
97.0%
2024-05-04T08:03:52.231554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2386
 
3.5%
점 1618
 
2.4%
이 1419
 
2.1%
스 1271
 
1.9%
원 971
 
1.4%
리 873
 
1.3%
산 849
 
1.2%
어 775
 
1.1%
( 737
 
1.1%
) 724
 
1.1%
Other values (1065) 56900
83.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59922
87.4%
Space Separator 2386
 
3.5%
Decimal Number 1879
 
2.7%
Uppercase Letter 1685
 
2.5%
Lowercase Letter 983
 
1.4%
Open Punctuation 755
 
1.1%
Close Punctuation 742
 
1.1%
Other Punctuation 140
 
0.2%
Dash Punctuation 13
 
< 0.1%
Other Symbol 8
 
< 0.1%
Other values (3) 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1618
 
2.7%
이 1419
 
2.4%
스 1271
 
2.1%
원 971
 
1.6%
리 873
 
1.5%
산 849
 
1.4%
어 775
 
1.3%
아 688
 
1.1%
사 650
 
1.1%
대 648
 
1.1%
Other values (984) 50160
83.7%
Uppercase Letter
ValueCountFrequency (%)
C 166
 
9.9%
S 145
 
8.6%
G 113
 
6.7%
E 107
 
6.4%
O 99
 
5.9%
A 87
 
5.2%
U 87
 
5.2%
I 77
 
4.6%
T 75
 
4.5%
P 74
 
4.4%
Other values (16) 655
38.9%
Lowercase Letter
ValueCountFrequency (%)
e 133
13.5%
a 116
11.8%
o 87
 
8.9%
n 68
 
6.9%
i 66
 
6.7%
r 60
 
6.1%
s 56
 
5.7%
l 48
 
4.9%
t 44
 
4.5%
d 39
 
4.0%
Other values (16) 266
27.1%
Decimal Number
ValueCountFrequency (%)
5 368
19.6%
2 327
17.4%
1 308
16.4%
3 285
15.2%
4 142
 
7.6%
0 125
 
6.7%
8 97
 
5.2%
7 88
 
4.7%
9 76
 
4.0%
6 63
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 52
37.1%
& 48
34.3%
, 21
15.0%
/ 10
 
7.1%
; 6
 
4.3%
? 2
 
1.4%
: 1
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 737
97.6%
[ 17
 
2.3%
（ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 724
97.6%
] 17
 
2.3%
） 1
 
0.1%
Space Separator
ValueCountFrequency (%)
2386
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 8
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59922
87.4%
Common 5925
 
8.6%
Latin 2668
 
3.9%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1618
 
2.7%
이 1419
 
2.4%
스 1271
 
2.1%
원 971
 
1.6%
리 873
 
1.5%
산 849
 
1.4%
어 775
 
1.3%
아 688
 
1.1%
사 650
 
1.1%
대 648
 
1.1%
Other values (978) 50160
83.7%
Latin
ValueCountFrequency (%)
C 166
 
6.2%
S 145
 
5.4%
e 133
 
5.0%
a 116
 
4.3%
G 113
 
4.2%
E 107
 
4.0%
O 99
 
3.7%
o 87
 
3.3%
A 87
 
3.3%
U 87
 
3.3%
Other values (42) 1528
57.3%
Common
ValueCountFrequency (%)
2386
40.3%
( 737
 
12.4%
) 724
 
12.2%
5 368
 
6.2%
2 327
 
5.5%
1 308
 
5.2%
3 285
 
4.8%
4 142
 
2.4%
0 125
 
2.1%
8 97
 
1.6%
Other values (18) 426
 
7.2%
Han
ValueCountFrequency (%)
家 2
25.0%
宮 1
12.5%
本 1
12.5%
生 1
12.5%
月 1
12.5%
王 1
12.5%
美 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59914
87.4%
ASCII 8586
 
12.5%
None 10
 
< 0.1%
CJK 8
 
< 0.1%
Punctuation 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2386
27.8%
( 737
 
8.6%
) 724
 
8.4%
5 368
 
4.3%
2 327
 
3.8%
1 308
 
3.6%
3 285
 
3.3%
C 166
 
1.9%
S 145
 
1.7%
4 142
 
1.7%
Other values (67) 2998
34.9%
Hangul
ValueCountFrequency (%)
점 1618
 
2.7%
이 1419
 
2.4%
스 1271
 
2.1%
원 971
 
1.6%
리 873
 
1.5%
산 849
 
1.4%
어 775
 
1.3%
아 688
 
1.1%
사 650
 
1.1%
대 648
 
1.1%
Other values (977) 50152
83.7%
None
ValueCountFrequency (%)
㈜ 8
80.0%
） 1
 
10.0%
（ 1
 
10.0%
Punctuation
ValueCountFrequency (%)
’ 5
100.0%
CJK
ValueCountFrequency (%)
家 2
25.0%
宮 1
12.5%
本 1
12.5%
生 1
12.5%
月 1
12.5%
王 1
12.5%
美 1
12.5%

사용가능지역화폐
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부천페이
3215 
경산사랑카드
2086 
군산사랑상품권
1779 
파주페이
1191 
진도아리랑상품권
335 
Other values (10)
1394 

Length

Max length19
Median length9
Mean length5.8341
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row부천페이
2nd row부천페이
3rd row군산사랑상품권
4th row경산사랑카드
5th row무주사랑상품권

Common Values

ValueCountFrequency (%)
부천페이 3215
32.1%
경산사랑카드 2086
20.9%
군산사랑상품권 1779
17.8%
파주페이 1191
 
11.9%
진도아리랑상품권 335
 
3.4%
완주사랑상품권 273
 
2.7%
증평사랑으뜸상품권 269
 
2.7%
여수사랑상품권 250
 
2.5%
카드형 태백사랑상품권+태백사랑상품권 234
 
2.3%
무주사랑상품권 224
 
2.2%
Other values (5) 144
 
1.4%

Length

2024-05-04T08:03:52.871011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부천페이 3215
31.4%
경산사랑카드 2086
20.4%
군산사랑상품권 1779
17.4%
파주페이 1191
 
11.6%
진도아리랑상품권 335
 
3.3%
완주사랑상품권 273
 
2.7%
증평사랑으뜸상품권 269
 
2.6%
여수사랑상품권 250
 
2.4%
카드형 234
 
2.3%
태백사랑상품권+태백사랑상품권 234
 
2.3%
Other values (6) 368
 
3.6%

시도명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
4410 
전북특별자치도
2276 
경상북도
2086 
전라남도
585 
충청북도
 
270
Other values (4)
 
373

Length

Max length7
Median length5
Mean length4.3131
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도
2nd row경기도
3rd row전북특별자치도
4th row경상북도
5th row전북특별자치도

Common Values

ValueCountFrequency (%)
경기도 4410
44.1%
전북특별자치도 2276
22.8%
경상북도 2086
20.9%
전라남도 585
 
5.9%
충청북도 270
 
2.7%
강원특별자치도 234
 
2.3%
경상남도 128
 
1.3%
인천광역시 8
 
0.1%
서울특별시 3
 
< 0.1%

Length

2024-05-04T08:03:53.692988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:03:54.314791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 4410
44.1%
전북특별자치도 2276
22.8%
경상북도 2086
20.9%
전라남도 585
 
5.9%
충청북도 270
 
2.7%
강원특별자치도 234
 
2.3%
경상남도 128
 
1.3%
인천광역시 8
 
0.1%
서울특별시 3
 
< 0.1%

시군구명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부천시
3215 
경산시
2086 
군산시
1779 
파주시
1191 
진도군
335 
Other values (11)
1394 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row부천시
2nd row부천시
3rd row군산시
4th row경산시
5th row무주군

Common Values

ValueCountFrequency (%)
부천시 3215
32.1%
경산시 2086
20.9%
군산시 1779
17.8%
파주시 1191
 
11.9%
진도군 335
 
3.4%
완주군 273
 
2.7%
증평군 269
 
2.7%
여수시 250
 
2.5%
태백시 234
 
2.3%
무주군 224
 
2.2%
Other values (6) 144
 
1.4%

Length

2024-05-04T08:03:55.063019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부천시 3215
32.1%
경산시 2086
20.9%
군산시 1779
17.8%
파주시 1191
 
11.9%
진도군 335
 
3.4%
완주군 273
 
2.7%
증평군 269
 
2.7%
여수시 250
 
2.5%
태백시 234
 
2.3%
무주군 224
 
2.2%
Other values (6) 144
 
1.4%

소재지도로명주소
Text

MISSING 

Distinct7916
Distinct (%)92.1%
Missing1406
Missing (%)14.1%
Memory size156.2 KiB
2024-05-04T08:03:56.094670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length57
Mean length27.849081
Min length14

Characters and Unicode

Total characters239335
Distinct characters548
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7557 ?
Unique (%)87.9%

Sample

1st row경기도 부천시 오정구 삼작로 465, 108동 401호 (작동,부천동도센트리움까치울숲)
2nd row경기도 부천시 원미구 상일로 100, 501호 (상동,부건프라자)
3rd row전북특별자치도 군산시 장미1길 16
4th row경상북도 경산시 압량읍 압독2로 57 103호, 104호
5th row전북특별자치도 무주군 적상면 괴목로 568
ValueCountFrequency (%)
경기도 3332
 
6.9%
부천시 3112
 
6.4%
전북특별자치도 2260
 
4.7%
원미구 1819
 
3.7%
군산시 1779
 
3.7%
경산시 1777
 
3.7%
경상북도 1777
 
3.7%
1층 1583
 
3.3%
소사구 732
 
1.5%
전라남도 585
 
1.2%
Other values (6891) 29751
61.3%
2024-05-04T08:03:57.864030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39947
 
16.7%
1 10621
 
4.4%
도 9437
 
3.9%
경 7658
 
3.2%
시 7576
 
3.2%
로 7040
 
2.9%
동 6854
 
2.9%
2 5966
 
2.5%
) 5113
 
2.1%
( 5107
 
2.1%
Other values (538) 134016
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 143151
59.8%
Space Separator 39947
 
16.7%
Decimal Number 38963
 
16.3%
Close Punctuation 5113
 
2.1%
Open Punctuation 5107
 
2.1%
Other Punctuation 5050
 
2.1%
Dash Punctuation 1670
 
0.7%
Uppercase Letter 249
 
0.1%
Lowercase Letter 56
 
< 0.1%
Math Symbol 29
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 9437
 
6.6%
경 7658
 
5.3%
시 7576
 
5.3%
로 7040
 
4.9%
동 6854
 
4.8%
북 4420
 
3.1%
길 4336
 
3.0%
산 4303
 
3.0%
부 4212
 
2.9%
천 3898
 
2.7%
Other values (480) 83417
58.3%
Uppercase Letter
ValueCountFrequency (%)
B 73
29.3%
A 64
25.7%
I 29
 
11.6%
C 11
 
4.4%
S 11
 
4.4%
T 8
 
3.2%
D 8
 
3.2%
F 8
 
3.2%
O 8
 
3.2%
H 4
 
1.6%
Other values (12) 25
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
e 16
28.6%
n 9
16.1%
o 4
 
7.1%
a 3
 
5.4%
t 3
 
5.4%
c 3
 
5.4%
p 2
 
3.6%
m 2
 
3.6%
i 2
 
3.6%
u 2
 
3.6%
Other values (8) 10
17.9%
Decimal Number
ValueCountFrequency (%)
1 10621
27.3%
2 5966
15.3%
3 4167
 
10.7%
0 3822
 
9.8%
4 3137
 
8.1%
5 2771
 
7.1%
7 2339
 
6.0%
6 2245
 
5.8%
8 1949
 
5.0%
9 1946
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 4826
95.6%
. 223
 
4.4%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
39947
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5113
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5107
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1670
100.0%
Math Symbol
ValueCountFrequency (%)
~ 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 143151
59.8%
Common 95879
40.1%
Latin 305
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 9437
 
6.6%
경 7658
 
5.3%
시 7576
 
5.3%
로 7040
 
4.9%
동 6854
 
4.8%
북 4420
 
3.1%
길 4336
 
3.0%
산 4303
 
3.0%
부 4212
 
2.9%
천 3898
 
2.7%
Other values (480) 83417
58.3%
Latin
ValueCountFrequency (%)
B 73
23.9%
A 64
21.0%
I 29
 
9.5%
e 16
 
5.2%
C 11
 
3.6%
S 11
 
3.6%
n 9
 
3.0%
T 8
 
2.6%
D 8
 
2.6%
F 8
 
2.6%
Other values (30) 68
22.3%
Common
ValueCountFrequency (%)
39947
41.7%
1 10621
 
11.1%
2 5966
 
6.2%
) 5113
 
5.3%
( 5107
 
5.3%
, 4826
 
5.0%
3 4167
 
4.3%
0 3822
 
4.0%
4 3137
 
3.3%
5 2771
 
2.9%
Other values (8) 10402
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 143151
59.8%
ASCII 96184
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39947
41.5%
1 10621
 
11.0%
2 5966
 
6.2%
) 5113
 
5.3%
( 5107
 
5.3%
, 4826
 
5.0%
3 4167
 
4.3%
0 3822
 
4.0%
4 3137
 
3.3%
5 2771
 
2.9%
Other values (48) 10707
 
11.1%
Hangul
ValueCountFrequency (%)
도 9437
 
6.6%
경 7658
 
5.3%
시 7576
 
5.3%
로 7040
 
4.9%
동 6854
 
4.8%
북 4420
 
3.1%
길 4336
 
3.0%
산 4303
 
3.0%
부 4212
 
2.9%
천 3898
 
2.7%
Other values (480) 83417
58.3%

소재지지번주소
Text

MISSING 

Distinct1608
Distinct (%)98.0%
Missing8360
Missing (%)83.6%
Memory size156.2 KiB
2024-05-04T08:03:58.963120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length49
Mean length25.929878
Min length14

Characters and Unicode

Total characters42525
Distinct characters408
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1580 ?
Unique (%)96.3%

Sample

1st row경상북도 경산시 하양읍 금락리 53-2
2nd row강원특별자치도 태백시 황지동 368-23
3rd row경기도 파주시 책향기숲길 55 ,1층 (동패동)
4th row강원특별자치도 태백시 황지동 666-11
5th row경기도 파주시 광탄면 신산리 20-1
ValueCountFrequency (%)
경기도 1078
 
11.9%
파주시 975
 
10.8%
경산시 309
 
3.4%
경상북도 309
 
3.4%
강원특별자치도 234
 
2.6%
태백시 234
 
2.6%
1층 195
 
2.2%
황지동 177
 
2.0%
금촌동 104
 
1.2%
부천시 103
 
1.1%
Other values (2323) 5319
58.9%
2024-05-04T08:04:00.682673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7400
 
17.4%
1 2013
 
4.7%
경 1722
 
4.0%
도 1675
 
3.9%
시 1669
 
3.9%
동 1558
 
3.7%
2 1134
 
2.7%
파 1122
 
2.6%
기 1111
 
2.6%
주 1065
 
2.5%
Other values (398) 22056
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24270
57.1%
Decimal Number 8153
 
19.2%
Space Separator 7400
 
17.4%
Dash Punctuation 887
 
2.1%
Other Punctuation 614
 
1.4%
Open Punctuation 548
 
1.3%
Close Punctuation 548
 
1.3%
Uppercase Letter 95
 
0.2%
Math Symbol 9
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 1722
 
7.1%
도 1675
 
6.9%
시 1669
 
6.9%
동 1558
 
6.4%
파 1122
 
4.6%
기 1111
 
4.6%
주 1065
 
4.4%
로 634
 
2.6%
산 563
 
2.3%
상 482
 
2.0%
Other values (364) 12669
52.2%
Uppercase Letter
ValueCountFrequency (%)
B 25
26.3%
A 22
23.2%
I 7
 
7.4%
F 7
 
7.4%
N 5
 
5.3%
P 5
 
5.3%
R 5
 
5.3%
C 4
 
4.2%
G 4
 
4.2%
K 4
 
4.2%
Other values (4) 7
 
7.4%
Decimal Number
ValueCountFrequency (%)
1 2013
24.7%
2 1134
13.9%
0 960
11.8%
3 831
10.2%
4 697
 
8.5%
5 610
 
7.5%
6 532
 
6.5%
7 523
 
6.4%
8 460
 
5.6%
9 393
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 606
98.7%
. 6
 
1.0%
/ 2
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 8
88.9%
+ 1
 
11.1%
Space Separator
ValueCountFrequency (%)
7400
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 887
100.0%
Open Punctuation
ValueCountFrequency (%)
( 548
100.0%
Close Punctuation
ValueCountFrequency (%)
) 548
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24269
57.1%
Common 18159
42.7%
Latin 96
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 1722
 
7.1%
도 1675
 
6.9%
시 1669
 
6.9%
동 1558
 
6.4%
파 1122
 
4.6%
기 1111
 
4.6%
주 1065
 
4.4%
로 634
 
2.6%
산 563
 
2.3%
상 482
 
2.0%
Other values (363) 12668
52.2%
Common
ValueCountFrequency (%)
7400
40.8%
1 2013
 
11.1%
2 1134
 
6.2%
0 960
 
5.3%
- 887
 
4.9%
3 831
 
4.6%
4 697
 
3.8%
5 610
 
3.4%
, 606
 
3.3%
( 548
 
3.0%
Other values (9) 2473
 
13.6%
Latin
ValueCountFrequency (%)
B 25
26.0%
A 22
22.9%
I 7
 
7.3%
F 7
 
7.3%
N 5
 
5.2%
P 5
 
5.2%
R 5
 
5.2%
C 4
 
4.2%
G 4
 
4.2%
K 4
 
4.2%
Other values (5) 8
 
8.3%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24269
57.1%
ASCII 18255
42.9%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7400
40.5%
1 2013
 
11.0%
2 1134
 
6.2%
0 960
 
5.3%
- 887
 
4.9%
3 831
 
4.6%
4 697
 
3.8%
5 610
 
3.3%
, 606
 
3.3%
( 548
 
3.0%
Other values (24) 2569
 
14.1%
Hangul
ValueCountFrequency (%)
경 1722
 
7.1%
도 1675
 
6.9%
시 1669
 
6.9%
동 1558
 
6.4%
파 1122
 
4.6%
기 1111
 
4.6%
주 1065
 
4.4%
로 634
 
2.6%
산 563
 
2.3%
상 482
 
2.0%
Other values (363) 12668
52.2%
CJK
ValueCountFrequency (%)
內 1
100.0%

업종명
Text

MISSING 

Distinct577
Distinct (%)6.1%
Missing559
Missing (%)5.6%
Memory size156.2 KiB
2024-05-04T08:04:01.496855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length24
Mean length6.3832221
Min length2

Characters and Unicode

Total characters60264
Distinct characters294
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique208 ?
Unique (%)2.2%

Sample

1st row기타교육.교습.학원
2nd row화장품
3rd row소매업
4th row소매/편의점
5th row슈퍼마켓.마트
ValueCountFrequency (%)
소매업 843
 
8.1%
음식점업 840
 
8.1%
일반음식점 701
 
6.8%
개인서비스업 593
 
5.7%
일반음식점/한식 442
 
4.3%
일반한식 212
 
2.0%
편의점 199
 
1.9%
미용실(두발전문 175
 
1.7%
기타 164
 
1.6%
일반음식점/일반음식점기타 162
 
1.6%
Other values (629) 6021
58.2%
2024-05-04T08:04:02.722893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 4122
 
6.8%
식 4101
 
6.8%
음 3199
 
5.3%
업 2870
 
4.8%
/ 2743
 
4.6%
일 2212
 
3.7%
반 2148
 
3.6%
기 1609
 
2.7%
스 1298
 
2.2%
비 1203
 
2.0%
Other values (284) 34759
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54600
90.6%
Other Punctuation 4189
 
7.0%
Space Separator 912
 
1.5%
Close Punctuation 256
 
0.4%
Open Punctuation 256
 
0.4%
Uppercase Letter 29
 
< 0.1%
Math Symbol 16
 
< 0.1%
Decimal Number 5
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 4122
 
7.5%
식 4101
 
7.5%
음 3199
 
5.9%
업 2870
 
5.3%
일 2212
 
4.1%
반 2148
 
3.9%
기 1609
 
2.9%
스 1298
 
2.4%
비 1203
 
2.2%
매 1180
 
2.2%
Other values (262) 30658
56.2%
Uppercase Letter
ValueCountFrequency (%)
P 9
31.0%
C 8
27.6%
O 3
 
10.3%
L 2
 
6.9%
S 2
 
6.9%
A 2
 
6.9%
K 1
 
3.4%
G 1
 
3.4%
I 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
/ 2743
65.5%
. 782
 
18.7%
, 608
 
14.5%
· 36
 
0.9%
． 20
 
0.5%
Decimal Number
ValueCountFrequency (%)
4 3
60.0%
2 1
 
20.0%
1 1
 
20.0%
Space Separator
ValueCountFrequency (%)
912
100.0%
Close Punctuation
ValueCountFrequency (%)
) 256
100.0%
Open Punctuation
ValueCountFrequency (%)
( 256
100.0%
Math Symbol
ValueCountFrequency (%)
+ 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54600
90.6%
Common 5635
 
9.4%
Latin 29
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 4122
 
7.5%
식 4101
 
7.5%
음 3199
 
5.9%
업 2870
 
5.3%
일 2212
 
4.1%
반 2148
 
3.9%
기 1609
 
2.9%
스 1298
 
2.4%
비 1203
 
2.2%
매 1180
 
2.2%
Other values (262) 30658
56.2%
Common
ValueCountFrequency (%)
/ 2743
48.7%
912
 
16.2%
. 782
 
13.9%
, 608
 
10.8%
) 256
 
4.5%
( 256
 
4.5%
· 36
 
0.6%
． 20
 
0.4%
+ 16
 
0.3%
4 3
 
0.1%
Other values (3) 3
 
0.1%
Latin
ValueCountFrequency (%)
P 9
31.0%
C 8
27.6%
O 3
 
10.3%
L 2
 
6.9%
S 2
 
6.9%
A 2
 
6.9%
K 1
 
3.4%
G 1
 
3.4%
I 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54584
90.6%
ASCII 5608
 
9.3%
None 56
 
0.1%
Compat Jamo 16
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 4122
 
7.6%
식 4101
 
7.5%
음 3199
 
5.9%
업 2870
 
5.3%
일 2212
 
4.1%
반 2148
 
3.9%
기 1609
 
2.9%
스 1298
 
2.4%
비 1203
 
2.2%
매 1180
 
2.2%
Other values (261) 30642
56.1%
ASCII
ValueCountFrequency (%)
/ 2743
48.9%
912
 
16.3%
. 782
 
13.9%
, 608
 
10.8%
) 256
 
4.6%
( 256
 
4.6%
+ 16
 
0.3%
P 9
 
0.2%
C 8
 
0.1%
O 3
 
0.1%
Other values (10) 15
 
0.3%
None
ValueCountFrequency (%)
· 36
64.3%
． 20
35.7%
Compat Jamo
ValueCountFrequency (%)
ㆍ 16
100.0%

주요상품
Text

MISSING 

Distinct90
Distinct (%)17.9%
Missing9496
Missing (%)95.0%
Memory size156.2 KiB
2024-05-04T08:04:03.265593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length3.7718254
Min length2

Characters and Unicode

Total characters1901
Distinct characters136
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

Unique51 ?
Unique (%)10.1%

Sample

1st row철물점
2nd row시설대여업
3rd row주방기구점
4th row음식점업
5th row소매업
ValueCountFrequency (%)
음식점업 113
22.3%
소매업 86
17.0%
개인서비스업 43
 
8.5%
한식 35
 
6.9%
미용원 15
 
3.0%
일반음식점 15
 
3.0%
일반주점 14
 
2.8%
교육서비스업 11
 
2.2%
기타숙박업 7
 
1.4%
정육점 7
 
1.4%
Other values (80) 160
31.6%
2024-05-04T08:04:04.214265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 287
15.1%
점 185
 
9.7%
식 171
 
9.0%
음 141
 
7.4%
소 95
 
5.0%
매 93
 
4.9%
비 63
 
3.3%
스 63
 
3.3%
서 59
 
3.1%
인 52
 
2.7%
Other values (126) 692
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1899
99.9%
Space Separator 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 287
15.1%
점 185
 
9.7%
식 171
 
9.0%
음 141
 
7.4%
소 95
 
5.0%
매 93
 
4.9%
비 63
 
3.3%
스 63
 
3.3%
서 59
 
3.1%
인 52
 
2.7%
Other values (125) 690
36.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1899
99.9%
Common 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 287
15.1%
점 185
 
9.7%
식 171
 
9.0%
음 141
 
7.4%
소 95
 
5.0%
매 93
 
4.9%
비 63
 
3.3%
스 63
 
3.3%
서 59
 
3.1%
인 52
 
2.7%
Other values (125) 690
36.3%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1899
99.9%
ASCII 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 287
15.1%
점 185
 
9.7%
식 171
 
9.0%
음 141
 
7.4%
소 95
 
5.0%
매 93
 
4.9%
비 63
 
3.3%
스 63
 
3.3%
서 59
 
3.1%
인 52
 
2.7%
Other values (125) 690
36.3%
ASCII
ValueCountFrequency (%)
2
100.0%

전화번호
Text

MISSING 

Distinct1222
Distinct (%)78.6%
Missing8445
Missing (%)84.5%
Memory size156.2 KiB
2024-05-04T08:04:05.031862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.17492
Min length11

Characters and Unicode

Total characters18932
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

Unique1202 ?
Unique (%)77.3%

Sample

1st row031-945-3395
2nd row033-553-7030
3rd row031-0000-0000
4th row031-949-6900
5th row031-0000-0000
ValueCountFrequency (%)
031-0000-0000 213
 
13.7%
031-000-0000 92
 
5.9%
02-1577-8007 7
 
0.5%
02-1577-0711 6
 
0.4%
02-1577-0000 4
 
0.3%
031-943-5057 3
 
0.2%
033-553-3269 2
 
0.1%
031-941-4631 2
 
0.1%
031-943-9507 2
 
0.1%
063-261-4277 2
 
0.1%
Other values (1212) 1222
78.6%
2024-05-04T08:04:06.283194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4733
25.0%
- 3110
16.4%
3 2433
12.9%
1 1849
 
9.8%
9 1315
 
6.9%
5 1271
 
6.7%
4 1183
 
6.2%
2 1042
 
5.5%
6 705
 
3.7%
7 681
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15822
83.6%
Dash Punctuation 3110
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4733
29.9%
3 2433
15.4%
1 1849
 
11.7%
9 1315
 
8.3%
5 1271
 
8.0%
4 1183
 
7.5%
2 1042
 
6.6%
6 705
 
4.5%
7 681
 
4.3%
8 610
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 3110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18932
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4733
25.0%
- 3110
16.4%
3 2433
12.9%
1 1849
 
9.8%
9 1315
 
6.9%
5 1271
 
6.7%
4 1183
 
6.2%
2 1042
 
5.5%
6 705
 
3.7%
7 681
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18932
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4733
25.0%
- 3110
16.4%
3 2433
12.9%
1 1849
 
9.8%
9 1315
 
6.9%
5 1271
 
6.7%
4 1183
 
6.2%
2 1042
 
5.5%
6 705
 
3.7%
7 681
 
3.6%

데이터기준일자
Date

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-08-01 00:00:00
Maximum2024-02-16 00:00:00
2024-05-04T08:04:06.685431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:07.002076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

제공기관코드
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4475284
Minimum3140000
Maximum6280000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T08:04:07.275131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3140000
5-th percentile3860000
Q13860000
median4671000
Q35000000
95-th percentile5130000
Maximum6280000
Range3140000
Interquartile range (IQR)1140000

Descriptive statistics

Standard deviation551014.2
Coefficient of variation (CV)0.12312385
Kurtosis-1.3455202
Mean4475284
Median Absolute Deviation (MAD)459000
Skewness0.2088292
Sum4.475284 × 1010
Variance3.0361665 × 1011
MonotonicityNot monotonic
2024-05-04T08:04:07.664748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3860000 3215
32.1%
5130000 2086
20.9%
4671000 1779
17.8%
4060000 1191
 
11.9%
5000000 335
 
3.4%
4721000 273
 
2.7%
5570000 269
 
2.7%
4810000 250
 
2.5%
4221000 234
 
2.3%
4741000 224
 
2.2%
Other values (5) 144
 
1.4%
ValueCountFrequency (%)
3140000 3
 
< 0.1%
3860000 3215
32.1%
4060000 1191
 
11.9%
4170000 4
 
< 0.1%
4221000 234
 
2.3%
4450000 1
 
< 0.1%
4671000 1779
17.8%
4721000 273
 
2.7%
4741000 224
 
2.2%
4810000 250
 
2.5%
ValueCountFrequency (%)
6280000 8
 
0.1%
5570000 269
 
2.7%
5480000 128
 
1.3%
5130000 2086
20.9%
5000000 335
 
3.4%
4810000 250
 
2.5%
4741000 224
 
2.2%
4721000 273
 
2.7%
4671000 1779
17.8%
4450000 1
 
< 0.1%

제공기관명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도 부천시
3215 
경상북도 경산시
2086 
전북특별자치도 군산시
1779 
경기도 파주시
1191 
전라남도 진도군
335 
Other values (10)
1394 

Length

Max length11
Median length9
Mean length8.3099
Min length5

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row경기도 부천시
2nd row경기도 부천시
3rd row전북특별자치도 군산시
4th row경상북도 경산시
5th row전북특별자치도 무주군

Common Values

ValueCountFrequency (%)
경기도 부천시 3215
32.1%
경상북도 경산시 2086
20.9%
전북특별자치도 군산시 1779
17.8%
경기도 파주시 1191
 
11.9%
전라남도 진도군 335
 
3.4%
전북특별자치도 완주군 273
 
2.7%
충청북도 증평군 269
 
2.7%
전라남도 여수시 250
 
2.5%
강원특별자치도 태백시 234
 
2.3%
전북특별자치도 무주군 224
 
2.2%
Other values (5) 144
 
1.4%

Length

2024-05-04T08:04:08.103636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 4410
22.1%
부천시 3215
16.1%
전북특별자치도 2276
11.4%
경상북도 2086
10.4%
경산시 2086
10.4%
군산시 1779
8.9%
파주시 1191
 
6.0%
전라남도 585
 
2.9%
진도군 335
 
1.7%
완주군 273
 
1.4%
Other values (13) 1756
 
8.8%

Interactions

2024-05-04T08:03:47.225860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T08:04:08.445089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용가능지역화폐시도명시군구명주요상품데이터기준일자제공기관코드제공기관명
사용가능지역화폐1.0001.0001.0001.0001.0001.0001.000
시도명1.0001.0001.0001.0001.0000.9771.000
시군구명1.0001.0001.0001.0001.0001.0001.000
주요상품1.0001.0001.0001.0001.0001.0001.000
데이터기준일자1.0001.0001.0001.0001.0001.0001.000
제공기관코드1.0000.9771.0001.0001.0001.0001.000
제공기관명1.0001.0001.0001.0001.0001.0001.000
2024-05-04T08:04:08.749607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명사용가능지역화폐제공기관명시도명
시군구명1.0001.0001.0001.000
사용가능지역화폐1.0001.0001.0001.000
제공기관명1.0001.0001.0001.000
시도명1.0001.0001.0001.000
2024-05-04T08:04:09.011554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제공기관코드사용가능지역화폐시도명시군구명제공기관명
제공기관코드1.0001.0000.9561.0001.000
사용가능지역화폐1.0001.0001.0001.0001.000
시도명0.9561.0001.0001.0001.000
시군구명1.0001.0001.0001.0001.000
제공기관명1.0001.0001.0001.0001.000

Missing values

2024-05-04T08:03:47.871127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T08:03:48.847203image/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.
2024-05-04T08:03:49.434173image/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

가맹점명사용가능지역화폐시도명시군구명소재지도로명주소소재지지번주소업종명주요상품전화번호데이터기준일자제공기관코드제공기관명
34856아소비 작동 동도센트리움점부천페이경기도부천시경기도 부천시 오정구 삼작로 465, 108동 401호 (작동,부천동도센트리움까치울숲)<NA>기타교육.교습.학원<NA><NA>2024-01-253860000경기도 부천시
31491유니베라 부천상동부천페이경기도부천시경기도 부천시 원미구 상일로 100, 501호 (상동,부건프라자)<NA>화장품<NA><NA>2024-01-253860000경기도 부천시
26739금강가구점(파로마가구)군산사랑상품권전북특별자치도군산시전북특별자치도 군산시 장미1길 16<NA>소매업<NA><NA>2024-01-154671000전북특별자치도 군산시
4845세븐일레븐 경산신대부영점경산사랑카드경상북도경산시경상북도 경산시 압량읍 압독2로 57 103호, 104호<NA>소매/편의점<NA><NA>2022-08-015130000경상북도 경산시
36993하얀섬 금강민물무주사랑상품권전북특별자치도무주군전북특별자치도 무주군 적상면 괴목로 568<NA><NA><NA><NA>2024-01-244741000전북특별자치도 무주군
24428제일할인마트부천페이경기도부천시경기도 부천시 원미구 석천로30번길 44, 1층 (상동,일이빌딩)<NA>슈퍼마켓.마트<NA><NA>2024-01-253860000경기도 부천시
5311쌀전식육점경산사랑카드경상북도경산시<NA>경상북도 경산시 하양읍 금락리 53-2음료식품/정육점<NA><NA>2022-08-015130000경상북도 경산시
18246뽀얀세탁군산사랑상품권전북특별자치도군산시전북특별자치도 군산시 옥산면 월명로 69<NA>개인서비스업<NA><NA>2024-01-154671000전북특별자치도 군산시
27425전북31바5560군산사랑상품권전북특별자치도군산시전북특별자치도 군산시 구암3.1로 321(구암동)<NA>개인서비스업<NA><NA>2024-01-154671000전북특별자치도 군산시
39224송서방견과류부천페이경기도부천시경기도 부천시 원미구 조종로49번길 5, 1층 (원미동)<NA>기타식음료품<NA><NA>2024-01-253860000경기도 부천시
가맹점명사용가능지역화폐시도명시군구명소재지도로명주소소재지지번주소업종명주요상품전화번호데이터기준일자제공기관코드제공기관명
8031시크릿경산사랑카드경상북도경산시경상북도 경산시 둥지로 34 111동 201호<NA>일반음식점/일반음식점기타<NA><NA>2022-08-015130000경상북도 경산시
37730휴앤유매점부천페이경기도부천시경기도 부천시 소사구 심곡로10번길 63, 지하층 (송내동)<NA>기타종합소매점<NA><NA>2024-01-253860000경기도 부천시
17559153커피부천페이경기도부천시경기도 부천시 소사구 송내대로42번길 27, 1층 102호 (송내동)<NA>커피전문점<NA><NA>2024-01-253860000경기도 부천시
25568이티시부천페이경기도부천시경기도 부천시 소사구 소사로160번길 59 (소사본동)<NA>커피전문점<NA><NA>2024-01-253860000경기도 부천시
45935더폰파주페이경기도파주시<NA>경기도 파주시 조리읍 대원로 24, 다동통신기기<NA>031-944-90582023-01-254060000경기도 파주시
42136카앤피플 부천원미구5호점부천페이경기도부천시경기도 부천시 원미구 심중로123번길 20-3 (중동)<NA>세차장<NA><NA>2024-01-253860000경기도 부천시
30295풍년어탕국수부천페이경기도부천시경기도 부천시 오정구 성오로 34-1, 1층 (원종동)<NA>일반음식점<NA><NA>2024-01-253860000경기도 부천시
20749아키수학교습소군산사랑상품권전북특별자치도군산시전북특별자치도 군산시 미장남로 100(미장동)<NA>교육서비스업<NA><NA>2024-01-154671000전북특별자치도 군산시
20051경제공인중개사사무소군산사랑상품권전북특별자치도군산시전북특별자치도 군산시 팔마로 210(경장동)<NA>기타<NA><NA>2024-01-154671000전북특별자치도 군산시
16608밤마리오광대 영농조합법인합천사랑상품권경상남도합천군경상남도 합천군 덕곡면 율지2길 13-7<NA>그 외 기타 오락관련 서비스업<NA><NA>2024-02-165480000경상남도 합천군

Duplicate rows

Most frequently occurring

가맹점명사용가능지역화폐시도명시군구명소재지도로명주소소재지지번주소업종명주요상품전화번호데이터기준일자제공기관코드제공기관명# duplicates
4진도군청(진도명품관 판매장)진도아리랑상품권전라남도진도군전라남도 진도군 진도읍 남동1길 40-18<NA><NA><NA><NA>2022-08-245000000전라남도 진도군4
0씨유진도지산중앙점진도아리랑상품권전라남도진도군전라남도 진도군 지산면 지산로 1189<NA><NA><NA><NA>2022-08-245000000전라남도 진도군2
1아모레경산사랑카드경상북도경산시<NA>경상북도 경산시 옥산동 133-6 선방빌딩 3층미용/화장품점<NA><NA>2022-08-015130000경상북도 경산시2
2전혜주 머리터경산사랑카드경상북도경산시경상북도 경산시 원효로36길 55-1<NA>미용/미용원<NA><NA>2022-08-015130000경상북도 경산시2
3젠경산사랑카드경상북도경산시경상북도 경산시 경산로44길 3-5<NA>숙박/기타숙박업<NA><NA>2022-08-015130000경상북도 경산시2
5진도군청(진도항판매장)진도아리랑상품권전라남도진도군전라남도 진도군 진도읍 남동1길 40-18<NA><NA><NA><NA>2022-08-245000000전라남도 진도군2