Overview

Dataset statistics

Number of variables13
Number of observations30
Missing cells30
Missing cells (%)7.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory115.4 B

Variable types

Categorical5
Numeric4
Text2
Unsupported1
Boolean1

Dataset

Description샘플 데이터
Author코나아이㈜
URLhttps://bigdata-region.kr/#/dataset/23bc1782-39db-45c9-88b2-70580ad86239

Alerts

정책일간결제일자 has constant value ""Constant
결제상품ID has constant value ""Constant
시도명 has constant value ""Constant
사용여부 has constant value ""Constant
결제금액 has constant value ""Constant
가맹점우편번호 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 가맹점우편번호High correlation
결제상품명 has 30 (100.0%) missing valuesMissing
가맹점번호 has unique valuesUnique
가맹점우편번호 has unique valuesUnique
읍면동명 has unique valuesUnique
위도 has unique valuesUnique
결제상품명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 11:50:36.838667
Analysis finished2024-03-13 11:50:39.170256
Duration2.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

정책일간결제일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-10-01
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-01
2nd row2023-10-01
3rd row2023-10-01
4th row2023-10-01
5th row2023-10-01

Common Values

ValueCountFrequency (%)
2023-10-01 30
100.0%

Length

2024-03-13T20:50:39.247207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:50:39.368737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-01 30
100.0%

가맹점번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0664529 × 108
Minimum7.0000329 × 108
Maximum7.9933256 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:50:39.489403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.0000329 × 108
5-th percentile7.0000711 × 108
Q17.0001557 × 108
median7.0002782 × 108
Q37.0003836 × 108
95-th percentile7.5465107 × 108
Maximum7.9933256 × 108
Range99329271
Interquartile range (IQR)22783

Descriptive statistics

Standard deviation25195128
Coefficient of variation (CV)0.035654562
Kurtosis12.206626
Mean7.0664529 × 108
Median Absolute Deviation (MAD)11226.5
Skewness3.6599973
Sum2.1199359 × 1010
Variance6.3479448 × 1014
MonotonicityNot monotonic
2024-03-13T20:50:39.755581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
700003290 1
 
3.3%
700026262 1
 
3.3%
700040981 1
 
3.3%
700040234 1
 
3.3%
700039052 1
 
3.3%
700039038 1
 
3.3%
700038909 1
 
3.3%
700038544 1
 
3.3%
700037792 1
 
3.3%
700035928 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
700003290 1
3.3%
700006614 1
3.3%
700007715 1
3.3%
700008509 1
3.3%
700009724 1
3.3%
700010144 1
3.3%
700014497 1
3.3%
700015532 1
3.3%
700015696 1
3.3%
700016464 1
3.3%
ValueCountFrequency (%)
799332561 1
3.3%
799332058 1
3.3%
700040981 1
3.3%
700040234 1
3.3%
700039052 1
3.3%
700039038 1
3.3%
700038909 1
3.3%
700038544 1
3.3%
700037792 1
3.3%
700035928 1
3.3%

결제상품ID
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
999999999999999
30 

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row999999999999999
2nd row999999999999999
3rd row999999999999999
4th row999999999999999
5th row999999999999999

Common Values

ValueCountFrequency (%)
999999999999999 30
100.0%

Length

2024-03-13T20:50:39.898982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:50:39.989429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
999999999999999 30
100.0%

가맹점업종명
Categorical

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
일반/휴게 음식
9 
음료/식품
4 
미용/위생
3 
학원
3 
용역서비스
3 
Other values (6)
8 

Length

Max length10
Median length9
Mean length5.7666667
Min length2

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row미용/위생
2nd row일반/휴게 음식
3rd row일반/휴게 음식
4th row학원
5th row일반/휴게 음식

Common Values

ValueCountFrequency (%)
일반/휴게 음식 9
30.0%
음료/식품 4
13.3%
미용/위생 3
 
10.0%
학원 3
 
10.0%
용역서비스 3
 
10.0%
레저/스포츠 서비스 2
 
6.7%
일반유통 2
 
6.7%
의원 1
 
3.3%
자동차 정비/유지 1
 
3.3%
병원 1
 
3.3%

Length

2024-03-13T20:50:40.108019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반/휴게 9
21.4%
음식 9
21.4%
음료/식품 4
9.5%
미용/위생 3
 
7.1%
학원 3
 
7.1%
용역서비스 3
 
7.1%
레저/스포츠 2
 
4.8%
서비스 2
 
4.8%
일반유통 2
 
4.8%
의원 1
 
2.4%
Other values (4) 4
9.5%

가맹점우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14135.367
Minimum10011
Maximum18445
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:50:40.241241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10011
5-th percentile10267.4
Q112145.25
median14208
Q316189.75
95-th percentile18169.15
Maximum18445
Range8434
Interquartile range (IQR)4044.5

Descriptive statistics

Standard deviation2522.8553
Coefficient of variation (CV)0.17847824
Kurtosis-1.0255833
Mean14135.367
Median Absolute Deviation (MAD)2056.5
Skewness0.058818527
Sum424061
Variance6364798.9
MonotonicityNot monotonic
2024-03-13T20:50:40.382281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
11695 1
 
3.3%
14469 1
 
3.3%
16620 1
 
3.3%
14683 1
 
3.3%
18445 1
 
3.3%
10571 1
 
3.3%
14571 1
 
3.3%
13626 1
 
3.3%
10011 1
 
3.3%
16332 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10011 1
3.3%
10019 1
3.3%
10571 1
3.3%
10834 1
3.3%
11139 1
3.3%
11695 1
3.3%
12020 1
3.3%
12139 1
3.3%
12164 1
3.3%
12512 1
3.3%
ValueCountFrequency (%)
18445 1
3.3%
18382 1
3.3%
17909 1
3.3%
17420 1
3.3%
17128 1
3.3%
16620 1
3.3%
16332 1
3.3%
16240 1
3.3%
16039 1
3.3%
15853 1
3.3%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 30
100.0%

Length

2024-03-13T20:50:40.508678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:50:40.641996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Text

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-13T20:50:40.844496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length4.0666667
Min length3

Characters and Unicode

Total characters122
Distinct characters41
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

Unique18 ?
Unique (%)60.0%

Sample

1st row의정부시
2nd row남양주시
3rd row용인시 처인구
4th row남양주시
5th row군포시
ValueCountFrequency (%)
부천시 3
 
8.1%
수원시 3
 
8.1%
남양주시 3
 
8.1%
김포시 2
 
5.4%
하남시 2
 
5.4%
화성시 2
 
5.4%
동안구 1
 
2.7%
의정부시 1
 
2.7%
덕양구 1
 
2.7%
고양시 1
 
2.7%
Other values (18) 18
48.6%
2024-03-13T20:50:41.238242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 30
24.6%
구 7
 
5.7%
양 7
 
5.7%
7
 
5.7%
남 6
 
4.9%
천 6
 
4.9%
부 4
 
3.3%
주 4
 
3.3%
포 4
 
3.3%
안 3
 
2.5%
Other values (31) 44
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 115
94.3%
Space Separator 7
 
5.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 30
26.1%
구 7
 
6.1%
양 7
 
6.1%
남 6
 
5.2%
천 6
 
5.2%
부 4
 
3.5%
주 4
 
3.5%
포 4
 
3.5%
안 3
 
2.6%
성 3
 
2.6%
Other values (30) 41
35.7%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 115
94.3%
Common 7
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 30
26.1%
구 7
 
6.1%
양 7
 
6.1%
남 6
 
5.2%
천 6
 
5.2%
부 4
 
3.5%
주 4
 
3.5%
포 4
 
3.5%
안 3
 
2.6%
성 3
 
2.6%
Other values (30) 41
35.7%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 115
94.3%
ASCII 7
 
5.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 30
26.1%
구 7
 
6.1%
양 7
 
6.1%
남 6
 
5.2%
천 6
 
5.2%
부 4
 
3.5%
주 4
 
3.5%
포 4
 
3.5%
안 3
 
2.6%
성 3
 
2.6%
Other values (30) 41
35.7%
ASCII
ValueCountFrequency (%)
7
100.0%

읍면동명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-13T20:50:41.485008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0666667
Min length3

Characters and Unicode

Total characters92
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row의정부동
2nd row진접읍
3rd row이동읍
4th row화도읍
5th row당정동
ValueCountFrequency (%)
의정부동 1
 
3.3%
진접읍 1
 
3.3%
괴안동 1
 
3.3%
반송동 1
 
3.3%
신원동 1
 
3.3%
원미동 1
 
3.3%
구미동 1
 
3.3%
하성면 1
 
3.3%
정자동 1
 
3.3%
내손동 1
 
3.3%
Other values (20) 20
66.7%
2024-03-13T20:50:42.009290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 21
22.8%
읍 7
 
7.6%
정 5
 
5.4%
원 3
 
3.3%
진 3
 
3.3%
면 3
 
3.3%
하 2
 
2.2%
반 2
 
2.2%
월 2
 
2.2%
미 2
 
2.2%
Other values (40) 42
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 21
22.8%
읍 7
 
7.6%
정 5
 
5.4%
원 3
 
3.3%
진 3
 
3.3%
면 3
 
3.3%
하 2
 
2.2%
반 2
 
2.2%
월 2
 
2.2%
미 2
 
2.2%
Other values (40) 42
45.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 21
22.8%
읍 7
 
7.6%
정 5
 
5.4%
원 3
 
3.3%
진 3
 
3.3%
면 3
 
3.3%
하 2
 
2.2%
반 2
 
2.2%
월 2
 
2.2%
미 2
 
2.2%
Other values (40) 42
45.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 21
22.8%
읍 7
 
7.6%
정 5
 
5.4%
원 3
 
3.3%
진 3
 
3.3%
면 3
 
3.3%
하 2
 
2.2%
반 2
 
2.2%
월 2
 
2.2%
미 2
 
2.2%
Other values (40) 42
45.7%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.467333
Minimum36.993
Maximum37.939
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:50:42.201151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.993
5-th percentile37.15055
Q137.305
median37.466
Q337.65275
95-th percentile37.78995
Maximum37.939
Range0.946
Interquartile range (IQR)0.34775

Descriptive statistics

Standard deviation0.22428174
Coefficient of variation (CV)0.0059860609
Kurtosis-0.44679388
Mean37.467333
Median Absolute Deviation (MAD)0.18
Skewness0.039386308
Sum1124.02
Variance0.050302299
MonotonicityNot monotonic
2024-03-13T20:50:42.392700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
37.74 1
 
3.3%
37.523 1
 
3.3%
37.267 1
 
3.3%
37.481 1
 
3.3%
37.202 1
 
3.3%
37.663 1
 
3.3%
37.492 1
 
3.3%
37.338 1
 
3.3%
37.718 1
 
3.3%
37.294 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
36.993 1
3.3%
37.115 1
3.3%
37.194 1
3.3%
37.202 1
3.3%
37.229 1
3.3%
37.267 1
3.3%
37.28 1
3.3%
37.294 1
3.3%
37.338 1
3.3%
37.347 1
3.3%
ValueCountFrequency (%)
37.939 1
3.3%
37.83 1
3.3%
37.741 1
3.3%
37.74 1
3.3%
37.718 1
3.3%
37.69 1
3.3%
37.663 1
3.3%
37.657 1
3.3%
37.64 1
3.3%
37.559 1
3.3%

경도
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.03483
Minimum126.597
Maximum127.631
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:50:42.535183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.597
5-th percentile126.6724
Q1126.89
median127.013
Q3127.187
95-th percentile127.47735
Maximum127.631
Range1.034
Interquartile range (IQR)0.297

Descriptive statistics

Standard deviation0.240244
Coefficient of variation (CV)0.0018911663
Kurtosis0.96924224
Mean127.03483
Median Absolute Deviation (MAD)0.1655
Skewness0.61702142
Sum3811.045
Variance0.057717178
MonotonicityNot monotonic
2024-03-13T20:50:42.731651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
126.89 2
 
6.7%
127.049 1
 
3.3%
126.824 1
 
3.3%
126.994 1
 
3.3%
126.806 1
 
3.3%
127.067 1
 
3.3%
126.79 1
 
3.3%
127.12 1
 
3.3%
126.631 1
 
3.3%
126.989 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
126.597 1
3.3%
126.631 1
3.3%
126.723 1
3.3%
126.79 1
3.3%
126.806 1
3.3%
126.824 1
3.3%
126.832 1
3.3%
126.89 2
6.7%
126.955 1
3.3%
126.956 1
3.3%
ValueCountFrequency (%)
127.631 1
3.3%
127.62 1
3.3%
127.303 1
3.3%
127.237 1
3.3%
127.229 1
3.3%
127.206 1
3.3%
127.199 1
3.3%
127.195 1
3.3%
127.163 1
3.3%
127.12 1
3.3%

결제상품명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

사용여부
Boolean

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size162.0 B
False
30 
ValueCountFrequency (%)
False 30
100.0%
2024-03-13T20:50:43.180647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

결제금액
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 30
100.0%

Length

2024-03-13T20:50:43.318764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:50:43.443638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

Interactions

2024-03-13T20:50:38.445305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:37.146876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:37.692833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:38.051681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:38.572281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:37.328606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:37.786090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:38.147685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:38.675206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:37.485015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:37.870155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:38.238637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:38.761357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:37.598745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:37.960645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:50:38.333272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T20:50:43.510486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점업종명가맹점우편번호시군구명읍면동명위도경도
가맹점번호1.0000.5410.0000.0001.0000.7780.000
가맹점업종명0.5411.0000.0000.9071.0000.6250.000
가맹점우편번호0.0000.0001.0001.0001.0000.8030.715
시군구명0.0000.9071.0001.0001.0000.9660.899
읍면동명1.0001.0001.0001.0001.0001.0001.000
위도0.7780.6250.8030.9661.0001.0000.431
경도0.0000.0000.7150.8991.0000.4311.000
2024-03-13T20:50:43.626038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점우편번호위도경도가맹점업종명
가맹점번호1.0000.185-0.156-0.1550.431
가맹점우편번호0.1851.000-0.9380.1310.000
위도-0.156-0.9381.000-0.1330.292
경도-0.1550.131-0.1331.0000.000
가맹점업종명0.4310.0000.2920.0001.000

Missing values

2024-03-13T20:50:38.896938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:50:39.082869image/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

정책일간결제일자가맹점번호결제상품ID가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도결제상품명사용여부결제금액
02023-10-01700003290999999999999999미용/위생11695경기도의정부시의정부동37.74127.049<NA>N0
12023-10-01799332058999999999999999일반/휴게 음식12020경기도남양주시진접읍37.741127.199<NA>N0
22023-10-01700006614999999999999999일반/휴게 음식17128경기도용인시 처인구이동읍37.194127.206<NA>N0
32023-10-01700007715999999999999999학원12164경기도남양주시화도읍37.657127.303<NA>N0
42023-10-01700008509999999999999999일반/휴게 음식15853경기도군포시당정동37.347126.955<NA>N0
52023-10-01700009724999999999999999음료/식품10019경기도김포시통진읍37.69126.597<NA>N0
62023-10-01700010144999999999999999일반/휴게 음식13023경기도하남시창우동37.541127.237<NA>N0
72023-10-01799332561999999999999999의원17909경기도평택시합정동36.993127.092<NA>N0
82023-10-01700014497999999999999999레저/스포츠 서비스17420경기도이천시장호원읍37.115127.631<NA>N0
92023-10-01700015532999999999999999음료/식품12139경기도남양주시진건읍37.64127.163<NA>N0
정책일간결제일자가맹점번호결제상품ID가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도결제상품명사용여부결제금액
202023-10-01700032914999999999999999미용/위생13840경기도과천시갈현동37.417126.985<NA>N0
212023-10-01700035288999999999999999일반/휴게 음식16039경기도의왕시내손동37.379126.974<NA>N0
222023-10-01700035928999999999999999일반유통16332경기도수원시 장안구정자동37.294126.989<NA>N0
232023-10-01700037792999999999999999일반/휴게 음식10011경기도김포시하성면37.718126.631<NA>N0
242023-10-01700038544999999999999999학원13626경기도성남시 분당구구미동37.338127.12<NA>N0
252023-10-01700038909999999999999999일반/휴게 음식14571경기도부천시원미동37.492126.79<NA>N0
262023-10-01700039038999999999999999레저/스포츠 서비스10571경기도고양시 덕양구신원동37.663126.89<NA>N0
272023-10-01700039052999999999999999일반/휴게 음식18445경기도화성시반송동37.202127.067<NA>N0
282023-10-01700040234999999999999999음료/식품14683경기도부천시괴안동37.481126.806<NA>N0
292023-10-01700040981999999999999999건축자재16620경기도수원시 권선구서둔동37.267126.994<NA>N0