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/18b2f035-71aa-473f-a526-31cff9afb5f0

Alerts

일반일간결제일자 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 started2023-12-10 13:57:21.794764
Analysis finished2023-12-10 13:57:26.656770
Duration4.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일반일간결제일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2021-05-01
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-05-01
2nd row2021-05-01
3rd row2021-05-01
4th row2021-05-01
5th row2021-05-01

Common Values

ValueCountFrequency (%)
2021-05-01 30
100.0%

Length

2023-12-10T22:57:26.761816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:57:26.914304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-05-01 30
100.0%

가맹점번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0663123 × 108
Minimum7.000005 × 108
Maximum7.9933544 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:57:27.101751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.000005 × 108
5-th percentile7.000018 × 108
Q17.0000612 × 108
median7.0000952 × 108
Q37.0001589 × 108
95-th percentile7.5464286 × 108
Maximum7.9933544 × 108
Range99334932
Interquartile range (IQR)9769.5

Descriptive statistics

Standard deviation25199797
Coefficient of variation (CV)0.035661878
Kurtosis12.206631
Mean7.0663123 × 108
Median Absolute Deviation (MAD)3804.5
Skewness3.6599984
Sum2.1198937 × 1010
Variance6.3502975 × 1014
MonotonicityNot monotonic
2023-12-10T22:57:27.341689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
700000504 1
 
3.3%
700009345 1
 
3.3%
700018610 1
 
3.3%
700018336 1
 
3.3%
700018075 1
 
3.3%
700017615 1
 
3.3%
700016723 1
 
3.3%
700016480 1
 
3.3%
700014130 1
 
3.3%
700011378 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
700000504 1
3.3%
700001681 1
3.3%
700001956 1
3.3%
700002555 1
3.3%
700005104 1
3.3%
700005502 1
3.3%
700005925 1
3.3%
700006046 1
3.3%
700006354 1
3.3%
700006541 1
3.3%
ValueCountFrequency (%)
799335436 1
3.3%
799335428 1
3.3%
700018610 1
3.3%
700018336 1
3.3%
700018075 1
3.3%
700017615 1
3.3%
700016723 1
3.3%
700016480 1
3.3%
700014130 1
3.3%
700011378 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

2023-12-10T22:57:27.602598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:57:27.759450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
999999999999999 30
100.0%

가맹점업종명
Categorical

Distinct12
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
일반휴게음식
6 
유통업 영리
5 
보건위생
4 
건축자재
3 
음료식품
3 
Other values (7)
9 

Length

Max length8
Median length6
Mean length5.0333333
Min length2

Unique

Unique5 ?
Unique (%)16.7%

Sample

1st row레저업소
2nd row유통업 영리
3rd row자동차정비 유지
4th row건축자재
5th row일반휴게음식

Common Values

ValueCountFrequency (%)
일반휴게음식 6
20.0%
유통업 영리 5
16.7%
보건위생 4
13.3%
건축자재 3
10.0%
음료식품 3
10.0%
레저업소 2
 
6.7%
자동차정비 유지 2
 
6.7%
의류 1
 
3.3%
사무통신 1
 
3.3%
전기제품 1
 
3.3%
Other values (2) 2
 
6.7%

Length

2023-12-10T22:57:27.939577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반휴게음식 6
15.8%
유통업 5
13.2%
영리 5
13.2%
보건위생 4
10.5%
건축자재 3
7.9%
음료식품 3
7.9%
레저업소 2
 
5.3%
자동차정비 2
 
5.3%
유지 2
 
5.3%
의류 1
 
2.6%
Other values (5) 5
13.2%

가맹점우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13197.433
Minimum10030
Maximum18584
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:57:28.126508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10030
5-th percentile10132.4
Q110588.5
median12956
Q314685.5
95-th percentile17966
Maximum18584
Range8554
Interquartile range (IQR)4097

Descriptive statistics

Standard deviation2594.3044
Coefficient of variation (CV)0.19657643
Kurtosis-0.69928005
Mean13197.433
Median Absolute Deviation (MAD)2238.5
Skewness0.53048508
Sum395923
Variance6730415.2
MonotonicityNot monotonic
2023-12-10T22:57:28.298482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
10902 1
 
3.3%
13144 1
 
3.3%
14417 1
 
3.3%
12921 1
 
3.3%
15630 1
 
3.3%
14735 1
 
3.3%
14537 1
 
3.3%
14102 1
 
3.3%
16925 1
 
3.3%
14270 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10030 1
3.3%
10073 1
3.3%
10205 1
3.3%
10304 1
3.3%
10362 1
3.3%
10377 1
3.3%
10401 1
3.3%
10484 1
3.3%
10902 1
3.3%
11324 1
3.3%
ValueCountFrequency (%)
18584 1
3.3%
18137 1
3.3%
17757 1
3.3%
16925 1
3.3%
15807 1
3.3%
15630 1
3.3%
15379 1
3.3%
14735 1
3.3%
14537 1
3.3%
14417 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

2023-12-10T22:57:28.510514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:57:28.673934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Text

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:57:28.922209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.9
Min length3

Characters and Unicode

Total characters147
Distinct characters39
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

Unique16 ?
Unique (%)53.3%

Sample

1st row파주시
2nd row남양주시
3rd row고양시 일산서구
4th row하남시
5th row평택시
ValueCountFrequency (%)
고양시 6
 
14.3%
부천시 3
 
7.1%
일산동구 3
 
7.1%
일산서구 2
 
4.8%
하남시 2
 
4.8%
김포시 2
 
4.8%
남양주시 2
 
4.8%
성남시 2
 
4.8%
안산시 2
 
4.8%
안양시 1
 
2.4%
Other values (17) 17
40.5%
2023-12-10T22:57:29.448903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 30
20.4%
12
 
8.2%
구 12
 
8.2%
양 10
 
6.8%
산 8
 
5.4%
고 6
 
4.1%
남 6
 
4.1%
일 5
 
3.4%
동 5
 
3.4%
부 4
 
2.7%
Other values (29) 49
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 135
91.8%
Space Separator 12
 
8.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 30
22.2%
구 12
 
8.9%
양 10
 
7.4%
산 8
 
5.9%
고 6
 
4.4%
남 6
 
4.4%
일 5
 
3.7%
동 5
 
3.7%
부 4
 
3.0%
주 4
 
3.0%
Other values (28) 45
33.3%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 135
91.8%
Common 12
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 30
22.2%
구 12
 
8.9%
양 10
 
7.4%
산 8
 
5.9%
고 6
 
4.4%
남 6
 
4.4%
일 5
 
3.7%
동 5
 
3.7%
부 4
 
3.0%
주 4
 
3.0%
Other values (28) 45
33.3%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 135
91.8%
ASCII 12
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 30
22.2%
구 12
 
8.9%
양 10
 
7.4%
산 8
 
5.9%
고 6
 
4.4%
남 6
 
4.4%
일 5
 
3.7%
동 5
 
3.7%
부 4
 
3.0%
주 4
 
3.0%
Other values (28) 45
33.3%
ASCII
ValueCountFrequency (%)
12
100.0%

읍면동명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:57:29.872920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0333333
Min length2

Characters and Unicode

Total characters91
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 row동패동
2nd row진접읍
3rd row가좌동
4th row감북동
5th row지산동
ValueCountFrequency (%)
동패동 1
 
3.3%
진접읍 1
 
3.3%
망월동 1
 
3.3%
사동 1
 
3.3%
송내동 1
 
3.3%
중동 1
 
3.3%
관양동 1
 
3.3%
풍덕천동 1
 
3.3%
광명동 1
 
3.3%
식사동 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T22:57:30.364378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 26
28.6%
읍 4
 
4.4%
산 4
 
4.4%
대 3
 
3.3%
원 2
 
2.2%
양 2
 
2.2%
오 2
 
2.2%
사 2
 
2.2%
정 2
 
2.2%
장 2
 
2.2%
Other values (40) 42
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 26
28.6%
읍 4
 
4.4%
산 4
 
4.4%
대 3
 
3.3%
원 2
 
2.2%
양 2
 
2.2%
오 2
 
2.2%
사 2
 
2.2%
정 2
 
2.2%
장 2
 
2.2%
Other values (40) 42
46.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 26
28.6%
읍 4
 
4.4%
산 4
 
4.4%
대 3
 
3.3%
원 2
 
2.2%
양 2
 
2.2%
오 2
 
2.2%
사 2
 
2.2%
정 2
 
2.2%
장 2
 
2.2%
Other values (40) 42
46.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 26
28.6%
읍 4
 
4.4%
산 4
 
4.4%
대 3
 
3.3%
원 2
 
2.2%
양 2
 
2.2%
오 2
 
2.2%
사 2
 
2.2%
정 2
 
2.2%
장 2
 
2.2%
Other values (40) 42
46.2%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.510367
Minimum37.081
Maximum37.916
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:57:30.533917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.081
5-th percentile37.10775
Q137.38225
median37.523
Q337.66875
95-th percentile37.7318
Maximum37.916
Range0.835
Interquartile range (IQR)0.2865

Descriptive statistics

Standard deviation0.20364667
Coefficient of variation (CV)0.0054290769
Kurtosis-0.090443042
Mean37.510367
Median Absolute Deviation (MAD)0.147
Skewness-0.49864311
Sum1125.311
Variance0.041471964
MonotonicityNot monotonic
2023-12-10T22:57:30.694080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
37.711 1
 
3.3%
37.449 1
 
3.3%
37.525 1
 
3.3%
37.559 1
 
3.3%
37.284 1
 
3.3%
37.481 1
 
3.3%
37.505 1
 
3.3%
37.404 1
 
3.3%
37.315 1
 
3.3%
37.475 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
37.081 1
3.3%
37.083 1
3.3%
37.138 1
3.3%
37.284 1
3.3%
37.315 1
3.3%
37.331 1
3.3%
37.345 1
3.3%
37.375 1
3.3%
37.404 1
3.3%
37.438 1
3.3%
ValueCountFrequency (%)
37.916 1
3.3%
37.748 1
3.3%
37.712 1
3.3%
37.711 1
3.3%
37.7 1
3.3%
37.676 1
3.3%
37.673 1
3.3%
37.669 1
3.3%
37.668 1
3.3%
37.661 1
3.3%

경도
Real number (ℝ)

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.92847
Minimum126.584
Maximum127.212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:57:30.865706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.584
5-th percentile126.70125
Q1126.77125
median126.8565
Q3127.0895
95-th percentile127.2038
Maximum127.212
Range0.628
Interquartile range (IQR)0.31825

Descriptive statistics

Standard deviation0.18727349
Coefficient of variation (CV)0.0014754255
Kurtosis-1.3327333
Mean126.92847
Median Absolute Deviation (MAD)0.1245
Skewness0.1698
Sum3807.854
Variance0.035071361
MonotonicityNot monotonic
2023-12-10T22:57:31.056596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
127.158 2
 
6.7%
127.056 2
 
6.7%
126.738 1
 
3.3%
126.794 1
 
3.3%
126.812 1
 
3.3%
127.195 1
 
3.3%
126.854 1
 
3.3%
126.771 1
 
3.3%
126.762 1
 
3.3%
126.956 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
126.584 1
3.3%
126.681 1
3.3%
126.726 1
3.3%
126.738 1
3.3%
126.752 1
3.3%
126.762 1
3.3%
126.767 1
3.3%
126.771 1
3.3%
126.772 1
3.3%
126.794 1
3.3%
ValueCountFrequency (%)
127.212 1
3.3%
127.211 1
3.3%
127.195 1
3.3%
127.187 1
3.3%
127.162 1
3.3%
127.158 2
6.7%
127.097 1
3.3%
127.067 1
3.3%
127.056 2
6.7%
127.042 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%
2023-12-10T22:57:31.211994image/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

2023-12-10T22:57:31.369921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:57:31.522016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

Interactions

2023-12-10T22:57:24.911491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:22.790387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:23.452554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:24.179400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:25.051794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:22.991432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:23.617978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:24.353117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:25.188862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:23.139992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:23.734384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:24.465708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:25.364759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:23.258089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:23.898121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:57:24.695061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:57:31.607068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점업종명가맹점우편번호시군구명읍면동명위도경도
가맹점번호1.0000.0000.0000.4171.0000.0000.000
가맹점업종명0.0001.0000.4340.0001.0000.0000.658
가맹점우편번호0.0000.4341.0001.0001.0000.7900.786
시군구명0.4170.0001.0001.0001.0000.9330.883
읍면동명1.0001.0001.0001.0001.0001.0001.000
위도0.0000.0000.7900.9331.0001.0000.529
경도0.0000.6580.7860.8831.0000.5291.000
2023-12-10T22:57:31.828459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점우편번호위도경도가맹점업종명
가맹점번호1.0000.241-0.1640.1210.000
가맹점우편번호0.2411.000-0.8480.3850.052
위도-0.164-0.8481.000-0.3230.000
경도0.1210.385-0.3231.0000.300
가맹점업종명0.0000.0520.0000.3001.000

Missing values

2023-12-10T22:57:25.812156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:57:26.483270image/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

일반일간결제일자가맹점번호결제상품ID가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도결제상품명사용여부결제금액
02021-05-01700000504999999999999999레저업소10902경기도파주시동패동37.711126.738<NA>N0
12021-05-01799335428999999999999999유통업 영리12066경기도남양주시진접읍37.712127.187<NA>N0
22021-05-01700001681999999999999999자동차정비 유지10205경기도고양시 일산서구가좌동37.7126.726<NA>N0
32021-05-01700001956999999999999999건축자재12991경기도하남시감북동37.521127.158<NA>N0
42021-05-01700002555999999999999999일반휴게음식17757경기도평택시지산동37.081127.056<NA>N0
52021-05-01700005104999999999999999일반휴게음식11678경기도의정부시가능동37.748127.042<NA>N0
62021-05-01700005502999999999999999유통업 영리12774경기도광주시오포읍37.345127.212<NA>N0
72021-05-01799335436999999999999999유통업 영리10484경기도고양시 덕양구행신동37.626126.843<NA>N0
82021-05-01700005925999999999999999건축자재15807경기도군포시금정동37.375126.945<NA>N0
92021-05-01700006046999999999999999의류10377경기도고양시 일산서구대화동37.676126.752<NA>N0
일반일간결제일자가맹점번호결제상품ID가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도결제상품명사용여부결제금액
202021-05-01700011001999999999999999레저업소13397경기도성남시 중원구상대원동37.438127.162<NA>N0
212021-05-01700011068999999999999999자동차정비 유지10304경기도고양시 일산동구식사동37.668126.81<NA>N0
222021-05-01700011378999999999999999음료식품14270경기도광명시광명동37.475126.859<NA>N0
232021-05-01700014130999999999999999전기제품16925경기도용인시 수지구풍덕천동37.315127.097<NA>N0
242021-05-01700016480999999999999999유통업 영리14102경기도안양시 동안구관양동37.404126.956<NA>N0
252021-05-01700016723999999999999999유통업 영리14537경기도부천시중동37.505126.762<NA>N0
262021-05-01700017615999999999999999문화.취미14735경기도부천시송내동37.481126.771<NA>N0
272021-05-01700018075999999999999999일반휴게음식15630경기도안산시 상록구사동37.284126.854<NA>N0
282021-05-01700018336999999999999999용역 서비스12921경기도하남시망월동37.559127.195<NA>N0
292021-05-01700018610999999999999999건축자재14417경기도부천시고강동37.525126.812<NA>N0