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/bf59caa3-31c6-4d41-bc16-226e288ebabb

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
결제상품명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 13:53:57.844172
Analysis finished2023-12-10 13:54:00.960546
Duration3.12 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
2023-01-01
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

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

Length

2023-12-10T22:54:01.063456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:01.218686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-01-01 30
100.0%

가맹점번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0665129 × 108
Minimum7.0000583 × 108
Maximum7.993288 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:54:01.383909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.0000583 × 108
5-th percentile7.0000906 × 108
Q17.0002035 × 108
median7.0003625 × 108
Q37.0004319 × 108
95-th percentile7.5465338 × 108
Maximum7.993288 × 108
Range99322967
Interquartile range (IQR)22842.5

Descriptive statistics

Standard deviation25192482
Coefficient of variation (CV)0.035650515
Kurtosis12.206624
Mean7.0665129 × 108
Median Absolute Deviation (MAD)10639.5
Skewness3.6599969
Sum2.1199539 × 1010
Variance6.3466116 × 1014
MonotonicityNot monotonic
2023-12-10T22:54:01.584272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
700005828 1
 
3.3%
700034702 1
 
3.3%
700050652 1
 
3.3%
700049382 1
 
3.3%
700046969 1
 
3.3%
700046804 1
 
3.3%
700046504 1
 
3.3%
700043272 1
 
3.3%
700042959 1
 
3.3%
700042488 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
700005828 1
3.3%
700007407 1
3.3%
700011084 1
3.3%
700012844 1
3.3%
700014537 1
3.3%
700016601 1
3.3%
700019702 1
3.3%
700020234 1
3.3%
700020703 1
3.3%
700025525 1
3.3%
ValueCountFrequency (%)
799328795 1
3.3%
799328341 1
3.3%
700050652 1
3.3%
700049382 1
3.3%
700046969 1
3.3%
700046804 1
3.3%
700046504 1
3.3%
700043272 1
3.3%
700042959 1
3.3%
700042488 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

2023-12-10T22:54:01.775733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:01.933248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
999999999999999 30
100.0%

가맹점업종명
Categorical

Distinct14
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
일반휴게음식
8 
학원
3 
유통업 영리
3 
음료식품
3 
용역 서비스
2 
Other values (9)
11 

Length

Max length7
Median length6
Mean length4.5666667
Min length2

Unique

Unique7 ?
Unique (%)23.3%

Sample

1st row일반휴게음식
2nd row일반휴게음식
3rd row용역 서비스
4th row보건위생
5th row학원

Common Values

ValueCountFrequency (%)
일반휴게음식 8
26.7%
학원 3
 
10.0%
유통업 영리 3
 
10.0%
음료식품 3
 
10.0%
용역 서비스 2
 
6.7%
보건위생 2
 
6.7%
문화.취미 2
 
6.7%
서적문구 1
 
3.3%
기타 1
 
3.3%
전기제품 1
 
3.3%
Other values (4) 4
13.3%

Length

2023-12-10T22:54:02.175668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반휴게음식 8
22.2%
유통업 4
11.1%
학원 3
 
8.3%
영리 3
 
8.3%
음료식품 3
 
8.3%
용역 2
 
5.6%
서비스 2
 
5.6%
보건위생 2
 
5.6%
문화.취미 2
 
5.6%
서적문구 1
 
2.8%
Other values (6) 6
16.7%

가맹점우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13333.3
Minimum10011
Maximum18583
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:54:02.369956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10011
5-th percentile10032.2
Q111716.5
median12700.5
Q315264.5
95-th percentile18127.55
Maximum18583
Range8572
Interquartile range (IQR)3548

Descriptive statistics

Standard deviation2639.1673
Coefficient of variation (CV)0.19793804
Kurtosis-0.67926808
Mean13333.3
Median Absolute Deviation (MAD)1865
Skewness0.57271052
Sum399999
Variance6965204.2
MonotonicityNot monotonic
2023-12-10T22:54:02.679130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
12797 1
 
3.3%
10025 1
 
3.3%
13313 1
 
3.3%
12431 1
 
3.3%
11775 1
 
3.3%
10240 1
 
3.3%
12767 1
 
3.3%
16564 1
 
3.3%
15458 1
 
3.3%
12530 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10011 1
3.3%
10025 1
3.3%
10041 1
3.3%
10049 1
3.3%
10088 1
3.3%
10240 1
3.3%
11182 1
3.3%
11697 1
3.3%
11775 1
3.3%
12035 1
3.3%
ValueCountFrequency (%)
18583 1
3.3%
18146 1
3.3%
18105 1
3.3%
17031 1
3.3%
16921 1
3.3%
16564 1
3.3%
15458 1
3.3%
15382 1
3.3%
14912 1
3.3%
13820 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

2023-12-10T22:54:02.968948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:03.171790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Text

Distinct19
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:54:03.399505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length4.3666667
Min length3

Characters and Unicode

Total characters131
Distinct characters38
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

Unique11 ?
Unique (%)36.7%

Sample

1st row광주시
2nd row포천시
3rd row오산시
4th row남양주시
5th row용인시 처인구
ValueCountFrequency (%)
김포시 5
 
12.8%
성남시 3
 
7.7%
남양주시 2
 
5.1%
용인시 2
 
5.1%
안산시 2
 
5.1%
가평군 2
 
5.1%
오산시 2
 
5.1%
광주시 2
 
5.1%
의정부시 2
 
5.1%
수정구 2
 
5.1%
Other values (14) 15
38.5%
2023-12-10T22:54:03.857638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 28
21.4%
9
 
6.9%
구 9
 
6.9%
포 6
 
4.6%
김 5
 
3.8%
남 5
 
3.8%
산 5
 
3.8%
주 5
 
3.8%
양 4
 
3.1%
정 4
 
3.1%
Other values (28) 51
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 122
93.1%
Space Separator 9
 
6.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 28
23.0%
구 9
 
7.4%
포 6
 
4.9%
김 5
 
4.1%
남 5
 
4.1%
산 5
 
4.1%
주 5
 
4.1%
양 4
 
3.3%
정 4
 
3.3%
성 4
 
3.3%
Other values (27) 47
38.5%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 122
93.1%
Common 9
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 28
23.0%
구 9
 
7.4%
포 6
 
4.9%
김 5
 
4.1%
남 5
 
4.1%
산 5
 
4.1%
주 5
 
4.1%
양 4
 
3.3%
정 4
 
3.3%
성 4
 
3.3%
Other values (27) 47
38.5%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 122
93.1%
ASCII 9
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 28
23.0%
구 9
 
7.4%
포 6
 
4.9%
김 5
 
4.1%
남 5
 
4.1%
산 5
 
4.1%
주 5
 
4.1%
양 4
 
3.3%
정 4
 
3.3%
성 4
 
3.3%
Other values (27) 47
38.5%
ASCII
ValueCountFrequency (%)
9
100.0%

읍면동명
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:54:04.192769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters90
Distinct characters53
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

Unique28 ?
Unique (%)93.3%

Sample

1st row오포읍
2nd row소흘읍
3rd row갈곶동
4th row화도읍
5th row모현읍
ValueCountFrequency (%)
조종면 2
 
6.7%
오포읍 1
 
3.3%
양촌읍 1
 
3.3%
신곡동 1
 
3.3%
탄현동 1
 
3.3%
삼동 1
 
3.3%
권선동 1
 
3.3%
고잔동 1
 
3.3%
청운면 1
 
3.3%
원곡동 1
 
3.3%
Other values (19) 19
63.3%
2023-12-10T22:54:04.693266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 18
20.0%
면 7
 
7.8%
읍 5
 
5.6%
양 3
 
3.3%
곶 3
 
3.3%
조 2
 
2.2%
곡 2
 
2.2%
대 2
 
2.2%
현 2
 
2.2%
장 2
 
2.2%
Other values (43) 44
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 18
20.0%
면 7
 
7.8%
읍 5
 
5.6%
양 3
 
3.3%
곶 3
 
3.3%
조 2
 
2.2%
곡 2
 
2.2%
대 2
 
2.2%
현 2
 
2.2%
장 2
 
2.2%
Other values (43) 44
48.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 18
20.0%
면 7
 
7.8%
읍 5
 
5.6%
양 3
 
3.3%
곶 3
 
3.3%
조 2
 
2.2%
곡 2
 
2.2%
대 2
 
2.2%
현 2
 
2.2%
장 2
 
2.2%
Other values (43) 44
48.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 18
20.0%
면 7
 
7.8%
읍 5
 
5.6%
양 3
 
3.3%
곶 3
 
3.3%
조 2
 
2.2%
곡 2
 
2.2%
대 2
 
2.2%
현 2
 
2.2%
장 2
 
2.2%
Other values (43) 44
48.9%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.501933
Minimum37.083
Maximum37.914
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:54:05.010495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.083
5-th percentile37.15925
Q137.328
median37.449
Q337.6925
95-th percentile37.82
Maximum37.914
Range0.831
Interquartile range (IQR)0.3645

Descriptive statistics

Standard deviation0.22195354
Coefficient of variation (CV)0.005918456
Kurtosis-1.0018939
Mean37.501933
Median Absolute Deviation (MAD)0.189
Skewness-0.024562101
Sum1125.058
Variance0.049263375
MonotonicityNot monotonic
2023-12-10T22:54:05.358193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
37.82 2
 
6.7%
37.376 1
 
3.3%
37.439 1
 
3.3%
37.914 1
 
3.3%
37.748 1
 
3.3%
37.697 1
 
3.3%
37.41 1
 
3.3%
37.26 1
 
3.3%
37.315 1
 
3.3%
37.554 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
37.083 1
3.3%
37.13 1
3.3%
37.195 1
3.3%
37.26 1
3.3%
37.293 1
3.3%
37.298 1
3.3%
37.315 1
3.3%
37.327 1
3.3%
37.331 1
3.3%
37.338 1
3.3%
ValueCountFrequency (%)
37.914 1
3.3%
37.82 2
6.7%
37.748 1
3.3%
37.737 1
3.3%
37.718 1
3.3%
37.706 1
3.3%
37.697 1
3.3%
37.679 1
3.3%
37.648 1
3.3%
37.639 1
3.3%

경도
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.03887
Minimum126.542
Maximum127.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:54:05.624292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.542
5-th percentile126.5743
Q1126.806
median127.069
Q3127.1875
95-th percentile127.54055
Maximum127.71
Range1.168
Interquartile range (IQR)0.3815

Descriptive statistics

Standard deviation0.2959931
Coefficient of variation (CV)0.0023299412
Kurtosis0.016602835
Mean127.03887
Median Absolute Deviation (MAD)0.199
Skewness0.23339867
Sum3811.166
Variance0.087611913
MonotonicityNot monotonic
2023-12-10T22:54:05.900293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
127.069 2
 
6.7%
127.26 1
 
3.3%
126.559 1
 
3.3%
127.127 1
 
3.3%
127.386 1
 
3.3%
126.766 1
 
3.3%
127.201 1
 
3.3%
127.02 1
 
3.3%
126.824 1
 
3.3%
127.71 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
126.542 1
3.3%
126.559 1
3.3%
126.593 1
3.3%
126.631 1
3.3%
126.673 1
3.3%
126.766 1
3.3%
126.791 1
3.3%
126.8 1
3.3%
126.824 1
3.3%
126.862 1
3.3%
ValueCountFrequency (%)
127.71 1
3.3%
127.667 1
3.3%
127.386 1
3.3%
127.349 1
3.3%
127.302 1
3.3%
127.26 1
3.3%
127.237 1
3.3%
127.201 1
3.3%
127.147 1
3.3%
127.135 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%
2023-12-10T22:54:06.109055image/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

2023-12-10T22:54:06.273289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:06.499389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

Interactions

2023-12-10T22:53:59.921611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:53:58.314192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:53:58.871229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:53:59.376779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:54:00.105837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:53:58.460410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:53:58.999829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:53:59.530348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:54:00.258559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:53:58.610255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:53:59.118548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:53:59.666681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:54:00.388947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:53:58.732125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:53:59.233320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:53:59.796235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:54:06.607332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점업종명가맹점우편번호시군구명읍면동명위도경도
가맹점번호1.0000.5180.3551.0001.0000.3940.000
가맹점업종명0.5181.0000.1150.8040.9720.5800.000
가맹점우편번호0.3550.1151.0000.9921.0000.7580.588
시군구명1.0000.8040.9921.0001.0000.8710.871
읍면동명1.0000.9721.0001.0001.0000.0000.000
위도0.3940.5800.7580.8710.0001.0000.599
경도0.0000.0000.5880.8710.0000.5991.000
2023-12-10T22:54:06.787303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점우편번호위도경도가맹점업종명
가맹점번호1.000-0.0610.094-0.0880.293
가맹점우편번호-0.0611.000-0.8270.2210.000
위도0.094-0.8271.0000.0220.205
경도-0.0880.2210.0221.0000.000
가맹점업종명0.2930.0000.2050.0001.000

Missing values

2023-12-10T22:54:00.601434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:54:00.852827image/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
02023-01-01700005828999999999999999일반휴게음식12797경기도광주시오포읍37.376127.26<NA>N0
12023-01-01799328341999999999999999일반휴게음식11182경기도포천시소흘읍37.82127.147<NA>N0
22023-01-01700007407999999999999999용역 서비스18146경기도오산시갈곶동37.13127.069<NA>N0
32023-01-01700011084999999999999999보건위생12035경기도남양주시화도읍37.679127.302<NA>N0
42023-01-01700012844999999999999999학원17031경기도용인시 처인구모현읍37.331127.237<NA>N0
52023-01-01700014537999999999999999서적문구13820경기도과천시주암동37.455127.022<NA>N0
62023-01-01700016601999999999999999유통업 영리12108경기도남양주시별내동37.648127.117<NA>N0
72023-01-01799328795999999999999999기타18583경기도화성시장안면37.083126.862<NA>N0
82023-01-01700019702999999999999999음료식품12437경기도가평군조종면37.82127.349<NA>N0
92023-01-01700020234999999999999999전기제품11697경기도의정부시의정부동37.737127.05<NA>N0
일반일간결제일자가맹점번호결제상품ID가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도결제상품명사용여부결제금액
202023-01-01700040623999999999999999일반휴게음식13291경기도성남시 수정구태평동37.443127.135<NA>N0
212023-01-01700040825999999999999999일반휴게음식15382경기도안산시 단원구원곡동37.327126.8<NA>N0
222023-01-01700042488999999999999999유통업 비영리12530경기도양평군청운면37.554127.71<NA>N0
232023-01-01700042959999999999999999일반휴게음식15458경기도안산시 단원구고잔동37.315126.824<NA>N0
242023-01-01700043272999999999999999의류16564경기도수원시 권선구권선동37.26127.02<NA>N0
252023-01-01700046504999999999999999음료식품12767경기도광주시삼동37.41127.201<NA>N0
262023-01-01700046804999999999999999보건위생10240경기도고양시 일산서구탄현동37.697126.766<NA>N0
272023-01-01700046969999999999999999직물11775경기도의정부시신곡동37.748127.069<NA>N0
282023-01-01700049382999999999999999학원12431경기도가평군조종면37.914127.386<NA>N0
292023-01-01700050652999999999999999의원13313경기도성남시 수정구수진동37.439127.127<NA>N0