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

DateTime1
Numeric4
Categorical4
Text2
Unsupported1
Boolean1

Dataset

Description샘플 데이터
Author코나아이㈜
URLhttps://bigdata-region.kr/#/dataset/bb4d00dd-b790-413f-9ffb-fc205aafece4

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
가맹점번호 is highly overall correlated with 가맹점업종명High correlation
가맹점우편번호 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 가맹점우편번호 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 가맹점우편번호 and 1 other fieldsHigh correlation
가맹점업종명 is highly overall correlated with 가맹점번호High correlation
결제상품명 has 30 (100.0%) missing valuesMissing
가맹점번호 has unique valuesUnique
가맹점우편번호 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 14:15:42.979384
Analysis finished2023-12-10 14:15:46.792348
Duration3.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일반일간결제일자
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2022-01-01 00:00:00
Maximum2022-01-01 00:00:00
2023-12-10T23:15:46.904975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:47.239375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

가맹점번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0663322 × 108
Minimum7.0000006 × 108
Maximum7.9933461 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:47.470428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.0000006 × 108
5-th percentile7.0000262 × 108
Q17.000102 × 108
median7.0001349 × 108
Q37.0001561 × 108
95-th percentile7.5464139 × 108
Maximum7.9933461 × 108
Range99334552
Interquartile range (IQR)5405.5

Descriptive statistics

Standard deviation25199018
Coefficient of variation (CV)0.035660676
Kurtosis12.206632
Mean7.0663322 × 108
Median Absolute Deviation (MAD)2637
Skewness3.6599985
Sum2.1198997 × 1010
Variance6.3499053 × 1014
MonotonicityNot monotonic
2023-12-10T23:15:47.764830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
700000058 1
 
3.3%
700013077 1
 
3.3%
700016472 1
 
3.3%
700016423 1
 
3.3%
700016212 1
 
3.3%
700016180 1
 
3.3%
700016083 1
 
3.3%
700015696 1
 
3.3%
700015347 1
 
3.3%
700015143 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
700000058 1
3.3%
700000887 1
3.3%
700004743 1
3.3%
700005309 1
3.3%
700005828 1
3.3%
700008110 1
3.3%
700009190 1
3.3%
700010185 1
3.3%
700010258 1
3.3%
700011263 1
3.3%
ValueCountFrequency (%)
799334610 1
3.3%
799334504 1
3.3%
700016472 1
3.3%
700016423 1
3.3%
700016212 1
3.3%
700016180 1
3.3%
700016083 1
3.3%
700015696 1
3.3%
700015347 1
3.3%
700015143 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

2023-12-10T23:15:47.996852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:15:48.172599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
999999999999999 30
100.0%

가맹점업종명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
일반휴게음식
8 
학원
4 
레저업소
3 
건축자재
3 
보건위생
2 
Other values (9)
10 

Length

Max length8
Median length6
Mean length4.5
Min length2

Unique

Unique8 ?
Unique (%)26.7%

Sample

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

Common Values

ValueCountFrequency (%)
일반휴게음식 8
26.7%
학원 4
13.3%
레저업소 3
 
10.0%
건축자재 3
 
10.0%
보건위생 2
 
6.7%
유통업 영리 2
 
6.7%
자동차정비 유지 1
 
3.3%
의류 1
 
3.3%
문화.취미 1
 
3.3%
약국 1
 
3.3%
Other values (4) 4
13.3%

Length

2023-12-10T23:15:48.370728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반휴게음식 8
23.5%
학원 4
11.8%
레저업소 3
 
8.8%
건축자재 3
 
8.8%
보건위생 2
 
5.9%
유통업 2
 
5.9%
영리 2
 
5.9%
신변잡화 1
 
2.9%
서비스 1
 
2.9%
용역 1
 
2.9%
Other values (7) 7
20.6%

가맹점우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14384.933
Minimum10079
Maximum18344
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:48.615581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10079
5-th percentile10413
Q111410
median15007.5
Q317013.5
95-th percentile18121.95
Maximum18344
Range8265
Interquartile range (IQR)5603.5

Descriptive statistics

Standard deviation2884.9287
Coefficient of variation (CV)0.20055211
Kurtosis-1.4787931
Mean14384.933
Median Absolute Deviation (MAD)2501.5
Skewness-0.1708131
Sum431548
Variance8322813.4
MonotonicityNot monotonic
2023-12-10T23:15:48.811621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
11409 1
 
3.3%
11413 1
 
3.3%
15049 1
 
3.3%
17908 1
 
3.3%
16898 1
 
3.3%
10446 1
 
3.3%
10495 1
 
3.3%
10834 1
 
3.3%
15865 1
 
3.3%
18344 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10079 1
3.3%
10386 1
3.3%
10446 1
3.3%
10461 1
3.3%
10495 1
3.3%
10827 1
3.3%
10834 1
3.3%
11409 1
3.3%
11413 1
3.3%
12797 1
3.3%
ValueCountFrequency (%)
18344 1
3.3%
18297 1
3.3%
17908 1
3.3%
17902 1
3.3%
17868 1
3.3%
17598 1
3.3%
17420 1
3.3%
17052 1
3.3%
16898 1
3.3%
16284 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

2023-12-10T23:15:48.979338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:15:49.106260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Text

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:15:49.315426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length4.5333333
Min length3

Characters and Unicode

Total characters136
Distinct characters37
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

Unique13 ?
Unique (%)43.3%

Sample

1st row양주시
2nd row안성시
3rd row안산시 상록구
4th row평택시
5th row파주시
ValueCountFrequency (%)
고양시 4
 
9.8%
평택시 3
 
7.3%
군포시 2
 
4.9%
용인시 2
 
4.9%
시흥시 2
 
4.9%
덕양구 2
 
4.9%
양주시 2
 
4.9%
화성시 2
 
4.9%
파주시 2
 
4.9%
상록구 2
 
4.9%
Other values (17) 18
43.9%
2023-12-10T23:15:49.847842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 32
23.5%
11
 
8.1%
구 11
 
8.1%
양 9
 
6.6%
안 6
 
4.4%
주 5
 
3.7%
산 4
 
2.9%
고 4
 
2.9%
성 4
 
2.9%
평 3
 
2.2%
Other values (27) 47
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
91.9%
Space Separator 11
 
8.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 32
25.6%
구 11
 
8.8%
양 9
 
7.2%
안 6
 
4.8%
주 5
 
4.0%
산 4
 
3.2%
고 4
 
3.2%
성 4
 
3.2%
평 3
 
2.4%
포 3
 
2.4%
Other values (26) 44
35.2%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125
91.9%
Common 11
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 32
25.6%
구 11
 
8.8%
양 9
 
7.2%
안 6
 
4.8%
주 5
 
4.0%
산 4
 
3.2%
고 4
 
3.2%
성 4
 
3.2%
평 3
 
2.4%
포 3
 
2.4%
Other values (26) 44
35.2%
Common
ValueCountFrequency (%)
11
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125
91.9%
ASCII 11
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 32
25.6%
구 11
 
8.8%
양 9
 
7.2%
안 6
 
4.8%
주 5
 
4.0%
산 4
 
3.2%
고 4
 
3.2%
성 4
 
3.2%
평 3
 
2.4%
포 3
 
2.4%
Other values (26) 44
35.2%
ASCII
ValueCountFrequency (%)
11
100.0%

읍면동명
Text

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:15:50.167246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters90
Distinct characters46
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

Unique26 ?
Unique (%)86.7%

Sample

1st row남면
2nd row미양면
3rd row본오동
4th row용이동
5th row법원읍
ValueCountFrequency (%)
남면 2
 
6.7%
합정동 2
 
6.7%
월곶동 1
 
3.3%
보정동 1
 
3.3%
백석동 1
 
3.3%
행신동 1
 
3.3%
파주읍 1
 
3.3%
산본동 1
 
3.3%
배양동 1
 
3.3%
주암동 1
 
3.3%
Other values (18) 18
60.0%
2023-12-10T23:15:51.040127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 22
24.4%
정 5
 
5.6%
면 4
 
4.4%
주 4
 
4.4%
읍 4
 
4.4%
장 3
 
3.3%
원 3
 
3.3%
양 2
 
2.2%
호 2
 
2.2%
남 2
 
2.2%
Other values (36) 39
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 22
24.4%
정 5
 
5.6%
면 4
 
4.4%
주 4
 
4.4%
읍 4
 
4.4%
장 3
 
3.3%
원 3
 
3.3%
양 2
 
2.2%
호 2
 
2.2%
남 2
 
2.2%
Other values (36) 39
43.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 22
24.4%
정 5
 
5.6%
면 4
 
4.4%
주 4
 
4.4%
읍 4
 
4.4%
장 3
 
3.3%
원 3
 
3.3%
양 2
 
2.2%
호 2
 
2.2%
남 2
 
2.2%
Other values (36) 39
43.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 22
24.4%
정 5
 
5.6%
면 4
 
4.4%
주 4
 
4.4%
읍 4
 
4.4%
장 3
 
3.3%
원 3
 
3.3%
양 2
 
2.2%
호 2
 
2.2%
남 2
 
2.2%
Other values (36) 39
43.3%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.4102
Minimum36.983
Maximum37.875
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:51.433156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.983
5-th percentile36.98935
Q137.25375
median37.368
Q337.63825
95-th percentile37.85825
Maximum37.875
Range0.892
Interquartile range (IQR)0.3845

Descriptive statistics

Standard deviation0.26488389
Coefficient of variation (CV)0.0070805259
Kurtosis-0.65370547
Mean37.4102
Median Absolute Deviation (MAD)0.1505
Skewness0.15123704
Sum1122.306
Variance0.070163476
MonotonicityNot monotonic
2023-12-10T23:15:51.781496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
37.875 1
 
3.3%
37.865 1
 
3.3%
37.354 1
 
3.3%
36.991 1
 
3.3%
37.319 1
 
3.3%
37.646 1
 
3.3%
37.624 1
 
3.3%
37.83 1
 
3.3%
37.36 1
 
3.3%
37.219 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
36.983 1
3.3%
36.988 1
3.3%
36.991 1
3.3%
36.994 1
3.3%
37.115 1
3.3%
37.219 1
3.3%
37.236 1
3.3%
37.242 1
3.3%
37.289 1
3.3%
37.302 1
3.3%
ValueCountFrequency (%)
37.875 1
3.3%
37.865 1
3.3%
37.85 1
3.3%
37.83 1
3.3%
37.669 1
3.3%
37.656 1
3.3%
37.646 1
3.3%
37.643 1
3.3%
37.624 1
3.3%
37.52 1
3.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98977
Minimum126.671
Maximum127.631
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:52.147139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.671
5-th percentile126.7409
Q1126.842
median126.9685
Q3127.1145
95-th percentile127.25595
Maximum127.631
Range0.96
Interquartile range (IQR)0.2725

Descriptive statistics

Standard deviation0.20096606
Coefficient of variation (CV)0.0015825374
Kurtosis2.1019555
Mean126.98977
Median Absolute Deviation (MAD)0.135
Skewness1.0441737
Sum3809.693
Variance0.040387357
MonotonicityNot monotonic
2023-12-10T23:15:52.338710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
126.952 2
 
6.7%
126.835 2
 
6.7%
126.995 1
 
3.3%
126.985 1
 
3.3%
126.742 1
 
3.3%
127.096 1
 
3.3%
127.115 1
 
3.3%
126.787 1
 
3.3%
126.832 1
 
3.3%
126.929 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
126.671 1
3.3%
126.74 1
3.3%
126.742 1
3.3%
126.763 1
3.3%
126.787 1
3.3%
126.832 1
3.3%
126.835 2
6.7%
126.863 1
3.3%
126.865 1
3.3%
126.866 1
3.3%
ValueCountFrequency (%)
127.631 1
3.3%
127.26 1
3.3%
127.251 1
3.3%
127.207 1
3.3%
127.189 1
3.3%
127.138 1
3.3%
127.127 1
3.3%
127.115 1
3.3%
127.113 1
3.3%
127.096 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%
2023-12-10T23:15:52.543247image/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

2023-12-10T23:15:52.739845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:15:52.912823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

Interactions

2023-12-10T23:15:45.537214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:43.734618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:44.288290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:44.872576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:45.723622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:43.874849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:44.436787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:45.058087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:45.881104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:44.006277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:44.586741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:45.230942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:46.024842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:44.135300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:44.740316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:45.388097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:15:53.029093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점업종명가맹점우편번호시군구명읍면동명위도경도
가맹점번호1.0001.0000.0001.0001.0000.0000.451
가맹점업종명1.0001.0000.0000.5720.9850.4890.000
가맹점우편번호0.0000.0001.0000.9541.0000.8690.689
시군구명1.0000.5720.9541.0001.0001.0000.991
읍면동명1.0000.9851.0001.0001.0001.0001.000
위도0.0000.4890.8691.0001.0001.0000.776
경도0.4510.0000.6890.9911.0000.7761.000
2023-12-10T23:15:53.221678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점우편번호위도경도가맹점업종명
가맹점번호1.000-0.003-0.056-0.1800.756
가맹점우편번호-0.0031.000-0.9150.5500.000
위도-0.056-0.9151.000-0.5320.145
경도-0.1800.550-0.5321.0000.000
가맹점업종명0.7560.0000.1450.0001.000

Missing values

2023-12-10T23:15:46.334934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:15:46.683090image/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
02022-01-01700000058999999999999999일반휴게음식11409경기도양주시남면37.875126.995<NA>N0
12022-01-01799334504999999999999999자동차정비 유지17598경기도안성시미양면36.983127.251<NA>N0
22022-01-01700000887999999999999999의류15562경기도안산시 상록구본오동37.289126.866<NA>N0
32022-01-01700004743999999999999999레저업소17868경기도평택시용이동36.994127.138<NA>N0
42022-01-01700005309999999999999999건축자재10827경기도파주시법원읍37.85126.863<NA>N0
52022-01-01700005828999999999999999일반휴게음식12797경기도광주시오포읍37.376127.26<NA>N0
62022-01-01700008110999999999999999문화.취미13307경기도성남시 수정구태평동37.444127.127<NA>N0
72022-01-01799334610999999999999999약국10386경기도고양시 일산서구주엽동37.669126.763<NA>N0
82022-01-01700009190999999999999999일반휴게음식17902경기도평택시합정동36.988127.113<NA>N0
92022-01-01700010185999999999999999신변잡화18297경기도화성시매송면37.242126.952<NA>N0
일반일간결제일자가맹점번호결제상품ID가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도결제상품명사용여부결제금액
202022-01-01700014497999999999999999레저업소17420경기도이천시장호원읍37.115127.631<NA>N0
212022-01-01700014537999999999999999서적문구13820경기도과천시주암동37.455127.022<NA>N0
222022-01-01700015143999999999999999학원18344경기도화성시배양동37.219126.989<NA>N0
232022-01-01700015347999999999999999레저업소15865경기도군포시산본동37.36126.929<NA>N0
242022-01-01700015696999999999999999용역 서비스10834경기도파주시파주읍37.83126.832<NA>N0
252022-01-01700016083999999999999999광학제품10495경기도고양시 덕양구행신동37.624126.835<NA>N0
262022-01-01700016180999999999999999일반휴게음식10446경기도고양시 일산동구백석동37.646126.787<NA>N0
272022-01-01700016212999999999999999학원16898경기도용인시 기흥구보정동37.319127.115<NA>N0
282022-01-01700016423999999999999999유통업 영리17908경기도평택시합정동36.991127.096<NA>N0
292022-01-01700016472999999999999999유통업 영리15049경기도시흥시정왕동37.354126.742<NA>N0