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

Categorical4
Numeric4
Text3
Unsupported1
Boolean1

Dataset

Description샘플 데이터
Author코나아이㈜
URLhttps://bigdata-region.kr/#/dataset/179ea443-7193-4bac-8ace-9bdfc5415269

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 14:14:45.263957
Analysis finished2023-12-10 14:14:49.849275
Duration4.59 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
2022-02-01
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-02-01
2nd row2022-02-01
3rd row2022-02-01
4th row2022-02-01
5th row2022-02-01

Common Values

ValueCountFrequency (%)
2022-02-01 30
100.0%

Length

2023-12-10T23:14:49.961892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:50.224047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-02-01 30
100.0%

가맹점번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.556644 × 108
Minimum7.0000068 × 108
Maximum7.9825695 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:14:50.390834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.0000068 × 108
5-th percentile7.0000097 × 108
Q17.0000311 × 108
median7.9815189 × 108
Q37.9825173 × 108
95-th percentile7.9825531 × 108
Maximum7.9825695 × 108
Range98256273
Interquartile range (IQR)98248620

Descriptive statistics

Standard deviation49506373
Coefficient of variation (CV)0.065513703
Kurtosis-2.0620528
Mean7.556644 × 108
Median Absolute Deviation (MAD)103423.5
Skewness-0.28343978
Sum2.2669932 × 1010
Variance2.450881 × 1015
MonotonicityNot monotonic
2023-12-10T23:14:50.672880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
798247640 1
 
3.3%
798252604 1
 
3.3%
700006397 1
 
3.3%
798256949 1
 
3.3%
700005788 1
 
3.3%
798255326 1
 
3.3%
700005269 1
 
3.3%
798255300 1
 
3.3%
700004775 1
 
3.3%
798255065 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
700000676 1
3.3%
700000916 1
3.3%
700001030 1
3.3%
700002638 1
3.3%
700002684 1
3.3%
700002855 1
3.3%
700002992 1
3.3%
700003023 1
3.3%
700003374 1
3.3%
700004775 1
3.3%
ValueCountFrequency (%)
798256949 1
3.3%
798255326 1
3.3%
798255300 1
3.3%
798255065 1
3.3%
798253753 1
3.3%
798253721 1
3.3%
798252604 1
3.3%
798251924 1
3.3%
798251152 1
3.3%
798249884 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

2023-12-10T23:14:50.879775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:51.054897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
999999999999999 30
100.0%

가맹점업종명
Text

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:14:51.264752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.2666667
Min length2

Characters and Unicode

Total characters128
Distinct characters42
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

Unique9 ?
Unique (%)30.0%

Sample

1st row서적문구
2nd row일반휴게음식
3rd row건축자재
4th row일반휴게음식
5th row직물
ValueCountFrequency (%)
일반휴게음식 9
29.0%
레저업소 4
12.9%
서적문구 2
 
6.5%
건축자재 2
 
6.5%
음료식품 2
 
6.5%
보건위생 2
 
6.5%
직물 1
 
3.2%
약국 1
 
3.2%
레져용품 1
 
3.2%
의류 1
 
3.2%
Other values (6) 6
19.4%
2023-12-10T23:14:51.885591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
음 11
 
8.6%
식 11
 
8.6%
일 9
 
7.0%
휴 9
 
7.0%
게 9
 
7.0%
반 9
 
7.0%
레 5
 
3.9%
품 4
 
3.1%
건 4
 
3.1%
소 4
 
3.1%
Other values (32) 53
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 127
99.2%
Space Separator 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
음 11
 
8.7%
식 11
 
8.7%
일 9
 
7.1%
휴 9
 
7.1%
게 9
 
7.1%
반 9
 
7.1%
레 5
 
3.9%
품 4
 
3.1%
건 4
 
3.1%
소 4
 
3.1%
Other values (31) 52
40.9%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 127
99.2%
Common 1
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
음 11
 
8.7%
식 11
 
8.7%
일 9
 
7.1%
휴 9
 
7.1%
게 9
 
7.1%
반 9
 
7.1%
레 5
 
3.9%
품 4
 
3.1%
건 4
 
3.1%
소 4
 
3.1%
Other values (31) 52
40.9%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 127
99.2%
ASCII 1
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
음 11
 
8.7%
식 11
 
8.7%
일 9
 
7.1%
휴 9
 
7.1%
게 9
 
7.1%
반 9
 
7.1%
레 5
 
3.9%
품 4
 
3.1%
건 4
 
3.1%
소 4
 
3.1%
Other values (31) 52
40.9%
ASCII
ValueCountFrequency (%)
1
100.0%

가맹점우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14885.567
Minimum10070
Maximum18624
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:14:52.124115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10070
5-th percentile10189.35
Q112403.5
median15299.5
Q317044.75
95-th percentile18534.7
Maximum18624
Range8554
Interquartile range (IQR)4641.25

Descriptive statistics

Standard deviation2860.598
Coefficient of variation (CV)0.19217259
Kurtosis-1.191259
Mean14885.567
Median Absolute Deviation (MAD)2191.5
Skewness-0.34371699
Sum446567
Variance8183020.7
MonotonicityNot monotonic
2023-12-10T23:14:52.358362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
16527 1
 
3.3%
12945 1
 
3.3%
15239 1
 
3.3%
13961 1
 
3.3%
17052 1
 
3.3%
10422 1
 
3.3%
17328 1
 
3.3%
12223 1
 
3.3%
18434 1
 
3.3%
11759 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10070 1
3.3%
10098 1
3.3%
10301 1
3.3%
10422 1
3.3%
11451 1
3.3%
11678 1
3.3%
11759 1
3.3%
12223 1
3.3%
12945 1
3.3%
13595 1
3.3%
ValueCountFrequency (%)
18624 1
3.3%
18550 1
3.3%
18516 1
3.3%
18434 1
3.3%
18384 1
3.3%
18104 1
3.3%
17328 1
3.3%
17052 1
3.3%
17023 1
3.3%
16696 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

2023-12-10T23:14:52.660659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:52.920870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Text

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:14:53.211559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.9
Min length3

Characters and Unicode

Total characters147
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

Unique13 ?
Unique (%)43.3%

Sample

1st row수원시 영통구
2nd row수원시 장안구
3rd row수원시 권선구
4th row성남시 수정구
5th row화성시
ValueCountFrequency (%)
화성시 5
 
11.6%
수원시 4
 
9.3%
고양시 2
 
4.7%
일산동구 2
 
4.7%
의정부시 2
 
4.7%
용인시 2
 
4.7%
처인구 2
 
4.7%
안산시 2
 
4.7%
단원구 2
 
4.7%
영통구 2
 
4.7%
Other values (16) 18
41.9%
2023-12-10T23:14:53.746432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 31
21.1%
13
 
8.8%
구 13
 
8.8%
성 7
 
4.8%
원 6
 
4.1%
화 5
 
3.4%
수 5
 
3.4%
산 5
 
3.4%
양 5
 
3.4%
안 5
 
3.4%
Other values (28) 52
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 134
91.2%
Space Separator 13
 
8.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 31
23.1%
구 13
 
9.7%
성 7
 
5.2%
원 6
 
4.5%
화 5
 
3.7%
수 5
 
3.7%
산 5
 
3.7%
양 5
 
3.7%
안 5
 
3.7%
남 4
 
3.0%
Other values (27) 48
35.8%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 134
91.2%
Common 13
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 31
23.1%
구 13
 
9.7%
성 7
 
5.2%
원 6
 
4.5%
화 5
 
3.7%
수 5
 
3.7%
산 5
 
3.7%
양 5
 
3.7%
안 5
 
3.7%
남 4
 
3.0%
Other values (27) 48
35.8%
Common
ValueCountFrequency (%)
13
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 134
91.2%
ASCII 13
 
8.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 31
23.1%
구 13
 
9.7%
성 7
 
5.2%
원 6
 
4.5%
화 5
 
3.7%
수 5
 
3.7%
산 5
 
3.7%
양 5
 
3.7%
안 5
 
3.7%
남 4
 
3.0%
Other values (27) 48
35.8%
ASCII
ValueCountFrequency (%)
13
100.0%

읍면동명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:14:54.063576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters90
Distinct characters48
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 row매탄동
2nd row조원동
3rd row권선동
4th row창곡동
5th row정남면
ValueCountFrequency (%)
매탄동 1
 
3.3%
조원동 1
 
3.3%
석수동 1
 
3.3%
김량장동 1
 
3.3%
장항동 1
 
3.3%
부발읍 1
 
3.3%
평내동 1
 
3.3%
반송동 1
 
3.3%
금오동 1
 
3.3%
구래동 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:14:54.597333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 25
27.8%
장 4
 
4.4%
읍 3
 
3.3%
곡 3
 
3.3%
정 3
 
3.3%
남 2
 
2.2%
수 2
 
2.2%
가 2
 
2.2%
선 2
 
2.2%
반 2
 
2.2%
Other values (38) 42
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 25
27.8%
장 4
 
4.4%
읍 3
 
3.3%
곡 3
 
3.3%
정 3
 
3.3%
남 2
 
2.2%
수 2
 
2.2%
가 2
 
2.2%
선 2
 
2.2%
반 2
 
2.2%
Other values (38) 42
46.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 25
27.8%
장 4
 
4.4%
읍 3
 
3.3%
곡 3
 
3.3%
정 3
 
3.3%
남 2
 
2.2%
수 2
 
2.2%
가 2
 
2.2%
선 2
 
2.2%
반 2
 
2.2%
Other values (38) 42
46.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 25
27.8%
장 4
 
4.4%
읍 3
 
3.3%
곡 3
 
3.3%
정 3
 
3.3%
남 2
 
2.2%
수 2
 
2.2%
가 2
 
2.2%
선 2
 
2.2%
반 2
 
2.2%
Other values (38) 42
46.7%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.407033
Minimum37.116
Maximum37.837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:14:54.830768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.116
5-th percentile37.1709
Q137.25725
median37.337
Q337.6055
95-th percentile37.74865
Maximum37.837
Range0.721
Interquartile range (IQR)0.34825

Descriptive statistics

Standard deviation0.2032392
Coefficient of variation (CV)0.0054331814
Kurtosis-0.87856443
Mean37.407033
Median Absolute Deviation (MAD)0.1275
Skewness0.60277319
Sum1122.211
Variance0.041306171
MonotonicityNot monotonic
2023-12-10T23:14:55.115541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
37.269 1
 
3.3%
37.541 1
 
3.3%
37.336 1
 
3.3%
37.416 1
 
3.3%
37.235 1
 
3.3%
37.648 1
 
3.3%
37.26 1
 
3.3%
37.646 1
 
3.3%
37.208 1
 
3.3%
37.75 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
37.116 1
3.3%
37.161 1
3.3%
37.183 1
3.3%
37.208 1
3.3%
37.211 1
3.3%
37.229 1
3.3%
37.235 1
3.3%
37.257 1
3.3%
37.258 1
3.3%
37.26 1
3.3%
ValueCountFrequency (%)
37.837 1
3.3%
37.75 1
3.3%
37.747 1
3.3%
37.67 1
3.3%
37.648 1
3.3%
37.646 1
3.3%
37.637 1
3.3%
37.627 1
3.3%
37.541 1
3.3%
37.486 1
3.3%

경도
Real number (ℝ)

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.99247
Minimum126.628
Maximum127.475
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:14:55.343148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.628
5-th percentile126.7152
Q1126.8165
median127.0265
Q3127.064
95-th percentile127.22905
Maximum127.475
Range0.847
Interquartile range (IQR)0.2475

Descriptive statistics

Standard deviation0.19096032
Coefficient of variation (CV)0.0015037138
Kurtosis0.068540582
Mean126.99247
Median Absolute Deviation (MAD)0.1185
Skewness0.12586514
Sum3809.774
Variance0.036465844
MonotonicityNot monotonic
2023-12-10T23:14:55.602079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
127.064 4
 
13.3%
127.056 2
 
6.7%
127.009 2
 
6.7%
127.03 1
 
3.3%
126.81 1
 
3.3%
126.913 1
 
3.3%
127.202 1
 
3.3%
126.78 1
 
3.3%
127.475 1
 
3.3%
127.234 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
126.628 1
3.3%
126.708 1
3.3%
126.724 1
3.3%
126.743 1
3.3%
126.78 1
3.3%
126.781 1
3.3%
126.791 1
3.3%
126.81 1
3.3%
126.836 1
3.3%
126.913 1
3.3%
ValueCountFrequency (%)
127.475 1
 
3.3%
127.234 1
 
3.3%
127.223 1
 
3.3%
127.221 1
 
3.3%
127.202 1
 
3.3%
127.15 1
 
3.3%
127.113 1
 
3.3%
127.064 4
13.3%
127.056 2
6.7%
127.044 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%
2023-12-10T23:14:55.760761image/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

2023-12-10T23:14:55.909719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:56.088724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

Interactions

2023-12-10T23:14:48.454321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:45.928854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:46.746384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:47.379786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:48.653135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:46.142782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:46.946769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:47.532969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:48.791059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:46.323079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:47.076557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:47.668210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:48.990421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:46.530087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:47.250668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:48.281241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:14:56.190137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점업종명가맹점우편번호시군구명읍면동명위도경도
가맹점번호1.0000.4580.6160.4711.0000.0000.603
가맹점업종명0.4581.0000.0000.3101.0000.5640.515
가맹점우편번호0.6160.0001.0001.0001.0000.8430.661
시군구명0.4710.3101.0001.0001.0000.9440.926
읍면동명1.0001.0001.0001.0001.0001.0001.000
위도0.0000.5640.8430.9441.0001.0000.000
경도0.6030.5150.6610.9261.0000.0001.000
2023-12-10T23:14:56.363627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점우편번호위도경도
가맹점번호1.000-0.0630.107-0.094
가맹점우편번호-0.0631.000-0.9500.218
위도0.107-0.9501.000-0.113
경도-0.0940.218-0.1131.000

Missing values

2023-12-10T23:14:49.266295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:14:49.695473image/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
02022-02-01798247640999999999999999서적문구16527경기도수원시 영통구매탄동37.269127.056<NA>N0
12022-02-01798055862999999999999999일반휴게음식16284경기도수원시 장안구조원동37.302127.009<NA>N0
22022-02-01798247931999999999999999건축자재16566경기도수원시 권선구권선동37.258127.023<NA>N0
32022-02-01700000676999999999999999일반휴게음식13642경기도성남시 수정구창곡동37.473127.15<NA>N0
42022-02-01798248336999999999999999직물18516경기도화성시정남면37.183126.998<NA>N0
52022-02-01700000916999999999999999약국11451경기도양주시덕정동37.837127.064<NA>N0
62022-02-01798248951999999999999999건축자재18550경기도화성시송산면37.211126.743<NA>N0
72022-02-01798056139999999999999999음료식품13595경기도성남시 분당구수내동37.379127.113<NA>N0
82022-02-01798248985999999999999999일반휴게음식14634경기도부천시심곡동37.486126.781<NA>N0
92022-02-01700001030999999999999999레져용품18384경기도화성시반월동37.229127.064<NA>N0
일반일간결제일자가맹점번호결제상품ID가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도결제상품명사용여부결제금액
202022-02-01798253753999999999999999레저업소10301경기도고양시 일산동구풍동37.67126.791<NA>N0
212022-02-01700003374999999999999999일반휴게음식10070경기도김포시구래동37.637126.628<NA>N0
222022-02-01798255065999999999999999서적문구11759경기도의정부시금오동37.75127.056<NA>N0
232022-02-01700004775999999999999999레저업소18434경기도화성시반송동37.208127.064<NA>N0
242022-02-01798255300999999999999999음료식품12223경기도남양주시평내동37.646127.234<NA>N0
252022-02-01700005269999999999999999학원17328경기도이천시부발읍37.26127.475<NA>N0
262022-02-01798255326999999999999999보건위생10422경기도고양시 일산동구장항동37.648126.78<NA>N0
272022-02-01700005788999999999999999레저업소17052경기도용인시 처인구김량장동37.235127.202<NA>N0
282022-02-01798256949999999999999999보건위생13961경기도안양시 만안구석수동37.416126.913<NA>N0
292022-02-01700006397999999999999999일반휴게음식15239경기도안산시 단원구선부동37.336126.81<NA>N0