Overview

Dataset statistics

Number of variables13
Number of observations30
Missing cells32
Missing cells (%)8.2%
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/5568646b-3e18-4754-b33c-8ca90feeb889

Alerts

일반일간결제일자 has constant value ""Constant
결제상품ID 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 위도High correlation
위도 is highly overall correlated with 가맹점우편번호High correlation
가맹점업종명 is highly overall correlated with 가맹점번호High correlation
시도명 is highly imbalanced (78.9%)Imbalance
시군구명 has 1 (3.3%) missing valuesMissing
읍면동명 has 1 (3.3%) missing valuesMissing
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
위도 has 1 (3.3%) zerosZeros
경도 has 1 (3.3%) zerosZeros

Reproduction

Analysis started2024-03-13 11:45:57.328597
Analysis finished2024-03-13 11:45:59.817246
Duration2.49 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
2023-10-01
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

2024-03-13T20:45:59.886961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:45:59.994979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-01 30
100.0%

가맹점번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0664558 × 108
Minimum7.000005 × 108
Maximum7.993288 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:46:00.119195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.000005 × 108
5-th percentile7.0000189 × 108
Q17.0001793 × 108
median7.000295 × 108
Q37.000383 × 108
95-th percentile7.5464946 × 108
Maximum7.993288 × 108
Range99328291
Interquartile range (IQR)20375

Descriptive statistics

Standard deviation25193989
Coefficient of variation (CV)0.035652935
Kurtosis12.206625
Mean7.0664558 × 108
Median Absolute Deviation (MAD)10865.5
Skewness3.6599971
Sum2.1199367 × 1010
Variance6.3473707 × 1014
MonotonicityNot monotonic
2024-03-13T20:46:00.398154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
700000504 1
 
3.3%
700029342 1
 
3.3%
700042334 1
 
3.3%
700042073 1
 
3.3%
700042041 1
 
3.3%
700040999 1
 
3.3%
700038712 1
 
3.3%
700038608 1
 
3.3%
700037388 1
 
3.3%
700035693 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
700000504 1
3.3%
700001452 1
3.3%
700002425 1
3.3%
700004224 1
3.3%
700011116 1
3.3%
700012454 1
3.3%
700017632 1
3.3%
700017924 1
3.3%
700017940 1
3.3%
700019268 1
3.3%
ValueCountFrequency (%)
799328795 1
3.3%
799328022 1
3.3%
700042334 1
3.3%
700042073 1
3.3%
700042041 1
3.3%
700040999 1
3.3%
700038712 1
3.3%
700038608 1
3.3%
700037388 1
3.3%
700035693 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

2024-03-13T20:46:00.578618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:46:00.698006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
999999999999999 30
100.0%

가맹점업종명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
일반/휴게 음식
7 
미용/위생
5 
레저/스포츠 서비스
3 
기타유통
3 
학원
3 
Other values (6)
9 

Length

Max length10
Median length8
Mean length5.6333333
Min length2

Unique

Unique3 ?
Unique (%)10.0%

Sample

1st row레저/스포츠 서비스
2nd row기타유통
3rd row학원
4th row일반유통
5th row레저/스포츠 서비스

Common Values

ValueCountFrequency (%)
일반/휴게 음식 7
23.3%
미용/위생 5
16.7%
레저/스포츠 서비스 3
10.0%
기타유통 3
10.0%
학원 3
10.0%
일반유통 2
 
6.7%
음료/식품 2
 
6.7%
용역서비스 2
 
6.7%
학교/교육 1
 
3.3%
가구 1
 
3.3%

Length

2024-03-13T20:46:00.806180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반/휴게 7
17.5%
음식 7
17.5%
미용/위생 5
12.5%
레저/스포츠 3
7.5%
서비스 3
7.5%
기타유통 3
7.5%
학원 3
7.5%
일반유통 2
 
5.0%
음료/식품 2
 
5.0%
용역서비스 2
 
5.0%
Other values (3) 3
7.5%

가맹점우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13931.967
Minimum10298
Maximum18583
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:46:00.938358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10298
5-th percentile10373.2
Q111195.25
median14614.5
Q315500.75
95-th percentile18305.05
Maximum18583
Range8285
Interquartile range (IQR)4305.5

Descriptive statistics

Standard deviation2675.5069
Coefficient of variation (CV)0.19204087
Kurtosis-1.2435088
Mean13931.967
Median Absolute Deviation (MAD)2246
Skewness0.054395987
Sum417959
Variance7158337.4
MonotonicityNot monotonic
2024-03-13T20:46:01.142745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
10902 1
 
3.3%
15213 1
 
3.3%
12909 1
 
3.3%
13837 1
 
3.3%
10303 1
 
3.3%
14710 1
 
3.3%
15470 1
 
3.3%
15382 1
 
3.3%
10930 1
 
3.3%
16435 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10298 1
3.3%
10303 1
3.3%
10459 1
3.3%
10460 1
3.3%
10537 1
3.3%
10902 1
3.3%
10930 1
3.3%
11140 1
3.3%
11361 1
3.3%
11673 1
3.3%
ValueCountFrequency (%)
18583 1
3.3%
18445 1
3.3%
18134 1
3.3%
16919 1
3.3%
16802 1
3.3%
16435 1
3.3%
16286 1
3.3%
15511 1
3.3%
15470 1
3.3%
15382 1
3.3%

시도명
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
29 
NONE
 
1

Length

Max length4
Median length3
Mean length3.0333333
Min length3

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 29
96.7%
NONE 1
 
3.3%

Length

2024-03-13T20:46:01.327946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:46:01.440463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 29
96.7%
none 1
 
3.3%

시군구명
Text

MISSING 

Distinct19
Distinct (%)65.5%
Missing1
Missing (%)3.3%
Memory size372.0 B
2024-03-13T20:46:01.615391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.0689655
Min length3

Characters and Unicode

Total characters147
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 (%)44.8%

Sample

1st row파주시
2nd row포천시
3rd row시흥시
4th row부천시
5th row오산시
ValueCountFrequency (%)
고양시 5
 
11.6%
안산시 4
 
9.3%
덕양구 4
 
9.3%
부천시 3
 
7.0%
단원구 3
 
7.0%
파주시 2
 
4.7%
화성시 2
 
4.7%
의정부시 2
 
4.7%
수원시 2
 
4.7%
용인시 2
 
4.7%
Other values (14) 14
32.6%
2024-03-13T20:46:01.955722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 30
20.4%
14
 
9.5%
구 14
 
9.5%
양 10
 
6.8%
안 7
 
4.8%
천 6
 
4.1%
산 6
 
4.1%
고 5
 
3.4%
부 5
 
3.4%
원 5
 
3.4%
Other values (27) 45
30.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133
90.5%
Space Separator 14
 
9.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 30
22.6%
구 14
 
10.5%
양 10
 
7.5%
안 7
 
5.3%
천 6
 
4.5%
산 6
 
4.5%
고 5
 
3.8%
부 5
 
3.8%
원 5
 
3.8%
덕 4
 
3.0%
Other values (26) 41
30.8%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133
90.5%
Common 14
 
9.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 30
22.6%
구 14
 
10.5%
양 10
 
7.5%
안 7
 
5.3%
천 6
 
4.5%
산 6
 
4.5%
고 5
 
3.8%
부 5
 
3.8%
원 5
 
3.8%
덕 4
 
3.0%
Other values (26) 41
30.8%
Common
ValueCountFrequency (%)
14
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133
90.5%
ASCII 14
 
9.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 30
22.6%
구 14
 
10.5%
양 10
 
7.5%
안 7
 
5.3%
천 6
 
4.5%
산 6
 
4.5%
고 5
 
3.8%
부 5
 
3.8%
원 5
 
3.8%
덕 4
 
3.0%
Other values (26) 41
30.8%
ASCII
ValueCountFrequency (%)
14
100.0%

읍면동명
Text

MISSING 

Distinct26
Distinct (%)89.7%
Missing1
Missing (%)3.3%
Memory size372.0 B
2024-03-13T20:46:02.160796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters87
Distinct characters45
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

Unique24 ?
Unique (%)82.8%

Sample

1st row동패동
2nd row신북면
3rd row능곡동
4th row송내동
5th row오산동
ValueCountFrequency (%)
주교동 3
 
10.3%
고잔동 2
 
6.9%
조원동 1
 
3.4%
별양동 1
 
3.4%
풍동 1
 
3.4%
심곡본동 1
 
3.4%
금촌동 1
 
3.4%
화서동 1
 
3.4%
이동 1
 
3.4%
지행동 1
 
3.4%
Other values (16) 16
55.2%
2024-03-13T20:46:02.517951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 29
33.3%
주 3
 
3.4%
교 3
 
3.4%
곡 3
 
3.4%
면 2
 
2.3%
신 2
 
2.3%
화 2
 
2.3%
양 2
 
2.3%
부 2
 
2.3%
고 2
 
2.3%
Other values (35) 37
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 29
33.3%
주 3
 
3.4%
교 3
 
3.4%
곡 3
 
3.4%
면 2
 
2.3%
신 2
 
2.3%
화 2
 
2.3%
양 2
 
2.3%
부 2
 
2.3%
고 2
 
2.3%
Other values (35) 37
42.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 29
33.3%
주 3
 
3.4%
교 3
 
3.4%
곡 3
 
3.4%
면 2
 
2.3%
신 2
 
2.3%
화 2
 
2.3%
양 2
 
2.3%
부 2
 
2.3%
고 2
 
2.3%
Other values (35) 37
42.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 29
33.3%
주 3
 
3.4%
교 3
 
3.4%
곡 3
 
3.4%
면 2
 
2.3%
신 2
 
2.3%
화 2
 
2.3%
양 2
 
2.3%
부 2
 
2.3%
고 2
 
2.3%
Other values (35) 37
42.5%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.2396
Minimum0
Maximum37.903
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:46:02.705006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile37.1127
Q137.31025
median37.4555
Q337.662
95-th percentile37.8322
Maximum37.903
Range37.903
Interquartile range (IQR)0.35175

Descriptive statistics

Standard deviation6.8479882
Coefficient of variation (CV)0.18896423
Kurtosis29.933695
Mean36.2396
Median Absolute Deviation (MAD)0.168
Skewness-5.4684317
Sum1087.188
Variance46.894943
MonotonicityNot monotonic
2024-03-13T20:46:02.901359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
37.711 1
 
3.3%
37.346 1
 
3.3%
37.569 1
 
3.3%
37.428 1
 
3.3%
37.672 1
 
3.3%
37.483 1
 
3.3%
37.31 1
 
3.3%
0.0 1
 
3.3%
37.764 1
 
3.3%
37.282 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.0 1
3.3%
37.083 1
3.3%
37.149 1
3.3%
37.204 1
3.3%
37.282 1
3.3%
37.293 1
3.3%
37.299 1
3.3%
37.31 1
3.3%
37.311 1
3.3%
37.317 1
3.3%
ValueCountFrequency (%)
37.903 1
3.3%
37.888 1
3.3%
37.764 1
3.3%
37.739 1
3.3%
37.731 1
3.3%
37.711 1
3.3%
37.672 1
3.3%
37.663 1
3.3%
37.659 1
3.3%
37.657 1
3.3%

경도
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.69517
Minimum0
Maximum127.208
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:46:03.078561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile126.75195
Q1126.811
median126.86
Q3127.0525
95-th percentile127.1553
Maximum127.208
Range127.208
Interquartile range (IQR)0.2415

Descriptive statistics

Standard deviation23.173815
Coefficient of variation (CV)0.18887309
Kurtosis29.997722
Mean122.69517
Median Absolute Deviation (MAD)0.0925
Skewness-5.4769236
Sum3680.855
Variance537.02569
MonotonicityNot monotonic
2024-03-13T20:46:03.235107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
126.832 2
 
6.7%
126.811 2
 
6.7%
126.835 2
 
6.7%
127.063 2
 
6.7%
126.738 1
 
3.3%
127.185 1
 
3.3%
126.993 1
 
3.3%
126.797 1
 
3.3%
126.785 1
 
3.3%
0.0 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
0.0 1
3.3%
126.738 1
3.3%
126.769 1
3.3%
126.776 1
3.3%
126.778 1
3.3%
126.785 1
3.3%
126.797 1
3.3%
126.811 2
6.7%
126.832 2
6.7%
126.835 2
6.7%
ValueCountFrequency (%)
127.208 1
3.3%
127.185 1
3.3%
127.119 1
3.3%
127.074 1
3.3%
127.07 1
3.3%
127.063 2
6.7%
127.057 1
3.3%
127.039 1
3.3%
127.016 1
3.3%
126.994 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%
2024-03-13T20:46:03.390691image/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

2024-03-13T20:46:03.525547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:46:03.950701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

Interactions

2024-03-13T20:45:58.900257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:57.663554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:58.065988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:58.465079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:59.032940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:57.743855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:58.186816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:58.571821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:59.124712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:57.829499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:58.274967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:58.668052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:59.222491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:57.937470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:58.368304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:45:58.779898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T20:46:04.023763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도
가맹점번호1.0000.6910.0000.0000.5561.0000.0000.000
가맹점업종명0.6911.0000.0000.0000.8090.8090.0000.000
가맹점우편번호0.0000.0001.0000.0000.9831.0000.0000.000
시도명0.0000.0000.0001.000NaNNaN0.6550.655
시군구명0.5560.8090.983NaN1.0001.000NaNNaN
읍면동명1.0000.8091.000NaN1.0001.000NaNNaN
위도0.0000.0000.0000.655NaNNaN1.0000.655
경도0.0000.0000.0000.655NaNNaN0.6551.000
2024-03-13T20:46:04.173788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명가맹점업종명
시도명1.0000.000
가맹점업종명0.0001.000
2024-03-13T20:46:04.281148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점우편번호위도경도가맹점업종명시도명
가맹점번호1.0000.043-0.0110.1440.5560.000
가맹점우편번호0.0431.000-0.8820.2560.0000.000
위도-0.011-0.8821.000-0.0590.0000.454
경도0.1440.256-0.0591.0000.0000.454
가맹점업종명0.5560.0000.0000.0001.0000.000
시도명0.0000.0000.4540.4540.0001.000

Missing values

2024-03-13T20:45:59.381664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:45:59.610722image/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.
2024-03-13T20:45:59.751243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

일반일간결제일자가맹점번호결제상품ID가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도결제상품명사용여부결제금액
02023-10-01700000504999999999999999레저/스포츠 서비스10902경기도파주시동패동37.711126.738<NA>N0
12023-10-01799328022999999999999999기타유통11140경기도포천시신북면37.903127.208<NA>N0
22023-10-01700001452999999999999999학원14995경기도시흥시능곡동37.368126.811<NA>N0
32023-10-01700002425999999999999999일반유통14723경기도부천시송내동37.484126.769<NA>N0
42023-10-01700004224999999999999999레저/스포츠 서비스18134경기도오산시오산동37.149127.074<NA>N0
52023-10-01700011116999999999999999음료/식품10298경기도고양시 덕양구주교동37.663126.837<NA>N0
62023-10-01700012454999999999999999학교/교육16919경기도용인시 기흥구언남동37.293127.119<NA>N0
72023-10-01799328795999999999999999기타유통18583경기도화성시장안면37.083126.862<NA>N0
82023-10-01700017632999999999999999미용/위생14519경기도부천시도당동37.516126.778<NA>N0
92023-10-01700017924999999999999999일반유통10459경기도고양시 덕양구주교동37.659126.835<NA>N0
일반일간결제일자가맹점번호결제상품ID가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도결제상품명사용여부결제금액
202023-10-01700032963999999999999999문화/취미11361경기도동두천시지행동37.888127.063<NA>N0
212023-10-01700035588999999999999999미용/위생15511경기도안산시 상록구이동37.311126.858<NA>N0
222023-10-01700035693999999999999999일반/휴게 음식16435경기도수원시 팔달구화서동37.282126.994<NA>N0
232023-10-01700037388999999999999999용역서비스10930경기도파주시금촌동37.764126.776<NA>N0
242023-10-01700038608999999999999999일반/휴게 음식15382NONE<NA><NA>0.00.0<NA>N0
252023-10-01700038712999999999999999음료/식품15470경기도안산시 단원구고잔동37.31126.832<NA>N0
262023-10-01700040999999999999999999미용/위생14710경기도부천시심곡본동37.483126.785<NA>N0
272023-10-01700042041999999999999999학원10303경기도고양시 일산동구풍동37.672126.797<NA>N0
282023-10-01700042073999999999999999일반/휴게 음식13837경기도과천시별양동37.428126.993<NA>N0
292023-10-01700042334999999999999999학원12909경기도하남시망월동37.569127.185<NA>N0