Overview

Dataset statistics

Number of variables13
Number of observations30
Missing cells34
Missing cells (%)8.7%
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/355912a1-5335-42a1-942a-d76e227b2a91

Alerts

일반일간결제일자 has constant value ""Constant
결제상품ID has constant value ""Constant
사용여부 has constant value ""Constant
결제금액 has constant value ""Constant
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 시도명High correlation
시도명 is highly overall correlated with 가맹점우편번호 and 2 other fieldsHigh correlation
시도명 is highly imbalanced (64.7%)Imbalance
시군구명 has 2 (6.7%) missing valuesMissing
읍면동명 has 2 (6.7%) missing valuesMissing
결제상품명 has 30 (100.0%) missing valuesMissing
가맹점번호 has unique valuesUnique
결제상품명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
위도 has 2 (6.7%) zerosZeros
경도 has 2 (6.7%) zerosZeros

Reproduction

Analysis started2024-03-13 11:55:23.584409
Analysis finished2024-03-13 11:55:25.988328
Duration2.4 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
Minimum2023-08-01 00:00:00
Maximum2023-08-01 00:00:00
2024-03-13T20:55:26.054024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:26.167755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

가맹점번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0664032 × 108
Minimum7.0000198 × 108
Maximum7.9933352 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:26.277461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.0000198 × 108
5-th percentile7.0000456 × 108
Q17.0001102 × 108
median7.0001854 × 108
Q37.0003175 × 108
95-th percentile7.5465167 × 108
Maximum7.9933352 × 108
Range99331535
Interquartile range (IQR)20731.5

Descriptive statistics

Standard deviation25196664
Coefficient of variation (CV)0.035656987
Kurtosis12.206626
Mean7.0664032 × 108
Median Absolute Deviation (MAD)9270
Skewness3.6599974
Sum2.1199209 × 1010
Variance6.3487189 × 1014
MonotonicityNot monotonic
2024-03-13T20:55:26.705055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
700001981 1
 
3.3%
700018262 1
 
3.3%
700041831 1
 
3.3%
700041263 1
 
3.3%
700036982 1
 
3.3%
700036665 1
 
3.3%
700033229 1
 
3.3%
700033016 1
 
3.3%
700027942 1
 
3.3%
700027673 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
700001981 1
3.3%
700004192 1
3.3%
700005007 1
3.3%
700005040 1
3.3%
700005104 1
3.3%
700008242 1
3.3%
700009937 1
3.3%
700010566 1
3.3%
700012366 1
3.3%
700012617 1
3.3%
ValueCountFrequency (%)
799333516 1
3.3%
799332455 1
3.3%
700041831 1
3.3%
700041263 1
3.3%
700036982 1
3.3%
700036665 1
3.3%
700033229 1
3.3%
700033016 1
3.3%
700027942 1
3.3%
700027673 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

2024-03-13T20:55:26.857126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:26.967260image/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
일반/휴게 음식
9 
미용/위생
6 
용역서비스
4 
레저/스포츠 서비스
3 
주유/충전소
1 
Other values (7)
7 

Length

Max length10
Median length9
Mean length6.4
Min length2

Unique

Unique8 ?
Unique (%)26.7%

Sample

1st row일반/휴게 음식
2nd row일반/휴게 음식
3rd row미용/위생
4th row미용/위생
5th row일반/휴게 음식

Common Values

ValueCountFrequency (%)
일반/휴게 음식 9
30.0%
미용/위생 6
20.0%
용역서비스 4
13.3%
레저/스포츠 서비스 3
 
10.0%
주유/충전소 1
 
3.3%
전자제품 1
 
3.3%
학원 1
 
3.3%
대형유통 1
 
3.3%
의류 1
 
3.3%
레저/문화 용품 1
 
3.3%
Other values (2) 2
 
6.7%

Length

2024-03-13T20:55:27.078888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반/휴게 9
20.5%
음식 9
20.5%
미용/위생 6
13.6%
용역서비스 4
9.1%
레저/스포츠 3
 
6.8%
서비스 3
 
6.8%
주유/충전소 1
 
2.3%
전자제품 1
 
2.3%
학원 1
 
2.3%
대형유통 1
 
2.3%
Other values (6) 6
13.6%

가맹점우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14284.467
Minimum10460
Maximum18584
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:27.197903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10460
5-th percentile10469.55
Q111413.25
median14317
Q316961.25
95-th percentile18469.9
Maximum18584
Range8124
Interquartile range (IQR)5548

Descriptive statistics

Standard deviation2964.2857
Coefficient of variation (CV)0.20751812
Kurtosis-1.5183792
Mean14284.467
Median Absolute Deviation (MAD)2840.5
Skewness0.063770793
Sum428534
Variance8786989.9
MonotonicityNot monotonic
2024-03-13T20:55:27.312875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
10500 2
 
6.7%
10929 1
 
3.3%
12514 1
 
3.3%
17772 1
 
3.3%
16236 1
 
3.3%
17006 1
 
3.3%
12041 1
 
3.3%
14349 1
 
3.3%
15262 1
 
3.3%
10480 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
10460 1
3.3%
10461 1
3.3%
10480 1
3.3%
10500 2
6.7%
10909 1
3.3%
10929 1
3.3%
11325 1
3.3%
11678 1
3.3%
11757 1
3.3%
12041 1
3.3%
ValueCountFrequency (%)
18584 1
3.3%
18523 1
3.3%
18405 1
3.3%
18286 1
3.3%
17936 1
3.3%
17825 1
3.3%
17772 1
3.3%
17006 1
3.3%
16827 1
3.3%
16236 1
3.3%

시도명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
28 
NONE
 
2

Length

Max length4
Median length3
Mean length3.0666667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 28
93.3%
NONE 2
 
6.7%

Length

2024-03-13T20:55:27.458406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:27.574147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 28
93.3%
none 2
 
6.7%

시군구명
Text

MISSING 

Distinct14
Distinct (%)50.0%
Missing2
Missing (%)6.7%
Memory size372.0 B
2024-03-13T20:55:27.735534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.7142857
Min length3

Characters and Unicode

Total characters132
Distinct characters36
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

Unique7 ?
Unique (%)25.0%

Sample

1st row파주시
2nd row시흥시
3rd row화성시
4th row광명시
5th row동두천시
ValueCountFrequency (%)
고양시 5
12.8%
덕양구 5
12.8%
화성시 4
10.3%
광명시 3
 
7.7%
평택시 3
 
7.7%
파주시 2
 
5.1%
의정부시 2
 
5.1%
안산시 2
 
5.1%
상록구 2
 
5.1%
용인시 2
 
5.1%
Other values (9) 9
23.1%
2024-03-13T20:55:28.037900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
22.0%
양 11
 
8.3%
구 11
 
8.3%
11
 
8.3%
성 5
 
3.8%
고 5
 
3.8%
덕 5
 
3.8%
화 4
 
3.0%
광 3
 
2.3%
평 3
 
2.3%
Other values (26) 45
34.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 121
91.7%
Space Separator 11
 
8.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
24.0%
양 11
 
9.1%
구 11
 
9.1%
성 5
 
4.1%
고 5
 
4.1%
덕 5
 
4.1%
화 4
 
3.3%
광 3
 
2.5%
평 3
 
2.5%
택 3
 
2.5%
Other values (25) 42
34.7%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 121
91.7%
Common 11
 
8.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
24.0%
양 11
 
9.1%
구 11
 
9.1%
성 5
 
4.1%
고 5
 
4.1%
덕 5
 
4.1%
화 4
 
3.3%
광 3
 
2.5%
평 3
 
2.5%
택 3
 
2.5%
Other values (25) 42
34.7%
Common
ValueCountFrequency (%)
11
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 121
91.7%
ASCII 11
 
8.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
24.0%
양 11
 
9.1%
구 11
 
9.1%
성 5
 
4.1%
고 5
 
4.1%
덕 5
 
4.1%
화 4
 
3.3%
광 3
 
2.5%
평 3
 
2.5%
택 3
 
2.5%
Other values (25) 42
34.7%
ASCII
ValueCountFrequency (%)
11
100.0%

읍면동명
Text

MISSING 

Distinct26
Distinct (%)92.9%
Missing2
Missing (%)6.7%
Memory size372.0 B
2024-03-13T20:55:28.315197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9285714
Min length2

Characters and Unicode

Total characters82
Distinct characters41
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 (%)85.7%

Sample

1st row금촌동
2nd row정왕동
3rd row병점동
4th row광명동
5th row생연동
ValueCountFrequency (%)
화정동 2
 
7.1%
주교동 2
 
7.1%
금촌동 1
 
3.6%
야당동 1
 
3.6%
우만동 1
 
3.6%
중동 1
 
3.6%
오남읍 1
 
3.6%
일직동 1
 
3.6%
성사동 1
 
3.6%
성포동 1
 
3.6%
Other values (16) 16
57.1%
2024-03-13T20:55:28.652003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 24
29.3%
정 5
 
6.1%
면 3
 
3.7%
교 3
 
3.7%
화 2
 
2.4%
남 2
 
2.4%
금 2
 
2.4%
읍 2
 
2.4%
중 2
 
2.4%
안 2
 
2.4%
Other values (31) 35
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 82
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 24
29.3%
정 5
 
6.1%
면 3
 
3.7%
교 3
 
3.7%
화 2
 
2.4%
남 2
 
2.4%
금 2
 
2.4%
읍 2
 
2.4%
중 2
 
2.4%
안 2
 
2.4%
Other values (31) 35
42.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 82
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 24
29.3%
정 5
 
6.1%
면 3
 
3.7%
교 3
 
3.7%
화 2
 
2.4%
남 2
 
2.4%
금 2
 
2.4%
읍 2
 
2.4%
중 2
 
2.4%
안 2
 
2.4%
Other values (31) 35
42.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 82
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 24
29.3%
정 5
 
6.1%
면 3
 
3.7%
교 3
 
3.7%
화 2
 
2.4%
남 2
 
2.4%
금 2
 
2.4%
읍 2
 
2.4%
중 2
 
2.4%
안 2
 
2.4%
Other values (31) 35
42.7%

위도
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.939367
Minimum0
Maximum37.911
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:28.791835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16.6428
Q137.2295
median37.363
Q337.6525
95-th percentile37.75585
Maximum37.911
Range37.911
Interquartile range (IQR)0.423

Descriptive statistics

Standard deviation9.5008388
Coefficient of variation (CV)0.27192361
Kurtosis12.185621
Mean34.939367
Median Absolute Deviation (MAD)0.274
Skewness-3.6556465
Sum1048.181
Variance90.265938
MonotonicityNot monotonic
2024-03-13T20:55:28.927213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
37.632 2
 
6.7%
0.0 2
 
6.7%
37.759 1
 
3.3%
37.709 1
 
3.3%
37.066 1
 
3.3%
37.286 1
 
3.3%
37.276 1
 
3.3%
37.695 1
 
3.3%
37.415 1
 
3.3%
37.642 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0.0 2
6.7%
36.984 1
3.3%
37.009 1
3.3%
37.066 1
3.3%
37.083 1
3.3%
37.141 1
3.3%
37.214 1
3.3%
37.276 1
3.3%
37.277 1
3.3%
37.286 1
3.3%
ValueCountFrequency (%)
37.911 1
3.3%
37.759 1
3.3%
37.752 1
3.3%
37.748 1
3.3%
37.709 1
3.3%
37.695 1
3.3%
37.657 1
3.3%
37.656 1
3.3%
37.642 1
3.3%
37.632 2
6.7%

경도
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.4777
Minimum0
Maximum127.206
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:29.086489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile57.0303
Q1126.83125
median126.876
Q3127.05275
95-th percentile127.135
Maximum127.206
Range127.206
Interquartile range (IQR)0.2215

Descriptive statistics

Standard deviation32.20606
Coefficient of variation (CV)0.27183225
Kurtosis12.206158
Mean118.4777
Median Absolute Deviation (MAD)0.111
Skewness-3.6599004
Sum3554.331
Variance1037.2303
MonotonicityNot monotonic
2024-03-13T20:55:29.224739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 2
 
6.7%
126.776 1
 
3.3%
126.734 1
 
3.3%
127.058 1
 
3.3%
127.032 1
 
3.3%
127.153 1
 
3.3%
127.206 1
 
3.3%
126.886 1
 
3.3%
126.85 1
 
3.3%
126.842 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0.0 2
6.7%
126.734 1
3.3%
126.763 1
3.3%
126.776 1
3.3%
126.827 1
3.3%
126.83 1
3.3%
126.831 1
3.3%
126.832 1
3.3%
126.835 1
3.3%
126.842 1
3.3%
ValueCountFrequency (%)
127.206 1
3.3%
127.153 1
3.3%
127.113 1
3.3%
127.099 1
3.3%
127.072 1
3.3%
127.069 1
3.3%
127.058 1
3.3%
127.056 1
3.3%
127.043 1
3.3%
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%
2024-03-13T20:55:29.347943image/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

2024-03-13T20:55:29.445839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:29.536637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

Interactions

2024-03-13T20:55:25.140541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:23.996545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:24.373044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:24.793326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:25.238902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:24.104784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:24.469331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:24.879450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:25.357758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:24.195963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:24.567727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:24.962372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:25.463244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:24.289633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:24.685591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:25.050001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T20:55:29.603846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도
가맹점번호1.0000.0000.8540.0001.0001.0000.0000.000
가맹점업종명0.0001.0000.0000.0000.0000.8830.0000.000
가맹점우편번호0.8540.0001.0000.8600.9761.0000.8600.860
시도명0.0000.0000.8601.000NaNNaN0.9060.906
시군구명1.0000.0000.976NaN1.0001.000NaNNaN
읍면동명1.0000.8831.000NaN1.0001.000NaNNaN
위도0.0000.0000.8600.906NaNNaN1.0000.906
경도0.0000.0000.8600.906NaNNaN0.9061.000
2024-03-13T20:55:29.730639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명가맹점업종명
시도명1.0000.000
가맹점업종명0.0001.000
2024-03-13T20:55:29.843614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점우편번호위도경도가맹점업종명시도명
가맹점번호1.000-0.004-0.1620.1160.0000.000
가맹점우편번호-0.0041.000-0.7860.3220.0000.587
위도-0.162-0.7861.0000.0070.0000.721
경도0.1160.3220.0071.0000.0000.721
가맹점업종명0.0000.0000.0000.0001.0000.000
시도명0.0000.5870.7210.7210.0001.000

Missing values

2024-03-13T20:55:25.600151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:55:25.780610image/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.
2024-03-13T20:55:25.910778image/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
02023-08-01700001981999999999999999일반/휴게 음식10929경기도파주시금촌동37.759126.776<NA>N0
12023-08-01799332455999999999999999일반/휴게 음식15036경기도시흥시정왕동37.347126.734<NA>N0
22023-08-01700004192999999999999999미용/위생18405경기도화성시병점동37.214127.043<NA>N0
32023-08-01700005007999999999999999미용/위생14285경기도광명시광명동37.479126.852<NA>N0
42023-08-01700005040999999999999999일반/휴게 음식11325경기도동두천시생연동37.911127.056<NA>N0
52023-08-01700005104999999999999999일반/휴게 음식11678경기도의정부시가능동37.748127.042<NA>N0
62023-08-01700008242999999999999999레저/스포츠 서비스17936경기도평택시안중읍36.984126.927<NA>N0
72023-08-01799333516999999999999999용역서비스13595경기도성남시 분당구수내동37.379127.113<NA>N0
82023-08-01700009937999999999999999일반/휴게 음식18584경기도화성시장안면37.083126.827<NA>N0
92023-08-01700010566999999999999999용역서비스16827경기도용인시 수지구동천동37.335127.099<NA>N0
일반일간결제일자가맹점번호결제상품ID가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도결제상품명사용여부결제금액
202023-08-01700024377999999999999999학원11757경기도의정부시금오동37.752127.069<NA>N0
212023-08-01700025671999999999999999대형유통10460경기도고양시 덕양구주교동37.657126.83<NA>N0
222023-08-01700027673999999999999999의류15296경기도안산시 상록구성포동37.32126.842<NA>N0
232023-08-01700027942999999999999999일반/휴게 음식10480경기도고양시 덕양구성사동37.642126.85<NA>N0
242023-08-01700033016999999999999999일반/휴게 음식15262NONE<NA><NA>0.00.0<NA>N0
252023-08-01700033229999999999999999레저/문화 용품14349경기도광명시일직동37.415126.886<NA>N0
262023-08-01700036665999999999999999용역서비스12041경기도남양주시오남읍37.695127.206<NA>N0
272023-08-01700036982999999999999999미용/위생17006경기도용인시 기흥구중동37.276127.153<NA>N0
282023-08-01700041263999999999999999자동차 정비/유지16236경기도수원시 팔달구우만동37.286127.032<NA>N0
292023-08-01700041831999999999999999문화/취미17772경기도평택시서정동37.066127.058<NA>N0