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
Categorical3
Text3
Unsupported1
Boolean1

Dataset

Description샘플 데이터
Author코나아이㈜
URLhttps://bigdata-region.kr/#/dataset/5b35279c-c640-4ea9-9410-34ae5f9a7372

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 위도High 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 위도 and 1 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
가맹점우편번호 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 11:52:40.996121
Analysis finished2024-03-13 11:52:43.710005
Duration2.71 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
Minimum2023-06-01 00:00:00
Maximum2023-06-01 00:00:00
2024-03-13T20:52:43.757836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:43.847912image/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%
Mean7.0663817 × 108
Minimum7.00001 × 108
Maximum7.9932852 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:52:43.973851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.00001 × 108
5-th percentile7.0000308 × 108
Q17.0000786 × 108
median7.0001996 × 108
Q37.0002676 × 108
95-th percentile7.5464479 × 108
Maximum7.9932852 × 108
Range99327514
Interquartile range (IQR)18900

Descriptive statistics

Standard deviation25195790
Coefficient of variation (CV)0.035655857
Kurtosis12.206628
Mean7.0663817 × 108
Median Absolute Deviation (MAD)8880
Skewness3.6599976
Sum2.1199145 × 1010
Variance6.3482783 × 1014
MonotonicityNot monotonic
2024-03-13T20:52:44.151514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
700001005 1
 
3.3%
700017234 1
 
3.3%
700033512 1
 
3.3%
700032102 1
 
3.3%
700031626 1
 
3.3%
700030395 1
 
3.3%
700029057 1
 
3.3%
700026871 1
 
3.3%
700026441 1
 
3.3%
700025891 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
700001005 1
3.3%
700002992 1
3.3%
700003195 1
3.3%
700003305 1
3.3%
700003308 1
3.3%
700003884 1
3.3%
700006622 1
3.3%
700006719 1
3.3%
700011297 1
3.3%
700012236 1
3.3%
ValueCountFrequency (%)
799328519 1
3.3%
799326737 1
3.3%
700033512 1
3.3%
700032102 1
3.3%
700031626 1
3.3%
700030395 1
3.3%
700029057 1
3.3%
700026871 1
3.3%
700026441 1
3.3%
700025891 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

2024-03-13T20:52:44.342190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:52:44.452366image/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
2024-03-13T20:52:44.597173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length5.9666667
Min length2

Characters and Unicode

Total characters179
Distinct characters47
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)20.0%

Sample

1st row용역서비스
2nd row가구
3rd row가구
4th row일반/휴게 음식
5th row레저/스포츠 서비스
ValueCountFrequency (%)
일반/휴게 5
12.5%
음식 5
12.5%
레저/스포츠 4
10.0%
서비스 4
10.0%
가구 3
 
7.5%
일반유통 2
 
5.0%
미용/위생 2
 
5.0%
서적/문구/학습자재 2
 
5.0%
건축자재 2
 
5.0%
음료/식품 2
 
5.0%
Other values (8) 9
22.5%
2024-03-13T20:52:44.972509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 20
 
11.2%
스 10
 
5.6%
10
 
5.6%
서 8
 
4.5%
일 7
 
3.9%
반 7
 
3.9%
음 7
 
3.9%
식 7
 
3.9%
비 7
 
3.9%
구 5
 
2.8%
Other values (37) 91
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149
83.2%
Other Punctuation 20
 
11.2%
Space Separator 10
 
5.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 10
 
6.7%
서 8
 
5.4%
일 7
 
4.7%
반 7
 
4.7%
음 7
 
4.7%
식 7
 
4.7%
비 7
 
4.7%
구 5
 
3.4%
자 5
 
3.4%
휴 5
 
3.4%
Other values (35) 81
54.4%
Other Punctuation
ValueCountFrequency (%)
/ 20
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149
83.2%
Common 30
 
16.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 10
 
6.7%
서 8
 
5.4%
일 7
 
4.7%
반 7
 
4.7%
음 7
 
4.7%
식 7
 
4.7%
비 7
 
4.7%
구 5
 
3.4%
자 5
 
3.4%
휴 5
 
3.4%
Other values (35) 81
54.4%
Common
ValueCountFrequency (%)
/ 20
66.7%
10
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149
83.2%
ASCII 30
 
16.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 20
66.7%
10
33.3%
Hangul
ValueCountFrequency (%)
스 10
 
6.7%
서 8
 
5.4%
일 7
 
4.7%
반 7
 
4.7%
음 7
 
4.7%
식 7
 
4.7%
비 7
 
4.7%
구 5
 
3.4%
자 5
 
3.4%
휴 5
 
3.4%
Other values (35) 81
54.4%

가맹점우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14066.9
Minimum10209
Maximum18137
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:52:45.114013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10209
5-th percentile10409.6
Q111750.75
median13793
Q316630.75
95-th percentile18012.2
Maximum18137
Range7928
Interquartile range (IQR)4880

Descriptive statistics

Standard deviation2594.3474
Coefficient of variation (CV)0.18442922
Kurtosis-1.3231389
Mean14066.9
Median Absolute Deviation (MAD)2521.5
Skewness0.03402
Sum422007
Variance6730638.5
MonotonicityNot monotonic
2024-03-13T20:52:45.292964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
16456 1
 
3.3%
13647 1
 
3.3%
16689 1
 
3.3%
10414 1
 
3.3%
16708 1
 
3.3%
15806 1
 
3.3%
14239 1
 
3.3%
14932 1
 
3.3%
13288 1
 
3.3%
11028 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10209 1
3.3%
10406 1
3.3%
10414 1
3.3%
10495 1
3.3%
10925 1
3.3%
11028 1
3.3%
11413 1
3.3%
11730 1
3.3%
11813 1
3.3%
12614 1
3.3%
ValueCountFrequency (%)
18137 1
3.3%
18104 1
3.3%
17900 1
3.3%
17024 1
3.3%
16954 1
3.3%
16897 1
3.3%
16708 1
3.3%
16689 1
3.3%
16456 1
3.3%
15871 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

2024-03-13T20:52:45.488607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:52:45.604987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 28
93.3%
none 2
 
6.7%

시군구명
Text

MISSING 

Distinct20
Distinct (%)71.4%
Missing2
Missing (%)6.7%
Memory size372.0 B
2024-03-13T20:52:45.803307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.1785714
Min length3

Characters and Unicode

Total characters145
Distinct characters39
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 (%)46.4%

Sample

1st row수원시 팔달구
2nd row군포시
3rd row오산시
4th row여주시
5th row부천시
ValueCountFrequency (%)
고양시 4
 
9.5%
성남시 3
 
7.1%
수정구 3
 
7.1%
용인시 3
 
7.1%
수원시 3
 
7.1%
일산동구 2
 
4.8%
영통구 2
 
4.8%
의정부시 2
 
4.8%
군포시 2
 
4.8%
기흥구 2
 
4.8%
Other values (15) 16
38.1%
2024-03-13T20:52:46.178650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 28
19.3%
14
 
9.7%
구 14
 
9.7%
양 7
 
4.8%
수 6
 
4.1%
정 5
 
3.4%
산 5
 
3.4%
고 4
 
2.8%
인 4
 
2.8%
성 3
 
2.1%
Other values (29) 55
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 131
90.3%
Space Separator 14
 
9.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 28
21.4%
구 14
 
10.7%
양 7
 
5.3%
수 6
 
4.6%
정 5
 
3.8%
산 5
 
3.8%
고 4
 
3.1%
인 4
 
3.1%
성 3
 
2.3%
부 3
 
2.3%
Other values (28) 52
39.7%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 131
90.3%
Common 14
 
9.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 28
21.4%
구 14
 
10.7%
양 7
 
5.3%
수 6
 
4.6%
정 5
 
3.8%
산 5
 
3.8%
고 4
 
3.1%
인 4
 
3.1%
성 3
 
2.3%
부 3
 
2.3%
Other values (28) 52
39.7%
Common
ValueCountFrequency (%)
14
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 131
90.3%
ASCII 14
 
9.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 28
21.4%
구 14
 
10.7%
양 7
 
5.3%
수 6
 
4.6%
정 5
 
3.8%
산 5
 
3.8%
고 4
 
3.1%
인 4
 
3.1%
성 3
 
2.3%
부 3
 
2.3%
Other values (28) 52
39.7%
ASCII
ValueCountFrequency (%)
14
100.0%

읍면동명
Text

MISSING 

Distinct28
Distinct (%)100.0%
Missing2
Missing (%)6.7%
Memory size372.0 B
2024-03-13T20:52:46.458890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9642857
Min length2

Characters and Unicode

Total characters83
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

Unique28 ?
Unique (%)100.0%

Sample

1st row매교동
2nd row당동
3rd row가장동
4th row북내면
5th row고강동
ValueCountFrequency (%)
당동 1
 
3.6%
가장동 1
 
3.6%
포곡읍 1
 
3.6%
마두동 1
 
3.6%
영통동 1
 
3.6%
산본동 1
 
3.6%
철산동 1
 
3.6%
과림동 1
 
3.6%
태평동 1
 
3.6%
전곡읍 1
 
3.6%
Other values (18) 18
64.3%
2024-03-13T20:52:46.880805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 24
28.9%
곡 4
 
4.8%
산 4
 
4.8%
전 2
 
2.4%
읍 2
 
2.4%
가 2
 
2.4%
포 2
 
2.4%
신 2
 
2.4%
면 2
 
2.4%
양 2
 
2.4%
Other values (35) 37
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 24
28.9%
곡 4
 
4.8%
산 4
 
4.8%
전 2
 
2.4%
읍 2
 
2.4%
가 2
 
2.4%
포 2
 
2.4%
신 2
 
2.4%
면 2
 
2.4%
양 2
 
2.4%
Other values (35) 37
44.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 24
28.9%
곡 4
 
4.8%
산 4
 
4.8%
전 2
 
2.4%
읍 2
 
2.4%
가 2
 
2.4%
포 2
 
2.4%
신 2
 
2.4%
면 2
 
2.4%
양 2
 
2.4%
Other values (35) 37
44.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 24
28.9%
곡 4
 
4.8%
산 4
 
4.8%
전 2
 
2.4%
읍 2
 
2.4%
가 2
 
2.4%
포 2
 
2.4%
신 2
 
2.4%
면 2
 
2.4%
양 2
 
2.4%
Other values (35) 37
44.6%

위도
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.9652
Minimum0
Maximum38.027
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:52:47.030756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16.6464
Q137.2695
median37.4205
Q337.6435
95-th percentile37.81595
Maximum38.027
Range38.027
Interquartile range (IQR)0.374

Descriptive statistics

Standard deviation9.5074086
Coefficient of variation (CV)0.2719106
Kurtosis12.188552
Mean34.9652
Median Absolute Deviation (MAD)0.168
Skewness-3.6562453
Sum1048.956
Variance90.390818
MonotonicityNot monotonic
2024-03-13T20:52:47.177230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 2
 
6.7%
37.268 1
 
3.3%
37.347 1
 
3.3%
37.242 1
 
3.3%
37.65 1
 
3.3%
37.263 1
 
3.3%
37.37 1
 
3.3%
37.475 1
 
3.3%
37.436 1
 
3.3%
37.445 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0.0 2
6.7%
36.992 1
3.3%
37.138 1
3.3%
37.161 1
3.3%
37.242 1
3.3%
37.263 1
3.3%
37.268 1
3.3%
37.274 1
3.3%
37.281 1
3.3%
37.322 1
3.3%
ValueCountFrequency (%)
38.027 1
3.3%
37.865 1
3.3%
37.756 1
3.3%
37.743 1
3.3%
37.731 1
3.3%
37.685 1
3.3%
37.67 1
3.3%
37.65 1
3.3%
37.624 1
3.3%
37.528 1
3.3%

경도
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.54387
Minimum0
Maximum127.694
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:52:47.333434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile57.02355
Q1126.836
median127.022
Q3127.0905
95-th percentile127.1762
Maximum127.694
Range127.694
Interquartile range (IQR)0.2545

Descriptive statistics

Standard deviation32.224317
Coefficient of variation (CV)0.27183453
Kurtosis12.205645
Mean118.54387
Median Absolute Deviation (MAD)0.101
Skewness-3.6597938
Sum3556.316
Variance1038.4066
MonotonicityNot monotonic
2024-03-13T20:52:47.495846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
127.067 2
 
6.7%
0.0 2
 
6.7%
127.014 1
 
3.3%
127.187 1
 
3.3%
127.052 1
 
3.3%
126.779 1
 
3.3%
127.077 1
 
3.3%
126.938 1
 
3.3%
126.87 1
 
3.3%
126.839 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0.0 2
6.7%
126.719 1
3.3%
126.772 1
3.3%
126.779 1
3.3%
126.785 1
3.3%
126.822 1
3.3%
126.835 1
3.3%
126.839 1
3.3%
126.87 1
3.3%
126.938 1
3.3%
ValueCountFrequency (%)
127.694 1
3.3%
127.187 1
3.3%
127.163 1
3.3%
127.137 1
3.3%
127.136 1
3.3%
127.11 1
3.3%
127.107 1
3.3%
127.095 1
3.3%
127.077 1
3.3%
127.071 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%
2024-03-13T20:52:47.662380image/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

2024-03-13T20:52:47.808700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:52:47.909677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

Interactions

2024-03-13T20:52:42.756488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:41.414631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:41.831912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:42.307540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:42.846064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:41.517897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:41.957422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:42.395042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:42.948410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:41.626256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:42.098639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:42.552135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:43.056156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:41.729312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:42.208514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:42.660536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T20:52:47.979110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도
가맹점번호1.0000.0000.3470.0000.4901.0000.0000.000
가맹점업종명0.0001.0000.0000.7530.0001.0000.7530.753
가맹점우편번호0.3470.0001.0000.0000.9371.0000.0000.000
시도명0.0000.7530.0001.000NaNNaN0.9060.906
시군구명0.4900.0000.937NaN1.0001.000NaNNaN
읍면동명1.0001.0001.000NaN1.0001.000NaNNaN
위도0.0000.7530.0000.906NaNNaN1.0000.906
경도0.0000.7530.0000.906NaNNaN0.9061.000
2024-03-13T20:52:48.128181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점우편번호위도경도시도명
가맹점번호1.0000.076-0.096-0.0810.000
가맹점우편번호0.0761.000-0.7630.4010.000
위도-0.096-0.7631.000-0.1450.721
경도-0.0810.401-0.1451.0000.721
시도명0.0000.0000.7210.7211.000

Missing values

2024-03-13T20:52:43.219139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:52:43.422296image/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.
2024-03-13T20:52:43.566870image/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
02023-06-01700001005999999999999999용역서비스16456경기도수원시 팔달구매교동37.268127.014<NA>N0
12023-06-01799326737999999999999999가구15871경기도군포시당동37.347126.94<NA>N0
22023-06-01700002992999999999999999가구18104경기도오산시가장동37.161127.03<NA>N0
32023-06-01700003195999999999999999일반/휴게 음식12614경기도여주시북내면37.332127.694<NA>N0
42023-06-01700003305999999999999999레저/스포츠 서비스14406경기도부천시고강동37.528126.822<NA>N0
52023-06-01700003308999999999999999자동차 정비/유지13136경기도성남시 수정구양지동37.459127.163<NA>N0
62023-06-01700003884999999999999999레저/스포츠 서비스10209경기도고양시 일산서구가좌동37.685126.719<NA>N0
72023-06-01799328519999999999999999일반/휴게 음식17900경기도평택시비전동36.992127.107<NA>N0
82023-06-01700006622999999999999999신변잡화10925경기도파주시금촌동37.756126.772<NA>N0
92023-06-01700006719999999999999999음료/식품18137경기도오산시오산동37.138127.067<NA>N0
일반일간결제일자가맹점번호결제상품ID가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도결제상품명사용여부결제금액
202023-06-01700025398999999999999999레저/스포츠 서비스11730경기도의정부시신곡동37.731127.057<NA>N0
212023-06-01700025485999999999999999서적/문구/학습자재13640NONE<NA><NA>0.00.0<NA>N0
222023-06-01700025891999999999999999미용/위생11028경기도연천군전곡읍38.027127.067<NA>N0
232023-06-01700026441999999999999999용역서비스13288경기도성남시 수정구태평동37.445127.136<NA>N0
242023-06-01700026871999999999999999건축자재14932경기도시흥시과림동37.436126.839<NA>N0
252023-06-01700029057999999999999999일반/휴게 음식14239경기도광명시철산동37.475126.87<NA>N0
262023-06-01700030395999999999999999음료/식품15806경기도군포시산본동37.37126.938<NA>N0
272023-06-01700031626999999999999999서적/문구/학습자재16708경기도수원시 영통구영통동37.263127.077<NA>N0
282023-06-01700032102999999999999999미용/위생10414경기도고양시 일산동구마두동37.65126.779<NA>N0
292023-06-01700033512999999999999999일반유통16689경기도수원시 영통구망포동37.242127.052<NA>N0