Overview

Dataset statistics

Number of variables13
Number of observations30
Missing cells36
Missing cells (%)9.2%
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/cc014000-3f67-4ca8-8f93-13d82f869e2e

Alerts

일반일간결제일자 has constant value ""Constant
결제상품ID has constant value ""Constant
사용여부 has constant value ""Constant
결제금액 has constant value ""Constant
위도 is highly overall correlated with 시도명High 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 (53.1%)Imbalance
시군구명 has 3 (10.0%) missing valuesMissing
읍면동명 has 3 (10.0%) 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 3 (10.0%) zerosZeros
경도 has 3 (10.0%) zerosZeros

Reproduction

Analysis started2023-12-10 14:16:26.078865
Analysis finished2023-12-10 14:16:30.392886
Duration4.31 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
Minimum2022-11-01 00:00:00
Maximum2022-11-01 00:00:00
2023-12-10T23:16:30.466419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:30.633490image/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%
Mean7.4896119 × 108
Minimum7.0000062 × 108
Maximum7.9791966 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:16:30.844925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.0000062 × 108
5-th percentile7.0000162 × 108
Q17.0001313 × 108
median7.489618 × 108
Q37.9790857 × 108
95-th percentile7.979172 × 108
Maximum7.9791966 × 108
Range97919039
Interquartile range (IQR)97895432

Descriptive statistics

Standard deviation49783971
Coefficient of variation (CV)0.066470695
Kurtosis-2.148148
Mean7.4896119 × 108
Median Absolute Deviation (MAD)48947779
Skewness-1.6639173 × 10-8
Sum2.2468836 × 1010
Variance2.4784437 × 1015
MonotonicityNot monotonic
2023-12-10T23:16:31.168611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
797897781 1
 
3.3%
797910445 1
 
3.3%
700025817 1
 
3.3%
797919658 1
 
3.3%
700025509 1
 
3.3%
797918889 1
 
3.3%
700025012 1
 
3.3%
797915135 1
 
3.3%
700022489 1
 
3.3%
797915003 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
700000619 1
3.3%
700001178 1
3.3%
700002166 1
3.3%
700007407 1
3.3%
700008777 1
3.3%
700011471 1
3.3%
700011986 1
3.3%
700012366 1
3.3%
700015434 1
3.3%
700017243 1
3.3%
ValueCountFrequency (%)
797919658 1
3.3%
797918889 1
3.3%
797915135 1
3.3%
797915003 1
3.3%
797912802 1
3.3%
797910867 1
3.3%
797910445 1
3.3%
797908711 1
3.3%
797908129 1
3.3%
797905851 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

2023-12-10T23:16:31.477038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:16:31.703334image/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
2023-12-10T23:16:32.049644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.2666667
Min length2

Characters and Unicode

Total characters128
Distinct characters46
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

Unique8 ?
Unique (%)26.7%

Sample

1st row건축자재
2nd row일반휴게음식
3rd row보건위생
4th row일반휴게음식
5th row자동차판매
ValueCountFrequency (%)
일반휴게음식 8
25.0%
학원 3
 
9.4%
음료식품 3
 
9.4%
건축자재 2
 
6.2%
보건위생 2
 
6.2%
레저업소 2
 
6.2%
의원 2
 
6.2%
직물 1
 
3.1%
자동차정비 1
 
3.1%
의류 1
 
3.1%
Other values (7) 7
21.9%
2023-12-10T23:16:32.711904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
음 11
 
8.6%
식 11
 
8.6%
일 8
 
6.2%
휴 8
 
6.2%
게 8
 
6.2%
반 8
 
6.2%
원 5
 
3.9%
자 4
 
3.1%
건 4
 
3.1%
학 3
 
2.3%
Other values (36) 58
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
97.7%
Space Separator 2
 
1.6%
Other Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
음 11
 
8.8%
식 11
 
8.8%
일 8
 
6.4%
휴 8
 
6.4%
게 8
 
6.4%
반 8
 
6.4%
원 5
 
4.0%
자 4
 
3.2%
건 4
 
3.2%
학 3
 
2.4%
Other values (34) 55
44.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125
97.7%
Common 3
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
음 11
 
8.8%
식 11
 
8.8%
일 8
 
6.4%
휴 8
 
6.4%
게 8
 
6.4%
반 8
 
6.4%
원 5
 
4.0%
자 4
 
3.2%
건 4
 
3.2%
학 3
 
2.4%
Other values (34) 55
44.0%
Common
ValueCountFrequency (%)
2
66.7%
. 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125
97.7%
ASCII 3
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
음 11
 
8.8%
식 11
 
8.8%
일 8
 
6.4%
휴 8
 
6.4%
게 8
 
6.4%
반 8
 
6.4%
원 5
 
4.0%
자 4
 
3.2%
건 4
 
3.2%
학 3
 
2.4%
Other values (34) 55
44.0%
ASCII
ValueCountFrequency (%)
2
66.7%
. 1
33.3%

가맹점우편번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14248.067
Minimum10245
Maximum18580
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:16:32.986895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10245
5-th percentile10645.35
Q111706.75
median14339
Q316329.75
95-th percentile18209.25
Maximum18580
Range8335
Interquartile range (IQR)4623

Descriptive statistics

Standard deviation2583.2117
Coefficient of variation (CV)0.18130261
Kurtosis-1.2339934
Mean14248.067
Median Absolute Deviation (MAD)2389.5
Skewness0.052892489
Sum427442
Variance6672982.6
MonotonicityNot monotonic
2023-12-10T23:16:33.194179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
10245 1
 
3.3%
16972 1
 
3.3%
12644 1
 
3.3%
17777 1
 
3.3%
18580 1
 
3.3%
15851 1
 
3.3%
15248 1
 
3.3%
15855 1
 
3.3%
11695 1
 
3.3%
14547 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10245 1
3.3%
10500 1
3.3%
10823 1
3.3%
10845 1
3.3%
11181 1
3.3%
11485 1
3.3%
11695 1
3.3%
11698 1
3.3%
11733 1
3.3%
12571 1
3.3%
ValueCountFrequency (%)
18580 1
3.3%
18261 1
3.3%
18146 1
3.3%
17777 1
3.3%
17148 1
3.3%
16972 1
3.3%
16512 1
3.3%
16488 1
3.3%
15855 1
3.3%
15851 1
3.3%

시도명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
27 
NONE
3 

Length

Max length4
Median length3
Mean length3.1
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 27
90.0%
NONE 3
 
10.0%

Length

2023-12-10T23:16:33.426221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:16:33.600984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 27
90.0%
none 3
 
10.0%

시군구명
Text

MISSING 

Distinct20
Distinct (%)74.1%
Missing3
Missing (%)10.0%
Memory size372.0 B
2023-12-10T23:16:33.900248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length4.5925926
Min length3

Characters and Unicode

Total characters124
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

Unique14 ?
Unique (%)51.9%

Sample

1st row고양시 일산동구
2nd row양평군
3rd row파주시
4th row안양시 동안구
5th row군포시
ValueCountFrequency (%)
군포시 3
 
8.1%
동안구 2
 
5.4%
광명시 2
 
5.4%
부천시 2
 
5.4%
화성시 2
 
5.4%
의정부시 2
 
5.4%
수원시 2
 
5.4%
고양시 2
 
5.4%
안양시 2
 
5.4%
용인시 2
 
5.4%
Other values (16) 16
43.2%
2023-12-10T23:16:34.534214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 26
21.0%
10
 
8.1%
구 10
 
8.1%
양 6
 
4.8%
안 5
 
4.0%
군 4
 
3.2%
포 4
 
3.2%
부 4
 
3.2%
성 3
 
2.4%
산 3
 
2.4%
Other values (29) 49
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 114
91.9%
Space Separator 10
 
8.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 26
22.8%
구 10
 
8.8%
양 6
 
5.3%
안 5
 
4.4%
군 4
 
3.5%
포 4
 
3.5%
부 4
 
3.5%
성 3
 
2.6%
산 3
 
2.6%
원 3
 
2.6%
Other values (28) 46
40.4%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 114
91.9%
Common 10
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 26
22.8%
구 10
 
8.8%
양 6
 
5.3%
안 5
 
4.4%
군 4
 
3.5%
포 4
 
3.5%
부 4
 
3.5%
성 3
 
2.6%
산 3
 
2.6%
원 3
 
2.6%
Other values (28) 46
40.4%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 114
91.9%
ASCII 10
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 26
22.8%
구 10
 
8.8%
양 6
 
5.3%
안 5
 
4.4%
군 4
 
3.5%
포 4
 
3.5%
부 4
 
3.5%
성 3
 
2.6%
산 3
 
2.6%
원 3
 
2.6%
Other values (28) 46
40.4%
ASCII
ValueCountFrequency (%)
10
100.0%

읍면동명
Text

MISSING 

Distinct26
Distinct (%)96.3%
Missing3
Missing (%)10.0%
Memory size372.0 B
2023-12-10T23:16:34.844766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.8148148
Min length2

Characters and Unicode

Total characters76
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

Unique25 ?
Unique (%)92.6%

Sample

1st row설문동
2nd row강상면
3rd row월롱면
4th row관양동
5th row금정동
ValueCountFrequency (%)
관양동 2
 
7.4%
하동 1
 
3.7%
설문동 1
 
3.7%
화정동 1
 
3.7%
서정동 1
 
3.7%
장안면 1
 
3.7%
당정동 1
 
3.7%
와동 1
 
3.7%
당동 1
 
3.7%
중동 1
 
3.7%
Other values (16) 16
59.3%
2023-12-10T23:16:35.413864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 22
28.9%
정 5
 
6.6%
면 3
 
3.9%
양 3
 
3.9%
관 2
 
2.6%
당 2
 
2.6%
하 2
 
2.6%
갈 2
 
2.6%
읍 2
 
2.6%
소 2
 
2.6%
Other values (31) 31
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 22
28.9%
정 5
 
6.6%
면 3
 
3.9%
양 3
 
3.9%
관 2
 
2.6%
당 2
 
2.6%
하 2
 
2.6%
갈 2
 
2.6%
읍 2
 
2.6%
소 2
 
2.6%
Other values (31) 31
40.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 22
28.9%
정 5
 
6.6%
면 3
 
3.9%
양 3
 
3.9%
관 2
 
2.6%
당 2
 
2.6%
하 2
 
2.6%
갈 2
 
2.6%
읍 2
 
2.6%
소 2
 
2.6%
Other values (31) 31
40.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 22
28.9%
정 5
 
6.6%
면 3
 
3.9%
양 3
 
3.9%
관 2
 
2.6%
당 2
 
2.6%
하 2
 
2.6%
갈 2
 
2.6%
읍 2
 
2.6%
소 2
 
2.6%
Other values (31) 31
40.8%

위도
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.6782
Minimum0
Maximum37.814
Zeros3
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:16:35.724257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q137.25025
median37.3585
Q337.49875
95-th percentile37.78175
Maximum37.814
Range37.814
Interquartile range (IQR)0.2485

Descriptive statistics

Standard deviation11.419706
Coefficient of variation (CV)0.33908301
Kurtosis6.3024664
Mean33.6782
Median Absolute Deviation (MAD)0.137
Skewness-2.8075255
Sum1010.346
Variance130.40967
MonotonicityNot monotonic
2023-12-10T23:16:36.179854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 3
 
10.0%
37.723 1
 
3.3%
37.632 1
 
3.3%
37.287 1
 
3.3%
37.066 1
 
3.3%
37.116 1
 
3.3%
37.343 1
 
3.3%
37.345 1
 
3.3%
37.354 1
 
3.3%
37.502 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0.0 3
10.0%
37.066 1
 
3.3%
37.116 1
 
3.3%
37.13 1
 
3.3%
37.209 1
 
3.3%
37.246 1
 
3.3%
37.263 1
 
3.3%
37.282 1
 
3.3%
37.287 1
 
3.3%
37.292 1
 
3.3%
ValueCountFrequency (%)
37.814 1
3.3%
37.811 1
3.3%
37.746 1
3.3%
37.731 1
3.3%
37.723 1
3.3%
37.632 1
3.3%
37.514 1
3.3%
37.502 1
3.3%
37.489 1
3.3%
37.442 1
3.3%

경도
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.29993
Minimum0
Maximum127.629
Zeros3
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:16:36.398062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1126.817
median126.948
Q3127.06525
95-th percentile127.35855
Maximum127.629
Range127.629
Interquartile range (IQR)0.24825

Descriptive statistics

Standard deviation38.751794
Coefficient of variation (CV)0.33903601
Kurtosis6.3075893
Mean114.29993
Median Absolute Deviation (MAD)0.1275
Skewness-2.8089876
Sum3428.998
Variance1501.7015
MonotonicityNot monotonic
2023-12-10T23:16:36.981457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.0 3
 
10.0%
127.057 2
 
6.7%
126.79 1
 
3.3%
126.831 1
 
3.3%
127.629 1
 
3.3%
126.82 1
 
3.3%
126.95 1
 
3.3%
126.821 1
 
3.3%
126.946 1
 
3.3%
126.763 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
0.0 3
10.0%
126.763 1
 
3.3%
126.777 1
 
3.3%
126.79 1
 
3.3%
126.814 1
 
3.3%
126.816 1
 
3.3%
126.82 1
 
3.3%
126.821 1
 
3.3%
126.831 1
 
3.3%
126.879 1
 
3.3%
ValueCountFrequency (%)
127.629 1
3.3%
127.476 1
3.3%
127.215 1
3.3%
127.16 1
3.3%
127.127 1
3.3%
127.112 1
3.3%
127.069 1
3.3%
127.068 1
3.3%
127.057 2
6.7%
127.051 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%
2023-12-10T23:16:37.179439image/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

2023-12-10T23:16:37.338459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:16:37.520738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

Interactions

2023-12-10T23:16:28.958988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:26.682620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:27.406827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:28.253188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:29.143935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:26.892692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:27.626934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:28.416853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:29.287146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:27.062774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:27.824231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:28.633751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:29.501437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:27.237877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:28.059964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:28.785613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:16:37.650164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도
가맹점번호1.0000.6880.6170.0001.0001.0000.0000.000
가맹점업종명0.6881.0000.5040.8440.7330.9950.8440.844
가맹점우편번호0.6170.5041.0000.0001.0001.0000.0000.000
시도명0.0000.8440.0001.000NaNNaN0.9550.955
시군구명1.0000.7331.000NaN1.0001.000NaNNaN
읍면동명1.0000.9951.000NaN1.0001.000NaNNaN
위도0.0000.8440.0000.955NaNNaN1.0000.955
경도0.0000.8440.0000.955NaNNaN0.9551.000
2023-12-10T23:16:37.862699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점우편번호위도경도시도명
가맹점번호1.0000.312-0.170-0.1180.000
가맹점우편번호0.3121.000-0.4910.2580.000
위도-0.170-0.4911.0000.1130.807
경도-0.1180.2580.1131.0000.807
시도명0.0000.0000.8070.8071.000

Missing values

2023-12-10T23:16:29.770734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:16:30.087667image/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.
2023-12-10T23:16:30.300906image/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
02022-11-01797897781999999999999999건축자재10245경기도고양시 일산동구설문동37.723126.79<NA>N0
12022-11-01700000619999999999999999일반휴게음식12571경기도양평군강상면37.489127.476<NA>N0
22022-11-01797898209999999999999999보건위생10845경기도파주시월롱면37.811126.777<NA>N0
32022-11-01700001178999999999999999일반휴게음식14054경기도안양시 동안구관양동37.394126.961<NA>N0
42022-11-01797899432999999999999999자동차판매15827경기도군포시금정동37.363126.94<NA>N0
52022-11-01700002166999999999999999건축자재11485NONE<NA><NA>0.00.0<NA>N0
62022-11-01797900539999999999999999일반휴게음식14351경기도광명시일직동37.414126.881<NA>N0
72022-11-01700007407999999999999999용역 서비스18146경기도오산시갈곶동37.13127.069<NA>N0
82022-11-01797904492999999999999999레저업소14668경기도부천시작동37.514126.814<NA>N0
92022-11-01700008777999999999999999음료식품11181경기도포천시소흘읍37.814127.16<NA>N0
일반일간결제일자가맹점번호결제상품ID가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도결제상품명사용여부결제금액
202022-11-01797912802999999999999999일반휴게음식17148경기도용인시 처인구고림동37.246127.215<NA>N0
212022-11-01700022319999999999999999학원14102경기도안양시 동안구관양동37.404126.956<NA>N0
222022-11-01797915003999999999999999보건위생14547경기도부천시중동37.502126.763<NA>N0
232022-11-01700022489999999999999999의류11695NONE<NA><NA>0.00.0<NA>N0
242022-11-01797915135999999999999999일반휴게음식15855경기도군포시당동37.354126.946<NA>N0
252022-11-01700025012999999999999999일반휴게음식15248경기도안산시 단원구와동37.345126.821<NA>N0
262022-11-01797918889999999999999999일반휴게음식15851경기도군포시당정동37.343126.95<NA>N0
272022-11-01700025509999999999999999자동차정비 유지18580경기도화성시장안면37.116126.82<NA>N0
282022-11-01797919658999999999999999레저업소17777경기도평택시서정동37.066127.057<NA>N0
292022-11-01700025817999999999999999음료식품12644경기도여주시교동37.287127.629<NA>N0