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

Categorical4
Numeric4
Text3
Unsupported1
Boolean1

Dataset

Description샘플 데이터
Author코나아이㈜
URLhttps://bigdata-region.kr/#/dataset/91f9a7e3-30c4-4fa8-a943-d9c6a8bd39ad

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 started2023-12-10 14:11:30.057503
Analysis finished2023-12-10 14:11:34.613371
Duration4.56 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
2021-07-01
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-07-01
2nd row2021-07-01
3rd row2021-07-01
4th row2021-07-01
5th row2021-07-01

Common Values

ValueCountFrequency (%)
2021-07-01 30
100.0%

Length

2023-12-10T23:11:34.768363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:11:35.109710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-07-01 30
100.0%

가맹점번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0663283 × 108
Minimum7.0000075 × 108
Maximum7.99335 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:11:35.323585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.0000075 × 108
5-th percentile7.0000238 × 108
Q17.0000632 × 108
median7.0001148 × 108
Q37.0001798 × 108
95-th percentile7.5464414 × 108
Maximum7.99335 × 108
Range99334255
Interquartile range (IQR)11662.5

Descriptive statistics

Standard deviation25199207
Coefficient of variation (CV)0.035660963
Kurtosis12.206631
Mean7.0663283 × 108
Median Absolute Deviation (MAD)5756
Skewness3.6599983
Sum2.1198985 × 1010
Variance6.3500004 × 1014
MonotonicityNot monotonic
2023-12-10T23:11:35.630726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
700000749 1
 
3.3%
700011471 1
 
3.3%
700022319 1
 
3.3%
700020876 1
 
3.3%
700020332 1
 
3.3%
700019874 1
 
3.3%
700018562 1
 
3.3%
700018199 1
 
3.3%
700017340 1
 
3.3%
700015599 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
700000749 1
3.3%
700002166 1
3.3%
700002638 1
3.3%
700002791 1
3.3%
700003308 1
3.3%
700004118 1
3.3%
700005828 1
3.3%
700006257 1
3.3%
700006516 1
3.3%
700006719 1
3.3%
ValueCountFrequency (%)
799335004 1
3.3%
799334723 1
3.3%
700022319 1
3.3%
700020876 1
3.3%
700020332 1
3.3%
700019874 1
3.3%
700018562 1
3.3%
700018199 1
3.3%
700017340 1
3.3%
700015599 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

2023-12-10T23:11:36.014658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:11:36.230529image/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
2023-12-10T23:11:36.476356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.5
Min length2

Characters and Unicode

Total characters135
Distinct characters48
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

Unique8 ?
Unique (%)26.7%

Sample

1st row가구
2nd row수리서비스
3rd row건축자재
4th row의류
5th row의류
ValueCountFrequency (%)
일반휴게음식 8
22.2%
영리 3
 
8.3%
학원 3
 
8.3%
유통업 3
 
8.3%
가구 2
 
5.6%
의류 2
 
5.6%
용역 2
 
5.6%
서비스 2
 
5.6%
레저업소 2
 
5.6%
음료식품 1
 
2.8%
Other values (8) 8
22.2%
2023-12-10T23:11:37.017406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
음 9
 
6.7%
식 9
 
6.7%
일 8
 
5.9%
휴 8
 
5.9%
게 8
 
5.9%
반 8
 
5.9%
6
 
4.4%
업 5
 
3.7%
리 4
 
3.0%
통 4
 
3.0%
Other values (38) 66
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 129
95.6%
Space Separator 6
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
음 9
 
7.0%
식 9
 
7.0%
일 8
 
6.2%
휴 8
 
6.2%
게 8
 
6.2%
반 8
 
6.2%
업 5
 
3.9%
리 4
 
3.1%
통 4
 
3.1%
유 4
 
3.1%
Other values (37) 62
48.1%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 129
95.6%
Common 6
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
음 9
 
7.0%
식 9
 
7.0%
일 8
 
6.2%
휴 8
 
6.2%
게 8
 
6.2%
반 8
 
6.2%
업 5
 
3.9%
리 4
 
3.1%
통 4
 
3.1%
유 4
 
3.1%
Other values (37) 62
48.1%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 129
95.6%
ASCII 6
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
음 9
 
7.0%
식 9
 
7.0%
일 8
 
6.2%
휴 8
 
6.2%
게 8
 
6.2%
반 8
 
6.2%
업 5
 
3.9%
리 4
 
3.1%
통 4
 
3.1%
유 4
 
3.1%
Other values (37) 62
48.1%
ASCII
ValueCountFrequency (%)
6
100.0%

가맹점우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14358.033
Minimum10098
Maximum18591
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:11:37.269102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10098
5-th percentile10619.75
Q112254
median14269.5
Q316580
95-th percentile18139.2
Maximum18591
Range8493
Interquartile range (IQR)4326

Descriptive statistics

Standard deviation2526.2082
Coefficient of variation (CV)0.17594389
Kurtosis-1.1249489
Mean14358.033
Median Absolute Deviation (MAD)2305
Skewness0.057403601
Sum430741
Variance6381727.8
MonotonicityNot monotonic
2023-12-10T23:11:37.564375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
15599 1
 
3.3%
11698 1
 
3.3%
14102 1
 
3.3%
16979 1
 
3.3%
15537 1
 
3.3%
11806 1
 
3.3%
13165 1
 
3.3%
14437 1
 
3.3%
18141 1
 
3.3%
16271 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10098 1
3.3%
10406 1
3.3%
10881 1
3.3%
11314 1
3.3%
11485 1
3.3%
11698 1
3.3%
11806 1
3.3%
12073 1
3.3%
12797 1
3.3%
13136 1
3.3%
ValueCountFrequency (%)
18591 1
3.3%
18141 1
3.3%
18137 1
3.3%
18120 1
3.3%
17094 1
3.3%
16979 1
3.3%
16807 1
3.3%
16683 1
3.3%
16271 1
3.3%
15599 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 rowNONE
4th row경기도
5th row경기도

Common Values

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

Length

2023-12-10T23:11:37.794465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:11:37.961915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 28
93.3%
none 2
 
6.7%

시군구명
Text

MISSING 

Distinct21
Distinct (%)75.0%
Missing2
Missing (%)6.7%
Memory size372.0 B
2023-12-10T23:11:38.214159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7.5
Mean length5.3214286
Min length3

Characters and Unicode

Total characters149
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

Unique15 ?
Unique (%)53.6%

Sample

1st row안산시 단원구
2nd row시흥시
3rd row김포시
4th row동두천시
5th row성남시 수정구
ValueCountFrequency (%)
성남시 5
 
11.6%
오산시 3
 
7.0%
안산시 3
 
7.0%
용인시 3
 
7.0%
수정구 2
 
4.7%
상록구 2
 
4.7%
기흥구 2
 
4.7%
의정부시 2
 
4.7%
중원구 2
 
4.7%
수원시 2
 
4.7%
Other values (17) 17
39.5%
2023-12-10T23:11:38.973471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
19.5%
15
 
10.1%
구 15
 
10.1%
산 7
 
4.7%
성 6
 
4.0%
남 6
 
4.0%
안 6
 
4.0%
원 5
 
3.4%
수 5
 
3.4%
정 4
 
2.7%
Other values (29) 51
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 134
89.9%
Space Separator 15
 
10.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
21.6%
구 15
 
11.2%
산 7
 
5.2%
성 6
 
4.5%
남 6
 
4.5%
안 6
 
4.5%
원 5
 
3.7%
수 5
 
3.7%
정 4
 
3.0%
흥 3
 
2.2%
Other values (28) 48
35.8%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 134
89.9%
Common 15
 
10.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
21.6%
구 15
 
11.2%
산 7
 
5.2%
성 6
 
4.5%
남 6
 
4.5%
안 6
 
4.5%
원 5
 
3.7%
수 5
 
3.7%
정 4
 
3.0%
흥 3
 
2.2%
Other values (28) 48
35.8%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 134
89.9%
ASCII 15
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
21.6%
구 15
 
11.2%
산 7
 
5.2%
성 6
 
4.5%
남 6
 
4.5%
안 6
 
4.5%
원 5
 
3.7%
수 5
 
3.7%
정 4
 
3.0%
흥 3
 
2.2%
Other values (28) 48
35.8%
ASCII
ValueCountFrequency (%)
15
100.0%

읍면동명
Text

MISSING 

Distinct28
Distinct (%)100.0%
Missing2
Missing (%)6.7%
Memory size372.0 B
2023-12-10T23:11:39.607292image/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 row목내동
2nd row장곡동
3rd row북변동
4th row생연동
5th row양지동
ValueCountFrequency (%)
진접읍 1
 
3.6%
북변동 1
 
3.6%
상대원동 1
 
3.6%
구갈동 1
 
3.6%
본오동 1
 
3.6%
민락동 1
 
3.6%
금광동 1
 
3.6%
오정동 1
 
3.6%
원동 1
 
3.6%
영화동 1
 
3.6%
Other values (18) 18
64.3%
2023-12-10T23:11:40.321028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 25
30.1%
오 4
 
4.8%
정 4
 
4.8%
읍 3
 
3.6%
원 2
 
2.4%
발 2
 
2.4%
양 2
 
2.4%
신 2
 
2.4%
갈 2
 
2.4%
산 2
 
2.4%
Other values (35) 35
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 25
30.1%
오 4
 
4.8%
정 4
 
4.8%
읍 3
 
3.6%
원 2
 
2.4%
발 2
 
2.4%
양 2
 
2.4%
신 2
 
2.4%
갈 2
 
2.4%
산 2
 
2.4%
Other values (35) 35
42.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 25
30.1%
오 4
 
4.8%
정 4
 
4.8%
읍 3
 
3.6%
원 2
 
2.4%
발 2
 
2.4%
양 2
 
2.4%
신 2
 
2.4%
갈 2
 
2.4%
산 2
 
2.4%
Other values (35) 35
42.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 25
30.1%
오 4
 
4.8%
정 4
 
4.8%
읍 3
 
3.6%
원 2
 
2.4%
발 2
 
2.4%
양 2
 
2.4%
신 2
 
2.4%
갈 2
 
2.4%
산 2
 
2.4%
Other values (35) 35
42.2%

위도
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.927767
Minimum0
Maximum37.905
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:11:40.620251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16.7094
Q137.273
median37.373
Q337.51
95-th percentile37.74375
Maximum37.905
Range37.905
Interquartile range (IQR)0.237

Descriptive statistics

Standard deviation9.4965665
Coefficient of variation (CV)0.2718916
Kurtosis12.192821
Mean34.927767
Median Absolute Deviation (MAD)0.113
Skewness-3.6571294
Sum1047.833
Variance90.184775
MonotonicityNot monotonic
2023-12-10T23:11:40.913787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
37.303 2
 
6.7%
0.0 2
 
6.7%
37.273 2
 
6.7%
37.438 1
 
3.3%
37.404 1
 
3.3%
37.301 1
 
3.3%
37.741 1
 
3.3%
37.449 1
 
3.3%
37.527 1
 
3.3%
37.145 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
0.0 2
6.7%
37.132 1
3.3%
37.138 1
3.3%
37.145 1
3.3%
37.158 1
3.3%
37.247 1
3.3%
37.273 2
6.7%
37.291 1
3.3%
37.301 1
3.3%
37.303 2
6.7%
ValueCountFrequency (%)
37.905 1
3.3%
37.746 1
3.3%
37.741 1
3.3%
37.708 1
3.3%
37.704 1
3.3%
37.67 1
3.3%
37.627 1
3.3%
37.527 1
3.3%
37.459 1
3.3%
37.449 1
3.3%

경도
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.53607
Minimum0
Maximum127.26
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:11:41.468407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile57.0087
Q1126.8055
median127.0545
Q3127.11075
95-th percentile127.1785
Maximum127.26
Range127.26
Interquartile range (IQR)0.30525

Descriptive statistics

Standard deviation32.222047
Coefficient of variation (CV)0.27183328
Kurtosis12.205927
Mean118.53607
Median Absolute Deviation (MAD)0.108
Skewness-3.6598527
Sum3556.082
Variance1038.2603
MonotonicityNot monotonic
2023-12-10T23:11:41.703124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 2
 
6.7%
126.785 2
 
6.7%
126.775 1
 
3.3%
127.162 1
 
3.3%
126.956 1
 
3.3%
127.129 1
 
3.3%
126.861 1
 
3.3%
127.097 1
 
3.3%
127.173 1
 
3.3%
127.07 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0.0 2
6.7%
126.686 1
3.3%
126.708 1
3.3%
126.775 1
3.3%
126.785 2
6.7%
126.787 1
3.3%
126.861 1
3.3%
126.866 1
3.3%
126.927 1
3.3%
126.956 1
3.3%
ValueCountFrequency (%)
127.26 1
3.3%
127.183 1
3.3%
127.173 1
3.3%
127.163 1
3.3%
127.162 1
3.3%
127.141 1
3.3%
127.129 1
3.3%
127.114 1
3.3%
127.101 1
3.3%
127.097 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%
2023-12-10T23:11:41.908375image/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

2023-12-10T23:11:42.127591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:11:42.406833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

Interactions

2023-12-10T23:11:33.076702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:30.615313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:31.501811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:32.386068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:33.301516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:30.776661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:31.810441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:32.552381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:33.466769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:31.003700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:32.049202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:32.700888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:33.649108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:31.224186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:32.218328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:11:32.892704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:11:42.574412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도
가맹점번호1.0000.6020.0000.0001.0001.0000.0000.000
가맹점업종명0.6021.0000.6261.0000.6881.0001.0001.000
가맹점우편번호0.0000.6261.0000.0000.9971.0000.0000.000
시도명0.0001.0000.0001.000NaNNaN0.9060.906
시군구명1.0000.6880.997NaN1.0001.000NaNNaN
읍면동명1.0001.0001.000NaN1.0001.000NaNNaN
위도0.0001.0000.0000.906NaNNaN1.0000.906
경도0.0001.0000.0000.906NaNNaN0.9061.000
2023-12-10T23:11:42.889664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호가맹점우편번호위도경도시도명
가맹점번호1.0000.2490.043-0.0130.000
가맹점우편번호0.2491.000-0.7570.0930.000
위도0.043-0.7571.0000.1740.721
경도-0.0130.0930.1741.0000.721
시도명0.0000.0000.7210.7211.000

Missing values

2023-12-10T23:11:33.959015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:11:34.301670image/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.
2023-12-10T23:11:34.516897image/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
02021-07-01700000749999999999999999가구15599경기도안산시 단원구목내동37.303126.775<NA>N0
12021-07-01799334723999999999999999수리서비스15002경기도시흥시장곡동37.381126.787<NA>N0
22021-07-01700002166999999999999999건축자재11485NONE<NA><NA>0.00.0<NA>N0
32021-07-01700002638999999999999999의류10098경기도김포시북변동37.627126.708<NA>N0
42021-07-01700002791999999999999999의류11314경기도동두천시생연동37.905127.058<NA>N0
52021-07-01700003308999999999999999자동차정비 유지13136경기도성남시 수정구양지동37.459127.163<NA>N0
62021-07-01700004118999999999999999일반휴게음식16683경기도수원시 영통구신동37.247127.044<NA>N0
72021-07-01799335004999999999999999유통업 영리16807경기도용인시 수지구성복동37.32127.062<NA>N0
82021-07-01700005828999999999999999일반휴게음식12797경기도광주시오포읍37.376127.26<NA>N0
92021-07-01700006257999999999999999일반휴게음식13281경기도성남시 수정구태평동37.444127.141<NA>N0
일반일간결제일자가맹점번호결제상품ID가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도결제상품명사용여부결제금액
202021-07-01700014503999999999999999사무통신10406경기도고양시 일산동구정발산동37.67126.785<NA>N0
212021-07-01700014829999999999999999일반휴게음식15517경기도안산시 상록구일동37.303126.866<NA>N0
222021-07-01700015599999999999999999전기제품16271경기도수원시 장안구영화동37.291127.012<NA>N0
232021-07-01700017340999999999999999일반휴게음식18141경기도오산시원동37.145127.07<NA>N0
242021-07-01700018199999999999999999유통업 영리14437경기도부천시오정동37.527126.785<NA>N0
252021-07-01700018562999999999999999용역 서비스13165경기도성남시 중원구금광동37.449127.173<NA>N0
262021-07-01700019874999999999999999학원11806경기도의정부시민락동37.741127.097<NA>N0
272021-07-01700020332999999999999999보건위생15537경기도안산시 상록구본오동37.301126.861<NA>N0
282021-07-01700020876999999999999999일반휴게음식16979경기도용인시 기흥구구갈동37.273127.129<NA>N0
292021-07-01700022319999999999999999학원14102경기도안양시 동안구관양동37.404126.956<NA>N0