Overview

Dataset statistics

Number of variables8
Number of observations73
Missing cells2
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory67.8 B

Variable types

Text4
Numeric2
DateTime2

Dataset

Description경상남도 거제시 세탁업소현황(업소명, 주소, 좌표, 전화번호, 영업시작일자, 기준일자)등의 정보를 제공합니다.
Author경상남도 거제시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3079219

Alerts

기준일자 has constant value ""Constant
소재지전화번호 has 2 (2.7%) missing valuesMissing
업소명 has unique valuesUnique
영업소주소(지번) has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:04:44.054680
Analysis finished2023-12-11 00:04:45.396045
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size716.0 B
2023-12-11T09:04:45.585155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.890411
Min length3

Characters and Unicode

Total characters430
Distinct characters122
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)100.0%

Sample

1st row백모세탁소
2nd row부산세탁소
3rd row태양세탁소
4th row거제컴퓨터세탁
5th row백광컴퓨터크리닝
ValueCountFrequency (%)
세탁소 3
 
3.7%
백모세탁소 1
 
1.2%
운동화빨래방 1
 
1.2%
토탈크리닝 1
 
1.2%
부부 1
 
1.2%
수월세탁소 1
 
1.2%
ok 1
 
1.2%
참조은세탁나라 1
 
1.2%
부영크리닝전문점 1
 
1.2%
슈즈쿨 1
 
1.2%
Other values (69) 69
85.2%
2023-12-11T09:04:46.006096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 52
 
12.1%
탁 52
 
12.1%
소 38
 
8.8%
리 13
 
3.0%
크 13
 
3.0%
닝 11
 
2.6%
동 9
 
2.1%
8
 
1.9%
컴 7
 
1.6%
터 7
 
1.6%
Other values (112) 220
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 418
97.2%
Space Separator 8
 
1.9%
Uppercase Letter 2
 
0.5%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 52
 
12.4%
탁 52
 
12.4%
소 38
 
9.1%
리 13
 
3.1%
크 13
 
3.1%
닝 11
 
2.6%
동 9
 
2.2%
컴 7
 
1.7%
터 7
 
1.7%
퓨 7
 
1.7%
Other values (107) 209
50.0%
Uppercase Letter
ValueCountFrequency (%)
O 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 418
97.2%
Common 10
 
2.3%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 52
 
12.4%
탁 52
 
12.4%
소 38
 
9.1%
리 13
 
3.1%
크 13
 
3.1%
닝 11
 
2.6%
동 9
 
2.2%
컴 7
 
1.7%
터 7
 
1.7%
퓨 7
 
1.7%
Other values (107) 209
50.0%
Common
ValueCountFrequency (%)
8
80.0%
( 1
 
10.0%
) 1
 
10.0%
Latin
ValueCountFrequency (%)
O 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 418
97.2%
ASCII 12
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 52
 
12.4%
탁 52
 
12.4%
소 38
 
9.1%
리 13
 
3.1%
크 13
 
3.1%
닝 11
 
2.6%
동 9
 
2.2%
컴 7
 
1.7%
터 7
 
1.7%
퓨 7
 
1.7%
Other values (107) 209
50.0%
ASCII
ValueCountFrequency (%)
8
66.7%
O 1
 
8.3%
K 1
 
8.3%
( 1
 
8.3%
) 1
 
8.3%

영업소주소(도로명)
Text

Distinct72
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size716.0 B
2023-12-11T09:04:46.386384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length35
Mean length27.082192
Min length19

Characters and Unicode

Total characters1977
Distinct characters112
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)97.3%

Sample

1st row경상남도 거제시 고현로9길 4 (고현동)
2nd row경상남도 거제시 일운면 지세포로 101
3rd row경상남도 거제시 거제면 읍내로2길 33
4th row경상남도 거제시 거제면 읍내로2길 29-1
5th row경상남도 거제시 장승포로1길 37 (장승포동)
ValueCountFrequency (%)
경상남도 73
 
17.7%
거제시 73
 
17.7%
1층 18
 
4.4%
고현동 17
 
4.1%
옥포동 12
 
2.9%
6 6
 
1.5%
101호 4
 
1.0%
능포동 4
 
1.0%
9 4
 
1.0%
거제대로 4
 
1.0%
Other values (158) 198
47.9%
2023-12-11T09:04:47.030164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
340
 
17.2%
제 88
 
4.5%
1 86
 
4.4%
거 86
 
4.4%
상 85
 
4.3%
동 80
 
4.0%
남 74
 
3.7%
도 74
 
3.7%
경 73
 
3.7%
시 73
 
3.7%
Other values (102) 918
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1140
57.7%
Space Separator 340
 
17.2%
Decimal Number 303
 
15.3%
Open Punctuation 69
 
3.5%
Close Punctuation 69
 
3.5%
Other Punctuation 38
 
1.9%
Dash Punctuation 17
 
0.9%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 88
 
7.7%
거 86
 
7.5%
상 85
 
7.5%
동 80
 
7.0%
남 74
 
6.5%
도 74
 
6.5%
경 73
 
6.4%
시 73
 
6.4%
로 63
 
5.5%
길 45
 
3.9%
Other values (86) 399
35.0%
Decimal Number
ValueCountFrequency (%)
1 86
28.4%
3 41
13.5%
2 39
12.9%
0 30
 
9.9%
5 28
 
9.2%
4 19
 
6.3%
9 19
 
6.3%
6 16
 
5.3%
7 15
 
5.0%
8 10
 
3.3%
Space Separator
ValueCountFrequency (%)
340
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Other Punctuation
ValueCountFrequency (%)
, 38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1140
57.7%
Common 836
42.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 88
 
7.7%
거 86
 
7.5%
상 85
 
7.5%
동 80
 
7.0%
남 74
 
6.5%
도 74
 
6.5%
경 73
 
6.4%
시 73
 
6.4%
로 63
 
5.5%
길 45
 
3.9%
Other values (86) 399
35.0%
Common
ValueCountFrequency (%)
340
40.7%
1 86
 
10.3%
( 69
 
8.3%
) 69
 
8.3%
3 41
 
4.9%
2 39
 
4.7%
, 38
 
4.5%
0 30
 
3.6%
5 28
 
3.3%
4 19
 
2.3%
Other values (5) 77
 
9.2%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1140
57.7%
ASCII 837
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
340
40.6%
1 86
 
10.3%
( 69
 
8.2%
) 69
 
8.2%
3 41
 
4.9%
2 39
 
4.7%
, 38
 
4.5%
0 30
 
3.6%
5 28
 
3.3%
4 19
 
2.3%
Other values (6) 78
 
9.3%
Hangul
ValueCountFrequency (%)
제 88
 
7.7%
거 86
 
7.5%
상 85
 
7.5%
동 80
 
7.0%
남 74
 
6.5%
도 74
 
6.5%
경 73
 
6.4%
시 73
 
6.4%
로 63
 
5.5%
길 45
 
3.9%
Other values (86) 399
35.0%

영업소주소(지번)
Text

UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size716.0 B
2023-12-11T09:04:47.424964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length34
Mean length22.972603
Min length15

Characters and Unicode

Total characters1677
Distinct characters96
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)100.0%

Sample

1st row경상남도 거제시 고현동 818-20
2nd row경상남도 거제시 일운면 지세포리 927-6
3rd row경상남도 거제시 거제면 동상리 423-4
4th row경상남도 거제시 거제면 동상리 417-2
5th row경상남도 거제시 장승포동 455-14
ValueCountFrequency (%)
경상남도 73
20.9%
거제시 73
20.9%
고현동 18
 
5.2%
옥포동 16
 
4.6%
1층 10
 
2.9%
장평동 5
 
1.4%
아주동 5
 
1.4%
101호 4
 
1.1%
거제면 4
 
1.1%
상동동 4
 
1.1%
Other values (121) 137
39.3%
2023-12-11T09:04:48.012688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
341
20.3%
1 93
 
5.5%
상 87
 
5.2%
제 78
 
4.7%
거 77
 
4.6%
동 76
 
4.5%
경 73
 
4.4%
남 73
 
4.4%
도 73
 
4.4%
시 73
 
4.4%
Other values (86) 633
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 899
53.6%
Decimal Number 368
21.9%
Space Separator 341
 
20.3%
Dash Punctuation 58
 
3.5%
Open Punctuation 5
 
0.3%
Close Punctuation 5
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 87
 
9.7%
제 78
 
8.7%
거 77
 
8.6%
동 76
 
8.5%
경 73
 
8.1%
남 73
 
8.1%
도 73
 
8.1%
시 73
 
8.1%
포 26
 
2.9%
고 20
 
2.2%
Other values (71) 243
27.0%
Decimal Number
ValueCountFrequency (%)
1 93
25.3%
2 39
10.6%
0 38
10.3%
9 35
 
9.5%
6 31
 
8.4%
4 30
 
8.2%
5 29
 
7.9%
8 28
 
7.6%
7 23
 
6.2%
3 22
 
6.0%
Space Separator
ValueCountFrequency (%)
341
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 899
53.6%
Common 778
46.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 87
 
9.7%
제 78
 
8.7%
거 77
 
8.6%
동 76
 
8.5%
경 73
 
8.1%
남 73
 
8.1%
도 73
 
8.1%
시 73
 
8.1%
포 26
 
2.9%
고 20
 
2.2%
Other values (71) 243
27.0%
Common
ValueCountFrequency (%)
341
43.8%
1 93
 
12.0%
- 58
 
7.5%
2 39
 
5.0%
0 38
 
4.9%
9 35
 
4.5%
6 31
 
4.0%
4 30
 
3.9%
5 29
 
3.7%
8 28
 
3.6%
Other values (5) 56
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 899
53.6%
ASCII 778
46.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
341
43.8%
1 93
 
12.0%
- 58
 
7.5%
2 39
 
5.0%
0 38
 
4.9%
9 35
 
4.5%
6 31
 
4.0%
4 30
 
3.9%
5 29
 
3.7%
8 28
 
3.6%
Other values (5) 56
 
7.2%
Hangul
ValueCountFrequency (%)
상 87
 
9.7%
제 78
 
8.7%
거 77
 
8.6%
동 76
 
8.5%
경 73
 
8.1%
남 73
 
8.1%
도 73
 
8.1%
시 73
 
8.1%
포 26
 
2.9%
고 20
 
2.2%
Other values (71) 243
27.0%

위도
Real number (ℝ)

Distinct72
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.884672
Minimum34.82959
Maximum34.988897
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-11T09:04:48.223390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.82959
5-th percentile34.850158
Q134.876091
median34.889265
Q334.895353
95-th percentile34.906144
Maximum34.988897
Range0.15930765
Interquartile range (IQR)0.01926239

Descriptive statistics

Standard deviation0.021279537
Coefficient of variation (CV)0.00060999677
Kurtosis7.6188398
Mean34.884672
Median Absolute Deviation (MAD)0.00778255
Skewness1.0111778
Sum2546.581
Variance0.00045281871
MonotonicityNot monotonic
2023-12-11T09:04:48.438404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.89726297 2
 
2.7%
34.88687685 1
 
1.4%
34.9012666 1
 
1.4%
34.88626867 1
 
1.4%
34.89361878 1
 
1.4%
34.8872063 1
 
1.4%
34.89535344 1
 
1.4%
34.89530867 1
 
1.4%
34.87962275 1
 
1.4%
34.88433404 1
 
1.4%
Other values (62) 62
84.9%
ValueCountFrequency (%)
34.82958971 1
1.4%
34.83234455 1
1.4%
34.84999024 1
1.4%
34.85010596 1
1.4%
34.8501928 1
1.4%
34.851439 1
1.4%
34.85319402 1
1.4%
34.85874083 1
1.4%
34.85984156 1
1.4%
34.86368863 1
1.4%
ValueCountFrequency (%)
34.98889736 1
1.4%
34.91802233 1
1.4%
34.91437881 1
1.4%
34.9134605 1
1.4%
34.9012666 1
1.4%
34.89992702 1
1.4%
34.89991071 1
1.4%
34.89848567 1
1.4%
34.89726297 2
2.7%
34.8972158 1
1.4%

경도
Real number (ℝ)

Distinct72
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.65406
Minimum128.4776
Maximum128.7336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-11T09:04:48.594476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.4776
5-th percentile128.5903
Q1128.62494
median128.64251
Q3128.69143
95-th percentile128.72739
Maximum128.7336
Range0.2560049
Interquartile range (IQR)0.0664974

Descriptive statistics

Standard deviation0.048551351
Coefficient of variation (CV)0.0003773791
Kurtosis1.31903
Mean128.65406
Median Absolute Deviation (MAD)0.0408136
Skewness-0.63641164
Sum9391.746
Variance0.0023572337
MonotonicityNot monotonic
2023-12-11T09:04:48.773342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6867745 2
 
2.7%
128.623119 1
 
1.4%
128.6866028 1
 
1.4%
128.6911884 1
 
1.4%
128.6119696 1
 
1.4%
128.6051869 1
 
1.4%
128.6432025 1
 
1.4%
128.6941605 1
 
1.4%
128.6235645 1
 
1.4%
128.6233513 1
 
1.4%
Other values (62) 62
84.9%
ValueCountFrequency (%)
128.4775952 1
1.4%
128.525476 1
1.4%
128.5894022 1
1.4%
128.5901905 1
1.4%
128.5903806 1
1.4%
128.5923049 1
1.4%
128.6051434 1
1.4%
128.6051869 1
1.4%
128.6085843 1
1.4%
128.6119696 1
1.4%
ValueCountFrequency (%)
128.7336001 1
1.4%
128.733228 1
1.4%
128.7323519 1
1.4%
128.7305015 1
1.4%
128.7253181 1
1.4%
128.7238926 1
1.4%
128.7219771 1
1.4%
128.7214371 1
1.4%
128.7037273 1
1.4%
128.7005188 1
1.4%

소재지전화번호
Text

MISSING 

Distinct71
Distinct (%)100.0%
Missing2
Missing (%)2.7%
Memory size716.0 B
2023-12-11T09:04:49.071877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters923
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)100.0%

Sample

1st row 055-632-0108
2nd row 055-681-0630
3rd row 055-633-3510
4th row 055-633-4145
5th row 055-681-6982
ValueCountFrequency (%)
055-632-0108 1
 
1.4%
055-632-7270 1
 
1.4%
055-687-9257 1
 
1.4%
055-633-0833 1
 
1.4%
055-633-0021 1
 
1.4%
055-688-4646 1
 
1.4%
055-638-4900 1
 
1.4%
055-688-1700 1
 
1.4%
055-638-5737 1
 
1.4%
055-688-1184 1
 
1.4%
Other values (61) 61
85.9%
2023-12-11T09:04:49.563297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 182
19.7%
- 142
15.4%
0 109
11.8%
6 93
10.1%
8 76
8.2%
71
 
7.7%
3 69
 
7.5%
7 53
 
5.7%
2 46
 
5.0%
1 37
 
4.0%
Other values (2) 45
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 710
76.9%
Dash Punctuation 142
 
15.4%
Space Separator 71
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 182
25.6%
0 109
15.4%
6 93
13.1%
8 76
10.7%
3 69
 
9.7%
7 53
 
7.5%
2 46
 
6.5%
1 37
 
5.2%
4 30
 
4.2%
9 15
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 142
100.0%
Space Separator
ValueCountFrequency (%)
71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 923
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 182
19.7%
- 142
15.4%
0 109
11.8%
6 93
10.1%
8 76
8.2%
71
 
7.7%
3 69
 
7.5%
7 53
 
5.7%
2 46
 
5.0%
1 37
 
4.0%
Other values (2) 45
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 923
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 182
19.7%
- 142
15.4%
0 109
11.8%
6 93
10.1%
8 76
8.2%
71
 
7.7%
3 69
 
7.5%
7 53
 
5.7%
2 46
 
5.0%
1 37
 
4.0%
Other values (2) 45
 
4.9%

영업자시작일자
Date

Distinct67
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size716.0 B
Minimum1987-05-11 00:00:00
Maximum2021-05-11 00:00:00
2023-12-11T09:04:49.776083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:50.249306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
Minimum2021-08-30 00:00:00
Maximum2021-08-30 00:00:00
2023-12-11T09:04:50.370816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:50.487718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T09:04:44.904555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:44.663133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:45.037081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:44.788443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:04:50.571299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명영업소주소(도로명)영업소주소(지번)위도경도소재지전화번호영업자시작일자
업소명1.0001.0001.0001.0001.0001.0001.000
영업소주소(도로명)1.0001.0001.0001.0001.0001.0000.993
영업소주소(지번)1.0001.0001.0001.0001.0001.0001.000
위도1.0001.0001.0001.0000.9011.0000.000
경도1.0001.0001.0000.9011.0001.0000.734
소재지전화번호1.0001.0001.0001.0001.0001.0001.000
영업자시작일자1.0000.9931.0000.0000.7341.0001.000
2023-12-11T09:04:50.683718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.045
경도-0.0451.000

Missing values

2023-12-11T09:04:45.193769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:04:45.334106image/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.

Sample

업소명영업소주소(도로명)영업소주소(지번)위도경도소재지전화번호영업자시작일자기준일자
0백모세탁소경상남도 거제시 고현로9길 4 (고현동)경상남도 거제시 고현동 818-2034.886877128.623119055-632-01081987-05-112021-08-30
1부산세탁소경상남도 거제시 일운면 지세포로 101경상남도 거제시 일운면 지세포리 927-634.82959128.703727055-681-06301987-05-112021-08-30
2태양세탁소경상남도 거제시 거제면 읍내로2길 33경상남도 거제시 거제면 동상리 423-434.84999128.590191055-633-35101987-05-112021-08-30
3거제컴퓨터세탁경상남도 거제시 거제면 읍내로2길 29-1경상남도 거제시 거제면 동상리 417-234.850193128.590381055-633-41451987-05-112021-08-30
4백광컴퓨터크리닝경상남도 거제시 장승포로1길 37 (장승포동)경상남도 거제시 장승포동 455-1434.868824128.723893055-681-69821987-05-112021-08-30
5흑백세탁경상남도 거제시 장승로 50 (장승포동)경상남도 거제시 장승포동 596-234.859842128.721977055-681-85572016-12-012021-08-30
6옥포세탁소경상남도 거제시 서간도길 78 (옥포동)경상남도 거제시 옥포동 167034.890489128.687621055-687-30632020-03-162021-08-30
7중앙컴퓨터크리닝경상남도 거제시 옥포대첩로3길 8 (옥포동)경상남도 거제시 옥포동 529-134.89397128.689238055-687-02021987-05-112021-08-30
8백조세탁소경상남도 거제시 옥포로 275 (옥포동)경상남도 거제시 옥포동 1290-134.898486128.687362055-687-63711991-09-272021-08-30
9화인세탁소경상남도 거제시 서문로3길 11 (고현동)경상남도 거제시 고현동 959-834.889265128.618725055-635-75052004-02-102021-08-30
업소명영업소주소(도로명)영업소주소(지번)위도경도소재지전화번호영업자시작일자기준일자
63호텔세탁경상남도 거제시 아주로 43-4 (아주동)경상남도 거제시 아주동 319-1134.864545128.690028055-681-33862019-04-102021-08-30
64좋은세탁소경상남도 거제시 수양로 489, 1호동 1층 102호 (양정동)경상남도 거제시 양정동 929-234.891231128.63798055-635-54572019-02-132021-08-30
65와우아트크린경상남도 거제시 아주1로2길 84, 1층 (아주동)경상남도 거제시 아주동 1676-1134.868004128.683327055-682-57772018-12-102021-08-30
66빨래방망이 거제본점경상남도 거제시 연초면 연사4길 75, 1층경상남도 거제시 연초면 연사리 859-134.91346128.642514055-636-11822016-11-242021-08-30
67성재산업경상남도 거제시 능포로6길 9, 1층 (능포동)경상남도 거제시 능포동 354-334.877345128.7336055-682-71002017-06-132021-08-30
68이재관세탁전문점경상남도 거제시 중곡1로 92, 한일빌딩 1층 105호 (고현동)경상남도 거제시 고현동 987 한일빌딩34.897216128.629073055-687-48822019-10-152021-08-30
69로또세탁소경상남도 거제시 능포로 164-1, 1층 (능포동)경상남도 거제시 능포동 376-6 1층34.877893128.733228055-682-21212018-02-072021-08-30
70라라랜드경상남도 거제시 사등면 거제대로 5697-4, 주1동 1층경상남도 거제시 사등면 성포리 196 주1동34.918022128.525476<NA>2019-08-132021-08-30
71삼진기업경상남도 거제시 수양로 208-2, 1층 (양정동)경상남도 거제시 양정동 416-334.874327128.653343055-638-00132019-04-022021-08-30
72세탁일번지경상남도 거제시 일운면 거제대로 2533, 1층경상남도 거제시 일운면 지세포리 80934.832345128.700519055-681-26302019-04-182021-08-30