Overview

Dataset statistics

Number of variables9
Number of observations68
Missing cells8
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory75.9 B

Variable types

Categorical2
Text4
DateTime1
Numeric2

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

업종명 has constant value ""Constant
기준일자 has constant value ""Constant
소재지전화 has 8 (11.8%) missing valuesMissing
업소명 has unique valuesUnique
영업소 주소(지번) has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:04:52.593361
Analysis finished2023-12-11 00:04:53.773537
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
세탁업
68 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세탁업 68
100.0%

Length

2023-12-11T09:04:53.837875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:04:53.940220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세탁업 68
100.0%

업소명
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2023-12-11T09:04:54.216885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length10
Mean length6.1029412
Min length3

Characters and Unicode

Total characters415
Distinct characters128
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)100.0%

Sample

1st row부산세탁소
2nd row태양세탁소
3rd row거제컴퓨터세탁
4th row백광컴퓨터크리닝
5th row흑백세탁
ValueCountFrequency (%)
부산세탁소 1
 
1.3%
슈즈쿨 1
 
1.3%
반야세탁소 1
 
1.3%
연초세탁소 1
 
1.3%
숲속그린세탁소 1
 
1.3%
화이트세탁전문점 1
 
1.3%
백광사 1
 
1.3%
슈즈쿨운동화빨래방 1
 
1.3%
태양세탁소 1
 
1.3%
운동화빨래방 1
 
1.3%
Other values (66) 66
86.8%
2023-12-11T09:04:54.673751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 47
 
11.3%
탁 47
 
11.3%
소 32
 
7.7%
리 13
 
3.1%
크 12
 
2.9%
닝 11
 
2.7%
동 10
 
2.4%
8
 
1.9%
화 7
 
1.7%
터 6
 
1.4%
Other values (118) 222
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 405
97.6%
Space Separator 8
 
1.9%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 47
 
11.6%
탁 47
 
11.6%
소 32
 
7.9%
리 13
 
3.2%
크 12
 
3.0%
닝 11
 
2.7%
동 10
 
2.5%
화 7
 
1.7%
터 6
 
1.5%
이 6
 
1.5%
Other values (115) 214
52.8%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 405
97.6%
Common 10
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 47
 
11.6%
탁 47
 
11.6%
소 32
 
7.9%
리 13
 
3.2%
크 12
 
3.0%
닝 11
 
2.7%
동 10
 
2.5%
화 7
 
1.7%
터 6
 
1.5%
이 6
 
1.5%
Other values (115) 214
52.8%
Common
ValueCountFrequency (%)
8
80.0%
) 1
 
10.0%
( 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 405
97.6%
ASCII 10
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 47
 
11.6%
탁 47
 
11.6%
소 32
 
7.9%
리 13
 
3.2%
크 12
 
3.0%
닝 11
 
2.7%
동 10
 
2.5%
화 7
 
1.7%
터 6
 
1.5%
이 6
 
1.5%
Other values (115) 214
52.8%
ASCII
ValueCountFrequency (%)
8
80.0%
) 1
 
10.0%
( 1
 
10.0%

영업자시작일
Date

Distinct63
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size676.0 B
Minimum1987-05-11 00:00:00
Maximum2022-07-22 00:00:00
2023-12-11T09:04:54.813907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:54.981636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업소 주소(도로명)
Text

Distinct67
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
2023-12-11T09:04:55.306276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length38
Mean length26.75
Min length19

Characters and Unicode

Total characters1819
Distinct characters120
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)97.1%

Sample

1st row경상남도 거제시 일운면 지세포로 101
2nd row경상남도 거제시 거제면 읍내로2길 33
3rd row경상남도 거제시 거제면 읍내로2길 29
4th row경상남도 거제시 장승포로1길 37 (장승포동)
5th row경상남도 거제시 장승로 50 (장승포동)
ValueCountFrequency (%)
경상남도 68
 
18.8%
거제시 68
 
18.8%
고현동 13
 
3.6%
옥포동 8
 
2.2%
1층 7
 
1.9%
거제면 4
 
1.1%
연초면 4
 
1.1%
능포동 4
 
1.1%
거제대로 4
 
1.1%
상동동 4
 
1.1%
Other values (149) 177
49.0%
2023-12-11T09:04:55.758006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
293
 
16.1%
제 84
 
4.6%
1 82
 
4.5%
거 82
 
4.5%
상 79
 
4.3%
동 77
 
4.2%
남 69
 
3.8%
경 68
 
3.7%
도 68
 
3.7%
시 68
 
3.7%
Other values (110) 849
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1068
58.7%
Space Separator 293
 
16.1%
Decimal Number 282
 
15.5%
Open Punctuation 61
 
3.4%
Close Punctuation 61
 
3.4%
Other Punctuation 40
 
2.2%
Dash Punctuation 13
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 84
 
7.9%
거 82
 
7.7%
상 79
 
7.4%
동 77
 
7.2%
남 69
 
6.5%
경 68
 
6.4%
도 68
 
6.4%
시 68
 
6.4%
로 57
 
5.3%
길 40
 
3.7%
Other values (94) 376
35.2%
Decimal Number
ValueCountFrequency (%)
1 82
29.1%
3 36
12.8%
2 35
12.4%
5 27
 
9.6%
0 27
 
9.6%
4 18
 
6.4%
9 18
 
6.4%
6 16
 
5.7%
7 13
 
4.6%
8 10
 
3.5%
Space Separator
ValueCountFrequency (%)
293
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Other Punctuation
ValueCountFrequency (%)
， 40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1068
58.7%
Common 750
41.2%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 84
 
7.9%
거 82
 
7.7%
상 79
 
7.4%
동 77
 
7.2%
남 69
 
6.5%
경 68
 
6.4%
도 68
 
6.4%
시 68
 
6.4%
로 57
 
5.3%
길 40
 
3.7%
Other values (94) 376
35.2%
Common
ValueCountFrequency (%)
293
39.1%
1 82
 
10.9%
( 61
 
8.1%
) 61
 
8.1%
， 40
 
5.3%
3 36
 
4.8%
2 35
 
4.7%
5 27
 
3.6%
0 27
 
3.6%
4 18
 
2.4%
Other values (5) 70
 
9.3%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1068
58.7%
ASCII 711
39.1%
None 40
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
293
41.2%
1 82
 
11.5%
( 61
 
8.6%
) 61
 
8.6%
3 36
 
5.1%
2 35
 
4.9%
5 27
 
3.8%
0 27
 
3.8%
4 18
 
2.5%
9 18
 
2.5%
Other values (5) 53
 
7.5%
Hangul
ValueCountFrequency (%)
제 84
 
7.9%
거 82
 
7.7%
상 79
 
7.4%
동 77
 
7.2%
남 69
 
6.5%
경 68
 
6.4%
도 68
 
6.4%
시 68
 
6.4%
로 57
 
5.3%
길 40
 
3.7%
Other values (94) 376
35.2%
None
ValueCountFrequency (%)
， 40
100.0%

영업소 주소(지번)
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2023-12-11T09:04:56.080229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length22.867647
Min length15

Characters and Unicode

Total characters1555
Distinct characters98
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)100.0%

Sample

1st row경상남도 거제시 일운면 지세포리 927-6
2nd row경상남도 거제시 거제면 동상리 423-4
3rd row경상남도 거제시 거제면 동상리 417-1
4th row경상남도 거제시 장승포동 455-14
5th row경상남도 거제시 장승포동 596-2
ValueCountFrequency (%)
경상남도 68
21.0%
거제시 68
21.0%
고현동 15
 
4.6%
옥포동 13
 
4.0%
1층 8
 
2.5%
아주동 5
 
1.5%
101호 5
 
1.5%
상동동 5
 
1.5%
연초면 4
 
1.2%
능포동 4
 
1.2%
Other values (114) 129
39.8%
2023-12-11T09:04:56.586571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
316
20.3%
1 86
 
5.5%
상 80
 
5.1%
제 75
 
4.8%
거 74
 
4.8%
동 71
 
4.6%
경 68
 
4.4%
남 68
 
4.4%
도 68
 
4.4%
시 68
 
4.4%
Other values (88) 581
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 839
54.0%
Decimal Number 341
21.9%
Space Separator 316
 
20.3%
Dash Punctuation 53
 
3.4%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 80
 
9.5%
제 75
 
8.9%
거 74
 
8.8%
동 71
 
8.5%
경 68
 
8.1%
남 68
 
8.1%
도 68
 
8.1%
시 68
 
8.1%
포 22
 
2.6%
고 15
 
1.8%
Other values (74) 230
27.4%
Decimal Number
ValueCountFrequency (%)
1 86
25.2%
0 38
11.1%
9 33
 
9.7%
4 32
 
9.4%
2 32
 
9.4%
6 30
 
8.8%
5 26
 
7.6%
8 24
 
7.0%
7 21
 
6.2%
3 19
 
5.6%
Space Separator
ValueCountFrequency (%)
316
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 839
54.0%
Common 716
46.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 80
 
9.5%
제 75
 
8.9%
거 74
 
8.8%
동 71
 
8.5%
경 68
 
8.1%
남 68
 
8.1%
도 68
 
8.1%
시 68
 
8.1%
포 22
 
2.6%
고 15
 
1.8%
Other values (74) 230
27.4%
Common
ValueCountFrequency (%)
316
44.1%
1 86
 
12.0%
- 53
 
7.4%
0 38
 
5.3%
9 33
 
4.6%
4 32
 
4.5%
2 32
 
4.5%
6 30
 
4.2%
5 26
 
3.6%
8 24
 
3.4%
Other values (4) 46
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 839
54.0%
ASCII 716
46.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
316
44.1%
1 86
 
12.0%
- 53
 
7.4%
0 38
 
5.3%
9 33
 
4.6%
4 32
 
4.5%
2 32
 
4.5%
6 30
 
4.2%
5 26
 
3.6%
8 24
 
3.4%
Other values (4) 46
 
6.4%
Hangul
ValueCountFrequency (%)
상 80
 
9.5%
제 75
 
8.9%
거 74
 
8.8%
동 71
 
8.5%
경 68
 
8.1%
남 68
 
8.1%
도 68
 
8.1%
시 68
 
8.1%
포 22
 
2.6%
고 15
 
1.8%
Other values (74) 230
27.4%

소재지전화
Text

MISSING 

Distinct60
Distinct (%)100.0%
Missing8
Missing (%)11.8%
Memory size676.0 B
2023-12-11T09:04:56.897168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters720
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row055-681-0630
2nd row055-633-3510
3rd row055-633-4145
4th row055-681-6982
5th row055-681-8557
ValueCountFrequency (%)
055-687-2867 1
 
1.7%
055-688-2567 1
 
1.7%
055-633-5929 1
 
1.7%
055-637-8820 1
 
1.7%
055-632-0063 1
 
1.7%
055-681-7251 1
 
1.7%
055-682-5282 1
 
1.7%
055-632-0057 1
 
1.7%
055-632-3416 1
 
1.7%
055-687-9257 1
 
1.7%
Other values (50) 50
83.3%
2023-12-11T09:04:57.350560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 158
21.9%
- 120
16.7%
0 92
12.8%
6 77
10.7%
8 60
 
8.3%
3 59
 
8.2%
7 44
 
6.1%
2 41
 
5.7%
1 34
 
4.7%
4 22
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 600
83.3%
Dash Punctuation 120
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 158
26.3%
0 92
15.3%
6 77
12.8%
8 60
 
10.0%
3 59
 
9.8%
7 44
 
7.3%
2 41
 
6.8%
1 34
 
5.7%
4 22
 
3.7%
9 13
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 720
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 158
21.9%
- 120
16.7%
0 92
12.8%
6 77
10.7%
8 60
 
8.3%
3 59
 
8.2%
7 44
 
6.1%
2 41
 
5.7%
1 34
 
4.7%
4 22
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 158
21.9%
- 120
16.7%
0 92
12.8%
6 77
10.7%
8 60
 
8.3%
3 59
 
8.2%
7 44
 
6.1%
2 41
 
5.7%
1 34
 
4.7%
4 22
 
3.1%

위도
Real number (ℝ)

Distinct67
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.884252
Minimum34.829592
Maximum34.988898
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-11T09:04:57.523551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.829592
5-th percentile34.850156
Q134.874678
median34.88589
Q334.89569
95-th percentile34.909193
Maximum34.988898
Range0.15930681
Interquartile range (IQR)0.021012895

Descriptive statistics

Standard deviation0.021861327
Coefficient of variation (CV)0.00062668184
Kurtosis7.323588
Mean34.884252
Median Absolute Deviation (MAD)0.010470925
Skewness1.0981896
Sum2372.1291
Variance0.00047791762
MonotonicityNot monotonic
2023-12-11T09:04:57.681548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.89726258 2
 
2.9%
34.82959157 1
 
1.5%
34.85143925 1
 
1.5%
34.87610676 1
 
1.5%
34.85010898 1
 
1.5%
34.88626671 1
 
1.5%
34.89361549 1
 
1.5%
34.89465165 1
 
1.5%
34.87965582 1
 
1.5%
34.87493204 1
 
1.5%
Other values (57) 57
83.8%
ValueCountFrequency (%)
34.82959157 1
1.5%
34.83234154 1
1.5%
34.84999306 1
1.5%
34.85010898 1
1.5%
34.85024413 1
1.5%
34.85143925 1
1.5%
34.8587359 1
1.5%
34.85983676 1
1.5%
34.86368766 1
1.5%
34.86454798 1
1.5%
ValueCountFrequency (%)
34.98889838 1
1.5%
34.91801831 1
1.5%
34.91437637 1
1.5%
34.91346103 1
1.5%
34.90126606 1
1.5%
34.90032046 1
1.5%
34.89992536 1
1.5%
34.89990765 1
1.5%
34.89848523 1
1.5%
34.89726258 2
2.9%

경도
Real number (ℝ)

Distinct67
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.65375
Minimum128.47759
Maximum128.7336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-11T09:04:57.854076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.47759
5-th percentile128.59029
Q1128.62571
median128.64113
Q3128.69152
95-th percentile128.72869
Maximum128.7336
Range0.2560082
Interquartile range (IQR)0.06580225

Descriptive statistics

Standard deviation0.049163541
Coefficient of variation (CV)0.00038213843
Kurtosis1.3849105
Mean128.65375
Median Absolute Deviation (MAD)0.0412684
Skewness-0.6384472
Sum8748.4547
Variance0.0024170537
MonotonicityNot monotonic
2023-12-11T09:04:58.042379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6867726 2
 
2.9%
128.7037229 1
 
1.5%
128.5894047 1
 
1.5%
128.6265321 1
 
1.5%
128.592304 1
 
1.5%
128.6911881 1
 
1.5%
128.6119715 1
 
1.5%
128.643424 1
 
1.5%
128.6235617 1
 
1.5%
128.6917603 1
 
1.5%
Other values (57) 57
83.8%
ValueCountFrequency (%)
128.4775913 1
1.5%
128.5254744 1
1.5%
128.5894047 1
1.5%
128.5901927 1
1.5%
128.5904679 1
1.5%
128.592304 1
1.5%
128.6052069 1
1.5%
128.6085883 1
1.5%
128.6119715 1
1.5%
128.6125953 1
1.5%
ValueCountFrequency (%)
128.7335995 1
1.5%
128.7332324 1
1.5%
128.7323522 1
1.5%
128.7305031 1
1.5%
128.7253131 1
1.5%
128.7238985 1
1.5%
128.7220674 1
1.5%
128.7219823 1
1.5%
128.7037229 1
1.5%
128.7005211 1
1.5%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
2022-08-25
68 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-25
2nd row2022-08-25
3rd row2022-08-25
4th row2022-08-25
5th row2022-08-25

Common Values

ValueCountFrequency (%)
2022-08-25 68
100.0%

Length

2023-12-11T09:04:58.195104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:04:58.308980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-25 68
100.0%

Interactions

2023-12-11T09:04:53.300474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:53.102942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:53.387921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:53.214437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:04:58.379111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명영업자시작일영업소 주소(도로명)영업소 주소(지번)소재지전화위도경도
업소명1.0001.0001.0001.0001.0001.0001.000
영업자시작일1.0001.0000.9931.0001.0000.0000.682
영업소 주소(도로명)1.0000.9931.0001.0001.0001.0001.000
영업소 주소(지번)1.0001.0001.0001.0001.0001.0001.000
소재지전화1.0001.0001.0001.0001.0001.0001.000
위도1.0000.0001.0001.0001.0001.0000.911
경도1.0000.6821.0001.0001.0000.9111.000
2023-12-11T09:04:58.484189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.060
경도-0.0601.000

Missing values

2023-12-11T09:04:53.492429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:04:53.696439image/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

업종명업소명영업자시작일영업소 주소(도로명)영업소 주소(지번)소재지전화위도경도기준일자
0세탁업부산세탁소1987-05-11경상남도 거제시 일운면 지세포로 101경상남도 거제시 일운면 지세포리 927-6055-681-063034.829592128.7037232022-08-25
1세탁업태양세탁소1987-05-11경상남도 거제시 거제면 읍내로2길 33경상남도 거제시 거제면 동상리 423-4055-633-351034.849993128.5901932022-08-25
2세탁업거제컴퓨터세탁1987-05-11경상남도 거제시 거제면 읍내로2길 29경상남도 거제시 거제면 동상리 417-1055-633-414534.850244128.5904682022-08-25
3세탁업백광컴퓨터크리닝1987-05-11경상남도 거제시 장승포로1길 37 (장승포동)경상남도 거제시 장승포동 455-14055-681-698234.868822128.7238982022-08-25
4세탁업흑백세탁2016-12-01경상남도 거제시 장승로 50 (장승포동)경상남도 거제시 장승포동 596-2055-681-855734.859837128.7219822022-08-25
5세탁업중앙컴퓨터크리닝1987-05-11경상남도 거제시 옥포대첩로3길 8 (옥포동)경상남도 거제시 옥포동 529-1055-687-020234.893967128.689242022-08-25
6세탁업백조세탁소1991-09-27경상남도 거제시 옥포로 275 (옥포동)경상남도 거제시 옥포동 1290-1055-687-637134.898485128.6873632022-08-25
7세탁업화인세탁소2004-02-10경상남도 거제시 서문로3길 11 (고현동)경상남도 거제시 고현동 959-8055-635-750534.889263128.6187222022-08-25
8세탁업뽀송이세탁소2013-01-15경상남도 거제시 옥포중앙로 79 (옥포동，1층)경상남도 거제시 옥포동 507-4 1층055-687-702634.896461128.6945012022-08-25
9세탁업한신세탁2021-01-18경상남도 거제시 진목로 19 (옥포동)경상남도 거제시 옥포동 1298-4<NA>34.897263128.6867732022-08-25
업종명업소명영업자시작일영업소 주소(도로명)영업소 주소(지번)소재지전화위도경도기준일자
58세탁업와우아트크린2018-12-10경상남도 거제시 아주1로2길 84，1층 (아주동)경상남도 거제시 아주동 1676-11055-682-577734.868003128.6833242022-08-25
59세탁업빨래방망이 거제본점2016-11-24경상남도 거제시 연초면 연사4길 75，1층경상남도 거제시 연초면 연사리 859-1055-636-118234.913461128.6425092022-08-25
60세탁업성재산업2017-06-13경상남도 거제시 능포로6길 9，1층 (능포동)경상남도 거제시 능포동 354-3055-682-710034.877346128.7335992022-08-25
61세탁업이재관세탁전문점2019-10-15경상남도 거제시 중곡1로 92，한일빌딩 1층 105호 (고현동)경상남도 거제시 고현동 987 한일빌딩055-687-488234.897215128.6290782022-08-25
62세탁업로또세탁소2018-02-07경상남도 거제시 능포로 164-1，1층 (능포동)경상남도 거제시 능포동 376-6 1층055-682-212134.877889128.7332322022-08-25
63세탁업주식회사 다온2022-06-16경상남도 거제시 사등면 거제대로 5697-4，주1동 1층경상남도 거제시 사등면 성포리 196 주1동<NA>34.918018128.5254742022-08-25
64세탁업삼진기업2019-04-02경상남도 거제시 수양로 208-2，1층 (양정동)경상남도 거제시 양정동 416-3055-638-001334.874325128.6533392022-08-25
65세탁업세탁일번지2019-04-18경상남도 거제시 일운면 거제대로 2533，1층경상남도 거제시 일운면 지세포리 809<NA>34.832342128.7005212022-08-25
66세탁업거제시노동자작업복공동세탁소 블루클리닝2021-08-30경상남도 거제시 연초면 소오비길 30，노동자작업복공동세탁소 및 주민쉼터 1층경상남도 거제시 연초면 오비리 166-4055-635-100834.90032128.6299552022-08-25
67세탁업영희네세탁2022-05-23경상남도 거제시 중곡1로2길 12，1층 (고현동)경상남도 거제시 고현동 1003<NA>34.894344128.626432022-08-25