Overview

Dataset statistics

Number of variables9
Number of observations41
Missing cells3
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory77.2 B

Variable types

Categorical2
Text4
Numeric2
DateTime1

Dataset

Description경상남도 거제시 목욕업등록현황(업종명, 업소명, 주소, 좌표, 전화번호, 영업시작일, 기준일자)등의 정보를 제공합니다.
Author경상남도 거제시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3079217

Alerts

업종명 has constant value ""Constant
기준일자 has constant value ""Constant
전화번호 has 3 (7.3%) missing valuesMissing
주소(도로명) has unique valuesUnique
주소(지번) has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:47:07.935460
Analysis finished2023-12-10 23:47:09.029668
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
목욕장업
41 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
목욕장업 41
100.0%

Length

2023-12-11T08:47:09.104261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:47:09.220492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 41
100.0%

업소명
Text

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T08:47:09.446485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length5.9756098
Min length3

Characters and Unicode

Total characters245
Distinct characters100
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)95.1%

Sample

1st row계룡목욕탕
2nd row부영탕
3rd row옥수탕
4th row능수탕
5th row은하탕
ValueCountFrequency (%)
수정탕 2
 
4.7%
일운목욕탕 1
 
2.3%
계룡산온천 1
 
2.3%
거제도해수보양온천 1
 
2.3%
해금강워터랜드 1
 
2.3%
삼성중공업거제호텔사우나 1
 
2.3%
학산토굴황토방 1
 
2.3%
오량황토찜질방 1
 
2.3%
대성오아시스 1
 
2.3%
계룡목욕탕 1
 
2.3%
Other values (32) 32
74.4%
2023-12-11T08:47:09.831995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 22
 
9.0%
수 10
 
4.1%
나 10
 
4.1%
사 8
 
3.3%
우 8
 
3.3%
목 8
 
3.3%
제 7
 
2.9%
거 7
 
2.9%
욕 7
 
2.9%
해 6
 
2.4%
Other values (90) 152
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 239
97.6%
Space Separator 2
 
0.8%
Decimal Number 2
 
0.8%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 22
 
9.2%
수 10
 
4.2%
나 10
 
4.2%
사 8
 
3.3%
우 8
 
3.3%
목 8
 
3.3%
제 7
 
2.9%
거 7
 
2.9%
욕 7
 
2.9%
해 6
 
2.5%
Other values (85) 146
61.1%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 239
97.6%
Common 6
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 22
 
9.2%
수 10
 
4.2%
나 10
 
4.2%
사 8
 
3.3%
우 8
 
3.3%
목 8
 
3.3%
제 7
 
2.9%
거 7
 
2.9%
욕 7
 
2.9%
해 6
 
2.5%
Other values (85) 146
61.1%
Common
ValueCountFrequency (%)
2
33.3%
4 1
16.7%
2 1
16.7%
( 1
16.7%
) 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 239
97.6%
ASCII 6
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 22
 
9.2%
수 10
 
4.2%
나 10
 
4.2%
사 8
 
3.3%
우 8
 
3.3%
목 8
 
3.3%
제 7
 
2.9%
거 7
 
2.9%
욕 7
 
2.9%
해 6
 
2.5%
Other values (85) 146
61.1%
ASCII
ValueCountFrequency (%)
2
33.3%
4 1
16.7%
2 1
16.7%
( 1
16.7%
) 1
16.7%

주소(도로명)
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T08:47:10.096618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length35
Mean length25.804878
Min length18

Characters and Unicode

Total characters1058
Distinct characters95
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)100.0%

Sample

1st row경상남도 거제시 거제중앙로 1879-1 (고현동)
2nd row경상남도 거제시 능포로2길 57 (능포동)
3rd row경상남도 거제시 거제면 동상1길 11
4th row경상남도 거제시 옥수로6길 153 (능포동)
5th row경상남도 거제시 능포로2길 65-1 (능포동)
ValueCountFrequency (%)
경상남도 41
19.2%
거제시 41
19.2%
고현동 8
 
3.8%
옥포동 5
 
2.3%
거제중앙로 3
 
1.4%
거제대로 3
 
1.4%
능포동 3
 
1.4%
거제면 3
 
1.4%
사등면 3
 
1.4%
일운면 3
 
1.4%
Other values (86) 100
46.9%
2023-12-11T08:47:10.610307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
172
 
16.3%
제 58
 
5.5%
거 58
 
5.5%
상 43
 
4.1%
남 42
 
4.0%
시 42
 
4.0%
경 41
 
3.9%
도 41
 
3.9%
1 40
 
3.8%
로 37
 
3.5%
Other values (85) 484
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 637
60.2%
Space Separator 172
 
16.3%
Decimal Number 160
 
15.1%
Open Punctuation 31
 
2.9%
Close Punctuation 31
 
2.9%
Other Punctuation 15
 
1.4%
Dash Punctuation 10
 
0.9%
Math Symbol 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 58
 
9.1%
거 58
 
9.1%
상 43
 
6.8%
남 42
 
6.6%
시 42
 
6.6%
경 41
 
6.4%
도 41
 
6.4%
로 37
 
5.8%
동 32
 
5.0%
포 23
 
3.6%
Other values (69) 220
34.5%
Decimal Number
ValueCountFrequency (%)
1 40
25.0%
2 27
16.9%
3 20
12.5%
7 15
 
9.4%
0 15
 
9.4%
6 13
 
8.1%
5 12
 
7.5%
4 8
 
5.0%
9 5
 
3.1%
8 5
 
3.1%
Space Separator
ValueCountFrequency (%)
172
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Other Punctuation
ValueCountFrequency (%)
， 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 637
60.2%
Common 421
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 58
 
9.1%
거 58
 
9.1%
상 43
 
6.8%
남 42
 
6.6%
시 42
 
6.6%
경 41
 
6.4%
도 41
 
6.4%
로 37
 
5.8%
동 32
 
5.0%
포 23
 
3.6%
Other values (69) 220
34.5%
Common
ValueCountFrequency (%)
172
40.9%
1 40
 
9.5%
( 31
 
7.4%
) 31
 
7.4%
2 27
 
6.4%
3 20
 
4.8%
7 15
 
3.6%
， 15
 
3.6%
0 15
 
3.6%
6 13
 
3.1%
Other values (6) 42
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 637
60.2%
ASCII 406
38.4%
None 15
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
172
42.4%
1 40
 
9.9%
( 31
 
7.6%
) 31
 
7.6%
2 27
 
6.7%
3 20
 
4.9%
7 15
 
3.7%
0 15
 
3.7%
6 13
 
3.2%
5 12
 
3.0%
Other values (5) 30
 
7.4%
Hangul
ValueCountFrequency (%)
제 58
 
9.1%
거 58
 
9.1%
상 43
 
6.8%
남 42
 
6.6%
시 42
 
6.6%
경 41
 
6.4%
도 41
 
6.4%
로 37
 
5.8%
동 32
 
5.0%
포 23
 
3.6%
Other values (69) 220
34.5%
None
ValueCountFrequency (%)
， 15
100.0%

주소(지번)
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T08:47:10.932502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length34
Mean length22.390244
Min length16

Characters and Unicode

Total characters918
Distinct characters87
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)100.0%

Sample

1st row경상남도 거제시 고현동 98-15
2nd row경상남도 거제시 능포동 664-2
3rd row경상남도 거제시 거제면 동상리 635-1
4th row경상남도 거제시 능포동 449-2
5th row경상남도 거제시 능포동 332-6
ValueCountFrequency (%)
경상남도 41
21.2%
거제시 41
21.2%
고현동 8
 
4.1%
옥포동 7
 
3.6%
능포동 4
 
2.1%
거제면 3
 
1.6%
사등면 3
 
1.6%
장평동 3
 
1.6%
일운면 3
 
1.6%
동부면 2
 
1.0%
Other values (77) 78
40.4%
2023-12-11T08:47:11.398640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
194
21.1%
거 46
 
5.0%
제 46
 
5.0%
상 43
 
4.7%
남 42
 
4.6%
경 41
 
4.5%
도 41
 
4.5%
시 41
 
4.5%
1 40
 
4.4%
동 34
 
3.7%
Other values (77) 350
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 510
55.6%
Space Separator 194
 
21.1%
Decimal Number 175
 
19.1%
Dash Punctuation 30
 
3.3%
Other Punctuation 3
 
0.3%
Math Symbol 2
 
0.2%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 46
 
9.0%
제 46
 
9.0%
상 43
 
8.4%
남 42
 
8.2%
경 41
 
8.0%
도 41
 
8.0%
시 41
 
8.0%
동 34
 
6.7%
포 15
 
2.9%
리 15
 
2.9%
Other values (61) 146
28.6%
Decimal Number
ValueCountFrequency (%)
1 40
22.9%
2 25
14.3%
6 21
12.0%
3 20
11.4%
4 19
10.9%
5 16
 
9.1%
9 13
 
7.4%
7 11
 
6.3%
0 7
 
4.0%
8 3
 
1.7%
Space Separator
ValueCountFrequency (%)
194
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Other Punctuation
ValueCountFrequency (%)
， 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 510
55.6%
Common 408
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 46
 
9.0%
제 46
 
9.0%
상 43
 
8.4%
남 42
 
8.2%
경 41
 
8.0%
도 41
 
8.0%
시 41
 
8.0%
동 34
 
6.7%
포 15
 
2.9%
리 15
 
2.9%
Other values (61) 146
28.6%
Common
ValueCountFrequency (%)
194
47.5%
1 40
 
9.8%
- 30
 
7.4%
2 25
 
6.1%
6 21
 
5.1%
3 20
 
4.9%
4 19
 
4.7%
5 16
 
3.9%
9 13
 
3.2%
7 11
 
2.7%
Other values (6) 19
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 510
55.6%
ASCII 405
44.1%
None 3
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
194
47.9%
1 40
 
9.9%
- 30
 
7.4%
2 25
 
6.2%
6 21
 
5.2%
3 20
 
4.9%
4 19
 
4.7%
5 16
 
4.0%
9 13
 
3.2%
7 11
 
2.7%
Other values (5) 16
 
4.0%
Hangul
ValueCountFrequency (%)
거 46
 
9.0%
제 46
 
9.0%
상 43
 
8.4%
남 42
 
8.2%
경 41
 
8.0%
도 41
 
8.0%
시 41
 
8.0%
동 34
 
6.7%
포 15
 
2.9%
리 15
 
2.9%
Other values (61) 146
28.6%
None
ValueCountFrequency (%)
， 3
100.0%

위도
Real number (ℝ)

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.87766
Minimum34.776671
Maximum35.007888
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-11T08:47:11.561891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.776671
5-th percentile34.822064
Q134.867091
median34.883084
Q334.892918
95-th percentile34.8971
Maximum35.007888
Range0.23121632
Interquartile range (IQR)0.0258268

Descriptive statistics

Standard deviation0.03423452
Coefficient of variation (CV)0.00098156012
Kurtosis5.9124519
Mean34.87766
Median Absolute Deviation (MAD)0.01113793
Skewness0.38387082
Sum1429.984
Variance0.0011720023
MonotonicityNot monotonic
2023-12-11T08:47:11.713061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
34.8860554 1
 
2.4%
34.88819926 1
 
2.4%
34.89536387 1
 
2.4%
34.87760982 1
 
2.4%
34.89089246 1
 
2.4%
34.89094929 1
 
2.4%
34.89615741 1
 
2.4%
34.86709112 1
 
2.4%
34.88308398 1
 
2.4%
34.88275627 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
34.77667146 1
2.4%
34.81149117 1
2.4%
34.82206415 1
2.4%
34.82968153 1
2.4%
34.842309 1
2.4%
34.84379126 1
2.4%
34.84959557 1
2.4%
34.84980745 1
2.4%
34.86151174 1
2.4%
34.86572915 1
2.4%
ValueCountFrequency (%)
35.00788778 1
2.4%
34.91426555 1
2.4%
34.89709996 1
2.4%
34.89664526 1
2.4%
34.89615741 1
2.4%
34.89593623 1
2.4%
34.89536387 1
2.4%
34.89530426 1
2.4%
34.89422191 1
2.4%
34.89378723 1
2.4%

경도
Real number (ℝ)

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.64665
Minimum128.47683
Maximum128.73472
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-11T08:47:11.844168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.47683
5-th percentile128.50959
Q1128.61384
median128.63524
Q3128.6962
95-th percentile128.73241
Maximum128.73472
Range0.2578881
Interquartile range (IQR)0.0823605

Descriptive statistics

Standard deviation0.066339668
Coefficient of variation (CV)0.00051567348
Kurtosis0.34830597
Mean128.64665
Median Absolute Deviation (MAD)0.0532634
Skewness-0.76885698
Sum5274.5128
Variance0.0044009516
MonotonicityNot monotonic
2023-12-11T08:47:11.980785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
128.6240315 1
 
2.4%
128.5380014 1
 
2.4%
128.6284614 1
 
2.4%
128.6282693 1
 
2.4%
128.6352414 1
 
2.4%
128.6039936 1
 
2.4%
128.6123224 1
 
2.4%
128.4870783 1
 
2.4%
128.5095916 1
 
2.4%
128.6250776 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
128.4768317 1
2.4%
128.4870783 1
2.4%
128.5095916 1
2.4%
128.5380014 1
2.4%
128.5890596 1
2.4%
128.5924116 1
2.4%
128.593421 1
2.4%
128.6039936 1
2.4%
128.6068822 1
2.4%
128.6123224 1
2.4%
ValueCountFrequency (%)
128.7347198 1
2.4%
128.7326461 1
2.4%
128.7324079 1
2.4%
128.7323511 1
2.4%
128.7269456 1
2.4%
128.7229727 1
2.4%
128.712119 1
2.4%
128.7058695 1
2.4%
128.7040067 1
2.4%
128.7029426 1
2.4%

전화번호
Text

MISSING 

Distinct38
Distinct (%)100.0%
Missing3
Missing (%)7.3%
Memory size460.0 B
2023-12-11T08:47:12.202475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters456
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

Unique38 ?
Unique (%)100.0%

Sample

1st row055-635-2149
2nd row055-681-4850
3rd row055-633-3504
4th row055-681-8212
5th row055-681-4512
ValueCountFrequency (%)
055-687-2874 1
 
2.6%
055-632-0544 1
 
2.6%
055-688-4552 1
 
2.6%
055-688-1501 1
 
2.6%
055-638-0072 1
 
2.6%
055-638-0002 1
 
2.6%
055-638-3000 1
 
2.6%
055-633-7120 1
 
2.6%
055-631-2622 1
 
2.6%
055-682-1780 1
 
2.6%
Other values (28) 28
73.7%
2023-12-11T08:47:12.591319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 95
20.8%
0 76
16.7%
- 76
16.7%
6 46
10.1%
8 37
 
8.1%
3 35
 
7.7%
2 32
 
7.0%
7 23
 
5.0%
1 19
 
4.2%
4 11
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 380
83.3%
Dash Punctuation 76
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 95
25.0%
0 76
20.0%
6 46
12.1%
8 37
 
9.7%
3 35
 
9.2%
2 32
 
8.4%
7 23
 
6.1%
1 19
 
5.0%
4 11
 
2.9%
9 6
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 456
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 95
20.8%
0 76
16.7%
- 76
16.7%
6 46
10.1%
8 37
 
8.1%
3 35
 
7.7%
2 32
 
7.0%
7 23
 
5.0%
1 19
 
4.2%
4 11
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 95
20.8%
0 76
16.7%
- 76
16.7%
6 46
10.1%
8 37
 
8.1%
3 35
 
7.7%
2 32
 
7.0%
7 23
 
5.0%
1 19
 
4.2%
4 11
 
2.4%

영업시작일
Date

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
Minimum1981-09-05 00:00:00
Maximum2022-02-08 00:00:00
2023-12-11T08:47:13.047395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:47:13.198457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
2022-08-08
41 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2022-08-08 41
100.0%

Length

2023-12-11T08:47:13.318106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:47:13.417113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-08 41
100.0%

Interactions

2023-12-11T08:47:08.460124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:47:08.310428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:47:08.559968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:47:08.383795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:47:13.508458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명주소(도로명)주소(지번)위도경도전화번호영업시작일
업소명1.0001.0001.0000.9430.9771.0000.995
주소(도로명)1.0001.0001.0001.0001.0001.0001.000
주소(지번)1.0001.0001.0001.0001.0001.0001.000
위도0.9431.0001.0001.0000.4401.0000.000
경도0.9771.0001.0000.4401.0001.0000.935
전화번호1.0001.0001.0001.0001.0001.0001.000
영업시작일0.9951.0001.0000.0000.9351.0001.000
2023-12-11T08:47:13.623905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.025
경도0.0251.000

Missing values

2023-12-11T08:47:08.721458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:47:08.962017image/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

업종명업소명주소(도로명)주소(지번)위도경도전화번호영업시작일기준일자
0목욕장업계룡목욕탕경상남도 거제시 거제중앙로 1879-1 (고현동)경상남도 거제시 고현동 98-1534.886055128.624032055-635-21492008-07-012022-08-08
1목욕장업부영탕경상남도 거제시 능포로2길 57 (능포동)경상남도 거제시 능포동 664-234.876303128.732408055-681-48502008-01-182022-08-08
2목욕장업옥수탕경상남도 거제시 거제면 동상1길 11경상남도 거제시 거제면 동상리 635-134.849807128.593421055-633-35041981-09-052022-08-08
3목욕장업능수탕경상남도 거제시 옥수로6길 153 (능포동)경상남도 거제시 능포동 449-234.88049128.73472055-681-82122019-12-102022-08-08
4목욕장업은하탕경상남도 거제시 능포로2길 65-1 (능포동)경상남도 거제시 능포동 332-634.877079128.732646055-681-45122005-09-232022-08-08
5목욕장업대원탕경상남도 거제시 능포로 150-1경상남도 거제시 능포동 660-134.876799128.732351055-682-23332012-02-152022-08-08
6목욕장업성호탕경상남도 거제시 거제중앙로17길 26 (고현동)경상남도 거제시 고현동 735-234.884246128.622227055-632-04762002-03-122022-08-08
7목욕장업동남탕경상남도 거제시 거제면 읍내로11길 8경상남도 거제시 거제면 남동리 11234.849596128.58906055-632-97771985-10-182022-08-08
8목욕장업청금탕경상남도 거제시 옥포로24길 13 (옥포동)경상남도 거제시 옥포동 512-1334.895936128.692076055-687-28742004-01-122022-08-08
9목욕장업연초탕경상남도 거제시 연초면 거제북로 40-1경상남도 거제시 연초면 죽토리 1104-1534.914266128.655897055-636-01351998-03-112022-08-08
업종명업소명주소(도로명)주소(지번)위도경도전화번호영업시작일기준일자
31목욕장업금세기관광목장황토찜질방경상남도 거제시 사등면 언양로 320경상남도 거제시 사등면 사등리 1316-1634.888199128.538001055-636-37272009-09-102022-08-08
32목욕장업옥포24시사우나경상남도 거제시 옥포대첩로6길 13 (옥포동，(1층~5층))경상남도 거제시 옥포동 542-2 (1층~5층)34.892918128.694165055-687-92152019-07-242022-08-08
33목욕장업카멜리아경상남도 거제시 일운면 거제대로 2190 (지하3층)경상남도 거제시 일운면 와현리 622 지하3층34.811491128.704007055-730-11002014-10-282022-08-08
34목욕장업거제황토파라스파찜질방경상남도 거제시 거제면 오수2길 75경상남도 거제시 거제면 오수리 673-134.842309128.592412055-632-88092013-01-182022-08-08
35목욕장업소노캄거제목욕장(사우나)경상남도 거제시 일운면 거제대로 2660，지2，지3층 (외36필지)경상남도 거제시 일운면 소동리 115 외36필지 지2층，지3층34.843791128.702943055-773-72012021-10-222022-08-08
36목욕장업거제히노끼해수찜경상남도 거제시 동부면 거제중앙로 20，1~3층경상남도 거제시 동부면 학동리 266-6 1층~3층34.776671128.640803055-637-05052021-02-152022-08-08
37목욕장업아주사우나 휘트니스 찜질방경상남도 거제시 아주로9길 7 (아주동)경상남도 거제시 아주동 1271 외 7필지34.865729128.68041055-682-17802015-03-032022-08-08
38목욕장업사우나경상남도 거제시 장목면 거제북로 2501-40，한화리조트 거제 벨버디어 지하3층경상남도 거제시 장목면 농소리 25 한화리조트 거제 벨버디어35.007888128.712119<NA>2022-02-082022-08-08
39목욕장업일운목욕탕경상남도 거제시 일운면 지세포해안로 97，지세포어민복지센타 2층경상남도 거제시 일운면 지세포리 931-57 지세포어민복지센타34.829682128.70587055-682-05352019-06-052022-08-08
40목욕장업거제시하나행복나눔복지회관목욕장경상남도 거제시 동부면 동부로2길 21，거제시하나행복나눔복지회관 1층경상남도 거제시 동부면 산양리 36334.822064128.606882<NA>2021-02-152022-08-08