Overview

Dataset statistics

Number of variables10
Number of observations78
Missing cells7
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory82.7 B

Variable types

Text5
DateTime2
Numeric1
Categorical2

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

기준일 has constant value ""Constant
업태명 is highly imbalanced (75.4%)Imbalance
소재지전화 has 7 (9.0%) missing valuesMissing
교부번호 has unique valuesUnique
업소명 has unique valuesUnique
업소소재지(지번) has unique valuesUnique
영업장면적 has 7 (9.0%) zerosZeros

Reproduction

Analysis started2023-12-11 00:04:35.363038
Analysis finished2023-12-11 00:04:36.630830
Duration1.27 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교부번호
Text

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-11T09:04:36.866148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length2
Mean length2.8076923
Min length1

Characters and Unicode

Total characters219
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

Unique78 ?
Unique (%)100.0%

Sample

1st row1
2nd row4
3rd row5
4th row6
5th row8
ValueCountFrequency (%)
1 1
 
1.3%
90 1
 
1.3%
105 1
 
1.3%
102 1
 
1.3%
99 1
 
1.3%
98 1
 
1.3%
97 1
 
1.3%
96 1
 
1.3%
116 1
 
1.3%
88 1
 
1.3%
Other values (68) 68
87.2%
2023-12-11T09:04:37.286599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 47
21.5%
0 38
17.4%
2 27
12.3%
9 16
 
7.3%
6 15
 
6.8%
7 15
 
6.8%
8 13
 
5.9%
4 13
 
5.9%
3 12
 
5.5%
5 11
 
5.0%
Other values (2) 12
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 207
94.5%
Space Separator 6
 
2.7%
Dash Punctuation 6
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 47
22.7%
0 38
18.4%
2 27
13.0%
9 16
 
7.7%
6 15
 
7.2%
7 15
 
7.2%
8 13
 
6.3%
4 13
 
6.3%
3 12
 
5.8%
5 11
 
5.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 219
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 47
21.5%
0 38
17.4%
2 27
12.3%
9 16
 
7.3%
6 15
 
6.8%
7 15
 
6.8%
8 13
 
5.9%
4 13
 
5.9%
3 12
 
5.5%
5 11
 
5.0%
Other values (2) 12
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 219
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 47
21.5%
0 38
17.4%
2 27
12.3%
9 16
 
7.3%
6 15
 
6.8%
7 15
 
6.8%
8 13
 
5.9%
4 13
 
5.9%
3 12
 
5.5%
5 11
 
5.0%
Other values (2) 12
 
5.5%

신고일자
Date

Distinct71
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
Minimum1987-05-11 00:00:00
Maximum2019-04-18 00:00:00
2023-12-11T09:04:37.458995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:37.984278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소명
Text

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-11T09:04:38.294837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.9358974
Min length3

Characters and Unicode

Total characters463
Distinct characters126
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

Unique78 ?
Unique (%)100.0%

Sample

1st row백모세탁소
2nd row부산세탁소
3rd row태양세탁소
4th row거제컴퓨터세탁
5th row백광컴퓨터크리닝
ValueCountFrequency (%)
세탁소 3
 
3.4%
주)웰리브 2
 
2.3%
백모세탁소 1
 
1.1%
착한세탁소 1
 
1.1%
부부 1
 
1.1%
수월세탁소 1
 
1.1%
ok 1
 
1.1%
참조은세탁나라 1
 
1.1%
부영크리닝전문점 1
 
1.1%
슈즈쿨 1
 
1.1%
Other values (74) 74
85.1%
2023-12-11T09:04:38.713352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 54
 
11.7%
탁 54
 
11.7%
소 39
 
8.4%
크 17
 
3.7%
리 15
 
3.2%
닝 12
 
2.6%
9
 
1.9%
동 9
 
1.9%
퓨 7
 
1.5%
터 7
 
1.5%
Other values (116) 240
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 448
96.8%
Space Separator 9
 
1.9%
Open Punctuation 2
 
0.4%
Close Punctuation 2
 
0.4%
Uppercase Letter 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 54
 
12.1%
탁 54
 
12.1%
소 39
 
8.7%
크 17
 
3.8%
리 15
 
3.3%
닝 12
 
2.7%
동 9
 
2.0%
퓨 7
 
1.6%
터 7
 
1.6%
린 7
 
1.6%
Other values (111) 227
50.7%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
O 1
50.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 448
96.8%
Common 13
 
2.8%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 54
 
12.1%
탁 54
 
12.1%
소 39
 
8.7%
크 17
 
3.8%
리 15
 
3.3%
닝 12
 
2.7%
동 9
 
2.0%
퓨 7
 
1.6%
터 7
 
1.6%
린 7
 
1.6%
Other values (111) 227
50.7%
Common
ValueCountFrequency (%)
9
69.2%
( 2
 
15.4%
) 2
 
15.4%
Latin
ValueCountFrequency (%)
K 1
50.0%
O 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 448
96.8%
ASCII 15
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 54
 
12.1%
탁 54
 
12.1%
소 39
 
8.7%
크 17
 
3.8%
리 15
 
3.3%
닝 12
 
2.7%
동 9
 
2.0%
퓨 7
 
1.6%
터 7
 
1.6%
린 7
 
1.6%
Other values (111) 227
50.7%
ASCII
ValueCountFrequency (%)
9
60.0%
( 2
 
13.3%
) 2
 
13.3%
K 1
 
6.7%
O 1
 
6.7%

업소소재지(도로명)
Text

Distinct77
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-11T09:04:39.033019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length36
Mean length27.076923
Min length19

Characters and Unicode

Total characters2112
Distinct characters113
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

Unique76 ?
Unique (%)97.4%

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 78
 
17.8%
거제시 78
 
17.8%
고현동 18
 
4.1%
1층 18
 
4.1%
옥포동 13
 
3.0%
거제대로 5
 
1.1%
6 5
 
1.1%
9 4
 
0.9%
상동동 4
 
0.9%
거제면 4
 
0.9%
Other values (167) 211
48.2%
2023-12-11T09:04:39.650593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
360
 
17.0%
제 95
 
4.5%
1 94
 
4.5%
거 93
 
4.4%
상 90
 
4.3%
동 85
 
4.0%
남 79
 
3.7%
도 79
 
3.7%
시 79
 
3.7%
경 78
 
3.7%
Other values (103) 980
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1221
57.8%
Space Separator 360
 
17.0%
Decimal Number 325
 
15.4%
Open Punctuation 74
 
3.5%
Close Punctuation 74
 
3.5%
Other Punctuation 39
 
1.8%
Dash Punctuation 18
 
0.9%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 95
 
7.8%
거 93
 
7.6%
상 90
 
7.4%
동 85
 
7.0%
남 79
 
6.5%
도 79
 
6.5%
시 79
 
6.5%
경 78
 
6.4%
로 68
 
5.6%
길 49
 
4.0%
Other values (87) 426
34.9%
Decimal Number
ValueCountFrequency (%)
1 94
28.9%
2 43
13.2%
3 40
12.3%
0 31
 
9.5%
5 30
 
9.2%
4 24
 
7.4%
9 20
 
6.2%
7 16
 
4.9%
6 15
 
4.6%
8 12
 
3.7%
Space Separator
ValueCountFrequency (%)
360
100.0%
Open Punctuation
ValueCountFrequency (%)
( 74
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Other Punctuation
ValueCountFrequency (%)
, 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1221
57.8%
Common 890
42.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 95
 
7.8%
거 93
 
7.6%
상 90
 
7.4%
동 85
 
7.0%
남 79
 
6.5%
도 79
 
6.5%
시 79
 
6.5%
경 78
 
6.4%
로 68
 
5.6%
길 49
 
4.0%
Other values (87) 426
34.9%
Common
ValueCountFrequency (%)
360
40.4%
1 94
 
10.6%
( 74
 
8.3%
) 74
 
8.3%
2 43
 
4.8%
3 40
 
4.5%
, 39
 
4.4%
0 31
 
3.5%
5 30
 
3.4%
4 24
 
2.7%
Other values (5) 81
 
9.1%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1221
57.8%
ASCII 891
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
360
40.4%
1 94
 
10.5%
( 74
 
8.3%
) 74
 
8.3%
2 43
 
4.8%
3 40
 
4.5%
, 39
 
4.4%
0 31
 
3.5%
5 30
 
3.4%
4 24
 
2.7%
Other values (6) 82
 
9.2%
Hangul
ValueCountFrequency (%)
제 95
 
7.8%
거 93
 
7.6%
상 90
 
7.4%
동 85
 
7.0%
남 79
 
6.5%
도 79
 
6.5%
시 79
 
6.5%
경 78
 
6.4%
로 68
 
5.6%
길 49
 
4.0%
Other values (87) 426
34.9%

업소소재지(지번)
Text

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-11T09:04:40.018465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length27.089744
Min length5

Characters and Unicode

Total characters2113
Distinct characters96
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

Unique78 ?
Unique (%)100.0%

Sample

1st row경상남도 거제시 고현동 818번지 20호
2nd row경상남도 거제시 일운면 지세포리 927번지 6호
3rd row경상남도 거제시 거제면 동상리 423번지 4호
4th row경상남도 거제시 거제면 동상리 417번지 2호
5th row경상남도 거제시 장승포동 455번지 14호
ValueCountFrequency (%)
경상남도 77
18.1%
거제시 77
18.1%
고현동 19
 
4.5%
옥포동 17
 
4.0%
1호 10
 
2.4%
1층 10
 
2.4%
2호 9
 
2.1%
장평동 6
 
1.4%
능포동 5
 
1.2%
아주동 5
 
1.2%
Other values (142) 190
44.7%
2023-12-11T09:04:40.529324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
553
26.2%
1 92
 
4.4%
상 90
 
4.3%
제 82
 
3.9%
거 81
 
3.8%
지 81
 
3.8%
시 78
 
3.7%
동 78
 
3.7%
경 77
 
3.6%
남 77
 
3.6%
Other values (86) 824
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1160
54.9%
Space Separator 553
26.2%
Decimal Number 386
 
18.3%
Open Punctuation 6
 
0.3%
Close Punctuation 6
 
0.3%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 90
 
7.8%
제 82
 
7.1%
거 81
 
7.0%
지 81
 
7.0%
시 78
 
6.7%
동 78
 
6.7%
경 77
 
6.6%
남 77
 
6.6%
도 77
 
6.6%
번 77
 
6.6%
Other values (72) 362
31.2%
Decimal Number
ValueCountFrequency (%)
1 92
23.8%
0 41
10.6%
2 39
10.1%
9 37
9.6%
6 34
 
8.8%
8 33
 
8.5%
4 31
 
8.0%
5 28
 
7.3%
7 26
 
6.7%
3 25
 
6.5%
Space Separator
ValueCountFrequency (%)
553
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1160
54.9%
Common 953
45.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 90
 
7.8%
제 82
 
7.1%
거 81
 
7.0%
지 81
 
7.0%
시 78
 
6.7%
동 78
 
6.7%
경 77
 
6.6%
남 77
 
6.6%
도 77
 
6.6%
번 77
 
6.6%
Other values (72) 362
31.2%
Common
ValueCountFrequency (%)
553
58.0%
1 92
 
9.7%
0 41
 
4.3%
2 39
 
4.1%
9 37
 
3.9%
6 34
 
3.6%
8 33
 
3.5%
4 31
 
3.3%
5 28
 
2.9%
7 26
 
2.7%
Other values (4) 39
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1160
54.9%
ASCII 953
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
553
58.0%
1 92
 
9.7%
0 41
 
4.3%
2 39
 
4.1%
9 37
 
3.9%
6 34
 
3.6%
8 33
 
3.5%
4 31
 
3.3%
5 28
 
2.9%
7 26
 
2.7%
Other values (4) 39
 
4.1%
Hangul
ValueCountFrequency (%)
상 90
 
7.8%
제 82
 
7.1%
거 81
 
7.0%
지 81
 
7.0%
시 78
 
6.7%
동 78
 
6.7%
경 77
 
6.6%
남 77
 
6.6%
도 77
 
6.6%
번 77
 
6.6%
Other values (72) 362
31.2%

영업장면적
Real number (ℝ)

ZEROS 

Distinct66
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.449103
Minimum0
Maximum318.5
Zeros7
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-11T09:04:40.671914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q128.7
median43.36
Q369.78
95-th percentile174.7715
Maximum318.5
Range318.5
Interquartile range (IQR)41.08

Descriptive statistics

Standard deviation60.597584
Coefficient of variation (CV)0.95505818
Kurtosis4.8094487
Mean63.449103
Median Absolute Deviation (MAD)17.36
Skewness2.052749
Sum4949.03
Variance3672.0672
MonotonicityNot monotonic
2023-12-11T09:04:40.876651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 7
 
9.0%
36.0 3
 
3.8%
26.0 3
 
3.8%
66.0 2
 
2.6%
59.4 2
 
2.6%
29.0 1
 
1.3%
63.84 1
 
1.3%
35.67 1
 
1.3%
35.0 1
 
1.3%
25.0 1
 
1.3%
Other values (56) 56
71.8%
ValueCountFrequency (%)
0.0 7
9.0%
12.8 1
 
1.3%
16.4 1
 
1.3%
18.6 1
 
1.3%
20.88 1
 
1.3%
23.14 1
 
1.3%
25.0 1
 
1.3%
26.0 3
3.8%
27.36 1
 
1.3%
27.38 1
 
1.3%
ValueCountFrequency (%)
318.5 1
1.3%
264.0 1
1.3%
232.05 1
1.3%
178.01 1
1.3%
174.2 1
1.3%
168.88 1
1.3%
164.1 1
1.3%
160.74 1
1.3%
157.11 1
1.3%
152.9 1
1.3%

소재지전화
Text

MISSING 

Distinct71
Distinct (%)100.0%
Missing7
Missing (%)9.0%
Memory size756.0 B
2023-12-11T09:04:41.139727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters852
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

Unique71 ?
Unique (%)100.0%

Sample

1st row055-632-0108
2nd row055-681-0630
3rd row055-633-3510
4th row055-633-4145
5th row055-681-6982
ValueCountFrequency (%)
055-632-0108 1
 
1.4%
055-633-0021 1
 
1.4%
055-633-0833 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%
055-687-9257 1
 
1.4%
055-632-3416 1
 
1.4%
055-632-7270 1
 
1.4%
Other values (61) 61
85.9%
2023-12-11T09:04:41.543514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 185
21.7%
- 142
16.7%
0 112
13.1%
6 95
11.2%
3 71
 
8.3%
8 71
 
8.3%
2 51
 
6.0%
7 47
 
5.5%
1 37
 
4.3%
4 26
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 710
83.3%
Dash Punctuation 142
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 185
26.1%
0 112
15.8%
6 95
13.4%
3 71
 
10.0%
8 71
 
10.0%
2 51
 
7.2%
7 47
 
6.6%
1 37
 
5.2%
4 26
 
3.7%
9 15
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 142
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 852
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 185
21.7%
- 142
16.7%
0 112
13.1%
6 95
11.2%
3 71
 
8.3%
8 71
 
8.3%
2 51
 
6.0%
7 47
 
5.5%
1 37
 
4.3%
4 26
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 852
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 185
21.7%
- 142
16.7%
0 112
13.1%
6 95
11.2%
3 71
 
8.3%
8 71
 
8.3%
2 51
 
6.0%
7 47
 
5.5%
1 37
 
4.3%
4 26
 
3.1%

영업자시작일
Date

Distinct72
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
Minimum1987-05-11 00:00:00
Maximum2019-10-15 00:00:00
2023-12-11T09:04:41.722262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:41.919466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size756.0 B
일반세탁업
73 
운동화전문세탁업
 
4
빨래방업
 
1

Length

Max length8
Median length5
Mean length5.1410256
Min length4

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 73
93.6%
운동화전문세탁업 4
 
5.1%
빨래방업 1
 
1.3%

Length

2023-12-11T09:04:42.102346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:04:42.253525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 73
93.6%
운동화전문세탁업 4
 
5.1%
빨래방업 1
 
1.3%

기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
2019-10-31
78 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-10-31
2nd row2019-10-31
3rd row2019-10-31
4th row2019-10-31
5th row2019-10-31

Common Values

ValueCountFrequency (%)
2019-10-31 78
100.0%

Length

2023-12-11T09:04:42.373660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:04:42.495906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-10-31 78
100.0%

Interactions

2023-12-11T09:04:36.253415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:04:42.567327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교부번호신고일자업소명업소소재지(도로명)업소소재지(지번)영업장면적소재지전화영업자시작일업태명
교부번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
신고일자1.0001.0001.0000.9941.0000.9941.0000.9991.000
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.000
업소소재지(도로명)1.0000.9941.0001.0001.0001.0001.0000.9941.000
업소소재지(지번)1.0001.0001.0001.0001.0001.0001.0001.0001.000
영업장면적1.0000.9941.0001.0001.0001.0001.0000.9940.154
소재지전화1.0001.0001.0001.0001.0001.0001.0001.0001.000
영업자시작일1.0000.9991.0000.9941.0000.9941.0001.0001.000
업태명1.0001.0001.0001.0001.0000.1541.0001.0001.000
2023-12-11T09:04:42.711600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업장면적업태명
영업장면적1.0000.053
업태명0.0531.000

Missing values

2023-12-11T09:04:36.405498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:04:36.565629image/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

교부번호신고일자업소명업소소재지(도로명)업소소재지(지번)영업장면적소재지전화영업자시작일업태명기준일
011987-05-11백모세탁소경상남도 거제시 고현로9길 4 (고현동)경상남도 거제시 고현동 818번지 20호0.0055-632-01081987-05-11일반세탁업2019-10-31
141987-05-11부산세탁소경상남도 거제시 일운면 지세포로 101경상남도 거제시 일운면 지세포리 927번지 6호0.0055-681-06301987-05-11일반세탁업2019-10-31
251987-05-11태양세탁소경상남도 거제시 거제면 읍내로2길 33경상남도 거제시 거제면 동상리 423번지 4호0.0055-633-35101987-05-11일반세탁업2019-10-31
361987-05-11거제컴퓨터세탁경상남도 거제시 거제면 읍내로2길 29-1경상남도 거제시 거제면 동상리 417번지 2호0.0055-633-41451987-05-11일반세탁업2019-10-31
481987-05-11백광컴퓨터크리닝경상남도 거제시 장승포로1길 37 (장승포동)경상남도 거제시 장승포동 455번지 14호52.8055-681-69821987-05-11일반세탁업2019-10-31
591987-05-11흑백세탁경상남도 거제시 장승로 50 (장승포동)경상남도 거제시 장승포동 596번지 2호58.25055-681-85572016-12-01일반세탁업2019-10-31
6121987-05-11(주)웰리브 옥포세탁소경상남도 거제시 서간도길 78 (옥포동)경상남도 거제시 옥포동 1670번지0.0055-687-30632019-01-16일반세탁업2019-10-31
7141987-05-11중앙컴퓨터크리닝경상남도 거제시 옥포대첩로3길 8 (옥포동)경상남도 거제시 옥포동 529번지 1호0.0055-687-02021987-05-11일반세탁업2019-10-31
8151991-09-27백조세탁소경상남도 거제시 옥포로 275 (옥포동)경상남도 거제시 옥포동 1290번지 1호46.0055-687-63711991-09-27일반세탁업2019-10-31
9161992-06-09화인세탁소경상남도 거제시 서문로3길 11 (고현동)경상남도 거제시 고현동 959번지 8호36.55055-635-75052004-02-10일반세탁업2019-10-31
교부번호신고일자업소명업소소재지(도로명)업소소재지(지번)영업장면적소재지전화영업자시작일업태명기준일
681262015-10-01한일크리닝경상남도 거제시 아주로 43-4 (아주동)경상남도 거제시 아주동 319번지 11호71.0055-681-33862019-04-10일반세탁업2019-10-31
691282016-08-30좋은세탁소경상남도 거제시 수양로 489, 1호동 1층 102호 (양정동)경상남도 거제시 양정동 929번지 2호43.82055-635-54572019-02-13일반세탁업2019-10-31
701292016-11-08와우아트크린경상남도 거제시 아주1로2길 84, 1층 (아주동)경상남도 거제시 아주동 1676번지 11호106.45055-682-57772018-12-10일반세탁업2019-10-31
711302016-11-24빨래방망이 거제본점경상남도 거제시 연초면 연사4길 75, 1층경상남도 거제시 연초면 연사리 859번지 1호178.01055-636-11822016-11-24빨래방업2019-10-31
722017-012017-06-13성재산업경상남도 거제시 능포로6길 9, 1층 (능포동)경상남도 거제시 능포동 354번지 3호168.88055-682-71002017-06-13일반세탁업2019-10-31
732017-000022017-07-17이재관세탁전문점경상남도 거제시 중곡1로 92, 한일빌딩 1층 105호 (고현동)경상남도 거제시 고현동 987번지 한일빌딩60.48055-687-48822019-10-15일반세탁업2019-10-31
742018-000012018-02-07로또세탁소경상남도 거제시 능포로 164-1, 1층 (능포동)경상남도 거제시 능포동 376번지 6호 1층59.4055-682-21212018-02-07일반세탁업2019-10-31
752018-000022018-06-04라라랜드경상남도 거제시 사등면 거제대로 5697-4, 주1동 1층경상남도 거제시 사등면 성포리 196번지 주1동318.5<NA>2019-08-13일반세탁업2019-10-31
762019-000012019-04-02삼진기업경상남도 거제시 수양로 208-2, 1층 (양정동)경상남도 거제시 양정동 416번지 3호160.74055-638-00132019-04-02일반세탁업2019-10-31
772019-000022019-04-18세탁일번지경상남도 거제시 일운면 거제대로 2533, 1층경상남도 거제시 일운면 지세포리 809번지46.91<NA>2019-04-18일반세탁업2019-10-31