Overview

Dataset statistics

Number of variables4
Number of observations60
Missing cells137
Missing cells (%)57.1%
Duplicate rows1
Duplicate rows (%)1.7%
Total size in memory2.0 KiB
Average record size in memory34.2 B

Variable types

Text3
DateTime1

Dataset

Description부산광역시_기장군_세탁업현황_20230613
Author부산광역시 기장군
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3072189

Alerts

Dataset has 1 (1.7%) duplicate rowsDuplicates
업소명 has 34 (56.7%) missing valuesMissing
영업소 주소(도로명) has 34 (56.7%) missing valuesMissing
소재지전화 has 35 (58.3%) missing valuesMissing
영업자시작일 has 34 (56.7%) missing valuesMissing

Reproduction

Analysis started2023-12-10 16:01:44.869736
Analysis finished2023-12-10 16:01:45.871492
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing34
Missing (%)56.7%
Memory size612.0 B
2023-12-11T01:01:46.073526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14
Mean length5.9230769
Min length3

Characters and Unicode

Total characters154
Distinct characters70
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row동해탕
2nd row대한탕
3rd row새기장탕
4th row월천탕
5th row덕발약수탕
ValueCountFrequency (%)
대한탕 1
 
3.0%
길천해수탕 1
 
3.0%
하이리페움 1
 
3.0%
동부산스포츠센터 1
 
3.0%
주)오션시티 1
 
3.0%
월내탕 1
 
3.0%
월내새마을회 1
 
3.0%
동부산온천 1
 
3.0%
워터하우스 1
 
3.0%
사우나(힐튼 1
 
3.0%
Other values (23) 23
69.7%
2023-12-11T01:01:46.675683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 17
 
11.0%
7
 
4.5%
천 7
 
4.5%
대 5
 
3.2%
우 4
 
2.6%
수 4
 
2.6%
나 3
 
1.9%
산 3
 
1.9%
장 3
 
1.9%
온 3
 
1.9%
Other values (60) 98
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 141
91.6%
Space Separator 7
 
4.5%
Open Punctuation 3
 
1.9%
Close Punctuation 3
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 17
 
12.1%
천 7
 
5.0%
대 5
 
3.5%
우 4
 
2.8%
수 4
 
2.8%
나 3
 
2.1%
산 3
 
2.1%
장 3
 
2.1%
온 3
 
2.1%
해 3
 
2.1%
Other values (57) 89
63.1%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 140
90.9%
Common 13
 
8.4%
Han 1
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 17
 
12.1%
천 7
 
5.0%
대 5
 
3.6%
우 4
 
2.9%
수 4
 
2.9%
나 3
 
2.1%
산 3
 
2.1%
장 3
 
2.1%
온 3
 
2.1%
해 3
 
2.1%
Other values (56) 88
62.9%
Common
ValueCountFrequency (%)
7
53.8%
( 3
23.1%
) 3
23.1%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 140
90.9%
ASCII 13
 
8.4%
CJK 1
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 17
 
12.1%
천 7
 
5.0%
대 5
 
3.6%
우 4
 
2.9%
수 4
 
2.9%
나 3
 
2.1%
산 3
 
2.1%
장 3
 
2.1%
온 3
 
2.1%
해 3
 
2.1%
Other values (56) 88
62.9%
ASCII
ValueCountFrequency (%)
7
53.8%
( 3
23.1%
) 3
23.1%
CJK
ValueCountFrequency (%)
愛 1
100.0%

영업소 주소(도로명)
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing34
Missing (%)56.7%
Memory size612.0 B
2023-12-11T01:01:47.015934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length25.769231
Min length20

Characters and Unicode

Total characters670
Distinct characters72
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row부산광역시 기장군 기장읍 기장해안로 585-1
2nd row부산광역시 기장군 장안읍 장곡길 197-1
3rd row부산광역시 기장군 기장읍 차성남로 57
4th row부산광역시 기장군 장안읍 월내해안4길 8
5th row부산광역시 기장군 기장읍 기장대로 504-3
ValueCountFrequency (%)
부산광역시 26
18.1%
기장군 26
18.1%
기장읍 12
 
8.3%
장안읍 5
 
3.5%
정관읍 4
 
2.8%
일광읍 3
 
2.1%
기장해안로 3
 
2.1%
지하1층 2
 
1.4%
268-32 2
 
1.4%
7 2
 
1.4%
Other values (57) 59
41.0%
2023-12-11T01:01:47.587582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
118
17.6%
장 50
 
7.5%
기 42
 
6.3%
광 30
 
4.5%
부 27
 
4.0%
산 27
 
4.0%
역 27
 
4.0%
시 26
 
3.9%
군 26
 
3.9%
읍 24
 
3.6%
Other values (62) 273
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 422
63.0%
Space Separator 118
 
17.6%
Decimal Number 103
 
15.4%
Other Punctuation 11
 
1.6%
Dash Punctuation 7
 
1.0%
Math Symbol 3
 
0.4%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%
Uppercase Letter 1
 
0.1%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 50
11.8%
기 42
 
10.0%
광 30
 
7.1%
부 27
 
6.4%
산 27
 
6.4%
역 27
 
6.4%
시 26
 
6.2%
군 26
 
6.2%
읍 24
 
5.7%
로 19
 
4.5%
Other values (44) 124
29.4%
Decimal Number
ValueCountFrequency (%)
1 19
18.4%
3 15
14.6%
2 13
12.6%
4 11
10.7%
8 10
9.7%
5 9
8.7%
6 9
8.7%
7 8
7.8%
0 7
 
6.8%
9 2
 
1.9%
Space Separator
ValueCountFrequency (%)
118
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 422
63.0%
Common 246
36.7%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 50
11.8%
기 42
 
10.0%
광 30
 
7.1%
부 27
 
6.4%
산 27
 
6.4%
역 27
 
6.4%
시 26
 
6.2%
군 26
 
6.2%
읍 24
 
5.7%
로 19
 
4.5%
Other values (44) 124
29.4%
Common
ValueCountFrequency (%)
118
48.0%
1 19
 
7.7%
3 15
 
6.1%
2 13
 
5.3%
, 11
 
4.5%
4 11
 
4.5%
8 10
 
4.1%
5 9
 
3.7%
6 9
 
3.7%
7 8
 
3.3%
Other values (6) 23
 
9.3%
Latin
ValueCountFrequency (%)
B 1
50.0%
Ⅱ 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 422
63.0%
ASCII 247
36.9%
Number Forms 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
118
47.8%
1 19
 
7.7%
3 15
 
6.1%
2 13
 
5.3%
, 11
 
4.5%
4 11
 
4.5%
8 10
 
4.0%
5 9
 
3.6%
6 9
 
3.6%
7 8
 
3.2%
Other values (7) 24
 
9.7%
Hangul
ValueCountFrequency (%)
장 50
11.8%
기 42
 
10.0%
광 30
 
7.1%
부 27
 
6.4%
산 27
 
6.4%
역 27
 
6.4%
시 26
 
6.2%
군 26
 
6.2%
읍 24
 
5.7%
로 19
 
4.5%
Other values (44) 124
29.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지전화
Text

MISSING 

Distinct25
Distinct (%)100.0%
Missing35
Missing (%)58.3%
Memory size612.0 B
2023-12-11T01:01:47.838106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters350
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

Unique25 ?
Unique (%)100.0%

Sample

1st row 051- 721-3782
2nd row 051- 727-0124
3rd row 051- 721-2015
4th row 051- 727-2155
5th row 051- 721-3779
ValueCountFrequency (%)
051 25
39.1%
727 4
 
6.2%
728 2
 
3.1%
722 1
 
1.6%
5200 1
 
1.6%
723 1
 
1.6%
2900 1
 
1.6%
7006 1
 
1.6%
3505 1
 
1.6%
1066 1
 
1.6%
Other values (26) 26
40.6%
2023-12-11T01:01:48.324453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50
14.3%
- 50
14.3%
0 42
12.0%
1 41
11.7%
7 40
11.4%
2 40
11.4%
5 39
11.1%
8 12
 
3.4%
9 11
 
3.1%
4 10
 
2.9%
Other values (2) 15
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 250
71.4%
Space Separator 50
 
14.3%
Dash Punctuation 50
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 42
16.8%
1 41
16.4%
7 40
16.0%
2 40
16.0%
5 39
15.6%
8 12
 
4.8%
9 11
 
4.4%
4 10
 
4.0%
3 8
 
3.2%
6 7
 
2.8%
Space Separator
ValueCountFrequency (%)
50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 350
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
50
14.3%
- 50
14.3%
0 42
12.0%
1 41
11.7%
7 40
11.4%
2 40
11.4%
5 39
11.1%
8 12
 
3.4%
9 11
 
3.1%
4 10
 
2.9%
Other values (2) 15
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50
14.3%
- 50
14.3%
0 42
12.0%
1 41
11.7%
7 40
11.4%
2 40
11.4%
5 39
11.1%
8 12
 
3.4%
9 11
 
3.1%
4 10
 
2.9%
Other values (2) 15
 
4.3%

영업자시작일
Date

MISSING 

Distinct26
Distinct (%)100.0%
Missing34
Missing (%)56.7%
Memory size612.0 B
Minimum1976-12-03 00:00:00
Maximum2023-05-31 00:00:00
2023-12-11T01:01:48.511499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:01:48.702016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

Correlations

2023-12-11T01:01:48.845114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명영업소 주소(도로명)소재지전화영업자시작일
업소명1.0001.0001.0001.000
영업소 주소(도로명)1.0001.0001.0001.000
소재지전화1.0001.0001.0001.000
영업자시작일1.0001.0001.0001.000

Missing values

2023-12-11T01:01:45.491180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:01:45.632298image/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.
2023-12-11T01:01:45.780324image/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

업소명영업소 주소(도로명)소재지전화영업자시작일
0동해탕부산광역시 기장군 기장읍 기장해안로 585-1051- 721-37821976-12-03
1대한탕부산광역시 기장군 장안읍 장곡길 197-1051- 727-01242022-02-09
2새기장탕부산광역시 기장군 기장읍 차성남로 57051- 721-20152004-08-11
3월천탕부산광역시 기장군 장안읍 월내해안4길 8051- 727-21551987-04-25
4덕발약수탕부산광역시 기장군 기장읍 기장대로 504-3051- 721-37792006-06-19
5대성탕부산광역시 기장군 기장읍 차성로436번길 14051 -721 -07822011-10-18
6영일탕부산광역시 기장군 기장읍 차성로322번길 27051- 722-42842011-07-01
7유성탕부산광역시 기장군 일광읍 일역길 86051- 722-77121995-07-27
8궁전목욕탕부산광역시 기장군 기장읍 차성서로101번길 1051- 721-12352022-07-05
9대라탕부산광역시 기장군 기장읍 대청로21번길 16051- 723-09792006-02-23
업소명영업소 주소(도로명)소재지전화영업자시작일
50<NA><NA><NA><NA>
51<NA><NA><NA><NA>
52<NA><NA><NA><NA>
53<NA><NA><NA><NA>
54<NA><NA><NA><NA>
55<NA><NA><NA><NA>
56<NA><NA><NA><NA>
57<NA><NA><NA><NA>
58<NA><NA><NA><NA>
59<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

업소명영업소 주소(도로명)소재지전화영업자시작일# duplicates
0<NA><NA><NA><NA>34