Overview

Dataset statistics

Number of variables4
Number of observations94
Missing cells6
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory33.4 B

Variable types

Categorical1
Text3

Dataset

Description부산광역시북구_세탁업현황_20221216
Author부산광역시 북구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3069424

Alerts

업종명 has constant value ""Constant
소재지전화 has 6 (6.4%) missing valuesMissing
영업소 주소(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:25:19.549323
Analysis finished2023-12-10 16:25:20.032160
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
세탁업
94 

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 94
100.0%

Length

2023-12-11T01:25:20.102078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:25:20.212989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세탁업 94
100.0%

업소명
Text

Distinct91
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-11T01:25:20.468378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length4.8297872
Min length2

Characters and Unicode

Total characters454
Distinct characters139
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

Unique89 ?
Unique (%)94.7%

Sample

1st row백조세탁소
2nd row구남기계세탁소
3rd row한양
4th row부부세탁소
5th row일성
ValueCountFrequency (%)
백조세탁소 3
 
3.1%
동원세탁 2
 
2.1%
강변세탁 1
 
1.0%
동원듀크 1
 
1.0%
리버빌1차세탁소 1
 
1.0%
덕진 1
 
1.0%
동아세탁마트 1
 
1.0%
코오롱세탁 1
 
1.0%
금성세탁 1
 
1.0%
유림노르웨이숲세탁 1
 
1.0%
Other values (83) 83
86.5%
2023-12-11T01:25:20.892121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 58
 
12.8%
탁 57
 
12.6%
소 32
 
7.0%
리 10
 
2.2%
대 10
 
2.2%
크 10
 
2.2%
성 9
 
2.0%
우 8
 
1.8%
동 7
 
1.5%
백 6
 
1.3%
Other values (129) 247
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 449
98.9%
Space Separator 2
 
0.4%
Decimal Number 2
 
0.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 58
 
12.9%
탁 57
 
12.7%
소 32
 
7.1%
리 10
 
2.2%
대 10
 
2.2%
크 10
 
2.2%
성 9
 
2.0%
우 8
 
1.8%
동 7
 
1.6%
백 6
 
1.3%
Other values (126) 242
53.9%
Space Separator
ValueCountFrequency (%)
2
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 449
98.9%
Common 5
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 58
 
12.9%
탁 57
 
12.7%
소 32
 
7.1%
리 10
 
2.2%
대 10
 
2.2%
크 10
 
2.2%
성 9
 
2.0%
우 8
 
1.8%
동 7
 
1.6%
백 6
 
1.3%
Other values (126) 242
53.9%
Common
ValueCountFrequency (%)
2
40.0%
1 2
40.0%
& 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 449
98.9%
ASCII 5
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 58
 
12.9%
탁 57
 
12.7%
소 32
 
7.1%
리 10
 
2.2%
대 10
 
2.2%
크 10
 
2.2%
성 9
 
2.0%
우 8
 
1.8%
동 7
 
1.6%
백 6
 
1.3%
Other values (126) 242
53.9%
ASCII
ValueCountFrequency (%)
2
40.0%
1 2
40.0%
& 1
20.0%

영업소 주소(도로명)
Text

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-11T01:25:21.193710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length44
Mean length34.531915
Min length21

Characters and Unicode

Total characters3246
Distinct characters155
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)100.0%

Sample

1st row부산광역시 북구 낙동대로1780번길 99 (구포동, (T/B))
2nd row부산광역시 북구 백양대로1071번길 15 (구포동)
3rd row부산광역시 북구 백양대로1050번길 11-1 (구포동)
4th row부산광역시 북구 백양대로1124번길 75 (구포동)
5th row부산광역시 북구 의성로121번길 26, 1층 (덕천동)
ValueCountFrequency (%)
부산광역시 94
 
15.2%
북구 94
 
15.2%
구포동 33
 
5.3%
상가동 25
 
4.0%
1층 18
 
2.9%
화명동 17
 
2.7%
만덕동 17
 
2.7%
덕천동 13
 
2.1%
금곡동 8
 
1.3%
화명신도시로 7
 
1.1%
Other values (221) 294
47.4%
2023-12-11T01:25:21.710294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
526
 
16.2%
동 144
 
4.4%
1 142
 
4.4%
구 131
 
4.0%
시 109
 
3.4%
, 105
 
3.2%
산 100
 
3.1%
로 97
 
3.0%
북 96
 
3.0%
부 95
 
2.9%
Other values (145) 1701
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1860
57.3%
Decimal Number 544
 
16.8%
Space Separator 526
 
16.2%
Other Punctuation 108
 
3.3%
Open Punctuation 95
 
2.9%
Close Punctuation 95
 
2.9%
Dash Punctuation 9
 
0.3%
Uppercase Letter 8
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 144
 
7.7%
구 131
 
7.0%
시 109
 
5.9%
산 100
 
5.4%
로 97
 
5.2%
북 96
 
5.2%
부 95
 
5.1%
광 94
 
5.1%
역 94
 
5.1%
덕 61
 
3.3%
Other values (122) 839
45.1%
Decimal Number
ValueCountFrequency (%)
1 142
26.1%
2 88
16.2%
0 77
14.2%
4 48
 
8.8%
3 48
 
8.8%
6 35
 
6.4%
5 32
 
5.9%
7 30
 
5.5%
9 26
 
4.8%
8 18
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 105
97.2%
@ 1
 
0.9%
· 1
 
0.9%
/ 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
B 3
37.5%
T 2
25.0%
A 2
25.0%
R 1
 
12.5%
Space Separator
ValueCountFrequency (%)
526
100.0%
Open Punctuation
ValueCountFrequency (%)
( 95
100.0%
Close Punctuation
ValueCountFrequency (%)
) 95
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1860
57.3%
Common 1378
42.5%
Latin 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 144
 
7.7%
구 131
 
7.0%
시 109
 
5.9%
산 100
 
5.4%
로 97
 
5.2%
북 96
 
5.2%
부 95
 
5.1%
광 94
 
5.1%
역 94
 
5.1%
덕 61
 
3.3%
Other values (122) 839
45.1%
Common
ValueCountFrequency (%)
526
38.2%
1 142
 
10.3%
, 105
 
7.6%
( 95
 
6.9%
) 95
 
6.9%
2 88
 
6.4%
0 77
 
5.6%
4 48
 
3.5%
3 48
 
3.5%
6 35
 
2.5%
Other values (9) 119
 
8.6%
Latin
ValueCountFrequency (%)
B 3
37.5%
T 2
25.0%
A 2
25.0%
R 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1860
57.3%
ASCII 1385
42.7%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
526
38.0%
1 142
 
10.3%
, 105
 
7.6%
( 95
 
6.9%
) 95
 
6.9%
2 88
 
6.4%
0 77
 
5.6%
4 48
 
3.5%
3 48
 
3.5%
6 35
 
2.5%
Other values (12) 126
 
9.1%
Hangul
ValueCountFrequency (%)
동 144
 
7.7%
구 131
 
7.0%
시 109
 
5.9%
산 100
 
5.4%
로 97
 
5.2%
북 96
 
5.2%
부 95
 
5.1%
광 94
 
5.1%
역 94
 
5.1%
덕 61
 
3.3%
Other values (122) 839
45.1%
None
ValueCountFrequency (%)
· 1
100.0%

소재지전화
Text

MISSING 

Distinct88
Distinct (%)100.0%
Missing6
Missing (%)6.4%
Memory size884.0 B
2023-12-11T01:25:21.971923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1056
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

Unique88 ?
Unique (%)100.0%

Sample

1st row051-334-5413
2nd row051-332-7027
3rd row051-343-8577
4th row051-332-2969
5th row051-333-7356
ValueCountFrequency (%)
051-332-7027 1
 
1.1%
051-343-8577 1
 
1.1%
051-342-5576 1
 
1.1%
051-362-0562 1
 
1.1%
051-333-6769 1
 
1.1%
051-341-3989 1
 
1.1%
051-363-5908 1
 
1.1%
051-337-8060 1
 
1.1%
051-343-3334 1
 
1.1%
051-361-0606 1
 
1.1%
Other values (78) 78
88.6%
2023-12-11T01:25:22.413738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 209
19.8%
- 176
16.7%
5 140
13.3%
0 135
12.8%
1 135
12.8%
6 57
 
5.4%
2 49
 
4.6%
7 45
 
4.3%
4 39
 
3.7%
8 39
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 880
83.3%
Dash Punctuation 176
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 209
23.8%
5 140
15.9%
0 135
15.3%
1 135
15.3%
6 57
 
6.5%
2 49
 
5.6%
7 45
 
5.1%
4 39
 
4.4%
8 39
 
4.4%
9 32
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1056
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 209
19.8%
- 176
16.7%
5 140
13.3%
0 135
12.8%
1 135
12.8%
6 57
 
5.4%
2 49
 
4.6%
7 45
 
4.3%
4 39
 
3.7%
8 39
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1056
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 209
19.8%
- 176
16.7%
5 140
13.3%
0 135
12.8%
1 135
12.8%
6 57
 
5.4%
2 49
 
4.6%
7 45
 
4.3%
4 39
 
3.7%
8 39
 
3.7%

Correlations

2023-12-11T01:25:22.520026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명영업소 주소(도로명)소재지전화
업소명1.0001.0001.000
영업소 주소(도로명)1.0001.0001.000
소재지전화1.0001.0001.000

Missing values

2023-12-11T01:25:19.891133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:25:19.993096image/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

업종명업소명영업소 주소(도로명)소재지전화
0세탁업백조세탁소부산광역시 북구 낙동대로1780번길 99 (구포동, (T/B))051-334-5413
1세탁업구남기계세탁소부산광역시 북구 백양대로1071번길 15 (구포동)051-332-7027
2세탁업한양부산광역시 북구 백양대로1050번길 11-1 (구포동)051-343-8577
3세탁업부부세탁소부산광역시 북구 백양대로1124번길 75 (구포동)051-332-2969
4세탁업일성부산광역시 북구 의성로121번길 26, 1층 (덕천동)051-333-7356
5세탁업우성부산광역시 북구 금곡대로20번길 39 (덕천동)051-333-1235
6세탁업부국세탁소부산광역시 북구 만덕대로27번길 14 (덕천동)051-333-6183
7세탁업날개부산광역시 북구 만덕1로 35 (만덕동)051-333-7804
8세탁업우리세탁소부산광역시 북구 만덕1로 6 (만덕동)051-332-8705
9세탁업광명사부산광역시 북구 상리로 37 (만덕동)051-332-9300
업종명업소명영업소 주소(도로명)소재지전화
84세탁업하얀기쁨세탁소부산광역시 북구 만덕대로39번길 52, 1층 (덕천동)051-342-5539
85세탁업빛차린운동화세탁부산광역시 북구 백양대로1015번길 44, 1층 (구포동, 성우로얄빌)051-338-7989
86세탁업럭키세탁소부산광역시 북구 덕천로234번길 24, 럭키아파트 상가동 302호 (만덕동)051-342-4700
87세탁업시민세탁소부산광역시 북구 낙동대로1762번가길 6, 1층 (구포동)<NA>
88세탁업명품세탁소부산광역시 북구 모분재로149번길 22, 1층 (구포동)<NA>
89세탁업세탁1번지부산광역시 북구 시랑로 129, 1층 (구포동)<NA>
90세탁업경남컴퓨터세탁부산광역시 북구 양달로 20, 경남아너스빌 상가동 1층 101호 (화명동)051-362-3868
91세탁업오스카부산광역시 북구 금곡대로616번길 98, 1층 (금곡동)051-361-9129
92세탁업하얀기쁨부산광역시 북구 덕천로 166, 1층 (덕천동)<NA>
93세탁업백설세탁부산광역시 북구 팽나무로 3, 1층 (구포동)<NA>