Overview

Dataset statistics

Number of variables4
Number of observations231
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.4%
Total size in memory7.3 KiB
Average record size in memory32.6 B

Variable types

Categorical2
Text2

Dataset

Description부산광역시금정구_공중서비스평가정보_20230509
Author부산광역시 금정구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3055402

Alerts

Dataset has 1 (0.4%) duplicate rowsDuplicates

Reproduction

Analysis started2024-04-21 11:21:14.021083
Analysis finished2024-04-21 11:21:14.659651
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

평가구분
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
백색(일반관리)
106 
황색(우수)
65 
녹색(최우수)
60 

Length

Max length8
Median length7
Mean length7.1774892
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row녹색(최우수)
2nd row녹색(최우수)
3rd row녹색(최우수)
4th row녹색(최우수)
5th row녹색(최우수)

Common Values

ValueCountFrequency (%)
백색(일반관리) 106
45.9%
황색(우수) 65
28.1%
녹색(최우수) 60
26.0%

Length

2024-04-21T20:21:14.799394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:21:15.027768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
백색(일반관리 106
45.9%
황색(우수 65
28.1%
녹색(최우수 60
26.0%

업종
Categorical

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
세탁업
122 
숙박업(일반)
55 
목욕장업
44 
숙박업(생활)
 
10

Length

Max length7
Median length3
Mean length4.3160173
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(생활)

Common Values

ValueCountFrequency (%)
세탁업 122
52.8%
숙박업(일반) 55
23.8%
목욕장업 44
 
19.0%
숙박업(생활) 10
 
4.3%

Length

2024-04-21T20:21:15.407896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:21:15.753629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세탁업 122
52.8%
숙박업(일반 55
23.8%
목욕장업 44
 
19.0%
숙박업(생활 10
 
4.3%

업소명
Text

Distinct224
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-21T20:21:16.734765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length10
Mean length4.2597403
Min length1

Characters and Unicode

Total characters984
Distinct characters242
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

Unique218 ?
Unique (%)94.4%

Sample

1st row브라운도트호텔
2nd row버튼호텔 구서역점
3rd row호텔G&G
4th row로즈베이2
5th row로즈베이호텔
ValueCountFrequency (%)
제일 3
 
1.3%
대성사 2
 
0.8%
미화 2
 
0.8%
모모 2
 
0.8%
태양 2
 
0.8%
백성 2
 
0.8%
부산 2
 
0.8%
예가명품세탁 1
 
0.4%
한백 1
 
0.4%
뉴그린세탁소 1
 
0.4%
Other values (221) 221
92.5%
2024-04-21T20:21:17.919764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 46
 
4.7%
탁 43
 
4.4%
탕 33
 
3.4%
텔 30
 
3.0%
모 22
 
2.2%
사 22
 
2.2%
크 19
 
1.9%
소 19
 
1.9%
장 16
 
1.6%
이 15
 
1.5%
Other values (232) 719
73.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 923
93.8%
Uppercase Letter 27
 
2.7%
Space Separator 9
 
0.9%
Lowercase Letter 7
 
0.7%
Close Punctuation 6
 
0.6%
Open Punctuation 6
 
0.6%
Decimal Number 4
 
0.4%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 46
 
5.0%
탁 43
 
4.7%
탕 33
 
3.6%
텔 30
 
3.3%
모 22
 
2.4%
사 22
 
2.4%
크 19
 
2.1%
소 19
 
2.1%
장 16
 
1.7%
이 15
 
1.6%
Other values (204) 658
71.3%
Uppercase Letter
ValueCountFrequency (%)
O 3
11.1%
T 2
 
7.4%
H 2
 
7.4%
M 2
 
7.4%
L 2
 
7.4%
K 2
 
7.4%
N 2
 
7.4%
S 2
 
7.4%
Y 2
 
7.4%
G 2
 
7.4%
Other values (6) 6
22.2%
Lowercase Letter
ValueCountFrequency (%)
o 4
57.1%
s 1
 
14.3%
p 1
 
14.3%
n 1
 
14.3%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 1
25.0%
5 1
25.0%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 923
93.8%
Latin 34
 
3.5%
Common 27
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 46
 
5.0%
탁 43
 
4.7%
탕 33
 
3.6%
텔 30
 
3.3%
모 22
 
2.4%
사 22
 
2.4%
크 19
 
2.1%
소 19
 
2.1%
장 16
 
1.7%
이 15
 
1.6%
Other values (204) 658
71.3%
Latin
ValueCountFrequency (%)
o 4
 
11.8%
O 3
 
8.8%
T 2
 
5.9%
H 2
 
5.9%
M 2
 
5.9%
L 2
 
5.9%
K 2
 
5.9%
N 2
 
5.9%
S 2
 
5.9%
Y 2
 
5.9%
Other values (10) 11
32.4%
Common
ValueCountFrequency (%)
9
33.3%
) 6
22.2%
( 6
22.2%
2 2
 
7.4%
1 1
 
3.7%
& 1
 
3.7%
5 1
 
3.7%
. 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 923
93.8%
ASCII 61
 
6.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 46
 
5.0%
탁 43
 
4.7%
탕 33
 
3.6%
텔 30
 
3.3%
모 22
 
2.4%
사 22
 
2.4%
크 19
 
2.1%
소 19
 
2.1%
장 16
 
1.7%
이 15
 
1.6%
Other values (204) 658
71.3%
ASCII
ValueCountFrequency (%)
9
 
14.8%
) 6
 
9.8%
( 6
 
9.8%
o 4
 
6.6%
O 3
 
4.9%
T 2
 
3.3%
H 2
 
3.3%
M 2
 
3.3%
L 2
 
3.3%
K 2
 
3.3%
Other values (18) 23
37.7%

소재지(도로명)
Text

Distinct225
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-21T20:21:19.019562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length43
Mean length26.822511
Min length10

Characters and Unicode

Total characters6196
Distinct characters130
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique219 ?
Unique (%)94.8%

Sample

1st row부산광역시 금정구 중앙대로 1833 (구서동)
2nd row부산광역시 금정구 금정로237번길 28 (구서동)
3rd row부산광역시 금정구 금정로 242 (구서동)
4th row부산광역시 금정구 금정로237번길 36 (구서동)
5th row부산광역시 금정구 금정로237번길 36 (구서동)
ValueCountFrequency (%)
부산광역시 231
18.9%
금정구 231
18.9%
서동 72
 
5.9%
구서동 37
 
3.0%
장전동 37
 
3.0%
부곡동 36
 
2.9%
1층 23
 
1.9%
남산동 22
 
1.8%
금강로 12
 
1.0%
금사로 11
 
0.9%
Other values (311) 512
41.8%
2024-04-21T20:21:20.637430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
999
 
16.1%
동 297
 
4.8%
부 296
 
4.8%
금 293
 
4.7%
구 275
 
4.4%
산 264
 
4.3%
정 243
 
3.9%
1 241
 
3.9%
시 234
 
3.8%
역 231
 
3.7%
Other values (120) 2823
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3665
59.2%
Space Separator 999
 
16.1%
Decimal Number 967
 
15.6%
Open Punctuation 229
 
3.7%
Close Punctuation 229
 
3.7%
Other Punctuation 56
 
0.9%
Dash Punctuation 51
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 297
 
8.1%
부 296
 
8.1%
금 293
 
8.0%
구 275
 
7.5%
산 264
 
7.2%
정 243
 
6.6%
시 234
 
6.4%
역 231
 
6.3%
광 231
 
6.3%
로 225
 
6.1%
Other values (105) 1076
29.4%
Decimal Number
ValueCountFrequency (%)
1 241
24.9%
2 134
13.9%
3 96
 
9.9%
4 87
 
9.0%
5 83
 
8.6%
6 69
 
7.1%
9 68
 
7.0%
0 68
 
7.0%
7 63
 
6.5%
8 58
 
6.0%
Space Separator
ValueCountFrequency (%)
999
100.0%
Open Punctuation
ValueCountFrequency (%)
( 229
100.0%
Close Punctuation
ValueCountFrequency (%)
) 229
100.0%
Other Punctuation
ValueCountFrequency (%)
, 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3665
59.2%
Common 2531
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 297
 
8.1%
부 296
 
8.1%
금 293
 
8.0%
구 275
 
7.5%
산 264
 
7.2%
정 243
 
6.6%
시 234
 
6.4%
역 231
 
6.3%
광 231
 
6.3%
로 225
 
6.1%
Other values (105) 1076
29.4%
Common
ValueCountFrequency (%)
999
39.5%
1 241
 
9.5%
( 229
 
9.0%
) 229
 
9.0%
2 134
 
5.3%
3 96
 
3.8%
4 87
 
3.4%
5 83
 
3.3%
6 69
 
2.7%
9 68
 
2.7%
Other values (5) 296
 
11.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3665
59.2%
ASCII 2531
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
999
39.5%
1 241
 
9.5%
( 229
 
9.0%
) 229
 
9.0%
2 134
 
5.3%
3 96
 
3.8%
4 87
 
3.4%
5 83
 
3.3%
6 69
 
2.7%
9 68
 
2.7%
Other values (5) 296
 
11.7%
Hangul
ValueCountFrequency (%)
동 297
 
8.1%
부 296
 
8.1%
금 293
 
8.0%
구 275
 
7.5%
산 264
 
7.2%
정 243
 
6.6%
시 234
 
6.4%
역 231
 
6.3%
광 231
 
6.3%
로 225
 
6.1%
Other values (105) 1076
29.4%

Correlations

2024-04-21T20:21:20.791452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평가구분업종
평가구분1.0000.229
업종0.2291.000
2024-04-21T20:21:20.930862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평가구분업종
평가구분1.0000.217
업종0.2171.000
2024-04-21T20:21:21.066453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평가구분업종
평가구분1.0000.217
업종0.2171.000

Missing values

2024-04-21T20:21:14.453366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T20:21:14.600734image/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

평가구분업종업소명소재지(도로명)
0녹색(최우수)숙박업(일반)브라운도트호텔부산광역시 금정구 중앙대로 1833 (구서동)
1녹색(최우수)숙박업(일반)버튼호텔 구서역점부산광역시 금정구 금정로237번길 28 (구서동)
2녹색(최우수)숙박업(일반)호텔G&G부산광역시 금정구 금정로 242 (구서동)
3녹색(최우수)숙박업(일반)로즈베이2부산광역시 금정구 금정로237번길 36 (구서동)
4녹색(최우수)숙박업(생활)로즈베이호텔부산광역시 금정구 금정로237번길 36 (구서동)
5녹색(최우수)숙박업(일반)호텔 프렌치코드부산광역시 금정구 중앙대로1805번길 16 (구서동)
6녹색(최우수)숙박업(일반)호텔캔들부산광역시 금정구 금정로231번길 8 (구서동)
7녹색(최우수)숙박업(일반)디웰호텔부산광역시 금정구 중앙대로1929번길 8-16, 그랜드모텔 (구서동)
8녹색(최우수)숙박업(일반)브이원모텔부산광역시 금정구 공단로 15 (금사동)
9녹색(최우수)숙박업(일반)No.25호텔부산광역시 금정구 서동로 193-11 (서동)
평가구분업종업소명소재지(도로명)
221백색(일반관리)세탁업새신처럼부산광역시 금정구 구서중앙로15번길 5, 1층 (구서동)
222백색(일반관리)세탁업유림세탁부산광역시 금정구 중앙대로 1799 (구서동)
223백색(일반관리)세탁업유림맑은세탁부산광역시 금정구 중앙대로1793번길 40, 1층 (구서동)
224백색(일반관리)세탁업영세탁소부산광역시 금정구 두실로45번길 46 (구서동,(선경3차상가114호))
225백색(일반관리)세탁업청룡사부산광역시 금정구 청룡로43번길 54 (남산동)
226백색(일반관리)세탁업현대부산광역시 금정구
227백색(일반관리)세탁업세련사부산광역시 금정구 남산로37번길 49, 1층 (남산동)
228백색(일반관리)세탁업신안세탁부산광역시 금정구 학산로 11, 1층 (남산동)
229백색(일반관리)세탁업지오산업부산광역시 금정구 청룡로 65, 지하1층 (남산동)
230백색(일반관리)세탁업그린벨리부산광역시 금정구 구서동 203-19

Duplicate rows

Most frequently occurring

평가구분업종업소명소재지(도로명)# duplicates
0녹색(최우수)세탁업대성사부산광역시 금정구 금정로91번길 8 (장전동)2