Overview

Dataset statistics

Number of variables4
Number of observations236
Missing cells106
Missing cells (%)11.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.5 KiB
Average record size in memory32.6 B

Variable types

Categorical1
Text3

Dataset

Description부산광역시 연제구 관내에 신고된 신고 체육시설업 업체들에 대한 업종, 상호명, 시설주소(도로명) 등의 데이터 현황입니다.
Author부산광역시 연제구
URLhttps://www.data.go.kr/data/3040712/fileData.do

Alerts

시설전화번호 has 104 (44.1%) missing valuesMissing

Reproduction

Analysis started2024-04-29 23:20:26.041576
Analysis finished2024-04-29 23:20:26.905787
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

Distinct9
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
체력단련장업
69 
체육도장업
59 
당구장업
46 
골프연습장업
37 
가상체험 체육시설업
10 
Other values (4)
15 

Length

Max length10
Median length6
Mean length5.4533898
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row수영장업
2nd row수영장업
3rd row체육도장업
4th row체육도장업
5th row체육도장업

Common Values

ValueCountFrequency (%)
체력단련장업 69
29.2%
체육도장업 59
25.0%
당구장업 46
19.5%
골프연습장업 37
15.7%
가상체험 체육시설업 10
 
4.2%
체육교습업 10
 
4.2%
수영장업 2
 
0.8%
무도학원업 2
 
0.8%
<NA> 1
 
0.4%

Length

2024-04-30T08:20:26.976261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T08:20:27.101028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 69
28.0%
체육도장업 59
24.0%
당구장업 46
18.7%
골프연습장업 37
15.0%
가상체험 10
 
4.1%
체육시설업 10
 
4.1%
체육교습업 10
 
4.1%
수영장업 2
 
0.8%
무도학원업 2
 
0.8%
na 1
 
0.4%

상호
Text

Distinct232
Distinct (%)98.7%
Missing1
Missing (%)0.4%
Memory size2.0 KiB
2024-04-30T08:20:27.374986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length17
Mean length7.506383
Min length1

Characters and Unicode

Total characters1764
Distinct characters310
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

Unique230 ?
Unique (%)97.9%

Sample

1st row대영 스포렉스
2nd row더 퍼스트 수영장
3rd row송무인 동명태권도
4th row경동태권도
5th row새화랑체육도장
ValueCountFrequency (%)
당구클럽 6
 
1.7%
짐 6
 
1.7%
피트니스 6
 
1.7%
연산점 5
 
1.4%
태권도 4
 
1.1%
대영 3
 
0.9%
시청점 3
 
0.9%
골프 3
 
0.9%
합기도 3
 
0.9%
휘트니스 3
 
0.9%
Other values (285) 307
88.0%
2024-04-30T08:20:27.806764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
114
 
6.5%
스 89
 
5.0%
프 50
 
2.8%
장 48
 
2.7%
구 44
 
2.5%
당 42
 
2.4%
골 41
 
2.3%
도 41
 
2.3%
연 38
 
2.2%
트 30
 
1.7%
Other values (300) 1227
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1504
85.3%
Space Separator 114
 
6.5%
Uppercase Letter 83
 
4.7%
Lowercase Letter 15
 
0.9%
Close Punctuation 14
 
0.8%
Open Punctuation 14
 
0.8%
Other Punctuation 9
 
0.5%
Decimal Number 9
 
0.5%
Letter Number 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 89
 
5.9%
프 50
 
3.3%
장 48
 
3.2%
구 44
 
2.9%
당 42
 
2.8%
골 41
 
2.7%
도 41
 
2.7%
연 38
 
2.5%
트 30
 
2.0%
권 29
 
1.9%
Other values (255) 1052
69.9%
Uppercase Letter
ValueCountFrequency (%)
A 10
12.0%
M 9
10.8%
T 7
 
8.4%
K 7
 
8.4%
S 6
 
7.2%
B 6
 
7.2%
P 5
 
6.0%
G 5
 
6.0%
Y 4
 
4.8%
N 4
 
4.8%
Other values (9) 20
24.1%
Lowercase Letter
ValueCountFrequency (%)
i 3
20.0%
r 2
13.3%
a 2
13.3%
l 2
13.3%
s 1
 
6.7%
d 1
 
6.7%
b 1
 
6.7%
k 1
 
6.7%
t 1
 
6.7%
f 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 2
22.2%
3 1
11.1%
8 1
11.1%
9 1
11.1%
0 1
11.1%
1 1
11.1%
4 1
11.1%
7 1
11.1%
Other Punctuation
ValueCountFrequency (%)
. 6
66.7%
& 2
 
22.2%
: 1
 
11.1%
Space Separator
ValueCountFrequency (%)
114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1504
85.3%
Common 161
 
9.1%
Latin 99
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 89
 
5.9%
프 50
 
3.3%
장 48
 
3.2%
구 44
 
2.9%
당 42
 
2.8%
골 41
 
2.7%
도 41
 
2.7%
연 38
 
2.5%
트 30
 
2.0%
권 29
 
1.9%
Other values (255) 1052
69.9%
Latin
ValueCountFrequency (%)
A 10
 
10.1%
M 9
 
9.1%
T 7
 
7.1%
K 7
 
7.1%
S 6
 
6.1%
B 6
 
6.1%
P 5
 
5.1%
G 5
 
5.1%
Y 4
 
4.0%
N 4
 
4.0%
Other values (20) 36
36.4%
Common
ValueCountFrequency (%)
114
70.8%
) 14
 
8.7%
( 14
 
8.7%
. 6
 
3.7%
2 2
 
1.2%
& 2
 
1.2%
3 1
 
0.6%
8 1
 
0.6%
9 1
 
0.6%
0 1
 
0.6%
Other values (5) 5
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1504
85.3%
ASCII 259
 
14.7%
Number Forms 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
114
44.0%
) 14
 
5.4%
( 14
 
5.4%
A 10
 
3.9%
M 9
 
3.5%
T 7
 
2.7%
K 7
 
2.7%
. 6
 
2.3%
S 6
 
2.3%
B 6
 
2.3%
Other values (34) 66
25.5%
Hangul
ValueCountFrequency (%)
스 89
 
5.9%
프 50
 
3.3%
장 48
 
3.2%
구 44
 
2.9%
당 42
 
2.8%
골 41
 
2.7%
도 41
 
2.7%
연 38
 
2.5%
트 30
 
2.0%
권 29
 
1.9%
Other values (255) 1052
69.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

시설주소(도로명)
Text

Distinct230
Distinct (%)97.9%
Missing1
Missing (%)0.4%
Memory size2.0 KiB
2024-04-30T08:20:28.052718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length43
Mean length30.140426
Min length21

Characters and Unicode

Total characters7083
Distinct characters186
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

Unique225 ?
Unique (%)95.7%

Sample

1st row부산광역시 연제구 연안로 25 (연산동)
2nd row부산광역시 연제구 거제천로87번길 30, 지하1층 (거제동, 연제그린타워)
3rd row부산광역시 연제구 연제로8번길 54 (연산동)
4th row부산광역시 연제구 세병로 16 (연산동)
5th row부산광역시 연제구 쌍미천로 11 (연산동)
ValueCountFrequency (%)
부산광역시 235
16.6%
연제구 235
16.6%
연산동 177
 
12.5%
거제동 60
 
4.2%
2층 30
 
2.1%
3층 30
 
2.1%
과정로 27
 
1.9%
4층 19
 
1.3%
지하1층 16
 
1.1%
중앙대로 15
 
1.1%
Other values (327) 575
40.5%
2024-04-30T08:20:28.440967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1184
 
16.7%
연 436
 
6.2%
산 422
 
6.0%
제 327
 
4.6%
시 257
 
3.6%
동 251
 
3.5%
부 238
 
3.4%
광 236
 
3.3%
역 236
 
3.3%
구 235
 
3.3%
Other values (176) 3261
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4219
59.6%
Space Separator 1184
 
16.7%
Decimal Number 985
 
13.9%
Close Punctuation 235
 
3.3%
Open Punctuation 235
 
3.3%
Other Punctuation 186
 
2.6%
Dash Punctuation 20
 
0.3%
Uppercase Letter 19
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
연 436
 
10.3%
산 422
 
10.0%
제 327
 
7.8%
시 257
 
6.1%
동 251
 
5.9%
부 238
 
5.6%
광 236
 
5.6%
역 236
 
5.6%
구 235
 
5.6%
로 235
 
5.6%
Other values (152) 1346
31.9%
Decimal Number
ValueCountFrequency (%)
1 212
21.5%
2 174
17.7%
3 156
15.8%
4 99
10.1%
0 82
 
8.3%
5 75
 
7.6%
6 56
 
5.7%
8 47
 
4.8%
7 47
 
4.8%
9 37
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 4
21.1%
I 3
15.8%
S 2
10.5%
K 2
10.5%
E 2
10.5%
W 2
10.5%
V 2
10.5%
A 1
 
5.3%
G 1
 
5.3%
Space Separator
ValueCountFrequency (%)
1184
100.0%
Close Punctuation
ValueCountFrequency (%)
) 235
100.0%
Open Punctuation
ValueCountFrequency (%)
( 235
100.0%
Other Punctuation
ValueCountFrequency (%)
, 186
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4219
59.6%
Common 2845
40.2%
Latin 19
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
연 436
 
10.3%
산 422
 
10.0%
제 327
 
7.8%
시 257
 
6.1%
동 251
 
5.9%
부 238
 
5.6%
광 236
 
5.6%
역 236
 
5.6%
구 235
 
5.6%
로 235
 
5.6%
Other values (152) 1346
31.9%
Common
ValueCountFrequency (%)
1184
41.6%
) 235
 
8.3%
( 235
 
8.3%
1 212
 
7.5%
, 186
 
6.5%
2 174
 
6.1%
3 156
 
5.5%
4 99
 
3.5%
0 82
 
2.9%
5 75
 
2.6%
Other values (5) 207
 
7.3%
Latin
ValueCountFrequency (%)
B 4
21.1%
I 3
15.8%
S 2
10.5%
K 2
10.5%
E 2
10.5%
W 2
10.5%
V 2
10.5%
A 1
 
5.3%
G 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4219
59.6%
ASCII 2864
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1184
41.3%
) 235
 
8.2%
( 235
 
8.2%
1 212
 
7.4%
, 186
 
6.5%
2 174
 
6.1%
3 156
 
5.4%
4 99
 
3.5%
0 82
 
2.9%
5 75
 
2.6%
Other values (14) 226
 
7.9%
Hangul
ValueCountFrequency (%)
연 436
 
10.3%
산 422
 
10.0%
제 327
 
7.8%
시 257
 
6.1%
동 251
 
5.9%
부 238
 
5.6%
광 236
 
5.6%
역 236
 
5.6%
구 235
 
5.6%
로 235
 
5.6%
Other values (152) 1346
31.9%

시설전화번호
Text

MISSING 

Distinct128
Distinct (%)97.0%
Missing104
Missing (%)44.1%
Memory size2.0 KiB
2024-04-30T08:20:28.671670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length10

Characters and Unicode

Total characters1584
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

Unique125 ?
Unique (%)94.7%

Sample

1st row051-757-0101
2nd row051-852-1141
3rd row051-864-3505
4th row051-861-2028
5th row051-864-7463
ValueCountFrequency (%)
051-757-0101 3
 
2.3%
051-555-1500 2
 
1.5%
051-868-9624 2
 
1.5%
051-851-5263 1
 
0.8%
051-507-5351 1
 
0.8%
051-918-1087 1
 
0.8%
051-867-1544 1
 
0.8%
051-868-2973 1
 
0.8%
051-867-9688 1
 
0.8%
051-867-4445 1
 
0.8%
Other values (118) 118
89.4%
2024-04-30T08:20:29.037085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 264
16.7%
- 262
16.5%
0 236
14.9%
1 214
13.5%
8 151
9.5%
7 106
6.7%
6 105
 
6.6%
3 67
 
4.2%
9 64
 
4.0%
2 61
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1322
83.5%
Dash Punctuation 262
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 264
20.0%
0 236
17.9%
1 214
16.2%
8 151
11.4%
7 106
8.0%
6 105
 
7.9%
3 67
 
5.1%
9 64
 
4.8%
2 61
 
4.6%
4 54
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 262
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1584
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 264
16.7%
- 262
16.5%
0 236
14.9%
1 214
13.5%
8 151
9.5%
7 106
6.7%
6 105
 
6.6%
3 67
 
4.2%
9 64
 
4.0%
2 61
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1584
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 264
16.7%
- 262
16.5%
0 236
14.9%
1 214
13.5%
8 151
9.5%
7 106
6.7%
6 105
 
6.6%
3 67
 
4.2%
9 64
 
4.0%
2 61
 
3.9%

Missing values

2024-04-30T08:20:26.655920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T08:20:26.744603image/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.
2024-04-30T08:20:26.845679image/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

업종상호시설주소(도로명)시설전화번호
0수영장업대영 스포렉스부산광역시 연제구 연안로 25 (연산동)051-757-0101
1수영장업더 퍼스트 수영장부산광역시 연제구 거제천로87번길 30, 지하1층 (거제동, 연제그린타워)051-852-1141
2체육도장업송무인 동명태권도부산광역시 연제구 연제로8번길 54 (연산동)051-864-3505
3체육도장업경동태권도부산광역시 연제구 세병로 16 (연산동)051-861-2028
4체육도장업새화랑체육도장부산광역시 연제구 쌍미천로 11 (연산동)051-864-7463
5체육도장업태극체육관부산광역시 연제구 연안로13번길 65 (연산동)051-751-8441
6체육도장업대세 태권도장부산광역시 연제구 거제천로 112 (연산동)051-867-1843
7체육도장업거성체육관부산광역시 연제구 해맞이로 23, 115동 305호 (거제동, 거제유림아시아드)051-503-7313
8체육도장업경원체육관부산광역시 연제구 중앙천로 38, 3층 (연산동)051-864-2353
9체육도장업연산체육관부산광역시 연제구 중앙천로39번길 13, 지하1층 (연산동)051-852-3280
업종상호시설주소(도로명)시설전화번호
226체육교습업SM SSAKA(에쓰엠싸카)부산광역시 연제구 좌수영로 295, 2층 (연산동)<NA>
227체육교습업루키즈부산광역시 연제구 월드컵대로 54, 4층 (연산동)<NA>
228체육교습업(주)모션스포츠부산광역시 연제구 쌍미천로 160, 행복한교회 3층 (연산동)<NA>
229체육교습업FC BS89 축구클럽부산광역시 연제구 반송로 89, 6층 (연산동)<NA>
230체육교습업지니어스 음악줄넘기 연일점부산광역시 연제구 쌍미천로 106, 2층 (연산동)<NA>
231체육교습업더퍼스트 FC부산광역시 연제구 과정로 314, A동 4층 (연산동)<NA>
232체육교습업조이풋볼클럽부산광역시 연제구 월드컵대로 21, 한원 메디칼 빌딩 7층 (연산동)<NA>
233체육교습업망고키즈수영장 부산중앙본점부산광역시 연제구 거제대로252번길 20, 대산직업전문학교 1층 (거제동)<NA>
234체육교습업음악줄넘기 줄친구 점프점프부산광역시 연제구 중앙천로 38, 4층 (연산동)<NA>
235<NA><NA><NA><NA>