Overview

Dataset statistics

Number of variables5
Number of observations421
Missing cells222
Missing cells (%)10.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.0 KiB
Average record size in memory41.3 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description부산광역시해운대구_신고체육시설업현황_20211121
Author부산광역시 해운대구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3075744

Alerts

연번 is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 연번High correlation
연락처 has 222 (52.7%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:04:03.873247
Analysis finished2023-12-10 17:04:04.986235
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct421
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean211
Minimum1
Maximum421
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-11T02:04:05.101001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22
Q1106
median211
Q3316
95-th percentile400
Maximum421
Range420
Interquartile range (IQR)210

Descriptive statistics

Standard deviation121.67648
Coefficient of variation (CV)0.5766658
Kurtosis-1.2
Mean211
Median Absolute Deviation (MAD)105
Skewness0
Sum88831
Variance14805.167
MonotonicityStrictly increasing
2023-12-11T02:04:05.333788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
265 1
 
0.2%
289 1
 
0.2%
288 1
 
0.2%
287 1
 
0.2%
286 1
 
0.2%
285 1
 
0.2%
284 1
 
0.2%
283 1
 
0.2%
282 1
 
0.2%
Other values (411) 411
97.6%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
421 1
0.2%
420 1
0.2%
419 1
0.2%
418 1
0.2%
417 1
0.2%
416 1
0.2%
415 1
0.2%
414 1
0.2%
413 1
0.2%
412 1
0.2%

업종
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
체력단련장업
138 
체육도장업
104 
골프연습장업
57 
당구장업
52 
가상체험 체육시설업
37 
Other values (4)
33 

Length

Max length10
Median length7
Mean length5.7672209
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 138
32.8%
체육도장업 104
24.7%
골프연습장업 57
13.5%
당구장업 52
 
12.4%
가상체험 체육시설업 37
 
8.8%
체육교습업 19
 
4.5%
수영장업 10
 
2.4%
종합체육시설업 3
 
0.7%
빙상장업 1
 
0.2%

Length

2023-12-11T02:04:05.901520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:04:06.120603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 138
30.1%
체육도장업 104
22.7%
골프연습장업 57
12.4%
당구장업 52
 
11.4%
가상체험 37
 
8.1%
체육시설업 37
 
8.1%
체육교습업 19
 
4.1%
수영장업 10
 
2.2%
종합체육시설업 3
 
0.7%
빙상장업 1
 
0.2%

상호명
Text

Distinct414
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2023-12-11T02:04:06.607958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length8.5083135
Min length2

Characters and Unicode

Total characters3582
Distinct characters387
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique408 ?
Unique (%)96.9%

Sample

1st row(주)파라다이스호텔부산신관수영장(실외)
2nd row아이 올림픽
3rd row(주)조선호텔앤리조트 부산 수영장
4th row트리니티스포츠클럽&스파
5th row코오롱씨클라우드호텔수영장(실외)
ValueCountFrequency (%)
태권도 18
 
2.5%
피트니스 15
 
2.1%
골프 14
 
1.9%
당구장 13
 
1.8%
휘트니스 11
 
1.5%
당구클럽 10
 
1.4%
스크린 9
 
1.2%
스크린골프 7
 
1.0%
gym 7
 
1.0%
부산 7
 
1.0%
Other values (526) 620
84.8%
2023-12-11T02:04:07.470535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
310
 
8.7%
스 208
 
5.8%
프 96
 
2.7%
골 88
 
2.5%
장 77
 
2.1%
트 73
 
2.0%
도 64
 
1.8%
구 57
 
1.6%
니 54
 
1.5%
태 51
 
1.4%
Other values (377) 2504
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2820
78.7%
Space Separator 310
 
8.7%
Uppercase Letter 248
 
6.9%
Lowercase Letter 88
 
2.5%
Open Punctuation 32
 
0.9%
Close Punctuation 32
 
0.9%
Decimal Number 28
 
0.8%
Other Punctuation 24
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 208
 
7.4%
프 96
 
3.4%
골 88
 
3.1%
장 77
 
2.7%
트 73
 
2.6%
도 64
 
2.3%
구 57
 
2.0%
니 54
 
1.9%
태 51
 
1.8%
당 51
 
1.8%
Other values (316) 2001
71.0%
Uppercase Letter
ValueCountFrequency (%)
T 28
 
11.3%
G 23
 
9.3%
M 20
 
8.1%
S 16
 
6.5%
O 16
 
6.5%
A 15
 
6.0%
I 12
 
4.8%
P 12
 
4.8%
C 10
 
4.0%
B 9
 
3.6%
Other values (14) 87
35.1%
Lowercase Letter
ValueCountFrequency (%)
e 10
11.4%
m 10
11.4%
i 9
10.2%
o 8
 
9.1%
y 6
 
6.8%
s 6
 
6.8%
r 5
 
5.7%
a 5
 
5.7%
n 5
 
5.7%
l 4
 
4.5%
Other values (10) 20
22.7%
Decimal Number
ValueCountFrequency (%)
2 9
32.1%
1 7
25.0%
9 3
 
10.7%
4 3
 
10.7%
0 2
 
7.1%
5 1
 
3.6%
6 1
 
3.6%
3 1
 
3.6%
8 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
& 12
50.0%
. 7
29.2%
, 3
 
12.5%
· 1
 
4.2%
: 1
 
4.2%
Space Separator
ValueCountFrequency (%)
310
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2820
78.7%
Common 426
 
11.9%
Latin 336
 
9.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 208
 
7.4%
프 96
 
3.4%
골 88
 
3.1%
장 77
 
2.7%
트 73
 
2.6%
도 64
 
2.3%
구 57
 
2.0%
니 54
 
1.9%
태 51
 
1.8%
당 51
 
1.8%
Other values (316) 2001
71.0%
Latin
ValueCountFrequency (%)
T 28
 
8.3%
G 23
 
6.8%
M 20
 
6.0%
S 16
 
4.8%
O 16
 
4.8%
A 15
 
4.5%
I 12
 
3.6%
P 12
 
3.6%
C 10
 
3.0%
e 10
 
3.0%
Other values (34) 174
51.8%
Common
ValueCountFrequency (%)
310
72.8%
( 32
 
7.5%
) 32
 
7.5%
& 12
 
2.8%
2 9
 
2.1%
. 7
 
1.6%
1 7
 
1.6%
, 3
 
0.7%
9 3
 
0.7%
4 3
 
0.7%
Other values (7) 8
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2820
78.7%
ASCII 761
 
21.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
310
40.7%
( 32
 
4.2%
) 32
 
4.2%
T 28
 
3.7%
G 23
 
3.0%
M 20
 
2.6%
S 16
 
2.1%
O 16
 
2.1%
A 15
 
2.0%
I 12
 
1.6%
Other values (50) 257
33.8%
Hangul
ValueCountFrequency (%)
스 208
 
7.4%
프 96
 
3.4%
골 88
 
3.1%
장 77
 
2.7%
트 73
 
2.6%
도 64
 
2.3%
구 57
 
2.0%
니 54
 
1.9%
태 51
 
1.8%
당 51
 
1.8%
Other values (316) 2001
71.0%
None
ValueCountFrequency (%)
· 1
100.0%

소재지
Text

Distinct414
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2023-12-11T02:04:08.052814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length47
Mean length34.7981
Min length22

Characters and Unicode

Total characters14650
Distinct characters264
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

Unique408 ?
Unique (%)96.9%

Sample

1st row부산광역시 해운대구 해운대해변로 296 (중동)
2nd row부산광역시 해운대구 재반로125번길 63 (재송동)
3rd row부산광역시 해운대구 동백로 67 (우동)
4th row부산광역시 해운대구 센텀남대로 35 (우동)
5th row부산광역시 해운대구 해운대해변로 287, 4층 (중동)
ValueCountFrequency (%)
부산광역시 421
 
15.4%
해운대구 421
 
15.4%
우동 101
 
3.7%
좌동 91
 
3.3%
재송동 56
 
2.0%
반여동 56
 
2.0%
중동 53
 
1.9%
3층 50
 
1.8%
2층 38
 
1.4%
좌동순환로 33
 
1.2%
Other values (645) 1414
51.7%
2023-12-11T02:04:08.911780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2335
 
15.9%
동 568
 
3.9%
대 542
 
3.7%
운 526
 
3.6%
해 520
 
3.5%
시 486
 
3.3%
, 483
 
3.3%
1 478
 
3.3%
산 444
 
3.0%
부 427
 
2.9%
Other values (254) 7841
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8600
58.7%
Space Separator 2335
 
15.9%
Decimal Number 2247
 
15.3%
Other Punctuation 488
 
3.3%
Open Punctuation 424
 
2.9%
Close Punctuation 424
 
2.9%
Dash Punctuation 61
 
0.4%
Uppercase Letter 54
 
0.4%
Math Symbol 13
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 568
 
6.6%
대 542
 
6.3%
운 526
 
6.1%
해 520
 
6.0%
시 486
 
5.7%
산 444
 
5.2%
부 427
 
5.0%
구 426
 
5.0%
광 423
 
4.9%
역 421
 
4.9%
Other values (217) 3817
44.4%
Uppercase Letter
ValueCountFrequency (%)
B 22
40.7%
C 7
 
13.0%
A 5
 
9.3%
S 4
 
7.4%
N 3
 
5.6%
P 2
 
3.7%
E 2
 
3.7%
K 2
 
3.7%
I 2
 
3.7%
F 1
 
1.9%
Other values (4) 4
 
7.4%
Decimal Number
ValueCountFrequency (%)
1 478
21.3%
2 366
16.3%
3 309
13.8%
0 278
12.4%
4 184
 
8.2%
5 156
 
6.9%
6 146
 
6.5%
7 133
 
5.9%
8 109
 
4.9%
9 88
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 483
99.0%
@ 3
 
0.6%
? 1
 
0.2%
？ 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
y 1
25.0%
c 1
25.0%
x 1
25.0%
e 1
25.0%
Space Separator
ValueCountFrequency (%)
2335
100.0%
Open Punctuation
ValueCountFrequency (%)
( 424
100.0%
Close Punctuation
ValueCountFrequency (%)
) 424
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8600
58.7%
Common 5992
40.9%
Latin 58
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 568
 
6.6%
대 542
 
6.3%
운 526
 
6.1%
해 520
 
6.0%
시 486
 
5.7%
산 444
 
5.2%
부 427
 
5.0%
구 426
 
5.0%
광 423
 
4.9%
역 421
 
4.9%
Other values (217) 3817
44.4%
Common
ValueCountFrequency (%)
2335
39.0%
, 483
 
8.1%
1 478
 
8.0%
( 424
 
7.1%
) 424
 
7.1%
2 366
 
6.1%
3 309
 
5.2%
0 278
 
4.6%
4 184
 
3.1%
5 156
 
2.6%
Other values (9) 555
 
9.3%
Latin
ValueCountFrequency (%)
B 22
37.9%
C 7
 
12.1%
A 5
 
8.6%
S 4
 
6.9%
N 3
 
5.2%
P 2
 
3.4%
E 2
 
3.4%
K 2
 
3.4%
I 2
 
3.4%
y 1
 
1.7%
Other values (8) 8
 
13.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8600
58.7%
ASCII 6049
41.3%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2335
38.6%
, 483
 
8.0%
1 478
 
7.9%
( 424
 
7.0%
) 424
 
7.0%
2 366
 
6.1%
3 309
 
5.1%
0 278
 
4.6%
4 184
 
3.0%
5 156
 
2.6%
Other values (26) 612
 
10.1%
Hangul
ValueCountFrequency (%)
동 568
 
6.6%
대 542
 
6.3%
운 526
 
6.1%
해 520
 
6.0%
시 486
 
5.7%
산 444
 
5.2%
부 427
 
5.0%
구 426
 
5.0%
광 423
 
4.9%
역 421
 
4.9%
Other values (217) 3817
44.4%
None
ValueCountFrequency (%)
？ 1
100.0%

연락처
Text

MISSING 

Distinct192
Distinct (%)96.5%
Missing222
Missing (%)52.7%
Memory size3.4 KiB
2023-12-11T02:04:09.344682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2388
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

Unique187 ?
Unique (%)94.0%

Sample

1st row051-749-2613
2nd row051-747-7783
3rd row051-749-7000
4th row051-745-1900
5th row051-933-1441
ValueCountFrequency (%)
051-749-2613 4
 
2.0%
051-744-0753 2
 
1.0%
051-702-1848 2
 
1.0%
051-745-1900 2
 
1.0%
051-744-8900 2
 
1.0%
051-742-1113 1
 
0.5%
051-701-8593 1
 
0.5%
051-741-8442 1
 
0.5%
051-524-6657 1
 
0.5%
051-526-1009 1
 
0.5%
Other values (182) 182
91.5%
2023-12-11T02:04:09.932492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 398
16.7%
0 377
15.8%
1 345
14.4%
5 336
14.1%
7 261
10.9%
4 172
7.2%
2 132
 
5.5%
3 122
 
5.1%
8 105
 
4.4%
6 82
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1990
83.3%
Dash Punctuation 398
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 377
18.9%
1 345
17.3%
5 336
16.9%
7 261
13.1%
4 172
8.6%
2 132
 
6.6%
3 122
 
6.1%
8 105
 
5.3%
6 82
 
4.1%
9 58
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 398
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2388
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 398
16.7%
0 377
15.8%
1 345
14.4%
5 336
14.1%
7 261
10.9%
4 172
7.2%
2 132
 
5.5%
3 122
 
5.1%
8 105
 
4.4%
6 82
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 398
16.7%
0 377
15.8%
1 345
14.4%
5 336
14.1%
7 261
10.9%
4 172
7.2%
2 132
 
5.5%
3 122
 
5.1%
8 105
 
4.4%
6 82
 
3.4%

Interactions

2023-12-11T02:04:04.554873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:04:10.110343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.874
업종0.8741.000
2023-12-11T02:04:10.258193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.645
업종0.6451.000

Missing values

2023-12-11T02:04:04.753260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:04:04.920300image/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

연번업종상호명소재지연락처
01수영장업(주)파라다이스호텔부산신관수영장(실외)부산광역시 해운대구 해운대해변로 296 (중동)051-749-2613
12수영장업아이 올림픽부산광역시 해운대구 재반로125번길 63 (재송동)051-747-7783
23수영장업(주)조선호텔앤리조트 부산 수영장부산광역시 해운대구 동백로 67 (우동)051-749-7000
34수영장업트리니티스포츠클럽&스파부산광역시 해운대구 센텀남대로 35 (우동)051-745-1900
45수영장업코오롱씨클라우드호텔수영장(실외)부산광역시 해운대구 해운대해변로 287, 4층 (중동)051-933-1441
56수영장업유앤유 키즈 수영장부산광역시 해운대구 해운대해변로 371 (중동)<NA>
67수영장업J&P 수영장부산광역시 해운대구 세실로 87, 영진파스타 B-101호 (좌동)051-703-7078
78수영장업신라스테이 해운대호텔부산광역시 해운대구 해운대로570번길 46 (우동)051-911-9386
89수영장업The 스포츠센터부산광역시 해운대구 선수촌로 122, 지하호 (반여동, 아시아선수촌아파트)051-521-7100
910수영장업제이앤피수영장(마린센텀점)부산광역시 해운대구 센텀2로 10, 센텀메디컬센타 지하층 제이비이02호 (우동)051-747-2005
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411412체육교습업벡스 스포츠 스쿨부산광역시 해운대구 세실로 31, 대승프라임 2층 (좌동)051-701-0033
412413체육교습업용인대 지니어스 줄넘기센터부산광역시 해운대구 해운대로 658, 2층 (우동)<NA>
413414체육교습업히어로스포츠부산광역시 해운대구 세실로27번길 21, 원재프라자 5층 (좌동)051-704-7738
414415체육교습업DK FC부산광역시 해운대구 재반로 176, 옥상층 (재송동)<NA>
415416체육교습업히어로 아카데미부산광역시 해운대구 양운로42번길 6, 새삶교회 5층 (좌동)<NA>
416417체육교습업하이스포츠센터부산광역시 해운대구 명장로67번길 121-7, 2층 (반여동)<NA>
417418체육교습업에이치에스 스포츠 아카데미부산광역시 해운대구 선수촌로208번길 71 (반여동)<NA>
418419체육교습업센텀HJ풋볼클럽부산광역시 해운대구 해운대로76번길 40, 옥상층 (재송동, 센텀리슈빌)<NA>
419420체육교습업THE GRIT(더 그릿)부산광역시 해운대구 좌동순환로 414, 오산교회 3,4층 (중동)<NA>
420421체육교습업플렉스 스포츠부산광역시 해운대구 세실로27번길 21, 원재프라자 4층 (좌동)<NA>