Overview

Dataset statistics

Number of variables5
Number of observations245
Missing cells105
Missing cells (%)8.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory41.5 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description부산광역시남구_체육시설업현황_20210813
Author부산광역시 남구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15055499

Alerts

연번 is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 연번High correlation
전화번호 has 105 (42.9%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:02:05.657178
Analysis finished2023-12-10 17:02:06.581801
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct245
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123
Minimum1
Maximum245
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-11T02:02:06.715309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.2
Q162
median123
Q3184
95-th percentile232.8
Maximum245
Range244
Interquartile range (IQR)122

Descriptive statistics

Standard deviation70.869599
Coefficient of variation (CV)0.5761756
Kurtosis-1.2
Mean123
Median Absolute Deviation (MAD)61
Skewness0
Sum30135
Variance5022.5
MonotonicityStrictly increasing
2023-12-11T02:02:06.959723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
155 1
 
0.4%
157 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
Other values (235) 235
95.9%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
245 1
0.4%
244 1
0.4%
243 1
0.4%
242 1
0.4%
241 1
0.4%
240 1
0.4%
239 1
0.4%
238 1
0.4%
237 1
0.4%
236 1
0.4%

업종
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
체육도장업
73 
체력단련장업
72 
당구장업
62 
골프연습장업
28 
수영장업
 
4
Other values (3)
 
6

Length

Max length10
Median length6
Mean length5.1959184
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
체육도장업 73
29.8%
체력단련장업 72
29.4%
당구장업 62
25.3%
골프연습장업 28
 
11.4%
수영장업 4
 
1.6%
가상체험 체육시설업 3
 
1.2%
체육교습업 2
 
0.8%
빙상장업 1
 
0.4%

Length

2023-12-11T02:02:07.190186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:02:07.393816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체육도장업 73
29.4%
체력단련장업 72
29.0%
당구장업 62
25.0%
골프연습장업 28
 
11.3%
수영장업 4
 
1.6%
가상체험 3
 
1.2%
체육시설업 3
 
1.2%
체육교습업 2
 
0.8%
빙상장업 1
 
0.4%

상호
Text

Distinct242
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-11T02:02:07.735053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length7.4530612
Min length2

Characters and Unicode

Total characters1826
Distinct characters314
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique239 ?
Unique (%)97.6%

Sample

1st row용호레포츠수영장
2nd row대호 키즈수영장
3rd row주식회사 센츄리 스포렉스
4th row아이올림픽 키즈 수영장
5th row청운체육관
ValueCountFrequency (%)
당구클럽 20
 
5.2%
당구장 14
 
3.7%
휘트니스 11
 
2.9%
태권도 9
 
2.3%
핏 5
 
1.3%
주식회사 3
 
0.8%
센츄리 3
 
0.8%
짐 3
 
0.8%
스크린골프 3
 
0.8%
합기도 2
 
0.5%
Other values (299) 310
80.9%
2023-12-11T02:02:08.358416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
138
 
7.6%
스 80
 
4.4%
구 60
 
3.3%
당 59
 
3.2%
장 58
 
3.2%
도 54
 
3.0%
태 43
 
2.4%
권 43
 
2.4%
럽 38
 
2.1%
클 37
 
2.0%
Other values (304) 1216
66.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1489
81.5%
Space Separator 138
 
7.6%
Uppercase Letter 118
 
6.5%
Lowercase Letter 26
 
1.4%
Decimal Number 18
 
1.0%
Close Punctuation 15
 
0.8%
Open Punctuation 15
 
0.8%
Other Punctuation 4
 
0.2%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 80
 
5.4%
구 60
 
4.0%
당 59
 
4.0%
장 58
 
3.9%
도 54
 
3.6%
태 43
 
2.9%
권 43
 
2.9%
럽 38
 
2.6%
클 37
 
2.5%
트 34
 
2.3%
Other values (254) 983
66.0%
Uppercase Letter
ValueCountFrequency (%)
M 12
 
10.2%
A 12
 
10.2%
I 12
 
10.2%
G 9
 
7.6%
N 7
 
5.9%
L 6
 
5.1%
F 6
 
5.1%
E 5
 
4.2%
Y 5
 
4.2%
B 5
 
4.2%
Other values (13) 39
33.1%
Lowercase Letter
ValueCountFrequency (%)
n 4
15.4%
o 4
15.4%
e 3
11.5%
t 2
7.7%
i 2
7.7%
s 2
7.7%
c 2
7.7%
f 2
7.7%
y 1
 
3.8%
m 1
 
3.8%
Other values (3) 3
11.5%
Decimal Number
ValueCountFrequency (%)
2 7
38.9%
9 2
 
11.1%
4 2
 
11.1%
8 2
 
11.1%
0 2
 
11.1%
7 2
 
11.1%
3 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
, 1
25.0%
& 1
25.0%
Space Separator
ValueCountFrequency (%)
138
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1489
81.5%
Common 193
 
10.6%
Latin 144
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 80
 
5.4%
구 60
 
4.0%
당 59
 
4.0%
장 58
 
3.9%
도 54
 
3.6%
태 43
 
2.9%
권 43
 
2.9%
럽 38
 
2.6%
클 37
 
2.5%
트 34
 
2.3%
Other values (254) 983
66.0%
Latin
ValueCountFrequency (%)
M 12
 
8.3%
A 12
 
8.3%
I 12
 
8.3%
G 9
 
6.2%
N 7
 
4.9%
L 6
 
4.2%
F 6
 
4.2%
E 5
 
3.5%
Y 5
 
3.5%
B 5
 
3.5%
Other values (26) 65
45.1%
Common
ValueCountFrequency (%)
138
71.5%
) 15
 
7.8%
( 15
 
7.8%
2 7
 
3.6%
- 3
 
1.6%
9 2
 
1.0%
4 2
 
1.0%
8 2
 
1.0%
. 2
 
1.0%
0 2
 
1.0%
Other values (4) 5
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1489
81.5%
ASCII 337
 
18.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
138
40.9%
) 15
 
4.5%
( 15
 
4.5%
M 12
 
3.6%
A 12
 
3.6%
I 12
 
3.6%
G 9
 
2.7%
2 7
 
2.1%
N 7
 
2.1%
L 6
 
1.8%
Other values (40) 104
30.9%
Hangul
ValueCountFrequency (%)
스 80
 
5.4%
구 60
 
4.0%
당 59
 
4.0%
장 58
 
3.9%
도 54
 
3.6%
태 43
 
2.9%
권 43
 
2.9%
럽 38
 
2.6%
클 37
 
2.5%
트 34
 
2.3%
Other values (254) 983
66.0%

도로명주소
Text

Distinct243
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-11T02:02:08.722997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length49
Mean length31.853061
Min length19

Characters and Unicode

Total characters7804
Distinct characters208
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique241 ?
Unique (%)98.4%

Sample

1st row부산광역시 남구 동명로152번길 27 (용호동)
2nd row부산광역시 남구 석포로 119, 지하1층 (대연동)
3rd row부산광역시 남구 수영로 312, 지하2층 14호 (대연동, 센츄리빌딩)
4th row부산광역시 남구 용호로 132, 지하1층 (용호동)
5th row부산광역시 남구 우암로 40-1, 2층 (감만동)
ValueCountFrequency (%)
부산광역시 245
 
15.4%
남구 245
 
15.4%
대연동 124
 
7.8%
용호동 57
 
3.6%
3층 45
 
2.8%
2층 36
 
2.3%
수영로 36
 
2.3%
문현동 33
 
2.1%
용호로 19
 
1.2%
4층 19
 
1.2%
Other values (371) 731
46.0%
2023-12-11T02:02:09.294496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1348
 
17.3%
동 308
 
3.9%
1 296
 
3.8%
, 296
 
3.8%
남 259
 
3.3%
시 254
 
3.3%
부 251
 
3.2%
산 251
 
3.2%
로 249
 
3.2%
광 246
 
3.2%
Other values (198) 4046
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4364
55.9%
Space Separator 1348
 
17.3%
Decimal Number 1247
 
16.0%
Other Punctuation 296
 
3.8%
Open Punctuation 243
 
3.1%
Close Punctuation 243
 
3.1%
Uppercase Letter 35
 
0.4%
Dash Punctuation 27
 
0.3%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 308
 
7.1%
남 259
 
5.9%
시 254
 
5.8%
부 251
 
5.8%
산 251
 
5.8%
로 249
 
5.7%
광 246
 
5.6%
구 246
 
5.6%
역 245
 
5.6%
대 169
 
3.9%
Other values (169) 1886
43.2%
Uppercase Letter
ValueCountFrequency (%)
B 13
37.1%
A 7
20.0%
S 3
 
8.6%
I 2
 
5.7%
P 2
 
5.7%
L 1
 
2.9%
V 1
 
2.9%
G 1
 
2.9%
K 1
 
2.9%
O 1
 
2.9%
Other values (3) 3
 
8.6%
Decimal Number
ValueCountFrequency (%)
1 296
23.7%
2 198
15.9%
3 171
13.7%
0 114
 
9.1%
4 112
 
9.0%
5 91
 
7.3%
6 90
 
7.2%
9 62
 
5.0%
8 58
 
4.7%
7 55
 
4.4%
Space Separator
ValueCountFrequency (%)
1348
100.0%
Other Punctuation
ValueCountFrequency (%)
, 296
100.0%
Open Punctuation
ValueCountFrequency (%)
( 243
100.0%
Close Punctuation
ValueCountFrequency (%)
) 243
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4364
55.9%
Common 3404
43.6%
Latin 36
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 308
 
7.1%
남 259
 
5.9%
시 254
 
5.8%
부 251
 
5.8%
산 251
 
5.8%
로 249
 
5.7%
광 246
 
5.6%
구 246
 
5.6%
역 245
 
5.6%
대 169
 
3.9%
Other values (169) 1886
43.2%
Common
ValueCountFrequency (%)
1348
39.6%
1 296
 
8.7%
, 296
 
8.7%
( 243
 
7.1%
) 243
 
7.1%
2 198
 
5.8%
3 171
 
5.0%
0 114
 
3.3%
4 112
 
3.3%
5 91
 
2.7%
Other values (5) 292
 
8.6%
Latin
ValueCountFrequency (%)
B 13
36.1%
A 7
19.4%
S 3
 
8.3%
I 2
 
5.6%
P 2
 
5.6%
L 1
 
2.8%
V 1
 
2.8%
G 1
 
2.8%
K 1
 
2.8%
O 1
 
2.8%
Other values (4) 4
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4364
55.9%
ASCII 3440
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1348
39.2%
1 296
 
8.6%
, 296
 
8.6%
( 243
 
7.1%
) 243
 
7.1%
2 198
 
5.8%
3 171
 
5.0%
0 114
 
3.3%
4 112
 
3.3%
5 91
 
2.6%
Other values (19) 328
 
9.5%
Hangul
ValueCountFrequency (%)
동 308
 
7.1%
남 259
 
5.9%
시 254
 
5.8%
부 251
 
5.8%
산 251
 
5.8%
로 249
 
5.7%
광 246
 
5.6%
구 246
 
5.6%
역 245
 
5.6%
대 169
 
3.9%
Other values (169) 1886
43.2%

전화번호
Text

MISSING 

Distinct140
Distinct (%)100.0%
Missing105
Missing (%)42.9%
Memory size2.0 KiB
2023-12-11T02:02:09.723909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.9714286
Min length8

Characters and Unicode

Total characters1256
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

Unique140 ?
Unique (%)100.0%

Sample

1st row627-7373
2nd row611-6227
3rd row610-1111
4th row626-7783
5th row635-8961
ValueCountFrequency (%)
634-2362 1
 
0.7%
051-623-9696 1
 
0.7%
627-7372 1
 
0.7%
621-0003 1
 
0.7%
627-3672 1
 
0.7%
623-3119 1
 
0.7%
622-9679 1
 
0.7%
633-2147 1
 
0.7%
051-905-0444 1
 
0.7%
624-2584 1
 
0.7%
Other values (130) 130
92.9%
2023-12-11T02:02:10.710705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 192
15.3%
- 174
13.9%
2 146
11.6%
1 132
10.5%
0 125
10.0%
3 102
8.1%
7 92
7.3%
5 91
7.2%
8 72
 
5.7%
9 71
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1082
86.1%
Dash Punctuation 174
 
13.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 192
17.7%
2 146
13.5%
1 132
12.2%
0 125
11.6%
3 102
9.4%
7 92
8.5%
5 91
8.4%
8 72
 
6.7%
9 71
 
6.6%
4 59
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 174
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1256
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 192
15.3%
- 174
13.9%
2 146
11.6%
1 132
10.5%
0 125
10.0%
3 102
8.1%
7 92
7.3%
5 91
7.2%
8 72
 
5.7%
9 71
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1256
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 192
15.3%
- 174
13.9%
2 146
11.6%
1 132
10.5%
0 125
10.0%
3 102
8.1%
7 92
7.3%
5 91
7.2%
8 72
 
5.7%
9 71
 
5.7%

Interactions

2023-12-11T02:02:06.161250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:02:10.883153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.839
업종0.8391.000
2023-12-11T02:02:11.021727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.607
업종0.6071.000

Missing values

2023-12-11T02:02:06.345906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:02:06.516336image/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

연번업종상호도로명주소전화번호
01수영장업용호레포츠수영장부산광역시 남구 동명로152번길 27 (용호동)627-7373
12수영장업대호 키즈수영장부산광역시 남구 석포로 119, 지하1층 (대연동)611-6227
23수영장업주식회사 센츄리 스포렉스부산광역시 남구 수영로 312, 지하2층 14호 (대연동, 센츄리빌딩)610-1111
34수영장업아이올림픽 키즈 수영장부산광역시 남구 용호로 132, 지하1층 (용호동)626-7783
45체육도장업청운체육관부산광역시 남구 우암로 40-1, 2층 (감만동)635-8961
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