Overview

Dataset statistics

Number of variables9
Number of observations337
Missing cells500
Missing cells (%)16.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.8 KiB
Average record size in memory75.4 B

Variable types

Categorical2
Text4
Numeric3

Dataset

Description부산광역시_동래구_체육시설업소현황_20230825
Author부산광역시 동래구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3078915

Alerts

업종 is highly overall correlated with 시설부지면적(제곱미터) and 2 other fieldsHigh correlation
체육도장업상세분류 is highly overall correlated with 업종High correlation
시설부지면적(제곱미터) is highly overall correlated with 시설면적(제곱미터) and 2 other fieldsHigh correlation
시설면적(제곱미터) is highly overall correlated with 시설부지면적(제곱미터) and 2 other fieldsHigh correlation
건물연면적(제곱미터) is highly overall correlated with 시설부지면적(제곱미터) and 1 other fieldsHigh correlation
체육도장업상세분류 is highly imbalanced (53.7%)Imbalance
시설전화번호 has 149 (44.2%) missing valuesMissing
시설부지면적(제곱미터) has 190 (56.4%) missing valuesMissing
건물연면적(제곱미터) has 158 (46.9%) missing valuesMissing
건물연면적(제곱미터) has 5 (1.5%) zerosZeros

Reproduction

Analysis started2023-12-10 16:44:04.909348
Analysis finished2023-12-10 16:44:08.193863
Duration3.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
체력단련장업
102 
체육도장업
90 
당구장업
63 
골프연습장업
33 
가상체험 체육시설업
21 
Other values (6)
28 

Length

Max length10
Median length7
Mean length5.5252226
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 102
30.3%
체육도장업 90
26.7%
당구장업 63
18.7%
골프연습장업 33
 
9.8%
가상체험 체육시설업 21
 
6.2%
체육교습업 12
 
3.6%
수영장업 6
 
1.8%
무도학원업 4
 
1.2%
인공암벽장업 3
 
0.9%
종합체육시설업 2
 
0.6%

Length

2023-12-11T01:44:08.313102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
체력단련장업 102
28.5%
체육도장업 90
25.1%
당구장업 63
17.6%
골프연습장업 33
 
9.2%
가상체험 21
 
5.9%
체육시설업 21
 
5.9%
체육교습업 12
 
3.4%
수영장업 6
 
1.7%
무도학원업 4
 
1.1%
인공암벽장업 3
 
0.8%
Other values (2) 3
 
0.8%

상호
Text

Distinct332
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-11T01:44:08.753323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length7.5014837
Min length2

Characters and Unicode

Total characters2528
Distinct characters374
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

Unique327 ?
Unique (%)97.0%

Sample

1st row키즈스플래쉬(부산본점)
2nd row망고키즈수영장(사직점)
3rd row아이올림픽 유소년 체육센터
4th row골드키즈
5th row지니키즈스윔스쿨
ValueCountFrequency (%)
당구클럽 12
 
2.2%
동래점 11
 
2.0%
당구장 11
 
2.0%
휘트니스 10
 
1.8%
태권도 8
 
1.5%
gym 7
 
1.3%
피트니스 5
 
0.9%
사직점 5
 
0.9%
스크린골프 4
 
0.7%
골프 4
 
0.7%
Other values (422) 467
85.8%
2023-12-11T01:44:09.396574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
207
 
8.2%
스 123
 
4.9%
구 64
 
2.5%
도 63
 
2.5%
장 60
 
2.4%
당 56
 
2.2%
프 50
 
2.0%
골 47
 
1.9%
트 47
 
1.9%
태 43
 
1.7%
Other values (364) 1768
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2110
83.5%
Space Separator 207
 
8.2%
Uppercase Letter 126
 
5.0%
Lowercase Letter 47
 
1.9%
Decimal Number 14
 
0.6%
Open Punctuation 10
 
0.4%
Close Punctuation 10
 
0.4%
Other Punctuation 3
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 123
 
5.8%
구 64
 
3.0%
도 63
 
3.0%
장 60
 
2.8%
당 56
 
2.7%
프 50
 
2.4%
골 47
 
2.2%
트 47
 
2.2%
태 43
 
2.0%
클 43
 
2.0%
Other values (309) 1514
71.8%
Uppercase Letter
ValueCountFrequency (%)
M 17
13.5%
G 13
 
10.3%
P 9
 
7.1%
T 8
 
6.3%
Y 8
 
6.3%
J 8
 
6.3%
I 6
 
4.8%
S 6
 
4.8%
F 5
 
4.0%
B 5
 
4.0%
Other values (15) 41
32.5%
Lowercase Letter
ValueCountFrequency (%)
i 6
12.8%
n 5
10.6%
o 5
10.6%
m 4
8.5%
r 4
8.5%
c 4
8.5%
s 3
 
6.4%
y 3
 
6.4%
t 2
 
4.3%
f 2
 
4.3%
Other values (6) 9
19.1%
Decimal Number
ValueCountFrequency (%)
1 3
21.4%
5 2
14.3%
6 2
14.3%
3 2
14.3%
2 2
14.3%
9 2
14.3%
4 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
& 1
33.3%
' 1
33.3%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
207
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2110
83.5%
Common 244
 
9.7%
Latin 174
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 123
 
5.8%
구 64
 
3.0%
도 63
 
3.0%
장 60
 
2.8%
당 56
 
2.7%
프 50
 
2.4%
골 47
 
2.2%
트 47
 
2.2%
태 43
 
2.0%
클 43
 
2.0%
Other values (309) 1514
71.8%
Latin
ValueCountFrequency (%)
M 17
 
9.8%
G 13
 
7.5%
P 9
 
5.2%
T 8
 
4.6%
Y 8
 
4.6%
J 8
 
4.6%
i 6
 
3.4%
I 6
 
3.4%
S 6
 
3.4%
n 5
 
2.9%
Other values (32) 88
50.6%
Common
ValueCountFrequency (%)
207
84.8%
( 10
 
4.1%
) 10
 
4.1%
1 3
 
1.2%
5 2
 
0.8%
6 2
 
0.8%
3 2
 
0.8%
2 2
 
0.8%
9 2
 
0.8%
4 1
 
0.4%
Other values (3) 3
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2110
83.5%
ASCII 417
 
16.5%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
207
49.6%
M 17
 
4.1%
G 13
 
3.1%
( 10
 
2.4%
) 10
 
2.4%
P 9
 
2.2%
T 8
 
1.9%
Y 8
 
1.9%
J 8
 
1.9%
i 6
 
1.4%
Other values (44) 121
29.0%
Hangul
ValueCountFrequency (%)
스 123
 
5.8%
구 64
 
3.0%
도 63
 
3.0%
장 60
 
2.8%
당 56
 
2.7%
프 50
 
2.4%
골 47
 
2.2%
트 47
 
2.2%
태 43
 
2.0%
클 43
 
2.0%
Other values (309) 1514
71.8%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

시설주소(지번)
Text

Distinct310
Distinct (%)92.3%
Missing1
Missing (%)0.3%
Memory size2.8 KiB
2023-12-11T01:44:09.880904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length42
Mean length23.714286
Min length18

Characters and Unicode

Total characters7968
Distinct characters146
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

Unique291 ?
Unique (%)86.6%

Sample

1st row부산광역시 동래구 낙민동 84-8 보림프라자 지1층 108호
2nd row부산광역시 동래구 사직동 74-18
3rd row부산광역시 동래구 명륜동 96-5
4th row부산광역시 동래구 낙민동 90-4 B동
5th row부산광역시 동래구 온천동 1834 동래 지웰
ValueCountFrequency (%)
부산광역시 336
21.1%
동래구 336
21.1%
온천동 102
 
6.4%
사직동 88
 
5.5%
안락동 55
 
3.5%
명륜동 46
 
2.9%
3층 27
 
1.7%
명장동 25
 
1.6%
2층 20
 
1.3%
수안동 15
 
0.9%
Other values (396) 542
34.0%
2023-12-11T01:44:10.460362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1573
19.7%
동 705
 
8.8%
래 344
 
4.3%
산 340
 
4.3%
부 338
 
4.2%
광 337
 
4.2%
역 336
 
4.2%
시 336
 
4.2%
구 336
 
4.2%
1 336
 
4.2%
Other values (136) 2987
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4353
54.6%
Decimal Number 1675
 
21.0%
Space Separator 1573
 
19.7%
Dash Punctuation 311
 
3.9%
Uppercase Letter 26
 
0.3%
Other Punctuation 14
 
0.2%
Close Punctuation 6
 
0.1%
Open Punctuation 6
 
0.1%
Math Symbol 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 705
16.2%
래 344
 
7.9%
산 340
 
7.8%
부 338
 
7.8%
광 337
 
7.7%
역 336
 
7.7%
시 336
 
7.7%
구 336
 
7.7%
천 108
 
2.5%
온 105
 
2.4%
Other values (112) 1068
24.5%
Decimal Number
ValueCountFrequency (%)
1 336
20.1%
2 211
12.6%
4 209
12.5%
3 193
11.5%
5 150
9.0%
7 127
 
7.6%
0 120
 
7.2%
6 113
 
6.7%
9 111
 
6.6%
8 105
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
B 6
23.1%
K 6
23.1%
S 6
23.1%
H 3
11.5%
U 2
 
7.7%
Y 2
 
7.7%
J 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 13
92.9%
· 1
 
7.1%
Space Separator
ValueCountFrequency (%)
1573
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 311
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4353
54.6%
Common 3589
45.0%
Latin 26
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 705
16.2%
래 344
 
7.9%
산 340
 
7.8%
부 338
 
7.8%
광 337
 
7.7%
역 336
 
7.7%
시 336
 
7.7%
구 336
 
7.7%
천 108
 
2.5%
온 105
 
2.4%
Other values (112) 1068
24.5%
Common
ValueCountFrequency (%)
1573
43.8%
1 336
 
9.4%
- 311
 
8.7%
2 211
 
5.9%
4 209
 
5.8%
3 193
 
5.4%
5 150
 
4.2%
7 127
 
3.5%
0 120
 
3.3%
6 113
 
3.1%
Other values (7) 246
 
6.9%
Latin
ValueCountFrequency (%)
B 6
23.1%
K 6
23.1%
S 6
23.1%
H 3
11.5%
U 2
 
7.7%
Y 2
 
7.7%
J 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4353
54.6%
ASCII 3614
45.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1573
43.5%
1 336
 
9.3%
- 311
 
8.6%
2 211
 
5.8%
4 209
 
5.8%
3 193
 
5.3%
5 150
 
4.2%
7 127
 
3.5%
0 120
 
3.3%
6 113
 
3.1%
Other values (13) 271
 
7.5%
Hangul
ValueCountFrequency (%)
동 705
16.2%
래 344
 
7.9%
산 340
 
7.8%
부 338
 
7.8%
광 337
 
7.7%
역 336
 
7.7%
시 336
 
7.7%
구 336
 
7.7%
천 108
 
2.5%
온 105
 
2.4%
Other values (112) 1068
24.5%
None
ValueCountFrequency (%)
· 1
100.0%

시설주소(도로명)
Text

Distinct328
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-11T01:44:10.757501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length50
Mean length31.988131
Min length22

Characters and Unicode

Total characters10780
Distinct characters194
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

Unique321 ?
Unique (%)95.3%

Sample

1st row부산광역시 동래구 안남로 23, 지1층 108호 (낙민동, 보림프라자)
2nd row부산광역시 동래구 석사로18번길 41 (사직동)
3rd row부산광역시 동래구 시실로 60 (명륜동)
4th row부산광역시 동래구 안남로 32, B동 (낙민동)
5th row부산광역시 동래구 쇠미로 197, 104동 지하1층 101~103호 (온천동, 동래 지웰)
ValueCountFrequency (%)
동래구 338
 
16.1%
부산광역시 337
 
16.1%
온천동 90
 
4.3%
사직동 83
 
4.0%
2층 48
 
2.3%
안락동 46
 
2.2%
3층 43
 
2.1%
명륜동 43
 
2.1%
지하1층 26
 
1.2%
명장동 23
 
1.1%
Other values (466) 1020
48.6%
2023-12-11T01:44:11.237221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1779
 
16.5%
동 729
 
6.8%
시 372
 
3.5%
래 355
 
3.3%
, 353
 
3.3%
산 341
 
3.2%
( 340
 
3.2%
) 339
 
3.1%
부 338
 
3.1%
광 338
 
3.1%
Other values (184) 5496
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6294
58.4%
Space Separator 1779
 
16.5%
Decimal Number 1602
 
14.9%
Other Punctuation 354
 
3.3%
Open Punctuation 340
 
3.2%
Close Punctuation 339
 
3.1%
Uppercase Letter 37
 
0.3%
Dash Punctuation 26
 
0.2%
Math Symbol 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 729
 
11.6%
시 372
 
5.9%
래 355
 
5.6%
산 341
 
5.4%
부 338
 
5.4%
광 338
 
5.4%
구 338
 
5.4%
역 337
 
5.4%
로 334
 
5.3%
층 249
 
4.0%
Other values (159) 2563
40.7%
Decimal Number
ValueCountFrequency (%)
1 329
20.5%
2 273
17.0%
3 206
12.9%
4 163
10.2%
0 146
9.1%
5 122
 
7.6%
6 101
 
6.3%
8 100
 
6.2%
7 89
 
5.6%
9 73
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 9
24.3%
K 8
21.6%
S 8
21.6%
H 4
10.8%
Y 3
 
8.1%
U 3
 
8.1%
J 1
 
2.7%
A 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 353
99.7%
· 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1779
100.0%
Open Punctuation
ValueCountFrequency (%)
( 340
100.0%
Close Punctuation
ValueCountFrequency (%)
) 339
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6294
58.4%
Common 4449
41.3%
Latin 37
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 729
 
11.6%
시 372
 
5.9%
래 355
 
5.6%
산 341
 
5.4%
부 338
 
5.4%
광 338
 
5.4%
구 338
 
5.4%
역 337
 
5.4%
로 334
 
5.3%
층 249
 
4.0%
Other values (159) 2563
40.7%
Common
ValueCountFrequency (%)
1779
40.0%
, 353
 
7.9%
( 340
 
7.6%
) 339
 
7.6%
1 329
 
7.4%
2 273
 
6.1%
3 206
 
4.6%
4 163
 
3.7%
0 146
 
3.3%
5 122
 
2.7%
Other values (7) 399
 
9.0%
Latin
ValueCountFrequency (%)
B 9
24.3%
K 8
21.6%
S 8
21.6%
H 4
10.8%
Y 3
 
8.1%
U 3
 
8.1%
J 1
 
2.7%
A 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6294
58.4%
ASCII 4485
41.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1779
39.7%
, 353
 
7.9%
( 340
 
7.6%
) 339
 
7.6%
1 329
 
7.3%
2 273
 
6.1%
3 206
 
4.6%
4 163
 
3.6%
0 146
 
3.3%
5 122
 
2.7%
Other values (14) 435
 
9.7%
Hangul
ValueCountFrequency (%)
동 729
 
11.6%
시 372
 
5.9%
래 355
 
5.6%
산 341
 
5.4%
부 338
 
5.4%
광 338
 
5.4%
구 338
 
5.4%
역 337
 
5.4%
로 334
 
5.3%
층 249
 
4.0%
Other values (159) 2563
40.7%
None
ValueCountFrequency (%)
· 1
100.0%

시설전화번호
Text

MISSING 

Distinct185
Distinct (%)98.4%
Missing149
Missing (%)44.2%
Memory size2.8 KiB
2023-12-11T01:44:11.562660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.989362
Min length9

Characters and Unicode

Total characters2254
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

Unique182 ?
Unique (%)96.8%

Sample

1st row051-524-0321
2nd row051-505-1212
3rd row051-556-9090
4th row051-525-7707
5th row051-925-9090
ValueCountFrequency (%)
051-505-0777 2
 
1.1%
051-552-9999 2
 
1.1%
051-552-7774 2
 
1.1%
051-526-7330 1
 
0.5%
051-507-1117 1
 
0.5%
051-557-9682 1
 
0.5%
051-524-0321 1
 
0.5%
051-507-7705 1
 
0.5%
051-558-8689 1
 
0.5%
051-556-0034 1
 
0.5%
Other values (175) 175
93.1%
2023-12-11T01:44:12.053857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 518
23.0%
- 374
16.6%
0 357
15.8%
1 287
12.7%
2 158
 
7.0%
7 149
 
6.6%
3 97
 
4.3%
9 92
 
4.1%
8 78
 
3.5%
6 78
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1880
83.4%
Dash Punctuation 374
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 518
27.6%
0 357
19.0%
1 287
15.3%
2 158
 
8.4%
7 149
 
7.9%
3 97
 
5.2%
9 92
 
4.9%
8 78
 
4.1%
6 78
 
4.1%
4 66
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 374
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2254
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 518
23.0%
- 374
16.6%
0 357
15.8%
1 287
12.7%
2 158
 
7.0%
7 149
 
6.6%
3 97
 
4.3%
9 92
 
4.1%
8 78
 
3.5%
6 78
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2254
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 518
23.0%
- 374
16.6%
0 357
15.8%
1 287
12.7%
2 158
 
7.0%
7 149
 
6.6%
3 97
 
4.3%
9 92
 
4.1%
8 78
 
3.5%
6 78
 
3.5%

시설부지면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct143
Distinct (%)97.3%
Missing190
Missing (%)56.4%
Infinite0
Infinite (%)0.0%
Mean334.8398
Minimum0
Maximum3580
Zeros2
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T01:44:12.210558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile100.382
Q1153.305
median213.11
Q3326.79
95-th percentile821.52
Maximum3580
Range3580
Interquartile range (IQR)173.485

Descriptive statistics

Standard deviation442.14596
Coefficient of variation (CV)1.3204702
Kurtosis28.829406
Mean334.8398
Median Absolute Deviation (MAD)78.11
Skewness4.8942356
Sum49221.45
Variance195493.05
MonotonicityNot monotonic
2023-12-11T01:44:12.391700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
348.36 2
 
0.6%
195.54 2
 
0.6%
0.0 2
 
0.6%
326.79 2
 
0.6%
493.4 1
 
0.3%
489.8 1
 
0.3%
192.24 1
 
0.3%
177.54 1
 
0.3%
228.96 1
 
0.3%
135.8 1
 
0.3%
Other values (133) 133
39.5%
(Missing) 190
56.4%
ValueCountFrequency (%)
0.0 2
0.6%
71.15 1
0.3%
81.38 1
0.3%
95.04 1
0.3%
96.0 1
0.3%
97.2 1
0.3%
98.78 1
0.3%
104.12 1
0.3%
104.76 1
0.3%
105.63 1
0.3%
ValueCountFrequency (%)
3580.0 1
0.3%
2952.0 1
0.3%
1939.86 1
0.3%
1821.6 1
0.3%
1230.0 1
0.3%
1036.16 1
0.3%
955.68 1
0.3%
831.18 1
0.3%
798.98 1
0.3%
776.34 1
0.3%

시설면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct319
Distinct (%)95.2%
Missing2
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean335.63687
Minimum30
Maximum4869.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T01:44:12.582737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile96.553
Q1151.225
median225.95
Q3345.57
95-th percentile763.946
Maximum4869.06
Range4839.06
Interquartile range (IQR)194.345

Descriptive statistics

Standard deviation465.85141
Coefficient of variation (CV)1.3879626
Kurtosis47.324279
Mean335.63687
Median Absolute Deviation (MAD)90.15
Skewness6.2004829
Sum112438.35
Variance217017.54
MonotonicityNot monotonic
2023-12-11T01:44:12.740850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
233.58 3
 
0.9%
326.79 3
 
0.9%
280.8 2
 
0.6%
173.54 2
 
0.6%
175.23 2
 
0.6%
174.79 2
 
0.6%
134.4 2
 
0.6%
195.54 2
 
0.6%
305.07 2
 
0.6%
212.42 2
 
0.6%
Other values (309) 313
92.9%
ValueCountFrequency (%)
30.0 1
0.3%
42.93 1
0.3%
48.14 1
0.3%
59.82 1
0.3%
64.4 1
0.3%
65.5 1
0.3%
71.15 1
0.3%
81.38 1
0.3%
84.91 1
0.3%
86.62 1
0.3%
ValueCountFrequency (%)
4869.06 1
0.3%
4216.81 1
0.3%
2952.0 1
0.3%
2764.0 1
0.3%
2710.75 1
0.3%
1939.86 1
0.3%
1707.47 1
0.3%
1596.92 1
0.3%
1237.98 1
0.3%
1190.9 1
0.3%

건물연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct157
Distinct (%)87.7%
Missing158
Missing (%)46.9%
Infinite0
Infinite (%)0.0%
Mean5510.6656
Minimum0
Maximum222898.94
Zeros5
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T01:44:12.925653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile111.754
Q1655.575
median1148.47
Q32912.71
95-th percentile23195.35
Maximum222898.94
Range222898.94
Interquartile range (IQR)2257.135

Descriptive statistics

Standard deviation19567.184
Coefficient of variation (CV)3.5507841
Kurtosis87.699912
Mean5510.6656
Median Absolute Deviation (MAD)749.63
Skewness8.5046733
Sum986409.15
Variance3.8287468 × 108
MonotonicityNot monotonic
2023-12-11T01:44:13.099887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 5
 
1.5%
23195.35 4
 
1.2%
5241.68 3
 
0.9%
1399.11 2
 
0.6%
2204.52 2
 
0.6%
987.04 2
 
0.6%
1706.27 2
 
0.6%
1497.2 2
 
0.6%
4560.44 2
 
0.6%
3772.26 2
 
0.6%
Other values (147) 153
45.4%
(Missing) 158
46.9%
ValueCountFrequency (%)
0.0 5
1.5%
81.38 1
 
0.3%
87.93 1
 
0.3%
96.0 1
 
0.3%
107.2 1
 
0.3%
112.26 1
 
0.3%
129.0 1
 
0.3%
129.6 1
 
0.3%
142.2 1
 
0.3%
213.84 1
 
0.3%
ValueCountFrequency (%)
222898.94 1
 
0.3%
76389.4 1
 
0.3%
64681.13 2
0.6%
48705.09 1
 
0.3%
42844.95 1
 
0.3%
30146.0 1
 
0.3%
23195.36 1
 
0.3%
23195.35 4
1.2%
22278.93 1
 
0.3%
21338.4 1
 
0.3%

체육도장업상세분류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct12
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
224 
태권도
63 
골프종목
 
19
권투
 
7
합기도
 
6
Other values (7)
 
18

Length

Max length4
Median length4
Mean length3.6676558
Min length2

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 224
66.5%
태권도 63
 
18.7%
골프종목 19
 
5.6%
권투 7
 
2.1%
합기도 6
 
1.8%
검도 5
 
1.5%
유도 5
 
1.5%
우슈 2
 
0.6%
레슬링 2
 
0.6%
야구종목 2
 
0.6%
Other values (2) 2
 
0.6%

Length

2023-12-11T01:44:13.265606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 224
66.5%
태권도 63
 
18.7%
골프종목 19
 
5.6%
권투 7
 
2.1%
합기도 6
 
1.8%
검도 5
 
1.5%
유도 5
 
1.5%
우슈 2
 
0.6%
레슬링 2
 
0.6%
야구종목 2
 
0.6%
Other values (2) 2
 
0.6%

Interactions

2023-12-11T01:44:07.162444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:05.828797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:06.383722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:07.300372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:06.036438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:06.570858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:07.438250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:06.220698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:06.696171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:44:13.357521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종시설부지면적(제곱미터)시설면적(제곱미터)건물연면적(제곱미터)체육도장업상세분류
업종1.0000.7580.7760.6521.000
시설부지면적(제곱미터)0.7581.0000.9880.0000.788
시설면적(제곱미터)0.7760.9881.0000.8550.144
건물연면적(제곱미터)0.6520.0000.8551.0000.349
체육도장업상세분류1.0000.7880.1440.3491.000
2023-12-11T01:44:13.494883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종체육도장업상세분류
업종1.0000.963
체육도장업상세분류0.9631.000
2023-12-11T01:44:13.625393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설부지면적(제곱미터)시설면적(제곱미터)건물연면적(제곱미터)업종체육도장업상세분류
시설부지면적(제곱미터)1.0000.9560.5940.5360.453
시설면적(제곱미터)0.9561.0000.6120.5110.072
건물연면적(제곱미터)0.5940.6121.0000.3220.320
업종0.5360.5110.3221.0000.963
체육도장업상세분류0.4530.0720.3200.9631.000

Missing values

2023-12-11T01:44:07.622186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:44:07.831845image/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.
2023-12-11T01:44:08.057589image/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(지번)시설주소(도로명)시설전화번호시설부지면적(제곱미터)시설면적(제곱미터)건물연면적(제곱미터)체육도장업상세분류
0수영장업키즈스플래쉬(부산본점)부산광역시 동래구 낙민동 84-8 보림프라자 지1층 108호부산광역시 동래구 안남로 23, 지1층 108호 (낙민동, 보림프라자)051-524-0321<NA>369.68993.58<NA>
1수영장업망고키즈수영장(사직점)부산광역시 동래구 사직동 74-18부산광역시 동래구 석사로18번길 41 (사직동)051-505-1212<NA>345.0<NA><NA>
2수영장업아이올림픽 유소년 체육센터부산광역시 동래구 명륜동 96-5부산광역시 동래구 시실로 60 (명륜동)051-556-9090<NA>709.7<NA><NA>
3수영장업골드키즈부산광역시 동래구 낙민동 90-4 B동부산광역시 동래구 안남로 32, B동 (낙민동)051-525-7707<NA>329.7<NA><NA>
4수영장업지니키즈스윔스쿨부산광역시 동래구 온천동 1834 동래 지웰부산광역시 동래구 쇠미로 197, 104동 지하1층 101~103호 (온천동, 동래 지웰)051-925-9090<NA>374.81844.72<NA>
5수영장업(주)케이비스포츠인재교육원부산광역시 동래구 사직동 151-8 여고 플래티넘부산광역시 동래구 미남로 52, 여고 플래티넘 1층 (사직동)051-503-6888<NA>292.98<NA><NA>
6체육도장업복천태권도부산광역시 동래구 복천동 500-1 우성아파트 상가 104호부산광역시 동래구 복천로5번길 34, 상가동 104호 (복천동, 우성아파트)051-558-2422190.9190.9<NA>태권도
7체육도장업수안체육관부산광역시 동래구 수안동 4-11부산광역시 동래구 명륜로63번길 14 (수안동)051-552-7774129.0129.0129.0태권도
8체육도장업대한태권도부산광역시 동래구 온천동 1592-1 동래삼정그린코아포레스트부산광역시 동래구 쇠미로 153, 107동 2층 (온천동, 동래삼정그린코아포레스트)<NA><NA>118.28<NA>태권도
9체육도장업동아태권도부산광역시 동래구 명장동 506-6부산광역시 동래구 명서로 116 (명장동)051-529-964871.1571.15<NA>태권도
업종상호시설주소(지번)시설주소(도로명)시설전화번호시설부지면적(제곱미터)시설면적(제곱미터)건물연면적(제곱미터)체육도장업상세분류
327체육교습업지니어스 음악줄넘기부산광역시 동래구 안락동 448-7부산광역시 동래구 안락로 82, 4층 (안락동)051-526-7330<NA>161.33822.87<NA>
328체육교습업제이에스 축구클럽부산광역시 동래구 안락동 461-2부산광역시 동래구 화현길 8, 2층 (안락동)<NA><NA>295.2733.96<NA>
329체육교습업백호축구클럽부산광역시 동래구 낙민동 76-10 신라하우징부산광역시 동래구 온천천로337번길 12, 신라하우징 2층 (낙민동)<NA><NA>209.52750.77<NA>
330체육교습업히어로 스포츠부산광역시 동래구 사직동 47-3부산광역시 동래구 석사로 15, 지하1층 (사직동)<NA><NA>415.94985.04<NA>
331체육교습업타고나 스포츠 아카데미 4호점부산광역시 동래구 온천동 502-3 롯데백화점부산광역시 동래구 중앙대로 1393, 롯데백화점 10층 (온천동)051-555-8414<NA>30.0<NA><NA>
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