Overview

Dataset statistics

Number of variables10
Number of observations313
Missing cells483
Missing cells (%)15.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.8 KiB
Average record size in memory84.4 B

Variable types

Categorical2
Text4
Numeric4

Dataset

Description부산광역시_동래구_체육시설업소현황_20220823
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 시설부지면적(제곱미터) and 1 other fieldsHigh correlation
시설부지면적(제곱미터) is highly overall correlated with 시설면적(제곱미터) and 3 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 (52.5%)Imbalance
우편번호 has 60 (19.2%) missing valuesMissing
시설전화번호 has 130 (41.5%) missing valuesMissing
시설부지면적(제곱미터) has 163 (52.1%) missing valuesMissing
건물연면적(제곱미터) has 127 (40.6%) missing valuesMissing
건물연면적(제곱미터) has 5 (1.6%) zerosZeros

Reproduction

Analysis started2023-12-10 16:44:15.028067
Analysis finished2023-12-10 16:44:18.560135
Duration3.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
체력단련장업
88 
체육도장업
87 
당구장업
63 
골프연습장업
35 
가상체험 체육시설업
15 
Other values (6)
25 

Length

Max length10
Median length7
Mean length5.4345048
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 88
28.1%
체육도장업 87
27.8%
당구장업 63
20.1%
골프연습장업 35
 
11.2%
가상체험 체육시설업 15
 
4.8%
체육교습업 10
 
3.2%
수영장업 5
 
1.6%
무도학원업 4
 
1.3%
인공암벽장업 3
 
1.0%
종합체육시설업 2
 
0.6%

Length

2023-12-11T01:44:18.638354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
체력단련장업 88
26.8%
체육도장업 87
26.5%
당구장업 63
19.2%
골프연습장업 35
 
10.7%
가상체험 15
 
4.6%
체육시설업 15
 
4.6%
체육교습업 10
 
3.0%
수영장업 5
 
1.5%
무도학원업 4
 
1.2%
인공암벽장업 3
 
0.9%
Other values (2) 3
 
0.9%

상호
Text

Distinct309
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T01:44:18.963789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length7.3258786
Min length2

Characters and Unicode

Total characters2293
Distinct characters358
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

Unique305 ?
Unique (%)97.4%

Sample

1st row키즈스플래쉬(부산본점)
2nd row망고키즈수영장(사직점)
3rd row아이올림픽 유소년 체육센터
4th row골드키즈
5th row지니키즈스윔스쿨
ValueCountFrequency (%)
당구클럽 13
 
2.7%
휘트니스 10
 
2.0%
당구장 10
 
2.0%
동래점 8
 
1.6%
태권도 7
 
1.4%
피트니스 5
 
1.0%
gym 5
 
1.0%
스크린골프 5
 
1.0%
스포츠 4
 
0.8%
골프 4
 
0.8%
Other values (384) 418
85.5%
2023-12-11T01:44:19.482971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
176
 
7.7%
스 113
 
4.9%
구 65
 
2.8%
도 59
 
2.6%
당 58
 
2.5%
장 58
 
2.5%
프 49
 
2.1%
골 46
 
2.0%
클 45
 
2.0%
럽 43
 
1.9%
Other values (348) 1581
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1942
84.7%
Space Separator 176
 
7.7%
Uppercase Letter 102
 
4.4%
Lowercase Letter 34
 
1.5%
Decimal Number 14
 
0.6%
Open Punctuation 11
 
0.5%
Close Punctuation 11
 
0.5%
Other Punctuation 2
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 113
 
5.8%
구 65
 
3.3%
도 59
 
3.0%
당 58
 
3.0%
장 58
 
3.0%
프 49
 
2.5%
골 46
 
2.4%
클 45
 
2.3%
럽 43
 
2.2%
트 43
 
2.2%
Other values (297) 1363
70.2%
Uppercase Letter
ValueCountFrequency (%)
M 12
 
11.8%
G 10
 
9.8%
P 9
 
8.8%
Y 7
 
6.9%
T 7
 
6.9%
I 6
 
5.9%
J 5
 
4.9%
B 5
 
4.9%
A 4
 
3.9%
N 4
 
3.9%
Other values (14) 33
32.4%
Lowercase Letter
ValueCountFrequency (%)
o 5
14.7%
i 3
8.8%
s 3
8.8%
m 3
8.8%
n 3
8.8%
c 3
8.8%
r 3
8.8%
e 2
 
5.9%
y 2
 
5.9%
d 2
 
5.9%
Other values (4) 5
14.7%
Decimal Number
ValueCountFrequency (%)
3 3
21.4%
1 3
21.4%
5 2
14.3%
6 2
14.3%
9 2
14.3%
2 1
 
7.1%
4 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
' 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
176
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1942
84.7%
Common 214
 
9.3%
Latin 137
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 113
 
5.8%
구 65
 
3.3%
도 59
 
3.0%
당 58
 
3.0%
장 58
 
3.0%
프 49
 
2.5%
골 46
 
2.4%
클 45
 
2.3%
럽 43
 
2.2%
트 43
 
2.2%
Other values (297) 1363
70.2%
Latin
ValueCountFrequency (%)
M 12
 
8.8%
G 10
 
7.3%
P 9
 
6.6%
Y 7
 
5.1%
T 7
 
5.1%
I 6
 
4.4%
o 5
 
3.6%
J 5
 
3.6%
B 5
 
3.6%
A 4
 
2.9%
Other values (29) 67
48.9%
Common
ValueCountFrequency (%)
176
82.2%
( 11
 
5.1%
) 11
 
5.1%
3 3
 
1.4%
1 3
 
1.4%
5 2
 
0.9%
6 2
 
0.9%
9 2
 
0.9%
2 1
 
0.5%
' 1
 
0.5%
Other values (2) 2
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1942
84.7%
ASCII 350
 
15.3%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
176
50.3%
M 12
 
3.4%
( 11
 
3.1%
) 11
 
3.1%
G 10
 
2.9%
P 9
 
2.6%
Y 7
 
2.0%
T 7
 
2.0%
I 6
 
1.7%
o 5
 
1.4%
Other values (40) 96
27.4%
Hangul
ValueCountFrequency (%)
스 113
 
5.8%
구 65
 
3.3%
도 59
 
3.0%
당 58
 
3.0%
장 58
 
3.0%
프 49
 
2.5%
골 46
 
2.4%
클 45
 
2.3%
럽 43
 
2.2%
트 43
 
2.2%
Other values (297) 1363
70.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

우편번호
Real number (ℝ)

MISSING 

Distinct106
Distinct (%)41.9%
Missing60
Missing (%)19.2%
Infinite0
Infinite (%)0.0%
Mean47806.909
Minimum47706
Maximum47905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T01:44:19.659127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47706
5-th percentile47709.6
Q147744
median47818
Q347865
95-th percentile47898
Maximum47905
Range199
Interquartile range (IQR)121

Descriptive statistics

Standard deviation62.796184
Coefficient of variation (CV)0.0013135378
Kurtosis-1.4154323
Mean47806.909
Median Absolute Deviation (MAD)50
Skewness-0.14298978
Sum12095148
Variance3943.3608
MonotonicityNot monotonic
2023-12-11T01:44:19.855689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47837 12
 
3.8%
47744 10
 
3.2%
47865 10
 
3.2%
47709 10
 
3.2%
47866 9
 
2.9%
47736 7
 
2.2%
47738 6
 
1.9%
47863 5
 
1.6%
47750 4
 
1.3%
47864 4
 
1.3%
Other values (96) 176
56.2%
(Missing) 60
 
19.2%
ValueCountFrequency (%)
47706 1
 
0.3%
47708 2
 
0.6%
47709 10
3.2%
47710 3
 
1.0%
47711 4
 
1.3%
47712 3
 
1.0%
47714 1
 
0.3%
47715 1
 
0.3%
47719 1
 
0.3%
47720 1
 
0.3%
ValueCountFrequency (%)
47905 1
 
0.3%
47903 2
0.6%
47901 2
0.6%
47900 2
0.6%
47899 4
1.3%
47898 3
1.0%
47895 3
1.0%
47894 1
 
0.3%
47893 1
 
0.3%
47892 3
1.0%

시설주소(지번)
Text

Distinct293
Distinct (%)93.9%
Missing1
Missing (%)0.3%
Memory size2.6 KiB
2023-12-11T01:44:20.272306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length42
Mean length23.711538
Min length18

Characters and Unicode

Total characters7398
Distinct characters134
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

Unique279 ?
Unique (%)89.4%

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 312
21.1%
동래구 312
21.1%
온천동 90
 
6.1%
사직동 80
 
5.4%
안락동 55
 
3.7%
명륜동 43
 
2.9%
3층 27
 
1.8%
명장동 24
 
1.6%
2층 20
 
1.3%
수안동 14
 
0.9%
Other values (373) 505
34.1%
2023-12-11T01:44:20.885455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1463
19.8%
동 656
 
8.9%
래 319
 
4.3%
부 314
 
4.2%
산 314
 
4.2%
광 313
 
4.2%
역 312
 
4.2%
시 312
 
4.2%
구 312
 
4.2%
1 311
 
4.2%
Other values (124) 2772
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4026
54.4%
Decimal Number 1568
 
21.2%
Space Separator 1463
 
19.8%
Dash Punctuation 289
 
3.9%
Uppercase Letter 24
 
0.3%
Other Punctuation 14
 
0.2%
Close Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%
Math Symbol 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 656
16.3%
래 319
 
7.9%
부 314
 
7.8%
산 314
 
7.8%
광 313
 
7.8%
역 312
 
7.7%
시 312
 
7.7%
구 312
 
7.7%
층 98
 
2.4%
천 96
 
2.4%
Other values (101) 980
24.3%
Decimal Number
ValueCountFrequency (%)
1 311
19.8%
2 205
13.1%
4 198
12.6%
3 178
11.4%
5 143
9.1%
7 114
 
7.3%
6 111
 
7.1%
0 111
 
7.1%
9 106
 
6.8%
8 91
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
B 6
25.0%
K 6
25.0%
S 5
20.8%
H 3
12.5%
U 2
 
8.3%
Y 2
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 13
92.9%
· 1
 
7.1%
Space Separator
ValueCountFrequency (%)
1463
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 289
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4026
54.4%
Common 3348
45.3%
Latin 24
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 656
16.3%
래 319
 
7.9%
부 314
 
7.8%
산 314
 
7.8%
광 313
 
7.8%
역 312
 
7.7%
시 312
 
7.7%
구 312
 
7.7%
층 98
 
2.4%
천 96
 
2.4%
Other values (101) 980
24.3%
Common
ValueCountFrequency (%)
1463
43.7%
1 311
 
9.3%
- 289
 
8.6%
2 205
 
6.1%
4 198
 
5.9%
3 178
 
5.3%
5 143
 
4.3%
7 114
 
3.4%
6 111
 
3.3%
0 111
 
3.3%
Other values (7) 225
 
6.7%
Latin
ValueCountFrequency (%)
B 6
25.0%
K 6
25.0%
S 5
20.8%
H 3
12.5%
U 2
 
8.3%
Y 2
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4026
54.4%
ASCII 3371
45.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1463
43.4%
1 311
 
9.2%
- 289
 
8.6%
2 205
 
6.1%
4 198
 
5.9%
3 178
 
5.3%
5 143
 
4.2%
7 114
 
3.4%
6 111
 
3.3%
0 111
 
3.3%
Other values (12) 248
 
7.4%
Hangul
ValueCountFrequency (%)
동 656
16.3%
래 319
 
7.9%
부 314
 
7.8%
산 314
 
7.8%
광 313
 
7.8%
역 312
 
7.7%
시 312
 
7.7%
구 312
 
7.7%
층 98
 
2.4%
천 96
 
2.4%
Other values (101) 980
24.3%
None
ValueCountFrequency (%)
· 1
100.0%

시설주소(도로명)
Text

Distinct305
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T01:44:21.368656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length50
Mean length31.738019
Min length22

Characters and Unicode

Total characters9934
Distinct characters186
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

Unique299 ?
Unique (%)95.5%

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 314
 
16.3%
부산광역시 313
 
16.2%
온천동 78
 
4.0%
사직동 75
 
3.9%
안락동 46
 
2.4%
2층 44
 
2.3%
명륜동 40
 
2.1%
3층 39
 
2.0%
지하1층 22
 
1.1%
명장동 22
 
1.1%
Other values (442) 938
48.6%
2023-12-11T01:44:21.987883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1637
 
16.5%
동 677
 
6.8%
시 346
 
3.5%
래 329
 
3.3%
, 320
 
3.2%
산 315
 
3.2%
( 315
 
3.2%
부 314
 
3.2%
광 314
 
3.2%
구 314
 
3.2%
Other values (176) 5053
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5805
58.4%
Space Separator 1637
 
16.5%
Decimal Number 1476
 
14.9%
Other Punctuation 321
 
3.2%
Open Punctuation 315
 
3.2%
Close Punctuation 314
 
3.2%
Uppercase Letter 35
 
0.4%
Dash Punctuation 24
 
0.2%
Math Symbol 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 677
 
11.7%
시 346
 
6.0%
래 329
 
5.7%
산 315
 
5.4%
부 314
 
5.4%
광 314
 
5.4%
구 314
 
5.4%
역 313
 
5.4%
로 310
 
5.3%
층 222
 
3.8%
Other values (152) 2351
40.5%
Decimal Number
ValueCountFrequency (%)
1 294
19.9%
2 257
17.4%
3 184
12.5%
4 151
10.2%
0 140
9.5%
5 108
 
7.3%
8 100
 
6.8%
6 94
 
6.4%
7 82
 
5.6%
9 66
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 9
25.7%
K 8
22.9%
S 7
20.0%
H 4
11.4%
U 3
 
8.6%
Y 3
 
8.6%
A 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 320
99.7%
· 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1637
100.0%
Open Punctuation
ValueCountFrequency (%)
( 315
100.0%
Close Punctuation
ValueCountFrequency (%)
) 314
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5805
58.4%
Common 4094
41.2%
Latin 35
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 677
 
11.7%
시 346
 
6.0%
래 329
 
5.7%
산 315
 
5.4%
부 314
 
5.4%
광 314
 
5.4%
구 314
 
5.4%
역 313
 
5.4%
로 310
 
5.3%
층 222
 
3.8%
Other values (152) 2351
40.5%
Common
ValueCountFrequency (%)
1637
40.0%
, 320
 
7.8%
( 315
 
7.7%
) 314
 
7.7%
1 294
 
7.2%
2 257
 
6.3%
3 184
 
4.5%
4 151
 
3.7%
0 140
 
3.4%
5 108
 
2.6%
Other values (7) 374
 
9.1%
Latin
ValueCountFrequency (%)
B 9
25.7%
K 8
22.9%
S 7
20.0%
H 4
11.4%
U 3
 
8.6%
Y 3
 
8.6%
A 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5805
58.4%
ASCII 4128
41.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1637
39.7%
, 320
 
7.8%
( 315
 
7.6%
) 314
 
7.6%
1 294
 
7.1%
2 257
 
6.2%
3 184
 
4.5%
4 151
 
3.7%
0 140
 
3.4%
5 108
 
2.6%
Other values (13) 408
 
9.9%
Hangul
ValueCountFrequency (%)
동 677
 
11.7%
시 346
 
6.0%
래 329
 
5.7%
산 315
 
5.4%
부 314
 
5.4%
광 314
 
5.4%
구 314
 
5.4%
역 313
 
5.4%
로 310
 
5.3%
층 222
 
3.8%
Other values (152) 2351
40.5%
None
ValueCountFrequency (%)
· 1
100.0%

시설전화번호
Text

MISSING 

Distinct181
Distinct (%)98.9%
Missing130
Missing (%)41.5%
Memory size2.6 KiB
2023-12-11T01:44:22.347772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.016393
Min length12

Characters and Unicode

Total characters2199
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

Unique179 ?
Unique (%)97.8%

Sample

1st row051-524-0321
2nd row051-505-1212
3rd row051-556-9090
4th row051-525-7707
5th row051-925-9090
ValueCountFrequency (%)
051-552-9999 2
 
1.1%
051-505-0777 2
 
1.1%
051-532-0205 1
 
0.5%
070-4036-2400 1
 
0.5%
051-506-0852 1
 
0.5%
051-553-9682 1
 
0.5%
051-557-6471 1
 
0.5%
051-555-0031 1
 
0.5%
051-531-5657 1
 
0.5%
051-528-3030 1
 
0.5%
Other values (171) 171
93.4%
2023-12-11T01:44:22.915154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 497
22.6%
- 366
16.6%
0 351
16.0%
1 279
12.7%
2 154
 
7.0%
7 149
 
6.8%
3 97
 
4.4%
9 86
 
3.9%
6 77
 
3.5%
4 72
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1833
83.4%
Dash Punctuation 366
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 497
27.1%
0 351
19.1%
1 279
15.2%
2 154
 
8.4%
7 149
 
8.1%
3 97
 
5.3%
9 86
 
4.7%
6 77
 
4.2%
4 72
 
3.9%
8 71
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 366
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2199
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 497
22.6%
- 366
16.6%
0 351
16.0%
1 279
12.7%
2 154
 
7.0%
7 149
 
6.8%
3 97
 
4.4%
9 86
 
3.9%
6 77
 
3.5%
4 72
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2199
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 497
22.6%
- 366
16.6%
0 351
16.0%
1 279
12.7%
2 154
 
7.0%
7 149
 
6.8%
3 97
 
4.4%
9 86
 
3.9%
6 77
 
3.5%
4 72
 
3.3%

시설부지면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct146
Distinct (%)97.3%
Missing163
Missing (%)52.1%
Infinite0
Infinite (%)0.0%
Mean330.8514
Minimum0
Maximum3580
Zeros2
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T01:44:23.205089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile101.183
Q1149.735
median212.24
Q3326.0875
95-th percentile816.69
Maximum3580
Range3580
Interquartile range (IQR)176.3525

Descriptive statistics

Standard deviation438.55301
Coefficient of variation (CV)1.3255286
Kurtosis29.383477
Mean330.8514
Median Absolute Deviation (MAD)74.155
Skewness4.9389898
Sum49627.71
Variance192328.74
MonotonicityNot monotonic
2023-12-11T01:44:23.411419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2
 
0.6%
348.36 2
 
0.6%
195.54 2
 
0.6%
326.79 2
 
0.6%
495.26 1
 
0.3%
236.13 1
 
0.3%
242.77 1
 
0.3%
220.6 1
 
0.3%
769.0 1
 
0.3%
468.36 1
 
0.3%
Other values (136) 136
43.5%
(Missing) 163
52.1%
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 

Distinct299
Distinct (%)96.1%
Missing2
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean320.60125
Minimum30
Maximum4869.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T01:44:23.601602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile96.395
Q1147.465
median215.76
Q3330.655
95-th percentile758.26
Maximum4869.06
Range4839.06
Interquartile range (IQR)183.19

Descriptive statistics

Standard deviation452.94567
Coefficient of variation (CV)1.4128007
Kurtosis55.690304
Mean320.60125
Median Absolute Deviation (MAD)82.36
Skewness6.7723795
Sum99706.99
Variance205159.78
MonotonicityNot monotonic
2023-12-11T01:44:23.776604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
233.58 3
 
1.0%
280.8 2
 
0.6%
237.6 2
 
0.6%
326.79 2
 
0.6%
135.0 2
 
0.6%
478.0 2
 
0.6%
199.33 2
 
0.6%
195.54 2
 
0.6%
134.4 2
 
0.6%
212.42 2
 
0.6%
Other values (289) 290
92.7%
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%
2710.75 1
0.3%
1939.86 1
0.3%
1707.47 1
0.3%
1190.9 1
0.3%
1086.29 1
0.3%
955.68 1
0.3%
897.6 1
0.3%

건물연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct163
Distinct (%)87.6%
Missing127
Missing (%)40.6%
Infinite0
Infinite (%)0.0%
Mean5240.7475
Minimum0
Maximum222898.94
Zeros5
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T01:44:23.938682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile116.445
Q1654.3525
median1137.34
Q32767.585
95-th percentile23195.35
Maximum222898.94
Range222898.94
Interquartile range (IQR)2113.2325

Descriptive statistics

Standard deviation19172.71
Coefficient of variation (CV)3.6583922
Kurtosis92.056444
Mean5240.7475
Median Absolute Deviation (MAD)697.77
Skewness8.7332429
Sum974779.03
Variance3.675928 × 108
MonotonicityNot monotonic
2023-12-11T01:44:24.107546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 5
 
1.6%
23195.35 4
 
1.3%
5241.68 3
 
1.0%
1399.11 2
 
0.6%
2204.52 2
 
0.6%
987.04 2
 
0.6%
1706.27 2
 
0.6%
3430.7 2
 
0.6%
1497.2 2
 
0.6%
4560.44 2
 
0.6%
Other values (153) 160
51.1%
(Missing) 127
40.6%
ValueCountFrequency (%)
0.0 5
1.6%
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
1.3%
21338.4 1
 
0.3%
9988.89 1
 
0.3%

체육도장업상세분류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
211 
태권도
61 
골프종목
 
13
권투
 
7
검도
 
6
Other values (5)
 
15

Length

Max length4
Median length4
Mean length3.6645367
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 211
67.4%
태권도 61
 
19.5%
골프종목 13
 
4.2%
권투 7
 
2.2%
검도 6
 
1.9%
합기도 6
 
1.9%
유도 3
 
1.0%
우슈 2
 
0.6%
레슬링 2
 
0.6%
야구종목 2
 
0.6%

Length

2023-12-11T01:44:24.304116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:44:24.439276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 211
67.4%
태권도 61
 
19.5%
골프종목 13
 
4.2%
권투 7
 
2.2%
검도 6
 
1.9%
합기도 6
 
1.9%
유도 3
 
1.0%
우슈 2
 
0.6%
레슬링 2
 
0.6%
야구종목 2
 
0.6%

Interactions

2023-12-11T01:44:17.523917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:15.721100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:16.193813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:16.728559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:17.651421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:15.852821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:16.323822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:16.873937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:17.755320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:15.983512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:16.454057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:17.333019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:17.877499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:16.096228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:16.580693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:17.434199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:44:24.561301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종우편번호시설부지면적(제곱미터)시설면적(제곱미터)건물연면적(제곱미터)체육도장업상세분류
업종1.0000.2630.7610.7960.6561.000
우편번호0.2631.0000.0000.0000.4690.000
시설부지면적(제곱미터)0.7610.0001.0000.9880.0000.857
시설면적(제곱미터)0.7960.0000.9881.0000.8560.505
건물연면적(제곱미터)0.6560.4690.0000.8561.0000.364
체육도장업상세분류1.0000.0000.8570.5050.3641.000
2023-12-11T01:44:24.695259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종체육도장업상세분류
업종1.0000.964
체육도장업상세분류0.9641.000
2023-12-11T01:44:24.787548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호시설부지면적(제곱미터)시설면적(제곱미터)건물연면적(제곱미터)업종체육도장업상세분류
우편번호1.0000.0580.021-0.0100.1150.000
시설부지면적(제곱미터)0.0581.0000.9590.5970.5400.536
시설면적(제곱미터)0.0210.9591.0000.6180.5370.248
건물연면적(제곱미터)-0.0100.5970.6181.0000.3250.336
업종0.1150.5400.5370.3251.0000.964
체육도장업상세분류0.0000.5360.2480.3360.9641.000

Missing values

2023-12-11T01:44:18.040921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:44:18.258717image/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.
2023-12-11T01:44:18.452373image/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

업종상호우편번호시설주소(지번)시설주소(도로명)시설전화번호시설부지면적(제곱미터)시설면적(제곱미터)건물연면적(제곱미터)체육도장업상세분류
0수영장업키즈스플래쉬(부산본점)47892부산광역시 동래구 낙민동 84-8 보림프라자 지1층 108호부산광역시 동래구 안남로 23, 지1층 108호 (낙민동, 보림프라자)051-524-0321<NA>369.68993.58<NA>
1수영장업망고키즈수영장(사직점)47867부산광역시 동래구 사직동 74-18부산광역시 동래구 석사로18번길 41 (사직동)051-505-1212<NA>345.0<NA><NA>
2수영장업아이올림픽 유소년 체육센터47744부산광역시 동래구 명륜동 96-5부산광역시 동래구 시실로 60 (명륜동)051-556-9090<NA>709.7<NA><NA>
3수영장업골드키즈47903부산광역시 동래구 낙민동 90-4 B동부산광역시 동래구 안남로 32, B동 (낙민동)051-525-7707<NA>329.7<NA><NA>
4수영장업지니키즈스윔스쿨47869부산광역시 동래구 온천동 1834 동래 지웰부산광역시 동래구 쇠미로 197, 104동 지하1층 101~103호 (온천동, 동래 지웰)051-925-9090<NA>374.81844.72<NA>
5체육도장업복천태권도47803부산광역시 동래구 복천동 500-1 우성아파트 상가 104호부산광역시 동래구 복천로5번길 34, 상가동 104호 (복천동, 우성아파트)051-558-2422190.9190.9<NA>태권도
6체육도장업수안체육관47818부산광역시 동래구 수안동 4-11부산광역시 동래구 명륜로63번길 14 (수안동)051-552-7774129.0129.0129.0태권도
7체육도장업대한태권도47869부산광역시 동래구 온천동 1592-1 동래삼정그린코아포레스트부산광역시 동래구 쇠미로 153, 107동 2층 (온천동, 동래삼정그린코아포레스트)<NA><NA>118.28<NA>태권도
8체육도장업동아태권도47759부산광역시 동래구 명장동 506-6부산광역시 동래구 명서로 116 (명장동)051-529-964871.1571.15<NA>태권도
9체육도장업낙민체육관47878부산광역시 동래구 낙민동 213-5부산광역시 동래구 충렬대로272번길 26, 1,2층 (낙민동)<NA>133.28214.35431.45태권도
업종상호우편번호시설주소(지번)시설주소(도로명)시설전화번호시설부지면적(제곱미터)시설면적(제곱미터)건물연면적(제곱미터)체육도장업상세분류
303체육교습업줄넘기세상 부산본점47865부산광역시 동래구 사직동 89-19부산광역시 동래구 사직로58번길 9, 2층 (사직동)<NA><NA>280.15967.74<NA>
304체육교습업명장 줄넘기세상 교육원47769부산광역시 동래구 명장동 153-27부산광역시 동래구 명장로 121, 지하1층 (명장동)051-532-0205<NA>125.21409.98<NA>
305체육교습업지니어스 음악줄넘기47790부산광역시 동래구 안락동 448-7부산광역시 동래구 안락로 82, 4층 (안락동)051-526-7330<NA>161.33822.87<NA>
306체육교습업제이에스 축구클럽47795부산광역시 동래구 안락동 461-2부산광역시 동래구 화현길 8, 2층 (안락동)<NA><NA>295.2733.96<NA>
307체육교습업백호축구클럽47885부산광역시 동래구 낙민동 76-10 신라하우징부산광역시 동래구 온천천로337번길 12, 신라하우징 2층 (낙민동)<NA><NA>209.52750.77<NA>
308체육교습업히어로 스포츠47859부산광역시 동래구 사직동 47-3부산광역시 동래구 석사로 15, 지하1층 (사직동)<NA><NA>415.94985.04<NA>
309체육교습업타고나 스포츠 아카데미 4호점47727부산광역시 동래구 온천동 502-3 롯데백화점부산광역시 동래구 중앙대로 1393, 롯데백화점 10층 (온천동)051-555-8414<NA>30.0<NA><NA>
310인공암벽장업죠스클라이밍47865부산광역시 동래구 사직동 92-8 호영빌딩부산광역시 동래구 사직로 48, 호영빌딩 7층 (사직동)<NA><NA>280.82204.52<NA>
311인공암벽장업패밀리 클라이밍센터47858부산광역시 동래구 사직동 71-24부산광역시 동래구 석사로 42-1, 지하1층 (사직동)051-506-9915<NA>283.141401.39<NA>
312인공암벽장업락오디세이 동래47893부산광역시 동래구 낙민동 91-3부산광역시 동래구 안남로31번길 6, 1,2층 (낙민동)<NA><NA>310.0597.17<NA>