Overview

Dataset statistics

Number of variables5
Number of observations289
Missing cells138
Missing cells (%)9.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.7 KiB
Average record size in memory41.5 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description서울시 서초구에서 제공하는 영업중 헬스장 현황(2023.08.16 기준) 데이터 정보(상호, 시설 주소) 자료입니다.
Author서울특별시 서초구
URLhttps://www.data.go.kr/data/15074392/fileData.do

Alerts

연번 is highly overall correlated with 기타유의사항High correlation
기타유의사항 is highly overall correlated with 연번High correlation
시설전화번호 has 138 (47.8%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:20:23.322779
Analysis finished2023-12-12 14:20:23.997140
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct289
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean145
Minimum1
Maximum289
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-12T23:20:24.082311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.4
Q173
median145
Q3217
95-th percentile274.6
Maximum289
Range288
Interquartile range (IQR)144

Descriptive statistics

Standard deviation83.571327
Coefficient of variation (CV)0.57635398
Kurtosis-1.2
Mean145
Median Absolute Deviation (MAD)72
Skewness0
Sum41905
Variance6984.1667
MonotonicityStrictly increasing
2023-12-12T23:20:24.216574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
218 1
 
0.3%
198 1
 
0.3%
197 1
 
0.3%
196 1
 
0.3%
195 1
 
0.3%
194 1
 
0.3%
193 1
 
0.3%
192 1
 
0.3%
191 1
 
0.3%
Other values (279) 279
96.5%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
289 1
0.3%
288 1
0.3%
287 1
0.3%
286 1
0.3%
285 1
0.3%
284 1
0.3%
283 1
0.3%
282 1
0.3%
281 1
0.3%
280 1
0.3%

상호
Text

Distinct287
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-12T23:20:24.613244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length8.5294118
Min length1

Characters and Unicode

Total characters2465
Distinct characters332
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique285 ?
Unique (%)98.6%

Sample

1st row서초헬스크럽
2nd row그린헬스
3rd row현대헬스
4th row헬스토피아
5th row동호헬스클럽
ValueCountFrequency (%)
pt 14
 
2.9%
휘트니스 11
 
2.2%
gym 10
 
2.0%
피트니스 10
 
2.0%
주식회사 7
 
1.4%
studio 7
 
1.4%
fitness 7
 
1.4%
서초점 6
 
1.2%
스튜디오 6
 
1.2%
주)케이디스포츠 5
 
1.0%
Other values (356) 407
83.1%
2023-12-12T23:20:25.074568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
201
 
8.2%
스 163
 
6.6%
트 81
 
3.3%
짐 79
 
3.2%
이 68
 
2.8%
니 67
 
2.7%
T 44
 
1.8%
디 42
 
1.7%
) 38
 
1.5%
피 37
 
1.5%
Other values (322) 1645
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1715
69.6%
Uppercase Letter 242
 
9.8%
Lowercase Letter 205
 
8.3%
Space Separator 201
 
8.2%
Close Punctuation 38
 
1.5%
Open Punctuation 35
 
1.4%
Decimal Number 19
 
0.8%
Other Punctuation 8
 
0.3%
Dash Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 163
 
9.5%
트 81
 
4.7%
짐 79
 
4.6%
이 68
 
4.0%
니 67
 
3.9%
디 42
 
2.4%
피 37
 
2.2%
점 33
 
1.9%
휘 33
 
1.9%
포 29
 
1.7%
Other values (259) 1083
63.1%
Uppercase Letter
ValueCountFrequency (%)
T 44
18.2%
P 28
11.6%
M 18
 
7.4%
G 18
 
7.4%
S 14
 
5.8%
O 13
 
5.4%
Y 12
 
5.0%
A 11
 
4.5%
F 10
 
4.1%
B 9
 
3.7%
Other values (13) 65
26.9%
Lowercase Letter
ValueCountFrequency (%)
e 24
11.7%
t 22
10.7%
i 20
9.8%
s 18
 
8.8%
a 17
 
8.3%
n 14
 
6.8%
y 14
 
6.8%
o 11
 
5.4%
r 10
 
4.9%
m 10
 
4.9%
Other values (12) 45
22.0%
Decimal Number
ValueCountFrequency (%)
2 5
26.3%
4 3
15.8%
3 2
 
10.5%
6 2
 
10.5%
5 2
 
10.5%
9 2
 
10.5%
1 1
 
5.3%
7 1
 
5.3%
0 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
& 3
37.5%
. 3
37.5%
, 1
 
12.5%
' 1
 
12.5%
Space Separator
ValueCountFrequency (%)
201
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1715
69.6%
Latin 447
 
18.1%
Common 303
 
12.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 163
 
9.5%
트 81
 
4.7%
짐 79
 
4.6%
이 68
 
4.0%
니 67
 
3.9%
디 42
 
2.4%
피 37
 
2.2%
점 33
 
1.9%
휘 33
 
1.9%
포 29
 
1.7%
Other values (259) 1083
63.1%
Latin
ValueCountFrequency (%)
T 44
 
9.8%
P 28
 
6.3%
e 24
 
5.4%
t 22
 
4.9%
i 20
 
4.5%
M 18
 
4.0%
G 18
 
4.0%
s 18
 
4.0%
a 17
 
3.8%
n 14
 
3.1%
Other values (35) 224
50.1%
Common
ValueCountFrequency (%)
201
66.3%
) 38
 
12.5%
( 35
 
11.6%
2 5
 
1.7%
& 3
 
1.0%
. 3
 
1.0%
4 3
 
1.0%
3 2
 
0.7%
6 2
 
0.7%
5 2
 
0.7%
Other values (8) 9
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1715
69.6%
ASCII 750
30.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
201
26.8%
T 44
 
5.9%
) 38
 
5.1%
( 35
 
4.7%
P 28
 
3.7%
e 24
 
3.2%
t 22
 
2.9%
i 20
 
2.7%
M 18
 
2.4%
G 18
 
2.4%
Other values (53) 302
40.3%
Hangul
ValueCountFrequency (%)
스 163
 
9.5%
트 81
 
4.7%
짐 79
 
4.6%
이 68
 
4.0%
니 67
 
3.9%
디 42
 
2.4%
피 37
 
2.2%
점 33
 
1.9%
휘 33
 
1.9%
포 29
 
1.7%
Other values (259) 1083
63.1%

시설주소(도로명)
Text

Distinct287
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-12T23:20:25.333071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length45
Mean length34.591696
Min length23

Characters and Unicode

Total characters9997
Distinct characters267
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique285 ?
Unique (%)98.6%

Sample

1st row서울특별시 서초구 사평대로 349 (반포동,2층)
2nd row서울특별시 서초구 동광로 18 (방배동)
3rd row서울특별시 서초구 방배천로 22 (방배동,3층)
4th row서울특별시 서초구 사평대로 362 (서초동,(3층))
5th row서울특별시 서초구 고무래로10길 17 (반포동,4층)
ValueCountFrequency (%)
서울특별시 289
 
15.2%
서초구 289
 
15.2%
서초동 114
 
6.0%
지하1층 60
 
3.1%
방배동 55
 
2.9%
2층 40
 
2.1%
반포동 39
 
2.0%
3층 22
 
1.2%
강남대로 19
 
1.0%
잠원동 18
 
0.9%
Other values (572) 960
50.4%
2023-12-12T23:20:25.714238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1643
 
16.4%
서 826
 
8.3%
초 511
 
5.1%
1 356
 
3.6%
, 337
 
3.4%
동 334
 
3.3%
) 315
 
3.2%
( 315
 
3.2%
시 298
 
3.0%
구 293
 
2.9%
Other values (257) 4769
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5883
58.8%
Space Separator 1643
 
16.4%
Decimal Number 1402
 
14.0%
Other Punctuation 342
 
3.4%
Close Punctuation 315
 
3.2%
Open Punctuation 315
 
3.2%
Uppercase Letter 54
 
0.5%
Dash Punctuation 29
 
0.3%
Lowercase Letter 10
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 826
 
14.0%
초 511
 
8.7%
동 334
 
5.7%
시 298
 
5.1%
구 293
 
5.0%
울 291
 
4.9%
로 290
 
4.9%
별 289
 
4.9%
특 289
 
4.9%
층 248
 
4.2%
Other values (211) 2214
37.6%
Uppercase Letter
ValueCountFrequency (%)
B 14
25.9%
E 7
13.0%
R 5
 
9.3%
O 3
 
5.6%
G 3
 
5.6%
T 2
 
3.7%
A 2
 
3.7%
N 2
 
3.7%
S 2
 
3.7%
W 2
 
3.7%
Other values (9) 12
22.2%
Decimal Number
ValueCountFrequency (%)
1 356
25.4%
2 248
17.7%
3 193
13.8%
4 128
 
9.1%
0 109
 
7.8%
5 98
 
7.0%
7 88
 
6.3%
6 78
 
5.6%
9 55
 
3.9%
8 49
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
b 2
20.0%
s 2
20.0%
o 1
10.0%
r 1
10.0%
e 1
10.0%
v 1
10.0%
i 1
10.0%
f 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 337
98.5%
& 2
 
0.6%
/ 2
 
0.6%
@ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1643
100.0%
Close Punctuation
ValueCountFrequency (%)
) 315
100.0%
Open Punctuation
ValueCountFrequency (%)
( 315
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5883
58.8%
Common 4050
40.5%
Latin 64
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 826
 
14.0%
초 511
 
8.7%
동 334
 
5.7%
시 298
 
5.1%
구 293
 
5.0%
울 291
 
4.9%
로 290
 
4.9%
별 289
 
4.9%
특 289
 
4.9%
층 248
 
4.2%
Other values (211) 2214
37.6%
Latin
ValueCountFrequency (%)
B 14
21.9%
E 7
 
10.9%
R 5
 
7.8%
O 3
 
4.7%
G 3
 
4.7%
b 2
 
3.1%
T 2
 
3.1%
A 2
 
3.1%
s 2
 
3.1%
N 2
 
3.1%
Other values (17) 22
34.4%
Common
ValueCountFrequency (%)
1643
40.6%
1 356
 
8.8%
, 337
 
8.3%
) 315
 
7.8%
( 315
 
7.8%
2 248
 
6.1%
3 193
 
4.8%
4 128
 
3.2%
0 109
 
2.7%
5 98
 
2.4%
Other values (9) 308
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5883
58.8%
ASCII 4114
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1643
39.9%
1 356
 
8.7%
, 337
 
8.2%
) 315
 
7.7%
( 315
 
7.7%
2 248
 
6.0%
3 193
 
4.7%
4 128
 
3.1%
0 109
 
2.6%
5 98
 
2.4%
Other values (36) 372
 
9.0%
Hangul
ValueCountFrequency (%)
서 826
 
14.0%
초 511
 
8.7%
동 334
 
5.7%
시 298
 
5.1%
구 293
 
5.0%
울 291
 
4.9%
로 290
 
4.9%
별 289
 
4.9%
특 289
 
4.9%
층 248
 
4.2%
Other values (211) 2214
37.6%

시설전화번호
Text

MISSING 

Distinct150
Distinct (%)99.3%
Missing138
Missing (%)47.8%
Memory size2.4 KiB
2023-12-12T23:20:25.935672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length11.463576
Min length11

Characters and Unicode

Total characters1731
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique149 ?
Unique (%)98.7%

Sample

1st row02-542-5457
2nd row02-537-9780
3rd row02-583-9013
4th row02-534-7758
5th row02-586-2458
ValueCountFrequency (%)
02-579-8485 2
 
1.3%
02-595-5976 1
 
0.7%
070-8233-3355 1
 
0.7%
02-542-5457 1
 
0.7%
02-598-4528 1
 
0.7%
02-522-7937 1
 
0.7%
02-598-5777 1
 
0.7%
02-6401-4011 1
 
0.7%
0506-050-1111 1
 
0.7%
070-8993-0779 1
 
0.7%
Other values (140) 140
92.7%
2023-12-12T23:20:26.292964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 302
17.4%
0 263
15.2%
2 256
14.8%
5 208
12.0%
3 120
 
6.9%
8 118
 
6.8%
9 110
 
6.4%
7 102
 
5.9%
1 95
 
5.5%
6 77
 
4.4%
Other values (3) 80
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1425
82.3%
Dash Punctuation 302
 
17.4%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 263
18.5%
2 256
18.0%
5 208
14.6%
3 120
8.4%
8 118
8.3%
9 110
7.7%
7 102
 
7.2%
1 95
 
6.7%
6 77
 
5.4%
4 76
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 302
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1731
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 302
17.4%
0 263
15.2%
2 256
14.8%
5 208
12.0%
3 120
 
6.9%
8 118
 
6.8%
9 110
 
6.4%
7 102
 
5.9%
1 95
 
5.5%
6 77
 
4.4%
Other values (3) 80
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1731
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 302
17.4%
0 263
15.2%
2 256
14.8%
5 208
12.0%
3 120
 
6.9%
8 118
 
6.8%
9 110
 
6.4%
7 102
 
5.9%
1 95
 
5.5%
6 77
 
4.4%
Other values (3) 80
 
4.6%

기타유의사항
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
151 
전화번호 데이터 미수집
138 

Length

Max length12
Median length4
Mean length7.8200692
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 151
52.2%
전화번호 데이터 미수집 138
47.8%

Length

2023-12-12T23:20:26.434156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:20:26.537041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 151
26.7%
전화번호 138
24.4%
데이터 138
24.4%
미수집 138
24.4%

Interactions

2023-12-12T23:20:23.694707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:20:26.608956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번
연번1.000
2023-12-12T23:20:26.681251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번기타유의사항
연번1.0001.000
기타유의사항1.0001.000

Missing values

2023-12-12T23:20:23.824588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:20:23.948909image/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

연번상호시설주소(도로명)시설전화번호기타유의사항
01서초헬스크럽서울특별시 서초구 사평대로 349 (반포동,2층)02-542-5457<NA>
12그린헬스서울특별시 서초구 동광로 18 (방배동)02-537-9780<NA>
23현대헬스서울특별시 서초구 방배천로 22 (방배동,3층)02-583-9013<NA>
34헬스토피아서울특별시 서초구 사평대로 362 (서초동,(3층))<NA>전화번호 데이터 미수집
45동호헬스클럽서울특별시 서초구 고무래로10길 17 (반포동,4층)02-534-7758<NA>
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