Overview

Dataset statistics

Number of variables4
Number of observations72
Missing cells3
Missing cells (%)1.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory33.8 B

Variable types

Categorical1
Text3

Dataset

Description서울특별시 중랑구의 체력단련장업에 관한 데이터 입니다. 업종, 상호, 시설주소, 시설전화번호를 제공합니다. 참고해주시기 바랍니다. 감사합니다.
Author서울특별시 중랑구
URLhttps://www.data.go.kr/data/15089139/fileData.do

Alerts

업종 has constant value ""Constant
시설전화번호 has 3 (4.2%) missing valuesMissing
시설주소(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:05:28.075317
Analysis finished2023-12-12 12:05:28.606275
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
체력단련장업
72 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 72
100.0%

Length

2023-12-12T21:05:28.721653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:05:28.849347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 72
100.0%

상호
Text

Distinct71
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-12T21:05:29.146502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length13
Mean length8.0138889
Min length2

Characters and Unicode

Total characters577
Distinct characters160
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

Unique70 ?
Unique (%)97.2%

Sample

1st row유코치의 바디스토리PT
2nd row아모르 PT
3rd row럭키 헬스
4th row이코리아스포츠
5th row세방헬스클럽
ValueCountFrequency (%)
휘트니스 8
 
6.0%
pt 7
 
5.3%
피트니스 5
 
3.8%
gym 5
 
3.8%
면목점 3
 
2.3%
스튜디오 3
 
2.3%
운동창고 3
 
2.3%
코어스트롱 2
 
1.5%
휘트니스&스쿼시 2
 
1.5%
카인드짐 2
 
1.5%
Other values (86) 93
69.9%
2023-12-12T21:05:29.651925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61
 
10.6%
스 48
 
8.3%
짐 23
 
4.0%
트 21
 
3.6%
니 19
 
3.3%
T 16
 
2.8%
P 13
 
2.3%
디 12
 
2.1%
휘 11
 
1.9%
이 10
 
1.7%
Other values (150) 343
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 417
72.3%
Uppercase Letter 76
 
13.2%
Space Separator 61
 
10.6%
Close Punctuation 5
 
0.9%
Open Punctuation 4
 
0.7%
Other Punctuation 4
 
0.7%
Decimal Number 4
 
0.7%
Lowercase Letter 4
 
0.7%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 48
 
11.5%
짐 23
 
5.5%
트 21
 
5.0%
니 19
 
4.6%
디 12
 
2.9%
휘 11
 
2.6%
이 10
 
2.4%
바 10
 
2.4%
리 9
 
2.2%
점 8
 
1.9%
Other values (120) 246
59.0%
Uppercase Letter
ValueCountFrequency (%)
T 16
21.1%
P 13
17.1%
M 7
9.2%
Y 7
9.2%
G 7
9.2%
O 5
 
6.6%
E 4
 
5.3%
B 3
 
3.9%
I 2
 
2.6%
S 2
 
2.6%
Other values (8) 10
13.2%
Lowercase Letter
ValueCountFrequency (%)
h 1
25.0%
o 1
25.0%
u 1
25.0%
r 1
25.0%
Other Punctuation
ValueCountFrequency (%)
& 3
75.0%
. 1
 
25.0%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
4 2
50.0%
Space Separator
ValueCountFrequency (%)
61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 417
72.3%
Common 80
 
13.9%
Latin 80
 
13.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 48
 
11.5%
짐 23
 
5.5%
트 21
 
5.0%
니 19
 
4.6%
디 12
 
2.9%
휘 11
 
2.6%
이 10
 
2.4%
바 10
 
2.4%
리 9
 
2.2%
점 8
 
1.9%
Other values (120) 246
59.0%
Latin
ValueCountFrequency (%)
T 16
20.0%
P 13
16.2%
M 7
8.8%
Y 7
8.8%
G 7
8.8%
O 5
 
6.2%
E 4
 
5.0%
B 3
 
3.8%
I 2
 
2.5%
S 2
 
2.5%
Other values (12) 14
17.5%
Common
ValueCountFrequency (%)
61
76.2%
) 5
 
6.2%
( 4
 
5.0%
& 3
 
3.8%
2 2
 
2.5%
4 2
 
2.5%
- 2
 
2.5%
. 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 417
72.3%
ASCII 160
 
27.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
61
38.1%
T 16
 
10.0%
P 13
 
8.1%
M 7
 
4.4%
Y 7
 
4.4%
G 7
 
4.4%
) 5
 
3.1%
O 5
 
3.1%
( 4
 
2.5%
E 4
 
2.5%
Other values (20) 31
19.4%
Hangul
ValueCountFrequency (%)
스 48
 
11.5%
짐 23
 
5.5%
트 21
 
5.0%
니 19
 
4.6%
디 12
 
2.9%
휘 11
 
2.6%
이 10
 
2.4%
바 10
 
2.4%
리 9
 
2.2%
점 8
 
1.9%
Other values (120) 246
59.0%

시설주소(도로명)
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-12T21:05:29.975606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length42
Mean length33.722222
Min length25

Characters and Unicode

Total characters2428
Distinct characters147
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)100.0%

Sample

1st row서울특별시 중랑구 면목로 220, 6층 (면목동)
2nd row서울특별시 중랑구 용마산로 296-2, 4층 (면목동)
3rd row서울특별시 중랑구 중랑역로 51, 5층 (중화동)
4th row서울특별시 중랑구 망우로 454, 3층 (망우동)
5th row서울특별시 중랑구 면목로37길 17, 세방사우나 4층 (면목동)
ValueCountFrequency (%)
서울특별시 72
 
14.5%
중랑구 72
 
14.5%
면목동 24
 
4.8%
상봉동 16
 
3.2%
지하1층 13
 
2.6%
면목로 12
 
2.4%
2층 12
 
2.4%
3층 12
 
2.4%
4층 11
 
2.2%
신내동 10
 
2.0%
Other values (173) 241
48.7%
2023-12-12T21:05:30.420692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
423
 
17.4%
, 99
 
4.1%
동 90
 
3.7%
중 83
 
3.4%
랑 75
 
3.1%
시 74
 
3.0%
) 73
 
3.0%
( 73
 
3.0%
로 72
 
3.0%
울 72
 
3.0%
Other values (137) 1294
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1390
57.2%
Space Separator 423
 
17.4%
Decimal Number 356
 
14.7%
Other Punctuation 99
 
4.1%
Close Punctuation 73
 
3.0%
Open Punctuation 73
 
3.0%
Uppercase Letter 9
 
0.4%
Dash Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 90
 
6.5%
중 83
 
6.0%
랑 75
 
5.4%
시 74
 
5.3%
로 72
 
5.2%
울 72
 
5.2%
서 72
 
5.2%
별 72
 
5.2%
특 72
 
5.2%
구 72
 
5.2%
Other values (116) 636
45.8%
Decimal Number
ValueCountFrequency (%)
2 65
18.3%
1 64
18.0%
3 54
15.2%
4 38
10.7%
0 29
8.1%
8 26
 
7.3%
5 22
 
6.2%
6 21
 
5.9%
9 21
 
5.9%
7 16
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 3
33.3%
M 2
22.2%
C 1
 
11.1%
A 1
 
11.1%
S 1
 
11.1%
G 1
 
11.1%
Space Separator
ValueCountFrequency (%)
423
100.0%
Other Punctuation
ValueCountFrequency (%)
, 99
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1390
57.2%
Common 1029
42.4%
Latin 9
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 90
 
6.5%
중 83
 
6.0%
랑 75
 
5.4%
시 74
 
5.3%
로 72
 
5.2%
울 72
 
5.2%
서 72
 
5.2%
별 72
 
5.2%
특 72
 
5.2%
구 72
 
5.2%
Other values (116) 636
45.8%
Common
ValueCountFrequency (%)
423
41.1%
, 99
 
9.6%
) 73
 
7.1%
( 73
 
7.1%
2 65
 
6.3%
1 64
 
6.2%
3 54
 
5.2%
4 38
 
3.7%
0 29
 
2.8%
8 26
 
2.5%
Other values (5) 85
 
8.3%
Latin
ValueCountFrequency (%)
B 3
33.3%
M 2
22.2%
C 1
 
11.1%
A 1
 
11.1%
S 1
 
11.1%
G 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1390
57.2%
ASCII 1038
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
423
40.8%
, 99
 
9.5%
) 73
 
7.0%
( 73
 
7.0%
2 65
 
6.3%
1 64
 
6.2%
3 54
 
5.2%
4 38
 
3.7%
0 29
 
2.8%
8 26
 
2.5%
Other values (11) 94
 
9.1%
Hangul
ValueCountFrequency (%)
동 90
 
6.5%
중 83
 
6.0%
랑 75
 
5.4%
시 74
 
5.3%
로 72
 
5.2%
울 72
 
5.2%
서 72
 
5.2%
별 72
 
5.2%
특 72
 
5.2%
구 72
 
5.2%
Other values (116) 636
45.8%

시설전화번호
Text

MISSING 

Distinct69
Distinct (%)100.0%
Missing3
Missing (%)4.2%
Memory size708.0 B
2023-12-12T21:05:30.720263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length12.130435
Min length11

Characters and Unicode

Total characters837
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

Unique69 ?
Unique (%)100.0%

Sample

1st row02-494-1031
2nd row02-2209-3022
3rd row02-432-5111
4th row02-435-1113
5th row02-435-5346
ValueCountFrequency (%)
0507-1407-9683 1
 
1.4%
0507-1403-9025 1
 
1.4%
02-435-0062 1
 
1.4%
02-6462-2223 1
 
1.4%
02-972-9108 1
 
1.4%
070-7543-7465 1
 
1.4%
0507-1465-2583 1
 
1.4%
02-433-4311 1
 
1.4%
02-6080-8085 1
 
1.4%
070-8119-9679 1
 
1.4%
Other values (59) 59
85.5%
2023-12-12T21:05:31.163051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 139
16.6%
- 138
16.5%
2 92
11.0%
4 73
8.7%
3 70
8.4%
1 68
8.1%
5 58
6.9%
7 56
6.7%
8 52
 
6.2%
9 47
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 699
83.5%
Dash Punctuation 138
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 139
19.9%
2 92
13.2%
4 73
10.4%
3 70
10.0%
1 68
9.7%
5 58
8.3%
7 56
8.0%
8 52
 
7.4%
9 47
 
6.7%
6 44
 
6.3%
Dash Punctuation
ValueCountFrequency (%)
- 138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 837
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 139
16.6%
- 138
16.5%
2 92
11.0%
4 73
8.7%
3 70
8.4%
1 68
8.1%
5 58
6.9%
7 56
6.7%
8 52
 
6.2%
9 47
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 837
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 139
16.6%
- 138
16.5%
2 92
11.0%
4 73
8.7%
3 70
8.4%
1 68
8.1%
5 58
6.9%
7 56
6.7%
8 52
 
6.2%
9 47
 
5.6%

Correlations

2023-12-12T21:05:31.283664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호시설주소(도로명)시설전화번호
상호1.0001.0001.000
시설주소(도로명)1.0001.0001.000
시설전화번호1.0001.0001.000

Missing values

2023-12-12T21:05:28.438318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:05:28.556174image/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

업종상호시설주소(도로명)시설전화번호
0체력단련장업유코치의 바디스토리PT서울특별시 중랑구 면목로 220, 6층 (면목동)02-494-1031
1체력단련장업아모르 PT서울특별시 중랑구 용마산로 296-2, 4층 (면목동)02-2209-3022
2체력단련장업럭키 헬스서울특별시 중랑구 중랑역로 51, 5층 (중화동)02-432-5111
3체력단련장업이코리아스포츠서울특별시 중랑구 망우로 454, 3층 (망우동)02-435-1113
4체력단련장업세방헬스클럽서울특별시 중랑구 면목로37길 17, 세방사우나 4층 (면목동)02-435-5346
5체력단련장업비바 휘트니스서울특별시 중랑구 용마산로 494, 4층 (망우동)02-435-8294
6체력단련장업피트니스 에스 핏서울특별시 중랑구 신내로14길 13, 5층 (신내동)0507-1468-3692
7체력단련장업오메가 쓰리 스포츠서울특별시 중랑구 봉화산로 117, 2,3,4층 (상봉동)02-434-9633
8체력단련장업바디캠프서울특별시 중랑구 동일로 851, 3층 (묵동)0507-1407-9683
9체력단련장업굿모닝 휘트니스서울특별시 중랑구 망우로 186, 2층 (상봉동)02-491-6264
업종상호시설주소(도로명)시설전화번호
62체력단련장업J-PT서울특별시 중랑구 공릉로 18, 3층 (묵동)0507-1385-8254
63체력단련장업콤마짐서울특별시 중랑구 양원역로10길 3, 제이타워 7층 (망우동)0507-1305-7709
64체력단련장업퍼플피플서울특별시 중랑구 중랑역로 62, 5층 (중화동)0507-1301-0853
65체력단련장업코어핏 PT&필라테스서울특별시 중랑구 봉우재로33길 65, 4층 (상봉동)0507-1418-2201
66체력단련장업뉴페이스짐서울특별시 중랑구 면목로 469, 2층 (상봉동, 대성타워)<NA>
67체력단련장업랩 지피티짐서울특별시 중랑구 사가정로50길 30, 3층 (면목동)0507-1316-6026
68체력단련장업피트니스 에이치서울특별시 중랑구 사가정로 373, 성윤빌딩 (면목동)0507-1334-7812
69체력단련장업저스트PT서울특별시 중랑구 망우로 463, 태광치과의원 3층 302호 (망우동)0507-1317-4347
70체력단련장업시너지 휘트니스서울특별시 중랑구 면목로 283, 우리은행 4, 5층 (면목동)02-6339-8818
71체력단련장업프리빗 PT 스튜디오서울특별시 중랑구 신내로14길 22, 삼영빌딩 3층 (신내동)0507-1420-7878