Overview

Dataset statistics

Number of variables4
Number of observations67
Missing cells18
Missing cells (%)6.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory34.0 B

Variable types

Categorical1
Text3

Dataset

Description전라남도 순천시의 체육시설(헬스장) 현황에 대한 데이터로 업종, 상호, 주소, 전화번호 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15077164/fileData.do

Alerts

업종 has constant value ""Constant
전화번호 has 18 (26.9%) missing valuesMissing
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:53:41.651963
Analysis finished2023-12-12 02:53:42.295492
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
체력단련장업
67 

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 67
100.0%

Length

2023-12-12T11:53:42.394743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:53:42.507843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 67
100.0%

상호
Text

Distinct66
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-12T11:53:42.834679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length16
Mean length8.8059701
Min length3

Characters and Unicode

Total characters590
Distinct characters174
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

Unique65 ?
Unique (%)97.0%

Sample

1st row팔마헬스클럽
2nd row남정헬스클럽
3rd row유심천헬스클럽
4th rowY휘트니스GYM(3층)
5th row스포타임
ValueCountFrequency (%)
gym 4
 
4.2%
휘트니스 4
 
4.2%
the 3
 
3.2%
헬스크럽 2
 
2.1%
헬스 2
 
2.1%
힘피트니스 2
 
2.1%
드림스포츠트레이닝센터 1
 
1.1%
joo 1
 
1.1%
smith 1
 
1.1%
body's 1
 
1.1%
Other values (74) 74
77.9%
2023-12-12T11:53:43.392467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 57
 
9.7%
28
 
4.7%
트 23
 
3.9%
니 22
 
3.7%
휘 18
 
3.1%
헬 16
 
2.7%
) 13
 
2.2%
( 13
 
2.2%
층 11
 
1.9%
3 11
 
1.9%
Other values (164) 378
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 398
67.5%
Uppercase Letter 84
 
14.2%
Decimal Number 31
 
5.3%
Space Separator 28
 
4.7%
Lowercase Letter 15
 
2.5%
Close Punctuation 13
 
2.2%
Open Punctuation 13
 
2.2%
Other Punctuation 7
 
1.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 57
 
14.3%
트 23
 
5.8%
니 22
 
5.5%
휘 18
 
4.5%
헬 16
 
4.0%
층 11
 
2.8%
럽 10
 
2.5%
이 9
 
2.3%
클 8
 
2.0%
센 7
 
1.8%
Other values (119) 217
54.5%
Uppercase Letter
ValueCountFrequency (%)
M 10
11.9%
Y 10
11.9%
T 8
 
9.5%
G 7
 
8.3%
E 6
 
7.1%
O 6
 
7.1%
H 5
 
6.0%
B 4
 
4.8%
S 4
 
4.8%
F 3
 
3.6%
Other values (11) 21
25.0%
Decimal Number
ValueCountFrequency (%)
3 11
35.5%
1 7
22.6%
2 5
16.1%
6 2
 
6.5%
4 2
 
6.5%
5 2
 
6.5%
8 1
 
3.2%
0 1
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
s 5
33.3%
e 3
20.0%
n 2
 
13.3%
m 1
 
6.7%
a 1
 
6.7%
t 1
 
6.7%
i 1
 
6.7%
v 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 3
42.9%
' 2
28.6%
. 1
 
14.3%
& 1
 
14.3%
Space Separator
ValueCountFrequency (%)
28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 398
67.5%
Latin 99
 
16.8%
Common 93
 
15.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 57
 
14.3%
트 23
 
5.8%
니 22
 
5.5%
휘 18
 
4.5%
헬 16
 
4.0%
층 11
 
2.8%
럽 10
 
2.5%
이 9
 
2.3%
클 8
 
2.0%
센 7
 
1.8%
Other values (119) 217
54.5%
Latin
ValueCountFrequency (%)
M 10
 
10.1%
Y 10
 
10.1%
T 8
 
8.1%
G 7
 
7.1%
E 6
 
6.1%
O 6
 
6.1%
s 5
 
5.1%
H 5
 
5.1%
B 4
 
4.0%
S 4
 
4.0%
Other values (19) 34
34.3%
Common
ValueCountFrequency (%)
28
30.1%
) 13
14.0%
( 13
14.0%
3 11
 
11.8%
1 7
 
7.5%
2 5
 
5.4%
, 3
 
3.2%
6 2
 
2.2%
4 2
 
2.2%
5 2
 
2.2%
Other values (6) 7
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 398
67.5%
ASCII 192
32.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 57
 
14.3%
트 23
 
5.8%
니 22
 
5.5%
휘 18
 
4.5%
헬 16
 
4.0%
층 11
 
2.8%
럽 10
 
2.5%
이 9
 
2.3%
클 8
 
2.0%
센 7
 
1.8%
Other values (119) 217
54.5%
ASCII
ValueCountFrequency (%)
28
 
14.6%
) 13
 
6.8%
( 13
 
6.8%
3 11
 
5.7%
M 10
 
5.2%
Y 10
 
5.2%
T 8
 
4.2%
G 7
 
3.6%
1 7
 
3.6%
E 6
 
3.1%
Other values (35) 79
41.1%

주소
Text

UNIQUE 

Distinct67
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-12T11:53:43.959306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length27.19403
Min length18

Characters and Unicode

Total characters1822
Distinct characters179
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

Unique67 ?
Unique (%)100.0%

Sample

1st row전라남도 순천시 풍덕주택길 52 (풍덕동, 새마을금고)
2nd row전라남도 순천시 우석로 150 (남정동, 남정헬스)
3rd row전라남도 순천시 중앙로 306 (가곡동, 유심천스포츠관광호텔)
4th row전라남도 순천시 충효로 93 (연향동, 르노삼성자동차)
5th row전라남도 순천시 시민로 46-1 (남내동)
ValueCountFrequency (%)
전라남도 67
 
17.0%
순천시 67
 
17.0%
조례동 23
 
5.8%
해룡면 8
 
2.0%
연향동 8
 
2.0%
2층 6
 
1.5%
풍덕동 6
 
1.5%
충효로 5
 
1.3%
신월큰길 5
 
1.3%
2 4
 
1.0%
Other values (155) 196
49.6%
2023-12-12T11:53:44.668001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
328
 
18.0%
천 80
 
4.4%
남 72
 
4.0%
순 72
 
4.0%
전 70
 
3.8%
라 69
 
3.8%
시 68
 
3.7%
도 67
 
3.7%
동 61
 
3.3%
( 58
 
3.2%
Other values (169) 877
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1114
61.1%
Space Separator 328
 
18.0%
Decimal Number 198
 
10.9%
Open Punctuation 58
 
3.2%
Close Punctuation 58
 
3.2%
Other Punctuation 49
 
2.7%
Dash Punctuation 7
 
0.4%
Uppercase Letter 6
 
0.3%
Lowercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 80
 
7.2%
남 72
 
6.5%
순 72
 
6.5%
전 70
 
6.3%
라 69
 
6.2%
시 68
 
6.1%
도 67
 
6.0%
동 61
 
5.5%
길 34
 
3.1%
로 33
 
3.0%
Other values (146) 488
43.8%
Decimal Number
ValueCountFrequency (%)
2 32
16.2%
1 32
16.2%
3 29
14.6%
5 20
10.1%
0 18
9.1%
6 17
8.6%
4 17
8.6%
9 12
 
6.1%
7 11
 
5.6%
8 10
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
P 2
33.3%
G 2
33.3%
L 1
16.7%
C 1
16.7%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
c 1
25.0%
a 1
25.0%
l 1
25.0%
Space Separator
ValueCountFrequency (%)
328
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Other Punctuation
ValueCountFrequency (%)
, 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1114
61.1%
Common 698
38.3%
Latin 10
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 80
 
7.2%
남 72
 
6.5%
순 72
 
6.5%
전 70
 
6.3%
라 69
 
6.2%
시 68
 
6.1%
도 67
 
6.0%
동 61
 
5.5%
길 34
 
3.1%
로 33
 
3.0%
Other values (146) 488
43.8%
Common
ValueCountFrequency (%)
328
47.0%
( 58
 
8.3%
) 58
 
8.3%
, 49
 
7.0%
2 32
 
4.6%
1 32
 
4.6%
3 29
 
4.2%
5 20
 
2.9%
0 18
 
2.6%
6 17
 
2.4%
Other values (5) 57
 
8.2%
Latin
ValueCountFrequency (%)
P 2
20.0%
G 2
20.0%
e 1
10.0%
c 1
10.0%
a 1
10.0%
l 1
10.0%
L 1
10.0%
C 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1114
61.1%
ASCII 708
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
328
46.3%
( 58
 
8.2%
) 58
 
8.2%
, 49
 
6.9%
2 32
 
4.5%
1 32
 
4.5%
3 29
 
4.1%
5 20
 
2.8%
0 18
 
2.5%
6 17
 
2.4%
Other values (13) 67
 
9.5%
Hangul
ValueCountFrequency (%)
천 80
 
7.2%
남 72
 
6.5%
순 72
 
6.5%
전 70
 
6.3%
라 69
 
6.2%
시 68
 
6.1%
도 67
 
6.0%
동 61
 
5.5%
길 34
 
3.1%
로 33
 
3.0%
Other values (146) 488
43.8%

전화번호
Text

MISSING 

Distinct47
Distinct (%)95.9%
Missing18
Missing (%)26.9%
Memory size668.0 B
2023-12-12T11:53:44.996026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters588
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

Unique45 ?
Unique (%)91.8%

Sample

1st row061-745-7787
2nd row061-743-1144
3rd row061-755-5001
4th row061-724-1934
5th row061-755-7272
ValueCountFrequency (%)
061-755-5001 2
 
4.1%
061-745-7787 2
 
4.1%
061-721-1990 1
 
2.0%
061-726-4948 1
 
2.0%
061-742-8800 1
 
2.0%
061-753-7180 1
 
2.0%
061-743-7787 1
 
2.0%
061-727-7100 1
 
2.0%
061-723-1028 1
 
2.0%
061-746-9696 1
 
2.0%
Other values (37) 37
75.5%
2023-12-12T11:53:45.389791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 98
16.7%
0 90
15.3%
1 83
14.1%
7 81
13.8%
6 68
11.6%
2 50
8.5%
5 33
 
5.6%
4 30
 
5.1%
9 21
 
3.6%
8 20
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 490
83.3%
Dash Punctuation 98
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 90
18.4%
1 83
16.9%
7 81
16.5%
6 68
13.9%
2 50
10.2%
5 33
 
6.7%
4 30
 
6.1%
9 21
 
4.3%
8 20
 
4.1%
3 14
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 98
16.7%
0 90
15.3%
1 83
14.1%
7 81
13.8%
6 68
11.6%
2 50
8.5%
5 33
 
5.6%
4 30
 
5.1%
9 21
 
3.6%
8 20
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 98
16.7%
0 90
15.3%
1 83
14.1%
7 81
13.8%
6 68
11.6%
2 50
8.5%
5 33
 
5.6%
4 30
 
5.1%
9 21
 
3.6%
8 20
 
3.4%

Correlations

2023-12-12T11:53:45.491939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호주소전화번호
상호1.0001.0000.988
주소1.0001.0001.000
전화번호0.9881.0001.000

Missing values

2023-12-12T11:53:42.128762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:53:42.248594image/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

업종상호주소전화번호
0체력단련장업팔마헬스클럽전라남도 순천시 풍덕주택길 52 (풍덕동, 새마을금고)061-745-7787
1체력단련장업남정헬스클럽전라남도 순천시 우석로 150 (남정동, 남정헬스)061-743-1144
2체력단련장업유심천헬스클럽전라남도 순천시 중앙로 306 (가곡동, 유심천스포츠관광호텔)061-755-5001
3체력단련장업Y휘트니스GYM(3층)전라남도 순천시 충효로 93 (연향동, 르노삼성자동차)061-724-1934
4체력단련장업스포타임전라남도 순천시 시민로 46-1 (남내동)061-755-7272
5체력단련장업유심천건강랜드체력단련장전라남도 순천시 왕궁길 11 (조례동, 유심천)061-725-5001
6체력단련장업천지헬스클럽전라남도 순천시 삼산로 69 (용당동, 천지사우나)061-755-0015
7체력단련장업옥담우스포츠센타전라남도 순천시 장명5길 6-5 (장천동)061-741-3675
8체력단련장업낙안온천헬스전라남도 순천시 낙안면 조정래길 933, 낙안온천061-753-0812
9체력단련장업스카이휘트니스헬스전라남도 순천시 비봉2길 4-40 (조례동, 동서휘트니스)061-726-7711
업종상호주소전화번호
57체력단련장업타이거 휘트니스전라남도 순천시 백강로 367 (조례동)061-721-1990
58체력단련장업제이에스 필라테스&짐전라남도 순천시 장선배기2길 6 (조례동)<NA>
59체력단련장업PK휘트니스전라남도 순천시 장승길 48, 더벨류넘버2 2,3층 (조례동)<NA>
60체력단련장업에이치짐전라남도 순천시 삼산로 94, 4,5층 (용당동)061-753-7180
61체력단련장업드림스포츠트레이닝센터전라남도 순천시 순천만정원로 86, 7층 703호 (풍덕동)061-742-8800
62체력단련장업잇츠짐힘핏전라남도 순천시 신월큰길 10, 삼성홈플러스 (조례동)<NA>
63체력단련장업라이브휘트니스(풍덕동)전라남도 순천시 순천만정원로 78, 3층 (풍덕동)<NA>
64체력단련장업아놀드피트니스컴퍼니전라남도 순천시 가곡3길 31, 홈마트 (가곡동)<NA>
65체력단련장업크로스핏야인전라남도 순천시 충효로 109, 디지털프라자전자랜드 지하층 (조례동)061-744-8867
66체력단련장업나는 몸짱이다전라남도 순천시 장선배기길 8, 광수사 2층 (조례동)<NA>