Overview

Dataset statistics

Number of variables5
Number of observations119
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory41.1 B

Variable types

Categorical2
Text2
DateTime1

Dataset

Description서울특별시 동대문구 체육시설업(체력단련장) 현황 자료입니다. 업종, 상호명, 도로명주소 등이 기재되어 있습니다.
Author서울특별시 동대문구
URLhttps://www.data.go.kr/data/15074380/fileData.do

Alerts

업종 has constant value ""Constant
관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2024-03-23 06:49:29.348403
Analysis finished2024-03-23 06:49:30.716224
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
체력단련장업
119 

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 119
100.0%

Length

2024-03-23T06:49:30.990819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:49:31.315637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 119
100.0%

상호
Text

Distinct117
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-23T06:49:32.250109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length8.1008403
Min length3

Characters and Unicode

Total characters964
Distinct characters222
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

Unique115 ?
Unique (%)96.6%

Sample

1st row태정헬스
2nd row동대문종합사회복지관(체력단련장업)
3rd row헬스 119
4th row파워헬스클럽
5th row비너스헬스
ValueCountFrequency (%)
휘트니스 12
 
6.1%
gym 8
 
4.1%
짐 4
 
2.0%
회기점 3
 
1.5%
에이치짐 3
 
1.5%
101퍼센트짐 2
 
1.0%
장안점 2
 
1.0%
필라테스 2
 
1.0%
피티 2
 
1.0%
더블에스 2
 
1.0%
Other values (148) 157
79.7%
2024-03-23T06:49:33.527684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
78
 
8.1%
스 67
 
7.0%
짐 37
 
3.8%
트 34
 
3.5%
이 25
 
2.6%
니 25
 
2.6%
휘 22
 
2.3%
점 19
 
2.0%
T 17
 
1.8%
에 14
 
1.5%
Other values (212) 626
64.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 677
70.2%
Uppercase Letter 106
 
11.0%
Space Separator 78
 
8.1%
Lowercase Letter 54
 
5.6%
Decimal Number 14
 
1.5%
Close Punctuation 12
 
1.2%
Open Punctuation 12
 
1.2%
Other Punctuation 9
 
0.9%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 67
 
9.9%
짐 37
 
5.5%
트 34
 
5.0%
이 25
 
3.7%
니 25
 
3.7%
휘 22
 
3.2%
점 19
 
2.8%
에 14
 
2.1%
리 11
 
1.6%
핏 11
 
1.6%
Other values (162) 412
60.9%
Uppercase Letter
ValueCountFrequency (%)
T 17
16.0%
G 12
11.3%
M 12
11.3%
Y 11
10.4%
H 8
 
7.5%
P 8
 
7.5%
O 6
 
5.7%
E 5
 
4.7%
S 4
 
3.8%
A 3
 
2.8%
Other values (11) 20
18.9%
Lowercase Letter
ValueCountFrequency (%)
y 8
14.8%
i 6
11.1%
t 5
9.3%
e 5
9.3%
o 5
9.3%
m 5
9.3%
d 3
 
5.6%
f 3
 
5.6%
g 3
 
5.6%
p 2
 
3.7%
Other values (5) 9
16.7%
Decimal Number
ValueCountFrequency (%)
1 8
57.1%
0 2
 
14.3%
4 1
 
7.1%
2 1
 
7.1%
3 1
 
7.1%
9 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
& 3
33.3%
. 3
33.3%
, 2
22.2%
! 1
 
11.1%
Space Separator
ValueCountFrequency (%)
78
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 677
70.2%
Latin 160
 
16.6%
Common 127
 
13.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 67
 
9.9%
짐 37
 
5.5%
트 34
 
5.0%
이 25
 
3.7%
니 25
 
3.7%
휘 22
 
3.2%
점 19
 
2.8%
에 14
 
2.1%
리 11
 
1.6%
핏 11
 
1.6%
Other values (162) 412
60.9%
Latin
ValueCountFrequency (%)
T 17
 
10.6%
G 12
 
7.5%
M 12
 
7.5%
Y 11
 
6.9%
H 8
 
5.0%
y 8
 
5.0%
P 8
 
5.0%
O 6
 
3.8%
i 6
 
3.8%
t 5
 
3.1%
Other values (26) 67
41.9%
Common
ValueCountFrequency (%)
78
61.4%
) 12
 
9.4%
( 12
 
9.4%
1 8
 
6.3%
& 3
 
2.4%
. 3
 
2.4%
0 2
 
1.6%
, 2
 
1.6%
- 2
 
1.6%
! 1
 
0.8%
Other values (4) 4
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 677
70.2%
ASCII 287
29.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
78
27.2%
T 17
 
5.9%
) 12
 
4.2%
( 12
 
4.2%
G 12
 
4.2%
M 12
 
4.2%
Y 11
 
3.8%
H 8
 
2.8%
1 8
 
2.8%
y 8
 
2.8%
Other values (40) 109
38.0%
Hangul
ValueCountFrequency (%)
스 67
 
9.9%
짐 37
 
5.5%
트 34
 
5.0%
이 25
 
3.7%
니 25
 
3.7%
휘 22
 
3.2%
점 19
 
2.8%
에 14
 
2.1%
리 11
 
1.6%
핏 11
 
1.6%
Other values (162) 412
60.9%

시설주소(도로명)
Text

Distinct117
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-23T06:49:34.428517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length18.831933
Min length16

Characters and Unicode

Total characters2241
Distinct characters65
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique115 ?
Unique (%)96.6%

Sample

1st row서울특별시 동대문구 망우로 74
2nd row서울특별시 동대문구 약령시로5길 22
3rd row서울특별시 동대문구 제기로 132
4th row서울특별시 동대문구 장한로 173
5th row서울특별시 동대문구 홍릉로 37
ValueCountFrequency (%)
서울특별시 119
25.0%
동대문구 119
25.0%
장한로 12
 
2.5%
왕산로 10
 
2.1%
이문로 8
 
1.7%
전농로 8
 
1.7%
사가정로 7
 
1.5%
답십리로 7
 
1.5%
망우로 5
 
1.1%
천호대로 5
 
1.1%
Other values (130) 176
37.0%
2024-03-23T06:49:36.228708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
389
17.4%
대 133
 
5.9%
문 127
 
5.7%
시 124
 
5.5%
울 122
 
5.4%
서 122
 
5.4%
동 119
 
5.3%
별 119
 
5.3%
구 119
 
5.3%
특 119
 
5.3%
Other values (55) 748
33.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1507
67.2%
Space Separator 389
 
17.4%
Decimal Number 336
 
15.0%
Dash Punctuation 9
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 133
8.8%
문 127
8.4%
시 124
8.2%
울 122
8.1%
서 122
8.1%
동 119
7.9%
별 119
7.9%
구 119
7.9%
특 119
7.9%
로 119
7.9%
Other values (43) 284
18.8%
Decimal Number
ValueCountFrequency (%)
1 78
23.2%
2 64
19.0%
3 35
10.4%
6 30
 
8.9%
4 25
 
7.4%
0 24
 
7.1%
9 24
 
7.1%
5 22
 
6.5%
7 19
 
5.7%
8 15
 
4.5%
Space Separator
ValueCountFrequency (%)
389
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1507
67.2%
Common 734
32.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 133
8.8%
문 127
8.4%
시 124
8.2%
울 122
8.1%
서 122
8.1%
동 119
7.9%
별 119
7.9%
구 119
7.9%
특 119
7.9%
로 119
7.9%
Other values (43) 284
18.8%
Common
ValueCountFrequency (%)
389
53.0%
1 78
 
10.6%
2 64
 
8.7%
3 35
 
4.8%
6 30
 
4.1%
4 25
 
3.4%
0 24
 
3.3%
9 24
 
3.3%
5 22
 
3.0%
7 19
 
2.6%
Other values (2) 24
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1507
67.2%
ASCII 734
32.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
389
53.0%
1 78
 
10.6%
2 64
 
8.7%
3 35
 
4.8%
6 30
 
4.1%
4 25
 
3.4%
0 24
 
3.3%
9 24
 
3.3%
5 22
 
3.0%
7 19
 
2.6%
Other values (2) 24
 
3.3%
Hangul
ValueCountFrequency (%)
대 133
8.8%
문 127
8.4%
시 124
8.2%
울 122
8.1%
서 122
8.1%
동 119
7.9%
별 119
7.9%
구 119
7.9%
특 119
7.9%
로 119
7.9%
Other values (43) 284
18.8%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
서울특별시 동대문구청
119 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 동대문구청
2nd row서울특별시 동대문구청
3rd row서울특별시 동대문구청
4th row서울특별시 동대문구청
5th row서울특별시 동대문구청

Common Values

ValueCountFrequency (%)
서울특별시 동대문구청 119
100.0%

Length

2024-03-23T06:49:36.934630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:49:37.206534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 119
50.0%
동대문구청 119
50.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2024-03-08 00:00:00
Maximum2024-03-08 00:00:00
2024-03-23T06:49:37.507518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:49:38.109605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-03-23T06:49:29.952123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T06:49:30.558042image/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)관리기관명데이터기준일자
0체력단련장업태정헬스서울특별시 동대문구 망우로 74서울특별시 동대문구청2024-03-08
1체력단련장업동대문종합사회복지관(체력단련장업)서울특별시 동대문구 약령시로5길 22서울특별시 동대문구청2024-03-08
2체력단련장업헬스 119서울특별시 동대문구 제기로 132서울특별시 동대문구청2024-03-08
3체력단련장업파워헬스클럽서울특별시 동대문구 장한로 173서울특별시 동대문구청2024-03-08
4체력단련장업비너스헬스서울특별시 동대문구 홍릉로 37서울특별시 동대문구청2024-03-08
5체력단련장업골든몽키짐(GYM)서울특별시 동대문구 무학로 100서울특별시 동대문구청2024-03-08
6체력단련장업헬스데이 답십리점서울특별시 동대문구 답십리로60길 134서울특별시 동대문구청2024-03-08
7체력단련장업헬스파크서울특별시 동대문구 이문로 73서울특별시 동대문구청2024-03-08
8체력단련장업에센휘트니스 크럽서울특별시 동대문구 장안벚꽃로 107서울특별시 동대문구청2024-03-08
9체력단련장업휴맥스 휘트니스크럽서울특별시 동대문구 장한로 40서울특별시 동대문구청2024-03-08
업종상호시설주소(도로명)관리기관명데이터기준일자
109체력단련장업바디공방서울특별시 동대문구 장한로18길 57서울특별시 동대문구청2024-03-08
110체력단련장업더바른핏서울특별시 동대문구 한천로24길 74-1서울특별시 동대문구청2024-03-08
111체력단련장업바디체크짐서울특별시 동대문구 한빛로 20서울특별시 동대문구청2024-03-08
112체력단련장업위아짐 회기점서울특별시 동대문구 이문로 9-1서울특별시 동대문구청2024-03-08
113체력단련장업베일리 짐서울특별시 동대문구 무학로36길 56서울특별시 동대문구청2024-03-08
114체력단련장업트리플에이스튜디오서울특별시 동대문구 서울시립대로 155서울특별시 동대문구청2024-03-08
115체력단련장업업타운 휘트니스 신설점서울특별시 동대문구 왕산로 22서울특별시 동대문구청2024-03-08
116체력단련장업애프터짐서울특별시 동대문구 망우로21길 26서울특별시 동대문구청2024-03-08
117체력단련장업헬스고 여성전용서울특별시 동대문구 전농로 94서울특별시 동대문구청2024-03-08
118체력단련장업소울트레이닝 청량리서울특별시 동대문구 고산자로32길 78서울특별시 동대문구청2024-03-08