Overview

Dataset statistics

Number of variables4
Number of observations217
Missing cells125
Missing cells (%)14.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory32.6 B

Variable types

Categorical1
Text3

Dataset

Description서울특별시_송파구_체력단련장에 대한 데이터로 업종, 상호, 시설주소(도로명), 시설전화번호 등에 항목으로 제공합니다.
Author서울특별시 송파구
URLhttps://www.data.go.kr/data/15073996/fileData.do

Alerts

업종 has constant value ""Constant
시설전화번호 has 125 (57.6%) missing valuesMissing

Reproduction

Analysis started2023-12-12 00:04:21.996653
Analysis finished2023-12-12 00:04:22.492354
Duration0.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
체력단련장업
217 

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 217
100.0%

Length

2023-12-12T09:04:22.583153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:04:22.698050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 217
100.0%

상호
Text

Distinct211
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T09:04:23.007036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length23
Mean length9.0967742
Min length2

Characters and Unicode

Total characters1974
Distinct characters297
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

Unique206 ?
Unique (%)94.9%

Sample

1st row바디웍
2nd row바디웍
3rd row풍납 헬스
4th row문정2호점 스포애니 (주)케이디스포츠
5th row골든짐
ValueCountFrequency (%)
gym 16
 
4.0%
휘트니스 12
 
3.0%
짐 7
 
1.7%
트레이닝 6
 
1.5%
pt 6
 
1.5%
스포애니 6
 
1.5%
주)케이디스포츠 6
 
1.5%
잠실점 5
 
1.2%
로그짐 5
 
1.2%
앤 4
 
1.0%
Other values (288) 329
81.8%
2023-12-12T09:04:23.454429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
185
 
9.4%
스 125
 
6.3%
트 65
 
3.3%
짐 56
 
2.8%
이 51
 
2.6%
니 50
 
2.5%
디 32
 
1.6%
휘 31
 
1.6%
T 31
 
1.6%
e 30
 
1.5%
Other values (287) 1318
66.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1255
63.6%
Uppercase Letter 251
 
12.7%
Lowercase Letter 197
 
10.0%
Space Separator 185
 
9.4%
Open Punctuation 28
 
1.4%
Close Punctuation 28
 
1.4%
Decimal Number 15
 
0.8%
Other Punctuation 14
 
0.7%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 125
 
10.0%
트 65
 
5.2%
짐 56
 
4.5%
이 51
 
4.1%
니 50
 
4.0%
디 32
 
2.5%
휘 31
 
2.5%
피 25
 
2.0%
점 23
 
1.8%
포 21
 
1.7%
Other values (230) 776
61.8%
Uppercase Letter
ValueCountFrequency (%)
T 31
12.4%
P 25
 
10.0%
G 24
 
9.6%
M 24
 
9.6%
Y 22
 
8.8%
I 10
 
4.0%
B 10
 
4.0%
S 10
 
4.0%
A 9
 
3.6%
R 9
 
3.6%
Other values (13) 77
30.7%
Lowercase Letter
ValueCountFrequency (%)
e 30
15.2%
s 22
11.2%
i 20
10.2%
t 20
10.2%
r 14
 
7.1%
y 12
 
6.1%
o 12
 
6.1%
n 11
 
5.6%
a 10
 
5.1%
l 7
 
3.6%
Other values (10) 39
19.8%
Decimal Number
ValueCountFrequency (%)
2 4
26.7%
3 3
20.0%
1 3
20.0%
9 2
13.3%
4 1
 
6.7%
0 1
 
6.7%
6 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
& 7
50.0%
. 5
35.7%
' 2
 
14.3%
Space Separator
ValueCountFrequency (%)
185
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1255
63.6%
Latin 448
 
22.7%
Common 271
 
13.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 125
 
10.0%
트 65
 
5.2%
짐 56
 
4.5%
이 51
 
4.1%
니 50
 
4.0%
디 32
 
2.5%
휘 31
 
2.5%
피 25
 
2.0%
점 23
 
1.8%
포 21
 
1.7%
Other values (230) 776
61.8%
Latin
ValueCountFrequency (%)
T 31
 
6.9%
e 30
 
6.7%
P 25
 
5.6%
G 24
 
5.4%
M 24
 
5.4%
s 22
 
4.9%
Y 22
 
4.9%
i 20
 
4.5%
t 20
 
4.5%
r 14
 
3.1%
Other values (33) 216
48.2%
Common
ValueCountFrequency (%)
185
68.3%
( 28
 
10.3%
) 28
 
10.3%
& 7
 
2.6%
. 5
 
1.8%
2 4
 
1.5%
3 3
 
1.1%
1 3
 
1.1%
9 2
 
0.7%
' 2
 
0.7%
Other values (4) 4
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1255
63.6%
ASCII 719
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
185
25.7%
T 31
 
4.3%
e 30
 
4.2%
( 28
 
3.9%
) 28
 
3.9%
P 25
 
3.5%
G 24
 
3.3%
M 24
 
3.3%
s 22
 
3.1%
Y 22
 
3.1%
Other values (47) 300
41.7%
Hangul
ValueCountFrequency (%)
스 125
 
10.0%
트 65
 
5.2%
짐 56
 
4.5%
이 51
 
4.1%
니 50
 
4.0%
디 32
 
2.5%
휘 31
 
2.5%
피 25
 
2.0%
점 23
 
1.8%
포 21
 
1.7%
Other values (230) 776
61.8%

시설주소(도로명)
Text

Distinct215
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T09:04:23.696504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length44
Mean length32.976959
Min length22

Characters and Unicode

Total characters7156
Distinct characters226
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

Unique213 ?
Unique (%)98.2%

Sample

1st row서울특별시 송파구 오금로 300 (가락동)
2nd row서울특별시 송파구 마천로 61 (오금동)
3rd row서울특별시 송파구 풍성로 65, 3층 301호 (풍납동)
4th row서울특별시 송파구 동남로4길 10 (문정동)
5th row서울특별시 송파구 가락로 94 (석촌동)
ValueCountFrequency (%)
서울특별시 217
 
15.3%
송파구 217
 
15.3%
잠실동 35
 
2.5%
문정동 34
 
2.4%
지하1층 28
 
2.0%
2층 25
 
1.8%
송파동 24
 
1.7%
방이동 23
 
1.6%
3층 20
 
1.4%
가락동 19
 
1.3%
Other values (433) 779
54.8%
2023-12-12T09:04:24.076930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1204
 
16.8%
파 290
 
4.1%
송 279
 
3.9%
1 247
 
3.5%
동 245
 
3.4%
시 222
 
3.1%
) 220
 
3.1%
( 220
 
3.1%
서 219
 
3.1%
로 219
 
3.1%
Other values (216) 3791
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4252
59.4%
Space Separator 1204
 
16.8%
Decimal Number 984
 
13.8%
Close Punctuation 220
 
3.1%
Open Punctuation 220
 
3.1%
Other Punctuation 217
 
3.0%
Uppercase Letter 39
 
0.5%
Dash Punctuation 16
 
0.2%
Math Symbol 3
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 290
 
6.8%
송 279
 
6.6%
동 245
 
5.8%
시 222
 
5.2%
서 219
 
5.2%
로 219
 
5.2%
울 219
 
5.2%
구 217
 
5.1%
별 217
 
5.1%
특 217
 
5.1%
Other values (184) 1908
44.9%
Uppercase Letter
ValueCountFrequency (%)
B 13
33.3%
A 4
 
10.3%
G 3
 
7.7%
U 2
 
5.1%
C 2
 
5.1%
K 2
 
5.1%
N 2
 
5.1%
M 2
 
5.1%
I 2
 
5.1%
D 2
 
5.1%
Other values (5) 5
 
12.8%
Decimal Number
ValueCountFrequency (%)
1 247
25.1%
2 161
16.4%
0 119
12.1%
3 103
10.5%
4 103
10.5%
5 78
 
7.9%
6 45
 
4.6%
8 44
 
4.5%
9 43
 
4.4%
7 41
 
4.2%
Space Separator
ValueCountFrequency (%)
1204
100.0%
Close Punctuation
ValueCountFrequency (%)
) 220
100.0%
Open Punctuation
ValueCountFrequency (%)
( 220
100.0%
Other Punctuation
ValueCountFrequency (%)
, 217
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4252
59.4%
Common 2864
40.0%
Latin 40
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 290
 
6.8%
송 279
 
6.6%
동 245
 
5.8%
시 222
 
5.2%
서 219
 
5.2%
로 219
 
5.2%
울 219
 
5.2%
구 217
 
5.1%
별 217
 
5.1%
특 217
 
5.1%
Other values (184) 1908
44.9%
Common
ValueCountFrequency (%)
1204
42.0%
1 247
 
8.6%
) 220
 
7.7%
( 220
 
7.7%
, 217
 
7.6%
2 161
 
5.6%
0 119
 
4.2%
3 103
 
3.6%
4 103
 
3.6%
5 78
 
2.7%
Other values (6) 192
 
6.7%
Latin
ValueCountFrequency (%)
B 13
32.5%
A 4
 
10.0%
G 3
 
7.5%
U 2
 
5.0%
C 2
 
5.0%
K 2
 
5.0%
N 2
 
5.0%
M 2
 
5.0%
I 2
 
5.0%
D 2
 
5.0%
Other values (6) 6
15.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4252
59.4%
ASCII 2904
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1204
41.5%
1 247
 
8.5%
) 220
 
7.6%
( 220
 
7.6%
, 217
 
7.5%
2 161
 
5.5%
0 119
 
4.1%
3 103
 
3.5%
4 103
 
3.5%
5 78
 
2.7%
Other values (22) 232
 
8.0%
Hangul
ValueCountFrequency (%)
파 290
 
6.8%
송 279
 
6.6%
동 245
 
5.8%
시 222
 
5.2%
서 219
 
5.2%
로 219
 
5.2%
울 219
 
5.2%
구 217
 
5.1%
별 217
 
5.1%
특 217
 
5.1%
Other values (184) 1908
44.9%

시설전화번호
Text

MISSING 

Distinct92
Distinct (%)100.0%
Missing125
Missing (%)57.6%
Memory size1.8 KiB
2023-12-12T09:04:24.378526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.315217
Min length8

Characters and Unicode

Total characters949
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

Unique92 ?
Unique (%)100.0%

Sample

1st row448-5161
2nd row448-7102
3rd row02-487-9385
4th row3401-3401
5th row417-1294
ValueCountFrequency (%)
02-2042-0902 1
 
1.1%
24079422 1
 
1.1%
02-416-2577 1
 
1.1%
02-414-7582 1
 
1.1%
02-412-6960 1
 
1.1%
02-402-3999 1
 
1.1%
02-423-6733 1
 
1.1%
070-8801-2510 1
 
1.1%
02-418-0111 1
 
1.1%
02-881-5579 1
 
1.1%
Other values (82) 82
89.1%
2023-12-12T09:04:24.816280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 151
15.9%
2 147
15.5%
- 145
15.3%
4 113
11.9%
1 76
8.0%
3 61
6.4%
8 57
 
6.0%
9 55
 
5.8%
7 54
 
5.7%
6 49
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 804
84.7%
Dash Punctuation 145
 
15.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 151
18.8%
2 147
18.3%
4 113
14.1%
1 76
9.5%
3 61
7.6%
8 57
 
7.1%
9 55
 
6.8%
7 54
 
6.7%
6 49
 
6.1%
5 41
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 145
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 949
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 151
15.9%
2 147
15.5%
- 145
15.3%
4 113
11.9%
1 76
8.0%
3 61
6.4%
8 57
 
6.0%
9 55
 
5.8%
7 54
 
5.7%
6 49
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 949
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 151
15.9%
2 147
15.5%
- 145
15.3%
4 113
11.9%
1 76
8.0%
3 61
6.4%
8 57
 
6.0%
9 55
 
5.8%
7 54
 
5.7%
6 49
 
5.2%

Missing values

2023-12-12T09:04:22.366276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:04:22.453523image/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
0체력단련장업바디웍서울특별시 송파구 오금로 300 (가락동)448-5161
1체력단련장업바디웍서울특별시 송파구 마천로 61 (오금동)448-7102
2체력단련장업풍납 헬스서울특별시 송파구 풍성로 65, 3층 301호 (풍납동)02-487-9385
3체력단련장업문정2호점 스포애니 (주)케이디스포츠서울특별시 송파구 동남로4길 10 (문정동)<NA>
4체력단련장업골든짐서울특별시 송파구 가락로 94 (석촌동)<NA>
5체력단련장업정락신용협동조합서울특별시 송파구 동남로4길 10 (문정동)3401-3401
6체력단련장업제임스짐JS점서울특별시 송파구 올림픽로4길 48, 지하1층 (잠실동)417-1294
7체력단련장업올림픽헬스교실서울특별시 송파구 올림픽로 424 (방이동)410-1626
8체력단련장업라인핏서울특별시 송파구 양산로 12, 세신거여훼미리타운 707, 708호 (거여동)<NA>
9체력단련장업가락휘트니스센터서울특별시 송파구 송파대로30길 11, 2층 (가락동)408-4580
업종상호시설주소(도로명)시설전화번호
207체력단련장업THE JUNG FIT서울특별시 송파구 백제고분로41길 33, 티에스티빌딩 지하1층 (송파동)<NA>
208체력단련장업바디 매니지먼트서울특별시 송파구 가락로 110, 3층 (석촌동)<NA>
209체력단련장업엠브이엠 거여역점서울특별시 송파구 양산로4길 9, 2층 (거여동)02-403-8821
210체력단련장업하이 피트니스서울특별시 송파구 백제고분로 128, H타워 지하1층 (잠실동)<NA>
211체력단련장업헬리오 GYM서울특별시 송파구 송파대로 345, B동 2층 92호 (가락동, 헬리오시티)<NA>
212체력단련장업에임트레이닝랩 부티크 스튜디오서울특별시 송파구 올림픽로35길 93, B106, B126호 (신천동, 더샵스타리버)02-421-8608
213체력단련장업나홀로짐에서울특별시 송파구 정의로7길 13, 힐스테이트에코송파 1층 114호 (문정동)<NA>
214체력단련장업효 GYM 3호점서울특별시 송파구 백제고분로27길 11, 2층 (삼전동)<NA>
215체력단련장업행복한휘트니스서울특별시 송파구 법원로 90, 파트너스2 B103, 104호 (문정동)02-403-8887
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