Overview

Dataset statistics

Number of variables5
Number of observations475
Missing cells344
Missing cells (%)14.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.7 KiB
Average record size in memory40.3 B

Variable types

Text4
Categorical1

Dataset

Description서울특별시_송파구_노래연습장에 대한 데이터로 상호명, 영업소도로명소재지, 영업소지번소재지, 전화번호, 데이터 기준일자 등에 항목으로 제공합니다.
Author서울특별시 송파구
URLhttps://www.data.go.kr/data/15044849/fileData.do

Alerts

데이터 기준일자 is highly imbalanced (97.8%)Imbalance
영업소도로명소재지 has 6 (1.3%) missing valuesMissing
전화번호 has 336 (70.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 03:20:32.744249
Analysis finished2023-12-12 03:20:33.752729
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호명
Text

Distinct405
Distinct (%)85.4%
Missing1
Missing (%)0.2%
Memory size3.8 KiB
2023-12-12T12:20:34.115677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length17
Mean length6.0675105
Min length1

Characters and Unicode

Total characters2876
Distinct characters343
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique361 ?
Unique (%)76.2%

Sample

1st row산울
2nd row마천
3rd row방방
4th row차차차
5th row영상
ValueCountFrequency (%)
노래연습장 50
 
9.2%
sbs 8
 
1.5%
sbs노래연습장 6
 
1.1%
코인노래연습장 6
 
1.1%
힐링노래연습장 5
 
0.9%
앵콜 4
 
0.7%
킹 4
 
0.7%
궁노래연습장 4
 
0.7%
행운노래연습장 3
 
0.6%
도레미 3
 
0.6%
Other values (398) 448
82.8%
2023-12-12T12:20:34.771334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
래 310
 
10.8%
노 308
 
10.7%
장 308
 
10.7%
연 307
 
10.7%
습 306
 
10.6%
67
 
2.3%
스 46
 
1.6%
이 37
 
1.3%
인 34
 
1.2%
S 33
 
1.1%
Other values (333) 1120
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2635
91.6%
Uppercase Letter 135
 
4.7%
Space Separator 67
 
2.3%
Decimal Number 13
 
0.5%
Lowercase Letter 12
 
0.4%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Other Punctuation 4
 
0.1%
Letter Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
래 310
 
11.8%
노 308
 
11.7%
장 308
 
11.7%
연 307
 
11.7%
습 306
 
11.6%
스 46
 
1.7%
이 37
 
1.4%
인 34
 
1.3%
코 33
 
1.3%
타 27
 
1.0%
Other values (294) 919
34.9%
Uppercase Letter
ValueCountFrequency (%)
S 33
24.4%
B 25
18.5%
M 10
 
7.4%
K 9
 
6.7%
O 8
 
5.9%
C 8
 
5.9%
A 6
 
4.4%
N 6
 
4.4%
P 4
 
3.0%
H 4
 
3.0%
Other values (11) 22
16.3%
Lowercase Letter
ValueCountFrequency (%)
s 2
16.7%
t 2
16.7%
a 2
16.7%
r 2
16.7%
m 2
16.7%
i 1
8.3%
f 1
8.3%
Decimal Number
ValueCountFrequency (%)
2 8
61.5%
7 2
 
15.4%
1 2
 
15.4%
3 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
. 2
50.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Space Separator
ValueCountFrequency (%)
67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2635
91.6%
Latin 149
 
5.2%
Common 92
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
래 310
 
11.8%
노 308
 
11.7%
장 308
 
11.7%
연 307
 
11.7%
습 306
 
11.6%
스 46
 
1.7%
이 37
 
1.4%
인 34
 
1.3%
코 33
 
1.3%
타 27
 
1.0%
Other values (294) 919
34.9%
Latin
ValueCountFrequency (%)
S 33
22.1%
B 25
16.8%
M 10
 
6.7%
K 9
 
6.0%
O 8
 
5.4%
C 8
 
5.4%
A 6
 
4.0%
N 6
 
4.0%
P 4
 
2.7%
H 4
 
2.7%
Other values (20) 36
24.2%
Common
ValueCountFrequency (%)
67
72.8%
2 8
 
8.7%
) 4
 
4.3%
( 4
 
4.3%
7 2
 
2.2%
, 2
 
2.2%
1 2
 
2.2%
. 2
 
2.2%
3 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2635
91.6%
ASCII 239
 
8.3%
Number Forms 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
래 310
 
11.8%
노 308
 
11.7%
장 308
 
11.7%
연 307
 
11.7%
습 306
 
11.6%
스 46
 
1.7%
이 37
 
1.4%
인 34
 
1.3%
코 33
 
1.3%
타 27
 
1.0%
Other values (294) 919
34.9%
ASCII
ValueCountFrequency (%)
67
28.0%
S 33
13.8%
B 25
 
10.5%
M 10
 
4.2%
K 9
 
3.8%
O 8
 
3.3%
C 8
 
3.3%
2 8
 
3.3%
A 6
 
2.5%
N 6
 
2.5%
Other values (27) 59
24.7%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%

영업소도로명소재지
Text

MISSING 

Distinct469
Distinct (%)100.0%
Missing6
Missing (%)1.3%
Memory size3.8 KiB
2023-12-12T12:20:35.214166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length47
Mean length28.733475
Min length22

Characters and Unicode

Total characters13476
Distinct characters159
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

Unique469 ?
Unique (%)100.0%

Sample

1st row서울특별시 송파구 성내천로 223 (마천동)
2nd row서울특별시 송파구 성내천로 302, 지층 (마천동)
3rd row서울특별시 송파구 올림픽로32길 9 (방이동)
4th row서울특별시 송파구 오금로11길 23-8 (방이동)
5th row서울특별시 송파구 풍성로25길 36-1 (풍납동)
ValueCountFrequency (%)
서울특별시 469
 
17.6%
송파구 469
 
17.6%
가락동 115
 
4.3%
지층 110
 
4.1%
방이동 72
 
2.7%
잠실동 54
 
2.0%
석촌동 43
 
1.6%
지1층 40
 
1.5%
문정동 36
 
1.4%
지하1층 31
 
1.2%
Other values (428) 1225
46.0%
2023-12-12T12:20:35.912109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2234
 
16.6%
송 541
 
4.0%
파 528
 
3.9%
동 500
 
3.7%
시 472
 
3.5%
서 469
 
3.5%
( 469
 
3.5%
특 469
 
3.5%
별 469
 
3.5%
구 469
 
3.5%
Other values (149) 6856
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8098
60.1%
Space Separator 2234
 
16.6%
Decimal Number 1842
 
13.7%
Open Punctuation 469
 
3.5%
Close Punctuation 469
 
3.5%
Other Punctuation 290
 
2.2%
Dash Punctuation 64
 
0.5%
Uppercase Letter 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
송 541
 
6.7%
파 528
 
6.5%
동 500
 
6.2%
시 472
 
5.8%
서 469
 
5.8%
특 469
 
5.8%
별 469
 
5.8%
구 469
 
5.8%
울 469
 
5.8%
로 468
 
5.8%
Other values (130) 3244
40.1%
Decimal Number
ValueCountFrequency (%)
1 432
23.5%
2 333
18.1%
3 230
12.5%
4 197
10.7%
5 125
 
6.8%
0 125
 
6.8%
9 109
 
5.9%
6 102
 
5.5%
8 101
 
5.5%
7 88
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 7
70.0%
G 1
 
10.0%
C 1
 
10.0%
A 1
 
10.0%
Space Separator
ValueCountFrequency (%)
2234
100.0%
Open Punctuation
ValueCountFrequency (%)
( 469
100.0%
Close Punctuation
ValueCountFrequency (%)
) 469
100.0%
Other Punctuation
ValueCountFrequency (%)
, 290
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8098
60.1%
Common 5368
39.8%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
송 541
 
6.7%
파 528
 
6.5%
동 500
 
6.2%
시 472
 
5.8%
서 469
 
5.8%
특 469
 
5.8%
별 469
 
5.8%
구 469
 
5.8%
울 469
 
5.8%
로 468
 
5.8%
Other values (130) 3244
40.1%
Common
ValueCountFrequency (%)
2234
41.6%
( 469
 
8.7%
) 469
 
8.7%
1 432
 
8.0%
2 333
 
6.2%
, 290
 
5.4%
3 230
 
4.3%
4 197
 
3.7%
5 125
 
2.3%
0 125
 
2.3%
Other values (5) 464
 
8.6%
Latin
ValueCountFrequency (%)
B 7
70.0%
G 1
 
10.0%
C 1
 
10.0%
A 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8098
60.1%
ASCII 5378
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2234
41.5%
( 469
 
8.7%
) 469
 
8.7%
1 432
 
8.0%
2 333
 
6.2%
, 290
 
5.4%
3 230
 
4.3%
4 197
 
3.7%
5 125
 
2.3%
0 125
 
2.3%
Other values (9) 474
 
8.8%
Hangul
ValueCountFrequency (%)
송 541
 
6.7%
파 528
 
6.5%
동 500
 
6.2%
시 472
 
5.8%
서 469
 
5.8%
특 469
 
5.8%
별 469
 
5.8%
구 469
 
5.8%
울 469
 
5.8%
로 468
 
5.8%
Other values (130) 3244
40.1%

영업소지번소재지
Text

Distinct456
Distinct (%)96.2%
Missing1
Missing (%)0.2%
Memory size3.8 KiB
2023-12-12T12:20:36.446616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length21.305907
Min length16

Characters and Unicode

Total characters10099
Distinct characters113
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique445 ?
Unique (%)93.9%

Sample

1st row서울특별시 송파구 마천동 158-2
2nd row서울특별시 송파구 마천동 287-6
3rd row서울특별시 송파구 방이동 36-3
4th row서울특별시 송파구 방이동 38-11
5th row서울특별시 송파구 풍납동 477-6
ValueCountFrequency (%)
서울특별시 474
22.6%
송파구 474
22.6%
가락동 118
 
5.6%
지층 93
 
4.4%
방이동 74
 
3.5%
잠실동 61
 
2.9%
석촌동 44
 
2.1%
문정동 37
 
1.8%
거여동 27
 
1.3%
송파동 26
 
1.2%
Other values (512) 670
31.9%
2023-12-12T12:20:37.221775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2094
20.7%
파 502
 
5.0%
송 500
 
5.0%
시 477
 
4.7%
동 476
 
4.7%
서 474
 
4.7%
구 474
 
4.7%
울 474
 
4.7%
별 474
 
4.7%
특 474
 
4.7%
Other values (103) 3680
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5738
56.8%
Space Separator 2094
 
20.7%
Decimal Number 1845
 
18.3%
Dash Punctuation 419
 
4.1%
Uppercase Letter 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 502
 
8.7%
송 500
 
8.7%
시 477
 
8.3%
동 476
 
8.3%
서 474
 
8.3%
구 474
 
8.3%
울 474
 
8.3%
별 474
 
8.3%
특 474
 
8.3%
층 129
 
2.2%
Other values (89) 1284
22.4%
Decimal Number
ValueCountFrequency (%)
1 447
24.2%
2 263
14.3%
3 157
 
8.5%
7 148
 
8.0%
8 148
 
8.0%
4 146
 
7.9%
9 145
 
7.9%
6 137
 
7.4%
0 128
 
6.9%
5 126
 
6.8%
Space Separator
ValueCountFrequency (%)
2094
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 419
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5738
56.8%
Common 4359
43.2%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 502
 
8.7%
송 500
 
8.7%
시 477
 
8.3%
동 476
 
8.3%
서 474
 
8.3%
구 474
 
8.3%
울 474
 
8.3%
별 474
 
8.3%
특 474
 
8.3%
층 129
 
2.2%
Other values (89) 1284
22.4%
Common
ValueCountFrequency (%)
2094
48.0%
1 447
 
10.3%
- 419
 
9.6%
2 263
 
6.0%
3 157
 
3.6%
7 148
 
3.4%
8 148
 
3.4%
4 146
 
3.3%
9 145
 
3.3%
6 137
 
3.1%
Other values (3) 255
 
5.8%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5738
56.8%
ASCII 4361
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2094
48.0%
1 447
 
10.2%
- 419
 
9.6%
2 263
 
6.0%
3 157
 
3.6%
7 148
 
3.4%
8 148
 
3.4%
4 146
 
3.3%
9 145
 
3.3%
6 137
 
3.1%
Other values (4) 257
 
5.9%
Hangul
ValueCountFrequency (%)
파 502
 
8.7%
송 500
 
8.7%
시 477
 
8.3%
동 476
 
8.3%
서 474
 
8.3%
구 474
 
8.3%
울 474
 
8.3%
별 474
 
8.3%
특 474
 
8.3%
층 129
 
2.2%
Other values (89) 1284
22.4%

전화번호
Text

MISSING 

Distinct138
Distinct (%)99.3%
Missing336
Missing (%)70.7%
Memory size3.8 KiB
2023-12-12T12:20:37.560417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11
Mean length9.9928058
Min length8

Characters and Unicode

Total characters1389
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique137 ?
Unique (%)98.6%

Sample

1st row02-424-1422
2nd row02-400-3144
3rd row02-425-0886
4th row408-8200
5th row02-406-5205
ValueCountFrequency (%)
02-415-6544 2
 
1.4%
02-3431-1243 1
 
0.7%
403-2245 1
 
0.7%
402-9038,431-0357 1
 
0.7%
414-5271 1
 
0.7%
02-430-4922 1
 
0.7%
02-419-2226 1
 
0.7%
02-400-3910 1
 
0.7%
400-5514 1
 
0.7%
425-5546 1
 
0.7%
Other values (128) 128
92.1%
2023-12-12T12:20:38.086067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 221
15.9%
4 217
15.6%
0 206
14.8%
2 200
14.4%
1 100
7.2%
7 87
 
6.3%
3 87
 
6.3%
5 77
 
5.5%
8 68
 
4.9%
6 64
 
4.6%
Other values (2) 62
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1167
84.0%
Dash Punctuation 221
 
15.9%
Other Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 217
18.6%
0 206
17.7%
2 200
17.1%
1 100
8.6%
7 87
7.5%
3 87
7.5%
5 77
 
6.6%
8 68
 
5.8%
6 64
 
5.5%
9 61
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 221
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1389
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 221
15.9%
4 217
15.6%
0 206
14.8%
2 200
14.4%
1 100
7.2%
7 87
 
6.3%
3 87
 
6.3%
5 77
 
5.5%
8 68
 
4.9%
6 64
 
4.6%
Other values (2) 62
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1389
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 221
15.9%
4 217
15.6%
0 206
14.8%
2 200
14.4%
1 100
7.2%
7 87
 
6.3%
3 87
 
6.3%
5 77
 
5.5%
8 68
 
4.9%
6 64
 
4.6%
Other values (2) 62
 
4.5%

데이터 기준일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2021-09-10
474 
<NA>
 
1

Length

Max length10
Median length10
Mean length9.9873684
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row2021-09-10
2nd row2021-09-10
3rd row2021-09-10
4th row2021-09-10
5th row2021-09-10

Common Values

ValueCountFrequency (%)
2021-09-10 474
99.8%
<NA> 1
 
0.2%

Length

2023-12-12T12:20:38.309976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:20:38.471307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-09-10 474
99.8%
na 1
 
0.2%

Missing values

2023-12-12T12:20:33.285705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:20:33.448816image/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.
2023-12-12T12:20:33.631552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

상호명영업소도로명소재지영업소지번소재지전화번호데이터 기준일자
0산울서울특별시 송파구 성내천로 223 (마천동)서울특별시 송파구 마천동 158-2<NA>2021-09-10
1마천서울특별시 송파구 성내천로 302, 지층 (마천동)서울특별시 송파구 마천동 287-6<NA>2021-09-10
2방방서울특별시 송파구 올림픽로32길 9 (방이동)서울특별시 송파구 방이동 36-3<NA>2021-09-10
3차차차서울특별시 송파구 오금로11길 23-8 (방이동)서울특별시 송파구 방이동 38-11<NA>2021-09-10
4영상서울특별시 송파구 풍성로25길 36-1 (풍납동)서울특별시 송파구 풍납동 477-6<NA>2021-09-10
5힐링노래연습장서울특별시 송파구 송이로31길 4-10 (문정동)서울특별시 송파구 문정동 116-8<NA>2021-09-10
6찬찬찬노래연습장서울특별시 송파구 마천로 24 (방이동)서울특별시 송파구 방이동 213-102-424-14222021-09-10
7써니 노래연습장서울특별시 송파구 올림픽로47길 15 (풍납동)서울특별시 송파구 풍납동 400-0<NA>2021-09-10
8엔젤노래연습장서울특별시 송파구 마천로 192, 지층 (오금동)서울특별시 송파구 오금동 131-2 지층02-400-31442021-09-10
9MBC서울특별시 송파구 문정로4길 34 (문정동)서울특별시 송파구 문정동 68-10<NA>2021-09-10
상호명영업소도로명소재지영업소지번소재지전화번호데이터 기준일자
465탄2코인노래연습장서울특별시 송파구 법원로 128, 문정에스케이브이원지엘메트로시티 CG동 지하층 103호 (문정동)서울특별시 송파구 문정동 642-3 문정에스케이브이원지엘메트로시티<NA>2021-09-10
466스타코인노래연습장서울특별시 송파구 오금로11길 11-8, 현대드림밸리 5층 503,504,505호 (방이동)서울특별시 송파구 방이동 34-2 현대드림밸리<NA>2021-09-10
467Kstar코인노래연습장(방이점)서울특별시 송파구 오금로13길 8, 부흥빌딩 지층 (방이동)서울특별시 송파구 방이동 67-7 부흥빌딩<NA>2021-09-10
468엄지노래연습장서울특별시 송파구 송파대로30길 21, 3층 (가락동)서울특별시 송파구 가락동 81<NA>2021-09-10
469힐링노래연습장서울특별시 송파구 삼전로9길 19, 거북이빌딩 지층 (잠실동)서울특별시 송파구 잠실동 246 거북이빌딩<NA>2021-09-10
470거송노래연습장서울특별시 송파구 중대로9길 22, 지하1층 (가락동)서울특별시 송파구 가락동 82-2<NA>2021-09-10
471왁스노래연습장서울특별시 송파구 송파대로28길 24, 밀리아나2차오피스텔 202호 (가락동)서울특별시 송파구 가락동 79-5 밀리아나2차오피스텔<NA>2021-09-10
472궁노래연습장서울특별시 송파구 중대로9길 32, 상원빌딩 지하층 (가락동)서울특별시 송파구 가락동 83-6 상원빌딩<NA>2021-09-10
473호수노래연습장서울특별시 송파구 중대로9길 24, 2층 (가락동)서울특별시 송파구 가락동 82-302-4725-11792021-09-10
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