Overview

Dataset statistics

Number of variables18
Number of observations406
Missing cells973
Missing cells (%)13.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory59.6 KiB
Average record size in memory150.3 B

Variable types

Numeric6
Categorical1
Text4
DateTime1
Boolean6

Dataset

Description전북특별자치도 전주시 노래연습장은 제공하며 업종, 사업장명, 인허가 일자, 주소, 노래방실수, 비상구여부 등을 제공합니다.
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=13&menuCd=DOM_000000103007001000&pListTypeStr=&pId=15042111

Alerts

업종 has constant value ""Constant
비상계단여부 is highly overall correlated with 청소년실수 and 4 other fieldsHigh correlation
자동환기여부 is highly overall correlated with 청소년실수 and 4 other fieldsHigh correlation
방음시설여부 is highly overall correlated with 청소년실수 and 4 other fieldsHigh correlation
비상구여부 is highly overall correlated with 청소년실수 and 4 other fieldsHigh correlation
특수조명여부 is highly overall correlated with 비상계단여부 and 3 other fieldsHigh correlation
시설면적 is highly overall correlated with 노래방실수High correlation
노래방실수 is highly overall correlated with 시설면적 and 1 other fieldsHigh correlation
청소년실수 is highly overall correlated with 노래방실수 and 5 other fieldsHigh correlation
청소년실여부 is highly overall correlated with 청소년실수High correlation
청소년실여부 is highly imbalanced (95.2%)Imbalance
전화번호 has 155 (38.2%) missing valuesMissing
청소년실수 has 105 (25.9%) missing valuesMissing
비상계단여부 has 88 (21.7%) missing valuesMissing
비상구여부 has 73 (18.0%) missing valuesMissing
자동환기여부 has 93 (22.9%) missing valuesMissing
청소년실여부 has 218 (53.7%) missing valuesMissing
특수조명여부 has 147 (36.2%) missing valuesMissing
방음시설여부 has 89 (21.9%) missing valuesMissing
연번 has unique valuesUnique
청소년실수 has 100 (24.6%) zerosZeros

Reproduction

Analysis started2024-03-14 00:13:44.256222
Analysis finished2024-03-14 00:13:48.455627
Duration4.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct406
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean203.5
Minimum1
Maximum406
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-03-14T09:13:48.512094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21.25
Q1102.25
median203.5
Q3304.75
95-th percentile385.75
Maximum406
Range405
Interquartile range (IQR)202.5

Descriptive statistics

Standard deviation117.34635
Coefficient of variation (CV)0.57664056
Kurtosis-1.2
Mean203.5
Median Absolute Deviation (MAD)101.5
Skewness0
Sum82621
Variance13770.167
MonotonicityStrictly increasing
2024-03-14T09:13:48.627998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
269 1
 
0.2%
279 1
 
0.2%
278 1
 
0.2%
277 1
 
0.2%
276 1
 
0.2%
275 1
 
0.2%
274 1
 
0.2%
273 1
 
0.2%
272 1
 
0.2%
Other values (396) 396
97.5%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
406 1
0.2%
405 1
0.2%
404 1
0.2%
403 1
0.2%
402 1
0.2%
401 1
0.2%
400 1
0.2%
399 1
0.2%
398 1
0.2%
397 1
0.2%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
노래연습장업
406 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노래연습장업 406
100.0%

Length

2024-03-14T09:13:48.730306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:13:48.818274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노래연습장업 406
100.0%

사업장명
Text

Distinct371
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-03-14T09:13:49.110360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length8.2931034
Min length1

Characters and Unicode

Total characters3367
Distinct characters358
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique343 ?
Unique (%)84.5%

Sample

1st row21세기 노래연습장
2nd row24시 노래연습장
3rd row314 노래연습장
4th rowB·T 노래연습장
5th rowBMW 노래연습장
ValueCountFrequency (%)
노래연습장 232
34.6%
코인노래연습장 14
 
2.1%
팡팡 5
 
0.7%
스카이 4
 
0.6%
파티 3
 
0.4%
수노래연습장 3
 
0.4%
쑝코인노래연습장 3
 
0.4%
세븐스타 3
 
0.4%
콜 2
 
0.3%
열창노래연습장 2
 
0.3%
Other values (374) 399
59.6%
2024-03-14T09:13:49.523379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
래 408
12.1%
노 407
12.1%
연 402
11.9%
장 402
11.9%
습 401
11.9%
264
 
7.8%
코 50
 
1.5%
인 47
 
1.4%
스 36
 
1.1%
타 21
 
0.6%
Other values (348) 929
27.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3024
89.8%
Space Separator 264
 
7.8%
Uppercase Letter 60
 
1.8%
Decimal Number 11
 
0.3%
Lowercase Letter 3
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
래 408
13.5%
노 407
13.5%
연 402
13.3%
장 402
13.3%
습 401
13.3%
코 50
 
1.7%
인 47
 
1.6%
스 36
 
1.2%
타 21
 
0.7%
이 21
 
0.7%
Other values (316) 829
27.4%
Uppercase Letter
ValueCountFrequency (%)
L 6
 
10.0%
M 6
 
10.0%
E 5
 
8.3%
K 4
 
6.7%
O 4
 
6.7%
C 4
 
6.7%
I 3
 
5.0%
N 3
 
5.0%
P 3
 
5.0%
T 3
 
5.0%
Other values (11) 19
31.7%
Decimal Number
ValueCountFrequency (%)
2 5
45.5%
4 3
27.3%
1 2
 
18.2%
3 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
v 1
33.3%
o 1
33.3%
Space Separator
ValueCountFrequency (%)
264
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3024
89.8%
Common 280
 
8.3%
Latin 63
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
래 408
13.5%
노 407
13.5%
연 402
13.3%
장 402
13.3%
습 401
13.3%
코 50
 
1.7%
인 47
 
1.6%
스 36
 
1.2%
타 21
 
0.7%
이 21
 
0.7%
Other values (316) 829
27.4%
Latin
ValueCountFrequency (%)
L 6
 
9.5%
M 6
 
9.5%
E 5
 
7.9%
K 4
 
6.3%
O 4
 
6.3%
C 4
 
6.3%
I 3
 
4.8%
N 3
 
4.8%
P 3
 
4.8%
T 3
 
4.8%
Other values (14) 22
34.9%
Common
ValueCountFrequency (%)
264
94.3%
2 5
 
1.8%
4 3
 
1.1%
( 2
 
0.7%
) 2
 
0.7%
1 2
 
0.7%
3 1
 
0.4%
· 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3024
89.8%
ASCII 342
 
10.2%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
래 408
13.5%
노 407
13.5%
연 402
13.3%
장 402
13.3%
습 401
13.3%
코 50
 
1.7%
인 47
 
1.6%
스 36
 
1.2%
타 21
 
0.7%
이 21
 
0.7%
Other values (316) 829
27.4%
ASCII
ValueCountFrequency (%)
264
77.2%
L 6
 
1.8%
M 6
 
1.8%
2 5
 
1.5%
E 5
 
1.5%
K 4
 
1.2%
O 4
 
1.2%
C 4
 
1.2%
I 3
 
0.9%
N 3
 
0.9%
Other values (21) 38
 
11.1%
None
ValueCountFrequency (%)
· 1
100.0%

인허가일자
Date

Distinct368
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum1994-02-24 00:00:00
Maximum2023-02-24 00:00:00
2024-03-14T09:13:49.636953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:49.738762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

도로명주소
Text

Distinct398
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-03-14T09:13:50.061079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length23.655172
Min length21

Characters and Unicode

Total characters9604
Distinct characters161
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

Unique390 ?
Unique (%)96.1%

Sample

1st row전북특별자치도 전주시 완산구 공수내로 22
2nd row전북특별자치도 전주시 완산구 하거마6길 39
3rd row전북특별자치도 전주시 완산구 전주객사4길 44-31
4th row전북특별자치도 전주시 완산구 전주객사4길 74-6
5th row전북특별자치도 전주시 완산구 홍산중앙로 20
ValueCountFrequency (%)
전북특별자치도 406
20.0%
전주시 406
20.0%
완산구 253
 
12.5%
덕진구 153
 
7.5%
용리로 17
 
0.8%
붓내3길 15
 
0.7%
건산로 14
 
0.7%
명륜4길 12
 
0.6%
17 11
 
0.5%
홍산중앙로 11
 
0.5%
Other values (384) 732
36.1%
2024-03-14T09:13:50.495247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1624
16.9%
전 834
 
8.7%
주 424
 
4.4%
북 418
 
4.4%
자 412
 
4.3%
구 409
 
4.3%
시 409
 
4.3%
도 408
 
4.2%
특 406
 
4.2%
별 406
 
4.2%
Other values (151) 3854
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6718
70.0%
Space Separator 1624
 
16.9%
Decimal Number 1162
 
12.1%
Dash Punctuation 100
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 834
 
12.4%
주 424
 
6.3%
북 418
 
6.2%
자 412
 
6.1%
구 409
 
6.1%
시 409
 
6.1%
도 408
 
6.1%
특 406
 
6.0%
별 406
 
6.0%
치 406
 
6.0%
Other values (139) 2186
32.5%
Decimal Number
ValueCountFrequency (%)
1 241
20.7%
2 175
15.1%
3 148
12.7%
4 143
12.3%
7 90
 
7.7%
5 88
 
7.6%
6 79
 
6.8%
8 77
 
6.6%
9 63
 
5.4%
0 58
 
5.0%
Space Separator
ValueCountFrequency (%)
1624
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6718
70.0%
Common 2886
30.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 834
 
12.4%
주 424
 
6.3%
북 418
 
6.2%
자 412
 
6.1%
구 409
 
6.1%
시 409
 
6.1%
도 408
 
6.1%
특 406
 
6.0%
별 406
 
6.0%
치 406
 
6.0%
Other values (139) 2186
32.5%
Common
ValueCountFrequency (%)
1624
56.3%
1 241
 
8.4%
2 175
 
6.1%
3 148
 
5.1%
4 143
 
5.0%
- 100
 
3.5%
7 90
 
3.1%
5 88
 
3.0%
6 79
 
2.7%
8 77
 
2.7%
Other values (2) 121
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6718
70.0%
ASCII 2886
30.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1624
56.3%
1 241
 
8.4%
2 175
 
6.1%
3 148
 
5.1%
4 143
 
5.0%
- 100
 
3.5%
7 90
 
3.1%
5 88
 
3.0%
6 79
 
2.7%
8 77
 
2.7%
Other values (2) 121
 
4.2%
Hangul
ValueCountFrequency (%)
전 834
 
12.4%
주 424
 
6.3%
북 418
 
6.2%
자 412
 
6.1%
구 409
 
6.1%
시 409
 
6.1%
도 408
 
6.1%
특 406
 
6.0%
별 406
 
6.0%
치 406
 
6.0%
Other values (139) 2186
32.5%

지번주소
Text

Distinct398
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-03-14T09:13:50.692827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length29
Mean length26.955665
Min length23

Characters and Unicode

Total characters10944
Distinct characters61
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

Unique390 ?
Unique (%)96.1%

Sample

1st row전북특별자치도 전주시 완산구 서서학동 117-1
2nd row전북특별자치도 전주시 완산구 삼천동1가 608-4
3rd row전북특별자치도 전주시 완산구 고사동 193
4th row전북특별자치도 전주시 완산구 고사동 173
5th row전북특별자치도 전주시 완산구 효자동3가 1541-8
ValueCountFrequency (%)
전북특별자치도 406
20.0%
전주시 406
20.0%
완산구 253
12.5%
덕진구 153
 
7.5%
중화산동2가 54
 
2.7%
삼천동1가 44
 
2.2%
효자동3가 31
 
1.5%
서신동 30
 
1.5%
송천동2가 26
 
1.3%
평화동1가 22
 
1.1%
Other values (427) 605
29.8%
2024-03-14T09:13:51.012575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1624
 
14.8%
전 812
 
7.4%
자 462
 
4.2%
1 451
 
4.1%
동 413
 
3.8%
북 407
 
3.7%
주 406
 
3.7%
구 406
 
3.7%
시 406
 
3.7%
도 406
 
3.7%
Other values (51) 5151
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6867
62.7%
Decimal Number 2071
 
18.9%
Space Separator 1624
 
14.8%
Dash Punctuation 382
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 812
 
11.8%
자 462
 
6.7%
동 413
 
6.0%
북 407
 
5.9%
주 406
 
5.9%
구 406
 
5.9%
시 406
 
5.9%
도 406
 
5.9%
치 406
 
5.9%
별 406
 
5.9%
Other values (39) 2337
34.0%
Decimal Number
ValueCountFrequency (%)
1 451
21.8%
2 370
17.9%
5 190
9.2%
3 187
9.0%
6 183
8.8%
4 176
 
8.5%
7 171
 
8.3%
8 139
 
6.7%
9 125
 
6.0%
0 79
 
3.8%
Space Separator
ValueCountFrequency (%)
1624
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 382
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6867
62.7%
Common 4077
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 812
 
11.8%
자 462
 
6.7%
동 413
 
6.0%
북 407
 
5.9%
주 406
 
5.9%
구 406
 
5.9%
시 406
 
5.9%
도 406
 
5.9%
치 406
 
5.9%
별 406
 
5.9%
Other values (39) 2337
34.0%
Common
ValueCountFrequency (%)
1624
39.8%
1 451
 
11.1%
- 382
 
9.4%
2 370
 
9.1%
5 190
 
4.7%
3 187
 
4.6%
6 183
 
4.5%
4 176
 
4.3%
7 171
 
4.2%
8 139
 
3.4%
Other values (2) 204
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6867
62.7%
ASCII 4077
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1624
39.8%
1 451
 
11.1%
- 382
 
9.4%
2 370
 
9.1%
5 190
 
4.7%
3 187
 
4.6%
6 183
 
4.5%
4 176
 
4.3%
7 171
 
4.2%
8 139
 
3.4%
Other values (2) 204
 
5.0%
Hangul
ValueCountFrequency (%)
전 812
 
11.8%
자 462
 
6.7%
동 413
 
6.0%
북 407
 
5.9%
주 406
 
5.9%
구 406
 
5.9%
시 406
 
5.9%
도 406
 
5.9%
치 406
 
5.9%
별 406
 
5.9%
Other values (39) 2337
34.0%

위도
Real number (ℝ)

Distinct398
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.825626
Minimum35.786584
Maximum35.873756
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-03-14T09:13:51.145236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.786584
5-th percentile35.794583
Q135.812708
median35.821168
Q335.83696
95-th percentile35.86653
Maximum35.873756
Range0.0871717
Interquartile range (IQR)0.02425208

Descriptive statistics

Standard deviation0.021632767
Coefficient of variation (CV)0.000603835
Kurtosis-0.50893018
Mean35.825626
Median Absolute Deviation (MAD)0.01428346
Skewness0.40322038
Sum14545.204
Variance0.0004679766
MonotonicityNot monotonic
2024-03-14T09:13:51.251316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.83097945 2
 
0.5%
35.81555702 2
 
0.5%
35.84383074 2
 
0.5%
35.81887191 2
 
0.5%
35.84759188 2
 
0.5%
35.83726335 2
 
0.5%
35.81922362 2
 
0.5%
35.84369303 2
 
0.5%
35.83666214 1
 
0.2%
35.81769526 1
 
0.2%
Other values (388) 388
95.6%
ValueCountFrequency (%)
35.78658427 1
0.2%
35.78663451 1
0.2%
35.786848 1
0.2%
35.78824558 1
0.2%
35.79199004 1
0.2%
35.79269823 1
0.2%
35.79271355 1
0.2%
35.79291408 1
0.2%
35.79297247 1
0.2%
35.79301562 1
0.2%
ValueCountFrequency (%)
35.87375597 1
0.2%
35.87371223 1
0.2%
35.87364099 1
0.2%
35.87350255 1
0.2%
35.87344149 1
0.2%
35.87333918 1
0.2%
35.87314427 1
0.2%
35.87187206 1
0.2%
35.87137608 1
0.2%
35.86772839 1
0.2%

경도
Real number (ℝ)

Distinct398
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.12763
Minimum127.0595
Maximum127.17569
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-03-14T09:13:51.370004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.0595
5-th percentile127.10152
Q1127.1155
median127.12339
Q3127.14211
95-th percentile127.16951
Maximum127.17569
Range0.1161925
Interquartile range (IQR)0.0266103

Descriptive statistics

Standard deviation0.021393308
Coefficient of variation (CV)0.00016828212
Kurtosis0.72016204
Mean127.12763
Median Absolute Deviation (MAD)0.0104941
Skewness0.071440925
Sum51613.819
Variance0.00045767361
MonotonicityNot monotonic
2024-03-14T09:13:51.483594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1726887 2
 
0.5%
127.1074915 2
 
0.5%
127.1257302 2
 
0.5%
127.1446463 2
 
0.5%
127.1572527 2
 
0.5%
127.0599536 2
 
0.5%
127.1462568 2
 
0.5%
127.1261623 2
 
0.5%
127.1675424 1
 
0.2%
127.1423559 1
 
0.2%
Other values (388) 388
95.6%
ValueCountFrequency (%)
127.0594965 1
0.2%
127.0599536 2
0.5%
127.0599667 1
0.2%
127.059978 1
0.2%
127.0730231 1
0.2%
127.0738796 1
0.2%
127.0776571 1
0.2%
127.078653 1
0.2%
127.0794504 1
0.2%
127.0807915 1
0.2%
ValueCountFrequency (%)
127.175689 1
0.2%
127.1745622 1
0.2%
127.173692 1
0.2%
127.1732257 1
0.2%
127.1726887 2
0.5%
127.1724092 1
0.2%
127.1722258 1
0.2%
127.1722106 1
0.2%
127.1721854 1
0.2%
127.1721081 1
0.2%

전화번호
Text

MISSING 

Distinct249
Distinct (%)99.2%
Missing155
Missing (%)38.2%
Memory size3.3 KiB
2024-03-14T09:13:51.685428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters3012
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

Unique247 ?
Unique (%)98.4%

Sample

1st row063-288-6530
2nd row063-222-0522
3rd row063-283-5342
4th row063-223-5616
5th row063-224-8420
ValueCountFrequency (%)
063-274-0739 2
 
0.8%
063-253-1388 2
 
0.8%
063-221-0302 1
 
0.4%
063-284-1971 1
 
0.4%
063-274-5007 1
 
0.4%
063-278-9949 1
 
0.4%
063-655-4327 1
 
0.4%
063-246-2557 1
 
0.4%
063-242-2002 1
 
0.4%
063-227-0100 1
 
0.4%
Other values (239) 239
95.2%
2024-03-14T09:13:51.969537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 502
16.7%
2 495
16.4%
3 397
13.2%
0 389
12.9%
6 351
11.7%
7 184
 
6.1%
5 165
 
5.5%
4 151
 
5.0%
8 147
 
4.9%
1 132
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2510
83.3%
Dash Punctuation 502
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 495
19.7%
3 397
15.8%
0 389
15.5%
6 351
14.0%
7 184
 
7.3%
5 165
 
6.6%
4 151
 
6.0%
8 147
 
5.9%
1 132
 
5.3%
9 99
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 502
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3012
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 502
16.7%
2 495
16.4%
3 397
13.2%
0 389
12.9%
6 351
11.7%
7 184
 
6.1%
5 165
 
5.5%
4 151
 
5.0%
8 147
 
4.9%
1 132
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3012
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 502
16.7%
2 495
16.4%
3 397
13.2%
0 389
12.9%
6 351
11.7%
7 184
 
6.1%
5 165
 
5.5%
4 151
 
5.0%
8 147
 
4.9%
1 132
 
4.4%

시설면적
Real number (ℝ)

HIGH CORRELATION 

Distinct371
Distinct (%)91.8%
Missing2
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean179.55671
Minimum33
Maximum590.64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-03-14T09:13:52.125224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile89.235
Q1132.8075
median168.535
Q3214
95-th percentile301.5305
Maximum590.64
Range557.64
Interquartile range (IQR)81.1925

Descriptive statistics

Standard deviation69.702855
Coefficient of variation (CV)0.3881941
Kurtosis4.1457236
Mean179.55671
Median Absolute Deviation (MAD)38.88
Skewness1.2841046
Sum72540.91
Variance4858.488
MonotonicityNot monotonic
2024-03-14T09:13:52.243094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
132.0 4
 
1.0%
231.0 4
 
1.0%
165.0 3
 
0.7%
146.0 3
 
0.7%
133.0 3
 
0.7%
112.0 3
 
0.7%
126.15 2
 
0.5%
121.3 2
 
0.5%
130.0 2
 
0.5%
123.99 2
 
0.5%
Other values (361) 376
92.6%
ValueCountFrequency (%)
33.0 1
0.2%
39.6 1
0.2%
40.0 1
0.2%
41.7 1
0.2%
44.89 1
0.2%
52.65 1
0.2%
52.89 1
0.2%
54.45 1
0.2%
57.05 1
0.2%
61.51 1
0.2%
ValueCountFrequency (%)
590.64 1
0.2%
513.7 1
0.2%
401.84 1
0.2%
399.04 1
0.2%
384.54 1
0.2%
379.23 1
0.2%
364.7 1
0.2%
359.37 1
0.2%
353.61 1
0.2%
350.37 1
0.2%

노래방실수
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)6.5%
Missing3
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean7.9602978
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-03-14T09:13:52.337903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q15
median6
Q38
95-th percentile20
Maximum33
Range32
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.7482295
Coefficient of variation (CV)0.59648893
Kurtosis4.967558
Mean7.9602978
Median Absolute Deviation (MAD)1
Skewness2.1663844
Sum3208
Variance22.545683
MonotonicityNot monotonic
2024-03-14T09:13:52.656433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
5 91
22.4%
6 80
19.7%
7 72
17.7%
4 27
 
6.7%
8 27
 
6.7%
9 22
 
5.4%
10 12
 
3.0%
20 8
 
2.0%
15 7
 
1.7%
16 6
 
1.5%
Other values (16) 51
12.6%
ValueCountFrequency (%)
1 2
 
0.5%
2 1
 
0.2%
3 6
 
1.5%
4 27
 
6.7%
5 91
22.4%
6 80
19.7%
7 72
17.7%
8 27
 
6.7%
9 22
 
5.4%
10 12
 
3.0%
ValueCountFrequency (%)
33 1
 
0.2%
31 1
 
0.2%
25 2
 
0.5%
23 3
 
0.7%
22 5
1.2%
21 2
 
0.5%
20 8
2.0%
19 2
 
0.5%
18 6
1.5%
17 4
1.0%

청소년실수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct24
Distinct (%)8.0%
Missing105
Missing (%)25.9%
Infinite0
Infinite (%)0.0%
Mean3.923588
Minimum0
Maximum31
Zeros100
Zeros (%)24.6%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-03-14T09:13:52.789060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile18
Maximum31
Range31
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.9997896
Coefficient of variation (CV)1.5291589
Kurtosis2.6202186
Mean3.923588
Median Absolute Deviation (MAD)1
Skewness1.838406
Sum1181
Variance35.997475
MonotonicityNot monotonic
2024-03-14T09:13:52.888123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 100
24.6%
1 74
18.2%
2 36
 
8.9%
7 11
 
2.7%
20 8
 
2.0%
3 8
 
2.0%
8 8
 
2.0%
18 6
 
1.5%
15 6
 
1.5%
6 5
 
1.2%
Other values (14) 39
 
9.6%
(Missing) 105
25.9%
ValueCountFrequency (%)
0 100
24.6%
1 74
18.2%
2 36
 
8.9%
3 8
 
2.0%
4 4
 
1.0%
5 4
 
1.0%
6 5
 
1.2%
7 11
 
2.7%
8 8
 
2.0%
9 5
 
1.2%
ValueCountFrequency (%)
31 1
 
0.2%
25 1
 
0.2%
22 1
 
0.2%
21 2
 
0.5%
20 8
2.0%
18 6
1.5%
17 4
1.0%
16 3
 
0.7%
15 6
1.5%
14 2
 
0.5%

비상계단여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.6%
Missing88
Missing (%)21.7%
Memory size944.0 B
False
231 
True
87 
(Missing)
88 
ValueCountFrequency (%)
False 231
56.9%
True 87
 
21.4%
(Missing) 88
 
21.7%
2024-03-14T09:13:52.983757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

비상구여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.6%
Missing73
Missing (%)18.0%
Memory size944.0 B
False
229 
True
104 
(Missing)
73 
ValueCountFrequency (%)
False 229
56.4%
True 104
25.6%
(Missing) 73
 
18.0%
2024-03-14T09:13:53.048628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

자동환기여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.6%
Missing93
Missing (%)22.9%
Memory size944.0 B
False
231 
True
82 
(Missing)
93 
ValueCountFrequency (%)
False 231
56.9%
True 82
 
20.2%
(Missing) 93
22.9%
2024-03-14T09:13:53.112713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

청소년실여부
Boolean

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)1.1%
Missing218
Missing (%)53.7%
Memory size944.0 B
True
187 
False
 
1
(Missing)
218 
ValueCountFrequency (%)
True 187
46.1%
False 1
 
0.2%
(Missing) 218
53.7%
2024-03-14T09:13:53.211428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

특수조명여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.8%
Missing147
Missing (%)36.2%
Memory size944.0 B
False
230 
True
29 
(Missing)
147 
ValueCountFrequency (%)
False 230
56.7%
True 29
 
7.1%
(Missing) 147
36.2%
2024-03-14T09:13:53.329967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

방음시설여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.6%
Missing89
Missing (%)21.9%
Memory size944.0 B
False
231 
True
86 
(Missing)
89 
ValueCountFrequency (%)
False 231
56.9%
True 86
 
21.2%
(Missing) 89
 
21.9%
2024-03-14T09:13:53.421650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2024-03-14T09:13:47.539400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:45.048089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:45.490750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:45.964833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:46.696056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:47.133557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:47.613992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:45.127990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:45.579222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:46.075607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:46.783467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:47.206227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:47.680762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:45.194688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:45.646828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:46.162979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:46.846149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:47.264849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:47.750154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:45.268047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:45.733982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:46.444563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:46.922456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:47.334176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:47.826249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:45.338159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:45.815698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:46.509144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:46.985290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:47.403975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:47.903492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:45.416933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:45.898376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:46.599578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:47.057014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:13:47.474351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:13:53.478009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도시설면적노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부
연번1.0000.0000.0000.0000.1560.2450.2560.2680.2570.0000.0960.237
위도0.0001.0000.7980.1940.2030.1530.4240.3720.4150.0000.0000.396
경도0.0000.7981.0000.2480.3080.2410.4360.4030.5240.0000.1960.483
시설면적0.0000.1940.2481.0000.6200.2490.2190.2100.1910.2580.0000.204
노래방실수0.1560.2030.3080.6201.0000.8250.5720.4350.4080.2130.3730.420
청소년실수0.2450.1530.2410.2490.8251.0000.5250.6810.520NaN0.4530.518
비상계단여부0.2560.4240.4360.2190.5720.5251.0000.9980.9990.0000.9830.995
비상구여부0.2680.3720.4030.2100.4350.6810.9981.0000.9980.0000.9930.999
자동환기여부0.2570.4150.5240.1910.4080.5200.9990.9981.0000.0000.9820.995
청소년실여부0.0000.0000.0000.2580.213NaN0.0000.0000.0001.0000.0000.000
특수조명여부0.0960.0000.1960.0000.3730.4530.9830.9930.9820.0001.0000.992
방음시설여부0.2370.3960.4830.2040.4200.5180.9950.9990.9950.0000.9921.000
2024-03-14T09:13:53.598257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비상계단여부자동환기여부청소년실여부방음시설여부비상구여부특수조명여부
비상계단여부1.0000.9730.0000.9380.9600.881
자동환기여부0.9731.0000.0000.9360.9580.878
청소년실여부0.0000.0001.0000.0000.0000.000
방음시설여부0.9380.9360.0001.0000.9760.921
비상구여부0.9600.9580.0000.9761.0000.923
특수조명여부0.8810.8780.0000.9210.9231.000
2024-03-14T09:13:53.698977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도시설면적노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부
연번1.0000.0100.022-0.046-0.029-0.0380.1830.1940.1940.0000.0720.171
위도0.0101.0000.0950.1030.1590.0350.3210.2820.3140.0000.0000.300
경도0.0220.0951.000-0.0550.033-0.0830.3310.3050.3990.0000.1930.367
시설면적-0.0460.103-0.0551.0000.5560.0680.2160.2080.1880.2530.0000.202
노래방실수-0.0290.1590.0330.5561.0000.5520.4280.4310.4040.2090.2770.416
청소년실수-0.0380.035-0.0830.0680.5521.0000.5190.5210.5141.0000.3350.512
비상계단여부0.1830.3210.3310.2160.4280.5191.0000.9600.9730.0000.8810.938
비상구여부0.1940.2820.3050.2080.4310.5210.9601.0000.9580.0000.9230.976
자동환기여부0.1940.3140.3990.1880.4040.5140.9730.9581.0000.0000.8780.936
청소년실여부0.0000.0000.0000.2530.2091.0000.0000.0000.0001.0000.0000.000
특수조명여부0.0720.0000.1930.0000.2770.3350.8810.9230.8780.0001.0000.921
방음시설여부0.1710.3000.3670.2020.4160.5120.9380.9760.9360.0000.9211.000

Missing values

2024-03-14T09:13:48.017933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:13:48.184299image/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.
2024-03-14T09:13:48.358345image/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

연번업종사업장명인허가일자도로명주소지번주소위도경도전화번호시설면적노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부
01노래연습장업21세기 노래연습장2003-01-24전북특별자치도 전주시 완산구 공수내로 22전북특별자치도 전주시 완산구 서서학동 117-135.805591127.148555063-288-6530132.2341NNNYNN
12노래연습장업24시 노래연습장2000-12-21전북특별자치도 전주시 완산구 하거마6길 39전북특별자치도 전주시 완산구 삼천동1가 608-435.796834127.117069063-222-0522111.3751NNNYNN
23노래연습장업314 노래연습장2013-04-11전북특별자치도 전주시 완산구 전주객사4길 44-31전북특별자치도 전주시 완산구 고사동 19335.82026127.144377063-283-5342280.261717YYYY<NA>Y
34노래연습장업B·T 노래연습장2017-09-29전북특별자치도 전주시 완산구 전주객사4길 74-6전북특별자치도 전주시 완산구 고사동 17335.820944127.143436<NA>54.458<NA>YYYY<NA><NA>
45노래연습장업BMW 노래연습장2011-12-08전북특별자치도 전주시 완산구 홍산중앙로 20전북특별자치도 전주시 완산구 효자동3가 1541-835.815358127.109312<NA>218.260<NA><NA><NA><NA><NA><NA>
56노래연습장업CF 노래연습장1998-01-14전북특별자치도 전주시 완산구 용리로 76전북특별자치도 전주시 완산구 삼천동1가 604-135.798471127.11832063-223-5616178.25<NA>NNN<NA>NN
67노래연습장업COMON MUSIC PLEX 코인노래연습장2019-09-06전북특별자치도 전주시 완산구 평화로 209전북특별자치도 전주시 완산구 평화동1가 718-535.79531127.136133<NA>281.652525<NA>YYY<NA>Y
78노래연습장업I LOVE 뭉치 노래연습장2012-06-18전북특별자치도 전주시 완산구 후곡길 10전북특별자치도 전주시 완산구 효자동2가 1312-135.809628127.096028063-224-8420322.3299YYYY<NA>Y
89노래연습장업I Love 뭉치노래연습장2015-03-20전북특별자치도 전주시 완산구 홍산북로 70-19전북특별자치도 전주시 완산구 효자동3가 1538-135.816738127.10977063-227-227441.71<NA>YYY<NA><NA>Y
910노래연습장업JJ 노래연습장2015-05-01전북특별자치도 전주시 완산구 홍산남로 79전북특별자치도 전주시 완산구 효자동3가 1539-535.816047127.110678<NA>199.397<NA>YYY<NA><NA>Y
연번업종사업장명인허가일자도로명주소지번주소위도경도전화번호시설면적노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부
396397노래연습장업황궁 노래연습장2009-02-12전북특별자치도 전주시 완산구 장승배기로 399전북특별자치도 전주시 완산구 동서학동 256-1035.806187127.152371<NA>169.9751YYY<NA>YY
397398노래연습장업황방산 노래연습장2000-10-27전북특별자치도 전주시 완산구 서곡로 71전북특별자치도 전주시 완산구 효자동3가 1435-535.835345127.101206063-274-3378119.041NNNYNN
398399노래연습장업황소 노래연습장1999-04-14전북특별자치도 전주시 완산구 한두평3길 9전북특별자치도 전주시 완산구 중화산동2가 660-535.814895127.123924063-221-0302156.070NNN<NA>NN
399400노래연습장업황제노래연습장2015-04-14전북특별자치도 전주시 덕진구 명륜4길 11-10전북특별자치도 전주시 덕진구 덕진동1가 1261-2835.843333127.126079<NA>168.9277YYYY<NA>Y
400401노래연습장업황제노래연습장1999-06-28전북특별자치도 전주시 덕진구 건산로 82전북특별자치도 전주시 덕진구 진북동 256-435.832178127.146236063-275-1306168.1582NNNYNN
401402노래연습장업휠라 노래연습장1999-04-28전북특별자치도 전주시 완산구 성지산3길 15전북특별자치도 전주시 완산구 효자동1가 55235.805372127.121952063-224-6217138.175<NA>NNN<NA>NN
402403노래연습장업휴노래연습장2010-02-18전북특별자치도 전주시 덕진구 건산로 258전북특별자치도 전주시 덕진구 인후동1가 846-935.834853127.165296<NA>186.5450YYY<NA><NA>Y
403404노래연습장업힐노래연습장2001-04-27전북특별자치도 전주시 덕진구 명륜4길 17-7전북특별자치도 전주시 덕진구 덕진동1가 1261-1935.843693127.126162063-253-1388163.5687NNNYNN
404405노래연습장업힐노래연습장22011-12-27전북특별자치도 전주시 덕진구 명륜4길 17-7전북특별자치도 전주시 덕진구 덕진동1가 1261-1935.843693127.126162063-253-1388163.5677<NA><NA><NA>Y<NA><NA>
405406노래연습장업힐링 노래연습장2013-11-06전북특별자치도 전주시 완산구 홍산중앙로 46전북특별자치도 전주시 완산구 효자동3가 1528-1535.817608127.109348<NA>250.6972YYYY<NA>Y