Overview

Dataset statistics

Number of variables5
Number of observations166
Missing cells3
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory41.8 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description전북별자치도 군산시 소재한 음악산업진흥에 관한 법률에 따른 노래연습장현황(업종, 업소명, 소재지-도로명, 소재지-지번)을 제공합니다.
Author전북특별자치도 군산시
URLhttps://www.data.go.kr/data/15086187/fileData.do

Alerts

업종 has constant value ""Constant
소재지도로명주소 has 3 (1.8%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 10:59:06.302862
Analysis finished2024-03-14 10:59:07.520377
Duration1.22 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct166
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.5
Minimum1
Maximum166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-03-14T19:59:07.739503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.25
Q142.25
median83.5
Q3124.75
95-th percentile157.75
Maximum166
Range165
Interquartile range (IQR)82.5

Descriptive statistics

Standard deviation48.064193
Coefficient of variation (CV)0.57561908
Kurtosis-1.2
Mean83.5
Median Absolute Deviation (MAD)41.5
Skewness0
Sum13861
Variance2310.1667
MonotonicityStrictly increasing
2024-03-14T19:59:08.377111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
106 1
 
0.6%
108 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
111 1
 
0.6%
112 1
 
0.6%
113 1
 
0.6%
114 1
 
0.6%
115 1
 
0.6%
Other values (156) 156
94.0%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
166 1
0.6%
165 1
0.6%
164 1
0.6%
163 1
0.6%
162 1
0.6%
161 1
0.6%
160 1
0.6%
159 1
0.6%
158 1
0.6%
157 1
0.6%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
노래연습장
166 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노래연습장 166
100.0%

Length

2024-03-14T19:59:08.789378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:59:09.101489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노래연습장 166
100.0%

상호명
Text

Distinct164
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-14T19:59:09.932114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length7.686747
Min length6

Characters and Unicode

Total characters1276
Distinct characters224
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique162 ?
Unique (%)97.6%

Sample

1st row희트노래연습장
2nd row아시아나노래연습장
3rd row하모니노래연습장
4th row코스모노래연습장
5th row영가요노래연습장
ValueCountFrequency (%)
노래연습장 14
 
7.7%
팀노래연습장 2
 
1.1%
팡팡노래연습장 2
 
1.1%
하나노래연습장 1
 
0.6%
다다2노래연습장 1
 
0.6%
삐용노래연습장 1
 
0.6%
서진노래연습장 1
 
0.6%
희트노래연습장 1
 
0.6%
가다 1
 
0.6%
나도 1
 
0.6%
Other values (156) 156
86.2%
2024-03-14T19:59:11.229676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
연 167
13.1%
노 166
13.0%
래 166
13.0%
습 166
13.0%
장 166
13.0%
15
 
1.2%
코 13
 
1.0%
인 12
 
0.9%
리 12
 
0.9%
스 10
 
0.8%
Other values (214) 383
30.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1227
96.2%
Space Separator 15
 
1.2%
Decimal Number 14
 
1.1%
Uppercase Letter 12
 
0.9%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%
Lowercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
연 167
13.6%
노 166
13.5%
래 166
13.5%
습 166
13.5%
장 166
13.5%
코 13
 
1.1%
인 12
 
1.0%
리 12
 
1.0%
스 10
 
0.8%
하 9
 
0.7%
Other values (191) 340
27.7%
Uppercase Letter
ValueCountFrequency (%)
T 2
16.7%
J 2
16.7%
M 1
8.3%
K 1
8.3%
G 1
8.3%
X 1
8.3%
O 1
8.3%
P 1
8.3%
D 1
8.3%
C 1
8.3%
Decimal Number
ValueCountFrequency (%)
2 5
35.7%
1 2
 
14.3%
0 2
 
14.3%
9 1
 
7.1%
3 1
 
7.1%
7 1
 
7.1%
8 1
 
7.1%
5 1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
h 1
50.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1227
96.2%
Common 35
 
2.7%
Latin 14
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
연 167
13.6%
노 166
13.5%
래 166
13.5%
습 166
13.5%
장 166
13.5%
코 13
 
1.1%
인 12
 
1.0%
리 12
 
1.0%
스 10
 
0.8%
하 9
 
0.7%
Other values (191) 340
27.7%
Latin
ValueCountFrequency (%)
T 2
14.3%
J 2
14.3%
M 1
7.1%
K 1
7.1%
t 1
7.1%
h 1
7.1%
G 1
7.1%
X 1
7.1%
O 1
7.1%
P 1
7.1%
Other values (2) 2
14.3%
Common
ValueCountFrequency (%)
15
42.9%
2 5
 
14.3%
( 3
 
8.6%
) 3
 
8.6%
1 2
 
5.7%
0 2
 
5.7%
9 1
 
2.9%
3 1
 
2.9%
7 1
 
2.9%
8 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1227
96.2%
ASCII 49
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
연 167
13.6%
노 166
13.5%
래 166
13.5%
습 166
13.5%
장 166
13.5%
코 13
 
1.1%
인 12
 
1.0%
리 12
 
1.0%
스 10
 
0.8%
하 9
 
0.7%
Other values (191) 340
27.7%
ASCII
ValueCountFrequency (%)
15
30.6%
2 5
 
10.2%
( 3
 
6.1%
) 3
 
6.1%
1 2
 
4.1%
0 2
 
4.1%
T 2
 
4.1%
J 2
 
4.1%
M 1
 
2.0%
K 1
 
2.0%
Other values (13) 13
26.5%

소재지도로명주소
Text

MISSING 

Distinct159
Distinct (%)97.5%
Missing3
Missing (%)1.8%
Memory size1.4 KiB
2024-03-14T19:59:12.808634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length38
Mean length26.607362
Min length21

Characters and Unicode

Total characters4337
Distinct characters143
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)95.1%

Sample

1st row전북특별자치도 군산시 동령길 27 (장미동)
2nd row전북특별자치도 군산시 구암3.1로 204 (구암동)
3rd row전북특별자치도 군산시 아리랑로 17 (개복동)
4th row전북특별자치도 군산시 신설4길 9 (나운동)
5th row전북특별자치도 군산시 동령길 59 (장미동)
ValueCountFrequency (%)
전북특별자치도 163
 
18.9%
군산시 163
 
18.9%
나운동 33
 
3.8%
수송동 16
 
1.9%
수송로 13
 
1.5%
소룡동 12
 
1.4%
2층 12
 
1.4%
조촌동 10
 
1.2%
미룡동 10
 
1.2%
장미동 9
 
1.0%
Other values (247) 423
49.0%
2024-03-14T19:59:14.814555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
703
 
16.2%
도 178
 
4.1%
산 175
 
4.0%
북 173
 
4.0%
동 171
 
3.9%
시 167
 
3.9%
자 166
 
3.8%
군 164
 
3.8%
치 163
 
3.8%
별 163
 
3.8%
Other values (133) 2114
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2763
63.7%
Space Separator 703
 
16.2%
Decimal Number 495
 
11.4%
Open Punctuation 156
 
3.6%
Close Punctuation 156
 
3.6%
Other Punctuation 43
 
1.0%
Dash Punctuation 21
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 178
 
6.4%
산 175
 
6.3%
북 173
 
6.3%
동 171
 
6.2%
시 167
 
6.0%
자 166
 
6.0%
군 164
 
5.9%
치 163
 
5.9%
별 163
 
5.9%
특 163
 
5.9%
Other values (117) 1080
39.1%
Decimal Number
ValueCountFrequency (%)
2 105
21.2%
1 101
20.4%
3 57
11.5%
4 50
10.1%
5 36
 
7.3%
9 32
 
6.5%
8 32
 
6.5%
6 30
 
6.1%
7 28
 
5.7%
0 24
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 41
95.3%
. 2
 
4.7%
Space Separator
ValueCountFrequency (%)
703
100.0%
Open Punctuation
ValueCountFrequency (%)
( 156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2763
63.7%
Common 1574
36.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 178
 
6.4%
산 175
 
6.3%
북 173
 
6.3%
동 171
 
6.2%
시 167
 
6.0%
자 166
 
6.0%
군 164
 
5.9%
치 163
 
5.9%
별 163
 
5.9%
특 163
 
5.9%
Other values (117) 1080
39.1%
Common
ValueCountFrequency (%)
703
44.7%
( 156
 
9.9%
) 156
 
9.9%
2 105
 
6.7%
1 101
 
6.4%
3 57
 
3.6%
4 50
 
3.2%
, 41
 
2.6%
5 36
 
2.3%
9 32
 
2.0%
Other values (6) 137
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2763
63.7%
ASCII 1574
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
703
44.7%
( 156
 
9.9%
) 156
 
9.9%
2 105
 
6.7%
1 101
 
6.4%
3 57
 
3.6%
4 50
 
3.2%
, 41
 
2.6%
5 36
 
2.3%
9 32
 
2.0%
Other values (6) 137
 
8.7%
Hangul
ValueCountFrequency (%)
도 178
 
6.4%
산 175
 
6.3%
북 173
 
6.3%
동 171
 
6.2%
시 167
 
6.0%
자 166
 
6.0%
군 164
 
5.9%
치 163
 
5.9%
별 163
 
5.9%
특 163
 
5.9%
Other values (117) 1080
39.1%

소재지지번주소
Text

Distinct163
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-14T19:59:16.430785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length39
Mean length24.078313
Min length20

Characters and Unicode

Total characters3997
Distinct characters103
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

Unique160 ?
Unique (%)96.4%

Sample

1st row전북특별자치도 군산시 장미동 11-8
2nd row전북특별자치도 군산시 구암동 322-2
3rd row전북특별자치도 군산시 개복동 12-10
4th row전북특별자치도 군산시 나운동 794-1
5th row전북특별자치도 군산시 장미동 21-4
ValueCountFrequency (%)
전북특별자치도 166
22.7%
군산시 166
22.7%
나운동 32
 
4.4%
수송동 16
 
2.2%
소룡동 12
 
1.6%
2층 11
 
1.5%
미룡동 10
 
1.4%
조촌동 10
 
1.4%
장미동 9
 
1.2%
지곡동 8
 
1.1%
Other values (231) 291
39.8%
2024-03-14T19:59:18.494670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
725
18.1%
도 178
 
4.5%
산 176
 
4.4%
북 173
 
4.3%
자 171
 
4.3%
군 166
 
4.2%
전 166
 
4.2%
치 166
 
4.2%
별 166
 
4.2%
특 166
 
4.2%
Other values (93) 1744
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2304
57.6%
Decimal Number 773
 
19.3%
Space Separator 725
 
18.1%
Dash Punctuation 156
 
3.9%
Open Punctuation 15
 
0.4%
Close Punctuation 15
 
0.4%
Other Punctuation 8
 
0.2%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 178
 
7.7%
산 176
 
7.6%
북 173
 
7.5%
자 171
 
7.4%
군 166
 
7.2%
전 166
 
7.2%
치 166
 
7.2%
별 166
 
7.2%
특 166
 
7.2%
시 166
 
7.2%
Other values (77) 610
26.5%
Decimal Number
ValueCountFrequency (%)
1 150
19.4%
2 116
15.0%
5 90
11.6%
4 83
10.7%
8 82
10.6%
3 80
10.3%
7 48
 
6.2%
0 47
 
6.1%
6 46
 
6.0%
9 31
 
4.0%
Space Separator
ValueCountFrequency (%)
725
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 156
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2304
57.6%
Common 1692
42.3%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 178
 
7.7%
산 176
 
7.6%
북 173
 
7.5%
자 171
 
7.4%
군 166
 
7.2%
전 166
 
7.2%
치 166
 
7.2%
별 166
 
7.2%
특 166
 
7.2%
시 166
 
7.2%
Other values (77) 610
26.5%
Common
ValueCountFrequency (%)
725
42.8%
- 156
 
9.2%
1 150
 
8.9%
2 116
 
6.9%
5 90
 
5.3%
4 83
 
4.9%
8 82
 
4.8%
3 80
 
4.7%
7 48
 
2.8%
0 47
 
2.8%
Other values (5) 115
 
6.8%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2304
57.6%
ASCII 1693
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
725
42.8%
- 156
 
9.2%
1 150
 
8.9%
2 116
 
6.9%
5 90
 
5.3%
4 83
 
4.9%
8 82
 
4.8%
3 80
 
4.7%
7 48
 
2.8%
0 47
 
2.8%
Other values (6) 116
 
6.9%
Hangul
ValueCountFrequency (%)
도 178
 
7.7%
산 176
 
7.6%
북 173
 
7.5%
자 171
 
7.4%
군 166
 
7.2%
전 166
 
7.2%
치 166
 
7.2%
별 166
 
7.2%
특 166
 
7.2%
시 166
 
7.2%
Other values (77) 610
26.5%

Interactions

2024-03-14T19:59:06.750099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-03-14T19:59:07.081443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:59:07.398520image/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

순번업종상호명소재지도로명주소소재지지번주소
01노래연습장희트노래연습장전북특별자치도 군산시 동령길 27 (장미동)전북특별자치도 군산시 장미동 11-8
12노래연습장아시아나노래연습장전북특별자치도 군산시 구암3.1로 204 (구암동)전북특별자치도 군산시 구암동 322-2
23노래연습장하모니노래연습장전북특별자치도 군산시 아리랑로 17 (개복동)전북특별자치도 군산시 개복동 12-10
34노래연습장코스모노래연습장전북특별자치도 군산시 신설4길 9 (나운동)전북특별자치도 군산시 나운동 794-1
45노래연습장영가요노래연습장전북특별자치도 군산시 동령길 59 (장미동)전북특별자치도 군산시 장미동 21-4
56노래연습장한마음노래연습장전북특별자치도 군산시 해망로 243 (장미동)전북특별자치도 군산시 장미동 42-2
67노래연습장방방노래연습장전북특별자치도 군산시 대학로 278 (나운동)전북특별자치도 군산시 나운동 780-19
78노래연습장왕방울노래연습장전북특별자치도 군산시 나운로 120 (나운동)전북특별자치도 군산시 나운동 843-2
89노래연습장월드노래연습장전북특별자치도 군산시 공단대로 621 (소룡동)전북특별자치도 군산시 소룡동 1539
910노래연습장아우토반노래연습장전북특별자치도 군산시 대학로 52 (명산동)전북특별자치도 군산시 명산동 1-4
순번업종상호명소재지도로명주소소재지지번주소
156157노래연습장킹코인노래연습장전북특별자치도 군산시 수송북로 22, 3층 (수송동)전북특별자치도 군산시 수송동 831-1 3층
157158노래연습장제우스코인노래연습장전북특별자치도 군산시 하나운로 38, 나운프라자(지하1층) (나운동)전북특별자치도 군산시 나운동 107-8 나운프라자
158159노래연습장퀸코인노래연습장전북특별자치도 군산시 월명로 255, 4층 402호 (수송동)전북특별자치도 군산시 수송동 808-1 4층 402호
159160노래연습장세븐스타코인노래연습장 디오션점전북특별자치도 군산시 궁포1로 24-9, 엔비빌딩 402호,403(일부)호 (조촌동)전북특별자치도 군산시 조촌동 2-18 엔비빌딩 402호,403(일부)호
160161노래연습장하나노래연습장전북특별자치도 군산시 칠성5길 32, 2층 202호 (미룡동)전북특별자치도 군산시 미룡동 846-6 2층 202호
161162노래연습장세종노래연습장전북특별자치도 군산시 궁포1로 24-5, 4층 403호 (조촌동)전북특별자치도 군산시 조촌동 2-21 4층 403호
162163노래연습장별별킹코인노래연습장전북특별자치도 군산시 의료원로 121, 지하1층 (나운동)전북특별자치도 군산시 나운동 156-7 지하1층
163164노래연습장명품노래연습장전북특별자치도 군산시 미장안7길 18, 3층 1호 (미장동)전북특별자치도 군산시 미장동 518-17
164165노래연습장까르페노래연습장전북특별자치도 군산시 가도로 197, 102호 (오식도동)전북특별자치도 군산시 오식도동 625-5 102호
165166노래연습장샾노래연습장전북특별자치도 군산시 수송로 16, 1 (나운동)전북특별자치도 군산시 나운동 829-3 1