Overview

Dataset statistics

Number of variables7
Number of observations147
Missing cells71
Missing cells (%)6.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.3 KiB
Average record size in memory57.9 B

Variable types

Numeric1
Categorical1
DateTime2
Text3

Dataset

Description광주광역시 광산구 관내에 위치한 단란주점 현황 정보(구분, 허가(신고)일, 사업장명, 주소, 소재지전화번호 등)를 제공합니다.
Author광주광역시 광산구
URLhttps://www.data.go.kr/data/15108745/fileData.do

Alerts

구분 has constant value ""Constant
데이터기준일자 has constant value ""Constant
소재지전화 has 71 (48.3%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:52:48.106530
Analysis finished2023-12-12 08:52:48.930416
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct147
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74
Minimum1
Maximum147
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T17:52:49.025513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.3
Q137.5
median74
Q3110.5
95-th percentile139.7
Maximum147
Range146
Interquartile range (IQR)73

Descriptive statistics

Standard deviation42.579338
Coefficient of variation (CV)0.57539646
Kurtosis-1.2
Mean74
Median Absolute Deviation (MAD)37
Skewness0
Sum10878
Variance1813
MonotonicityStrictly increasing
2023-12-12T17:52:49.213976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
94 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
Other values (137) 137
93.2%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
단란주점
147 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단란주점 147
100.0%

Length

2023-12-12T17:52:49.479621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:52:49.666279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단란주점 147
100.0%

허가(신고)일
Date

Distinct139
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1994-02-21 00:00:00
Maximum2023-09-12 00:00:00
2023-12-12T17:52:49.896454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:50.399870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업장명
Text

Distinct144
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T17:52:50.691473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length12
Mean length5.5170068
Min length1

Characters and Unicode

Total characters811
Distinct characters242
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique141 ?
Unique (%)95.9%

Sample

1st row술마시는대박노래홀
2nd rowKTV(케이티브이)
3rd row엘에이7080
4th row엑스포
5th row아미바(Amy Bar)
ValueCountFrequency (%)
썸7080 2
 
1.3%
오렌지 2
 
1.3%
황진이 2
 
1.3%
필7080 1
 
0.7%
노라7080라이브 1
 
0.7%
킹7080 1
 
0.7%
술마시는스타노래홀 1
 
0.7%
술마시는대박노래홀 1
 
0.7%
보아 1
 
0.7%
술마시는포인트노래홀 1
 
0.7%
Other values (139) 139
91.4%
2023-12-12T17:52:51.271608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 83
 
10.2%
8 40
 
4.9%
7 39
 
4.8%
래 30
 
3.7%
홀 30
 
3.7%
노 28
 
3.5%
마 17
 
2.1%
이 16
 
2.0%
술 16
 
2.0%
는 15
 
1.8%
Other values (232) 497
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 576
71.0%
Decimal Number 167
 
20.6%
Uppercase Letter 35
 
4.3%
Lowercase Letter 10
 
1.2%
Open Punctuation 7
 
0.9%
Close Punctuation 7
 
0.9%
Space Separator 5
 
0.6%
Math Symbol 2
 
0.2%
Other Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
래 30
 
5.2%
홀 30
 
5.2%
노 28
 
4.9%
마 17
 
3.0%
이 16
 
2.8%
술 16
 
2.8%
는 15
 
2.6%
시 14
 
2.4%
아 13
 
2.3%
트 13
 
2.3%
Other values (192) 384
66.7%
Uppercase Letter
ValueCountFrequency (%)
B 4
 
11.4%
E 4
 
11.4%
R 3
 
8.6%
L 2
 
5.7%
S 2
 
5.7%
A 2
 
5.7%
C 2
 
5.7%
P 2
 
5.7%
U 2
 
5.7%
K 2
 
5.7%
Other values (9) 10
28.6%
Lowercase Letter
ValueCountFrequency (%)
r 2
20.0%
a 2
20.0%
w 1
10.0%
e 1
10.0%
y 1
10.0%
t 1
10.0%
m 1
10.0%
k 1
10.0%
Decimal Number
ValueCountFrequency (%)
0 83
49.7%
8 40
24.0%
7 39
23.4%
9 3
 
1.8%
2 1
 
0.6%
1 1
 
0.6%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 576
71.0%
Common 190
 
23.4%
Latin 41
 
5.1%
Cyrillic 4
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
래 30
 
5.2%
홀 30
 
5.2%
노 28
 
4.9%
마 17
 
3.0%
이 16
 
2.8%
술 16
 
2.8%
는 15
 
2.6%
시 14
 
2.4%
아 13
 
2.3%
트 13
 
2.3%
Other values (192) 384
66.7%
Latin
ValueCountFrequency (%)
B 4
 
9.8%
E 4
 
9.8%
R 3
 
7.3%
L 2
 
4.9%
S 2
 
4.9%
A 2
 
4.9%
C 2
 
4.9%
P 2
 
4.9%
r 2
 
4.9%
a 2
 
4.9%
Other values (13) 16
39.0%
Common
ValueCountFrequency (%)
0 83
43.7%
8 40
21.1%
7 39
20.5%
( 7
 
3.7%
) 7
 
3.7%
5
 
2.6%
9 3
 
1.6%
2 1
 
0.5%
> 1
 
0.5%
< 1
 
0.5%
Other values (3) 3
 
1.6%
Cyrillic
ValueCountFrequency (%)
С 1
25.0%
О 1
25.0%
Ё 1
25.0%
Л 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 576
71.0%
ASCII 231
28.5%
Cyrillic 4
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 83
35.9%
8 40
17.3%
7 39
16.9%
( 7
 
3.0%
) 7
 
3.0%
5
 
2.2%
B 4
 
1.7%
E 4
 
1.7%
R 3
 
1.3%
9 3
 
1.3%
Other values (26) 36
15.6%
Hangul
ValueCountFrequency (%)
래 30
 
5.2%
홀 30
 
5.2%
노 28
 
4.9%
마 17
 
3.0%
이 16
 
2.8%
술 16
 
2.8%
는 15
 
2.6%
시 14
 
2.4%
아 13
 
2.3%
트 13
 
2.3%
Other values (192) 384
66.7%
Cyrillic
ValueCountFrequency (%)
С 1
25.0%
О 1
25.0%
Ё 1
25.0%
Л 1
25.0%

주소
Text

Distinct142
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T17:52:51.550689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length38
Mean length31.945578
Min length22

Characters and Unicode

Total characters4696
Distinct characters82
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

Unique137 ?
Unique (%)93.2%

Sample

1st row광주광역시 광산구 내상로 27 (송정동)
2nd row광주광역시 광산구 사암로 363 (월곡동)
3rd row광주광역시 광산구 사암로171번길 78 (우산동)
4th row광주광역시 광산구 사암로 285 (월곡동)
5th row광주광역시 광산구 사암로 286 (월곡동)
ValueCountFrequency (%)
광주광역시 147
17.7%
광산구 147
17.7%
2층 46
 
5.5%
쌍암동 23
 
2.8%
우산동 22
 
2.7%
월계동 21
 
2.5%
3층 19
 
2.3%
사암로216번길 15
 
1.8%
첨단중앙로152번길 14
 
1.7%
첨단중앙로106번길 12
 
1.4%
Other values (195) 364
43.9%
2023-12-12T17:52:51.940459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
683
 
14.5%
광 443
 
9.4%
2 215
 
4.6%
( 184
 
3.9%
) 184
 
3.9%
산 181
 
3.9%
1 177
 
3.8%
동 149
 
3.2%
주 147
 
3.1%
구 147
 
3.1%
Other values (72) 2186
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2604
55.5%
Decimal Number 872
 
18.6%
Space Separator 683
 
14.5%
Open Punctuation 184
 
3.9%
Close Punctuation 184
 
3.9%
Other Punctuation 121
 
2.6%
Dash Punctuation 47
 
1.0%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 443
17.0%
산 181
 
7.0%
동 149
 
5.7%
주 147
 
5.6%
구 147
 
5.6%
로 147
 
5.6%
역 147
 
5.6%
시 147
 
5.6%
층 118
 
4.5%
길 113
 
4.3%
Other values (56) 865
33.2%
Decimal Number
ValueCountFrequency (%)
2 215
24.7%
1 177
20.3%
0 92
10.6%
3 87
10.0%
6 80
 
9.2%
5 60
 
6.9%
8 53
 
6.1%
4 48
 
5.5%
7 35
 
4.0%
9 25
 
2.9%
Space Separator
ValueCountFrequency (%)
683
100.0%
Open Punctuation
ValueCountFrequency (%)
( 184
100.0%
Close Punctuation
ValueCountFrequency (%)
) 184
100.0%
Other Punctuation
ValueCountFrequency (%)
, 121
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2604
55.5%
Common 2091
44.5%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 443
17.0%
산 181
 
7.0%
동 149
 
5.7%
주 147
 
5.6%
구 147
 
5.6%
로 147
 
5.6%
역 147
 
5.6%
시 147
 
5.6%
층 118
 
4.5%
길 113
 
4.3%
Other values (56) 865
33.2%
Common
ValueCountFrequency (%)
683
32.7%
2 215
 
10.3%
( 184
 
8.8%
) 184
 
8.8%
1 177
 
8.5%
, 121
 
5.8%
0 92
 
4.4%
3 87
 
4.2%
6 80
 
3.8%
5 60
 
2.9%
Other values (5) 208
 
9.9%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2604
55.5%
ASCII 2092
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
683
32.6%
2 215
 
10.3%
( 184
 
8.8%
) 184
 
8.8%
1 177
 
8.5%
, 121
 
5.8%
0 92
 
4.4%
3 87
 
4.2%
6 80
 
3.8%
5 60
 
2.9%
Other values (6) 209
 
10.0%
Hangul
ValueCountFrequency (%)
광 443
17.0%
산 181
 
7.0%
동 149
 
5.7%
주 147
 
5.6%
구 147
 
5.6%
로 147
 
5.6%
역 147
 
5.6%
시 147
 
5.6%
층 118
 
4.5%
길 113
 
4.3%
Other values (56) 865
33.2%

소재지전화
Text

MISSING 

Distinct76
Distinct (%)100.0%
Missing71
Missing (%)48.3%
Memory size1.3 KiB
2023-12-12T17:52:52.183228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.960526
Min length12

Characters and Unicode

Total characters1061
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

Unique76 ?
Unique (%)100.0%

Sample

1st row 062- 943-1596
2nd row 062- 951-0540
3rd row 062- 942-9574
4th row 062- 953-0477
5th row 062- 954-0774
ValueCountFrequency (%)
062 73
38.2%
971 8
 
4.2%
951 6
 
3.1%
959 4
 
2.1%
973 4
 
2.1%
3
 
1.6%
956 3
 
1.6%
944 2
 
1.0%
7080 2
 
1.0%
941 2
 
1.0%
Other values (82) 84
44.0%
2023-12-12T17:52:52.580280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 152
14.3%
149
14.0%
0 124
11.7%
2 115
10.8%
6 113
10.7%
9 100
9.4%
5 71
6.7%
7 71
6.7%
1 67
6.3%
4 36
 
3.4%
Other values (2) 63
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 760
71.6%
Dash Punctuation 152
 
14.3%
Space Separator 149
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 124
16.3%
2 115
15.1%
6 113
14.9%
9 100
13.2%
5 71
9.3%
7 71
9.3%
1 67
8.8%
4 36
 
4.7%
3 35
 
4.6%
8 28
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 152
100.0%
Space Separator
ValueCountFrequency (%)
149
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1061
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 152
14.3%
149
14.0%
0 124
11.7%
2 115
10.8%
6 113
10.7%
9 100
9.4%
5 71
6.7%
7 71
6.7%
1 67
6.3%
4 36
 
3.4%
Other values (2) 63
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1061
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 152
14.3%
149
14.0%
0 124
11.7%
2 115
10.8%
6 113
10.7%
9 100
9.4%
5 71
6.7%
7 71
6.7%
1 67
6.3%
4 36
 
3.4%
Other values (2) 63
5.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2023-10-30 00:00:00
Maximum2023-10-30 00:00:00
2023-12-12T17:52:52.715294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:52.852939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T17:52:48.524566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:52:52.928331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소재지전화
연번1.0001.000
소재지전화1.0001.000

Missing values

2023-12-12T17:52:48.711272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:52:48.869166image/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

연번구분허가(신고)일사업장명주소소재지전화데이터기준일자
01단란주점1994-02-21술마시는대박노래홀광주광역시 광산구 내상로 27 (송정동)062- 943-15962023-10-30
12단란주점1994-10-14KTV(케이티브이)광주광역시 광산구 사암로 363 (월곡동)062- 951-05402023-10-30
23단란주점1994-10-14엘에이7080광주광역시 광산구 사암로171번길 78 (우산동)062- 942-95742023-10-30
34단란주점1995-07-04엑스포광주광역시 광산구 사암로 285 (월곡동)062- 953-04772023-10-30
45단란주점1995-02-21아미바(Amy Bar)광주광역시 광산구 사암로 286 (월곡동)<NA>2023-10-30
56단란주점1995-10-05뉴스타(New Star)광주광역시 광산구 무진대로211번길 21-23 (우산동)062- 954-07742023-10-30
67단란주점1996-11-12봉순이7080광주광역시 광산구 광산로 27-4 (송정동)062- 945-27942023-10-30
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