Overview

Dataset statistics

Number of variables4
Number of observations175
Missing cells69
Missing cells (%)9.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory33.8 B

Variable types

Numeric1
Text3

Dataset

Description인천광역시 부평구 유흥주점 현황 데이터는 유흥주점 업소명, 업소 소재지, 업소 전화번호에 대한 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15104148/fileData.do

Alerts

소재지전화 has 69 (39.4%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:44:40.519252
Analysis finished2023-12-12 13:44:41.050651
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct175
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88
Minimum1
Maximum175
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T22:44:41.267258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.7
Q144.5
median88
Q3131.5
95-th percentile166.3
Maximum175
Range174
Interquartile range (IQR)87

Descriptive statistics

Standard deviation50.662281
Coefficient of variation (CV)0.57570773
Kurtosis-1.2
Mean88
Median Absolute Deviation (MAD)44
Skewness0
Sum15400
Variance2566.6667
MonotonicityStrictly increasing
2023-12-12T22:44:41.680410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
2 1
 
0.6%
113 1
 
0.6%
114 1
 
0.6%
115 1
 
0.6%
116 1
 
0.6%
117 1
 
0.6%
118 1
 
0.6%
119 1
 
0.6%
120 1
 
0.6%
Other values (165) 165
94.3%
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 (%)
175 1
0.6%
174 1
0.6%
173 1
0.6%
172 1
0.6%
171 1
0.6%
170 1
0.6%
169 1
0.6%
168 1
0.6%
167 1
0.6%
166 1
0.6%

업소명
Text

Distinct167
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T22:44:42.263672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length13
Mean length5.9485714
Min length1

Characters and Unicode

Total characters1041
Distinct characters244
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)90.9%

Sample

1st row개구리
2nd row챠밍노래클럽
3rd row꼭지노래클럽
4th row문라이트사이공(MoonLight sai gon)노래클럽
5th row삼정노래짱
ValueCountFrequency (%)
노래클럽 4
 
2.1%
갤러리 2
 
1.1%
발리노래클럽 2
 
1.1%
백악관 2
 
1.1%
빙고 2
 
1.1%
필노래클럽 2
 
1.1%
대박노래클럽 2
 
1.1%
수노래클럽 2
 
1.1%
쎄븐노래클럽 2
 
1.1%
노래타운 2
 
1.1%
Other values (166) 167
88.4%
2023-12-12T22:44:42.843742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
노 116
 
11.1%
래 115
 
11.0%
클 76
 
7.3%
럽 76
 
7.3%
이 17
 
1.6%
스 17
 
1.6%
( 16
 
1.5%
) 16
 
1.5%
14
 
1.3%
주 12
 
1.2%
Other values (234) 566
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 925
88.9%
Uppercase Letter 34
 
3.3%
Lowercase Letter 19
 
1.8%
Open Punctuation 16
 
1.5%
Close Punctuation 16
 
1.5%
Decimal Number 15
 
1.4%
Space Separator 14
 
1.3%
Other Punctuation 1
 
0.1%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
노 116
 
12.5%
래 115
 
12.4%
클 76
 
8.2%
럽 76
 
8.2%
이 17
 
1.8%
스 17
 
1.8%
주 12
 
1.3%
점 12
 
1.3%
운 11
 
1.2%
타 10
 
1.1%
Other values (200) 463
50.1%
Uppercase Letter
ValueCountFrequency (%)
M 5
14.7%
S 4
11.8%
K 3
8.8%
B 3
8.8%
E 3
8.8%
N 3
8.8%
G 2
 
5.9%
L 2
 
5.9%
I 2
 
5.9%
O 2
 
5.9%
Other values (5) 5
14.7%
Lowercase Letter
ValueCountFrequency (%)
o 4
21.1%
s 3
15.8%
t 2
10.5%
h 2
10.5%
g 2
10.5%
n 2
10.5%
i 2
10.5%
e 1
 
5.3%
a 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 7
46.7%
0 3
20.0%
3 2
 
13.3%
5 2
 
13.3%
2 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
# 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 922
88.6%
Common 62
 
6.0%
Latin 54
 
5.2%
Han 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
노 116
 
12.6%
래 115
 
12.5%
클 76
 
8.2%
럽 76
 
8.2%
이 17
 
1.8%
스 17
 
1.8%
주 12
 
1.3%
점 12
 
1.3%
운 11
 
1.2%
타 10
 
1.1%
Other values (197) 460
49.9%
Latin
ValueCountFrequency (%)
M 5
 
9.3%
S 4
 
7.4%
o 4
 
7.4%
K 3
 
5.6%
B 3
 
5.6%
s 3
 
5.6%
E 3
 
5.6%
N 3
 
5.6%
G 2
 
3.7%
t 2
 
3.7%
Other values (15) 22
40.7%
Common
ValueCountFrequency (%)
( 16
25.8%
) 16
25.8%
14
22.6%
1 7
11.3%
0 3
 
4.8%
3 2
 
3.2%
5 2
 
3.2%
# 1
 
1.6%
2 1
 
1.6%
Han
ValueCountFrequency (%)
名 1
33.3%
品 1
33.3%
車 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 922
88.6%
ASCII 115
 
11.0%
CJK 3
 
0.3%
Number Forms 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
노 116
 
12.6%
래 115
 
12.5%
클 76
 
8.2%
럽 76
 
8.2%
이 17
 
1.8%
스 17
 
1.8%
주 12
 
1.3%
점 12
 
1.3%
운 11
 
1.2%
타 10
 
1.1%
Other values (197) 460
49.9%
ASCII
ValueCountFrequency (%)
( 16
 
13.9%
) 16
 
13.9%
14
 
12.2%
1 7
 
6.1%
M 5
 
4.3%
S 4
 
3.5%
o 4
 
3.5%
K 3
 
2.6%
B 3
 
2.6%
s 3
 
2.6%
Other values (23) 40
34.8%
CJK
ValueCountFrequency (%)
名 1
33.3%
品 1
33.3%
車 1
33.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지(도로명)
Text

Distinct172
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T22:44:43.097961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length42
Mean length29.851429
Min length20

Characters and Unicode

Total characters5224
Distinct characters100
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

Unique169 ?
Unique (%)96.6%

Sample

1st row인천광역시 부평구 부평대로 44 (부평동)
2nd row인천광역시 부평구 부평문화로 54 (부평동)
3rd row인천광역시 부평구 시장로 38 (부평동)
4th row인천광역시 부평구 부평대로32번길 7 (부평동)
5th row인천광역시 부평구 열우물로 45 (십정동, 지하1층 일부)
ValueCountFrequency (%)
인천광역시 175
17.6%
부평구 175
17.6%
부평동 115
 
11.6%
지하1층 30
 
3.0%
시장로 23
 
2.3%
십정동 20
 
2.0%
2층 17
 
1.7%
경원대로1403번길 16
 
1.6%
열우물로 14
 
1.4%
부평대로 12
 
1.2%
Other values (201) 396
39.9%
2023-12-12T22:44:43.539990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
825
 
15.8%
부 387
 
7.4%
평 352
 
6.7%
1 218
 
4.2%
시 217
 
4.2%
( 189
 
3.6%
) 189
 
3.6%
광 183
 
3.5%
동 183
 
3.5%
인 175
 
3.3%
Other values (90) 2306
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3125
59.8%
Space Separator 825
 
15.8%
Decimal Number 750
 
14.4%
Open Punctuation 189
 
3.6%
Close Punctuation 189
 
3.6%
Other Punctuation 115
 
2.2%
Dash Punctuation 22
 
0.4%
Uppercase Letter 9
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 387
12.4%
평 352
 
11.3%
시 217
 
6.9%
광 183
 
5.9%
동 183
 
5.9%
인 175
 
5.6%
역 175
 
5.6%
구 175
 
5.6%
천 175
 
5.6%
로 171
 
5.5%
Other values (69) 932
29.8%
Decimal Number
ValueCountFrequency (%)
1 218
29.1%
3 114
15.2%
4 94
12.5%
2 90
12.0%
0 65
 
8.7%
7 42
 
5.6%
6 42
 
5.6%
5 35
 
4.7%
8 31
 
4.1%
9 19
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
E 3
33.3%
B 2
22.2%
A 1
 
11.1%
N 1
 
11.1%
V 1
 
11.1%
L 1
 
11.1%
Space Separator
ValueCountFrequency (%)
825
100.0%
Open Punctuation
ValueCountFrequency (%)
( 189
100.0%
Close Punctuation
ValueCountFrequency (%)
) 189
100.0%
Other Punctuation
ValueCountFrequency (%)
, 115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3125
59.8%
Common 2090
40.0%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 387
12.4%
평 352
 
11.3%
시 217
 
6.9%
광 183
 
5.9%
동 183
 
5.9%
인 175
 
5.6%
역 175
 
5.6%
구 175
 
5.6%
천 175
 
5.6%
로 171
 
5.5%
Other values (69) 932
29.8%
Common
ValueCountFrequency (%)
825
39.5%
1 218
 
10.4%
( 189
 
9.0%
) 189
 
9.0%
, 115
 
5.5%
3 114
 
5.5%
4 94
 
4.5%
2 90
 
4.3%
0 65
 
3.1%
7 42
 
2.0%
Other values (5) 149
 
7.1%
Latin
ValueCountFrequency (%)
E 3
33.3%
B 2
22.2%
A 1
 
11.1%
N 1
 
11.1%
V 1
 
11.1%
L 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3125
59.8%
ASCII 2099
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
825
39.3%
1 218
 
10.4%
( 189
 
9.0%
) 189
 
9.0%
, 115
 
5.5%
3 114
 
5.4%
4 94
 
4.5%
2 90
 
4.3%
0 65
 
3.1%
7 42
 
2.0%
Other values (11) 158
 
7.5%
Hangul
ValueCountFrequency (%)
부 387
12.4%
평 352
 
11.3%
시 217
 
6.9%
광 183
 
5.9%
동 183
 
5.9%
인 175
 
5.6%
역 175
 
5.6%
구 175
 
5.6%
천 175
 
5.6%
로 171
 
5.5%
Other values (69) 932
29.8%

소재지전화
Text

MISSING 

Distinct105
Distinct (%)99.1%
Missing69
Missing (%)39.4%
Memory size1.5 KiB
2023-12-12T22:44:43.813528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1272
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

Unique104 ?
Unique (%)98.1%

Sample

1st row032-507-3895
2nd row032-528-1870
3rd row032-523-9777
4th row032-528-4523
5th row032-437-3449
ValueCountFrequency (%)
032-506-4888 2
 
1.9%
032-423-6886 1
 
0.9%
032-507-3895 1
 
0.9%
032-506-6070 1
 
0.9%
032-527-9516 1
 
0.9%
032-504-9755 1
 
0.9%
032-330-8827 1
 
0.9%
032-330-0510 1
 
0.9%
032-514-0777 1
 
0.9%
032-506-0989 1
 
0.9%
Other values (95) 95
89.6%
2023-12-12T22:44:44.231922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 212
16.7%
2 205
16.1%
0 193
15.2%
3 176
13.8%
5 129
10.1%
1 86
6.8%
8 66
 
5.2%
7 61
 
4.8%
6 56
 
4.4%
4 54
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1060
83.3%
Dash Punctuation 212
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 205
19.3%
0 193
18.2%
3 176
16.6%
5 129
12.2%
1 86
8.1%
8 66
 
6.2%
7 61
 
5.8%
6 56
 
5.3%
4 54
 
5.1%
9 34
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 212
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1272
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 212
16.7%
2 205
16.1%
0 193
15.2%
3 176
13.8%
5 129
10.1%
1 86
6.8%
8 66
 
5.2%
7 61
 
4.8%
6 56
 
4.4%
4 54
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1272
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 212
16.7%
2 205
16.1%
0 193
15.2%
3 176
13.8%
5 129
10.1%
1 86
6.8%
8 66
 
5.2%
7 61
 
4.8%
6 56
 
4.4%
4 54
 
4.2%

Interactions

2023-12-12T22:44:40.739987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T22:44:40.860431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:44:40.959537image/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

연번업소명소재지(도로명)소재지전화
01개구리인천광역시 부평구 부평대로 44 (부평동)032-507-3895
12챠밍노래클럽인천광역시 부평구 부평문화로 54 (부평동)032-528-1870
23꼭지노래클럽인천광역시 부평구 시장로 38 (부평동)032-523-9777
34문라이트사이공(MoonLight sai gon)노래클럽인천광역시 부평구 부평대로32번길 7 (부평동)032-528-4523
45삼정노래짱인천광역시 부평구 열우물로 45 (십정동, 지하1층 일부)032-437-3449
56올인노래클럽인천광역시 부평구 경원대로1377번길 47 (부평동)032-522-0740
67와인천광역시 부평구 부평대로 40 (부평동)032-516-1163
78대박노래인천광역시 부평구 부평대로32번길 2 (부평동)032-512-6128
89뉴머슴인천광역시 부평구 경원대로1354번길 11 (부평동)032-517-0261
910나인노래클럽인천광역시 부평구 부평동 182-8032-521-1726
연번업소명소재지(도로명)소재지전화
165166지어이다국적노래클럽인천광역시 부평구 경원대로 1412, 타이콘스빌딩 지하1층 일부호 (부평동)<NA>
166167썬노래광장인천광역시 부평구 대정로 30, 지하1층 일부호 (부평동)<NA>
167168준투노래타운인천광역시 부평구 경원대로1403번길 21, 동강 2빌딩 3층 일부호 (부평동)<NA>
168169킹마이웨이인천광역시 부평구 부평대로 24, 가나베스트빌 14층 1403호 (부평동)<NA>
169170퀸노래타운인천광역시 부평구 부평대로 24, 가나베스트빌 14층 1404호 (부평동)<NA>
170171부평붐붐인천광역시 부평구 시장로 47, 3층 (부평동)<NA>
171172바운스 뮤직뱅크인천광역시 부평구 시장로12번길 6, 2층 (부평동)<NA>
172173아지트노래클럽인천광역시 부평구 시장로 76, 지하1층 (부평동)<NA>
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