Overview

Dataset statistics

Number of variables6
Number of observations121
Missing cells35
Missing cells (%)4.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory50.1 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description인천광역시 서구관내에 위치한 유흥주점 및 단란주점 현황(업종명, 업소명, 소재지, 전화번호)에 관하여 입력된 데이터파일입니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15039954&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 연번High correlation
전화번호 has 35 (28.9%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 11:00:46.625217
Analysis finished2024-01-28 11:00:47.095741
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61
Minimum1
Maximum121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-28T20:00:47.153145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q131
median61
Q391
95-th percentile115
Maximum121
Range120
Interquartile range (IQR)60

Descriptive statistics

Standard deviation35.073732
Coefficient of variation (CV)0.57497921
Kurtosis-1.2
Mean61
Median Absolute Deviation (MAD)30
Skewness0
Sum7381
Variance1230.1667
MonotonicityStrictly increasing
2024-01-28T20:00:47.263316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
92 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
Other values (111) 111
91.7%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%
112 1
0.8%

업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
단란주점
72 
유흥주점영업
49 

Length

Max length6
Median length4
Mean length4.8099174
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단란주점 72
59.5%
유흥주점영업 49
40.5%

Length

2024-01-28T20:00:47.381236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:00:47.460994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단란주점 72
59.5%
유흥주점영업 49
40.5%

업소명
Text

Distinct119
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-28T20:00:47.634385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length6.3636364
Min length1

Characters and Unicode

Total characters770
Distinct characters223
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

Unique117 ?
Unique (%)96.7%

Sample

1st row왕코노래클럽
2nd row놀러와
3rd row레이디
4th row러블리짱
5th row북항프라자2 203호
ValueCountFrequency (%)
라이브 8
 
5.6%
세시봉7080라이브 2
 
1.4%
팡팡단란주점 2
 
1.4%
7080 2
 
1.4%
티파니 2
 
1.4%
단란주점 2
 
1.4%
핑크단란주점 1
 
0.7%
맘모스 1
 
0.7%
째즈 1
 
0.7%
써니 1
 
0.7%
Other values (121) 121
84.6%
2024-01-28T20:00:47.940830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
래 39
 
5.1%
0 35
 
4.5%
주 34
 
4.4%
노 33
 
4.3%
이 32
 
4.2%
점 31
 
4.0%
라 28
 
3.6%
브 25
 
3.2%
22
 
2.9%
단 18
 
2.3%
Other values (213) 473
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 636
82.6%
Decimal Number 76
 
9.9%
Space Separator 22
 
2.9%
Uppercase Letter 14
 
1.8%
Lowercase Letter 11
 
1.4%
Close Punctuation 5
 
0.6%
Open Punctuation 5
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
래 39
 
6.1%
주 34
 
5.3%
노 33
 
5.2%
이 32
 
5.0%
점 31
 
4.9%
라 28
 
4.4%
브 25
 
3.9%
단 18
 
2.8%
란 18
 
2.8%
럽 15
 
2.4%
Other values (181) 363
57.1%
Uppercase Letter
ValueCountFrequency (%)
E 2
14.3%
L 2
14.3%
S 2
14.3%
G 2
14.3%
N 1
7.1%
I 1
7.1%
A 1
7.1%
H 1
7.1%
M 1
7.1%
K 1
7.1%
Lowercase Letter
ValueCountFrequency (%)
s 2
18.2%
i 1
9.1%
e 1
9.1%
p 1
9.1%
r 1
9.1%
u 1
9.1%
n 1
9.1%
g 1
9.1%
t 1
9.1%
h 1
9.1%
Decimal Number
ValueCountFrequency (%)
0 35
46.1%
8 16
21.1%
7 15
19.7%
9 3
 
3.9%
2 3
 
3.9%
1 2
 
2.6%
3 1
 
1.3%
6 1
 
1.3%
Space Separator
ValueCountFrequency (%)
22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 636
82.6%
Common 109
 
14.2%
Latin 25
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
래 39
 
6.1%
주 34
 
5.3%
노 33
 
5.2%
이 32
 
5.0%
점 31
 
4.9%
라 28
 
4.4%
브 25
 
3.9%
단 18
 
2.8%
란 18
 
2.8%
럽 15
 
2.4%
Other values (181) 363
57.1%
Latin
ValueCountFrequency (%)
E 2
 
8.0%
s 2
 
8.0%
L 2
 
8.0%
S 2
 
8.0%
G 2
 
8.0%
N 1
 
4.0%
I 1
 
4.0%
A 1
 
4.0%
H 1
 
4.0%
i 1
 
4.0%
Other values (10) 10
40.0%
Common
ValueCountFrequency (%)
0 35
32.1%
22
20.2%
8 16
14.7%
7 15
13.8%
) 5
 
4.6%
( 5
 
4.6%
9 3
 
2.8%
2 3
 
2.8%
1 2
 
1.8%
3 1
 
0.9%
Other values (2) 2
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 636
82.6%
ASCII 134
 
17.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
래 39
 
6.1%
주 34
 
5.3%
노 33
 
5.2%
이 32
 
5.0%
점 31
 
4.9%
라 28
 
4.4%
브 25
 
3.9%
단 18
 
2.8%
란 18
 
2.8%
럽 15
 
2.4%
Other values (181) 363
57.1%
ASCII
ValueCountFrequency (%)
0 35
26.1%
22
16.4%
8 16
11.9%
7 15
11.2%
) 5
 
3.7%
( 5
 
3.7%
9 3
 
2.2%
2 3
 
2.2%
E 2
 
1.5%
1 2
 
1.5%
Other values (22) 26
19.4%

소재지(도로명)
Text

Distinct120
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-28T20:00:48.210745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length43
Mean length31.669421
Min length21

Characters and Unicode

Total characters3832
Distinct characters133
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

Unique119 ?
Unique (%)98.3%

Sample

1st row인천광역시 서구 서곶로315번길 17 (심곡동)
2nd row인천광역시 서구 탁옥로51번길 11 (심곡동, 심곡네오프라자 403호,404호)
3rd row인천광역시 서구 완정로 160 (마전동, 802호)
4th row인천광역시 서구 길주로 101, 4층 일부호 (석남동)
5th row인천광역시 서구 북항로32번안길 9-20, 북항프라자2 203호 (원창동)
ValueCountFrequency (%)
인천광역시 121
 
16.0%
서구 121
 
16.0%
석남동 38
 
5.0%
심곡동 34
 
4.5%
가정로 25
 
3.3%
지하1층 22
 
2.9%
길주로 18
 
2.4%
탁옥로51번길 15
 
2.0%
2층 11
 
1.5%
가좌동 10
 
1.3%
Other values (222) 340
45.0%
2024-01-28T20:00:48.577437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
634
 
16.5%
1 178
 
4.6%
서 131
 
3.4%
( 129
 
3.4%
) 129
 
3.4%
동 124
 
3.2%
천 122
 
3.2%
로 122
 
3.2%
인 121
 
3.2%
광 121
 
3.2%
Other values (123) 2021
52.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2083
54.4%
Decimal Number 697
 
18.2%
Space Separator 634
 
16.5%
Open Punctuation 129
 
3.4%
Close Punctuation 129
 
3.4%
Other Punctuation 109
 
2.8%
Dash Punctuation 46
 
1.2%
Uppercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 131
 
6.3%
동 124
 
6.0%
천 122
 
5.9%
로 122
 
5.9%
인 121
 
5.8%
광 121
 
5.8%
역 121
 
5.8%
시 121
 
5.8%
구 121
 
5.8%
길 77
 
3.7%
Other values (105) 902
43.3%
Decimal Number
ValueCountFrequency (%)
1 178
25.5%
2 95
13.6%
3 85
12.2%
5 81
11.6%
0 72
10.3%
4 59
 
8.5%
6 43
 
6.2%
8 30
 
4.3%
7 29
 
4.2%
9 25
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
B 3
60.0%
G 1
 
20.0%
S 1
 
20.0%
Space Separator
ValueCountFrequency (%)
634
100.0%
Open Punctuation
ValueCountFrequency (%)
( 129
100.0%
Close Punctuation
ValueCountFrequency (%)
) 129
100.0%
Other Punctuation
ValueCountFrequency (%)
, 109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2083
54.4%
Common 1744
45.5%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 131
 
6.3%
동 124
 
6.0%
천 122
 
5.9%
로 122
 
5.9%
인 121
 
5.8%
광 121
 
5.8%
역 121
 
5.8%
시 121
 
5.8%
구 121
 
5.8%
길 77
 
3.7%
Other values (105) 902
43.3%
Common
ValueCountFrequency (%)
634
36.4%
1 178
 
10.2%
( 129
 
7.4%
) 129
 
7.4%
, 109
 
6.2%
2 95
 
5.4%
3 85
 
4.9%
5 81
 
4.6%
0 72
 
4.1%
4 59
 
3.4%
Other values (5) 173
 
9.9%
Latin
ValueCountFrequency (%)
B 3
60.0%
G 1
 
20.0%
S 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2083
54.4%
ASCII 1749
45.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
634
36.2%
1 178
 
10.2%
( 129
 
7.4%
) 129
 
7.4%
, 109
 
6.2%
2 95
 
5.4%
3 85
 
4.9%
5 81
 
4.6%
0 72
 
4.1%
4 59
 
3.4%
Other values (8) 178
 
10.2%
Hangul
ValueCountFrequency (%)
서 131
 
6.3%
동 124
 
6.0%
천 122
 
5.9%
로 122
 
5.9%
인 121
 
5.8%
광 121
 
5.8%
역 121
 
5.8%
시 121
 
5.8%
구 121
 
5.8%
길 77
 
3.7%
Other values (105) 902
43.3%

전화번호
Text

MISSING 

Distinct84
Distinct (%)97.7%
Missing35
Missing (%)28.9%
Memory size1.1 KiB
2024-01-28T20:00:48.779578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.011628
Min length12

Characters and Unicode

Total characters1033
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

Unique82 ?
Unique (%)95.3%

Sample

1st row032-561-1331
2nd row032-562-2236
3rd row032-562-5823
4th row032-562-8753
5th row032-564-8604
ValueCountFrequency (%)
032-582-4041 2
 
2.3%
032-582-0042 2
 
2.3%
032-579-0116 1
 
1.2%
032-583-3213 1
 
1.2%
032-583-0780 1
 
1.2%
032-582-7604 1
 
1.2%
032-582-3949 1
 
1.2%
032-582-3536 1
 
1.2%
032-581-6724 1
 
1.2%
032-581-3150 1
 
1.2%
Other values (74) 74
86.0%
2024-01-28T20:00:49.073386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 172
16.7%
3 142
13.7%
0 139
13.5%
2 135
13.1%
5 113
10.9%
7 76
7.4%
6 72
7.0%
8 60
 
5.8%
1 45
 
4.4%
4 44
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 861
83.3%
Dash Punctuation 172
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 142
16.5%
0 139
16.1%
2 135
15.7%
5 113
13.1%
7 76
8.8%
6 72
8.4%
8 60
7.0%
1 45
 
5.2%
4 44
 
5.1%
9 35
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1033
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 172
16.7%
3 142
13.7%
0 139
13.5%
2 135
13.1%
5 113
10.9%
7 76
7.4%
6 72
7.0%
8 60
 
5.8%
1 45
 
4.4%
4 44
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1033
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 172
16.7%
3 142
13.7%
0 139
13.5%
2 135
13.1%
5 113
10.9%
7 76
7.4%
6 72
7.0%
8 60
 
5.8%
1 45
 
4.4%
4 44
 
4.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2022-09-06
121 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-06
2nd row2022-09-06
3rd row2022-09-06
4th row2022-09-06
5th row2022-09-06

Common Values

ValueCountFrequency (%)
2022-09-06 121
100.0%

Length

2024-01-28T20:00:49.179441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:00:49.254189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-06 121
100.0%

Interactions

2024-01-28T20:00:46.894758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T20:00:49.298616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명전화번호
연번1.0001.0000.948
업종명1.0001.0001.000
전화번호0.9481.0001.000
2024-01-28T20:00:49.580624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.966
업종명0.9661.000

Missing values

2024-01-28T20:00:46.986622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T20:00:47.063951image/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

연번업종명업소명소재지(도로명)전화번호데이터기준일자
01유흥주점영업왕코노래클럽인천광역시 서구 서곶로315번길 17 (심곡동)<NA>2022-09-06
12유흥주점영업놀러와인천광역시 서구 탁옥로51번길 11 (심곡동, 심곡네오프라자 403호,404호)<NA>2022-09-06
23유흥주점영업레이디인천광역시 서구 완정로 160 (마전동, 802호)<NA>2022-09-06
34유흥주점영업러블리짱인천광역시 서구 길주로 101, 4층 일부호 (석남동)<NA>2022-09-06
45유흥주점영업북항프라자2 203호인천광역시 서구 북항로32번안길 9-20, 북항프라자2 203호 (원창동)<NA>2022-09-06
56유흥주점영업SINGHA(싱하)인천광역시 서구 완정로 160, 검단프라자 701호 (마전동)<NA>2022-09-06
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