Overview

Dataset statistics

Number of variables8
Number of observations63
Missing cells3
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory67.0 B

Variable types

Categorical2
Text3
DateTime2
Numeric1

Dataset

Description인천광역시 계양구 관내 숙박업소 현황에 대한 데이터로, 업종명, 업태명, 업소명, 영업소 주소, 전화번호, 영업시작일자 등을 제공합니다.
Author인천광역시 계양구
URLhttps://www.data.go.kr/data/3078057/fileData.do

Alerts

업종명 is highly overall correlated with 업태명High correlation
업태명 is highly overall correlated with 객실수 and 1 other fieldsHigh correlation
객실수 is highly overall correlated with 업태명High correlation
업종명 is highly imbalanced (72.4%)Imbalance
소재지전화 has 3 (4.8%) missing valuesMissing
업소명 has unique valuesUnique
영업소 주소(도로명) has unique valuesUnique
신고일자 has unique valuesUnique
영업자시작일 has unique valuesUnique

Reproduction

Analysis started2024-03-14 09:16:37.860302
Analysis finished2024-03-14 09:16:39.364869
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
숙박업(일반)
60 
숙박업(생활)
 
3

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(일반)

Common Values

ValueCountFrequency (%)
숙박업(일반) 60
95.2%
숙박업(생활) 3
 
4.8%

Length

2024-03-14T18:16:39.572551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:16:39.884453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업(일반 60
95.2%
숙박업(생활 3
 
4.8%

업태명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size632.0 B
여관업
42 
여인숙업
8 
관광호텔
7 
일반호텔
 
3
숙박업(생활)
 
3

Length

Max length7
Median length3
Mean length3.4761905
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여인숙업
2nd row여인숙업
3rd row여관업
4th row여인숙업
5th row여관업

Common Values

ValueCountFrequency (%)
여관업 42
66.7%
여인숙업 8
 
12.7%
관광호텔 7
 
11.1%
일반호텔 3
 
4.8%
숙박업(생활) 3
 
4.8%

Length

2024-03-14T18:16:40.259739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:16:40.622347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 42
66.7%
여인숙업 8
 
12.7%
관광호텔 7
 
11.1%
일반호텔 3
 
4.8%
숙박업(생활 3
 
4.8%

업소명
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size632.0 B
2024-03-14T18:16:41.662335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length5.6666667
Min length2

Characters and Unicode

Total characters357
Distinct characters129
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

Unique63 ?
Unique (%)100.0%

Sample

1st row큐여관
2nd row윈스톤
3rd row현대모텔
4th row동일여인숙
5th row모텔 드라마투(Ⅱ)
ValueCountFrequency (%)
큐여관 1
 
1.4%
buti 1
 
1.4%
써클호텔 1
 
1.4%
토마토모텔 1
 
1.4%
짝호텔 1
 
1.4%
알지호텔 1
 
1.4%
계양구청점 1
 
1.4%
명작 1
 
1.4%
비지니스호텔 1
 
1.4%
인천 1
 
1.4%
Other values (64) 64
86.5%
2024-03-14T18:16:43.194160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 39
 
10.9%
호 20
 
5.6%
모 17
 
4.8%
관 13
 
3.6%
11
 
3.1%
여 10
 
2.8%
스 9
 
2.5%
마 8
 
2.2%
인 7
 
2.0%
) 6
 
1.7%
Other values (119) 217
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 297
83.2%
Uppercase Letter 22
 
6.2%
Space Separator 11
 
3.1%
Decimal Number 9
 
2.5%
Close Punctuation 7
 
2.0%
Open Punctuation 7
 
2.0%
Other Punctuation 3
 
0.8%
Letter Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 39
 
13.1%
호 20
 
6.7%
모 17
 
5.7%
관 13
 
4.4%
여 10
 
3.4%
스 9
 
3.0%
마 8
 
2.7%
인 7
 
2.4%
이 6
 
2.0%
장 5
 
1.7%
Other values (96) 163
54.9%
Uppercase Letter
ValueCountFrequency (%)
O 4
18.2%
H 3
13.6%
T 3
13.6%
E 2
9.1%
L 2
9.1%
I 2
9.1%
U 2
9.1%
W 1
 
4.5%
V 1
 
4.5%
B 1
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 3
33.3%
5 3
33.3%
2 2
22.2%
0 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 6
85.7%
] 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 6
85.7%
[ 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
# 1
33.3%
Space Separator
ValueCountFrequency (%)
11
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 297
83.2%
Common 37
 
10.4%
Latin 23
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 39
 
13.1%
호 20
 
6.7%
모 17
 
5.7%
관 13
 
4.4%
여 10
 
3.4%
스 9
 
3.0%
마 8
 
2.7%
인 7
 
2.4%
이 6
 
2.0%
장 5
 
1.7%
Other values (96) 163
54.9%
Latin
ValueCountFrequency (%)
O 4
17.4%
H 3
13.0%
T 3
13.0%
E 2
8.7%
L 2
8.7%
I 2
8.7%
U 2
8.7%
W 1
 
4.3%
V 1
 
4.3%
B 1
 
4.3%
Other values (2) 2
8.7%
Common
ValueCountFrequency (%)
11
29.7%
) 6
16.2%
( 6
16.2%
1 3
 
8.1%
5 3
 
8.1%
& 2
 
5.4%
2 2
 
5.4%
] 1
 
2.7%
[ 1
 
2.7%
0 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 297
83.2%
ASCII 59
 
16.5%
Number Forms 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 39
 
13.1%
호 20
 
6.7%
모 17
 
5.7%
관 13
 
4.4%
여 10
 
3.4%
스 9
 
3.0%
마 8
 
2.7%
인 7
 
2.4%
이 6
 
2.0%
장 5
 
1.7%
Other values (96) 163
54.9%
ASCII
ValueCountFrequency (%)
11
18.6%
) 6
 
10.2%
( 6
 
10.2%
O 4
 
6.8%
H 3
 
5.1%
1 3
 
5.1%
T 3
 
5.1%
5 3
 
5.1%
E 2
 
3.4%
L 2
 
3.4%
Other values (12) 16
27.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

영업소 주소(도로명)
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size632.0 B
2024-03-14T18:16:44.208389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length32
Mean length26.809524
Min length23

Characters and Unicode

Total characters1689
Distinct characters64
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)100.0%

Sample

1st row인천광역시 계양구 안남로465번길 3-1 (효성동)
2nd row인천광역시 계양구 안남로 462 (효성동)
3rd row인천광역시 계양구 안남로490번길 9-7 (효성동)
4th row인천광역시 계양구 안남로 478-1 (효성동)
5th row인천광역시 계양구 아나지로177번길 7 (효성동)
ValueCountFrequency (%)
인천광역시 63
19.6%
계양구 63
19.6%
계산동 28
 
8.7%
작전동 19
 
5.9%
효성동 14
 
4.3%
계산천동로 6
 
1.9%
안남로 5
 
1.6%
계산로103번길 5
 
1.6%
계양문화로17번길 4
 
1.2%
8 4
 
1.2%
Other values (75) 111
34.5%
2024-03-14T18:16:45.649590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
259
 
15.3%
계 132
 
7.8%
양 82
 
4.9%
천 74
 
4.4%
동 72
 
4.3%
시 67
 
4.0%
광 64
 
3.8%
인 63
 
3.7%
역 63
 
3.7%
구 63
 
3.7%
Other values (54) 750
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1040
61.6%
Space Separator 259
 
15.3%
Decimal Number 226
 
13.4%
Close Punctuation 63
 
3.7%
Open Punctuation 63
 
3.7%
Dash Punctuation 25
 
1.5%
Other Punctuation 9
 
0.5%
Uppercase Letter 3
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 132
12.7%
양 82
 
7.9%
천 74
 
7.1%
동 72
 
6.9%
시 67
 
6.4%
광 64
 
6.2%
인 63
 
6.1%
역 63
 
6.1%
구 63
 
6.1%
로 59
 
5.7%
Other values (35) 301
28.9%
Decimal Number
ValueCountFrequency (%)
1 56
24.8%
3 27
11.9%
2 26
11.5%
7 23
10.2%
4 19
 
8.4%
9 19
 
8.4%
5 16
 
7.1%
8 16
 
7.1%
6 12
 
5.3%
0 12
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
O 1
33.3%
W 1
33.3%
V 1
33.3%
Space Separator
ValueCountFrequency (%)
259
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1040
61.6%
Common 646
38.2%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 132
12.7%
양 82
 
7.9%
천 74
 
7.1%
동 72
 
6.9%
시 67
 
6.4%
광 64
 
6.2%
인 63
 
6.1%
역 63
 
6.1%
구 63
 
6.1%
로 59
 
5.7%
Other values (35) 301
28.9%
Common
ValueCountFrequency (%)
259
40.1%
) 63
 
9.8%
( 63
 
9.8%
1 56
 
8.7%
3 27
 
4.2%
2 26
 
4.0%
- 25
 
3.9%
7 23
 
3.6%
4 19
 
2.9%
9 19
 
2.9%
Other values (6) 66
 
10.2%
Latin
ValueCountFrequency (%)
O 1
33.3%
W 1
33.3%
V 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1040
61.6%
ASCII 649
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
259
39.9%
) 63
 
9.7%
( 63
 
9.7%
1 56
 
8.6%
3 27
 
4.2%
2 26
 
4.0%
- 25
 
3.9%
7 23
 
3.5%
4 19
 
2.9%
9 19
 
2.9%
Other values (9) 69
 
10.6%
Hangul
ValueCountFrequency (%)
계 132
12.7%
양 82
 
7.9%
천 74
 
7.1%
동 72
 
6.9%
시 67
 
6.4%
광 64
 
6.2%
인 63
 
6.1%
역 63
 
6.1%
구 63
 
6.1%
로 59
 
5.7%
Other values (35) 301
28.9%

소재지전화
Text

MISSING 

Distinct60
Distinct (%)100.0%
Missing3
Missing (%)4.8%
Memory size632.0 B
2024-03-14T18:16:46.618035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters720
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

Unique60 ?
Unique (%)100.0%

Sample

1st row032-547-3793
2nd row032-522-2410
3rd row032-551-2366
4th row032-548-2570
5th row032-548-9182
ValueCountFrequency (%)
032-552-6697 1
 
1.7%
032-551-2443 1
 
1.7%
032-541-5385 1
 
1.7%
032-553-7722 1
 
1.7%
032-554-5989 1
 
1.7%
032-554-5588 1
 
1.7%
032-544-4922 1
 
1.7%
032-544-5550 1
 
1.7%
032-545-5803 1
 
1.7%
032-554-1881 1
 
1.7%
Other values (50) 50
83.3%
2024-03-14T18:16:48.196950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 123
17.1%
- 120
16.7%
2 102
14.2%
3 93
12.9%
0 92
12.8%
4 55
7.6%
1 42
 
5.8%
8 28
 
3.9%
6 25
 
3.5%
7 21
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 600
83.3%
Dash Punctuation 120
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 123
20.5%
2 102
17.0%
3 93
15.5%
0 92
15.3%
4 55
9.2%
1 42
 
7.0%
8 28
 
4.7%
6 25
 
4.2%
7 21
 
3.5%
9 19
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 720
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 123
17.1%
- 120
16.7%
2 102
14.2%
3 93
12.9%
0 92
12.8%
4 55
7.6%
1 42
 
5.8%
8 28
 
3.9%
6 25
 
3.5%
7 21
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 123
17.1%
- 120
16.7%
2 102
14.2%
3 93
12.9%
0 92
12.8%
4 55
7.6%
1 42
 
5.8%
8 28
 
3.9%
6 25
 
3.5%
7 21
 
2.9%

신고일자
Date

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size632.0 B
Minimum1976-04-24 00:00:00
Maximum2021-04-15 00:00:00
2024-03-14T18:16:48.554233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:16:48.973113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업자시작일
Date

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size632.0 B
Minimum1984-12-20 00:00:00
Maximum2024-02-05 00:00:00
2024-03-14T18:16:49.292538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:16:49.621891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

객실수
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.507937
Minimum4
Maximum142
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size695.0 B
2024-03-14T18:16:49.844026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile9.1
Q114.5
median24
Q335
95-th percentile66.8
Maximum142
Range138
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation22.174435
Coefficient of variation (CV)0.7514736
Kurtosis10.089092
Mean29.507937
Median Absolute Deviation (MAD)10
Skewness2.5779259
Sum1859
Variance491.70558
MonotonicityNot monotonic
2024-03-14T18:16:50.068984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
24 5
 
7.9%
35 4
 
6.3%
14 4
 
6.3%
18 4
 
6.3%
10 3
 
4.8%
32 3
 
4.8%
12 3
 
4.8%
17 3
 
4.8%
20 2
 
3.2%
29 2
 
3.2%
Other values (27) 30
47.6%
ValueCountFrequency (%)
4 1
 
1.6%
6 1
 
1.6%
8 1
 
1.6%
9 1
 
1.6%
10 3
4.8%
11 1
 
1.6%
12 3
4.8%
13 1
 
1.6%
14 4
6.3%
15 1
 
1.6%
ValueCountFrequency (%)
142 1
1.6%
85 1
1.6%
73 1
1.6%
67 1
1.6%
65 1
1.6%
54 1
1.6%
50 1
1.6%
49 1
1.6%
45 2
3.2%
44 1
1.6%

Interactions

2024-03-14T18:16:38.421947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T18:16:50.235132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업태명업소명영업소 주소(도로명)소재지전화신고일자영업자시작일객실수
업종명1.0001.0001.0001.0001.0001.0001.0000.111
업태명1.0001.0001.0001.0001.0001.0001.0000.687
업소명1.0001.0001.0001.0001.0001.0001.0001.000
영업소 주소(도로명)1.0001.0001.0001.0001.0001.0001.0001.000
소재지전화1.0001.0001.0001.0001.0001.0001.0001.000
신고일자1.0001.0001.0001.0001.0001.0001.0001.000
영업자시작일1.0001.0001.0001.0001.0001.0001.0001.000
객실수0.1110.6871.0001.0001.0001.0001.0001.000
2024-03-14T18:16:50.426168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업태명
업종명1.0000.975
업태명0.9751.000
2024-03-14T18:16:50.650506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객실수업종명업태명
객실수1.0000.1070.523
업종명0.1071.0000.975
업태명0.5230.9751.000

Missing values

2024-03-14T18:16:38.781365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:16:39.199964image/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

업종명업태명업소명영업소 주소(도로명)소재지전화신고일자영업자시작일객실수
0숙박업(일반)여인숙업큐여관인천광역시 계양구 안남로465번길 3-1 (효성동)032-547-37931976-04-242020-12-2410
1숙박업(일반)여인숙업윈스톤인천광역시 계양구 안남로 462 (효성동)032-522-24101976-08-082011-06-2912
2숙박업(일반)여관업현대모텔인천광역시 계양구 안남로490번길 9-7 (효성동)<NA>1979-12-152020-12-2311
3숙박업(일반)여인숙업동일여인숙인천광역시 계양구 안남로 478-1 (효성동)032-551-23661980-07-012003-01-164
4숙박업(일반)여관업모텔 드라마투(Ⅱ)인천광역시 계양구 아나지로177번길 7 (효성동)032-548-25701981-09-112022-02-1716
5숙박업(일반)여인숙업대도여인숙인천광역시 계양구 아나지로 18 (효성동)032-548-91821981-03-302022-01-2510
6숙박업(일반)여관업궁전여관인천광역시 계양구 안남로490번길 14-1 (효성동)032-545-41521982-06-232018-09-206
7숙박업(일반)여관업성화장인천광역시 계양구 계산천서로 16 (계산동)032-541-29261984-06-272017-04-2714
8숙박업(일반)여관업멜로디모텔인천광역시 계양구 계산천서로 32 (계산동)032-541-18061984-10-042009-12-1113
9숙박업(일반)여관업현대여관인천광역시 계양구 효서로229번길 6 (작전동)032-543-81961984-12-201984-12-2015
업종명업태명업소명영업소 주소(도로명)소재지전화신고일자영업자시작일객실수
53숙박업(일반)여관업스카이모텔인천광역시 계양구 계산로103번길 3-1 (계산동)032-541-61722002-12-132021-08-1117
54숙박업(일반)여인숙업나우모텔인천광역시 계양구 아나지로183번길 12 (효성동)032-555-78212003-04-212016-04-1812
55숙박업(일반)관광호텔아마레관광호텔인천광역시 계양구 장제로730번길 14 (작전동)032-541-22222014-08-122014-08-1267
56숙박업(일반)여관업휴모텔인천광역시 계양구 어사대로 5 (계산동, 2,3,4층)032-541-30592015-02-232023-08-2220
57숙박업(일반)관광호텔리버관광호텔인천광역시 계양구 계양문화로53번길 6 (계산동)032-554-03102016-10-182016-10-1865
58숙박업(일반)관광호텔보우(VOW)관광호텔인천광역시 계양구 계양문화로59번길 9 (계산동, VOW관광호텔)032-545-11112017-06-302017-06-3073
59숙박업(일반)관광호텔소울하다 계양인천광역시 계양구 계양문화로 58, 호텔 소울하다 (계산동)032-272-17002021-04-152021-04-1585
60숙박업(생활)숙박업(생활)원 스테이인천광역시 계양구 계산천동로 21 (계산동)032-554-05871999-05-122023-11-2232
61숙박업(생활)숙박업(생활)해피하우스인천광역시 계양구 계양문화로 54 (계산동, 7층 )032-545-65012014-09-192015-01-0849
62숙박업(생활)숙박업(생활)마이빌인천광역시 계양구 계산로103번길 3 (계산동, 1~4층)032-553-26002015-07-082015-07-0824