Overview

Dataset statistics

Number of variables4
Number of observations61
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory35.2 B

Variable types

Numeric1
Text3

Dataset

Description인천광역시 부평구 우수 숙박 업소 현황 데이터는 우수숙박업소 명, 숙박업소 소재지, 전화번호에 대한 데이터를 제공합니다.
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15104146&srcSe=7661IVAWM27C61E190

Alerts

순번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 06:51:19.101401
Analysis finished2024-01-28 06:51:19.669160
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31
Minimum1
Maximum61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-01-28T15:51:19.740286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q116
median31
Q346
95-th percentile58
Maximum61
Range60
Interquartile range (IQR)30

Descriptive statistics

Standard deviation17.752934
Coefficient of variation (CV)0.57267529
Kurtosis-1.2
Mean31
Median Absolute Deviation (MAD)15
Skewness0
Sum1891
Variance315.16667
MonotonicityStrictly increasing
2024-01-28T15:51:19.858032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.6%
47 1
 
1.6%
34 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
61 1
1.6%
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%
54 1
1.6%
53 1
1.6%
52 1
1.6%

업소명
Text

Distinct46
Distinct (%)75.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-01-28T15:51:20.066802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length6.3442623
Min length2

Characters and Unicode

Total characters387
Distinct characters118
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

Unique32 ?
Unique (%)52.5%

Sample

1st row이코노미호텔인천부평점
2nd row갤러리아호텔
3rd row더블유(W)
4th rowRg호텔(알지)
5th row이코노미호텔인천부평점
ValueCountFrequency (%)
이코노미호텔인천부평점 3
 
4.5%
칼튼모텔 2
 
3.0%
라임호텔 2
 
3.0%
갤러리아호텔 2
 
3.0%
리치모텔 2
 
3.0%
보보스모텔 2
 
3.0%
뉴상상호텔 2
 
3.0%
필모텔여관 2
 
3.0%
이오스호텔 2
 
3.0%
토요코인인천부평 2
 
3.0%
Other values (42) 46
68.7%
2024-01-28T15:51:20.376660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 49
 
12.7%
호 35
 
9.0%
모 14
 
3.6%
이 12
 
3.1%
스 12
 
3.1%
) 11
 
2.8%
( 11
 
2.8%
인 8
 
2.1%
부 8
 
2.1%
평 8
 
2.1%
Other values (108) 219
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 316
81.7%
Uppercase Letter 35
 
9.0%
Close Punctuation 11
 
2.8%
Open Punctuation 11
 
2.8%
Space Separator 6
 
1.6%
Other Punctuation 3
 
0.8%
Decimal Number 2
 
0.5%
Lowercase Letter 2
 
0.5%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 49
 
15.5%
호 35
 
11.1%
모 14
 
4.4%
이 12
 
3.8%
스 12
 
3.8%
인 8
 
2.5%
부 8
 
2.5%
평 8
 
2.5%
천 6
 
1.9%
트 6
 
1.9%
Other values (81) 158
50.0%
Uppercase Letter
ValueCountFrequency (%)
O 5
14.3%
R 3
 
8.6%
T 3
 
8.6%
E 3
 
8.6%
L 2
 
5.7%
N 2
 
5.7%
I 2
 
5.7%
A 2
 
5.7%
F 2
 
5.7%
W 2
 
5.7%
Other values (9) 9
25.7%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
& 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 316
81.7%
Latin 37
 
9.6%
Common 34
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 49
 
15.5%
호 35
 
11.1%
모 14
 
4.4%
이 12
 
3.8%
스 12
 
3.8%
인 8
 
2.5%
부 8
 
2.5%
평 8
 
2.5%
천 6
 
1.9%
트 6
 
1.9%
Other values (81) 158
50.0%
Latin
ValueCountFrequency (%)
O 5
13.5%
R 3
 
8.1%
T 3
 
8.1%
E 3
 
8.1%
L 2
 
5.4%
N 2
 
5.4%
I 2
 
5.4%
A 2
 
5.4%
F 2
 
5.4%
g 2
 
5.4%
Other values (10) 11
29.7%
Common
ValueCountFrequency (%)
) 11
32.4%
( 11
32.4%
6
17.6%
. 2
 
5.9%
1 2
 
5.9%
& 1
 
2.9%
- 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 316
81.7%
ASCII 71
 
18.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 49
 
15.5%
호 35
 
11.1%
모 14
 
4.4%
이 12
 
3.8%
스 12
 
3.8%
인 8
 
2.5%
부 8
 
2.5%
평 8
 
2.5%
천 6
 
1.9%
트 6
 
1.9%
Other values (81) 158
50.0%
ASCII
ValueCountFrequency (%)
) 11
15.5%
( 11
15.5%
6
 
8.5%
O 5
 
7.0%
R 3
 
4.2%
T 3
 
4.2%
E 3
 
4.2%
L 2
 
2.8%
. 2
 
2.8%
N 2
 
2.8%
Other values (17) 23
32.4%

소재지(도로명)
Text

Distinct46
Distinct (%)75.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-01-28T15:51:20.588063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length30
Mean length27.163934
Min length22

Characters and Unicode

Total characters1657
Distinct characters47
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)52.5%

Sample

1st row인천광역시 부평구 부평대로296번길 88-6 (갈산동)
2nd row인천광역시 부평구 대정로90번길 24 (부평동)
3rd row인천광역시 부평구 경원대로1377번길 17-5 (부평동)
4th row인천광역시 부평구 원길로11번길 7 (산곡동)
5th row인천광역시 부평구 부평대로296번길 88-6 (갈산동)
ValueCountFrequency (%)
인천광역시 61
21.9%
부평구 61
21.9%
부평동 27
 
9.7%
십정동 7
 
2.5%
경원대로 5
 
1.8%
경원대로1377번길 4
 
1.4%
7 4
 
1.4%
부평대로296번길 3
 
1.1%
88-6 3
 
1.1%
갈산동 3
 
1.1%
Other values (65) 100
36.0%
2024-01-28T15:51:20.892392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
218
 
13.2%
평 116
 
7.0%
부 115
 
6.9%
1 72
 
4.3%
광 71
 
4.3%
동 67
 
4.0%
천 66
 
4.0%
시 63
 
3.8%
구 61
 
3.7%
) 61
 
3.7%
Other values (37) 747
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1009
60.9%
Decimal Number 284
 
17.1%
Space Separator 218
 
13.2%
Close Punctuation 61
 
3.7%
Open Punctuation 61
 
3.7%
Dash Punctuation 24
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
평 116
11.5%
부 115
11.4%
광 71
 
7.0%
동 67
 
6.6%
천 66
 
6.5%
시 63
 
6.2%
구 61
 
6.0%
역 61
 
6.0%
인 61
 
6.0%
로 61
 
6.0%
Other values (23) 267
26.5%
Decimal Number
ValueCountFrequency (%)
1 72
25.4%
2 42
14.8%
7 39
13.7%
3 30
10.6%
4 24
 
8.5%
6 22
 
7.7%
8 17
 
6.0%
9 17
 
6.0%
0 13
 
4.6%
5 8
 
2.8%
Space Separator
ValueCountFrequency (%)
218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1009
60.9%
Common 648
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
평 116
11.5%
부 115
11.4%
광 71
 
7.0%
동 67
 
6.6%
천 66
 
6.5%
시 63
 
6.2%
구 61
 
6.0%
역 61
 
6.0%
인 61
 
6.0%
로 61
 
6.0%
Other values (23) 267
26.5%
Common
ValueCountFrequency (%)
218
33.6%
1 72
 
11.1%
) 61
 
9.4%
( 61
 
9.4%
2 42
 
6.5%
7 39
 
6.0%
3 30
 
4.6%
- 24
 
3.7%
4 24
 
3.7%
6 22
 
3.4%
Other values (4) 55
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1009
60.9%
ASCII 648
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
218
33.6%
1 72
 
11.1%
) 61
 
9.4%
( 61
 
9.4%
2 42
 
6.5%
7 39
 
6.0%
3 30
 
4.6%
- 24
 
3.7%
4 24
 
3.7%
6 22
 
3.4%
Other values (4) 55
 
8.5%
Hangul
ValueCountFrequency (%)
평 116
11.5%
부 115
11.4%
광 71
 
7.0%
동 67
 
6.6%
천 66
 
6.5%
시 63
 
6.2%
구 61
 
6.0%
역 61
 
6.0%
인 61
 
6.0%
로 61
 
6.0%
Other values (23) 267
26.5%

전화번호
Text

Distinct46
Distinct (%)75.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-01-28T15:51:21.079049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters732
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

Unique32 ?
Unique (%)52.5%

Sample

1st row032-529-4941
2nd row032-503-4848
3rd row032-527-4564
4th row032-502-5553
5th row032-529-4941
ValueCountFrequency (%)
032-529-4941 3
 
4.9%
032-524-4430 2
 
3.3%
032-504-4300 2
 
3.3%
032-503-4848 2
 
3.3%
032-519-9610 2
 
3.3%
032-429-0191 2
 
3.3%
032-522-3500 2
 
3.3%
032-517-9690 2
 
3.3%
032-512-2253 2
 
3.3%
032-527-1045 2
 
3.3%
Other values (36) 40
65.6%
2024-01-28T15:51:21.364391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 122
16.7%
2 115
15.7%
3 109
14.9%
0 106
14.5%
5 86
11.7%
4 52
7.1%
1 50
6.8%
9 31
 
4.2%
6 26
 
3.6%
7 18
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 610
83.3%
Dash Punctuation 122
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 115
18.9%
3 109
17.9%
0 106
17.4%
5 86
14.1%
4 52
8.5%
1 50
8.2%
9 31
 
5.1%
6 26
 
4.3%
7 18
 
3.0%
8 17
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 732
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 122
16.7%
2 115
15.7%
3 109
14.9%
0 106
14.5%
5 86
11.7%
4 52
7.1%
1 50
6.8%
9 31
 
4.2%
6 26
 
3.6%
7 18
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 732
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 122
16.7%
2 115
15.7%
3 109
14.9%
0 106
14.5%
5 86
11.7%
4 52
7.1%
1 50
6.8%
9 31
 
4.2%
6 26
 
3.6%
7 18
 
2.5%

Interactions

2024-01-28T15:51:19.486000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T15:51:21.441814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번업소명소재지(도로명)전화번호
순번1.0000.0000.0000.000
업소명0.0001.0001.0001.000
소재지(도로명)0.0001.0001.0001.000
전화번호0.0001.0001.0001.000

Missing values

2024-01-28T15:51:19.578144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T15:51:19.639780image/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

순번업소명소재지(도로명)전화번호
01이코노미호텔인천부평점인천광역시 부평구 부평대로296번길 88-6 (갈산동)032-529-4941
12갤러리아호텔인천광역시 부평구 대정로90번길 24 (부평동)032-503-4848
23더블유(W)인천광역시 부평구 경원대로1377번길 17-5 (부평동)032-527-4564
34Rg호텔(알지)인천광역시 부평구 원길로11번길 7 (산곡동)032-502-5553
45이코노미호텔인천부평점인천광역시 부평구 부평대로296번길 88-6 (갈산동)032-529-4941
56제니스호텔부평역인천광역시 부평구 경원대로 1427-1 (부평동)032-506-3366
67이오스호텔인천광역시 부평구 대정로82번길 25 (부평동)032-512-2253
78토요코인인천부평인천광역시 부평구 광장로 10 (부평동)032-527-1045
89라임호텔인천광역시 부평구 부평문화로 79번길 40(부평동)032-504-4300
910호텔주노인천광역시 부평구 대정로 36번길 7-1(부평동)032-521-1154
순번업소명소재지(도로명)전화번호
5152호텔세븐스텝인천광역시 부평구 장제로92번길13(부평동)032-525-2521
5253호텔 브랜드 (HOTEL BRAND)인천광역시 부평구 부평대로17번길30(부평동)032-513-5552
5354호텔게이트인천광역시 부평구 광장로30번길66(부평동)032-504-2600
5455온앤오프(ON&OFF)인천광역시 부평구 장제로91번길30(부평동)032-505-5181
5556센트로호텔인천광역시 부평구 부평문화로105번길13(부평동)032-501-7700
5657호텔오후인천점인천광역시 부평구 열우물로42-16(십정동)032-433-1374
5758골드호텔인천광역시 부평구 동암광장로14번길 15(십정동)032-431-6534
5859모텔 린인천광역시 부평구 동암광장로12번길 13(십정동)032-424-2247
5960호텔러브스인천광역시 부평구 경원대로1417번길 23(부평동)032-523-7135
6061호텔벨루스인천광역시 부평구 부흥로294번길 19(부평동)032-529-7925