Overview

Dataset statistics

Number of variables4
Number of observations43
Missing cells1
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory36.1 B

Variable types

Numeric1
Text3

Dataset

Description인천광역시 부평구 우수 숙박 업소 현황 데이터는 우수숙박업소 명, 숙박업소 소재지, 전화번호에 대한 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15104146/fileData.do

Alerts

전화번호 has 1 (2.3%) missing valuesMissing
순번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:05:39.595345
Analysis finished2023-12-12 14:05:40.050025
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T23:05:40.131699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.1
Q111.5
median22
Q332.5
95-th percentile40.9
Maximum43
Range42
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.556539
Coefficient of variation (CV)0.57075176
Kurtosis-1.2
Mean22
Median Absolute Deviation (MAD)11
Skewness0
Sum946
Variance157.66667
MonotonicityStrictly increasing
2023-12-12T23:05:40.296454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 1
 
2.3%
2 1
 
2.3%
25 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%
34 1
2.3%

업소명
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T23:05:40.569200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length6.6744186
Min length3

Characters and Unicode

Total characters287
Distinct characters109
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

Unique43 ?
Unique (%)100.0%

Sample

1st row갤러리아호텔
2nd row샴푸호텔
3rd row호텔러브스
4th row이오스호텔
5th row라임호텔
ValueCountFrequency (%)
갤러리아호텔 1
 
2.0%
모텔린 1
 
2.0%
샴푸모텔 1
 
2.0%
모텔세븐 1
 
2.0%
스테이 1
 
2.0%
인 1
 
2.0%
호텔(stay 1
 
2.0%
inn 1
 
2.0%
hotel 1
 
2.0%
에스원호텔(s-1)호텔 1
 
2.0%
Other values (41) 41
80.4%
2023-12-12T23:05:41.045254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 37
 
12.9%
호 28
 
9.8%
스 9
 
3.1%
모 9
 
3.1%
( 9
 
3.1%
) 9
 
3.1%
8
 
2.8%
이 6
 
2.1%
T 5
 
1.7%
인 4
 
1.4%
Other values (99) 163
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 213
74.2%
Uppercase Letter 40
 
13.9%
Open Punctuation 9
 
3.1%
Close Punctuation 9
 
3.1%
Space Separator 8
 
2.8%
Decimal Number 4
 
1.4%
Other Punctuation 2
 
0.7%
Dash Punctuation 1
 
0.3%
Lowercase Letter 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 37
 
17.4%
호 28
 
13.1%
스 9
 
4.2%
모 9
 
4.2%
이 6
 
2.8%
인 4
 
1.9%
리 4
 
1.9%
평 3
 
1.4%
루 3
 
1.4%
코 3
 
1.4%
Other values (72) 107
50.2%
Uppercase Letter
ValueCountFrequency (%)
T 5
12.5%
O 4
10.0%
E 4
10.0%
N 3
 
7.5%
L 3
 
7.5%
I 3
 
7.5%
A 3
 
7.5%
S 2
 
5.0%
Y 2
 
5.0%
R 2
 
5.0%
Other values (8) 9
22.5%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
2 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 213
74.2%
Latin 41
 
14.3%
Common 33
 
11.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 37
 
17.4%
호 28
 
13.1%
스 9
 
4.2%
모 9
 
4.2%
이 6
 
2.8%
인 4
 
1.9%
리 4
 
1.9%
평 3
 
1.4%
루 3
 
1.4%
코 3
 
1.4%
Other values (72) 107
50.2%
Latin
ValueCountFrequency (%)
T 5
12.2%
O 4
 
9.8%
E 4
 
9.8%
N 3
 
7.3%
L 3
 
7.3%
I 3
 
7.3%
A 3
 
7.3%
S 2
 
4.9%
Y 2
 
4.9%
R 2
 
4.9%
Other values (9) 10
24.4%
Common
ValueCountFrequency (%)
( 9
27.3%
) 9
27.3%
8
24.2%
1 2
 
6.1%
. 2
 
6.1%
- 1
 
3.0%
5 1
 
3.0%
2 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 213
74.2%
ASCII 74
 
25.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 37
 
17.4%
호 28
 
13.1%
스 9
 
4.2%
모 9
 
4.2%
이 6
 
2.8%
인 4
 
1.9%
리 4
 
1.9%
평 3
 
1.4%
루 3
 
1.4%
코 3
 
1.4%
Other values (72) 107
50.2%
ASCII
ValueCountFrequency (%)
( 9
 
12.2%
) 9
 
12.2%
8
 
10.8%
T 5
 
6.8%
O 4
 
5.4%
E 4
 
5.4%
N 3
 
4.1%
L 3
 
4.1%
I 3
 
4.1%
A 3
 
4.1%
Other values (17) 23
31.1%

소재지(도로명)
Text

Distinct42
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T23:05:41.370413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length29
Mean length26.651163
Min length21

Characters and Unicode

Total characters1146
Distinct characters49
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

Unique41 ?
Unique (%)95.3%

Sample

1st row인천광역시 부평구 대정로90번길 24 (부평동)
2nd row인천광역시 부평구 광장로4번길 23 (부평동)
3rd row인천광역시 부평구 경원대로1417번길 23 (부평동)
4th row인천광역시 부평구 대정로82번길 25 (부평동)
5th row인천광역시 부평구 부평문화로79번길 40 (부평동)
ValueCountFrequency (%)
인천광역시 43
23.0%
부평구 43
23.0%
부평동 10
 
5.3%
경원대로1377번길 3
 
1.6%
경원대로 3
 
1.6%
시장로12번길 3
 
1.6%
대정로82번길 3
 
1.6%
동암광장로4번길 2
 
1.1%
부평문화로116번길 2
 
1.1%
부평대로17번길 2
 
1.1%
Other values (62) 73
39.0%
2023-12-12T23:05:41.832108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
144
 
12.6%
부 79
 
6.9%
평 78
 
6.8%
광 53
 
4.6%
동 50
 
4.4%
1 50
 
4.4%
천 46
 
4.0%
시 46
 
4.0%
인 44
 
3.8%
구 43
 
3.8%
Other values (39) 513
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 712
62.1%
Decimal Number 190
 
16.6%
Space Separator 144
 
12.6%
Close Punctuation 43
 
3.8%
Open Punctuation 43
 
3.8%
Dash Punctuation 14
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 79
11.1%
평 78
11.0%
광 53
 
7.4%
동 50
 
7.0%
천 46
 
6.5%
시 46
 
6.5%
인 44
 
6.2%
구 43
 
6.0%
로 43
 
6.0%
역 43
 
6.0%
Other values (25) 187
26.3%
Decimal Number
ValueCountFrequency (%)
1 50
26.3%
2 30
15.8%
7 24
12.6%
4 21
11.1%
3 19
 
10.0%
8 13
 
6.8%
9 11
 
5.8%
6 11
 
5.8%
0 6
 
3.2%
5 5
 
2.6%
Space Separator
ValueCountFrequency (%)
144
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 712
62.1%
Common 434
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 79
11.1%
평 78
11.0%
광 53
 
7.4%
동 50
 
7.0%
천 46
 
6.5%
시 46
 
6.5%
인 44
 
6.2%
구 43
 
6.0%
로 43
 
6.0%
역 43
 
6.0%
Other values (25) 187
26.3%
Common
ValueCountFrequency (%)
144
33.2%
1 50
 
11.5%
) 43
 
9.9%
( 43
 
9.9%
2 30
 
6.9%
7 24
 
5.5%
4 21
 
4.8%
3 19
 
4.4%
- 14
 
3.2%
8 13
 
3.0%
Other values (4) 33
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 712
62.1%
ASCII 434
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
144
33.2%
1 50
 
11.5%
) 43
 
9.9%
( 43
 
9.9%
2 30
 
6.9%
7 24
 
5.5%
4 21
 
4.8%
3 19
 
4.4%
- 14
 
3.2%
8 13
 
3.0%
Other values (4) 33
 
7.6%
Hangul
ValueCountFrequency (%)
부 79
11.1%
평 78
11.0%
광 53
 
7.4%
동 50
 
7.0%
천 46
 
6.5%
시 46
 
6.5%
인 44
 
6.2%
구 43
 
6.0%
로 43
 
6.0%
역 43
 
6.0%
Other values (25) 187
26.3%

전화번호
Text

MISSING 

Distinct40
Distinct (%)95.2%
Missing1
Missing (%)2.3%
Memory size476.0 B
2023-12-12T23:05:42.088094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters504
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

Unique38 ?
Unique (%)90.5%

Sample

1st row032-503-4848
2nd row032-522-5855
3rd row032-523-7135
4th row032-512-2253
5th row032-526-5590
ValueCountFrequency (%)
032-522-5855 2
 
4.8%
032-424-2247 2
 
4.8%
032-515-0106 1
 
2.4%
032-434-8602 1
 
2.4%
032-525-2521 1
 
2.4%
032-502-0844 1
 
2.4%
032-421-0381 1
 
2.4%
032-512-7373 1
 
2.4%
032-518-1491 1
 
2.4%
032-330-8075 1
 
2.4%
Other values (30) 30
71.4%
2023-12-12T23:05:42.423377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 84
16.7%
- 84
16.7%
3 76
15.1%
0 69
13.7%
5 62
12.3%
1 40
7.9%
4 33
 
6.5%
8 16
 
3.2%
7 14
 
2.8%
6 14
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 420
83.3%
Dash Punctuation 84
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 84
20.0%
3 76
18.1%
0 69
16.4%
5 62
14.8%
1 40
9.5%
4 33
 
7.9%
8 16
 
3.8%
7 14
 
3.3%
6 14
 
3.3%
9 12
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 504
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 84
16.7%
- 84
16.7%
3 76
15.1%
0 69
13.7%
5 62
12.3%
1 40
7.9%
4 33
 
6.5%
8 16
 
3.2%
7 14
 
2.8%
6 14
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 504
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 84
16.7%
- 84
16.7%
3 76
15.1%
0 69
13.7%
5 62
12.3%
1 40
7.9%
4 33
 
6.5%
8 16
 
3.2%
7 14
 
2.8%
6 14
 
2.8%

Interactions

2023-12-12T23:05:39.810729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:05:42.518305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번업소명소재지(도로명)전화번호
순번1.0001.0000.9490.901
업소명1.0001.0001.0001.000
소재지(도로명)0.9491.0001.0001.000
전화번호0.9011.0001.0001.000

Missing values

2023-12-12T23:05:39.924582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:05:40.015543image/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
01갤러리아호텔인천광역시 부평구 대정로90번길 24 (부평동)032-503-4848
12샴푸호텔인천광역시 부평구 광장로4번길 23 (부평동)032-522-5855
23호텔러브스인천광역시 부평구 경원대로1417번길 23 (부평동)032-523-7135
34이오스호텔인천광역시 부평구 대정로82번길 25 (부평동)032-512-2253
45라임호텔인천광역시 부평구 부평문화로79번길 40 (부평동)032-526-5590
56호텔민트인천광역시 부평구 동암광장로4번길 7 (십정동)032-437-8136
67더블유(W)인천광역시 부평구 경원대로1377번길 17-5(부평동)032-527-4565
78호텔두루와(본관)인천광역시 부평구 시장로12번길 31(부평동)032-516-1006
89Rg호텔(알지)인천광역시 부평구 원길로11번길 7(산곡동)032-502-5553
910더상상호텔인천광역시 부평구 경원대로1377번길 17-10(부평동)032-522-3500
순번업소명소재지(도로명)전화번호
3334호텔브랜드(HOTEL BRAND)인천광역시 부평구 부평대로17번길 30(부평동)032-513-5553
3435보보스모텔인천광역시 부평구 부평대로17번길 23(부평동)032-517-9690
3536칼튼호텔인천광역시 부평구 경원대로1367번길 26-3(부평동)032-524-4430
3637넘버25호텔 동암역점인천광역시 부평구 열우물로42-16(십정동)032-433-1374
3738골드호텔인천광역시 부평구 동암광장로 14번길 15(십정동)032-431-6534
3839호텔벨루스인천광역시 부평구 부흥로294번길 19(부평동)032-529-7925
3940모텔 린인천광역시 부평구 동암광장로12번길 13(십정동)032-424-2247
4041금강여관인천광역시 부평구 경인로667번길 38(십정동)032-425-4819
4142노리터호텔인천광역시 부평구 시장로12번길 28(부평동)032-515-0106
4243필모텔여관인천광역시 부평구 청중로 75(청천동)032-518-1032