Overview

Dataset statistics

Number of variables5
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 KiB
Average record size in memory46.7 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description인천광역시 부평구 더베스트 우수 숙박업소 현황 데이터는 우수 숙박업소 명, 소재지, 소재지 전화번호 대한 데이터를 제공합니다
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15103346&srcSe=7661IVAWM27C61E190

Alerts

업종 has constant value ""Constant
순번 has unique valuesUnique
업소명 has unique valuesUnique
소재지(도로명) has unique valuesUnique
소재지전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-18 05:10:04.071843
Analysis finished2024-03-18 05:10:06.006581
Duration1.93 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-03-18T14:10:06.117546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2024-03-18T14:10:06.311399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
23 1
 
4.3%
22 1
 
4.3%
21 1
 
4.3%
20 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
16 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
6 1
4.3%
7 1
4.3%
8 1
4.3%
9 1
4.3%
10 1
4.3%
ValueCountFrequency (%)
23 1
4.3%
22 1
4.3%
21 1
4.3%
20 1
4.3%
19 1
4.3%
18 1
4.3%
17 1
4.3%
16 1
4.3%
15 1
4.3%
14 1
4.3%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
숙박업(일반)
23 

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) 23
100.0%

Length

2024-03-18T14:10:06.560713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:10:06.707366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업(일반 23
100.0%

업소명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-18T14:10:06.935475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11
Mean length6.6521739
Min length2

Characters and Unicode

Total characters153
Distinct characters80
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

Unique23 ?
Unique (%)100.0%

Sample

1st row버니
2nd row시크릿
3rd row에이플러스
4th row테이크원(TAKE 1)
5th row갤러리아호텔
ValueCountFrequency (%)
버니 1
 
4.2%
시크릿 1
 
4.2%
아이러브유(i.love.you 1
 
4.2%
호텔두루와 1
 
4.2%
뉴상상호텔 1
 
4.2%
아이엠티(imt)호텔 1
 
4.2%
호텔두루와(본관 1
 
4.2%
화이트캐슬 1
 
4.2%
호텔민트 1
 
4.2%
고추잠자리호텔 1
 
4.2%
Other values (14) 14
58.3%
2024-03-18T14:10:07.331548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 15
 
9.8%
호 14
 
9.2%
이 7
 
4.6%
) 6
 
3.9%
( 6
 
3.9%
러 3
 
2.0%
스 3
 
2.0%
평 3
 
2.0%
루 3
 
2.0%
인 3
 
2.0%
Other values (70) 90
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 119
77.8%
Uppercase Letter 17
 
11.1%
Close Punctuation 6
 
3.9%
Open Punctuation 6
 
3.9%
Other Punctuation 2
 
1.3%
Space Separator 1
 
0.7%
Decimal Number 1
 
0.7%
Lowercase Letter 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 15
 
12.6%
호 14
 
11.8%
이 7
 
5.9%
러 3
 
2.5%
스 3
 
2.5%
평 3
 
2.5%
루 3
 
2.5%
인 3
 
2.5%
아 3
 
2.5%
부 3
 
2.5%
Other values (51) 62
52.1%
Uppercase Letter
ValueCountFrequency (%)
I 2
11.8%
E 2
11.8%
T 2
11.8%
O 2
11.8%
M 1
 
5.9%
L 1
 
5.9%
V 1
 
5.9%
Y 1
 
5.9%
U 1
 
5.9%
A 1
 
5.9%
Other values (3) 3
17.6%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 119
77.8%
Latin 18
 
11.8%
Common 16
 
10.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 15
 
12.6%
호 14
 
11.8%
이 7
 
5.9%
러 3
 
2.5%
스 3
 
2.5%
평 3
 
2.5%
루 3
 
2.5%
인 3
 
2.5%
아 3
 
2.5%
부 3
 
2.5%
Other values (51) 62
52.1%
Latin
ValueCountFrequency (%)
I 2
11.1%
E 2
11.1%
T 2
11.1%
O 2
11.1%
M 1
 
5.6%
L 1
 
5.6%
V 1
 
5.6%
Y 1
 
5.6%
U 1
 
5.6%
A 1
 
5.6%
Other values (4) 4
22.2%
Common
ValueCountFrequency (%)
) 6
37.5%
( 6
37.5%
. 2
 
12.5%
1
 
6.2%
1 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 119
77.8%
ASCII 34
 
22.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 15
 
12.6%
호 14
 
11.8%
이 7
 
5.9%
러 3
 
2.5%
스 3
 
2.5%
평 3
 
2.5%
루 3
 
2.5%
인 3
 
2.5%
아 3
 
2.5%
부 3
 
2.5%
Other values (51) 62
52.1%
ASCII
ValueCountFrequency (%)
) 6
17.6%
( 6
17.6%
I 2
 
5.9%
E 2
 
5.9%
T 2
 
5.9%
. 2
 
5.9%
O 2
 
5.9%
M 1
 
2.9%
L 1
 
2.9%
V 1
 
2.9%
Other values (9) 9
26.5%

소재지(도로명)
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-18T14:10:07.503790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length20.652174
Min length16

Characters and Unicode

Total characters475
Distinct characters39
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

Unique23 ?
Unique (%)100.0%

Sample

1st row부평구 경원대로1417번길 17-6 (부평동)
2nd row부평구 장제로83번길 6 (부평동)
3rd row부평구 경원대로1431번길 23 (부평동)
4th row경원대로1417번길 18-1 (부평동)
5th row부평구 대정로90번길 24 (부평동)
ValueCountFrequency (%)
부평구 20
22.5%
부평동 16
18.0%
십정동 3
 
3.4%
7 3
 
3.4%
경원대로1377번길 2
 
2.2%
시장로12번길 2
 
2.2%
동암광장로4번길 2
 
2.2%
25 2
 
2.2%
경원대로1417번길 2
 
2.2%
대정로82번길 2
 
2.2%
Other values (33) 35
39.3%
2024-03-18T14:10:07.777046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67
14.1%
부 40
 
8.4%
평 40
 
8.4%
1 27
 
5.7%
동 25
 
5.3%
로 23
 
4.8%
) 23
 
4.8%
( 23
 
4.8%
길 22
 
4.6%
번 21
 
4.4%
Other values (29) 164
34.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 254
53.5%
Decimal Number 101
 
21.3%
Space Separator 67
 
14.1%
Close Punctuation 23
 
4.8%
Open Punctuation 23
 
4.8%
Dash Punctuation 7
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 40
15.7%
평 40
15.7%
동 25
9.8%
로 23
9.1%
길 22
8.7%
번 21
8.3%
구 20
7.9%
대 12
 
4.7%
장 8
 
3.1%
정 8
 
3.1%
Other values (15) 35
13.8%
Decimal Number
ValueCountFrequency (%)
1 27
26.7%
7 16
15.8%
2 13
12.9%
4 9
 
8.9%
3 9
 
8.9%
8 7
 
6.9%
6 6
 
5.9%
9 6
 
5.9%
0 5
 
5.0%
5 3
 
3.0%
Space Separator
ValueCountFrequency (%)
67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 254
53.5%
Common 221
46.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 40
15.7%
평 40
15.7%
동 25
9.8%
로 23
9.1%
길 22
8.7%
번 21
8.3%
구 20
7.9%
대 12
 
4.7%
장 8
 
3.1%
정 8
 
3.1%
Other values (15) 35
13.8%
Common
ValueCountFrequency (%)
67
30.3%
1 27
12.2%
) 23
 
10.4%
( 23
 
10.4%
7 16
 
7.2%
2 13
 
5.9%
4 9
 
4.1%
3 9
 
4.1%
8 7
 
3.2%
- 7
 
3.2%
Other values (4) 20
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 254
53.5%
ASCII 221
46.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67
30.3%
1 27
12.2%
) 23
 
10.4%
( 23
 
10.4%
7 16
 
7.2%
2 13
 
5.9%
4 9
 
4.1%
3 9
 
4.1%
8 7
 
3.2%
- 7
 
3.2%
Other values (4) 20
 
9.0%
Hangul
ValueCountFrequency (%)
부 40
15.7%
평 40
15.7%
동 25
9.8%
로 23
9.1%
길 22
8.7%
번 21
8.3%
구 20
7.9%
대 12
 
4.7%
장 8
 
3.1%
정 8
 
3.1%
Other values (15) 35
13.8%

소재지전화번호
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-18T14:10:07.947106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters276
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

Unique23 ?
Unique (%)100.0%

Sample

1st row032-524-9840
2nd row032-513-1242
3rd row032-522-4655
4th row032-526-5533
5th row032-503-4848
ValueCountFrequency (%)
032-524-9840 1
 
4.3%
032-521-1154 1
 
4.3%
032-519-3100 1
 
4.3%
032-433-2999 1
 
4.3%
032-522-3500 1
 
4.3%
032-523-1385 1
 
4.3%
032-361-3359 1
 
4.3%
032-526-0961 1
 
4.3%
032-437-8136 1
 
4.3%
032-421-0381 1
 
4.3%
Other values (13) 13
56.5%
2024-03-18T14:10:08.231639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 46
16.7%
2 45
16.3%
3 44
15.9%
0 38
13.8%
5 36
13.0%
1 19
6.9%
4 17
 
6.2%
6 10
 
3.6%
9 9
 
3.3%
8 8
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230
83.3%
Dash Punctuation 46
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 45
19.6%
3 44
19.1%
0 38
16.5%
5 36
15.7%
1 19
8.3%
4 17
 
7.4%
6 10
 
4.3%
9 9
 
3.9%
8 8
 
3.5%
7 4
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 276
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 46
16.7%
2 45
16.3%
3 44
15.9%
0 38
13.8%
5 36
13.0%
1 19
6.9%
4 17
 
6.2%
6 10
 
3.6%
9 9
 
3.3%
8 8
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 276
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 46
16.7%
2 45
16.3%
3 44
15.9%
0 38
13.8%
5 36
13.0%
1 19
6.9%
4 17
 
6.2%
6 10
 
3.6%
9 9
 
3.3%
8 8
 
2.9%

Interactions

2024-03-18T14:10:05.629177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:10:08.370527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번업소명소재지(도로명)소재지전화번호
순번1.0001.0001.0001.000
업소명1.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.000
소재지전화번호1.0001.0001.0001.000

Missing values

2024-03-18T14:10:05.816023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:10:05.940109image/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

순번업종업소명소재지(도로명)소재지전화번호
01숙박업(일반)버니부평구 경원대로1417번길 17-6 (부평동)032-524-9840
12숙박업(일반)시크릿부평구 장제로83번길 6 (부평동)032-513-1242
23숙박업(일반)에이플러스부평구 경원대로1431번길 23 (부평동)032-522-4655
34숙박업(일반)테이크원(TAKE 1)경원대로1417번길 18-1 (부평동)032-526-5533
45숙박업(일반)갤러리아호텔부평구 대정로90번길 24 (부평동)032-503-4848
56숙박업(일반)더블유(W)부평구 경원대로1377번길 17-5 (부평동)032-527-4564
67숙박업(일반)Rg호텔(알지)부평구 원길로11번길 7 (산곡동)032-502-5553
78숙박업(일반)이코노미호텔인천부평점부평구 부평대로296번길 88-6 (갈산동)032-529-4941
89숙박업(일반)제니스호텔부평역부평구 경원대로 1427-1 (부평동)032-506-3366
910숙박업(일반)이오스호텔부평구 대정로82번길 25 (부평동)032-512-2253
순번업종업소명소재지(도로명)소재지전화번호
1314숙박업(일반)샴푸모텔부평구 광장로4번길 23 (부평동)032-522-5855
1415숙박업(일반)고추잠자리호텔부평구 동암광장로4번길 12 (십정동)032-421-0381
1516숙박업(일반)호텔민트부평구 동암광장로4번길 7 (십정동)032-437-8136
1617숙박업(일반)화이트캐슬부평구 장제로91번길 16 (부평동)032-526-0961
1718숙박업(일반)호텔두루와(본관)부평구 시장로12번길 31 (부평동)032-361-3359
1819숙박업(일반)아이엠티(IMT)호텔부평구 대정로82번길 19 (부평동)032-523-1385
1920숙박업(일반)뉴상상호텔부평구 경원대로1377번길 17-10 (부평동)032-522-3500
2021숙박업(일반)호텔두루와부평구 열우물로38번길 7 (십정동)032-433-2999
2122숙박업(일반)아이러브유(I.LOVE.YOU)시장로12번길 25 (부평동)032-519-3100
2223숙박업(일반)호텔마루대정로90번길 27 (부평동)032-511-0178