Overview

Dataset statistics

Number of variables5
Number of observations122
Missing cells76
Missing cells (%)12.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory43.1 B

Variable types

Text3
Numeric2

Dataset

Description부산광역시남구_숙박업현황_20200701
Author부산광역시 남구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15055782

Alerts

소재지전화 has 20 (16.4%) missing valuesMissing
객실수 has 56 (45.9%) missing valuesMissing

Reproduction

Analysis started2023-12-10 16:52:00.618574
Analysis finished2023-12-10 16:52:01.830106
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct120
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:52:02.097761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length5.795082
Min length3

Characters and Unicode

Total characters707
Distinct characters209
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

Unique118 ?
Unique (%)96.7%

Sample

1st row우암여관
2nd row태양모텔
3rd row풍조장여관
4th row다래모텔
5th row범일 여인숙
ValueCountFrequency (%)
모텔 8
 
5.5%
주식회사 5
 
3.4%
여관 4
 
2.8%
여인숙 2
 
1.4%
낙원모텔 2
 
1.4%
브이모텔 2
 
1.4%
주)테무진가드 1
 
0.7%
부산환경 1
 
0.7%
크린닥터 1
 
0.7%
광진개발(주 1
 
0.7%
Other values (118) 118
81.4%
2023-12-11T01:52:02.618742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 43
 
6.1%
모 36
 
5.1%
주 35
 
5.0%
( 31
 
4.4%
) 31
 
4.4%
23
 
3.3%
스 19
 
2.7%
이 15
 
2.1%
관 14
 
2.0%
여 13
 
1.8%
Other values (199) 447
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 587
83.0%
Open Punctuation 31
 
4.4%
Close Punctuation 31
 
4.4%
Uppercase Letter 26
 
3.7%
Space Separator 23
 
3.3%
Decimal Number 7
 
1.0%
Other Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 43
 
7.3%
모 36
 
6.1%
주 35
 
6.0%
스 19
 
3.2%
이 15
 
2.6%
관 14
 
2.4%
여 13
 
2.2%
사 10
 
1.7%
장 10
 
1.7%
에 9
 
1.5%
Other values (172) 383
65.2%
Uppercase Letter
ValueCountFrequency (%)
K 4
15.4%
G 2
 
7.7%
C 2
 
7.7%
U 2
 
7.7%
L 2
 
7.7%
I 2
 
7.7%
S 1
 
3.8%
T 1
 
3.8%
N 1
 
3.8%
E 1
 
3.8%
Other values (8) 8
30.8%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
9 2
28.6%
7 1
 
14.3%
2 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 587
83.0%
Common 94
 
13.3%
Latin 26
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 43
 
7.3%
모 36
 
6.1%
주 35
 
6.0%
스 19
 
3.2%
이 15
 
2.6%
관 14
 
2.4%
여 13
 
2.2%
사 10
 
1.7%
장 10
 
1.7%
에 9
 
1.5%
Other values (172) 383
65.2%
Latin
ValueCountFrequency (%)
K 4
15.4%
G 2
 
7.7%
C 2
 
7.7%
U 2
 
7.7%
L 2
 
7.7%
I 2
 
7.7%
S 1
 
3.8%
T 1
 
3.8%
N 1
 
3.8%
E 1
 
3.8%
Other values (8) 8
30.8%
Common
ValueCountFrequency (%)
( 31
33.0%
) 31
33.0%
23
24.5%
1 3
 
3.2%
9 2
 
2.1%
& 1
 
1.1%
7 1
 
1.1%
+ 1
 
1.1%
2 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 587
83.0%
ASCII 120
 
17.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 43
 
7.3%
모 36
 
6.1%
주 35
 
6.0%
스 19
 
3.2%
이 15
 
2.6%
관 14
 
2.4%
여 13
 
2.2%
사 10
 
1.7%
장 10
 
1.7%
에 9
 
1.5%
Other values (172) 383
65.2%
ASCII
ValueCountFrequency (%)
( 31
25.8%
) 31
25.8%
23
19.2%
K 4
 
3.3%
1 3
 
2.5%
G 2
 
1.7%
C 2
 
1.7%
9 2
 
1.7%
U 2
 
1.7%
L 2
 
1.7%
Other values (17) 18
15.0%

업소소재지
Text

Distinct120
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:52:02.996652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length26.303279
Min length21

Characters and Unicode

Total characters3209
Distinct characters97
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

Unique118 ?
Unique (%)96.7%

Sample

1st row부산광역시 남구 우암번영로14번길 14 (우암동)
2nd row부산광역시 남구 전포대로 106-2 (문현동)
3rd row부산광역시 남구 수영로 159 (대연동)
4th row부산광역시 남구 유엔평화로17번길 5 (대연동)
5th row부산광역시 남구 남동천로 56-6 (문현동)
ValueCountFrequency (%)
부산광역시 122
18.8%
남구 122
18.8%
대연동 58
 
8.9%
문현동 27
 
4.2%
용호동 13
 
2.0%
용당동 9
 
1.4%
용호로 9
 
1.4%
유엔평화로4번길 9
 
1.4%
수영로13번길 7
 
1.1%
수영로 7
 
1.1%
Other values (166) 266
41.0%
2023-12-11T01:52:03.456391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
527
 
16.4%
동 129
 
4.0%
남 129
 
4.0%
) 125
 
3.9%
( 125
 
3.9%
부 124
 
3.9%
시 123
 
3.8%
산 123
 
3.8%
구 122
 
3.8%
역 122
 
3.8%
Other values (87) 1560
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1864
58.1%
Space Separator 527
 
16.4%
Decimal Number 498
 
15.5%
Close Punctuation 125
 
3.9%
Open Punctuation 125
 
3.9%
Other Punctuation 41
 
1.3%
Dash Punctuation 27
 
0.8%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 129
 
6.9%
남 129
 
6.9%
부 124
 
6.7%
시 123
 
6.6%
산 123
 
6.6%
구 122
 
6.5%
역 122
 
6.5%
광 122
 
6.5%
로 122
 
6.5%
대 66
 
3.5%
Other values (69) 682
36.6%
Decimal Number
ValueCountFrequency (%)
1 119
23.9%
2 80
16.1%
3 57
11.4%
4 56
11.2%
0 44
 
8.8%
5 41
 
8.2%
6 30
 
6.0%
9 25
 
5.0%
8 24
 
4.8%
7 22
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 40
97.6%
/ 1
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
O 1
50.0%
Space Separator
ValueCountFrequency (%)
527
100.0%
Close Punctuation
ValueCountFrequency (%)
) 125
100.0%
Open Punctuation
ValueCountFrequency (%)
( 125
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1864
58.1%
Common 1343
41.9%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 129
 
6.9%
남 129
 
6.9%
부 124
 
6.7%
시 123
 
6.6%
산 123
 
6.6%
구 122
 
6.5%
역 122
 
6.5%
광 122
 
6.5%
로 122
 
6.5%
대 66
 
3.5%
Other values (69) 682
36.6%
Common
ValueCountFrequency (%)
527
39.2%
) 125
 
9.3%
( 125
 
9.3%
1 119
 
8.9%
2 80
 
6.0%
3 57
 
4.2%
4 56
 
4.2%
0 44
 
3.3%
5 41
 
3.1%
, 40
 
3.0%
Other values (6) 129
 
9.6%
Latin
ValueCountFrequency (%)
T 1
50.0%
O 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1864
58.1%
ASCII 1345
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
527
39.2%
) 125
 
9.3%
( 125
 
9.3%
1 119
 
8.8%
2 80
 
5.9%
3 57
 
4.2%
4 56
 
4.2%
0 44
 
3.3%
5 41
 
3.0%
, 40
 
3.0%
Other values (8) 131
 
9.7%
Hangul
ValueCountFrequency (%)
동 129
 
6.9%
남 129
 
6.9%
부 124
 
6.7%
시 123
 
6.6%
산 123
 
6.6%
구 122
 
6.5%
역 122
 
6.5%
광 122
 
6.5%
로 122
 
6.5%
대 66
 
3.5%
Other values (69) 682
36.6%

소재지전화
Text

MISSING 

Distinct100
Distinct (%)98.0%
Missing20
Missing (%)16.4%
Memory size1.1 KiB
2023-12-11T01:52:03.677940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.029412
Min length12

Characters and Unicode

Total characters1227
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

Unique98 ?
Unique (%)96.1%

Sample

1st row051-646-3975
2nd row051-633-9297
3rd row051-639-0011
4th row051-625-4291
5th row051-633-7174
ValueCountFrequency (%)
051-638-7212 2
 
2.0%
051-627-1144 2
 
2.0%
051-802-7036 1
 
1.0%
051-646-3975 1
 
1.0%
051-466-9403 1
 
1.0%
070-8810-8903 1
 
1.0%
051-521-6500 1
 
1.0%
051-724-6887 1
 
1.0%
051-469-0900 1
 
1.0%
051-643-9365 1
 
1.0%
Other values (90) 90
88.2%
2023-12-11T01:52:04.031444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 204
16.6%
1 165
13.4%
0 160
13.0%
5 149
12.1%
6 144
11.7%
2 103
8.4%
4 81
 
6.6%
8 61
 
5.0%
7 61
 
5.0%
3 59
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1023
83.4%
Dash Punctuation 204
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 165
16.1%
0 160
15.6%
5 149
14.6%
6 144
14.1%
2 103
10.1%
4 81
7.9%
8 61
 
6.0%
7 61
 
6.0%
3 59
 
5.8%
9 40
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 204
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1227
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 204
16.6%
1 165
13.4%
0 160
13.0%
5 149
12.1%
6 144
11.7%
2 103
8.4%
4 81
 
6.6%
8 61
 
5.0%
7 61
 
5.0%
3 59
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1227
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 204
16.6%
1 165
13.4%
0 160
13.0%
5 149
12.1%
6 144
11.7%
2 103
8.4%
4 81
 
6.6%
8 61
 
5.0%
7 61
 
5.0%
3 59
 
4.8%

우편번호
Real number (ℝ)

Distinct53
Distinct (%)43.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48487.016
Minimum48402
Maximum48593
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:04.169045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48402
5-th percentile48409.1
Q148450.75
median48492
Q348510
95-th percentile48567
Maximum48593
Range191
Interquartile range (IQR)59.25

Descriptive statistics

Standard deviation48.463155
Coefficient of variation (CV)0.00099950789
Kurtosis-0.68286313
Mean48487.016
Median Absolute Deviation (MAD)37
Skewness0.10590889
Sum5915416
Variance2348.6774
MonotonicityNot monotonic
2023-12-11T01:52:04.311025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48492 12
 
9.8%
48445 9
 
7.4%
48415 7
 
5.7%
48567 6
 
4.9%
48504 5
 
4.1%
48402 5
 
4.1%
48475 5
 
4.1%
48496 4
 
3.3%
48548 4
 
3.3%
48497 3
 
2.5%
Other values (43) 62
50.8%
ValueCountFrequency (%)
48402 5
4.1%
48409 2
 
1.6%
48411 1
 
0.8%
48415 7
5.7%
48418 1
 
0.8%
48420 1
 
0.8%
48429 2
 
1.6%
48443 1
 
0.8%
48445 9
7.4%
48448 1
 
0.8%
ValueCountFrequency (%)
48593 1
 
0.8%
48587 1
 
0.8%
48579 1
 
0.8%
48568 2
 
1.6%
48567 6
4.9%
48562 1
 
0.8%
48556 3
2.5%
48554 1
 
0.8%
48548 4
3.3%
48547 1
 
0.8%

객실수
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)50.0%
Missing56
Missing (%)45.9%
Infinite0
Infinite (%)0.0%
Mean24.181818
Minimum8
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:52:04.493910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile9
Q115
median22
Q333.5
95-th percentile44.25
Maximum52
Range44
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation11.624787
Coefficient of variation (CV)0.48072426
Kurtosis-0.54015485
Mean24.181818
Median Absolute Deviation (MAD)8
Skewness0.59986839
Sum1596
Variance135.13566
MonotonicityNot monotonic
2023-12-11T01:52:04.703776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
22 4
 
3.3%
12 4
 
3.3%
9 4
 
3.3%
14 3
 
2.5%
10 3
 
2.5%
19 3
 
2.5%
35 3
 
2.5%
16 3
 
2.5%
20 3
 
2.5%
18 3
 
2.5%
Other values (23) 33
27.0%
(Missing) 56
45.9%
ValueCountFrequency (%)
8 1
 
0.8%
9 4
3.3%
10 3
2.5%
12 4
3.3%
13 1
 
0.8%
14 3
2.5%
15 2
1.6%
16 3
2.5%
17 1
 
0.8%
18 3
2.5%
ValueCountFrequency (%)
52 1
 
0.8%
51 1
 
0.8%
49 1
 
0.8%
45 1
 
0.8%
42 1
 
0.8%
41 2
1.6%
40 2
1.6%
38 2
1.6%
36 2
1.6%
35 3
2.5%

Interactions

2023-12-11T01:52:01.179405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:52:00.968008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:52:01.319918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:52:01.081347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:52:04.815144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지전화우편번호객실수
소재지전화1.0001.0000.971
우편번호1.0001.0000.368
객실수0.9710.3681.000
2023-12-11T01:52:04.917518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호객실수
우편번호1.000-0.156
객실수-0.1561.000

Missing values

2023-12-11T01:52:01.476092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:52:01.607067image/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.
2023-12-11T01:52:01.756597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업소명업소소재지소재지전화우편번호객실수
0우암여관부산광역시 남구 우암번영로14번길 14 (우암동)051-646-3975484799
1태양모텔부산광역시 남구 전포대로 106-2 (문현동)051-633-9297484119
2풍조장여관부산광역시 남구 수영로 159 (대연동)051-639-00114845312
3다래모텔부산광역시 남구 유엔평화로17번길 5 (대연동)051-625-42914850418
4범일 여인숙부산광역시 남구 남동천로 56-6 (문현동)051-633-71744840215
5남일 여인숙부산광역시 남구 못골로 92-1 (대연동)051-627-11444844514
6새여관부산광역시 남구 우암로79번길 17 (감만동)051-632-5580485568
7문현 모텔부산광역시 남구 지게골로10번길 5 (문현동)051-646-17454847610
8루이모텔부산광역시 남구 유엔평화로 4-74 (대연동)051-634-00114849214
9짝 모텔부산광역시 남구 수영로 195-7 (대연동)051-635-80014844527
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