Overview

Dataset statistics

Number of variables5
Number of observations315
Missing cells115
Missing cells (%)7.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.0 KiB
Average record size in memory42.4 B

Variable types

Numeric2
Text3

Dataset

Description부산광역시해운대구_숙박업현황_20230913
Author부산광역시 해운대구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3075790

Alerts

소재지전화 has 115 (36.5%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:52:05.084159
Analysis finished2023-12-10 16:52:06.222522
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct315
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158
Minimum1
Maximum315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T01:52:06.774008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16.7
Q179.5
median158
Q3236.5
95-th percentile299.3
Maximum315
Range314
Interquartile range (IQR)157

Descriptive statistics

Standard deviation91.076891
Coefficient of variation (CV)0.57643602
Kurtosis-1.2
Mean158
Median Absolute Deviation (MAD)79
Skewness0
Sum49770
Variance8295
MonotonicityStrictly increasing
2023-12-11T01:52:07.012302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
209 1
 
0.3%
216 1
 
0.3%
215 1
 
0.3%
214 1
 
0.3%
213 1
 
0.3%
212 1
 
0.3%
211 1
 
0.3%
210 1
 
0.3%
208 1
 
0.3%
Other values (305) 305
96.8%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
315 1
0.3%
314 1
0.3%
313 1
0.3%
312 1
0.3%
311 1
0.3%
310 1
0.3%
309 1
0.3%
308 1
0.3%
307 1
0.3%
306 1
0.3%

업소명
Text

Distinct308
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T01:52:07.468269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length26
Mean length8.1746032
Min length2

Characters and Unicode

Total characters2575
Distinct characters326
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique301 ?
Unique (%)95.6%

Sample

1st row은재모텔
2nd row물고기 미포
3rd row송정여인숙
4th row센텀1972
5th row합천여인숙
ValueCountFrequency (%)
호텔 28
 
5.5%
해운대 20
 
3.9%
hotel 11
 
2.2%
송정 10
 
2.0%
모텔 5
 
1.0%
해운대점 5
 
1.0%
부산 5
 
1.0%
더 4
 
0.8%
게스트하우스 4
 
0.8%
the 4
 
0.8%
Other values (372) 412
81.1%
2023-12-11T01:52:08.209486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
193
 
7.5%
텔 149
 
5.8%
호 122
 
4.7%
스 119
 
4.6%
이 66
 
2.6%
운 52
 
2.0%
) 50
 
1.9%
트 50
 
1.9%
( 50
 
1.9%
대 49
 
1.9%
Other values (316) 1675
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1889
73.4%
Uppercase Letter 236
 
9.2%
Space Separator 193
 
7.5%
Lowercase Letter 108
 
4.2%
Close Punctuation 50
 
1.9%
Open Punctuation 50
 
1.9%
Decimal Number 36
 
1.4%
Other Punctuation 10
 
0.4%
Letter Number 2
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 149
 
7.9%
호 122
 
6.5%
스 119
 
6.3%
이 66
 
3.5%
운 52
 
2.8%
트 50
 
2.6%
대 49
 
2.6%
해 47
 
2.5%
라 35
 
1.9%
모 33
 
1.7%
Other values (255) 1167
61.8%
Uppercase Letter
ValueCountFrequency (%)
E 26
11.0%
L 25
10.6%
H 25
10.6%
T 23
9.7%
O 21
 
8.9%
A 19
 
8.1%
N 12
 
5.1%
S 11
 
4.7%
I 9
 
3.8%
B 9
 
3.8%
Other values (15) 56
23.7%
Lowercase Letter
ValueCountFrequency (%)
e 22
20.4%
t 11
10.2%
o 10
9.3%
a 9
8.3%
l 7
 
6.5%
r 7
 
6.5%
n 6
 
5.6%
u 6
 
5.6%
i 5
 
4.6%
h 5
 
4.6%
Other values (10) 20
18.5%
Decimal Number
ValueCountFrequency (%)
6 6
16.7%
9 6
16.7%
1 5
13.9%
5 4
11.1%
4 4
11.1%
2 4
11.1%
3 3
8.3%
7 3
8.3%
0 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 8
80.0%
& 2
 
20.0%
Space Separator
ValueCountFrequency (%)
193
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1890
73.4%
Latin 346
 
13.4%
Common 339
 
13.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 149
 
7.9%
호 122
 
6.5%
스 119
 
6.3%
이 66
 
3.5%
운 52
 
2.8%
트 50
 
2.6%
대 49
 
2.6%
해 47
 
2.5%
라 35
 
1.9%
모 33
 
1.7%
Other values (256) 1168
61.8%
Latin
ValueCountFrequency (%)
E 26
 
7.5%
L 25
 
7.2%
H 25
 
7.2%
T 23
 
6.6%
e 22
 
6.4%
O 21
 
6.1%
A 19
 
5.5%
N 12
 
3.5%
t 11
 
3.2%
S 11
 
3.2%
Other values (36) 151
43.6%
Common
ValueCountFrequency (%)
193
56.9%
) 50
 
14.7%
( 50
 
14.7%
. 8
 
2.4%
6 6
 
1.8%
9 6
 
1.8%
1 5
 
1.5%
5 4
 
1.2%
4 4
 
1.2%
2 4
 
1.2%
Other values (4) 9
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1889
73.4%
ASCII 683
 
26.5%
Number Forms 2
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
193
28.3%
) 50
 
7.3%
( 50
 
7.3%
E 26
 
3.8%
L 25
 
3.7%
H 25
 
3.7%
T 23
 
3.4%
e 22
 
3.2%
O 21
 
3.1%
A 19
 
2.8%
Other values (49) 229
33.5%
Hangul
ValueCountFrequency (%)
텔 149
 
7.9%
호 122
 
6.5%
스 119
 
6.3%
이 66
 
3.5%
운 52
 
2.8%
트 50
 
2.6%
대 49
 
2.6%
해 47
 
2.5%
라 35
 
1.9%
모 33
 
1.7%
Other values (255) 1167
61.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

영업소 주소(도로명)
Text

Distinct293
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T01:52:08.650264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length30.396825
Min length21

Characters and Unicode

Total characters9575
Distinct characters127
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

Unique280 ?
Unique (%)88.9%

Sample

1st row부산광역시 해운대구 윗반송로31번길 99-23 (반송동)
2nd row부산광역시 해운대구 달맞이길62번가길 43 (중동)
3rd row부산광역시 해운대구 송정1로8번길 49 (송정동)
4th row부산광역시 해운대구 해운대로 333 (우동)
5th row부산광역시 해운대구 윗반송로31번길 113-12 (반송동)
ValueCountFrequency (%)
부산광역시 315
18.0%
해운대구 315
18.0%
송정동 105
 
6.0%
우동 92
 
5.3%
중동 84
 
4.8%
재송동 24
 
1.4%
송정광어골로 24
 
1.4%
송정해변로 21
 
1.2%
해운대해변로 20
 
1.1%
해운대해변로298번길 14
 
0.8%
Other values (322) 736
42.1%
2023-12-11T01:52:09.431597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1435
 
15.0%
해 520
 
5.4%
운 434
 
4.5%
대 433
 
4.5%
구 361
 
3.8%
동 340
 
3.6%
광 340
 
3.6%
시 334
 
3.5%
부 320
 
3.3%
) 318
 
3.3%
Other values (117) 4740
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5896
61.6%
Space Separator 1435
 
15.0%
Decimal Number 1364
 
14.2%
Close Punctuation 318
 
3.3%
Open Punctuation 318
 
3.3%
Other Punctuation 139
 
1.5%
Dash Punctuation 66
 
0.7%
Math Symbol 35
 
0.4%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
해 520
 
8.8%
운 434
 
7.4%
대 433
 
7.3%
구 361
 
6.1%
동 340
 
5.8%
광 340
 
5.8%
시 334
 
5.7%
부 320
 
5.4%
산 316
 
5.4%
역 315
 
5.3%
Other values (99) 2183
37.0%
Decimal Number
ValueCountFrequency (%)
1 274
20.1%
2 227
16.6%
3 173
12.7%
9 123
9.0%
4 113
8.3%
6 109
 
8.0%
5 99
 
7.3%
0 93
 
6.8%
8 78
 
5.7%
7 75
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
A 3
75.0%
B 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1435
100.0%
Close Punctuation
ValueCountFrequency (%)
) 318
100.0%
Open Punctuation
ValueCountFrequency (%)
( 318
100.0%
Other Punctuation
ValueCountFrequency (%)
, 139
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%
Math Symbol
ValueCountFrequency (%)
~ 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5896
61.6%
Common 3675
38.4%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
해 520
 
8.8%
운 434
 
7.4%
대 433
 
7.3%
구 361
 
6.1%
동 340
 
5.8%
광 340
 
5.8%
시 334
 
5.7%
부 320
 
5.4%
산 316
 
5.4%
역 315
 
5.3%
Other values (99) 2183
37.0%
Common
ValueCountFrequency (%)
1435
39.0%
) 318
 
8.7%
( 318
 
8.7%
1 274
 
7.5%
2 227
 
6.2%
3 173
 
4.7%
, 139
 
3.8%
9 123
 
3.3%
4 113
 
3.1%
6 109
 
3.0%
Other values (6) 446
 
12.1%
Latin
ValueCountFrequency (%)
A 3
75.0%
B 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5896
61.6%
ASCII 3679
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1435
39.0%
) 318
 
8.6%
( 318
 
8.6%
1 274
 
7.4%
2 227
 
6.2%
3 173
 
4.7%
, 139
 
3.8%
9 123
 
3.3%
4 113
 
3.1%
6 109
 
3.0%
Other values (8) 450
 
12.2%
Hangul
ValueCountFrequency (%)
해 520
 
8.8%
운 434
 
7.4%
대 433
 
7.3%
구 361
 
6.1%
동 340
 
5.8%
광 340
 
5.8%
시 334
 
5.7%
부 320
 
5.4%
산 316
 
5.4%
역 315
 
5.3%
Other values (99) 2183
37.0%

소재지전화
Text

MISSING 

Distinct195
Distinct (%)97.5%
Missing115
Missing (%)36.5%
Memory size2.6 KiB
2023-12-11T01:52:09.842668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.995
Min length10

Characters and Unicode

Total characters2399
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

Unique191 ?
Unique (%)95.5%

Sample

1st row051-531-8946
2nd row051-746-9688
3rd row051-703-8090
4th row051-543-8150
5th row051-746-1232
ValueCountFrequency (%)
051-741-7711 3
 
1.5%
1855-0788 2
 
1.0%
051-501-9440 2
 
1.0%
0517-4222-77 2
 
1.0%
051-664-1234 1
 
0.5%
051-740-7010 1
 
0.5%
051-531-8946 1
 
0.5%
051-760-7001 1
 
0.5%
051-742-9309 1
 
0.5%
051-606-0600 1
 
0.5%
Other values (185) 185
92.5%
2023-12-11T01:52:10.579789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 419
17.5%
- 400
16.7%
1 359
15.0%
7 285
11.9%
5 271
11.3%
4 176
7.3%
2 108
 
4.5%
3 108
 
4.5%
8 100
 
4.2%
6 90
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1999
83.3%
Dash Punctuation 400
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 419
21.0%
1 359
18.0%
7 285
14.3%
5 271
13.6%
4 176
8.8%
2 108
 
5.4%
3 108
 
5.4%
8 100
 
5.0%
6 90
 
4.5%
9 83
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 400
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2399
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 419
17.5%
- 400
16.7%
1 359
15.0%
7 285
11.9%
5 271
11.3%
4 176
7.3%
2 108
 
4.5%
3 108
 
4.5%
8 100
 
4.2%
6 90
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2399
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 419
17.5%
- 400
16.7%
1 359
15.0%
7 285
11.9%
5 271
11.3%
4 176
7.3%
2 108
 
4.5%
3 108
 
4.5%
8 100
 
4.2%
6 90
 
3.8%

객실수
Real number (ℝ)

Distinct97
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.577778
Minimum1
Maximum537
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T01:52:10.832482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median23
Q340.5
95-th percentile239.1
Maximum537
Range536
Interquartile range (IQR)32.5

Descriptive statistics

Standard deviation85.073382
Coefficient of variation (CV)1.7512819
Kurtosis12.131564
Mean48.577778
Median Absolute Deviation (MAD)15
Skewness3.3827931
Sum15302
Variance7237.4804
MonotonicityNot monotonic
2023-12-11T01:52:11.102311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 14
 
4.4%
8 14
 
4.4%
7 12
 
3.8%
30 10
 
3.2%
10 10
 
3.2%
2 10
 
3.2%
3 10
 
3.2%
9 10
 
3.2%
5 9
 
2.9%
1 9
 
2.9%
Other values (87) 207
65.7%
ValueCountFrequency (%)
1 9
2.9%
2 10
3.2%
3 10
3.2%
4 14
4.4%
5 9
2.9%
6 8
2.5%
7 12
3.8%
8 14
4.4%
9 10
3.2%
10 10
3.2%
ValueCountFrequency (%)
537 1
0.3%
510 1
0.3%
472 1
0.3%
417 1
0.3%
407 1
0.3%
402 1
0.3%
393 1
0.3%
353 1
0.3%
331 1
0.3%
330 1
0.3%

Interactions

2023-12-11T01:52:05.742475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:52:05.459161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:52:05.850287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:52:05.607359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:52:11.244575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번객실수
연번1.0000.324
객실수0.3241.000
2023-12-11T01:52:11.392332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번객실수
연번1.000-0.233
객실수-0.2331.000

Missing values

2023-12-11T01:52:05.983639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:52:06.143771image/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

연번업소명영업소 주소(도로명)소재지전화객실수
01은재모텔부산광역시 해운대구 윗반송로31번길 99-23 (반송동)051-531-89466
12물고기 미포부산광역시 해운대구 달맞이길62번가길 43 (중동)051-746-96883
23송정여인숙부산광역시 해운대구 송정1로8번길 49 (송정동)051-703-80907
34센텀1972부산광역시 해운대구 해운대로 333 (우동)<NA>7
45합천여인숙부산광역시 해운대구 윗반송로31번길 113-12 (반송동)051-543-81506
56비트윈 해운대부산광역시 해운대구 구남로21번길 9-22 (우동)051-746-123210
67(주)조선호텔앤리조트 부산부산광역시 해운대구 동백로 67 (우동)051-742-7411285
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307308호텔위드부산광역시 해운대구 해운대해변로298번길 29, 해운대푸르지오시티 B동 905호 (중동)<NA>69
308309심플앤와이드부산광역시 해운대구 송정중앙로36번길 48, 15층 (송정동)<NA>30
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