Overview

Dataset statistics

Number of variables5
Number of observations83
Missing cells2
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory41.6 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description사하구 관내에 영업신고된 숙박업(일반), 숙박업(생활) 현황에 대한 데이터로 업종명, 업소명, 주소, 전화번호 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/3079300/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
업종명 is highly imbalanced (77.6%)Imbalance
소재지전화 has 2 (2.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 16:29:36.658088
Analysis finished2023-12-12 16:29:37.492697
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size796.0 B
숙박업(일반)
80 
숙박업(생활)
 
3

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) 80
96.4%
숙박업(생활) 3
 
3.6%

Length

2023-12-13T01:29:37.568470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:29:37.675016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업(일반 80
96.4%
숙박업(생활 3
 
3.6%

업소명
Text

Distinct80
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-13T01:29:37.961133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length5.2650602
Min length2

Characters and Unicode

Total characters437
Distinct characters139
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)92.8%

Sample

1st row유진여인숙
2nd row귀빈여관
3rd row은하모텔
4th row하림
5th row삼풍
ValueCountFrequency (%)
모텔 10
 
9.4%
호텔 4
 
3.8%
wow 2
 
1.9%
모먼트(h.moment 2
 
1.9%
퀸모텔 2
 
1.9%
여관 2
 
1.9%
와이티티 2
 
1.9%
지티(g.t)모텔 1
 
0.9%
서울모텔 1
 
0.9%
momulda 1
 
0.9%
Other values (79) 79
74.5%
2023-12-13T01:29:38.411567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 46
 
10.5%
모 35
 
8.0%
23
 
5.3%
관 20
 
4.6%
여 20
 
4.6%
호 13
 
3.0%
장 11
 
2.5%
스 8
 
1.8%
) 7
 
1.6%
이 7
 
1.6%
Other values (129) 247
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 336
76.9%
Uppercase Letter 40
 
9.2%
Space Separator 23
 
5.3%
Lowercase Letter 14
 
3.2%
Close Punctuation 7
 
1.6%
Open Punctuation 7
 
1.6%
Decimal Number 7
 
1.6%
Other Punctuation 3
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 46
 
13.7%
모 35
 
10.4%
관 20
 
6.0%
여 20
 
6.0%
호 13
 
3.9%
장 11
 
3.3%
스 8
 
2.4%
이 7
 
2.1%
하 7
 
2.1%
라 6
 
1.8%
Other values (96) 163
48.5%
Uppercase Letter
ValueCountFrequency (%)
W 5
12.5%
O 5
12.5%
E 5
12.5%
A 4
10.0%
L 4
10.0%
M 3
7.5%
T 3
7.5%
H 2
 
5.0%
J 2
 
5.0%
U 1
 
2.5%
Other values (6) 6
15.0%
Decimal Number
ValueCountFrequency (%)
7 1
14.3%
3 1
14.3%
5 1
14.3%
2 1
14.3%
8 1
14.3%
9 1
14.3%
6 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
m 4
28.6%
e 2
14.3%
n 2
14.3%
h 2
14.3%
t 2
14.3%
o 2
14.3%
Space Separator
ValueCountFrequency (%)
23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 335
76.7%
Latin 54
 
12.4%
Common 47
 
10.8%
Han 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 46
 
13.7%
모 35
 
10.4%
관 20
 
6.0%
여 20
 
6.0%
호 13
 
3.9%
장 11
 
3.3%
스 8
 
2.4%
이 7
 
2.1%
하 7
 
2.1%
라 6
 
1.8%
Other values (95) 162
48.4%
Latin
ValueCountFrequency (%)
W 5
 
9.3%
O 5
 
9.3%
E 5
 
9.3%
A 4
 
7.4%
m 4
 
7.4%
L 4
 
7.4%
M 3
 
5.6%
T 3
 
5.6%
H 2
 
3.7%
e 2
 
3.7%
Other values (12) 17
31.5%
Common
ValueCountFrequency (%)
23
48.9%
) 7
 
14.9%
( 7
 
14.9%
. 3
 
6.4%
7 1
 
2.1%
3 1
 
2.1%
5 1
 
2.1%
2 1
 
2.1%
8 1
 
2.1%
9 1
 
2.1%
Han
ValueCountFrequency (%)
美 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 335
76.7%
ASCII 101
 
23.1%
CJK 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 46
 
13.7%
모 35
 
10.4%
관 20
 
6.0%
여 20
 
6.0%
호 13
 
3.9%
장 11
 
3.3%
스 8
 
2.4%
이 7
 
2.1%
하 7
 
2.1%
라 6
 
1.8%
Other values (95) 162
48.4%
ASCII
ValueCountFrequency (%)
23
22.8%
) 7
 
6.9%
( 7
 
6.9%
W 5
 
5.0%
O 5
 
5.0%
E 5
 
5.0%
A 4
 
4.0%
m 4
 
4.0%
L 4
 
4.0%
M 3
 
3.0%
Other values (23) 34
33.7%
CJK
ValueCountFrequency (%)
美 1
100.0%

업소소재지(도로명)
Text

Distinct82
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-13T01:29:38.787064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length37
Mean length27.578313
Min length22

Characters and Unicode

Total characters2289
Distinct characters63
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

Unique81 ?
Unique (%)97.6%

Sample

1st row부산광역시 사하구 낙동대로 210-1 (괴정동)
2nd row부산광역시 사하구 원양로 407-5 (감천동)
3rd row부산광역시 사하구 낙동대로 210-5 (괴정동)
4th row부산광역시 사하구 낙동대로327번길 2-3 (괴정동)
5th row부산광역시 사하구 원양로 390-3 (감천동)
ValueCountFrequency (%)
부산광역시 83
19.7%
사하구 83
19.7%
하단동 29
 
6.9%
괴정동 21
 
5.0%
하신번영로300번길 11
 
2.6%
다대동 11
 
2.6%
감천동 9
 
2.1%
장림동 7
 
1.7%
낙동남로1423번길 7
 
1.7%
다대로 6
 
1.4%
Other values (112) 155
36.7%
2023-12-13T01:29:39.244265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
339
 
14.8%
하 129
 
5.6%
동 125
 
5.5%
사 88
 
3.8%
광 84
 
3.7%
구 84
 
3.7%
부 83
 
3.6%
역 83
 
3.6%
시 83
 
3.6%
) 83
 
3.6%
Other values (53) 1108
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1359
59.4%
Decimal Number 387
 
16.9%
Space Separator 339
 
14.8%
Close Punctuation 83
 
3.6%
Open Punctuation 83
 
3.6%
Dash Punctuation 30
 
1.3%
Other Punctuation 7
 
0.3%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
하 129
 
9.5%
동 125
 
9.2%
사 88
 
6.5%
광 84
 
6.2%
구 84
 
6.2%
부 83
 
6.1%
역 83
 
6.1%
시 83
 
6.1%
로 83
 
6.1%
산 83
 
6.1%
Other values (37) 434
31.9%
Decimal Number
ValueCountFrequency (%)
1 72
18.6%
0 65
16.8%
3 57
14.7%
2 56
14.5%
4 34
8.8%
5 34
8.8%
7 25
 
6.5%
9 19
 
4.9%
6 13
 
3.4%
8 12
 
3.1%
Space Separator
ValueCountFrequency (%)
339
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%
Open Punctuation
ValueCountFrequency (%)
( 83
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1359
59.4%
Common 929
40.6%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
하 129
 
9.5%
동 125
 
9.2%
사 88
 
6.5%
광 84
 
6.2%
구 84
 
6.2%
부 83
 
6.1%
역 83
 
6.1%
시 83
 
6.1%
로 83
 
6.1%
산 83
 
6.1%
Other values (37) 434
31.9%
Common
ValueCountFrequency (%)
339
36.5%
) 83
 
8.9%
( 83
 
8.9%
1 72
 
7.8%
0 65
 
7.0%
3 57
 
6.1%
2 56
 
6.0%
4 34
 
3.7%
5 34
 
3.7%
- 30
 
3.2%
Other values (5) 76
 
8.2%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1359
59.4%
ASCII 930
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
339
36.5%
) 83
 
8.9%
( 83
 
8.9%
1 72
 
7.7%
0 65
 
7.0%
3 57
 
6.1%
2 56
 
6.0%
4 34
 
3.7%
5 34
 
3.7%
- 30
 
3.2%
Other values (6) 77
 
8.3%
Hangul
ValueCountFrequency (%)
하 129
 
9.5%
동 125
 
9.2%
사 88
 
6.5%
광 84
 
6.2%
구 84
 
6.2%
부 83
 
6.1%
역 83
 
6.1%
시 83
 
6.1%
로 83
 
6.1%
산 83
 
6.1%
Other values (37) 434
31.9%

소재지전화
Text

MISSING 

Distinct77
Distinct (%)95.1%
Missing2
Missing (%)2.4%
Memory size796.0 B
2023-12-13T01:29:39.535617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters972
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

Unique73 ?
Unique (%)90.1%

Sample

1st row051-291-5195
2nd row051-206-5050
3rd row051-201-5379
4th row051-206-9389
5th row051-291-3236
ValueCountFrequency (%)
051-205-2560 2
 
2.5%
051-203-1188 2
 
2.5%
051-207-1408 2
 
2.5%
051-202-2841 2
 
2.5%
051-207-7868 1
 
1.2%
051-208-1035 1
 
1.2%
051-266-0837 1
 
1.2%
051-202-0778 1
 
1.2%
051-203-8591 1
 
1.2%
051-293-8444 1
 
1.2%
Other values (67) 67
82.7%
2023-12-13T01:29:39.954515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 169
17.4%
- 162
16.7%
1 149
15.3%
5 120
12.3%
2 118
12.1%
3 62
 
6.4%
8 48
 
4.9%
9 46
 
4.7%
6 40
 
4.1%
4 33
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 810
83.3%
Dash Punctuation 162
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 169
20.9%
1 149
18.4%
5 120
14.8%
2 118
14.6%
3 62
 
7.7%
8 48
 
5.9%
9 46
 
5.7%
6 40
 
4.9%
4 33
 
4.1%
7 25
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 972
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 169
17.4%
- 162
16.7%
1 149
15.3%
5 120
12.3%
2 118
12.1%
3 62
 
6.4%
8 48
 
4.9%
9 46
 
4.7%
6 40
 
4.1%
4 33
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 972
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 169
17.4%
- 162
16.7%
1 149
15.3%
5 120
12.3%
2 118
12.1%
3 62
 
6.4%
8 48
 
4.9%
9 46
 
4.7%
6 40
 
4.1%
4 33
 
3.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
Minimum2023-05-10 00:00:00
Maximum2023-05-10 00:00:00
2023-12-13T01:29:40.077996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:29:40.180903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T01:29:40.247203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업소명업소소재지(도로명)소재지전화
업종명1.0000.0001.0000.000
업소명0.0001.0000.9961.000
업소소재지(도로명)1.0000.9961.0000.995
소재지전화0.0001.0000.9951.000

Missing values

2023-12-13T01:29:37.350424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:29:37.457456image/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

업종명업소명업소소재지(도로명)소재지전화데이터기준일자
0숙박업(일반)유진여인숙부산광역시 사하구 낙동대로 210-1 (괴정동)051-291-51952023-05-10
1숙박업(일반)귀빈여관부산광역시 사하구 원양로 407-5 (감천동)051-206-50502023-05-10
2숙박업(일반)은하모텔부산광역시 사하구 낙동대로 210-5 (괴정동)051-201-53792023-05-10
3숙박업(일반)하림부산광역시 사하구 낙동대로327번길 2-3 (괴정동)051-206-93892023-05-10
4숙박업(일반)삼풍부산광역시 사하구 원양로 390-3 (감천동)051-291-32362023-05-10
5숙박업(일반)대창부산광역시 사하구 원양로398번길 11 (감천동)<NA>2023-05-10
6숙박업(일반)문화여관부산광역시 사하구 다대로130번길 118 (신평동)051-203-28512023-05-10
7숙박업(일반)수도여관부산광역시 사하구 장림번영로 46-2 (장림동)051-264-45052023-05-10
8숙박업(일반)동진여관부산광역시 사하구 장림번영로37번길 15 (장림동)051-263-43272023-05-10
9숙박업(일반)연희장여관부산광역시 사하구 감천로 138 (감천동)051-291-85912023-05-10
업종명업소명업소소재지(도로명)소재지전화데이터기준일자
73숙박업(일반)로쏘호텔부산광역시 사하구 낙동대로216번길 2 (괴정동)051-203-36362023-05-10
74숙박업(일반)모텔 와이티티 별관부산광역시 사하구 하신번영로300번길 100-9 (하단동)051-202-73412023-05-10
75숙박업(일반)K 모텔부산광역시 사하구 낙동남로1405번길 27 (하단동)051-207-33382023-05-10
76숙박업(일반)휴 모텔부산광역시 사하구 낙동대로224번길 1-2 (괴정동)051-208-00932023-05-10
77숙박업(일반)브라운도트호텔(하단점)부산광역시 사하구 낙동남로1423번길 47, 브라운도트관광호텔 (하단동)051-201-39942023-05-10
78숙박업(일반)레이어스호텔부산광역시 사하구 낙동남로 1395, 레이어스호텔 (하단동)051-999-17322023-05-10
79숙박업(일반)하운드호텔(하단)부산광역시 사하구 낙동남로1405번길 17-1, 하운드호텔 (하단동)051-208-02452023-05-10
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