Overview

Dataset statistics

Number of variables5
Number of observations126
Missing cells31
Missing cells (%)4.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory41.0 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description경상북도 영덕군에 위치한 숙박시설 업종명, 업소명, 영업소주소, 전화번호 등 관련 정보를 아래와 같이 제공하고자 합니다.
URLhttps://www.data.go.kr/data/15090271/fileData.do

Alerts

데이터기준일 has constant value ""Constant
소재지전화 has 31 (24.6%) missing valuesMissing

Reproduction

Analysis started2023-12-12 13:31:53.058918
Analysis finished2023-12-12 13:31:53.456492
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
숙박업(일반)
70 
숙박업(생활)
56 

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) 70
55.6%
숙박업(생활) 56
44.4%

Length

2023-12-12T22:31:53.528860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:31:53.670705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업(일반 70
55.6%
숙박업(생활 56
44.4%

업소명
Text

Distinct124
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T22:31:53.962918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length18
Mean length6.5
Min length2

Characters and Unicode

Total characters819
Distinct characters210
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

Unique122 ?
Unique (%)96.8%

Sample

1st row경주여인숙
2nd row대성모텔
3rd row삼삼여인숙
4th row명성장여관
5th row호텔얌 영덕강구터미널점
ValueCountFrequency (%)
펜션 7
 
4.1%
모텔 4
 
2.4%
풀빌라 3
 
1.8%
호텔 3
 
1.8%
유성모텔 2
 
1.2%
영덕 2
 
1.2%
오션뷰 2
 
1.2%
산호장여관 2
 
1.2%
pool 1
 
0.6%
k모텔 1
 
0.6%
Other values (142) 142
84.0%
2023-12-12T22:31:54.443768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 57
 
7.0%
모 46
 
5.6%
43
 
5.3%
션 36
 
4.4%
펜 27
 
3.3%
리 16
 
2.0%
영 14
 
1.7%
호 14
 
1.7%
스 14
 
1.7%
여 13
 
1.6%
Other values (200) 539
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 690
84.2%
Uppercase Letter 49
 
6.0%
Space Separator 43
 
5.3%
Decimal Number 10
 
1.2%
Close Punctuation 9
 
1.1%
Open Punctuation 9
 
1.1%
Lowercase Letter 5
 
0.6%
Other Punctuation 2
 
0.2%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 57
 
8.3%
모 46
 
6.7%
션 36
 
5.2%
펜 27
 
3.9%
리 16
 
2.3%
영 14
 
2.0%
호 14
 
2.0%
스 14
 
2.0%
여 13
 
1.9%
이 12
 
1.7%
Other values (166) 441
63.9%
Uppercase Letter
ValueCountFrequency (%)
I 6
12.2%
E 6
12.2%
L 5
10.2%
V 4
 
8.2%
O 3
 
6.1%
H 3
 
6.1%
T 3
 
6.1%
M 3
 
6.1%
W 2
 
4.1%
R 2
 
4.1%
Other values (9) 12
24.5%
Decimal Number
ValueCountFrequency (%)
1 3
30.0%
2 3
30.0%
4 1
 
10.0%
3 1
 
10.0%
7 1
 
10.0%
0 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
i 2
40.0%
n 1
20.0%
e 1
20.0%
m 1
20.0%
Space Separator
ValueCountFrequency (%)
43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 690
84.2%
Common 75
 
9.2%
Latin 54
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 57
 
8.3%
모 46
 
6.7%
션 36
 
5.2%
펜 27
 
3.9%
리 16
 
2.3%
영 14
 
2.0%
호 14
 
2.0%
스 14
 
2.0%
여 13
 
1.9%
이 12
 
1.7%
Other values (166) 441
63.9%
Latin
ValueCountFrequency (%)
I 6
 
11.1%
E 6
 
11.1%
L 5
 
9.3%
V 4
 
7.4%
O 3
 
5.6%
H 3
 
5.6%
T 3
 
5.6%
M 3
 
5.6%
W 2
 
3.7%
R 2
 
3.7%
Other values (13) 17
31.5%
Common
ValueCountFrequency (%)
43
57.3%
) 9
 
12.0%
( 9
 
12.0%
1 3
 
4.0%
2 3
 
4.0%
& 2
 
2.7%
- 2
 
2.7%
4 1
 
1.3%
3 1
 
1.3%
7 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 690
84.2%
ASCII 129
 
15.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 57
 
8.3%
모 46
 
6.7%
션 36
 
5.2%
펜 27
 
3.9%
리 16
 
2.3%
영 14
 
2.0%
호 14
 
2.0%
스 14
 
2.0%
여 13
 
1.9%
이 12
 
1.7%
Other values (166) 441
63.9%
ASCII
ValueCountFrequency (%)
43
33.3%
) 9
 
7.0%
( 9
 
7.0%
I 6
 
4.7%
E 6
 
4.7%
L 5
 
3.9%
V 4
 
3.1%
1 3
 
2.3%
O 3
 
2.3%
H 3
 
2.3%
Other values (24) 38
29.5%

영업소 주소(도로명)
Text

Distinct125
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T22:31:54.680948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length22.650794
Min length18

Characters and Unicode

Total characters2854
Distinct characters93
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)98.4%

Sample

1st row경상북도 영덕군 영덕읍 남석1길 6
2nd row경상북도 영덕군 영해면 318만세길 170
3rd row경상북도 영덕군 강구면 강구대게3길 10-1
4th row경상북도 영덕군 영해면 예주2길 41-6
5th row경상북도 영덕군 강구면 동해대로 4497
ValueCountFrequency (%)
경상북도 126
19.4%
영덕군 126
19.4%
강구면 46
 
7.1%
동해대로 27
 
4.2%
영덕대게로 26
 
4.0%
남정면 24
 
3.7%
영덕읍 18
 
2.8%
병곡면 17
 
2.6%
영해면 13
 
2.0%
병곡1길 9
 
1.4%
Other values (163) 216
33.3%
2023-12-12T22:31:55.052427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
522
18.3%
영 192
 
6.7%
덕 178
 
6.2%
상 133
 
4.7%
군 127
 
4.4%
경 126
 
4.4%
북 126
 
4.4%
도 126
 
4.4%
면 108
 
3.8%
1 107
 
3.7%
Other values (83) 1109
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1808
63.3%
Space Separator 522
 
18.3%
Decimal Number 454
 
15.9%
Dash Punctuation 35
 
1.2%
Other Punctuation 23
 
0.8%
Math Symbol 8
 
0.3%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 192
 
10.6%
덕 178
 
9.8%
상 133
 
7.4%
군 127
 
7.0%
경 126
 
7.0%
북 126
 
7.0%
도 126
 
7.0%
면 108
 
6.0%
로 68
 
3.8%
길 58
 
3.2%
Other values (65) 566
31.3%
Decimal Number
ValueCountFrequency (%)
1 107
23.6%
4 56
12.3%
3 54
11.9%
2 49
10.8%
5 42
 
9.3%
6 41
 
9.0%
0 33
 
7.3%
7 27
 
5.9%
8 23
 
5.1%
9 22
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 1
25.0%
A 1
25.0%
C 1
25.0%
E 1
25.0%
Space Separator
ValueCountFrequency (%)
522
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Other Punctuation
ValueCountFrequency (%)
, 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1808
63.3%
Common 1042
36.5%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 192
 
10.6%
덕 178
 
9.8%
상 133
 
7.4%
군 127
 
7.0%
경 126
 
7.0%
북 126
 
7.0%
도 126
 
7.0%
면 108
 
6.0%
로 68
 
3.8%
길 58
 
3.2%
Other values (65) 566
31.3%
Common
ValueCountFrequency (%)
522
50.1%
1 107
 
10.3%
4 56
 
5.4%
3 54
 
5.2%
2 49
 
4.7%
5 42
 
4.0%
6 41
 
3.9%
- 35
 
3.4%
0 33
 
3.2%
7 27
 
2.6%
Other values (4) 76
 
7.3%
Latin
ValueCountFrequency (%)
B 1
25.0%
A 1
25.0%
C 1
25.0%
E 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1808
63.3%
ASCII 1046
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
522
49.9%
1 107
 
10.2%
4 56
 
5.4%
3 54
 
5.2%
2 49
 
4.7%
5 42
 
4.0%
6 41
 
3.9%
- 35
 
3.3%
0 33
 
3.2%
7 27
 
2.6%
Other values (8) 80
 
7.6%
Hangul
ValueCountFrequency (%)
영 192
 
10.6%
덕 178
 
9.8%
상 133
 
7.4%
군 127
 
7.0%
경 126
 
7.0%
북 126
 
7.0%
도 126
 
7.0%
면 108
 
6.0%
로 68
 
3.8%
길 58
 
3.2%
Other values (65) 566
31.3%

소재지전화
Text

MISSING 

Distinct94
Distinct (%)98.9%
Missing31
Missing (%)24.6%
Memory size1.1 KiB
2023-12-12T22:31:55.308525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1140
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

Unique93 ?
Unique (%)97.9%

Sample

1st row054-734-2294
2nd row054-733-4608
3rd row054-734-5663
4th row054-733-4512
5th row054-733-0609
ValueCountFrequency (%)
054-734-8550 2
 
2.1%
054-733-6669 1
 
1.1%
054-734-1957 1
 
1.1%
054-733-7080 1
 
1.1%
054-734-1986 1
 
1.1%
054-734-3410 1
 
1.1%
054-732-8080 1
 
1.1%
054-732-7751 1
 
1.1%
054-730-6298 1
 
1.1%
054-733-3345 1
 
1.1%
Other values (84) 84
88.4%
2023-12-12T22:31:55.647685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 190
16.7%
3 177
15.5%
0 156
13.7%
4 147
12.9%
5 137
12.0%
7 134
11.8%
1 46
 
4.0%
2 46
 
4.0%
9 40
 
3.5%
8 35
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 950
83.3%
Dash Punctuation 190
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 177
18.6%
0 156
16.4%
4 147
15.5%
5 137
14.4%
7 134
14.1%
1 46
 
4.8%
2 46
 
4.8%
9 40
 
4.2%
8 35
 
3.7%
6 32
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1140
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 190
16.7%
3 177
15.5%
0 156
13.7%
4 147
12.9%
5 137
12.0%
7 134
11.8%
1 46
 
4.0%
2 46
 
4.0%
9 40
 
3.5%
8 35
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 190
16.7%
3 177
15.5%
0 156
13.7%
4 147
12.9%
5 137
12.0%
7 134
11.8%
1 46
 
4.0%
2 46
 
4.0%
9 40
 
3.5%
8 35
 
3.1%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2023-08-29 00:00:00
Maximum2023-08-29 00:00:00
2023-12-12T22:31:55.754627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:31:55.830548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T22:31:55.884994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명소재지전화
업종명1.0000.000
소재지전화0.0001.000

Missing values

2023-12-12T22:31:53.331411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:31:53.419013image/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

업종명업소명영업소 주소(도로명)소재지전화데이터기준일
0숙박업(일반)경주여인숙경상북도 영덕군 영덕읍 남석1길 6054-734-22942023-08-29
1숙박업(일반)대성모텔경상북도 영덕군 영해면 318만세길 170<NA>2023-08-29
2숙박업(일반)삼삼여인숙경상북도 영덕군 강구면 강구대게3길 10-1054-733-46082023-08-29
3숙박업(일반)명성장여관경상북도 영덕군 영해면 예주2길 41-6054-734-56632023-08-29
4숙박업(일반)호텔얌 영덕강구터미널점경상북도 영덕군 강구면 동해대로 4497054-733-45122023-08-29
5숙박업(일반)대구여관경상북도 영덕군 남정면 진불1길 5054-733-06092023-08-29
6숙박업(일반)수도장모텔경상북도 영덕군 축산면 축산항길 16-1054-732-45752023-08-29
7숙박업(일반)카프리모텔경상북도 영덕군 영해면 예주2길 42-6054-732-02512023-08-29
8숙박업(일반)대화모텔경상북도 영덕군 영덕읍 군청길 57054-732-99882023-08-29
9숙박업(일반)오성모텔경상북도 영덕군 영해면 예주시장2길 16-3054-732-12912023-08-29
업종명업소명영업소 주소(도로명)소재지전화데이터기준일
116숙박업(생활)하프문베이경상북도 영덕군 남정면 구계길 6<NA>2023-08-29
117숙박업(생활)리브포레스트 풀빌라경상북도 영덕군 영덕읍 영덕대게로 625-284, 가~마동<NA>2023-08-29
118숙박업(생활)일화수펜션경상북도 영덕군 강구면 영덕대게로 563, 일화수펜션054-732-88832023-08-29
119숙박업(생활)스페이스 영덕경상북도 영덕군 영덕읍 영덕대게로 587<NA>2023-08-29
120숙박업(생활)포쉬 풀빌라경상북도 영덕군 강구면 영덕대게로 523<NA>2023-08-29
121숙박업(생활)DELIGHT 107 POOL VILLA경상북도 영덕군 강구면 영덕대게로 509-9<NA>2023-08-29
122숙박업(생활)가고파펜션경상북도 영덕군 영덕읍 영덕대게로 1340-23<NA>2023-08-29
123숙박업(생활)물마루경상북도 영덕군 남정면 동해대로 4114<NA>2023-08-29
124숙박업(생활)영펜션앤모텔2동경상북도 영덕군 남정면 동해대로 3443-16<NA>2023-08-29
125숙박업(생활)영펜션앤모텔1동경상북도 영덕군 남정면 동해대로 3443-17<NA>2023-08-29