Overview

Dataset statistics

Number of variables13
Number of observations94
Missing cells25
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.0 KiB
Average record size in memory108.4 B

Variable types

Text4
Categorical4
DateTime1
Boolean1
Numeric3

Dataset

Description대구광역시 북구 관광지주변 숙박업소 현황에 대한 데이터로 점포명, 서비스명, 전화번호, 주소 등의 데이터를 제공합니다.
Author대구광역시 북구
URLhttps://www.data.go.kr/data/15095877/fileData.do

Alerts

업종분류 has constant value ""Constant
서비스명 has constant value ""Constant
서비스아이디(ID) has constant value ""Constant
도로명우편번호 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 구우편번호High correlation
위도 is highly overall correlated with 도로명우편번호 and 1 other fieldsHigh correlation
영업상태 is highly overall correlated with 구우편번호High correlation
구우편번호 is highly overall correlated with 도로명우편번호 and 3 other fieldsHigh correlation
영업상태 is highly imbalanced (91.5%)Imbalance
소재지전화 has 25 (26.6%) missing valuesMissing
주소 has unique valuesUnique
도로명주소 has unique valuesUnique
경도 has unique valuesUnique
위도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:11:23.296444
Analysis finished2023-12-12 14:11:25.469642
Duration2.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct90
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-12T23:11:25.690947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length11
Mean length4.7553191
Min length1

Characters and Unicode

Total characters447
Distinct characters152
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

Unique88 ?
Unique (%)93.6%

Sample

1st row발리모텔
2nd row콜모텔
3rd row와와모텔
4th row로즈모텔
5th row아테네모텔
ValueCountFrequency (%)
스위트호텔 4
 
4.0%
호텔 2
 
2.0%
럭셔리모텔 2
 
2.0%
인카모텔 1
 
1.0%
휴 1
 
1.0%
지(g)모텔 1
 
1.0%
더존모텔 1
 
1.0%
컨벤션비지니스호텔 1
 
1.0%
대구여인숙 1
 
1.0%
린시아 1
 
1.0%
Other values (84) 84
84.8%
2023-12-12T23:11:26.136489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 64
 
14.3%
모 48
 
10.7%
호 18
 
4.0%
스 13
 
2.9%
리 12
 
2.7%
여 10
 
2.2%
아 9
 
2.0%
장 8
 
1.8%
인 8
 
1.8%
대 7
 
1.6%
Other values (142) 250
55.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 403
90.2%
Uppercase Letter 10
 
2.2%
Close Punctuation 7
 
1.6%
Open Punctuation 7
 
1.6%
Decimal Number 7
 
1.6%
Lowercase Letter 6
 
1.3%
Space Separator 5
 
1.1%
Dash Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 64
 
15.9%
모 48
 
11.9%
호 18
 
4.5%
스 13
 
3.2%
리 12
 
3.0%
여 10
 
2.5%
아 9
 
2.2%
장 8
 
2.0%
인 8
 
2.0%
대 7
 
1.7%
Other values (120) 206
51.1%
Uppercase Letter
ValueCountFrequency (%)
G 2
20.0%
A 2
20.0%
H 1
10.0%
K 1
10.0%
T 1
10.0%
C 1
10.0%
V 1
10.0%
S 1
10.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
33.3%
l 1
16.7%
t 1
16.7%
o 1
16.7%
h 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
2 2
28.6%
4 1
 
14.3%
0 1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 403
90.2%
Common 28
 
6.3%
Latin 16
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 64
 
15.9%
모 48
 
11.9%
호 18
 
4.5%
스 13
 
3.2%
리 12
 
3.0%
여 10
 
2.5%
아 9
 
2.2%
장 8
 
2.0%
인 8
 
2.0%
대 7
 
1.7%
Other values (120) 206
51.1%
Latin
ValueCountFrequency (%)
G 2
12.5%
A 2
12.5%
e 2
12.5%
l 1
 
6.2%
t 1
 
6.2%
o 1
 
6.2%
H 1
 
6.2%
K 1
 
6.2%
h 1
 
6.2%
T 1
 
6.2%
Other values (3) 3
18.8%
Common
ValueCountFrequency (%)
) 7
25.0%
( 7
25.0%
5
17.9%
1 3
10.7%
2 2
 
7.1%
- 1
 
3.6%
. 1
 
3.6%
4 1
 
3.6%
0 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 403
90.2%
ASCII 44
 
9.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 64
 
15.9%
모 48
 
11.9%
호 18
 
4.5%
스 13
 
3.2%
리 12
 
3.0%
여 10
 
2.5%
아 9
 
2.2%
장 8
 
2.0%
인 8
 
2.0%
대 7
 
1.7%
Other values (120) 206
51.1%
ASCII
ValueCountFrequency (%)
) 7
15.9%
( 7
15.9%
5
11.4%
1 3
 
6.8%
2 2
 
4.5%
G 2
 
4.5%
A 2
 
4.5%
e 2
 
4.5%
l 1
 
2.3%
t 1
 
2.3%
Other values (12) 12
27.3%

업종분류
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
숙소
94 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숙소
2nd row숙소
3rd row숙소
4th row숙소
5th row숙소

Common Values

ValueCountFrequency (%)
숙소 94
100.0%

Length

2023-12-12T23:11:26.277391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:11:26.366396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙소 94
100.0%

서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
숙박업
94 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숙박업
2nd row숙박업
3rd row숙박업
4th row숙박업
5th row숙박업

Common Values

ValueCountFrequency (%)
숙박업 94
100.0%

Length

2023-12-12T23:11:26.454350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:11:26.569807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업 94
100.0%

서비스아이디(ID)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
03_11_03_P
94 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03_11_03_P
2nd row03_11_03_P
3rd row03_11_03_P
4th row03_11_03_P
5th row03_11_03_P

Common Values

ValueCountFrequency (%)
03_11_03_P 94
100.0%

Length

2023-12-12T23:11:26.683832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:11:26.811203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 94
100.0%

인허가일자
Date

Distinct77
Distinct (%)81.9%
Missing0
Missing (%)0.0%
Memory size884.0 B
Minimum1989-08-07 00:00:00
Maximum2020-08-24 00:00:00
2023-12-12T23:11:27.041775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:11:27.220828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size226.0 B
True
93 
False
 
1
ValueCountFrequency (%)
True 93
98.9%
False 1
 
1.1%
2023-12-12T23:11:27.367660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

소재지전화
Text

MISSING 

Distinct69
Distinct (%)100.0%
Missing25
Missing (%)26.6%
Memory size884.0 B
2023-12-12T23:11:27.594492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.101449
Min length12

Characters and Unicode

Total characters835
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

Unique69 ?
Unique (%)100.0%

Sample

1st row053-423-5006
2nd row053-956-6666
3rd row053-956-5525
4th row053-953-8855
5th row053-326-1733
ValueCountFrequency (%)
053-424-6367 1
 
1.4%
053-324-5657 1
 
1.4%
053-325-2077 1
 
1.4%
0507-1443-7151 1
 
1.4%
053-955-0644 1
 
1.4%
053-352-5359 1
 
1.4%
053-352-1109 1
 
1.4%
053-422-7124 1
 
1.4%
053-954-7910 1
 
1.4%
053-311-1003 1
 
1.4%
Other values (59) 59
85.5%
2023-12-12T23:11:28.047374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 145
17.4%
3 139
16.6%
- 138
16.5%
0 134
16.0%
9 51
 
6.1%
1 51
 
6.1%
2 41
 
4.9%
7 39
 
4.7%
6 38
 
4.6%
4 36
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 697
83.5%
Dash Punctuation 138
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 145
20.8%
3 139
19.9%
0 134
19.2%
9 51
 
7.3%
1 51
 
7.3%
2 41
 
5.9%
7 39
 
5.6%
6 38
 
5.5%
4 36
 
5.2%
8 23
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 835
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 145
17.4%
3 139
16.6%
- 138
16.5%
0 134
16.0%
9 51
 
6.1%
1 51
 
6.1%
2 41
 
4.9%
7 39
 
4.7%
6 38
 
4.6%
4 36
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 835
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 145
17.4%
3 139
16.6%
- 138
16.5%
0 134
16.0%
9 51
 
6.1%
1 51
 
6.1%
2 41
 
4.9%
7 39
 
4.7%
6 38
 
4.6%
4 36
 
4.3%

구우편번호
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)27.7%
Missing0
Missing (%)0.0%
Memory size884.0 B
702-831
10 
702-040
9 
702-886
7 
702-852
6 
702-865
6 
Other values (21)
56 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique8 ?
Unique (%)8.5%

Sample

1st row702-852
2nd row702-832
3rd row702-831
4th row702-839
5th row702-886

Common Values

ValueCountFrequency (%)
702-831 10
 
10.6%
702-040 9
 
9.6%
702-886 7
 
7.4%
702-852 6
 
6.4%
702-865 6
 
6.4%
702-845 5
 
5.3%
702-803 5
 
5.3%
702-812 5
 
5.3%
702-885 5
 
5.3%
702-061 4
 
4.3%
Other values (16) 32
34.0%

Length

2023-12-12T23:11:28.216049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
702-831 10
 
10.6%
702-040 9
 
9.6%
702-886 7
 
7.4%
702-852 6
 
6.4%
702-865 6
 
6.4%
702-845 5
 
5.3%
702-803 5
 
5.3%
702-812 5
 
5.3%
702-885 5
 
5.3%
702-061 4
 
4.3%
Other values (16) 32
34.0%

주소
Text

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-12T23:11:28.526116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length21.212766
Min length17

Characters and Unicode

Total characters1994
Distinct characters44
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)100.0%

Sample

1st row대구광역시 북구 칠성동2가 302-311번지
2nd row대구광역시 북구 복현동 472-8번지
3rd row대구광역시 북구 복현동 402-8번지
4th row대구광역시 북구 산격동 1449-9번지
5th row대구광역시 북구 동천동 911-2번지
ValueCountFrequency (%)
대구광역시 94
25.0%
북구 94
25.0%
복현동 14
 
3.7%
산격동 12
 
3.2%
동천동 12
 
3.2%
대현동 9
 
2.4%
태전동 8
 
2.1%
칠성동2가 7
 
1.9%
노원동3가 5
 
1.3%
노원동2가 5
 
1.3%
Other values (103) 116
30.9%
2023-12-12T23:11:28.989999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
376
18.9%
구 188
 
9.4%
동 106
 
5.3%
대 103
 
5.2%
광 94
 
4.7%
역 94
 
4.7%
시 94
 
4.7%
북 94
 
4.7%
1 92
 
4.6%
- 82
 
4.1%
Other values (34) 671
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1108
55.6%
Decimal Number 428
 
21.5%
Space Separator 376
 
18.9%
Dash Punctuation 82
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 188
17.0%
동 106
9.6%
대 103
9.3%
광 94
8.5%
역 94
8.5%
시 94
8.5%
북 94
8.5%
번 71
 
6.4%
지 71
 
6.4%
가 26
 
2.3%
Other values (22) 167
15.1%
Decimal Number
ValueCountFrequency (%)
1 92
21.5%
2 62
14.5%
4 54
12.6%
3 46
10.7%
7 37
8.6%
8 35
 
8.2%
9 32
 
7.5%
0 28
 
6.5%
5 23
 
5.4%
6 19
 
4.4%
Space Separator
ValueCountFrequency (%)
376
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1108
55.6%
Common 886
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 188
17.0%
동 106
9.6%
대 103
9.3%
광 94
8.5%
역 94
8.5%
시 94
8.5%
북 94
8.5%
번 71
 
6.4%
지 71
 
6.4%
가 26
 
2.3%
Other values (22) 167
15.1%
Common
ValueCountFrequency (%)
376
42.4%
1 92
 
10.4%
- 82
 
9.3%
2 62
 
7.0%
4 54
 
6.1%
3 46
 
5.2%
7 37
 
4.2%
8 35
 
4.0%
9 32
 
3.6%
0 28
 
3.2%
Other values (2) 42
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1108
55.6%
ASCII 886
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
376
42.4%
1 92
 
10.4%
- 82
 
9.3%
2 62
 
7.0%
4 54
 
6.1%
3 46
 
5.2%
7 37
 
4.2%
8 35
 
4.0%
9 32
 
3.6%
0 28
 
3.2%
Other values (2) 42
 
4.7%
Hangul
ValueCountFrequency (%)
구 188
17.0%
동 106
9.6%
대 103
9.3%
광 94
8.5%
역 94
8.5%
시 94
8.5%
북 94
8.5%
번 71
 
6.4%
지 71
 
6.4%
가 26
 
2.3%
Other values (22) 167
15.1%

도로명우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41527.298
Minimum41422
Maximum41598
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-12T23:11:29.129980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41422
5-th percentile41423
Q141468
median41557
Q341571.75
95-th percentile41594
Maximum41598
Range176
Interquartile range (IQR)103.75

Descriptive statistics

Standard deviation58.971075
Coefficient of variation (CV)0.0014200557
Kurtosis-1.0317947
Mean41527.298
Median Absolute Deviation (MAD)24
Skewness-0.72844105
Sum3903566
Variance3477.5877
MonotonicityNot monotonic
2023-12-12T23:11:29.261755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
41562 9
 
9.6%
41423 9
 
9.6%
41581 6
 
6.4%
41558 5
 
5.3%
41447 5
 
5.3%
41468 5
 
5.3%
41557 5
 
5.3%
41572 5
 
5.3%
41564 4
 
4.3%
41598 4
 
4.3%
Other values (23) 37
39.4%
ValueCountFrequency (%)
41422 3
 
3.2%
41423 9
9.6%
41438 1
 
1.1%
41447 5
5.3%
41451 2
 
2.1%
41467 1
 
1.1%
41468 5
5.3%
41475 1
 
1.1%
41488 1
 
1.1%
41505 3
 
3.2%
ValueCountFrequency (%)
41598 4
4.3%
41594 3
3.2%
41583 1
 
1.1%
41582 3
3.2%
41581 6
6.4%
41580 1
 
1.1%
41576 1
 
1.1%
41572 5
5.3%
41571 2
 
2.1%
41570 1
 
1.1%

도로명주소
Text

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-12T23:11:29.577149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length24.755319
Min length21

Characters and Unicode

Total characters2327
Distinct characters74
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)100.0%

Sample

1st row대구광역시 북구 칠성남로30길 6-1 (칠성동2가)
2nd row대구광역시 북구 경대로27길 1 (복현동)
3rd row대구광역시 북구 대학로 136 (복현동)
4th row대구광역시 북구 대구체육관로 24 (산격동)
5th row대구광역시 북구 동천로24길 17-13 (동천동)
ValueCountFrequency (%)
대구광역시 94
19.9%
북구 94
19.9%
복현동 14
 
3.0%
산격동 12
 
2.5%
동천동 12
 
2.5%
대현동 9
 
1.9%
대현로 8
 
1.7%
태전동 8
 
1.7%
칠성동2가 7
 
1.5%
동천로 6
 
1.3%
Other values (134) 208
44.1%
2023-12-12T23:11:30.085383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
378
16.2%
구 194
 
8.3%
대 128
 
5.5%
동 124
 
5.3%
1 99
 
4.3%
시 98
 
4.2%
북 96
 
4.1%
( 94
 
4.0%
) 94
 
4.0%
로 94
 
4.0%
Other values (64) 928
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1365
58.7%
Space Separator 378
 
16.2%
Decimal Number 360
 
15.5%
Open Punctuation 94
 
4.0%
Close Punctuation 94
 
4.0%
Dash Punctuation 34
 
1.5%
Other Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 194
14.2%
대 128
 
9.4%
동 124
 
9.1%
시 98
 
7.2%
북 96
 
7.0%
로 94
 
6.9%
역 94
 
6.9%
광 94
 
6.9%
길 51
 
3.7%
현 32
 
2.3%
Other values (48) 360
26.4%
Decimal Number
ValueCountFrequency (%)
1 99
27.5%
2 68
18.9%
3 51
14.2%
8 27
 
7.5%
4 25
 
6.9%
0 25
 
6.9%
7 19
 
5.3%
9 17
 
4.7%
6 15
 
4.2%
5 14
 
3.9%
Space Separator
ValueCountFrequency (%)
378
100.0%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%
Close Punctuation
ValueCountFrequency (%)
) 94
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1365
58.7%
Common 962
41.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 194
14.2%
대 128
 
9.4%
동 124
 
9.1%
시 98
 
7.2%
북 96
 
7.0%
로 94
 
6.9%
역 94
 
6.9%
광 94
 
6.9%
길 51
 
3.7%
현 32
 
2.3%
Other values (48) 360
26.4%
Common
ValueCountFrequency (%)
378
39.3%
1 99
 
10.3%
( 94
 
9.8%
) 94
 
9.8%
2 68
 
7.1%
3 51
 
5.3%
- 34
 
3.5%
8 27
 
2.8%
4 25
 
2.6%
0 25
 
2.6%
Other values (6) 67
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1365
58.7%
ASCII 962
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
378
39.3%
1 99
 
10.3%
( 94
 
9.8%
) 94
 
9.8%
2 68
 
7.1%
3 51
 
5.3%
- 34
 
3.5%
8 27
 
2.8%
4 25
 
2.6%
0 25
 
2.6%
Other values (6) 67
 
7.0%
Hangul
ValueCountFrequency (%)
구 194
14.2%
대 128
 
9.4%
동 124
 
9.1%
시 98
 
7.2%
북 96
 
7.0%
로 94
 
6.9%
역 94
 
6.9%
광 94
 
6.9%
길 51
 
3.7%
현 32
 
2.3%
Other values (48) 360
26.4%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.58256
Minimum128.51751
Maximum128.62143
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-12T23:11:30.281188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.51751
5-th percentile128.54609
Q1128.56149
median128.59188
Q3128.60611
95-th percentile128.61616
Maximum128.62143
Range0.1039131
Interquartile range (IQR)0.044611725

Descriptive statistics

Standard deviation0.028041992
Coefficient of variation (CV)0.00021808551
Kurtosis-0.85374994
Mean128.58256
Median Absolute Deviation (MAD)0.0220432
Skewness-0.48090499
Sum12086.76
Variance0.00078635333
MonotonicityNot monotonic
2023-12-12T23:11:30.438506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.5955736 1
 
1.1%
128.548076 1
 
1.1%
128.5478046 1
 
1.1%
128.5747193 1
 
1.1%
128.6140442 1
 
1.1%
128.6018722 1
 
1.1%
128.6150712 1
 
1.1%
128.5748576 1
 
1.1%
128.5752368 1
 
1.1%
128.6017308 1
 
1.1%
Other values (84) 84
89.4%
ValueCountFrequency (%)
128.5175122 1
1.1%
128.5178626 1
1.1%
128.5186204 1
1.1%
128.5189356 1
1.1%
128.5431271 1
1.1%
128.5476893 1
1.1%
128.5476927 1
1.1%
128.5477193 1
1.1%
128.5477644 1
1.1%
128.5478046 1
1.1%
ValueCountFrequency (%)
128.6214253 1
1.1%
128.6208073 1
1.1%
128.620567 1
1.1%
128.6191781 1
1.1%
128.6161735 1
1.1%
128.616159 1
1.1%
128.6160708 1
1.1%
128.6155274 1
1.1%
128.6150712 1
1.1%
128.6148822 1
1.1%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.902223
Minimum35.875192
Maximum35.943805
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-12T23:11:30.584058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.875192
5-th percentile35.875933
Q135.888052
median35.89494
Q335.914704
95-th percentile35.943321
Maximum35.943805
Range0.06861343
Interquartile range (IQR)0.026652115

Descriptive statistics

Standard deviation0.022074198
Coefficient of variation (CV)0.00061484211
Kurtosis-0.71328964
Mean35.902223
Median Absolute Deviation (MAD)0.011795755
Skewness0.78773325
Sum3374.8089
Variance0.00048727023
MonotonicityNot monotonic
2023-12-12T23:11:31.053620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.87693513 1
 
1.1%
35.93386542 1
 
1.1%
35.93161481 1
 
1.1%
35.8887845 1
 
1.1%
35.90589634 1
 
1.1%
35.87519156 1
 
1.1%
35.8958856 1
 
1.1%
35.88876268 1
 
1.1%
35.88846709 1
 
1.1%
35.87532763 1
 
1.1%
Other values (84) 84
89.4%
ValueCountFrequency (%)
35.87519156 1
1.1%
35.87530081 1
1.1%
35.87532763 1
1.1%
35.87570939 1
1.1%
35.8757791 1
1.1%
35.87601617 1
1.1%
35.87606106 1
1.1%
35.8763486 1
1.1%
35.87693513 1
1.1%
35.87698054 1
1.1%
ValueCountFrequency (%)
35.94380499 1
1.1%
35.94359217 1
1.1%
35.94354457 1
1.1%
35.94349022 1
1.1%
35.94332299 1
1.1%
35.94331962 1
1.1%
35.94331915 1
1.1%
35.94310243 1
1.1%
35.94252324 1
1.1%
35.9422145 1
1.1%

Interactions

2023-12-12T23:11:24.884929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:11:24.216338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:11:24.581476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:11:24.977509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:11:24.342208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:11:24.697834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:11:25.083012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:11:24.459041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:11:24.783611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:11:31.201705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명인허가일자영업상태소재지전화구우편번호주소도로명우편번호도로명주소경도위도
사업장명1.0000.9071.0001.0000.9751.0000.9051.0000.0000.928
인허가일자0.9071.0001.0001.0000.8271.0000.9531.0000.6830.952
영업상태1.0001.0001.0001.0001.0001.0000.0001.0000.3400.000
소재지전화1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
구우편번호0.9750.8271.0001.0001.0001.0000.9861.0000.9860.979
주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명우편번호0.9050.9530.0001.0000.9861.0001.0001.0000.8020.975
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
경도0.0000.6830.3401.0000.9861.0000.8021.0001.0000.801
위도0.9280.9520.0001.0000.9791.0000.9751.0000.8011.000
2023-12-12T23:11:31.358794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태구우편번호
영업상태1.0000.860
구우편번호0.8601.000
2023-12-12T23:11:31.462238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로명우편번호경도위도영업상태구우편번호
도로명우편번호1.0000.421-0.8640.0000.821
경도0.4211.000-0.4160.3260.814
위도-0.864-0.4161.0000.0000.786
영업상태0.0000.3260.0001.0000.860
구우편번호0.8210.8140.7860.8601.000

Missing values

2023-12-12T23:11:25.208788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:11:25.388960image/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

사업장명업종분류서비스명서비스아이디(ID)인허가일자영업상태소재지전화구우편번호주소도로명우편번호도로명주소경도위도
0발리모텔숙소숙박업03_11_03_P2001-12-18Y053-423-5006702-852대구광역시 북구 칠성동2가 302-311번지41581대구광역시 북구 칠성남로30길 6-1 (칠성동2가)128.59557435.876935
1콜모텔숙소숙박업03_11_03_P2002-02-22Y053-956-6666702-832대구광역시 북구 복현동 472-8번지41564대구광역시 북구 경대로27길 1 (복현동)128.62056735.891566
2와와모텔숙소숙박업03_11_03_P2000-01-18Y053-956-5525702-831대구광역시 북구 복현동 402-8번지41562대구광역시 북구 대학로 136 (복현동)128.61345935.895958
3로즈모텔숙소숙박업03_11_03_P1996-12-01Y053-953-8855702-839대구광역시 북구 산격동 1449-9번지41543대구광역시 북구 대구체육관로 24 (산격동)128.60248335.891409
4아테네모텔숙소숙박업03_11_03_P2002-02-05Y053-326-1733702-886대구광역시 북구 동천동 911-2번지41423대구광역시 북구 동천로24길 17-13 (동천동)128.5617935.942184
5꼬모모텔숙소숙박업03_11_03_P2001-07-18Y0507-600-0760702-831대구광역시 북구 복현동 402-6번지41562대구광역시 북구 대학로 140 (복현동)128.61379435.89612
6스위트호텔숙소숙박업03_11_03_P2006-03-02Y053-313-7500702-803대구광역시 북구 관음동 1378-13번지41447대구광역시 북구 관음동로 16 (관음동)128.54815835.934378
7영모텔숙소숙박업03_11_03_P1996-12-10Y053-955-7862702-831대구광역시 북구 복현동 415번지41562대구광역시 북구 경진로1길 17 (복현동)128.61552735.896483
8스위트모텔숙소숙박업03_11_03_P2001-07-26Y053-424-6367702-852대구광역시 북구 칠성동2가 302-208번지41581대구광역시 북구 칠성남로38길 60 (칠성동2가)128.59663635.876349
9현대구모텔숙소숙박업03_11_03_P2010-12-21Y053-321-7990702-825대구광역시 북구 매천동 527-3번지41488대구광역시 북구 매천로18길 34 (매천동)128.54312735.902293
사업장명업종분류서비스명서비스아이디(ID)인허가일자영업상태소재지전화구우편번호주소도로명우편번호도로명주소경도위도
84썬모텔숙소숙박업03_11_03_P2008-02-19Y<NA>702-061대구광역시 북구 칠성동1가 20번지41582대구광역시 북구 칠성시장로7길 23 (칠성동1가)128.60283935.875779
85소울모텔숙소숙박업03_11_03_P1989-08-07Y053-354-5887702-072대구광역시 북구 고성동2가 57-241594대구광역시 북구 고성로 182 (고성동2가)128.58567435.880226
86이탈리안썸머경대북문점숙소숙박업03_11_03_P1997-05-23Y053-954-0010702-831대구광역시 북구 복현동 402-741562대구광역시 북구 대학로 138 (복현동)128.61364535.895989
87엘리제모텔숙소숙박업03_11_03_P2000-08-23Y053-325-5100702-868대구광역시 북구 태전동 940-3번지41451대구광역시 북구 칠곡중앙대로 403-1 (태전동)128.54784935.931873
88카네기 모텔숙소숙박업03_11_03_P2003-05-29Y053-327-1210702-803대구광역시 북구 관음동 1378번지41447대구광역시 북구 칠곡중앙대로 435 (관음동)128.54833435.934636
89다옴호텔숙소숙박업03_11_03_P2003-11-20Y<NA>702-865대구광역시 북구 태전동 496-141468대구광역시 북구 학정로9길 20 (태전동)128.54771935.915534
90호텔인터불고 엑스코숙소숙박업03_11_03_P2008-12-16Y053-380-0114702-845대구광역시 북구 산격동 167441515대구광역시 북구 유통단지로 80 (산격동)128.61128935.907098
91썸모텔숙소숙박업03_11_03_P1997-01-24Y053-953-9391702-846대구광역시 북구 산격동 824-2번지41533대구광역시 북구 연암로 150-1 (산격동)128.59585535.897914
92인카모텔숙소숙박업03_11_03_P2003-05-07Y053-324-5657702-886대구광역시 북구 동천동 911-1번지41423대구광역시 북구 동천로24길 17-15 (동천동)128.56154735.942214
93호텔소호102숙소숙박업03_11_03_P1999-06-26Y053-311-0880702-865대구광역시 북구 태전동 788-141468대구광역시 북구 학정로9길 10 (태전동)128.54776435.914474