Overview

Dataset statistics

Number of variables14
Number of observations232
Missing cells203
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.6 KiB
Average record size in memory117.6 B

Variable types

Numeric4
Text4
DateTime2
Categorical4

Dataset

Description경상남도 밀양시 숙박업소에 대한 자료로, 인허가일자, 사업장명, 도로명주소, 위도, 경도에 대한 정보를 제공합니다.
Author경상남도 밀양시
URLhttps://www.data.go.kr/data/15111086/fileData.do

Alerts

상세영업상태명 has constant value ""Constant
카테고리 is highly overall correlated with 상세영업상태코드High correlation
상세영업상태코드 is highly overall correlated with 관광상품번호(NameID) and 5 other fieldsHigh correlation
업태구분명 is highly overall correlated with 상세영업상태코드High correlation
관광상품번호(NameID) is highly overall correlated with 상세영업상태코드High correlation
도로명우편번호 is highly overall correlated with 좌표정보(위도) and 1 other fieldsHigh correlation
좌표정보(위도) is highly overall correlated with 도로명우편번호 and 1 other fieldsHigh correlation
좌표정보(경도) is highly overall correlated with 상세영업상태코드High correlation
관리번호 has 98 (42.2%) missing valuesMissing
인허가일자 has 98 (42.2%) missing valuesMissing
도로명전체주소 has 7 (3.0%) missing valuesMissing
관광상품번호(NameID) has unique valuesUnique
사업장명 has unique valuesUnique
좌표정보(위도) has 3 (1.3%) zerosZeros
좌표정보(경도) has 3 (1.3%) zerosZeros

Reproduction

Analysis started2023-12-12 23:08:41.150478
Analysis finished2023-12-12 23:08:44.039520
Duration2.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관광상품번호(NameID)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct232
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3000116.5
Minimum3000001
Maximum3000232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T08:08:44.113099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000001
5-th percentile3000012.5
Q13000058.8
median3000116.5
Q33000174.2
95-th percentile3000220.5
Maximum3000232
Range231
Interquartile range (IQR)115.5

Descriptive statistics

Standard deviation67.116814
Coefficient of variation (CV)2.2371402 × 10-5
Kurtosis-1.2
Mean3000116.5
Median Absolute Deviation (MAD)58
Skewness0
Sum6.9602703 × 108
Variance4504.6667
MonotonicityStrictly increasing
2023-12-13T08:08:44.246172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000001 1
 
0.4%
3000161 1
 
0.4%
3000149 1
 
0.4%
3000150 1
 
0.4%
3000151 1
 
0.4%
3000152 1
 
0.4%
3000153 1
 
0.4%
3000154 1
 
0.4%
3000155 1
 
0.4%
3000156 1
 
0.4%
Other values (222) 222
95.7%
ValueCountFrequency (%)
3000001 1
0.4%
3000002 1
0.4%
3000003 1
0.4%
3000004 1
0.4%
3000005 1
0.4%
3000006 1
0.4%
3000007 1
0.4%
3000008 1
0.4%
3000009 1
0.4%
3000010 1
0.4%
ValueCountFrequency (%)
3000232 1
0.4%
3000231 1
0.4%
3000230 1
0.4%
3000229 1
0.4%
3000228 1
0.4%
3000227 1
0.4%
3000226 1
0.4%
3000225 1
0.4%
3000224 1
0.4%
3000223 1
0.4%

관리번호
Text

MISSING 

Distinct134
Distinct (%)100.0%
Missing98
Missing (%)42.2%
Memory size1.9 KiB
2023-12-13T08:08:44.479297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.268657
Min length20

Characters and Unicode

Total characters2850
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)100.0%

Sample

1st row5360000-214-2019-00001
2nd row5360000-201-2019-00001
3rd row5360000-214-2019-00002
4th row5360000-201-2019-00002
5th row5360000-201-1986-00001
ValueCountFrequency (%)
5360000-201-1998-00001 1
 
0.7%
cdfi2262132021000004 1
 
0.7%
cdfi3261132016000001 1
 
0.7%
cdfi3261132013000002 1
 
0.7%
cdfi2262222022000002 1
 
0.7%
cdfi2262142017000001 1
 
0.7%
cdfi2262142016000005 1
 
0.7%
cdfi2262142016000004 1
 
0.7%
cdfi2262142016000002 1
 
0.7%
cdfi2262142016000001 1
 
0.7%
Other values (124) 124
92.5%
2023-12-13T08:08:44.863827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1135
39.8%
2 395
 
13.9%
1 278
 
9.8%
- 255
 
8.9%
6 158
 
5.5%
3 139
 
4.9%
5 120
 
4.2%
9 63
 
2.2%
4 62
 
2.2%
C 49
 
1.7%
Other values (5) 196
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2399
84.2%
Dash Punctuation 255
 
8.9%
Uppercase Letter 196
 
6.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1135
47.3%
2 395
 
16.5%
1 278
 
11.6%
6 158
 
6.6%
3 139
 
5.8%
5 120
 
5.0%
9 63
 
2.6%
4 62
 
2.6%
7 25
 
1.0%
8 24
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 49
25.0%
D 49
25.0%
F 49
25.0%
I 49
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 255
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2654
93.1%
Latin 196
 
6.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1135
42.8%
2 395
 
14.9%
1 278
 
10.5%
- 255
 
9.6%
6 158
 
6.0%
3 139
 
5.2%
5 120
 
4.5%
9 63
 
2.4%
4 62
 
2.3%
7 25
 
0.9%
Latin
ValueCountFrequency (%)
C 49
25.0%
D 49
25.0%
F 49
25.0%
I 49
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2850
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1135
39.8%
2 395
 
13.9%
1 278
 
9.8%
- 255
 
8.9%
6 158
 
5.5%
3 139
 
4.9%
5 120
 
4.2%
9 63
 
2.2%
4 62
 
2.2%
C 49
 
1.7%
Other values (5) 196
 
6.9%

인허가일자
Date

MISSING 

Distinct128
Distinct (%)95.5%
Missing98
Missing (%)42.2%
Memory size1.9 KiB
Minimum1963-06-30 00:00:00
Maximum2022-07-26 00:00:00
2023-12-13T08:08:45.017208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:45.169152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상세영업상태코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
1
134 
<NA>
98 

Length

Max length4
Median length1
Mean length2.2672414
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 134
57.8%
<NA> 98
42.2%

Length

2023-12-13T08:08:45.325311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:08:45.440143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 134
57.8%
na 98
42.2%

상세영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
영업
232 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 232
100.0%

Length

2023-12-13T08:08:45.540807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:08:45.639807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 232
100.0%

사업장명
Text

UNIQUE 

Distinct232
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T08:08:45.909617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length6.375
Min length2

Characters and Unicode

Total characters1479
Distinct characters308
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

Unique232 ?
Unique (%)100.0%

Sample

1st row폴인펜션
2nd row밀양애게스트하우스
3rd row비클래시 키즈풀빌라
4th row호텔레이크
5th rowG-D21모텔
ValueCountFrequency (%)
펜션 9
 
3.2%
밀양 4
 
1.4%
풀빌라 4
 
1.4%
캠핑장 3
 
1.1%
키즈풀빌라 3
 
1.1%
풍경펜션 2
 
0.7%
모텔 2
 
0.7%
오토캠핑장 2
 
0.7%
사과꽃피는저녁 1
 
0.4%
핑코하우스 1
 
0.4%
Other values (249) 249
88.9%
2023-12-13T08:08:46.338104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
션 84
 
5.7%
펜 83
 
5.6%
장 50
 
3.4%
48
 
3.2%
텔 45
 
3.0%
핑 41
 
2.8%
캠 39
 
2.6%
모 36
 
2.4%
스 30
 
2.0%
리 29
 
2.0%
Other values (298) 994
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1372
92.8%
Space Separator 48
 
3.2%
Decimal Number 22
 
1.5%
Uppercase Letter 18
 
1.2%
Other Punctuation 10
 
0.7%
Lowercase Letter 4
 
0.3%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
션 84
 
6.1%
펜 83
 
6.0%
장 50
 
3.6%
텔 45
 
3.3%
핑 41
 
3.0%
캠 39
 
2.8%
모 36
 
2.6%
스 30
 
2.2%
리 29
 
2.1%
밀 26
 
1.9%
Other values (270) 909
66.3%
Uppercase Letter
ValueCountFrequency (%)
A 3
16.7%
D 3
16.7%
W 2
11.1%
S 2
11.1%
R 1
 
5.6%
Z 1
 
5.6%
J 1
 
5.6%
O 1
 
5.6%
G 1
 
5.6%
P 1
 
5.6%
Other values (2) 2
11.1%
Decimal Number
ValueCountFrequency (%)
1 6
27.3%
0 4
18.2%
5 3
13.6%
9 3
13.6%
3 2
 
9.1%
2 2
 
9.1%
7 1
 
4.5%
4 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
& 8
80.0%
/ 2
 
20.0%
Lowercase Letter
ValueCountFrequency (%)
o 2
50.0%
g 2
50.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1372
92.8%
Common 85
 
5.7%
Latin 22
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
션 84
 
6.1%
펜 83
 
6.0%
장 50
 
3.6%
텔 45
 
3.3%
핑 41
 
3.0%
캠 39
 
2.8%
모 36
 
2.6%
스 30
 
2.2%
리 29
 
2.1%
밀 26
 
1.9%
Other values (270) 909
66.3%
Common
ValueCountFrequency (%)
48
56.5%
& 8
 
9.4%
1 6
 
7.1%
0 4
 
4.7%
5 3
 
3.5%
9 3
 
3.5%
/ 2
 
2.4%
3 2
 
2.4%
) 2
 
2.4%
( 2
 
2.4%
Other values (4) 5
 
5.9%
Latin
ValueCountFrequency (%)
A 3
13.6%
D 3
13.6%
o 2
9.1%
g 2
9.1%
W 2
9.1%
S 2
9.1%
R 1
 
4.5%
Z 1
 
4.5%
J 1
 
4.5%
O 1
 
4.5%
Other values (4) 4
18.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1372
92.8%
ASCII 107
 
7.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
션 84
 
6.1%
펜 83
 
6.0%
장 50
 
3.6%
텔 45
 
3.3%
핑 41
 
3.0%
캠 39
 
2.8%
모 36
 
2.6%
스 30
 
2.2%
리 29
 
2.1%
밀 26
 
1.9%
Other values (270) 909
66.3%
ASCII
ValueCountFrequency (%)
48
44.9%
& 8
 
7.5%
1 6
 
5.6%
0 4
 
3.7%
5 3
 
2.8%
A 3
 
2.8%
D 3
 
2.8%
9 3
 
2.8%
/ 2
 
1.9%
3 2
 
1.9%
Other values (18) 25
23.4%

업태구분명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
147 
여관업
46 
숙박업(생활)
22 
숙박업 기타
 
7
한식
 
5
Other values (3)
 
5

Length

Max length7
Median length4
Mean length4.0905172
Min length2

Unique

Unique2 ?
Unique (%)0.9%

Sample

1st row숙박업(생활)
2nd row숙박업 기타
3rd row숙박업(생활)
4th row숙박업 기타
5th row여관업

Common Values

ValueCountFrequency (%)
<NA> 147
63.4%
여관업 46
 
19.8%
숙박업(생활) 22
 
9.5%
숙박업 기타 7
 
3.0%
한식 5
 
2.2%
일반호텔 3
 
1.3%
기타 1
 
0.4%
경양식 1
 
0.4%

Length

2023-12-13T08:08:46.472171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:08:46.579836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 147
61.5%
여관업 46
 
19.2%
숙박업(생활 22
 
9.2%
기타 8
 
3.3%
숙박업 7
 
2.9%
한식 5
 
2.1%
일반호텔 3
 
1.3%
경양식 1
 
0.4%

도로명전체주소
Text

MISSING 

Distinct223
Distinct (%)99.1%
Missing7
Missing (%)3.0%
Memory size1.9 KiB
2023-12-13T08:08:46.964405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length34
Mean length22.444444
Min length16

Characters and Unicode

Total characters5050
Distinct characters155
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique221 ?
Unique (%)98.2%

Sample

1st row경상남도 밀양시 단장면 고례2길 15
2nd row경상남도 밀양시 중앙로 51, 가곡상가남천빌딩 2층 (가곡동)
3rd row경상남도 밀양시 초동면 방동안길 41
4th row경상남도 밀양시 삼랑진읍 천태로 398
5th row경상남도 밀양시 삼문중앙로6길 32-13 (삼문동)
ValueCountFrequency (%)
경상남도 225
19.7%
밀양시 225
19.7%
단장면 97
 
8.5%
산내면 27
 
2.4%
표충로 21
 
1.8%
산외면 18
 
1.6%
상동면 15
 
1.3%
삼랑진읍 14
 
1.2%
밀양대로 11
 
1.0%
고례로 10
 
0.9%
Other values (323) 477
41.8%
2023-12-13T08:08:47.496069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
915
18.1%
시 245
 
4.9%
상 244
 
4.8%
양 242
 
4.8%
도 240
 
4.8%
밀 237
 
4.7%
남 231
 
4.6%
경 225
 
4.5%
1 187
 
3.7%
면 173
 
3.4%
Other values (145) 2111
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3105
61.5%
Space Separator 915
 
18.1%
Decimal Number 849
 
16.8%
Dash Punctuation 113
 
2.2%
Close Punctuation 28
 
0.6%
Open Punctuation 28
 
0.6%
Other Punctuation 8
 
0.2%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 245
 
7.9%
상 244
 
7.9%
양 242
 
7.8%
도 240
 
7.7%
밀 237
 
7.6%
남 231
 
7.4%
경 225
 
7.2%
면 173
 
5.6%
길 125
 
4.0%
로 109
 
3.5%
Other values (126) 1034
33.3%
Decimal Number
ValueCountFrequency (%)
1 187
22.0%
2 119
14.0%
3 96
11.3%
4 81
9.5%
5 75
8.8%
8 62
 
7.3%
6 60
 
7.1%
9 60
 
7.1%
7 55
 
6.5%
0 54
 
6.4%
Lowercase Letter
ValueCountFrequency (%)
g 1
50.0%
o 1
50.0%
Space Separator
ValueCountFrequency (%)
915
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 113
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
V 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3105
61.5%
Common 1942
38.5%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 245
 
7.9%
상 244
 
7.9%
양 242
 
7.8%
도 240
 
7.7%
밀 237
 
7.6%
남 231
 
7.4%
경 225
 
7.2%
면 173
 
5.6%
길 125
 
4.0%
로 109
 
3.5%
Other values (126) 1034
33.3%
Common
ValueCountFrequency (%)
915
47.1%
1 187
 
9.6%
2 119
 
6.1%
- 113
 
5.8%
3 96
 
4.9%
4 81
 
4.2%
5 75
 
3.9%
8 62
 
3.2%
6 60
 
3.1%
9 60
 
3.1%
Other values (6) 174
 
9.0%
Latin
ValueCountFrequency (%)
g 1
33.3%
V 1
33.3%
o 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3105
61.5%
ASCII 1945
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
915
47.0%
1 187
 
9.6%
2 119
 
6.1%
- 113
 
5.8%
3 96
 
4.9%
4 81
 
4.2%
5 75
 
3.9%
8 62
 
3.2%
6 60
 
3.1%
9 60
 
3.1%
Other values (9) 177
 
9.1%
Hangul
ValueCountFrequency (%)
시 245
 
7.9%
상 244
 
7.9%
양 242
 
7.8%
도 240
 
7.7%
밀 237
 
7.6%
남 231
 
7.4%
경 225
 
7.2%
면 173
 
5.6%
길 125
 
4.0%
로 109
 
3.5%
Other values (126) 1034
33.3%

도로명우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50421.685
Minimum50400
Maximum50467
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T08:08:47.642487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50400
5-th percentile50407.55
Q150414
median50418
Q350418
95-th percentile50465
Maximum50467
Range67
Interquartile range (IQR)4

Descriptive statistics

Standard deviation15.494732
Coefficient of variation (CV)0.00030730293
Kurtosis2.446839
Mean50421.685
Median Absolute Deviation (MAD)3
Skewness1.8068342
Sum11697831
Variance240.08671
MonotonicityNot monotonic
2023-12-13T08:08:47.829420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
50418 87
37.5%
50415 19
 
8.2%
50412 14
 
6.0%
50410 11
 
4.7%
50417 10
 
4.3%
50466 7
 
3.0%
50419 7
 
3.0%
50413 6
 
2.6%
50411 6
 
2.6%
50445 6
 
2.6%
Other values (27) 59
25.4%
ValueCountFrequency (%)
50400 1
 
0.4%
50401 3
 
1.3%
50402 1
 
0.4%
50403 3
 
1.3%
50404 2
 
0.9%
50406 1
 
0.4%
50407 1
 
0.4%
50408 2
 
0.9%
50409 4
 
1.7%
50410 11
4.7%
ValueCountFrequency (%)
50467 3
1.3%
50466 7
3.0%
50465 3
1.3%
50462 1
 
0.4%
50461 2
 
0.9%
50459 3
1.3%
50455 2
 
0.9%
50447 1
 
0.4%
50445 6
2.6%
50444 1
 
0.4%

소재지전체주소
Text

Distinct230
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T08:08:48.167656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length21.642241
Min length15

Characters and Unicode

Total characters5021
Distinct characters100
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

Unique228 ?
Unique (%)98.3%

Sample

1st row경상남도 밀양시 단장면 고례리 1521-5번지
2nd row경상남도 밀양시 가곡동 458-1번지 가곡상가남천빌딩
3rd row경상남도 밀양시 초동면 봉황리 139
4th row경상남도 밀양시 삼랑진읍 안태리 638-6번지
5th row경상남도 밀양시 삼문동 221-29
ValueCountFrequency (%)
밀양시 232
20.5%
경상남도 231
20.4%
단장면 98
 
8.7%
구천리 47
 
4.2%
고례리 29
 
2.6%
산내면 29
 
2.6%
산외면 20
 
1.8%
상동면 15
 
1.3%
삼랑진읍 14
 
1.2%
범도리 11
 
1.0%
Other values (288) 404
35.8%
2023-12-13T08:08:48.670889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
898
17.9%
도 251
 
5.0%
남 249
 
5.0%
상 247
 
4.9%
양 244
 
4.9%
경 232
 
4.6%
밀 232
 
4.6%
시 232
 
4.6%
1 203
 
4.0%
리 199
 
4.0%
Other values (90) 2034
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3038
60.5%
Decimal Number 930
 
18.5%
Space Separator 898
 
17.9%
Dash Punctuation 155
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 251
 
8.3%
남 249
 
8.2%
상 247
 
8.1%
양 244
 
8.0%
경 232
 
7.6%
밀 232
 
7.6%
시 232
 
7.6%
리 199
 
6.6%
면 179
 
5.9%
장 99
 
3.3%
Other values (78) 874
28.8%
Decimal Number
ValueCountFrequency (%)
1 203
21.8%
5 103
11.1%
2 96
10.3%
7 88
9.5%
3 87
9.4%
4 82
8.8%
6 76
 
8.2%
8 75
 
8.1%
0 66
 
7.1%
9 54
 
5.8%
Space Separator
ValueCountFrequency (%)
898
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 155
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3038
60.5%
Common 1983
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 251
 
8.3%
남 249
 
8.2%
상 247
 
8.1%
양 244
 
8.0%
경 232
 
7.6%
밀 232
 
7.6%
시 232
 
7.6%
리 199
 
6.6%
면 179
 
5.9%
장 99
 
3.3%
Other values (78) 874
28.8%
Common
ValueCountFrequency (%)
898
45.3%
1 203
 
10.2%
- 155
 
7.8%
5 103
 
5.2%
2 96
 
4.8%
7 88
 
4.4%
3 87
 
4.4%
4 82
 
4.1%
6 76
 
3.8%
8 75
 
3.8%
Other values (2) 120
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3038
60.5%
ASCII 1983
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
898
45.3%
1 203
 
10.2%
- 155
 
7.8%
5 103
 
5.2%
2 96
 
4.8%
7 88
 
4.4%
3 87
 
4.4%
4 82
 
4.1%
6 76
 
3.8%
8 75
 
3.8%
Other values (2) 120
 
6.1%
Hangul
ValueCountFrequency (%)
도 251
 
8.3%
남 249
 
8.2%
상 247
 
8.1%
양 244
 
8.0%
경 232
 
7.6%
밀 232
 
7.6%
시 232
 
7.6%
리 199
 
6.6%
면 179
 
5.9%
장 99
 
3.3%
Other values (78) 874
28.8%

좌표정보(위도)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct228
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.05552
Minimum0
Maximum35.60679
Zeros3
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T08:08:48.816886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile35.400734
Q135.490476
median35.517793
Q335.5465
95-th percentile35.581712
Maximum35.60679
Range35.60679
Interquartile range (IQR)0.0560237

Descriptive statistics

Standard deviation4.0213292
Coefficient of variation (CV)0.11471315
Kurtosis73.933581
Mean35.05552
Median Absolute Deviation (MAD)0.02824436
Skewness-8.6766635
Sum8132.8807
Variance16.171088
MonotonicityNot monotonic
2023-12-13T08:08:48.984370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
1.3%
35.48741911 2
 
0.9%
35.56048782 2
 
0.9%
35.4906807 1
 
0.4%
35.49102604 1
 
0.4%
35.56732296 1
 
0.4%
35.53375781 1
 
0.4%
35.52291036 1
 
0.4%
35.56735249 1
 
0.4%
35.57184455 1
 
0.4%
Other values (218) 218
94.0%
ValueCountFrequency (%)
0.0 3
1.3%
35.35123191 1
 
0.4%
35.37132505 1
 
0.4%
35.37410237 1
 
0.4%
35.3747691 1
 
0.4%
35.37494508 1
 
0.4%
35.38705551 1
 
0.4%
35.39069767 1
 
0.4%
35.40028903 1
 
0.4%
35.40032126 1
 
0.4%
ValueCountFrequency (%)
35.60678983 1
0.4%
35.60293458 1
0.4%
35.60082436 1
0.4%
35.59909198 1
0.4%
35.59851342 1
0.4%
35.59829356 1
0.4%
35.59706892 1
0.4%
35.59470118 1
0.4%
35.58813207 1
0.4%
35.58718171 1
0.4%

좌표정보(경도)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct228
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.19287
Minimum0
Maximum128.98622
Zeros3
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T08:08:49.137711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile128.70694
Q1128.77403
median128.87818
Q3128.92822
95-th percentile128.95948
Maximum128.98622
Range128.98622
Interquartile range (IQR)0.15418923

Descriptive statistics

Standard deviation14.589863
Coefficient of variation (CV)0.11470661
Kurtosis73.951132
Mean127.19287
Median Absolute Deviation (MAD)0.0531766
Skewness-8.6781861
Sum29508.745
Variance212.86409
MonotonicityNot monotonic
2023-12-13T08:08:49.595967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
1.3%
128.931358 2
 
0.9%
128.9172272 2
 
0.9%
128.9295225 1
 
0.4%
128.9259752 1
 
0.4%
128.9186011 1
 
0.4%
128.9491943 1
 
0.4%
128.9264889 1
 
0.4%
128.8273601 1
 
0.4%
128.9195597 1
 
0.4%
Other values (218) 218
94.0%
ValueCountFrequency (%)
0.0 3
1.3%
128.591033 1
 
0.4%
128.6009643 1
 
0.4%
128.6177915 1
 
0.4%
128.6489613 1
 
0.4%
128.6519745 1
 
0.4%
128.671328 1
 
0.4%
128.6858634 1
 
0.4%
128.7003937 1
 
0.4%
128.7058098 1
 
0.4%
ValueCountFrequency (%)
128.986223 1
0.4%
128.985954 1
0.4%
128.9831133 1
0.4%
128.9807575 1
0.4%
128.9804401 1
0.4%
128.9800654 1
0.4%
128.9786271 1
0.4%
128.9775146 1
0.4%
128.9757878 1
0.4%
128.9720697 1
0.4%

최종수정시점
Date

Distinct100
Distinct (%)43.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2011-11-29 00:00:00
Maximum2022-10-26 00:00:00
2023-12-13T08:08:49.734838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:49.880189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

카테고리
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
펜션/풀빌라
122 
모텔/호텔
46 
글램핑/캠핑
42 
여관/여인숙
 
9
한옥
 
9
Other values (2)
 
4

Length

Max length6
Median length6
Mean length5.6293103
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row펜션/풀빌라
2nd row게스트하우스
3rd row펜션/풀빌라
4th row모텔/호텔
5th row모텔/호텔

Common Values

ValueCountFrequency (%)
펜션/풀빌라 122
52.6%
모텔/호텔 46
 
19.8%
글램핑/캠핑 42
 
18.1%
여관/여인숙 9
 
3.9%
한옥 9
 
3.9%
게스트하우스 2
 
0.9%
관광호텔 2
 
0.9%

Length

2023-12-13T08:08:50.044137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:08:50.154728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
펜션/풀빌라 122
52.6%
모텔/호텔 46
 
19.8%
글램핑/캠핑 42
 
18.1%
여관/여인숙 9
 
3.9%
한옥 9
 
3.9%
게스트하우스 2
 
0.9%
관광호텔 2
 
0.9%

Interactions

2023-12-13T08:08:43.087446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:41.727961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:42.316646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:42.688746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:43.192030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:42.049664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:42.412080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:42.773261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:43.310055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:42.133344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:42.506675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:42.877224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:43.423829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:42.230415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:42.592504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:08:42.988828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:08:50.241174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광상품번호(NameID)업태구분명도로명우편번호좌표정보(위도)좌표정보(경도)최종수정시점카테고리
관광상품번호(NameID)1.0000.5630.4160.0000.0000.8430.680
업태구분명0.5631.0000.0000.2760.2760.9790.652
도로명우편번호0.4160.0001.0000.0000.0000.9280.443
좌표정보(위도)0.0000.2760.0001.0000.9650.7810.000
좌표정보(경도)0.0000.2760.0000.9651.0000.7810.000
최종수정시점0.8430.9790.9280.7810.7811.0000.923
카테고리0.6800.6520.4430.0000.0000.9231.000
2023-12-13T08:08:50.344936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카테고리상세영업상태코드업태구분명
카테고리1.0001.0000.487
상세영업상태코드1.0001.0001.000
업태구분명0.4871.0001.000
2023-12-13T08:08:50.436911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광상품번호(NameID)도로명우편번호좌표정보(위도)좌표정보(경도)상세영업상태코드업태구분명카테고리
관광상품번호(NameID)1.000-0.1720.3100.3581.0000.3990.426
도로명우편번호-0.1721.000-0.614-0.0261.0000.0000.239
좌표정보(위도)0.310-0.6141.0000.4401.0000.2850.000
좌표정보(경도)0.358-0.0260.4401.0001.0000.2850.000
상세영업상태코드1.0001.0001.0001.0001.0001.0001.000
업태구분명0.3990.0000.2850.2851.0001.0000.487
카테고리0.4260.2390.0000.0001.0000.4871.000

Missing values

2023-12-13T08:08:43.597142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:08:43.829659image/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.
2023-12-13T08:08:43.973142image/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

관광상품번호(NameID)관리번호인허가일자상세영업상태코드상세영업상태명사업장명업태구분명도로명전체주소도로명우편번호소재지전체주소좌표정보(위도)좌표정보(경도)최종수정시점카테고리
030000015360000-214-2019-000012019-03-261영업폴인펜션숙박업(생활)경상남도 밀양시 단장면 고례2길 1550418경상남도 밀양시 단장면 고례리 1521-5번지35.490681128.9295222019-03-26펜션/풀빌라
130000025360000-201-2019-000012019-02-221영업밀양애게스트하우스숙박업 기타경상남도 밀양시 중앙로 51, 가곡상가남천빌딩 2층 (가곡동)50445경상남도 밀양시 가곡동 458-1번지 가곡상가남천빌딩35.473047128.771592019-02-22게스트하우스
230000035360000-214-2019-000022019-06-031영업비클래시 키즈풀빌라숙박업(생활)경상남도 밀양시 초동면 방동안길 4150447경상남도 밀양시 초동면 봉황리 13935.453984128.7078652022-03-04펜션/풀빌라
330000045360000-201-2019-000022019-08-131영업호텔레이크숙박업 기타경상남도 밀양시 삼랑진읍 천태로 39850466경상남도 밀양시 삼랑진읍 안태리 638-6번지35.409254128.8728992019-08-13모텔/호텔
430000055360000-201-1986-000011986-07-301영업G-D21모텔여관업경상남도 밀양시 삼문중앙로6길 32-13 (삼문동)50437경상남도 밀양시 삼문동 221-2935.487681128.7545912022-03-08모텔/호텔
530000065360000-201-1981-000031981-08-191영업진화장여관여관업경상남도 밀양시 중앙로 369 (내일동)50430경상남도 밀양시 내일동 495-6번지35.495164128.7520872019-10-17여관/여인숙
630000075360000-214-2020-000012020-06-161영업계수나무펜션숙박업(생활)경상남도 밀양시 단장면 고례3길 3350418경상남도 밀양시 단장면 고례리 1438-435.495217128.9264162021-05-27펜션/풀빌라
730000085360000-201-1992-000021992-07-071영업재약콘도여관업경상남도 밀양시 단장면 시전2길 12-1050418경상남도 밀양시 단장면 구천리 2005-735.532425128.9447312021-05-27펜션/풀빌라
830000095360000-201-1995-000021995-05-111영업유토피아모텔여관업경상남도 밀양시 중앙로 77-2 (가곡동)50445경상남도 밀양시 가곡동 594-335.474152128.7689862021-03-05모텔/호텔
930000105360000-201-1993-000021993-06-021영업노블리안모텔여관업경상남도 밀양시 북성로2길 9 (내이동)50423경상남도 밀양시 내이동 1186-11번지35.499148128.744262018-10-12모텔/호텔
관광상품번호(NameID)관리번호인허가일자상세영업상태코드상세영업상태명사업장명업태구분명도로명전체주소도로명우편번호소재지전체주소좌표정보(위도)좌표정보(경도)최종수정시점카테고리
2223000223<NA><NA><NA>영업프로방스펜션<NA>경상남도 밀양시 단장면 표충로 80650418경상남도 밀양시 단장면 범도리 83135.522691128.9038172022-10-18펜션/풀빌라
2233000224<NA><NA><NA>영업산이슬펜션<NA>경상남도 밀양시 단장면 표충로 970-450418경상남도 밀양시 단장면 구천리 737-1235.524587128.9195042022-10-18펜션/풀빌라
2243000225<NA><NA><NA>영업캐빈하우스<NA>경상남도 밀양시 단장면 바드리길 1950418경상남도 밀양시 단장면 구천리 676-1135.522317128.9273762022-10-18펜션/풀빌라
2253000226<NA><NA><NA>영업예다움풀펜션<NA>경상남도 밀양시 단장면 표충로 106650418경상남도 밀양시 단장면 구천리 534-735.525313128.9299532022-10-18펜션/풀빌라
2263000227<NA><NA><NA>영업코끼리펜션<NA>경상남도 밀양시 단장면 표충로 110550418경상남도 밀양시 단장면 구천리 516-235.526754128.9337762022-10-18펜션/풀빌라
2273000228<NA><NA><NA>영업벌떼펜션<NA>경상남도 밀양시 단장면 시전중앙길 8750418경상남도 밀양시 단장면 구천리 19635.533481128.9525882022-10-18펜션/풀빌라
2283000229<NA><NA><NA>영업청림펜션<NA>경상남도 밀양시 단장면 고례로 86350418경상남도 밀양시 단장면 고례리 138535.494125128.928532022-10-18펜션/풀빌라
2293000230<NA><NA><NA>영업고추잠자리펜션<NA>경상남도 밀양시 단장면 고례로 766-4450418경상남도 밀양시 단장면 고례리 170635.485733128.9285422022-10-18펜션/풀빌라
2303000231<NA><NA><NA>영업ADD펜션<NA>경상남도 밀양시 상동면 상동로 1117-4150410경상남도 밀양시 상동면 매화리 764-7135.581821128.8008382022-10-26펜션/풀빌라
2313000232<NA><NA><NA>영업윤이네호두나무캠핑장<NA>경상남도 밀양시 단장면 사연길 15-3450417경상남도 밀양시 단장면 사연리 1120-435.516415128.877422022-10-26글램핑/캠핑