Overview

Dataset statistics

Number of variables13
Number of observations56
Missing cells42
Missing cells (%)5.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory110.4 B

Variable types

Numeric4
Categorical3
Text5
DateTime1

Dataset

Description2024년 4월 16일 기준 경상남도 산청군 숙박정보에 대한 자료입니다. (업종명, 업소명, 주소, 관리자, 연락처, 객실수, 담당기관, 담당부서)
Author경상남도 산청군
URLhttps://www.data.go.kr/data/15052961/fileData.do

Alerts

담당기관 has constant value ""Constant
담당부서 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 업종명High correlation
객실수 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연락처 has 2 (3.6%) missing valuesMissing
홈페이지 has 40 (71.4%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2024-04-21 01:19:42.997058
Analysis finished2024-04-21 01:19:46.937669
Duration3.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.5
Minimum1
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-21T10:19:47.003498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.75
Q114.75
median28.5
Q342.25
95-th percentile53.25
Maximum56
Range55
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation16.309506
Coefficient of variation (CV)0.57226338
Kurtosis-1.2
Mean28.5
Median Absolute Deviation (MAD)14
Skewness0
Sum1596
Variance266
MonotonicityStrictly increasing
2024-04-21T10:19:47.112445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
30 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (46) 46
82.1%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%
47 1
1.8%

업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
숙박업(일반)
42 
숙박업(생활)
14 

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) 42
75.0%
숙박업(생활) 14
 
25.0%

Length

2024-04-21T10:19:47.217222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:19:47.293689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업(일반 42
75.0%
숙박업(생활 14
 
25.0%

업소명
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-04-21T10:19:47.477673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length5.5892857
Min length2

Characters and Unicode

Total characters313
Distinct characters126
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

Unique56 ?
Unique (%)100.0%

Sample

1st row경호장여관
2nd row백만장여관
3rd row지리산계곡호텔
4th row산청파크장
5th row단성모텔
ValueCountFrequency (%)
지리산리조트 2
 
3.4%
경호장여관 1
 
1.7%
항노화힐링누리원 1
 
1.7%
휴엔조이 1
 
1.7%
티(t)모텔 1
 
1.7%
삼보파크텔 1
 
1.7%
호텔홍천궁 1
 
1.7%
리베라2 1
 
1.7%
포유 1
 
1.7%
유(u)모텔 1
 
1.7%
Other values (48) 48
81.4%
2024-04-21T10:19:47.820746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 29
 
9.3%
모 24
 
7.7%
리 20
 
6.4%
산 15
 
4.8%
지 12
 
3.8%
장 9
 
2.9%
관 8
 
2.6%
여 7
 
2.2%
라 6
 
1.9%
크 6
 
1.9%
Other values (116) 177
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 292
93.3%
Close Punctuation 5
 
1.6%
Open Punctuation 5
 
1.6%
Uppercase Letter 4
 
1.3%
Space Separator 3
 
1.0%
Decimal Number 2
 
0.6%
Lowercase Letter 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 29
 
9.9%
모 24
 
8.2%
리 20
 
6.8%
산 15
 
5.1%
지 12
 
4.1%
장 9
 
3.1%
관 8
 
2.7%
여 7
 
2.4%
라 6
 
2.1%
크 6
 
2.1%
Other values (106) 156
53.4%
Uppercase Letter
ValueCountFrequency (%)
W 1
25.0%
F 1
25.0%
C 1
25.0%
T 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
u 1
50.0%
e 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
2 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 292
93.3%
Common 15
 
4.8%
Latin 6
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 29
 
9.9%
모 24
 
8.2%
리 20
 
6.8%
산 15
 
5.1%
지 12
 
4.1%
장 9
 
3.1%
관 8
 
2.7%
여 7
 
2.4%
라 6
 
2.1%
크 6
 
2.1%
Other values (106) 156
53.4%
Latin
ValueCountFrequency (%)
W 1
16.7%
u 1
16.7%
F 1
16.7%
C 1
16.7%
T 1
16.7%
e 1
16.7%
Common
ValueCountFrequency (%)
) 5
33.3%
( 5
33.3%
3
20.0%
2 2
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 292
93.3%
ASCII 21
 
6.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 29
 
9.9%
모 24
 
8.2%
리 20
 
6.8%
산 15
 
5.1%
지 12
 
4.1%
장 9
 
3.1%
관 8
 
2.7%
여 7
 
2.4%
라 6
 
2.1%
크 6
 
2.1%
Other values (106) 156
53.4%
ASCII
ValueCountFrequency (%)
) 5
23.8%
( 5
23.8%
3
14.3%
2 2
 
9.5%
W 1
 
4.8%
u 1
 
4.8%
F 1
 
4.8%
C 1
 
4.8%
T 1
 
4.8%
e 1
 
4.8%

주소
Text

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-04-21T10:19:48.062033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length30
Mean length24.839286
Min length20

Characters and Unicode

Total characters1391
Distinct characters81
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)96.4%

Sample

1st row경상남도 산청군 산청읍 친환경로 2674-10
2nd row경상남도 산청군 생초면 산수로 1038
3rd row경상남도 산청군 시천면 지리산대로 555
4th row경상남도 산청군 산청읍 웅석봉로 38
5th row경상남도 산청군 단성면 지리산대로3362번길 17
ValueCountFrequency (%)
경상남도 56
19.4%
산청군 56
19.4%
신안면 13
 
4.5%
시천면 12
 
4.2%
지리산대로 12
 
4.2%
산청읍 8
 
2.8%
단성면 8
 
2.8%
원지강변로 7
 
2.4%
생비량면 7
 
2.4%
금서면 6
 
2.1%
Other values (87) 103
35.8%
2024-04-21T10:19:48.427347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
232
 
16.7%
산 87
 
6.3%
청 65
 
4.7%
1 64
 
4.6%
경 63
 
4.5%
남 58
 
4.2%
로 57
 
4.1%
상 56
 
4.0%
도 56
 
4.0%
군 56
 
4.0%
Other values (71) 597
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 868
62.4%
Decimal Number 259
 
18.6%
Space Separator 232
 
16.7%
Dash Punctuation 23
 
1.7%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 87
 
10.0%
청 65
 
7.5%
경 63
 
7.3%
남 58
 
6.7%
로 57
 
6.6%
상 56
 
6.5%
도 56
 
6.5%
군 56
 
6.5%
면 48
 
5.5%
지 32
 
3.7%
Other values (56) 290
33.4%
Decimal Number
ValueCountFrequency (%)
1 64
24.7%
3 33
12.7%
2 32
12.4%
5 31
12.0%
4 21
 
8.1%
0 20
 
7.7%
6 20
 
7.7%
7 18
 
6.9%
9 14
 
5.4%
8 6
 
2.3%
Space Separator
ValueCountFrequency (%)
232
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 868
62.4%
Common 523
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 87
 
10.0%
청 65
 
7.5%
경 63
 
7.3%
남 58
 
6.7%
로 57
 
6.6%
상 56
 
6.5%
도 56
 
6.5%
군 56
 
6.5%
면 48
 
5.5%
지 32
 
3.7%
Other values (56) 290
33.4%
Common
ValueCountFrequency (%)
232
44.4%
1 64
 
12.2%
3 33
 
6.3%
2 32
 
6.1%
5 31
 
5.9%
- 23
 
4.4%
4 21
 
4.0%
0 20
 
3.8%
6 20
 
3.8%
7 18
 
3.4%
Other values (5) 29
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 868
62.4%
ASCII 523
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
232
44.4%
1 64
 
12.2%
3 33
 
6.3%
2 32
 
6.1%
5 31
 
5.9%
- 23
 
4.4%
4 21
 
4.0%
0 20
 
3.8%
6 20
 
3.8%
7 18
 
3.4%
Other values (5) 29
 
5.5%
Hangul
ValueCountFrequency (%)
산 87
 
10.0%
청 65
 
7.5%
경 63
 
7.3%
남 58
 
6.7%
로 57
 
6.6%
상 56
 
6.5%
도 56
 
6.5%
군 56
 
6.5%
면 48
 
5.5%
지 32
 
3.7%
Other values (56) 290
33.4%

영업자
Text

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-04-21T10:19:48.628043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.0892857
Min length3

Characters and Unicode

Total characters173
Distinct characters81
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)96.4%

Sample

1st row권용순
2nd row이응남
3rd row최재경
4th row이현실
5th row최정자
ValueCountFrequency (%)
최기봉 2
 
3.4%
정숙희 1
 
1.7%
양호경 1
 
1.7%
김순미 1
 
1.7%
윤계자 1
 
1.7%
김은진 1
 
1.7%
이성근 1
 
1.7%
강나리 1
 
1.7%
남미선 1
 
1.7%
정호정 1
 
1.7%
Other values (47) 47
81.0%
2024-04-21T10:19:48.944932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
최 10
 
5.8%
김 9
 
5.2%
이 9
 
5.2%
재 6
 
3.5%
정 6
 
3.5%
기 5
 
2.9%
미 4
 
2.3%
근 4
 
2.3%
자 4
 
2.3%
남 4
 
2.3%
Other values (71) 112
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 170
98.3%
Space Separator 2
 
1.2%
Decimal Number 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
최 10
 
5.9%
김 9
 
5.3%
이 9
 
5.3%
재 6
 
3.5%
정 6
 
3.5%
기 5
 
2.9%
미 4
 
2.4%
근 4
 
2.4%
자 4
 
2.4%
남 4
 
2.4%
Other values (69) 109
64.1%
Space Separator
ValueCountFrequency (%)
2
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 170
98.3%
Common 3
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
최 10
 
5.9%
김 9
 
5.3%
이 9
 
5.3%
재 6
 
3.5%
정 6
 
3.5%
기 5
 
2.9%
미 4
 
2.4%
근 4
 
2.4%
자 4
 
2.4%
남 4
 
2.4%
Other values (69) 109
64.1%
Common
ValueCountFrequency (%)
2
66.7%
1 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 170
98.3%
ASCII 3
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
최 10
 
5.9%
김 9
 
5.3%
이 9
 
5.3%
재 6
 
3.5%
정 6
 
3.5%
기 5
 
2.9%
미 4
 
2.4%
근 4
 
2.4%
자 4
 
2.4%
남 4
 
2.4%
Other values (69) 109
64.1%
ASCII
ValueCountFrequency (%)
2
66.7%
1 1
33.3%

연락처
Text

MISSING 

Distinct53
Distinct (%)98.1%
Missing2
Missing (%)3.6%
Memory size580.0 B
2024-04-21T10:19:49.143247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.12963
Min length12

Characters and Unicode

Total characters655
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

Unique52 ?
Unique (%)96.3%

Sample

1st row055-973-2625
2nd row055-973-1661
3rd row055-972-1441
4th row055-973-6840
5th row055-973-6616
ValueCountFrequency (%)
055-972-1451 2
 
3.7%
055-974-0560 1
 
1.9%
055-973-2625 1
 
1.9%
070-4200-5933 1
 
1.9%
055-974-0949 1
 
1.9%
055-972-9200 1
 
1.9%
055-972-0399 1
 
1.9%
055-974-2245 1
 
1.9%
055-974-0019 1
 
1.9%
055-973-0200 1
 
1.9%
Other values (43) 43
79.6%
2024-04-21T10:19:49.488288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 131
20.0%
- 108
16.5%
0 104
15.9%
9 67
10.2%
7 67
10.2%
3 42
 
6.4%
2 40
 
6.1%
4 32
 
4.9%
1 24
 
3.7%
6 24
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 547
83.5%
Dash Punctuation 108
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 131
23.9%
0 104
19.0%
9 67
12.2%
7 67
12.2%
3 42
 
7.7%
2 40
 
7.3%
4 32
 
5.9%
1 24
 
4.4%
6 24
 
4.4%
8 16
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 655
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 131
20.0%
- 108
16.5%
0 104
15.9%
9 67
10.2%
7 67
10.2%
3 42
 
6.4%
2 40
 
6.1%
4 32
 
4.9%
1 24
 
3.7%
6 24
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 655
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 131
20.0%
- 108
16.5%
0 104
15.9%
9 67
10.2%
7 67
10.2%
3 42
 
6.4%
2 40
 
6.1%
4 32
 
4.9%
1 24
 
3.7%
6 24
 
3.7%

홈페이지
Text

MISSING 

Distinct15
Distinct (%)93.8%
Missing40
Missing (%)71.4%
Memory size580.0 B
2024-04-21T10:19:49.662539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29.5
Mean length27.25
Min length17

Characters and Unicode

Total characters436
Distinct characters31
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

Unique14 ?
Unique (%)87.5%

Sample

1st rowhttp://www.seojiro.com/
2nd rowhttp://silkmotel.modoo.at/
3rd rowhttps://blog.naver.com/clearcake28
4th rowhttps://blog.naver.com/umotel0200
5th rowhttps://blog.naver.com/schauer0410
ValueCountFrequency (%)
http://www.seojiro.com 2
 
12.5%
http://silkmotel.modoo.at 1
 
6.2%
https://blog.naver.com/clearcake28 1
 
6.2%
https://blog.naver.com/umotel0200 1
 
6.2%
https://blog.naver.com/schauer0410 1
 
6.2%
http://www.chirilog.net 1
 
6.2%
http://www.viewcastle.co.kr 1
 
6.2%
http://www.jirisanresort.net 1
 
6.2%
http://www.thesancheong.com 1
 
6.2%
https://christmasvillage1.modoo.at 1
 
6.2%
Other values (5) 5
31.2%
2024-04-21T10:19:49.954316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 44
 
10.1%
/ 40
 
9.2%
o 36
 
8.3%
. 32
 
7.3%
w 27
 
6.2%
h 24
 
5.5%
e 22
 
5.0%
c 19
 
4.4%
a 19
 
4.4%
s 19
 
4.4%
Other values (21) 154
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 337
77.3%
Other Punctuation 88
 
20.2%
Decimal Number 11
 
2.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 44
13.1%
o 36
 
10.7%
w 27
 
8.0%
h 24
 
7.1%
e 22
 
6.5%
c 19
 
5.6%
a 19
 
5.6%
s 19
 
5.6%
r 19
 
5.6%
p 17
 
5.0%
Other values (13) 91
27.0%
Decimal Number
ValueCountFrequency (%)
0 5
45.5%
2 2
 
18.2%
1 2
 
18.2%
8 1
 
9.1%
4 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
/ 40
45.5%
. 32
36.4%
: 16
 
18.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 337
77.3%
Common 99
 
22.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 44
13.1%
o 36
 
10.7%
w 27
 
8.0%
h 24
 
7.1%
e 22
 
6.5%
c 19
 
5.6%
a 19
 
5.6%
s 19
 
5.6%
r 19
 
5.6%
p 17
 
5.0%
Other values (13) 91
27.0%
Common
ValueCountFrequency (%)
/ 40
40.4%
. 32
32.3%
: 16
 
16.2%
0 5
 
5.1%
2 2
 
2.0%
1 2
 
2.0%
8 1
 
1.0%
4 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 436
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 44
 
10.1%
/ 40
 
9.2%
o 36
 
8.3%
. 32
 
7.3%
w 27
 
6.2%
h 24
 
5.5%
e 22
 
5.0%
c 19
 
4.4%
a 19
 
4.4%
s 19
 
4.4%
Other values (21) 154
35.3%

위도
Real number (ℝ)

Distinct53
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.33715
Minimum35.229896
Maximum35.492657
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-21T10:19:50.085456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.229896
5-th percentile35.269034
Q135.296967
median35.314739
Q335.371496
95-th percentile35.439299
Maximum35.492657
Range0.262761
Interquartile range (IQR)0.07452975

Descriptive statistics

Standard deviation0.058987716
Coefficient of variation (CV)0.0016692833
Kurtosis-0.46379641
Mean35.33715
Median Absolute Deviation (MAD)0.031809
Skewness0.67567291
Sum1978.8804
Variance0.0034795507
MonotonicityNot monotonic
2024-04-21T10:19:50.215386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.346548 2
 
3.6%
35.415278 2
 
3.6%
35.337344 2
 
3.6%
35.416182 1
 
1.8%
35.297405 1
 
1.8%
35.276849 1
 
1.8%
35.314217 1
 
1.8%
35.302869 1
 
1.8%
35.280253 1
 
1.8%
35.261952 1
 
1.8%
Other values (43) 43
76.8%
ValueCountFrequency (%)
35.229896 1
1.8%
35.261952 1
1.8%
35.264496 1
1.8%
35.270546 1
1.8%
35.272111 1
1.8%
35.276849 1
1.8%
35.276982 1
1.8%
35.280253 1
1.8%
35.2860376 1
1.8%
35.289001 1
1.8%
ValueCountFrequency (%)
35.492657 1
1.8%
35.4417243 1
1.8%
35.441061 1
1.8%
35.438712 1
1.8%
35.427098 1
1.8%
35.417768 1
1.8%
35.416548 1
1.8%
35.416182 1
1.8%
35.415278 2
3.6%
35.414135 1
1.8%

경도
Real number (ℝ)

Distinct53
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.90309
Minimum127.74856
Maximum128.07906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-21T10:19:50.331515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.74856
5-th percentile127.75409
Q1127.83661
median127.89054
Q3127.96898
95-th percentile128.07341
Maximum128.07906
Range0.330498
Interquartile range (IQR)0.1323765

Descriptive statistics

Standard deviation0.096568414
Coefficient of variation (CV)0.00075501236
Kurtosis-0.72081971
Mean127.90309
Median Absolute Deviation (MAD)0.0764235
Skewness0.15743174
Sum7162.573
Variance0.0093254585
MonotonicityNot monotonic
2024-04-21T10:19:50.638088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.079063 2
 
3.6%
127.876579 2
 
3.6%
127.836605 2
 
3.6%
127.876211 1
 
1.8%
127.754358 1
 
1.8%
127.837242 1
 
1.8%
127.983691 1
 
1.8%
127.967246 1
 
1.8%
127.903193 1
 
1.8%
127.936154 1
 
1.8%
Other values (43) 43
76.8%
ValueCountFrequency (%)
127.748565 1
1.8%
127.7513347 1
1.8%
127.753573 1
1.8%
127.754269 1
1.8%
127.754358 1
1.8%
127.755628 1
1.8%
127.75632 1
1.8%
127.759005 1
1.8%
127.788204 1
1.8%
127.824986 1
1.8%
ValueCountFrequency (%)
128.079063 2
3.6%
128.075433 1
1.8%
128.072731 1
1.8%
128.072304 1
1.8%
128.067431 1
1.8%
128.063367 1
1.8%
127.987909 1
1.8%
127.983691 1
1.8%
127.974063 1
1.8%
127.969386 1
1.8%

객실수
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.321429
Minimum3
Maximum108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-21T10:19:50.747442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile7.75
Q111
median15
Q318.25
95-th percentile41
Maximum108
Range105
Interquartile range (IQR)7.25

Descriptive statistics

Standard deviation15.844824
Coefficient of variation (CV)0.86482469
Kurtosis19.562196
Mean18.321429
Median Absolute Deviation (MAD)4
Skewness4.0257553
Sum1026
Variance251.05844
MonotonicityNot monotonic
2024-04-21T10:19:50.859204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
12 6
 
10.7%
18 6
 
10.7%
11 5
 
8.9%
17 5
 
8.9%
10 4
 
7.1%
15 4
 
7.1%
14 3
 
5.4%
19 3
 
5.4%
20 3
 
5.4%
13 2
 
3.6%
Other values (14) 15
26.8%
ValueCountFrequency (%)
3 1
 
1.8%
4 1
 
1.8%
7 1
 
1.8%
8 2
 
3.6%
9 1
 
1.8%
10 4
7.1%
11 5
8.9%
12 6
10.7%
13 2
 
3.6%
14 3
5.4%
ValueCountFrequency (%)
108 1
 
1.8%
62 1
 
1.8%
56 1
 
1.8%
36 1
 
1.8%
32 1
 
1.8%
26 1
 
1.8%
24 1
 
1.8%
22 1
 
1.8%
20 3
5.4%
19 3
5.4%

담당기관
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
경상남도 산청군청
56 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상남도 산청군청
2nd row경상남도 산청군청
3rd row경상남도 산청군청
4th row경상남도 산청군청
5th row경상남도 산청군청

Common Values

ValueCountFrequency (%)
경상남도 산청군청 56
100.0%

Length

2024-04-21T10:19:50.963832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:19:51.041010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 56
50.0%
산청군청 56
50.0%

담당부서
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
항노화관광국 환경위생과
56 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row항노화관광국 환경위생과
2nd row항노화관광국 환경위생과
3rd row항노화관광국 환경위생과
4th row항노화관광국 환경위생과
5th row항노화관광국 환경위생과

Common Values

ValueCountFrequency (%)
항노화관광국 환경위생과 56
100.0%

Length

2024-04-21T10:19:51.132395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:19:51.224138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
항노화관광국 56
50.0%
환경위생과 56
50.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
Minimum2024-04-16 00:00:00
Maximum2024-04-16 00:00:00
2024-04-21T10:19:51.288183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:51.364115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-21T10:19:46.278840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:45.306350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:45.649179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:45.985722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:46.347809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:45.430845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:45.741040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:46.057182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:46.420119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:45.510651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:45.833886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:46.131534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:46.511980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:45.582492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:45.917686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:19:46.208338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:19:51.429430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명업소명주소영업자연락처홈페이지위도경도객실수
연번1.0000.9901.0000.9460.9460.9130.4970.2590.3560.261
업종명0.9901.0001.0001.0001.0000.0000.0000.5260.5280.721
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주소0.9461.0001.0001.0000.9990.9971.0001.0001.0001.000
영업자0.9461.0001.0000.9991.0000.9971.0001.0001.0000.982
연락처0.9130.0001.0000.9970.9971.0001.0000.0000.0000.981
홈페이지0.4970.0001.0001.0001.0001.0001.0000.8110.0000.961
위도0.2590.5261.0001.0001.0000.0000.8111.0000.8760.088
경도0.3560.5281.0001.0001.0000.0000.0000.8761.0000.000
객실수0.2610.7211.0001.0000.9820.9810.9610.0880.0001.000
2024-04-21T10:19:51.544738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도객실수업종명
연번1.0000.016-0.273-0.0230.840
위도0.0161.0000.0990.1050.371
경도-0.2730.0991.000-0.0650.492
객실수-0.0230.105-0.0651.0000.527
업종명0.8400.3710.4920.5271.000

Missing values

2024-04-21T10:19:46.636357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:19:46.776218image/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.
2024-04-21T10:19:46.885035image/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

연번업종명업소명주소영업자연락처홈페이지위도경도객실수담당기관담당부서데이터기준일자
01숙박업(일반)경호장여관경상남도 산청군 산청읍 친환경로 2674-10권용순055-973-2625<NA>35.416182127.8762117경상남도 산청군청항노화관광국 환경위생과2024-04-16
12숙박업(일반)백만장여관경상남도 산청군 생초면 산수로 1038이응남055-973-1661<NA>35.492657127.8319910경상남도 산청군청항노화관광국 환경위생과2024-04-16
23숙박업(일반)지리산계곡호텔경상남도 산청군 시천면 지리산대로 555최재경055-972-1441<NA>35.291416127.75562818경상남도 산청군청항노화관광국 환경위생과2024-04-16
34숙박업(일반)산청파크장경상남도 산청군 산청읍 웅석봉로 38이현실055-973-6840<NA>35.414135127.87264822경상남도 산청군청항노화관광국 환경위생과2024-04-16
45숙박업(일반)단성모텔경상남도 산청군 단성면 지리산대로3362번길 17최정자055-973-6616<NA>35.30241127.96426915경상남도 산청군청항노화관광국 환경위생과2024-04-16
56숙박업(일반)양천장여관경상남도 산청군 생비량면 비량로411번길 2-5하형근055-972-2540<NA>35.36296128.06336715경상남도 산청군청항노화관광국 환경위생과2024-04-16
67숙박업(일반)경호파크장경상남도 산청군 신안면 원지강변로 21이민선055-973-5204<NA>35.302992127.96938611경상남도 산청군청항노화관광국 환경위생과2024-04-16
78숙박업(일반)프라하경상남도 산청군 신안면 원지강변로61번길 9심재숙 외 1명055-973-7680<NA>35.301102127.96891518경상남도 산청군청항노화관광국 환경위생과2024-04-16
89숙박업(일반)덕산장여관경상남도 산청군 시천면 남명로 220-2김점남055-972-8610<NA>35.276982127.8386713경상남도 산청군청항노화관광국 환경위생과2024-04-16
910숙박업(일반)씨에프(CF)모텔경상남도 산청군 신안면 원지강변로61번길 10임은주055-972-2299<NA>35.301105127.96921224경상남도 산청군청항노화관광국 환경위생과2024-04-16
연번업종명업소명주소영업자연락처홈페이지위도경도객실수담당기관담당부서데이터기준일자
4647숙박업(생활)킹모텔경상남도 산청군 산청읍 꽃봉산로 132최윤자055-973-7645<NA>35.41227127.87897132경상남도 산청군청항노화관광국 환경위생과2024-04-16
4748숙박업(생활)산청한방가족호텔경상남도 산청군 금서면 동의보감로479번길 43심재범055-972-7000http://www.thesancheong.com35.438712127.827708108경상남도 산청군청항노화관광국 환경위생과2024-04-16
4849숙박업(생활)지리산리조트 주식회사경상남도 산청군 시천면 지리산대로511번길 11-31홍일근055-711-7015<NA>35.297338127.7535733경상남도 산청군청항노화관광국 환경위생과2024-04-16
4950숙박업(생활)(주)지리산청계수련원경상남도 산청군 단성면 호암로 915김병기0507-1475-9956https://christmasvillage1.modoo.at35.340559127.90724612경상남도 산청군청항노화관광국 환경위생과2024-04-16
5051숙박업(생활)라움펜션경상남도 산청군 단성면 호암로701번길 155-14, 외 1필지(155-22)이미연0507-1373-3007http://scraum.com35.334134127.89429610경상남도 산청군청항노화관광국 환경위생과2024-04-16
5152숙박업(생활)하나로 숙박경상남도 산청군 시천면 지리산대로 629, 하나로리포스하하봉<NA>http://www.hanarorepos.com35.286038127.75133511경상남도 산청군청항노화관광국 환경위생과2024-04-16
5253숙박업(생활)휴롬산청빌리지경상남도 산청군 금서면 동의보감로 645-40 (주)휴롬 산청빌리지 외 1필지(645-59)김재원055-720-9000https://huromville.com35.441724127.82498656경상남도 산청군청항노화관광국 환경위생과2024-04-16
5354숙박업(생활)바람꽃펜션경상남도 산청군 산청읍 호암로1253번길 26-17신태경<NA>https://staywindflower.modoo.at35.363913127.9058244경상남도 산청군청항노화관광국 환경위생과2024-04-16
5455숙박업(생활)지리산황토치유마을경상남도 산청군 시천면 지리산대로511번길 13이재숙055-973-8276http://www.nhvillage.co.kr35.2933127.7563236경상남도 산청군청항노화관광국 환경위생과2024-04-16
5556숙박업(생활)서지농원경상남도 산청군 시천면 반천로 211-102, 서지관광농원노재우055-972-1451http://www.seojiro.com/35.229896127.78820410경상남도 산청군청항노화관광국 환경위생과2024-04-16