Overview

Dataset statistics

Number of variables10
Number of observations260
Missing cells64
Missing cells (%)2.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.2 KiB
Average record size in memory83.5 B

Variable types

Categorical1
DateTime1
Text4
Numeric3
Boolean1

Dataset

Description경상남도 김해시 관내 숙박업소 현황 정보(사업장명, 소재지 전화번호, 지번주소, 도로명주소, 양실수 등 )에 대한 데이터 제공
URLhttps://www.data.go.kr/data/15000587/fileData.do

Alerts

발한실 has constant value ""Constant
객실수 is highly overall correlated with 양실수High correlation
양실수 is highly overall correlated with 객실수High correlation
업종명 is highly imbalanced (71.4%)Imbalance
소재지전화 has 63 (24.2%) missing valuesMissing
영업소 주소(도로명) has unique valuesUnique
영업소 주소(지번) has unique valuesUnique
한실수 has 203 (78.1%) zerosZeros
양실수 has 3 (1.2%) zerosZeros

Reproduction

Analysis started2023-12-12 05:53:10.264058
Analysis finished2023-12-12 05:53:12.037740
Duration1.77 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
숙박업(일반)
247 
숙박업(생활)
 
13

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) 247
95.0%
숙박업(생활) 13
 
5.0%

Length

2023-12-12T14:53:12.138596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:53:12.269426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업(일반 247
95.0%
숙박업(생활 13
 
5.0%

신고일자
Date

Distinct178
Distinct (%)68.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum1999-08-10 00:00:00
Maximum2023-02-06 00:00:00
2023-12-12T14:53:12.437268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:53:12.624851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소명
Text

Distinct254
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T14:53:12.939961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length5.8307692
Min length2

Characters and Unicode

Total characters1516
Distinct characters271
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

Unique248 ?
Unique (%)95.4%

Sample

1st row허니문장여관
2nd row프로포즈모텔
3rd row캐슬모텔
4th row대명여관
5th row초원장여관
ValueCountFrequency (%)
호텔 16
 
5.2%
hotel 4
 
1.3%
더 3
 
1.0%
덴바스타 2
 
0.6%
모텔 2
 
0.6%
꿈의궁전 2
 
0.6%
김해삼계점 2
 
0.6%
n모텔 2
 
0.6%
호텔101 2
 
0.6%
k모텔 2
 
0.6%
Other values (270) 272
88.0%
2023-12-12T14:53:13.419108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 169
 
11.1%
모 91
 
6.0%
호 82
 
5.4%
여 59
 
3.9%
49
 
3.2%
관 45
 
3.0%
스 42
 
2.8%
장 40
 
2.6%
이 30
 
2.0%
인 28
 
1.8%
Other values (261) 881
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1250
82.5%
Uppercase Letter 83
 
5.5%
Space Separator 49
 
3.2%
Lowercase Letter 47
 
3.1%
Decimal Number 41
 
2.7%
Open Punctuation 18
 
1.2%
Close Punctuation 18
 
1.2%
Dash Punctuation 6
 
0.4%
Other Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 169
 
13.5%
모 91
 
7.3%
호 82
 
6.6%
여 59
 
4.7%
관 45
 
3.6%
스 42
 
3.4%
장 40
 
3.2%
이 30
 
2.4%
인 28
 
2.2%
라 21
 
1.7%
Other values (214) 643
51.4%
Uppercase Letter
ValueCountFrequency (%)
N 9
 
10.8%
H 7
 
8.4%
M 7
 
8.4%
E 7
 
8.4%
O 6
 
7.2%
T 6
 
7.2%
W 5
 
6.0%
A 5
 
6.0%
U 4
 
4.8%
S 4
 
4.8%
Other values (12) 23
27.7%
Lowercase Letter
ValueCountFrequency (%)
e 9
19.1%
t 9
19.1%
o 5
10.6%
w 4
8.5%
l 4
8.5%
s 3
 
6.4%
a 3
 
6.4%
n 3
 
6.4%
i 2
 
4.3%
y 2
 
4.3%
Other values (2) 3
 
6.4%
Decimal Number
ValueCountFrequency (%)
1 9
22.0%
7 7
17.1%
0 7
17.1%
2 7
17.1%
5 5
12.2%
9 4
9.8%
4 2
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
/ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1250
82.5%
Common 136
 
9.0%
Latin 130
 
8.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 169
 
13.5%
모 91
 
7.3%
호 82
 
6.6%
여 59
 
4.7%
관 45
 
3.6%
스 42
 
3.4%
장 40
 
3.2%
이 30
 
2.4%
인 28
 
2.2%
라 21
 
1.7%
Other values (214) 643
51.4%
Latin
ValueCountFrequency (%)
e 9
 
6.9%
t 9
 
6.9%
N 9
 
6.9%
H 7
 
5.4%
M 7
 
5.4%
E 7
 
5.4%
O 6
 
4.6%
T 6
 
4.6%
o 5
 
3.8%
W 5
 
3.8%
Other values (24) 60
46.2%
Common
ValueCountFrequency (%)
49
36.0%
( 18
 
13.2%
) 18
 
13.2%
1 9
 
6.6%
7 7
 
5.1%
0 7
 
5.1%
2 7
 
5.1%
- 6
 
4.4%
5 5
 
3.7%
9 4
 
2.9%
Other values (3) 6
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1250
82.5%
ASCII 266
 
17.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 169
 
13.5%
모 91
 
7.3%
호 82
 
6.6%
여 59
 
4.7%
관 45
 
3.6%
스 42
 
3.4%
장 40
 
3.2%
이 30
 
2.4%
인 28
 
2.2%
라 21
 
1.7%
Other values (214) 643
51.4%
ASCII
ValueCountFrequency (%)
49
 
18.4%
( 18
 
6.8%
) 18
 
6.8%
e 9
 
3.4%
t 9
 
3.4%
N 9
 
3.4%
1 9
 
3.4%
H 7
 
2.6%
M 7
 
2.6%
7 7
 
2.6%
Other values (37) 124
46.6%

영업소 주소(도로명)
Text

UNIQUE 

Distinct260
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T14:53:13.690619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length41
Mean length26.323077
Min length19

Characters and Unicode

Total characters6844
Distinct characters140
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

Unique260 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 가락로15번길 3-2 (부원동)
2nd row경상남도 김해시 분성로 327-12 (서상동)
3rd row경상남도 김해시 인제로91번길 7 (어방동)
4th row경상남도 김해시 분성로336번길 8-5 (서상동)
5th row경상남도 김해시 가락로38번길 7-14 (부원동)
ValueCountFrequency (%)
경상남도 260
19.2%
김해시 260
19.2%
부원동 62
 
4.6%
어방동 47
 
3.5%
대청동 32
 
2.4%
진영읍 23
 
1.7%
서상동 21
 
1.6%
삼계동 19
 
1.4%
삼계로55번길 15
 
1.1%
삼방동 11
 
0.8%
Other values (300) 602
44.5%
2023-12-12T14:53:14.144039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1092
 
16.0%
해 293
 
4.3%
김 292
 
4.3%
상 286
 
4.2%
남 261
 
3.8%
경 260
 
3.8%
도 260
 
3.8%
시 260
 
3.8%
로 257
 
3.8%
1 245
 
3.6%
Other values (130) 3338
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3922
57.3%
Decimal Number 1210
 
17.7%
Space Separator 1092
 
16.0%
Close Punctuation 221
 
3.2%
Open Punctuation 221
 
3.2%
Dash Punctuation 103
 
1.5%
Other Punctuation 67
 
1.0%
Math Symbol 6
 
0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
해 293
 
7.5%
김 292
 
7.4%
상 286
 
7.3%
남 261
 
6.7%
경 260
 
6.6%
도 260
 
6.6%
시 260
 
6.6%
로 257
 
6.6%
동 222
 
5.7%
번 214
 
5.5%
Other values (112) 1317
33.6%
Decimal Number
ValueCountFrequency (%)
1 245
20.2%
2 162
13.4%
5 155
12.8%
7 136
11.2%
6 129
10.7%
3 124
10.2%
4 75
 
6.2%
0 69
 
5.7%
8 62
 
5.1%
9 53
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
1092
100.0%
Close Punctuation
ValueCountFrequency (%)
) 221
100.0%
Open Punctuation
ValueCountFrequency (%)
( 221
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%
Other Punctuation
ValueCountFrequency (%)
, 67
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3922
57.3%
Common 2920
42.7%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
해 293
 
7.5%
김 292
 
7.4%
상 286
 
7.3%
남 261
 
6.7%
경 260
 
6.6%
도 260
 
6.6%
시 260
 
6.6%
로 257
 
6.6%
동 222
 
5.7%
번 214
 
5.5%
Other values (112) 1317
33.6%
Common
ValueCountFrequency (%)
1092
37.4%
1 245
 
8.4%
) 221
 
7.6%
( 221
 
7.6%
2 162
 
5.5%
5 155
 
5.3%
7 136
 
4.7%
6 129
 
4.4%
3 124
 
4.2%
- 103
 
3.5%
Other values (6) 332
 
11.4%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3922
57.3%
ASCII 2922
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1092
37.4%
1 245
 
8.4%
) 221
 
7.6%
( 221
 
7.6%
2 162
 
5.5%
5 155
 
5.3%
7 136
 
4.7%
6 129
 
4.4%
3 124
 
4.2%
- 103
 
3.5%
Other values (8) 334
 
11.4%
Hangul
ValueCountFrequency (%)
해 293
 
7.5%
김 292
 
7.4%
상 286
 
7.3%
남 261
 
6.7%
경 260
 
6.6%
도 260
 
6.6%
시 260
 
6.6%
로 257
 
6.6%
동 222
 
5.7%
번 214
 
5.5%
Other values (112) 1317
33.6%

영업소 주소(지번)
Text

UNIQUE 

Distinct260
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T14:53:14.615967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length35
Mean length20.815385
Min length15

Characters and Unicode

Total characters5412
Distinct characters126
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

Unique260 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 부원동 604-25
2nd row경상남도 김해시 서상동 94-59
3rd row경상남도 김해시 어방동 1094-7
4th row경상남도 김해시 서상동 135
5th row경상남도 김해시 부원동 849-18
ValueCountFrequency (%)
경상남도 260
23.2%
김해시 260
23.2%
부원동 62
 
5.5%
어방동 47
 
4.2%
대청동 37
 
3.3%
진영읍 23
 
2.0%
서상동 21
 
1.9%
삼계동 19
 
1.7%
삼방동 11
 
1.0%
진영리 10
 
0.9%
Other values (327) 373
33.2%
2023-12-12T14:53:15.178303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1122
20.7%
상 285
 
5.3%
1 264
 
4.9%
남 261
 
4.8%
김 261
 
4.8%
해 261
 
4.8%
경 260
 
4.8%
도 260
 
4.8%
시 260
 
4.8%
- 245
 
4.5%
Other values (116) 1933
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2836
52.4%
Decimal Number 1185
21.9%
Space Separator 1122
 
20.7%
Dash Punctuation 245
 
4.5%
Other Punctuation 18
 
0.3%
Uppercase Letter 3
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 285
10.0%
남 261
9.2%
김 261
9.2%
해 261
9.2%
경 260
9.2%
도 260
9.2%
시 260
9.2%
동 228
 
8.0%
원 66
 
2.3%
부 64
 
2.3%
Other values (97) 630
22.2%
Decimal Number
ValueCountFrequency (%)
1 264
22.3%
0 139
11.7%
5 128
10.8%
6 118
10.0%
2 110
9.3%
3 102
 
8.6%
8 85
 
7.2%
7 82
 
6.9%
4 80
 
6.8%
9 77
 
6.5%
Other Punctuation
ValueCountFrequency (%)
, 17
94.4%
. 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
1122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 245
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2836
52.4%
Common 2573
47.5%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 285
10.0%
남 261
9.2%
김 261
9.2%
해 261
9.2%
경 260
9.2%
도 260
9.2%
시 260
9.2%
동 228
 
8.0%
원 66
 
2.3%
부 64
 
2.3%
Other values (97) 630
22.2%
Common
ValueCountFrequency (%)
1122
43.6%
1 264
 
10.3%
- 245
 
9.5%
0 139
 
5.4%
5 128
 
5.0%
6 118
 
4.6%
2 110
 
4.3%
3 102
 
4.0%
8 85
 
3.3%
7 82
 
3.2%
Other values (7) 178
 
6.9%
Latin
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2836
52.4%
ASCII 2576
47.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1122
43.6%
1 264
 
10.2%
- 245
 
9.5%
0 139
 
5.4%
5 128
 
5.0%
6 118
 
4.6%
2 110
 
4.3%
3 102
 
4.0%
8 85
 
3.3%
7 82
 
3.2%
Other values (9) 181
 
7.0%
Hangul
ValueCountFrequency (%)
상 285
10.0%
남 261
9.2%
김 261
9.2%
해 261
9.2%
경 260
9.2%
도 260
9.2%
시 260
9.2%
동 228
 
8.0%
원 66
 
2.3%
부 64
 
2.3%
Other values (97) 630
22.2%

소재지전화
Text

MISSING 

Distinct196
Distinct (%)99.5%
Missing63
Missing (%)24.2%
Memory size2.2 KiB
2023-12-12T14:53:15.427764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.994924
Min length11

Characters and Unicode

Total characters2363
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

Unique195 ?
Unique (%)99.0%

Sample

1st row055-902-4200
2nd row055-333-3133
3rd row055-332-1551
4th row055-333-4201
5th row055-336-3023
ValueCountFrequency (%)
055-335-5705 2
 
1.0%
055-339-3071 1
 
0.5%
055-331-9011 1
 
0.5%
055-331-7177 1
 
0.5%
055-339-3677 1
 
0.5%
055-339-7143 1
 
0.5%
055-313-3537 1
 
0.5%
055-334-8166 1
 
0.5%
055-313-9090 1
 
0.5%
055-322-9624 1
 
0.5%
Other values (186) 186
94.4%
2023-12-12T14:53:15.908434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 484
20.5%
3 398
16.8%
- 394
16.7%
0 306
12.9%
2 172
 
7.3%
1 142
 
6.0%
6 108
 
4.6%
4 101
 
4.3%
7 99
 
4.2%
9 89
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1969
83.3%
Dash Punctuation 394
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 484
24.6%
3 398
20.2%
0 306
15.5%
2 172
 
8.7%
1 142
 
7.2%
6 108
 
5.5%
4 101
 
5.1%
7 99
 
5.0%
9 89
 
4.5%
8 70
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 394
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2363
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 484
20.5%
3 398
16.8%
- 394
16.7%
0 306
12.9%
2 172
 
7.3%
1 142
 
6.0%
6 108
 
4.6%
4 101
 
4.3%
7 99
 
4.2%
9 89
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2363
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 484
20.5%
3 398
16.8%
- 394
16.7%
0 306
12.9%
2 172
 
7.3%
1 142
 
6.0%
6 108
 
4.6%
4 101
 
4.3%
7 99
 
4.2%
9 89
 
3.8%

객실수
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.634615
Minimum3
Maximum181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T14:53:16.079055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile8
Q117
median26
Q335
95-th percentile45
Maximum181
Range178
Interquartile range (IQR)18

Descriptive statistics

Standard deviation15.251595
Coefficient of variation (CV)0.57262306
Kurtosis39.941833
Mean26.634615
Median Absolute Deviation (MAD)9
Skewness4.2445637
Sum6925
Variance232.61115
MonotonicityNot monotonic
2023-12-12T14:53:16.229872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35 19
 
7.3%
27 14
 
5.4%
40 11
 
4.2%
28 11
 
4.2%
29 11
 
4.2%
18 11
 
4.2%
19 10
 
3.8%
16 10
 
3.8%
25 10
 
3.8%
15 9
 
3.5%
Other values (41) 144
55.4%
ValueCountFrequency (%)
3 1
 
0.4%
5 4
1.5%
6 2
 
0.8%
7 5
1.9%
8 4
1.5%
9 1
 
0.4%
10 8
3.1%
11 4
1.5%
12 2
 
0.8%
13 7
2.7%
ValueCountFrequency (%)
181 1
 
0.4%
79 1
 
0.4%
72 1
 
0.4%
55 1
 
0.4%
54 1
 
0.4%
50 1
 
0.4%
49 2
0.8%
48 2
0.8%
46 1
 
0.4%
45 3
1.2%

한실수
Real number (ℝ)

ZEROS 

Distinct16
Distinct (%)6.2%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean1.1312741
Minimum0
Maximum26
Zeros203
Zeros (%)78.1%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T14:53:16.674122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7
Maximum26
Range26
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.9619922
Coefficient of variation (CV)2.6182798
Kurtosis23.344621
Mean1.1312741
Median Absolute Deviation (MAD)0
Skewness4.121567
Sum293
Variance8.773398
MonotonicityNot monotonic
2023-12-12T14:53:16.793956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 203
78.1%
3 10
 
3.8%
4 8
 
3.1%
5 8
 
3.1%
1 8
 
3.1%
7 6
 
2.3%
2 5
 
1.9%
10 2
 
0.8%
8 2
 
0.8%
14 1
 
0.4%
Other values (6) 6
 
2.3%
ValueCountFrequency (%)
0 203
78.1%
1 8
 
3.1%
2 5
 
1.9%
3 10
 
3.8%
4 8
 
3.1%
5 8
 
3.1%
6 1
 
0.4%
7 6
 
2.3%
8 2
 
0.8%
9 1
 
0.4%
ValueCountFrequency (%)
26 1
 
0.4%
15 1
 
0.4%
14 1
 
0.4%
13 1
 
0.4%
12 1
 
0.4%
10 2
 
0.8%
9 1
 
0.4%
8 2
 
0.8%
7 6
2.3%
6 1
 
0.4%

양실수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct52
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.507692
Minimum0
Maximum181
Zeros3
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T14:53:16.914727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q116
median25
Q334
95-th percentile44.05
Maximum181
Range181
Interquartile range (IQR)18

Descriptive statistics

Standard deviation15.641864
Coefficient of variation (CV)0.61322143
Kurtosis37.106357
Mean25.507692
Median Absolute Deviation (MAD)9
Skewness4.0256296
Sum6632
Variance244.66789
MonotonicityNot monotonic
2023-12-12T14:53:17.086158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35 16
 
6.2%
27 11
 
4.2%
10 11
 
4.2%
13 10
 
3.8%
18 10
 
3.8%
16 10
 
3.8%
15 10
 
3.8%
33 10
 
3.8%
28 9
 
3.5%
29 9
 
3.5%
Other values (42) 154
59.2%
ValueCountFrequency (%)
0 3
 
1.2%
3 2
 
0.8%
5 5
1.9%
6 2
 
0.8%
7 7
2.7%
8 3
 
1.2%
9 2
 
0.8%
10 11
4.2%
11 2
 
0.8%
12 2
 
0.8%
ValueCountFrequency (%)
181 1
0.4%
79 1
0.4%
72 1
0.4%
55 1
0.4%
54 1
0.4%
50 1
0.4%
49 2
0.8%
48 2
0.8%
46 1
0.4%
45 2
0.8%

발한실
Boolean

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size392.0 B
False
260 
ValueCountFrequency (%)
False 260
100.0%
2023-12-12T14:53:17.230962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-12T14:53:11.363288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:53:10.705499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:53:11.064827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:53:11.456030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:53:10.812186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:53:11.163983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:53:11.566328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:53:10.958921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:53:11.263515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:53:17.306969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명객실수한실수양실수
업종명1.0000.1950.2350.279
객실수0.1951.0000.0000.995
한실수0.2350.0001.0000.000
양실수0.2790.9950.0001.000
2023-12-12T14:53:17.438170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객실수한실수양실수업종명
객실수1.0000.0110.9700.139
한실수0.0111.000-0.1860.249
양실수0.970-0.1861.0000.199
업종명0.1390.2490.1991.000

Missing values

2023-12-12T14:53:11.706517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:53:11.879112image/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.
2023-12-12T14:53:11.985383image/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

업종명신고일자업소명영업소 주소(도로명)영업소 주소(지번)소재지전화객실수한실수양실수발한실
0숙박업(일반)1999-10-07허니문장여관경상남도 김해시 가락로15번길 3-2 (부원동)경상남도 김해시 부원동 604-25055-902-420013013N
1숙박업(일반)1999-08-10프로포즈모텔경상남도 김해시 분성로 327-12 (서상동)경상남도 김해시 서상동 94-59<NA>17017N
2숙박업(일반)1999-11-22캐슬모텔경상남도 김해시 인제로91번길 7 (어방동)경상남도 김해시 어방동 1094-7055-333-313327027N
3숙박업(일반)2000-03-16대명여관경상남도 김해시 분성로336번길 8-5 (서상동)경상남도 김해시 서상동 135055-332-155110010N
4숙박업(일반)2000-03-16초원장여관경상남도 김해시 가락로38번길 7-14 (부원동)경상남도 김해시 부원동 849-18055-333-420110010N
5숙박업(일반)2000-03-16나나여관경상남도 김해시 분성로 305 (서상동)경상남도 김해시 서상동 273-4055-336-302313013N
6숙박업(일반)2000-03-16미광여인숙경상남도 김해시 가락로64번길 1 (부원동)경상남도 김해시 부원동 832-1055-333-559914014N
7숙박업(일반)2000-03-16한울모텔경상남도 김해시 분성로318번길 33 (부원동)경상남도 김해시 부원동 857-3<NA>16016N
8숙박업(일반)2000-03-16금단장여관경상남도 김해시 가락로63번길 26 (서상동)경상남도 김해시 서상동 332-7055-333-127215015N
9숙박업(일반)2000-03-16남문여관경상남도 김해시 가락로7번길 6-3 (부원동)경상남도 김해시 부원동 604-13055-332-16881165N
업종명신고일자업소명영업소 주소(도로명)영업소 주소(지번)소재지전화객실수한실수양실수발한실
250숙박업(생활)2000-03-16마음편한집경상남도 김해시 김해대로2355번길 27 (부원동)경상남도 김해시 부원동 609-15055-321-221615015N
251숙박업(생활)2000-03-16몽마르뜨빌경상남도 김해시 김해대로2355번길 27-1 (부원동)경상남도 김해시 부원동 609-7<NA>15015N
252숙박업(생활)2000-10-04크리스탈빌경상남도 김해시 가락로38번길 7-15 (부원동)경상남도 김해시 부원동 849-3<NA>18018N
253숙박업(생활)2004-06-12누리마루모텔경상남도 김해시 번화1로68번길 9 (대청동, 4,5,6층)경상남도 김해시 대청동 68-9 4,5,6층055-327-771227027N
254숙박업(생활)2010-07-20학송빌경상남도 김해시 가락로 108-7 (서상동)경상남도 김해시 서상동 11-3<NA>10010N
255숙박업(생활)2012-12-17모텔캣츠(Motel CATS)경상남도 김해시 번화1로76번길 16, 601호 (대청리,녹원빌딩)경상남도 김해시 대청동 68-6 녹원빌딩 601호<NA>1477N
256숙박업(생활)2015-06-30은하장모텔경상남도 김해시 가락로 108-11 (서상동)경상남도 김해시 서상동 11-2051-341-898911110N
257숙박업(생활)2016-05-18해피데이경상남도 김해시 인제로170번길 3-20 (어방동)경상남도 김해시 어방동 529-1<NA>26260N
258숙박업(생활)2017-02-07인제 프라임빌경상남도 김해시 인제로 89, 3,4층 (어방동)경상남도 김해시 어방동 1095-13<NA>18018N
259숙박업(생활)2021-02-01한성하우스경상남도 김해시 분성로335번길 12-14, 2~5층 (동상동)경상남도 김해시 동상동 973<NA>26026N