Overview

Dataset statistics

Number of variables5
Number of observations72
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory42.8 B

Variable types

Categorical1
Text3
Numeric1

Dataset

Description경상남도 창녕군 숙박업소 현황에 대한 데이터를 포함하고 있습니다.(업종명, 업소명, 영업소 주소, 소재지 전화번호, 객실수)
URLhttps://www.data.go.kr/data/15025315/fileData.do

Alerts

업종명 has constant value ""Constant

Reproduction

Analysis started2023-12-12 23:46:53.049777
Analysis finished2023-12-12 23:46:53.964915
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
숙박업(일반)
72 

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) 72
100.0%

Length

2023-12-13T08:46:54.032249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:46:54.128588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업(일반 72
100.0%

업소명
Text

Distinct71
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-13T08:46:54.379823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12.5
Mean length5.9027778
Min length3

Characters and Unicode

Total characters425
Distinct characters143
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)97.2%

Sample

1st row춘산여관
2nd row일광여인숙
3rd rowDW모텔
4th row(주)레이크힐스호텔
5th row모텔퀸(MOTEL QUEEN)
ValueCountFrequency (%)
주식회사 3
 
3.8%
m모텔 2
 
2.6%
썸무인호텔 2
 
2.6%
힐마루골프텔 1
 
1.3%
삼성온천호텔 1
 
1.3%
주)키즈스테이호텔인부곡 1
 
1.3%
c.f모텔(씨에프모텔 1
 
1.3%
주)레이크힐스골프텔 1
 
1.3%
러브홀릭 1
 
1.3%
j2모텔 1
 
1.3%
Other values (64) 64
82.1%
2023-12-13T08:46:54.801757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 62
 
14.6%
모 32
 
7.5%
호 28
 
6.6%
인 10
 
2.4%
부 8
 
1.9%
스 8
 
1.9%
온 7
 
1.6%
관 7
 
1.6%
여 7
 
1.6%
주 7
 
1.6%
Other values (133) 249
58.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 381
89.6%
Uppercase Letter 23
 
5.4%
Close Punctuation 6
 
1.4%
Open Punctuation 6
 
1.4%
Space Separator 6
 
1.4%
Other Punctuation 2
 
0.5%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 62
 
16.3%
모 32
 
8.4%
호 28
 
7.3%
인 10
 
2.6%
부 8
 
2.1%
스 8
 
2.1%
온 7
 
1.8%
관 7
 
1.8%
여 7
 
1.8%
주 7
 
1.8%
Other values (109) 205
53.8%
Uppercase Letter
ValueCountFrequency (%)
E 3
 
13.0%
M 3
 
13.0%
U 2
 
8.7%
O 1
 
4.3%
F 1
 
4.3%
C 1
 
4.3%
J 1
 
4.3%
T 1
 
4.3%
L 1
 
4.3%
Q 1
 
4.3%
Other values (8) 8
34.8%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
· 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 381
89.6%
Latin 23
 
5.4%
Common 21
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 62
 
16.3%
모 32
 
8.4%
호 28
 
7.3%
인 10
 
2.6%
부 8
 
2.1%
스 8
 
2.1%
온 7
 
1.8%
관 7
 
1.8%
여 7
 
1.8%
주 7
 
1.8%
Other values (109) 205
53.8%
Latin
ValueCountFrequency (%)
E 3
 
13.0%
M 3
 
13.0%
U 2
 
8.7%
O 1
 
4.3%
F 1
 
4.3%
C 1
 
4.3%
J 1
 
4.3%
T 1
 
4.3%
L 1
 
4.3%
Q 1
 
4.3%
Other values (8) 8
34.8%
Common
ValueCountFrequency (%)
) 6
28.6%
( 6
28.6%
6
28.6%
. 1
 
4.8%
2 1
 
4.8%
· 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 381
89.6%
ASCII 43
 
10.1%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 62
 
16.3%
모 32
 
8.4%
호 28
 
7.3%
인 10
 
2.6%
부 8
 
2.1%
스 8
 
2.1%
온 7
 
1.8%
관 7
 
1.8%
여 7
 
1.8%
주 7
 
1.8%
Other values (109) 205
53.8%
ASCII
ValueCountFrequency (%)
) 6
14.0%
( 6
14.0%
6
14.0%
E 3
 
7.0%
M 3
 
7.0%
U 2
 
4.7%
. 1
 
2.3%
O 1
 
2.3%
F 1
 
2.3%
C 1
 
2.3%
Other values (13) 13
30.2%
None
ValueCountFrequency (%)
· 1
100.0%

영업소 주소(도로명)
Text

Distinct71
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-13T08:46:55.142927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length25.5
Mean length21.527778
Min length19

Characters and Unicode

Total characters1550
Distinct characters72
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)97.2%

Sample

1st row경상남도 창녕군 남지읍 낙동로 503
2nd row경상남도 창녕군 남지읍 남지시장길 10-3
3rd row경상남도 창녕군 부곡면 온천2길 27
4th row경상남도 창녕군 부곡면 온천2길 41
5th row경상남도 창녕군 부곡면 온천1길 49
ValueCountFrequency (%)
경상남도 72
19.9%
창녕군 72
19.9%
부곡면 25
 
6.9%
창녕읍 12
 
3.3%
남지읍 11
 
3.0%
온천중앙로 10
 
2.8%
온천2길 9
 
2.5%
남지중앙1길 6
 
1.7%
대합면 5
 
1.4%
계성면 5
 
1.4%
Other values (101) 134
37.1%
2023-12-13T08:46:55.589168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
289
18.6%
남 94
 
6.1%
창 88
 
5.7%
녕 87
 
5.6%
경 76
 
4.9%
도 75
 
4.8%
상 73
 
4.7%
군 72
 
4.6%
면 49
 
3.2%
1 43
 
2.8%
Other values (62) 604
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1017
65.6%
Space Separator 289
 
18.6%
Decimal Number 219
 
14.1%
Dash Punctuation 23
 
1.5%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 94
 
9.2%
창 88
 
8.7%
녕 87
 
8.6%
경 76
 
7.5%
도 75
 
7.4%
상 73
 
7.2%
군 72
 
7.1%
면 49
 
4.8%
로 38
 
3.7%
길 34
 
3.3%
Other values (48) 331
32.5%
Decimal Number
ValueCountFrequency (%)
1 43
19.6%
2 31
14.2%
5 28
12.8%
3 24
11.0%
4 23
10.5%
6 21
9.6%
9 17
 
7.8%
7 13
 
5.9%
0 13
 
5.9%
8 6
 
2.7%
Space Separator
ValueCountFrequency (%)
289
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1017
65.6%
Common 533
34.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 94
 
9.2%
창 88
 
8.7%
녕 87
 
8.6%
경 76
 
7.5%
도 75
 
7.4%
상 73
 
7.2%
군 72
 
7.1%
면 49
 
4.8%
로 38
 
3.7%
길 34
 
3.3%
Other values (48) 331
32.5%
Common
ValueCountFrequency (%)
289
54.2%
1 43
 
8.1%
2 31
 
5.8%
5 28
 
5.3%
3 24
 
4.5%
- 23
 
4.3%
4 23
 
4.3%
6 21
 
3.9%
9 17
 
3.2%
7 13
 
2.4%
Other values (4) 21
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1017
65.6%
ASCII 533
34.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
289
54.2%
1 43
 
8.1%
2 31
 
5.8%
5 28
 
5.3%
3 24
 
4.5%
- 23
 
4.3%
4 23
 
4.3%
6 21
 
3.9%
9 17
 
3.2%
7 13
 
2.4%
Other values (4) 21
 
3.9%
Hangul
ValueCountFrequency (%)
남 94
 
9.2%
창 88
 
8.7%
녕 87
 
8.6%
경 76
 
7.5%
도 75
 
7.4%
상 73
 
7.2%
군 72
 
7.1%
면 49
 
4.8%
로 38
 
3.7%
길 34
 
3.3%
Other values (48) 331
32.5%

소재지전화
Text

Distinct70
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-13T08:46:55.861352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.013889
Min length12

Characters and Unicode

Total characters865
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

Unique68 ?
Unique (%)94.4%

Sample

1st row055-526-2224
2nd row055-526-2234
3rd row055-536-5555
4th row055-536-5181
5th row055-536-5511
ValueCountFrequency (%)
055-533-5519 2
 
2.8%
055-536-5181 2
 
2.8%
055-532-1255 1
 
1.4%
055-536-5573 1
 
1.4%
055-533-2720 1
 
1.4%
055-521-1083 1
 
1.4%
055-536-6111 1
 
1.4%
055-520-8013 1
 
1.4%
055-536-3448 1
 
1.4%
055-532-0609 1
 
1.4%
Other values (60) 60
83.3%
2023-12-13T08:46:56.247179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 255
29.5%
- 144
16.6%
0 126
14.6%
3 82
 
9.5%
2 68
 
7.9%
6 61
 
7.1%
1 49
 
5.7%
7 27
 
3.1%
8 24
 
2.8%
4 15
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 721
83.4%
Dash Punctuation 144
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 255
35.4%
0 126
17.5%
3 82
 
11.4%
2 68
 
9.4%
6 61
 
8.5%
1 49
 
6.8%
7 27
 
3.7%
8 24
 
3.3%
4 15
 
2.1%
9 14
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 865
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 255
29.5%
- 144
16.6%
0 126
14.6%
3 82
 
9.5%
2 68
 
7.9%
6 61
 
7.1%
1 49
 
5.7%
7 27
 
3.1%
8 24
 
2.8%
4 15
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 865
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 255
29.5%
- 144
16.6%
0 126
14.6%
3 82
 
9.5%
2 68
 
7.9%
6 61
 
7.1%
1 49
 
5.7%
7 27
 
3.1%
8 24
 
2.8%
4 15
 
1.7%

객실수
Real number (ℝ)

Distinct39
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.777778
Minimum8
Maximum238
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-13T08:46:56.394715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile11.55
Q116
median27
Q340
95-th percentile73.75
Maximum238
Range230
Interquartile range (IQR)24

Descriptive statistics

Standard deviation31.569384
Coefficient of variation (CV)0.90774585
Kurtosis23.94844
Mean34.777778
Median Absolute Deviation (MAD)11.5
Skewness4.1226023
Sum2504
Variance996.62598
MonotonicityNot monotonic
2023-12-13T08:46:56.523586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
14 5
 
6.9%
19 4
 
5.6%
15 4
 
5.6%
20 4
 
5.6%
29 4
 
5.6%
30 3
 
4.2%
38 3
 
4.2%
27 3
 
4.2%
13 3
 
4.2%
56 3
 
4.2%
Other values (29) 36
50.0%
ValueCountFrequency (%)
8 1
 
1.4%
9 1
 
1.4%
10 1
 
1.4%
11 1
 
1.4%
12 1
 
1.4%
13 3
4.2%
14 5
6.9%
15 4
5.6%
16 2
 
2.8%
18 2
 
2.8%
ValueCountFrequency (%)
238 1
 
1.4%
105 1
 
1.4%
92 1
 
1.4%
82 1
 
1.4%
67 1
 
1.4%
65 1
 
1.4%
60 2
2.8%
59 1
 
1.4%
58 1
 
1.4%
56 3
4.2%

Interactions

2023-12-13T08:46:53.479661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:46:56.622611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명영업소 주소(도로명)소재지전화객실수
업소명1.0000.9980.9951.000
영업소 주소(도로명)0.9981.0001.0000.000
소재지전화0.9951.0001.0000.000
객실수1.0000.0000.0001.000

Missing values

2023-12-13T08:46:53.815969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:46:53.912524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

업종명업소명영업소 주소(도로명)소재지전화객실수
0숙박업(일반)춘산여관경상남도 창녕군 남지읍 낙동로 503055-526-222411
1숙박업(일반)일광여인숙경상남도 창녕군 남지읍 남지시장길 10-3055-526-22348
2숙박업(일반)DW모텔경상남도 창녕군 부곡면 온천2길 27055-536-555540
3숙박업(일반)(주)레이크힐스호텔경상남도 창녕군 부곡면 온천2길 41055-536-5181105
4숙박업(일반)모텔퀸(MOTEL QUEEN)경상남도 창녕군 부곡면 온천1길 49055-536-551138
5숙박업(일반)주식회사 부곡신라호텔경상남도 창녕군 부곡면 온천중앙로 19055-520-660059
6숙박업(일반)오리온호텔경상남도 창녕군 부곡면 온천1길 35055-536-571160
7숙박업(일반)호텔레인보우경상남도 창녕군 부곡면 온천중앙로 33055-521-577765
8숙박업(일반)썬크루즈경상남도 창녕군 영산면 연지길 26-14055-521-279818
9숙박업(일반)부일온천경상남도 창녕군 부곡면 온천중앙로 62055-536-542038
업종명업소명영업소 주소(도로명)소재지전화객실수
62숙박업(일반)동궁무인텔경상남도 창녕군 도천면 치이골길 56-24055-521-666914
63숙박업(일반)U모텔경상남도 창녕군 도천면 치이골길 56-22055-521-826014
64숙박업(일반)하이츠호텔경상남도 창녕군 남지읍 남지중앙1길 47-9055-521-170046
65숙박업(일반)에스에스무인호텔경상남도 창녕군 대지면 미산길 3-50055-532-233415
66숙박업(일반)문도트호텔경상남도 창녕군 성산면 경남대로 5742-13 (문도트호텔)055-532-088919
67숙박업(일반)제이모텔경상남도 창녕군 대합면 평지퇴산로 432055-533-822812
68숙박업(일반)동정호무인호텔경상남도 창녕군 창녕읍 계성화왕산로 470055-521-661225
69숙박업(일반)썸무인호텔 A동경상남도 창녕군 대지면 경남대로 5055055-533-551913
70숙박업(일반)썸무인호텔 B동경상남도 창녕군 대합면 경남대로 5039-17055-533-551916
71숙박업(일반)크라운모텔경상남도 창녕군 창녕읍 우포1대로 1579055-533-100530