Overview

Dataset statistics

Number of variables15
Number of observations46
Missing cells2
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory125.9 B

Variable types

Numeric2
Categorical6
Text6
Unsupported1

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 순번High correlation
작성일 is highly imbalanced (84.9%)Imbalance
등급 has 1 (2.2%) missing valuesMissing
부대시설 has 1 (2.2%) missing valuesMissing
순번 has unique valuesUnique
상호명 has unique valuesUnique
등급 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:14:26.725321
Analysis finished2024-03-14 02:14:27.878014
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.5
Minimum1
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-14T11:14:27.936759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.25
Q112.25
median23.5
Q334.75
95-th percentile43.75
Maximum46
Range45
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation13.422618
Coefficient of variation (CV)0.57117522
Kurtosis-1.2
Mean23.5
Median Absolute Deviation (MAD)11.5
Skewness0
Sum1081
Variance180.16667
MonotonicityStrictly increasing
2024-03-14T11:14:28.044656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 1
 
2.2%
36 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
34 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
46 1
2.2%
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%

시군명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size500.0 B
전주시
16 
군산시
12 
남원시
7 
무주군
5 
부안군
3 
Other values (3)
3 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique3 ?
Unique (%)6.5%

Sample

1st row전주시
2nd row전주시
3rd row전주시
4th row완주군
5th row익산시

Common Values

ValueCountFrequency (%)
전주시 16
34.8%
군산시 12
26.1%
남원시 7
15.2%
무주군 5
 
10.9%
부안군 3
 
6.5%
완주군 1
 
2.2%
익산시 1
 
2.2%
정읍시 1
 
2.2%

Length

2024-03-14T11:14:28.196649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:14:28.307407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전주시 16
34.8%
군산시 12
26.1%
남원시 7
15.2%
무주군 5
 
10.9%
부안군 3
 
6.5%
완주군 1
 
2.2%
익산시 1
 
2.2%
정읍시 1
 
2.2%

상호명
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T11:14:28.506800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.5217391
Min length4

Characters and Unicode

Total characters346
Distinct characters113
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row풍남관광호텔
2nd row전주코아호텔
3rd row전주관광호텔
4th row대둔산관광호텔
5th row익산비즈니스관광호텔
ValueCountFrequency (%)
풍남관광호텔 1
 
2.1%
호텔티롤 1
 
2.1%
베스트웨스턴군산호텔 1
 
2.1%
전주영화호텔 1
 
2.1%
전주한옥태조궁관광호텔 1
 
2.1%
로니관광호텔 1
 
2.1%
진스호스텔 1
 
2.1%
궁관광호텔 1
 
2.1%
째즈어라운드호텔 1
 
2.1%
㈜호텔르윈 1
 
2.1%
Other values (38) 38
79.2%
2024-03-14T11:14:28.834636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
호 36
 
10.4%
텔 36
 
10.4%
관 19
 
5.5%
광 19
 
5.5%
스 18
 
5.2%
리 15
 
4.3%
산 15
 
4.3%
주 9
 
2.6%
트 9
 
2.6%
조 5
 
1.4%
Other values (103) 165
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 341
98.6%
Space Separator 2
 
0.6%
Uppercase Letter 2
 
0.6%
Other Symbol 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 36
 
10.6%
텔 36
 
10.6%
관 19
 
5.6%
광 19
 
5.6%
스 18
 
5.3%
리 15
 
4.4%
산 15
 
4.4%
주 9
 
2.6%
트 9
 
2.6%
조 5
 
1.5%
Other values (99) 160
46.9%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
J 1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 342
98.8%
Common 2
 
0.6%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 36
 
10.5%
텔 36
 
10.5%
관 19
 
5.6%
광 19
 
5.6%
스 18
 
5.3%
리 15
 
4.4%
산 15
 
4.4%
주 9
 
2.6%
트 9
 
2.6%
조 5
 
1.5%
Other values (100) 161
47.1%
Latin
ValueCountFrequency (%)
S 1
50.0%
J 1
50.0%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 341
98.6%
ASCII 4
 
1.2%
None 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
호 36
 
10.6%
텔 36
 
10.6%
관 19
 
5.6%
광 19
 
5.6%
스 18
 
5.3%
리 15
 
4.4%
산 15
 
4.4%
주 9
 
2.6%
트 9
 
2.6%
조 5
 
1.5%
Other values (99) 160
46.9%
ASCII
ValueCountFrequency (%)
2
50.0%
S 1
25.0%
J 1
25.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

업종별
Categorical

Distinct4
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
관광호텔
31 
휴양콘도
6 
가족호텔
5 
호스텔
4 

Length

Max length4
Median length4
Mean length3.9130435
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광호텔 31
67.4%
휴양콘도 6
 
13.0%
가족호텔 5
 
10.9%
호스텔 4
 
8.7%

Length

2024-03-14T11:14:28.944860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:14:29.024177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광호텔 31
67.4%
휴양콘도 6
 
13.0%
가족호텔 5
 
10.9%
호스텔 4
 
8.7%

도로명주소
Text

Distinct43
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T11:14:29.242010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length14.847826
Min length10

Characters and Unicode

Total characters683
Distinct characters92
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

Unique41 ?
Unique (%)89.1%

Sample

1st row전주시 완산구 전주객사2길 45-7
2nd row전주시 완산구 노송광장로 51
3rd row전주시 완산구 전주객사5길 44-5
4th row완주군 운주면 대둔산공원길 37
5th row익산시 인북로 10
ValueCountFrequency (%)
전주시 16
 
9.5%
완산구 13
 
7.7%
군산시 12
 
7.1%
남원시 7
 
4.2%
무주군 5
 
3.0%
185 3
 
1.8%
변산면 3
 
1.8%
부안군 3
 
1.8%
덕진구 3
 
1.8%
만선로 3
 
1.8%
Other values (88) 100
59.5%
2024-03-14T11:14:29.560508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
122
 
17.9%
산 37
 
5.4%
시 37
 
5.4%
주 30
 
4.4%
5 27
 
4.0%
1 26
 
3.8%
길 24
 
3.5%
전 24
 
3.5%
4 22
 
3.2%
로 22
 
3.2%
Other values (82) 312
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 409
59.9%
Decimal Number 138
 
20.2%
Space Separator 122
 
17.9%
Dash Punctuation 14
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 37
 
9.0%
시 37
 
9.0%
주 30
 
7.3%
길 24
 
5.9%
전 24
 
5.9%
로 22
 
5.4%
군 21
 
5.1%
구 17
 
4.2%
완 14
 
3.4%
면 14
 
3.4%
Other values (70) 169
41.3%
Decimal Number
ValueCountFrequency (%)
5 27
19.6%
1 26
18.8%
4 22
15.9%
2 19
13.8%
7 10
 
7.2%
3 10
 
7.2%
0 8
 
5.8%
8 7
 
5.1%
6 6
 
4.3%
9 3
 
2.2%
Space Separator
ValueCountFrequency (%)
122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 409
59.9%
Common 274
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 37
 
9.0%
시 37
 
9.0%
주 30
 
7.3%
길 24
 
5.9%
전 24
 
5.9%
로 22
 
5.4%
군 21
 
5.1%
구 17
 
4.2%
완 14
 
3.4%
면 14
 
3.4%
Other values (70) 169
41.3%
Common
ValueCountFrequency (%)
122
44.5%
5 27
 
9.9%
1 26
 
9.5%
4 22
 
8.0%
2 19
 
6.9%
- 14
 
5.1%
7 10
 
3.6%
3 10
 
3.6%
0 8
 
2.9%
8 7
 
2.6%
Other values (2) 9
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 409
59.9%
ASCII 274
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122
44.5%
5 27
 
9.9%
1 26
 
9.5%
4 22
 
8.0%
2 19
 
6.9%
- 14
 
5.1%
7 10
 
3.6%
3 10
 
3.6%
0 8
 
2.9%
8 7
 
2.6%
Other values (2) 9
 
3.3%
Hangul
ValueCountFrequency (%)
산 37
 
9.0%
시 37
 
9.0%
주 30
 
7.3%
길 24
 
5.9%
전 24
 
5.9%
로 22
 
5.4%
군 21
 
5.1%
구 17
 
4.2%
완 14
 
3.4%
면 14
 
3.4%
Other values (70) 169
41.3%

등급
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)2.2%
Memory size500.0 B

객실수
Real number (ℝ)

Distinct39
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.63043
Minimum9
Maximum974
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-14T11:14:29.678108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile20.25
Q138.5
median59
Q3116.5
95-th percentile358.75
Maximum974
Range965
Interquartile range (IQR)78

Descriptive statistics

Standard deviation159.8782
Coefficient of variation (CV)1.4583377
Kurtosis19.807574
Mean109.63043
Median Absolute Deviation (MAD)26.5
Skewness4.1360227
Sum5043
Variance25561.038
MonotonicityNot monotonic
2024-03-14T11:14:29.790924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
35 3
 
6.5%
40 3
 
6.5%
59 2
 
4.3%
30 2
 
4.3%
42 2
 
4.3%
63 1
 
2.2%
16 1
 
2.2%
17 1
 
2.2%
71 1
 
2.2%
81 1
 
2.2%
Other values (29) 29
63.0%
ValueCountFrequency (%)
9 1
 
2.2%
16 1
 
2.2%
17 1
 
2.2%
30 2
4.3%
31 1
 
2.2%
34 1
 
2.2%
35 3
6.5%
36 1
 
2.2%
38 1
 
2.2%
40 3
6.5%
ValueCountFrequency (%)
974 1
2.2%
504 1
2.2%
418 1
2.2%
181 1
2.2%
167 1
2.2%
166 1
2.2%
156 1
2.2%
153 1
2.2%
147 1
2.2%
137 1
2.2%

전화번호
Text

Distinct44
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T11:14:29.972854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.456522
Min length1

Characters and Unicode

Total characters527
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

Unique42 ?
Unique (%)91.3%

Sample

1st row063-231-7900
2nd row-
3rd row063-280-7700
4th row063-263-1260
5th row063-853-7171
ValueCountFrequency (%)
063-320-7000 2
 
4.3%
2
 
4.3%
063-271-0123 1
 
2.2%
063-469-1234 1
 
2.2%
063-468-2128 1
 
2.2%
063-287-6400 1
 
2.2%
063-281-1000 1
 
2.2%
063-282-9513 1
 
2.2%
063-255-3311 1
 
2.2%
063-247-5900 1
 
2.2%
Other values (34) 34
73.9%
2024-03-14T11:14:30.266121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 112
21.3%
- 89
16.9%
3 78
14.8%
6 72
13.7%
2 36
 
6.8%
8 29
 
5.5%
1 27
 
5.1%
4 26
 
4.9%
7 23
 
4.4%
5 18
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 438
83.1%
Dash Punctuation 89
 
16.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 112
25.6%
3 78
17.8%
6 72
16.4%
2 36
 
8.2%
8 29
 
6.6%
1 27
 
6.2%
4 26
 
5.9%
7 23
 
5.3%
5 18
 
4.1%
9 17
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 527
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 112
21.3%
- 89
16.9%
3 78
14.8%
6 72
13.7%
2 36
 
6.8%
8 29
 
5.5%
1 27
 
5.1%
4 26
 
4.9%
7 23
 
4.4%
5 18
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 527
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 112
21.3%
- 89
16.9%
3 78
14.8%
6 72
13.7%
2 36
 
6.8%
8 29
 
5.5%
1 27
 
5.1%
4 26
 
4.9%
7 23
 
4.4%
5 18
 
3.4%

홈페이지
Text

Distinct41
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T11:14:30.519903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length21
Mean length17.978261
Min length1

Characters and Unicode

Total characters827
Distinct characters46
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)82.6%

Sample

1st rowwww.pungnamhotel.com
2nd row-
3rd rowjeonjuhotel.co.kr
4th rowwww.dhotel.kr
5th rowwww.iksanbusinesshotel.kr
ValueCountFrequency (%)
3
 
6.5%
www.mdysresort.com 3
 
6.5%
www.tovice.net 2
 
4.3%
gallerystay.net 1
 
2.2%
www.anes.kr 1
 
2.2%
www.pungnamhotel.com 1
 
2.2%
www.타워팰리스관광호텔.kr 1
 
2.2%
www.jjgung.co.kr 1
 
2.2%
www.jazzaroundhotel.co.kr 1
 
2.2%
hotellewin.com 1
 
2.2%
Other values (31) 31
67.4%
2024-03-14T11:14:30.869725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 107
 
12.9%
. 90
 
10.9%
o 74
 
8.9%
e 53
 
6.4%
r 49
 
5.9%
n 41
 
5.0%
t 41
 
5.0%
c 35
 
4.2%
s 35
 
4.2%
m 34
 
4.1%
Other values (36) 268
32.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 681
82.3%
Other Punctuation 101
 
12.2%
Other Letter 21
 
2.5%
Decimal Number 18
 
2.2%
Dash Punctuation 6
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 107
15.7%
o 74
10.9%
e 53
 
7.8%
r 49
 
7.2%
n 41
 
6.0%
t 41
 
6.0%
c 35
 
5.1%
s 35
 
5.1%
m 34
 
5.0%
a 33
 
4.8%
Other values (14) 179
26.3%
Other Letter
ValueCountFrequency (%)
텔 3
14.3%
호 3
14.3%
광 3
14.3%
관 3
14.3%
스 2
9.5%
리 1
 
4.8%
팰 1
 
4.8%
워 1
 
4.8%
타 1
 
4.8%
폭 1
 
4.8%
Other values (2) 2
9.5%
Decimal Number
ValueCountFrequency (%)
0 6
33.3%
4 3
16.7%
5 2
 
11.1%
3 2
 
11.1%
1 2
 
11.1%
2 2
 
11.1%
6 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 90
89.1%
/ 11
 
10.9%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 681
82.3%
Common 125
 
15.1%
Hangul 21
 
2.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 107
15.7%
o 74
10.9%
e 53
 
7.8%
r 49
 
7.2%
n 41
 
6.0%
t 41
 
6.0%
c 35
 
5.1%
s 35
 
5.1%
m 34
 
5.0%
a 33
 
4.8%
Other values (14) 179
26.3%
Hangul
ValueCountFrequency (%)
텔 3
14.3%
호 3
14.3%
광 3
14.3%
관 3
14.3%
스 2
9.5%
리 1
 
4.8%
팰 1
 
4.8%
워 1
 
4.8%
타 1
 
4.8%
폭 1
 
4.8%
Other values (2) 2
9.5%
Common
ValueCountFrequency (%)
. 90
72.0%
/ 11
 
8.8%
0 6
 
4.8%
- 6
 
4.8%
4 3
 
2.4%
5 2
 
1.6%
3 2
 
1.6%
1 2
 
1.6%
2 2
 
1.6%
6 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 806
97.5%
Hangul 21
 
2.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 107
13.3%
. 90
 
11.2%
o 74
 
9.2%
e 53
 
6.6%
r 49
 
6.1%
n 41
 
5.1%
t 41
 
5.1%
c 35
 
4.3%
s 35
 
4.3%
m 34
 
4.2%
Other values (24) 247
30.6%
Hangul
ValueCountFrequency (%)
텔 3
14.3%
호 3
14.3%
광 3
14.3%
관 3
14.3%
스 2
9.5%
리 1
 
4.8%
팰 1
 
4.8%
워 1
 
4.8%
타 1
 
4.8%
폭 1
 
4.8%
Other values (2) 2
9.5%

관광정보
Text

Distinct28
Distinct (%)60.9%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T11:14:31.094378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length25
Mean length15.326087
Min length1

Characters and Unicode

Total characters705
Distinct characters105
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

Unique19 ?
Unique (%)41.3%

Sample

1st row전주한옥마을, 남부시장
2nd row-
3rd row전주한옥마을, 전동성당, 남부시장
4th row대둔산도립공원
5th row미륵사지, 왕궁리유적
ValueCountFrequency (%)
전주한옥마을 12
 
11.1%
은파유원지 11
 
10.2%
새만금방조제 6
 
5.6%
춘향테마파크 6
 
5.6%
군산근대역사박물관 6
 
5.6%
남부시장 6
 
5.6%
전동성당 5
 
4.6%
광한루원 5
 
4.6%
경기전 4
 
3.7%
덕유산국립공원 3
 
2.8%
Other values (30) 44
40.7%
2024-03-14T11:14:31.395058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 62
 
8.8%
62
 
8.8%
전 24
 
3.4%
원 24
 
3.4%
마 23
 
3.3%
한 21
 
3.0%
산 20
 
2.8%
주 20
 
2.8%
파 19
 
2.7%
유 19
 
2.7%
Other values (95) 411
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 579
82.1%
Other Punctuation 62
 
8.8%
Space Separator 62
 
8.8%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 24
 
4.1%
원 24
 
4.1%
마 23
 
4.0%
한 21
 
3.6%
산 20
 
3.5%
주 20
 
3.5%
파 19
 
3.3%
유 19
 
3.3%
옥 15
 
2.6%
을 15
 
2.6%
Other values (92) 379
65.5%
Other Punctuation
ValueCountFrequency (%)
, 62
100.0%
Space Separator
ValueCountFrequency (%)
62
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 579
82.1%
Common 126
 
17.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 24
 
4.1%
원 24
 
4.1%
마 23
 
4.0%
한 21
 
3.6%
산 20
 
3.5%
주 20
 
3.5%
파 19
 
3.3%
유 19
 
3.3%
옥 15
 
2.6%
을 15
 
2.6%
Other values (92) 379
65.5%
Common
ValueCountFrequency (%)
, 62
49.2%
62
49.2%
- 2
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 579
82.1%
ASCII 126
 
17.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 62
49.2%
62
49.2%
- 2
 
1.6%
Hangul
ValueCountFrequency (%)
전 24
 
4.1%
원 24
 
4.1%
마 23
 
4.0%
한 21
 
3.6%
산 20
 
3.5%
주 20
 
3.5%
파 19
 
3.3%
유 19
 
3.3%
옥 15
 
2.6%
을 15
 
2.6%
Other values (92) 379
65.5%

부대시설
Text

MISSING 

Distinct35
Distinct (%)77.8%
Missing1
Missing (%)2.2%
Memory size500.0 B
2024-03-14T11:14:31.574661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length10.333333
Min length1

Characters and Unicode

Total characters465
Distinct characters108
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)73.3%

Sample

1st row연회장, 커피숍, 인터넷센터
2nd row웨딩홀, 연회장, 건식사우나실
3rd row온천사우나, 연회장
4th row레스토랑, 오피스룸, 회의실
5th row수영장, 사우나, 연회장
ValueCountFrequency (%)
연회장 11
 
11.0%
10
 
10.0%
세미나실 8
 
8.0%
레스토랑 6
 
6.0%
카페 4
 
4.0%
한식당 3
 
3.0%
사우나 3
 
3.0%
웨딩홀 3
 
3.0%
비즈니스룸 3
 
3.0%
당구장 3
 
3.0%
Other values (44) 46
46.0%
2024-03-14T11:14:31.851244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 55
 
11.8%
55
 
11.8%
장 23
 
4.9%
스 20
 
4.3%
나 15
 
3.2%
연 13
 
2.8%
실 13
 
2.8%
회 13
 
2.8%
미 11
 
2.4%
세 11
 
2.4%
Other values (98) 236
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 342
73.5%
Other Punctuation 55
 
11.8%
Space Separator 55
 
11.8%
Dash Punctuation 10
 
2.2%
Uppercase Letter 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 23
 
6.7%
스 20
 
5.8%
나 15
 
4.4%
연 13
 
3.8%
실 13
 
3.8%
회 13
 
3.8%
미 11
 
3.2%
세 11
 
3.2%
니 9
 
2.6%
식 9
 
2.6%
Other values (92) 205
59.9%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
V 1
33.3%
I 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 55
100.0%
Space Separator
ValueCountFrequency (%)
55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 342
73.5%
Common 120
 
25.8%
Latin 3
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 23
 
6.7%
스 20
 
5.8%
나 15
 
4.4%
연 13
 
3.8%
실 13
 
3.8%
회 13
 
3.8%
미 11
 
3.2%
세 11
 
3.2%
니 9
 
2.6%
식 9
 
2.6%
Other values (92) 205
59.9%
Common
ValueCountFrequency (%)
, 55
45.8%
55
45.8%
- 10
 
8.3%
Latin
ValueCountFrequency (%)
P 1
33.3%
V 1
33.3%
I 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 342
73.5%
ASCII 123
 
26.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 55
44.7%
55
44.7%
- 10
 
8.1%
P 1
 
0.8%
V 1
 
0.8%
I 1
 
0.8%
Hangul
ValueCountFrequency (%)
장 23
 
6.7%
스 20
 
5.8%
나 15
 
4.4%
연 13
 
3.8%
실 13
 
3.8%
회 13
 
3.8%
미 11
 
3.2%
세 11
 
3.2%
니 9
 
2.6%
식 9
 
2.6%
Other values (92) 205
59.9%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
관광총괄과
46 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광총괄과 46
100.0%

Length

2024-03-14T11:14:31.963895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:14:32.035144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광총괄과 46
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
공개
46 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 46
100.0%

Length

2024-03-14T11:14:32.105435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:14:32.182130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 46
100.0%

작성일
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
2015.1
45 
2016.07
 
1

Length

Max length7
Median length6
Mean length6.0217391
Min length6

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st row2015.1
2nd row2015.1
3rd row2015.1
4th row2015.1
5th row2015.1

Common Values

ValueCountFrequency (%)
2015.1 45
97.8%
2016.07 1
 
2.2%

Length

2024-03-14T11:14:32.269280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:14:32.341909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 45
97.8%
2016.07 1
 
2.2%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
1년
46 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 46
100.0%

Length

2024-03-14T11:14:32.413113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:14:32.487772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 46
100.0%

Interactions

2024-03-14T11:14:27.424765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:14:27.305495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:14:27.482628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:14:27.363156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T11:14:32.558111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명상호명업종별도로명주소객실수전화번호홈페이지관광정보부대시설작성일
순번1.0000.8361.0000.5820.9820.4520.9720.9380.8730.8080.000
시군명0.8361.0001.0000.8071.0000.4430.0000.0000.9870.0000.000
상호명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
업종별0.5820.8071.0001.0000.8660.5371.0000.7750.9760.0000.000
도로명주소0.9821.0001.0000.8661.0000.0000.9940.9950.9860.9941.000
객실수0.4520.4431.0000.5370.0001.0000.0000.0000.0000.0000.000
전화번호0.9720.0001.0001.0000.9940.0001.0001.0001.0001.0001.000
홈페이지0.9380.0001.0000.7750.9950.0001.0001.0000.9890.9951.000
관광정보0.8730.9871.0000.9760.9860.0001.0000.9891.0000.9181.000
부대시설0.8080.0001.0000.0000.9940.0001.0000.9950.9181.0001.000
작성일0.0000.0001.0000.0001.0000.0001.0001.0001.0001.0001.000
2024-03-14T11:14:32.702615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명업종별작성일
시군명1.0000.4480.000
업종별0.4481.0000.000
작성일0.0000.0001.000
2024-03-14T11:14:32.786328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번객실수시군명업종별작성일
순번1.000-0.1930.5720.3890.000
객실수-0.1931.0000.2740.4570.000
시군명0.5720.2741.0000.4480.000
업종별0.3890.4570.4481.0000.000
작성일0.0000.0000.0000.0001.000

Missing values

2024-03-14T11:14:27.577304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:14:27.731634image/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.
2024-03-14T11:14:27.834259image/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

순번시군명상호명업종별도로명주소등급객실수전화번호홈페이지관광정보부대시설자료출처공개여부작성일갱신주기
01전주시풍남관광호텔관광호텔전주시 완산구 전주객사2길 45-7263063-231-7900www.pungnamhotel.com전주한옥마을, 남부시장연회장, 커피숍, 인터넷센터관광총괄과공개2015.11년
12전주시전주코아호텔관광호텔전주시 완산구 노송광장로 51특2111---<NA>관광총괄과공개2015.11년
23전주시전주관광호텔관광호텔전주시 완산구 전주객사5길 44-5331063-280-7700jeonjuhotel.co.kr전주한옥마을, 전동성당, 남부시장웨딩홀, 연회장, 건식사우나실관광총괄과공개2015.11년
34완주군대둔산관광호텔관광호텔완주군 운주면 대둔산공원길 37268063-263-1260www.dhotel.kr대둔산도립공원온천사우나, 연회장관광총괄과공개2015.11년
45익산시익산비즈니스관광호텔관광호텔익산시 인북로 10-38063-853-7171www.iksanbusinesshotel.kr미륵사지, 왕궁리유적레스토랑, 오피스룸, 회의실관광총괄과공개2015.11년
56부안군모항해나루가족호텔가족호텔부안군 변산면 모항해변길 73-112063-580-0700www.haenaruhotel.co.kr국립변산자연휴양림, 곰소항수영장, 사우나, 연회장관광총괄과공개2015.11년
67부안군채석강스타힐스 호텔관광호텔부안군 변산면 채석강길 33235063-581-9911www.starhillshotel.com채석강, 내소사, 부안영상테마파크마사지실, 식음료장, 바베큐장, 노래연습장관광총괄과공개2015.11년
78부안군대명리조트변산가족호텔가족호텔부안군 변산면 변산해변로 51-5041588-4888www.daemyungresort.com/bs/채석강, 부안영상테마파크뮤직시티, 스크린골프장, 세그웨이관광총괄과공개2015.11년
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