Overview

Dataset statistics

Number of variables8
Number of observations43
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory69.1 B

Variable types

Numeric2
Categorical2
Text4

Dataset

Description충청북도 숙박업소현황에 대한 데이터로 업소명, 분류, 지역, 주소, 대표전화, 홈페이지, 객실수, 주차시설, 부대시설, 신용카드, 픽업서비스, 조식제공 등을 제공하고 있습니다
URLhttps://www.data.go.kr/data/15053066/fileData.do

Alerts

번호 is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 번호High correlation
전화번호 has 1 (2.3%) missing valuesMissing
번호 has unique valuesUnique
명칭 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:55:21.224821
Analysis finished2023-12-12 07:55:22.228318
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:55:22.316885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.1
Q111.5
median22
Q332.5
95-th percentile40.9
Maximum43
Range42
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.556539
Coefficient of variation (CV)0.57075176
Kurtosis-1.2
Mean22
Median Absolute Deviation (MAD)11
Skewness0
Sum946
Variance157.66667
MonotonicityStrictly increasing
2023-12-12T16:55:22.449098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 1
 
2.3%
2 1
 
2.3%
25 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%
34 1
2.3%

시군구
Categorical

Distinct8
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Memory size476.0 B
충주시
16 
제천시
12 
청주시
6 
단양군
5 
보은군
 
1
Other values (3)
3 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique4 ?
Unique (%)9.3%

Sample

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

Common Values

ValueCountFrequency (%)
충주시 16
37.2%
제천시 12
27.9%
청주시 6
 
14.0%
단양군 5
 
11.6%
보은군 1
 
2.3%
음성군 1
 
2.3%
증평군 1
 
2.3%
진천군 1
 
2.3%

Length

2023-12-12T16:55:22.577410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:55:22.685456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충주시 16
37.2%
제천시 12
27.9%
청주시 6
 
14.0%
단양군 5
 
11.6%
보은군 1
 
2.3%
음성군 1
 
2.3%
증평군 1
 
2.3%
진천군 1
 
2.3%

업종
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
관광호텔업
17 
휴양콘도미니엄업
8 
호스텔업
7 
농어촌민박사업
7 
가족호텔업
2 
Other values (2)
2 

Length

Max length8
Median length7
Mean length5.7674419
Min length4

Unique

Unique2 ?
Unique (%)4.7%

Sample

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

Common Values

ValueCountFrequency (%)
관광호텔업 17
39.5%
휴양콘도미니엄업 8
18.6%
호스텔업 7
16.3%
농어촌민박사업 7
16.3%
가족호텔업 2
 
4.7%
농업촌민박사업 1
 
2.3%
생활숙박업 1
 
2.3%

Length

2023-12-12T16:55:23.235068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:55:23.399986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광호텔업 17
39.5%
휴양콘도미니엄업 8
18.6%
호스텔업 7
16.3%
농어촌민박사업 7
16.3%
가족호텔업 2
 
4.7%
농업촌민박사업 1
 
2.3%
생활숙박업 1
 
2.3%

명칭
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T16:55:23.694239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length9.0465116
Min length4

Characters and Unicode

Total characters389
Distinct characters139
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row그랜드플라자청주호텔
2nd row뉴베라관광호텔
3rd row더마크관광호텔
4th row세종스파텔
5th row관광호텔 뮤제오
ValueCountFrequency (%)
펜션 3
 
4.3%
게스트하우스 3
 
4.3%
월악별장펜션 2
 
2.9%
수안보 2
 
2.9%
주식회사 2
 
2.9%
한화호텔앤드리조트㈜ 1
 
1.4%
한화리조트 1
 
1.4%
이랜드파크 1
 
1.4%
리조트 1
 
1.4%
한국콘도 1
 
1.4%
Other values (52) 52
75.4%
2023-12-12T16:55:24.154136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
 
6.7%
호 23
 
5.9%
텔 22
 
5.7%
스 15
 
3.9%
리 11
 
2.8%
광 10
 
2.6%
트 10
 
2.6%
관 10
 
2.6%
펜 8
 
2.1%
션 8
 
2.1%
Other values (129) 246
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 321
82.5%
Space Separator 26
 
6.7%
Uppercase Letter 15
 
3.9%
Lowercase Letter 13
 
3.3%
Decimal Number 3
 
0.8%
Open Punctuation 3
 
0.8%
Close Punctuation 3
 
0.8%
Other Symbol 2
 
0.5%
Letter Number 2
 
0.5%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 23
 
7.2%
텔 22
 
6.9%
스 15
 
4.7%
리 11
 
3.4%
광 10
 
3.1%
트 10
 
3.1%
관 10
 
3.1%
펜 8
 
2.5%
션 8
 
2.5%
조 7
 
2.2%
Other values (103) 197
61.4%
Uppercase Letter
ValueCountFrequency (%)
A 4
26.7%
S 2
13.3%
B 2
13.3%
E 1
 
6.7%
U 1
 
6.7%
N 1
 
6.7%
O 1
 
6.7%
R 1
 
6.7%
M 1
 
6.7%
D 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
o 3
23.1%
l 3
23.1%
e 2
15.4%
d 1
 
7.7%
n 1
 
7.7%
c 1
 
7.7%
g 1
 
7.7%
a 1
 
7.7%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Decimal Number
ValueCountFrequency (%)
9 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 322
82.8%
Common 36
 
9.3%
Latin 30
 
7.7%
Han 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 23
 
7.1%
텔 22
 
6.8%
스 15
 
4.7%
리 11
 
3.4%
광 10
 
3.1%
트 10
 
3.1%
관 10
 
3.1%
펜 8
 
2.5%
션 8
 
2.5%
조 7
 
2.2%
Other values (103) 198
61.5%
Latin
ValueCountFrequency (%)
A 4
 
13.3%
o 3
 
10.0%
l 3
 
10.0%
e 2
 
6.7%
S 2
 
6.7%
B 2
 
6.7%
E 1
 
3.3%
Ⅰ 1
 
3.3%
Ⅱ 1
 
3.3%
U 1
 
3.3%
Other values (10) 10
33.3%
Common
ValueCountFrequency (%)
26
72.2%
9 3
 
8.3%
( 3
 
8.3%
) 3
 
8.3%
, 1
 
2.8%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 320
82.3%
ASCII 64
 
16.5%
None 2
 
0.5%
Number Forms 2
 
0.5%
CJK 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26
40.6%
A 4
 
6.2%
9 3
 
4.7%
o 3
 
4.7%
( 3
 
4.7%
l 3
 
4.7%
) 3
 
4.7%
e 2
 
3.1%
S 2
 
3.1%
B 2
 
3.1%
Other values (13) 13
20.3%
Hangul
ValueCountFrequency (%)
호 23
 
7.2%
텔 22
 
6.9%
스 15
 
4.7%
리 11
 
3.4%
광 10
 
3.1%
트 10
 
3.1%
관 10
 
3.1%
펜 8
 
2.5%
션 8
 
2.5%
조 7
 
2.2%
Other values (102) 196
61.3%
None
ValueCountFrequency (%)
㈜ 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
CJK
ValueCountFrequency (%)
家 1
100.0%

객실수
Real number (ℝ)

Distinct36
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90.744186
Minimum1
Maximum856
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T16:55:24.331666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q110
median50
Q396.5
95-th percentile320.7
Maximum856
Range855
Interquartile range (IQR)86.5

Descriptive statistics

Standard deviation150.92478
Coefficient of variation (CV)1.6631896
Kurtosis16.079478
Mean90.744186
Median Absolute Deviation (MAD)42
Skewness3.6655059
Sum3902
Variance22778.29
MonotonicityNot monotonic
2023-12-12T16:55:24.456584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
3 3
 
7.0%
6 3
 
7.0%
11 2
 
4.7%
60 2
 
4.7%
180 2
 
4.7%
451 1
 
2.3%
24 1
 
2.3%
72 1
 
2.3%
92 1
 
2.3%
44 1
 
2.3%
Other values (26) 26
60.5%
ValueCountFrequency (%)
1 1
 
2.3%
2 1
 
2.3%
3 3
7.0%
4 1
 
2.3%
5 1
 
2.3%
6 3
7.0%
9 1
 
2.3%
11 2
4.7%
16 1
 
2.3%
24 1
 
2.3%
ValueCountFrequency (%)
856 1
2.3%
451 1
2.3%
328 1
2.3%
255 1
2.3%
180 2
4.7%
175 1
2.3%
132 1
2.3%
113 1
2.3%
103 1
2.3%
101 1
2.3%

주소
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T16:55:24.735180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length23.186047
Min length15

Characters and Unicode

Total characters997
Distinct characters108
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

Unique43 ?
Unique (%)100.0%

Sample

1st row충청북도 청주시 청원구 충청대로 114
2nd row충청북도 청주시 흥덕구 풍년로193번길 32
3rd row충청북도 청주시 흥덕구 가로수로1164번길 41-34
4th row충청북도 청주시 청원구 내수읍 신기초정로 699
5th row충청북도 청주시 흥덕구 가로수로1164번길 41-20
ValueCountFrequency (%)
충청북도 43
 
19.6%
충주시 16
 
7.3%
제천시 12
 
5.5%
수안보면 7
 
3.2%
청주시 6
 
2.7%
단양군 5
 
2.3%
청풍면 3
 
1.4%
앙성면 3
 
1.4%
흥덕구 3
 
1.4%
27497 3
 
1.4%
Other values (106) 118
53.9%
2023-12-12T16:55:25.152644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
179
 
18.0%
충 60
 
6.0%
청 59
 
5.9%
도 44
 
4.4%
북 43
 
4.3%
1 39
 
3.9%
시 34
 
3.4%
로 33
 
3.3%
주 26
 
2.6%
면 25
 
2.5%
Other values (98) 455
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 607
60.9%
Decimal Number 186
 
18.7%
Space Separator 179
 
18.0%
Dash Punctuation 10
 
1.0%
Close Punctuation 7
 
0.7%
Open Punctuation 7
 
0.7%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 60
 
9.9%
청 59
 
9.7%
도 44
 
7.2%
북 43
 
7.1%
시 34
 
5.6%
로 33
 
5.4%
주 26
 
4.3%
면 25
 
4.1%
길 20
 
3.3%
천 16
 
2.6%
Other values (83) 247
40.7%
Decimal Number
ValueCountFrequency (%)
1 39
21.0%
3 24
12.9%
4 24
12.9%
2 23
12.4%
7 18
9.7%
6 14
 
7.5%
9 13
 
7.0%
0 12
 
6.5%
8 11
 
5.9%
5 8
 
4.3%
Space Separator
ValueCountFrequency (%)
179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 607
60.9%
Common 390
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 60
 
9.9%
청 59
 
9.7%
도 44
 
7.2%
북 43
 
7.1%
시 34
 
5.6%
로 33
 
5.4%
주 26
 
4.3%
면 25
 
4.1%
길 20
 
3.3%
천 16
 
2.6%
Other values (83) 247
40.7%
Common
ValueCountFrequency (%)
179
45.9%
1 39
 
10.0%
3 24
 
6.2%
4 24
 
6.2%
2 23
 
5.9%
7 18
 
4.6%
6 14
 
3.6%
9 13
 
3.3%
0 12
 
3.1%
8 11
 
2.8%
Other values (5) 33
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 607
60.9%
ASCII 390
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
179
45.9%
1 39
 
10.0%
3 24
 
6.2%
4 24
 
6.2%
2 23
 
5.9%
7 18
 
4.6%
6 14
 
3.6%
9 13
 
3.3%
0 12
 
3.1%
8 11
 
2.8%
Other values (5) 33
 
8.5%
Hangul
ValueCountFrequency (%)
충 60
 
9.9%
청 59
 
9.7%
도 44
 
7.2%
북 43
 
7.1%
시 34
 
5.6%
로 33
 
5.4%
주 26
 
4.3%
면 25
 
4.1%
길 20
 
3.3%
천 16
 
2.6%
Other values (83) 247
40.7%

전화번호
Text

MISSING 

Distinct41
Distinct (%)97.6%
Missing1
Missing (%)2.3%
Memory size476.0 B
2023-12-12T16:55:25.388022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.309524
Min length12

Characters and Unicode

Total characters517
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

Unique40 ?
Unique (%)95.2%

Sample

1st row043-290-1000
2nd row043-235-8181
3rd row043-238-3344
4th row043-213-2332
5th row043-267-3200
ValueCountFrequency (%)
0507-1447-1125 2
 
4.8%
0507-1310-0863 1
 
2.4%
043-649-6110 1
 
2.4%
043-643-4111 1
 
2.4%
043-644-3355 1
 
2.4%
043-649-1122 1
 
2.4%
043-846-8211 1
 
2.4%
043-856-1801 1
 
2.4%
043-854-3100 1
 
2.4%
043-846-0750 1
 
2.4%
Other values (31) 31
73.8%
2023-12-12T16:55:25.841537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 92
17.8%
- 84
16.2%
4 69
13.3%
3 61
11.8%
1 44
8.5%
8 39
7.5%
5 38
7.4%
2 31
 
6.0%
6 29
 
5.6%
7 21
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 433
83.8%
Dash Punctuation 84
 
16.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 92
21.2%
4 69
15.9%
3 61
14.1%
1 44
10.2%
8 39
9.0%
5 38
8.8%
2 31
 
7.2%
6 29
 
6.7%
7 21
 
4.8%
9 9
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 517
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 92
17.8%
- 84
16.2%
4 69
13.3%
3 61
11.8%
1 44
8.5%
8 39
7.5%
5 38
7.4%
2 31
 
6.0%
6 29
 
5.6%
7 21
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 517
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 92
17.8%
- 84
16.2%
4 69
13.3%
3 61
11.8%
1 44
8.5%
8 39
7.5%
5 38
7.4%
2 31
 
6.0%
6 29
 
5.6%
7 21
 
4.1%

부대시설
Text

Distinct35
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T16:55:26.168362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length220
Median length24
Mean length21.604651
Min length2

Characters and Unicode

Total characters929
Distinct characters152
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

Unique30 ?
Unique (%)69.8%

Sample

1st row식당, 커피숍, 연회장, 헬스클럽
2nd row식당
3rd row식당
4th row식당, 사우나, 세미나실, 대연회장
5th row식당, 비즈니스센터
ValueCountFrequency (%)
연회장 11
 
6.5%
식당 9
 
5.4%
등 7
 
4.2%
바비큐장 7
 
4.2%
카페 6
 
3.6%
커피숍 5
 
3.0%
세미나실 5
 
3.0%
사우나 5
 
3.0%
슈퍼마켓 5
 
3.0%
단란주점 4
 
2.4%
Other values (80) 104
61.9%
2023-12-12T16:55:26.640688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
133
 
14.3%
, 112
 
12.1%
장 50
 
5.4%
식 38
 
4.1%
점 26
 
2.8%
당 23
 
2.5%
연 20
 
2.2%
음 18
 
1.9%
회 15
 
1.6%
실 13
 
1.4%
Other values (142) 481
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 630
67.8%
Space Separator 133
 
14.3%
Other Punctuation 121
 
13.0%
Decimal Number 19
 
2.0%
Open Punctuation 12
 
1.3%
Close Punctuation 12
 
1.3%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 50
 
7.9%
식 38
 
6.0%
점 26
 
4.1%
당 23
 
3.7%
연 20
 
3.2%
음 18
 
2.9%
회 15
 
2.4%
실 13
 
2.1%
나 12
 
1.9%
스 11
 
1.7%
Other values (129) 404
64.1%
Decimal Number
ValueCountFrequency (%)
1 7
36.8%
2 6
31.6%
3 3
15.8%
4 2
 
10.5%
5 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 112
92.6%
: 5
 
4.1%
/ 4
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
133
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 630
67.8%
Common 297
32.0%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 50
 
7.9%
식 38
 
6.0%
점 26
 
4.1%
당 23
 
3.7%
연 20
 
3.2%
음 18
 
2.9%
회 15
 
2.4%
실 13
 
2.1%
나 12
 
1.9%
스 11
 
1.7%
Other values (129) 404
64.1%
Common
ValueCountFrequency (%)
133
44.8%
, 112
37.7%
( 12
 
4.0%
) 12
 
4.0%
1 7
 
2.4%
2 6
 
2.0%
: 5
 
1.7%
/ 4
 
1.3%
3 3
 
1.0%
4 2
 
0.7%
Latin
ValueCountFrequency (%)
P 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 630
67.8%
ASCII 299
32.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
133
44.5%
, 112
37.5%
( 12
 
4.0%
) 12
 
4.0%
1 7
 
2.3%
2 6
 
2.0%
: 5
 
1.7%
/ 4
 
1.3%
3 3
 
1.0%
4 2
 
0.7%
Other values (3) 3
 
1.0%
Hangul
ValueCountFrequency (%)
장 50
 
7.9%
식 38
 
6.0%
점 26
 
4.1%
당 23
 
3.7%
연 20
 
3.2%
음 18
 
2.9%
회 15
 
2.4%
실 13
 
2.1%
나 12
 
1.9%
스 11
 
1.7%
Other values (129) 404
64.1%

Interactions

2023-12-12T16:55:21.848711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:55:21.681195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:55:21.940089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:55:21.766472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:55:26.749442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호시군구업종명칭객실수주소전화번호부대시설
번호1.0000.7130.8851.0000.5681.0001.0000.976
시군구0.7131.0000.0001.0000.3281.0001.0000.000
업종0.8850.0001.0001.0000.0001.0001.0000.915
명칭1.0001.0001.0001.0001.0001.0001.0001.000
객실수0.5680.3280.0001.0001.0001.0001.0000.980
주소1.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
부대시설0.9760.0000.9151.0000.9801.0001.0001.000
2023-12-12T16:55:26.852535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종시군구
업종1.0000.000
시군구0.0001.000
2023-12-12T16:55:26.943913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호객실수시군구업종
번호1.000-0.4780.4330.669
객실수-0.4781.0000.1710.000
시군구0.4330.1711.0000.000
업종0.6690.0000.0001.000

Missing values

2023-12-12T16:55:22.066932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:55:22.183440image/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

번호시군구업종명칭객실수주소전화번호부대시설
01청주시관광호텔업그랜드플라자청주호텔328충청북도 청주시 청원구 충청대로 114043-290-1000식당, 커피숍, 연회장, 헬스클럽
12청주시관광호텔업뉴베라관광호텔51충청북도 청주시 흥덕구 풍년로193번길 32043-235-8181식당
23청주시관광호텔업더마크관광호텔56충청북도 청주시 흥덕구 가로수로1164번길 41-34043-238-3344식당
34청주시관광호텔업세종스파텔60충청북도 청주시 청원구 내수읍 신기초정로 699043-213-2332식당, 사우나, 세미나실, 대연회장
45청주시관광호텔업관광호텔 뮤제오59충청북도 청주시 흥덕구 가로수로1164번길 41-20043-267-3200식당, 비즈니스센터
56충주시관광호텔업수안보상록호텔101충청북도 충주시 수안보면 주정산로 22 (27497)043-850-3500온천사우나, 한식당, 커피숍, 특산물판매장
67충주시관광호텔업수안보파크관광호텔113충청북도 충주시 수안보면 탑골1길 36 (27497)043-846-2331일반음식점,회의실,온천사우나 등
78충주시관광호텔업충주호리조트관광호텔60충청북도 충주시 동량면 호반로 675 (380-813)043-856-7890음식점, 카페, 연회장, 헬스장, 웨딩홀 등
89충주시관광호텔업RAMADA SUANBO(라마다 수안보)103충청북도 충주시 수안보면 조산공원길 99 (27497)043-848-8833스포츠마사지, 연회장, 휴게실, 대중탕 등
910충주시관광호텔업리버호텔65충청북도 충주시 애향로 35 (27424)043-851-2235유흥음식점, 휴게음식점
번호시군구업종명칭객실수주소전화번호부대시설
3334단양군휴양콘도미니엄업소노문 단양856충청북도 단양군 단양읍 삼봉로 187-17043-420-8302노래연습장, 상점(1,2,3), 미용실, 일반음식점1(대중음식점), 일반음식점2(한식당), 일반음식점3(단체식당), 일반음식점4(한식당2), 일반음식점5, 휴게음식점1(커피숍), 휴게음식점2(제과점), 휴게음식점3(스낵), 기념품점, 슈퍼마켓, 청소년게임장, 탈의실, 일반목용장, 단란주점, 회의장(연회장), 세탁실, 멀티미디어 문화컨텐츠 설비제공업(PC방), 당구장, 단체급식소(직원식당)
3435충주시농업촌민박사업수안보관광펜션3충청북도 충주시 수안보면 온천리 472, 480043-846-4646바비큐장: 1개 캠프파이어장: 1개
3536제천시농어촌민박사업월악별장펜션 Ⅰ3충청북도 제천시 한수면 미륵송계로 13460507-1447-1125바비큐장, 족구장
3637제천시농어촌민박사업월악별장펜션 Ⅱ4충청북도 제천시 한수면 미륵송계로 13440507-1447-1125바비큐장, 족구장
3738제천시생활숙박업펜션, 호반의 성9충청북도 제천시 청풍면 청풍호로44길 200507-1361-7639바비큐장
3839제천시농어촌민박사업미소가든펜션5충청북도 제천시 봉양읍 제원로6길 39-2043-653-2885바비큐장
3940진천군농어촌민박사업시기공추2충청북도 진천군 진천읍 원동길 131-840507-1468-1217바비큐장
4041단양군농어촌민박사업가곡추억펜션6충청북도 단양군 가곡면 가대1길 55043-422-6221바베큐장: 1개, 카페
4142단양군농어촌민박사업가우리 펜션3충청북도 단양군 대강면 사인암2길 11-1<NA>바베큐장: 1개
4243단양군농어촌민박사업비비아나 펜션1충청북도 단양군 대강면 사인암리 18-20507-1401-2466바베큐장: 2개