Overview

Dataset statistics

Number of variables16
Number of observations2780
Missing cells7301
Missing cells (%)16.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory355.8 KiB
Average record size in memory131.0 B

Variable types

Text5
Categorical7
Numeric3
Boolean1

Alerts

주차장보유여부 has constant value ""Constant
서비스대상구분 is highly overall correlated with 외국어안내서비스 and 4 other fieldsHigh correlation
외국어안내서비스 is highly overall correlated with 서비스대상구분 and 3 other fieldsHigh correlation
데이터기준일자 is highly overall correlated with 위도 and 7 other fieldsHigh correlation
업종명 is highly overall correlated with 부대시설 and 3 other fieldsHigh correlation
주변관광정보 is highly overall correlated with 위도 and 7 other fieldsHigh correlation
부대시설 is highly overall correlated with 위도 and 6 other fieldsHigh correlation
결제방법 is highly overall correlated with 위도 and 7 other fieldsHigh correlation
위도 is highly overall correlated with 부대시설 and 3 other fieldsHigh correlation
경도 is highly overall correlated with 부대시설 and 3 other fieldsHigh correlation
업종명 is highly imbalanced (95.4%)Imbalance
서비스대상구분 is highly imbalanced (77.6%)Imbalance
외국어안내서비스 is highly imbalanced (60.0%)Imbalance
부대시설 is highly imbalanced (92.8%)Imbalance
결제방법 is highly imbalanced (83.8%)Imbalance
주변관광정보 is highly imbalanced (76.1%)Imbalance
전화번호 has 2550 (91.7%) missing valuesMissing
주차장보유여부 has 2017 (72.6%) missing valuesMissing
홈페이지주소 has 2731 (98.2%) missing valuesMissing

Reproduction

Analysis started2024-04-11 04:49:07.680781
Analysis finished2024-04-11 04:49:11.759327
Duration4.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct2688
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size21.8 KiB
2024-04-11T13:49:11.962773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length5.3665468
Min length1

Characters and Unicode

Total characters14919
Distinct characters723
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

Unique2606 ?
Unique (%)93.7%

Sample

1st row아쉬람펜션
2nd row건아들 펜션
3rd row샘물향기
4th row모이스티 펜션
5th row마당과 다락방
ValueCountFrequency (%)
펜션 143
 
4.1%
민박 45
 
1.3%
가평 30
 
0.9%
풀빌라 17
 
0.5%
하우스 16
 
0.5%
숲속의 16
 
0.5%
계곡 13
 
0.4%
더 11
 
0.3%
키즈 10
 
0.3%
스테이 10
 
0.3%
Other values (2861) 3202
91.1%
2024-04-11T13:49:12.343053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
션 735
 
4.9%
733
 
4.9%
펜 716
 
4.8%
스 466
 
3.1%
리 346
 
2.3%
이 331
 
2.2%
하 258
 
1.7%
민 228
 
1.5%
박 226
 
1.5%
우 212
 
1.4%
Other values (713) 10668
71.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13141
88.1%
Space Separator 733
 
4.9%
Decimal Number 310
 
2.1%
Uppercase Letter 276
 
1.8%
Lowercase Letter 249
 
1.7%
Open Punctuation 64
 
0.4%
Close Punctuation 64
 
0.4%
Other Punctuation 56
 
0.4%
Dash Punctuation 21
 
0.1%
Letter Number 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
션 735
 
5.6%
펜 716
 
5.4%
스 466
 
3.5%
리 346
 
2.6%
이 331
 
2.5%
하 258
 
2.0%
민 228
 
1.7%
박 226
 
1.7%
우 212
 
1.6%
라 205
 
1.6%
Other values (641) 9418
71.7%
Lowercase Letter
ValueCountFrequency (%)
e 36
14.5%
o 30
12.0%
s 24
9.6%
a 22
 
8.8%
r 16
 
6.4%
i 15
 
6.0%
t 14
 
5.6%
y 13
 
5.2%
l 12
 
4.8%
n 10
 
4.0%
Other values (14) 57
22.9%
Uppercase Letter
ValueCountFrequency (%)
A 28
 
10.1%
O 23
 
8.3%
H 18
 
6.5%
B 17
 
6.2%
T 15
 
5.4%
M 15
 
5.4%
U 15
 
5.4%
C 15
 
5.4%
E 15
 
5.4%
S 14
 
5.1%
Other values (14) 101
36.6%
Decimal Number
ValueCountFrequency (%)
2 77
24.8%
1 66
21.3%
4 30
 
9.7%
3 28
 
9.0%
0 27
 
8.7%
6 26
 
8.4%
5 19
 
6.1%
9 16
 
5.2%
7 12
 
3.9%
8 9
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 29
51.8%
& 9
 
16.1%
· 6
 
10.7%
: 6
 
10.7%
' 2
 
3.6%
? 2
 
3.6%
# 1
 
1.8%
. 1
 
1.8%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
60.0%
Ⅰ 2
40.0%
Space Separator
ValueCountFrequency (%)
733
100.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13139
88.1%
Common 1248
 
8.4%
Latin 530
 
3.6%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
션 735
 
5.6%
펜 716
 
5.4%
스 466
 
3.5%
리 346
 
2.6%
이 331
 
2.5%
하 258
 
2.0%
민 228
 
1.7%
박 226
 
1.7%
우 212
 
1.6%
라 205
 
1.6%
Other values (640) 9416
71.7%
Latin
ValueCountFrequency (%)
e 36
 
6.8%
o 30
 
5.7%
A 28
 
5.3%
s 24
 
4.5%
O 23
 
4.3%
a 22
 
4.2%
H 18
 
3.4%
B 17
 
3.2%
r 16
 
3.0%
T 15
 
2.8%
Other values (40) 301
56.8%
Common
ValueCountFrequency (%)
733
58.7%
2 77
 
6.2%
1 66
 
5.3%
( 64
 
5.1%
) 64
 
5.1%
4 30
 
2.4%
, 29
 
2.3%
3 28
 
2.2%
0 27
 
2.2%
6 26
 
2.1%
Other values (12) 104
 
8.3%
Han
ValueCountFrequency (%)
家 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13139
88.1%
ASCII 1767
 
11.8%
None 6
 
< 0.1%
Number Forms 5
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
션 735
 
5.6%
펜 716
 
5.4%
스 466
 
3.5%
리 346
 
2.6%
이 331
 
2.5%
하 258
 
2.0%
민 228
 
1.7%
박 226
 
1.7%
우 212
 
1.6%
라 205
 
1.6%
Other values (640) 9416
71.7%
ASCII
ValueCountFrequency (%)
733
41.5%
2 77
 
4.4%
1 66
 
3.7%
( 64
 
3.6%
) 64
 
3.6%
e 36
 
2.0%
4 30
 
1.7%
o 30
 
1.7%
, 29
 
1.6%
3 28
 
1.6%
Other values (59) 610
34.5%
None
ValueCountFrequency (%)
· 6
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
60.0%
Ⅰ 2
40.0%
CJK
ValueCountFrequency (%)
家 2
100.0%

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.8 KiB
민박
2766 
펜션
 
14

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
민박 2766
99.5%
펜션 14
 
0.5%

Length

2024-04-11T13:49:12.440551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T13:49:12.507240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민박 2766
99.5%
펜션 14
 
0.5%

서비스대상구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.8 KiB
내국인+외국인
2619 
내국인
 
136
외국인
 
25

Length

Max length7
Median length7
Mean length6.7683453
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row내국인+외국인
2nd row내국인+외국인
3rd row내국인+외국인
4th row내국인+외국인
5th row내국인+외국인

Common Values

ValueCountFrequency (%)
내국인+외국인 2619
94.2%
내국인 136
 
4.9%
외국인 25
 
0.9%

Length

2024-04-11T13:49:12.583840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T13:49:12.660007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
내국인+외국인 2619
94.2%
내국인 136
 
4.9%
외국인 25
 
0.9%

외국어안내서비스
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.8 KiB
<NA>
1363 
없음
1295 
X
 
90
영어
 
24
유
 
4
Other values (4)
 
4

Length

Max length8
Median length7
Mean length2.9507194
Min length1

Unique

Unique4 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1363
49.0%
없음 1295
46.6%
X 90
 
3.2%
영어 24
 
0.9%
유 4
 
0.1%
영어, 스페인어 1
 
< 0.1%
영어, 일본어 1
 
< 0.1%
일본어 1
 
< 0.1%
ㅇ 1
 
< 0.1%

Length

2024-04-11T13:49:12.741199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T13:49:12.832722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1363
49.0%
없음 1295
46.5%
x 90
 
3.2%
영어 26
 
0.9%
유 4
 
0.1%
일본어 2
 
0.1%
스페인어 1
 
< 0.1%
ㅇ 1
 
< 0.1%

소재지도로명주소
Text

Distinct2654
Distinct (%)95.6%
Missing3
Missing (%)0.1%
Memory size21.8 KiB
2024-04-11T13:49:13.023056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length44
Mean length21.778538
Min length15

Characters and Unicode

Total characters60479
Distinct characters352
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2550 ?
Unique (%)91.8%

Sample

1st row경기도 가평군 설악면 뽕나뭇골길 31-6
2nd row경기도 가평군 청평면 모꼬지로 21
3rd row경기도 가평군 청평면 수리재길 322-70
4th row경기도 가평군 상면 청군로 776-98
5th row경기도 가평군 상면 임초밤안골로 119-119
ValueCountFrequency (%)
경기도 2777
 
20.0%
가평군 1086
 
7.8%
양평군 571
 
4.1%
단원구 359
 
2.6%
안산시 359
 
2.6%
북면 288
 
2.1%
포천시 230
 
1.7%
가평읍 226
 
1.6%
청평면 187
 
1.3%
상면 178
 
1.3%
Other values (2877) 7618
54.9%
2024-04-11T13:49:13.353777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11102
 
18.4%
도 2848
 
4.7%
기 2825
 
4.7%
경 2797
 
4.6%
1 2311
 
3.8%
평 2121
 
3.5%
면 2027
 
3.4%
군 1731
 
2.9%
길 1726
 
2.9%
2 1701
 
2.8%
Other values (342) 29290
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36046
59.6%
Decimal Number 11734
 
19.4%
Space Separator 11102
 
18.4%
Dash Punctuation 1562
 
2.6%
Other Punctuation 12
 
< 0.1%
Open Punctuation 11
 
< 0.1%
Close Punctuation 11
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 2848
 
7.9%
기 2825
 
7.8%
경 2797
 
7.8%
평 2121
 
5.9%
면 2027
 
5.6%
군 1731
 
4.8%
길 1726
 
4.8%
로 1527
 
4.2%
가 1441
 
4.0%
시 1078
 
3.0%
Other values (326) 15925
44.2%
Decimal Number
ValueCountFrequency (%)
1 2311
19.7%
2 1701
14.5%
3 1272
10.8%
4 1125
9.6%
7 924
 
7.9%
5 916
 
7.8%
6 902
 
7.7%
0 876
 
7.5%
8 871
 
7.4%
9 836
 
7.1%
Space Separator
ValueCountFrequency (%)
11102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1562
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36046
59.6%
Common 24433
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 2848
 
7.9%
기 2825
 
7.8%
경 2797
 
7.8%
평 2121
 
5.9%
면 2027
 
5.6%
군 1731
 
4.8%
길 1726
 
4.8%
로 1527
 
4.2%
가 1441
 
4.0%
시 1078
 
3.0%
Other values (326) 15925
44.2%
Common
ValueCountFrequency (%)
11102
45.4%
1 2311
 
9.5%
2 1701
 
7.0%
- 1562
 
6.4%
3 1272
 
5.2%
4 1125
 
4.6%
7 924
 
3.8%
5 916
 
3.7%
6 902
 
3.7%
0 876
 
3.6%
Other values (6) 1742
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36046
59.6%
ASCII 24433
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11102
45.4%
1 2311
 
9.5%
2 1701
 
7.0%
- 1562
 
6.4%
3 1272
 
5.2%
4 1125
 
4.6%
7 924
 
3.8%
5 916
 
3.7%
6 902
 
3.7%
0 876
 
3.6%
Other values (6) 1742
 
7.1%
Hangul
ValueCountFrequency (%)
도 2848
 
7.9%
기 2825
 
7.8%
경 2797
 
7.8%
평 2121
 
5.9%
면 2027
 
5.6%
군 1731
 
4.8%
길 1726
 
4.8%
로 1527
 
4.2%
가 1441
 
4.0%
시 1078
 
3.0%
Other values (326) 15925
44.2%

소재지지번주소
Text

Distinct2685
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size21.8 KiB
2024-04-11T13:49:13.611328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length42
Mean length22.867626
Min length14

Characters and Unicode

Total characters63572
Distinct characters265
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

Unique2600 ?
Unique (%)93.5%

Sample

1st row경기도 가평군 설악면 천안리 210번지
2nd row경기도 가평군 청평면 대성리 586-11번지
3rd row경기도 가평군 청평면 상천리 721-4번지
4th row경기도 가평군 상면 임초리 480번지
5th row경기도 가평군 상면 임초리 132번지
ValueCountFrequency (%)
경기도 2780
 
19.8%
가평군 1086
 
7.7%
양평군 573
 
4.1%
단원구 359
 
2.6%
안산시 359
 
2.6%
북면 288
 
2.1%
포천시 231
 
1.6%
가평읍 226
 
1.6%
청평면 187
 
1.3%
상면 178
 
1.3%
Other values (2927) 7777
55.4%
2024-04-11T13:49:13.986181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11264
 
17.7%
도 2952
 
4.6%
기 2816
 
4.4%
지 2815
 
4.4%
경 2794
 
4.4%
번 2762
 
4.3%
리 2357
 
3.7%
평 2155
 
3.4%
- 2135
 
3.4%
1 2041
 
3.2%
Other values (255) 29481
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39008
61.4%
Space Separator 11264
 
17.7%
Decimal Number 10957
 
17.2%
Dash Punctuation 2135
 
3.4%
Uppercase Letter 84
 
0.1%
Other Punctuation 60
 
0.1%
Open Punctuation 31
 
< 0.1%
Close Punctuation 31
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 2952
 
7.6%
기 2816
 
7.2%
지 2815
 
7.2%
경 2794
 
7.2%
번 2762
 
7.1%
리 2357
 
6.0%
평 2155
 
5.5%
면 2029
 
5.2%
군 1715
 
4.4%
가 1401
 
3.6%
Other values (230) 15212
39.0%
Decimal Number
ValueCountFrequency (%)
1 2041
18.6%
2 1484
13.5%
3 1310
12.0%
6 1170
10.7%
4 1090
9.9%
5 1003
9.2%
7 841
7.7%
8 715
 
6.5%
9 665
 
6.1%
0 638
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
A 36
42.9%
B 23
27.4%
C 10
 
11.9%
D 6
 
7.1%
E 3
 
3.6%
F 2
 
2.4%
I 2
 
2.4%
P 1
 
1.2%
V 1
 
1.2%
Space Separator
ValueCountFrequency (%)
11264
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2135
100.0%
Other Punctuation
ValueCountFrequency (%)
, 60
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39008
61.4%
Common 24480
38.5%
Latin 84
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 2952
 
7.6%
기 2816
 
7.2%
지 2815
 
7.2%
경 2794
 
7.2%
번 2762
 
7.1%
리 2357
 
6.0%
평 2155
 
5.5%
면 2029
 
5.2%
군 1715
 
4.4%
가 1401
 
3.6%
Other values (230) 15212
39.0%
Common
ValueCountFrequency (%)
11264
46.0%
- 2135
 
8.7%
1 2041
 
8.3%
2 1484
 
6.1%
3 1310
 
5.4%
6 1170
 
4.8%
4 1090
 
4.5%
5 1003
 
4.1%
7 841
 
3.4%
8 715
 
2.9%
Other values (6) 1427
 
5.8%
Latin
ValueCountFrequency (%)
A 36
42.9%
B 23
27.4%
C 10
 
11.9%
D 6
 
7.1%
E 3
 
3.6%
F 2
 
2.4%
I 2
 
2.4%
P 1
 
1.2%
V 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39008
61.4%
ASCII 24564
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11264
45.9%
- 2135
 
8.7%
1 2041
 
8.3%
2 1484
 
6.0%
3 1310
 
5.3%
6 1170
 
4.8%
4 1090
 
4.4%
5 1003
 
4.1%
7 841
 
3.4%
8 715
 
2.9%
Other values (15) 1511
 
6.2%
Hangul
ValueCountFrequency (%)
도 2952
 
7.6%
기 2816
 
7.2%
지 2815
 
7.2%
경 2794
 
7.2%
번 2762
 
7.1%
리 2357
 
6.0%
평 2155
 
5.5%
면 2029
 
5.2%
군 1715
 
4.4%
가 1401
 
3.6%
Other values (230) 15212
39.0%

전화번호
Text

MISSING 

Distinct220
Distinct (%)95.7%
Missing2550
Missing (%)91.7%
Memory size21.8 KiB
2024-04-11T13:49:14.204511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.086957
Min length9

Characters and Unicode

Total characters2780
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

Unique210 ?
Unique (%)91.3%

Sample

1st row02-387-9533
2nd row02-386-3638
3rd row02-383-8581
4th row02-353-7722
5th row031-393-2851
ValueCountFrequency (%)
031-771-9911 2
 
0.9%
031-774-5011 2
 
0.9%
031-593-1910 2
 
0.9%
031-885-6292 2
 
0.9%
0504-0904-2403 2
 
0.9%
031-553-8208 2
 
0.9%
031-862-0930 2
 
0.9%
031-883-7356 2
 
0.9%
1661-1114 2
 
0.9%
031-774-7673 2
 
0.9%
Other values (210) 210
91.3%
2024-04-11T13:49:14.519487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 458
16.5%
3 397
14.3%
0 369
13.3%
1 360
12.9%
7 306
11.0%
5 215
7.7%
8 160
 
5.8%
2 144
 
5.2%
4 142
 
5.1%
9 129
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2322
83.5%
Dash Punctuation 458
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 397
17.1%
0 369
15.9%
1 360
15.5%
7 306
13.2%
5 215
9.3%
8 160
6.9%
2 144
 
6.2%
4 142
 
6.1%
9 129
 
5.6%
6 100
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 458
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2780
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 458
16.5%
3 397
14.3%
0 369
13.3%
1 360
12.9%
7 306
11.0%
5 215
7.7%
8 160
 
5.8%
2 144
 
5.2%
4 142
 
5.1%
9 129
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2780
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 458
16.5%
3 397
14.3%
0 369
13.3%
1 360
12.9%
7 306
11.0%
5 215
7.7%
8 160
 
5.8%
2 144
 
5.2%
4 142
 
5.1%
9 129
 
4.6%

객실수
Real number (ℝ)

Distinct13
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1320144
Minimum1
Maximum83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.6 KiB
2024-04-11T13:49:14.615156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile6
Maximum83
Range82
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.2621111
Coefficient of variation (CV)0.72225438
Kurtosis558.50178
Mean3.1320144
Median Absolute Deviation (MAD)1
Skewness16.138791
Sum8707
Variance5.1171467
MonotonicityNot monotonic
2024-04-11T13:49:14.690721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2 638
22.9%
3 574
20.6%
1 532
19.1%
4 467
16.8%
5 320
11.5%
6 143
 
5.1%
7 91
 
3.3%
8 7
 
0.3%
9 3
 
0.1%
11 2
 
0.1%
Other values (3) 3
 
0.1%
ValueCountFrequency (%)
1 532
19.1%
2 638
22.9%
3 574
20.6%
4 467
16.8%
5 320
11.5%
6 143
 
5.1%
7 91
 
3.3%
8 7
 
0.3%
9 3
 
0.1%
11 2
 
0.1%
ValueCountFrequency (%)
83 1
 
< 0.1%
14 1
 
< 0.1%
12 1
 
< 0.1%
11 2
 
0.1%
9 3
 
0.1%
8 7
 
0.3%
7 91
 
3.3%
6 143
 
5.1%
5 320
11.5%
4 467
16.8%

부대시설
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct12
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size21.8 KiB
<NA>
2687 
없음
 
72
야외바베큐장
 
7
바베큐장, 주차장 등
 
6
카페
 
1
Other values (7)
 
7

Length

Max length13
Median length4
Mean length3.9744604
Min length2

Unique

Unique8 ?
Unique (%)0.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2687
96.7%
없음 72
 
2.6%
야외바베큐장 7
 
0.3%
바베큐장, 주차장 등 6
 
0.2%
카페 1
 
< 0.1%
미니풀장 1
 
< 0.1%
풀장 1
 
< 0.1%
수영장 1
 
< 0.1%
월풀욕조+야외바베큐장 1
 
< 0.1%
간이 수영장+야외바베큐장 1
 
< 0.1%
Other values (2) 2
 
0.1%

Length

2024-04-11T13:49:14.774400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2687
96.2%
없음 72
 
2.6%
야외바베큐장 8
 
0.3%
등 7
 
0.3%
바베큐장 6
 
0.2%
주차장 6
 
0.2%
카페 1
 
< 0.1%
미니풀장 1
 
< 0.1%
풀장 1
 
< 0.1%
수영장 1
 
< 0.1%
Other values (4) 4
 
0.1%

주차장보유여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing2017
Missing (%)72.6%
Memory size5.6 KiB
True
763 
(Missing)
2017 
ValueCountFrequency (%)
True 763
 
27.4%
(Missing) 2017
72.6%
2024-04-11T13:49:14.859365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

결제방법
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.8 KiB
<NA>
2635 
현금, 신용카드
 
69
현금
 
58
현금+신용카드
 
12
카드, 현금
 
6

Length

Max length8
Median length4
Mean length4.0748201
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2635
94.8%
현금, 신용카드 69
 
2.5%
현금 58
 
2.1%
현금+신용카드 12
 
0.4%
카드, 현금 6
 
0.2%

Length

2024-04-11T13:49:15.136070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T13:49:15.212922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2635
92.3%
현금 133
 
4.7%
신용카드 69
 
2.4%
현금+신용카드 12
 
0.4%
카드 6
 
0.2%

홈페이지주소
Text

MISSING 

Distinct43
Distinct (%)87.8%
Missing2731
Missing (%)98.2%
Memory size21.8 KiB
2024-04-11T13:49:15.374837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length23.571429
Min length2

Characters and Unicode

Total characters1155
Distinct characters53
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

Unique39 ?
Unique (%)79.6%

Sample

1st rowhttp://www.82gallery.com/
2nd rowhttp://blog.naver.com/moonriver527/
3rd rowhttp://www.gujeolcho.com
4th rowhttp://sosul.kr
5th rowhttp://sosul.kr
ValueCountFrequency (%)
없음 4
 
8.2%
http://www.bluebirdpark.com 2
 
4.1%
http://www.dookyun.com 2
 
4.1%
http://sosul.kr 2
 
4.1%
http://unique.pensionweb.kr 1
 
2.0%
http://yoonscozy.com 1
 
2.0%
https://brick00.modoo.at 1
 
2.0%
http://pumsilmalu.com 1
 
2.0%
http://page.yapen.co.kr/27291 1
 
2.0%
http://rodam.kr 1
 
2.0%
Other values (33) 33
67.3%
2024-04-11T13:49:15.665039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 127
 
11.0%
t 114
 
9.9%
. 90
 
7.8%
o 84
 
7.3%
w 70
 
6.1%
p 62
 
5.4%
h 54
 
4.7%
e 47
 
4.1%
: 45
 
3.9%
r 45
 
3.9%
Other values (43) 417
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 829
71.8%
Other Punctuation 262
 
22.7%
Decimal Number 43
 
3.7%
Other Letter 20
 
1.7%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 114
13.8%
o 84
 
10.1%
w 70
 
8.4%
p 62
 
7.5%
h 54
 
6.5%
e 47
 
5.7%
r 45
 
5.4%
a 45
 
5.4%
m 41
 
4.9%
c 34
 
4.1%
Other values (15) 233
28.1%
Other Letter
ValueCountFrequency (%)
음 4
20.0%
없 4
20.0%
목 1
 
5.0%
울 1
 
5.0%
여 1
 
5.0%
흥 1
 
5.0%
장 1
 
5.0%
단 1
 
5.0%
드 1
 
5.0%
레 1
 
5.0%
Other values (4) 4
20.0%
Decimal Number
ValueCountFrequency (%)
0 11
25.6%
2 8
18.6%
9 6
14.0%
1 5
11.6%
4 3
 
7.0%
6 2
 
4.7%
3 2
 
4.7%
5 2
 
4.7%
8 2
 
4.7%
7 2
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/ 127
48.5%
. 90
34.4%
: 45
 
17.2%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 829
71.8%
Common 306
 
26.5%
Hangul 20
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 114
13.8%
o 84
 
10.1%
w 70
 
8.4%
p 62
 
7.5%
h 54
 
6.5%
e 47
 
5.7%
r 45
 
5.4%
a 45
 
5.4%
m 41
 
4.9%
c 34
 
4.1%
Other values (15) 233
28.1%
Common
ValueCountFrequency (%)
/ 127
41.5%
. 90
29.4%
: 45
 
14.7%
0 11
 
3.6%
2 8
 
2.6%
9 6
 
2.0%
1 5
 
1.6%
4 3
 
1.0%
6 2
 
0.7%
3 2
 
0.7%
Other values (4) 7
 
2.3%
Hangul
ValueCountFrequency (%)
음 4
20.0%
없 4
20.0%
목 1
 
5.0%
울 1
 
5.0%
여 1
 
5.0%
흥 1
 
5.0%
장 1
 
5.0%
단 1
 
5.0%
드 1
 
5.0%
레 1
 
5.0%
Other values (4) 4
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1135
98.3%
Hangul 20
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 127
 
11.2%
t 114
 
10.0%
. 90
 
7.9%
o 84
 
7.4%
w 70
 
6.2%
p 62
 
5.5%
h 54
 
4.8%
e 47
 
4.1%
: 45
 
4.0%
r 45
 
4.0%
Other values (29) 397
35.0%
Hangul
ValueCountFrequency (%)
음 4
20.0%
없 4
20.0%
목 1
 
5.0%
울 1
 
5.0%
여 1
 
5.0%
흥 1
 
5.0%
장 1
 
5.0%
단 1
 
5.0%
드 1
 
5.0%
레 1
 
5.0%
Other values (4) 4
20.0%

주변관광정보
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct34
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size21.8 KiB
<NA>
2304 
유리섬박물관+베르아델승마클럽
 
117
선감어촌체험마을+탄도항
 
114
해맞이승마클럽+동주염전
 
64
바다향기테마파크+그랑꼬또와이너리+구봉도낙조전망대
 
52
Other values (29)
 
129

Length

Max length37
Median length4
Mean length5.6413669
Min length3

Unique

Unique14 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2304
82.9%
유리섬박물관+베르아델승마클럽 117
 
4.2%
선감어촌체험마을+탄도항 114
 
4.1%
해맞이승마클럽+동주염전 64
 
2.3%
바다향기테마파크+그랑꼬또와이너리+구봉도낙조전망대 52
 
1.9%
이포보+신륵사 34
 
1.2%
이포보+해여림식물원 29
 
1.0%
왕방산계곡 8
 
0.3%
유리섬박물관 7
 
0.3%
북한산국립공원 6
 
0.2%
Other values (24) 45
 
1.6%

Length

2024-04-11T13:49:15.779988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2304
82.1%
유리섬박물관+베르아델승마클럽 117
 
4.2%
선감어촌체험마을+탄도항 114
 
4.1%
해맞이승마클럽+동주염전 64
 
2.3%
바다향기테마파크+그랑꼬또와이너리+구봉도낙조전망대 52
 
1.9%
이포보+신륵사 34
 
1.2%
이포보+해여림식물원 29
 
1.0%
왕방산계곡 8
 
0.3%
유리섬박물관 7
 
0.2%
등 6
 
0.2%
Other values (40) 70
 
2.5%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct2643
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.651013
Minimum36.90334
Maximum38.214428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.6 KiB
2024-04-11T13:49:15.888197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.90334
5-th percentile37.222187
Q137.503855
median37.701598
Q337.848993
95-th percentile38.006067
Maximum38.214428
Range1.3110884
Interquartile range (IQR)0.34513775

Descriptive statistics

Standard deviation0.25449657
Coefficient of variation (CV)0.0067593551
Kurtosis-0.6236699
Mean37.651013
Median Absolute Deviation (MAD)0.17397648
Skewness-0.45244574
Sum104669.82
Variance0.064768503
MonotonicityNot monotonic
2024-04-11T13:49:15.992760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.9417107528 4
 
0.1%
38.0935941577 4
 
0.1%
37.7255672 4
 
0.1%
37.230563 4
 
0.1%
37.230837 4
 
0.1%
37.5924334 4
 
0.1%
37.7903904 3
 
0.1%
37.74718 3
 
0.1%
38.0379646 3
 
0.1%
37.233948 3
 
0.1%
Other values (2633) 2744
98.7%
ValueCountFrequency (%)
36.9033398 1
< 0.1%
36.9084548 1
< 0.1%
36.9120675 1
< 0.1%
36.940261 1
< 0.1%
36.9433952 1
< 0.1%
36.954558 1
< 0.1%
36.9593907 1
< 0.1%
36.962475 1
< 0.1%
36.9707809 1
< 0.1%
36.9823014 1
< 0.1%
ValueCountFrequency (%)
38.2144282041 1
< 0.1%
38.2106053092 1
< 0.1%
38.1568374 1
< 0.1%
38.1524679461 1
< 0.1%
38.1456005273 1
< 0.1%
38.14491322 1
< 0.1%
38.1426582 1
< 0.1%
38.1415536 1
< 0.1%
38.1334027113 1
< 0.1%
38.1316053527 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct2643
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.29004
Minimum126.39113
Maximum127.79744
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.6 KiB
2024-04-11T13:49:16.092014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.39113
5-th percentile126.58874
Q1127.24824
median127.39613
Q3127.50519
95-th percentile127.64023
Maximum127.79744
Range1.4063105
Interquartile range (IQR)0.25694338

Descriptive statistics

Standard deviation0.33320786
Coefficient of variation (CV)0.0026177056
Kurtosis0.091394167
Mean127.29004
Median Absolute Deviation (MAD)0.11487438
Skewness-1.1658101
Sum353866.32
Variance0.11102748
MonotonicityNot monotonic
2024-04-11T13:49:16.192643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.580403 6
 
0.2%
126.580231 6
 
0.2%
127.4570861 4
 
0.1%
127.3191152696 4
 
0.1%
127.5100854 4
 
0.1%
127.1336505706 4
 
0.1%
127.0566927 3
 
0.1%
126.624821 3
 
0.1%
126.6866581651 3
 
0.1%
127.5121337 3
 
0.1%
Other values (2633) 2740
98.6%
ValueCountFrequency (%)
126.391134 1
< 0.1%
126.391829 1
< 0.1%
126.392081 1
< 0.1%
126.39241 1
< 0.1%
126.450689 1
< 0.1%
126.5329736 1
< 0.1%
126.545042 1
< 0.1%
126.545081 1
< 0.1%
126.545201 1
< 0.1%
126.54523 2
0.1%
ValueCountFrequency (%)
127.797444475 3
0.1%
127.7947934275 1
 
< 0.1%
127.7946897469 1
 
< 0.1%
127.7914677089 1
 
< 0.1%
127.7912363328 1
 
< 0.1%
127.7899900354 1
 
< 0.1%
127.7896839147 1
 
< 0.1%
127.7880417331 1
 
< 0.1%
127.7774093593 1
 
< 0.1%
127.7746713483 1
 
< 0.1%

데이터기준일자
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size21.8 KiB
2024-02-20
1086 
2021-06-24
573 
2019-04-15
359 
2022-05-20
231 
2023-02-13
141 
Other values (16)
390 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row2024-02-20
2nd row2024-02-20
3rd row2024-02-20
4th row2024-02-20
5th row2024-02-20

Common Values

ValueCountFrequency (%)
2024-02-20 1086
39.1%
2021-06-24 573
20.6%
2019-04-15 359
 
12.9%
2022-05-20 231
 
8.3%
2023-02-13 141
 
5.1%
2023-02-24 90
 
3.2%
2022-01-31 79
 
2.8%
2023-06-15 67
 
2.4%
2022-06-03 46
 
1.7%
2019-03-31 39
 
1.4%
Other values (11) 69
 
2.5%

Length

2024-04-11T13:49:16.291446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-02-20 1086
39.1%
2021-06-24 573
20.6%
2019-04-15 359
 
12.9%
2022-05-20 231
 
8.3%
2023-02-13 141
 
5.1%
2023-02-24 90
 
3.2%
2022-01-31 79
 
2.8%
2023-06-15 67
 
2.4%
2022-06-03 46
 
1.7%
2019-03-31 39
 
1.4%
Other values (11) 69
 
2.5%

Interactions

2024-04-11T13:49:10.994583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:49:10.345907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:49:10.694449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:49:11.082885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:49:10.479172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:49:10.785526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:49:11.175219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:49:10.585665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:49:10.888669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-11T13:49:16.352243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명서비스대상구분외국어안내서비스객실수부대시설결제방법홈페이지주소주변관광정보위도경도데이터기준일자
업종명1.0000.0880.6490.2301.0001.0001.0001.0000.0970.3520.827
서비스대상구분0.0881.0000.7300.2400.7950.5271.0001.0000.6490.5490.998
외국어안내서비스0.6490.7301.0000.0000.0001.0001.0001.0000.5590.8270.913
객실수0.2300.2400.0001.0000.5540.4811.0000.7040.0000.1590.666
부대시설1.0000.7950.0000.5541.0000.9280.9470.9420.9080.8450.942
결제방법1.0000.5271.0000.4810.9281.0001.0000.9810.8370.9110.915
홈페이지주소1.0001.0001.0001.0000.9471.0001.0000.8651.0000.9391.000
주변관광정보1.0001.0001.0000.7040.9420.9810.8651.0000.9900.9781.000
위도0.0970.6490.5590.0000.9080.8371.0000.9901.0000.8440.910
경도0.3520.5490.8270.1590.8450.9110.9390.9780.8441.0000.907
데이터기준일자0.8270.9980.9130.6660.9420.9151.0001.0000.9100.9071.000
2024-04-11T13:49:16.456419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
서비스대상구분외국어안내서비스데이터기준일자업종명주변관광정보부대시설결제방법
서비스대상구분1.0000.6250.9430.1460.9680.6380.528
외국어안내서비스0.6251.0000.7560.4910.9410.0000.993
데이터기준일자0.9430.7561.0000.7570.9750.8140.837
업종명0.1460.4910.7571.0000.9670.9490.993
주변관광정보0.9680.9410.9750.9671.0000.7320.822
부대시설0.6380.0000.8140.9490.7321.0000.819
결제방법0.5280.9930.8370.9930.8220.8191.000
2024-04-11T13:49:16.563942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객실수위도경도업종명서비스대상구분외국어안내서비스부대시설결제방법주변관광정보데이터기준일자
객실수1.0000.005-0.0830.3750.0770.0000.3690.4760.4260.400
위도0.0051.0000.1240.0740.4970.3150.7280.7040.9050.641
경도-0.0830.1241.0000.2700.3930.4150.6050.6100.8340.633
업종명0.3750.0740.2701.0000.1460.4910.9490.9930.9670.757
서비스대상구분0.0770.4970.3930.1461.0000.6250.6380.5280.9680.943
외국어안내서비스0.0000.3150.4150.4910.6251.0000.0000.9930.9410.756
부대시설0.3690.7280.6050.9490.6380.0001.0000.8190.7320.814
결제방법0.4760.7040.6100.9930.5280.9930.8191.0000.8220.837
주변관광정보0.4260.9050.8340.9670.9680.9410.7320.8221.0000.975
데이터기준일자0.4000.6410.6330.7570.9430.7560.8140.8370.9751.000

Missing values

2024-04-11T13:49:11.324203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-11T13:49:11.547342image/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.
2024-04-11T13:49:11.684047image/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

업소명업종명서비스대상구분외국어안내서비스소재지도로명주소소재지지번주소전화번호객실수부대시설주차장보유여부결제방법홈페이지주소주변관광정보위도경도데이터기준일자
0아쉬람펜션민박내국인+외국인없음경기도 가평군 설악면 뽕나뭇골길 31-6경기도 가평군 설악면 천안리 210번지<NA>4<NA><NA><NA><NA><NA>37.642523127.4804322024-02-20
1건아들 펜션민박내국인+외국인없음경기도 가평군 청평면 모꼬지로 21경기도 가평군 청평면 대성리 586-11번지<NA>4<NA><NA><NA><NA><NA>37.680949127.3752952024-02-20
2샘물향기민박내국인+외국인없음경기도 가평군 청평면 수리재길 322-70경기도 가평군 청평면 상천리 721-4번지<NA>4<NA><NA><NA><NA><NA>37.789555127.4350812024-02-20
3모이스티 펜션민박내국인+외국인없음경기도 가평군 상면 청군로 776-98경기도 가평군 상면 임초리 480번지<NA>6<NA><NA><NA><NA><NA>37.781473127.3742812024-02-20
4마당과 다락방민박내국인+외국인없음경기도 가평군 상면 임초밤안골로 119-119경기도 가평군 상면 임초리 132번지<NA>2<NA><NA><NA><NA><NA>37.756243127.3775232024-02-20
5산넘어 단체 수영장민박내국인+외국인없음경기도 가평군 조종면 운악청계로371번길 77-32경기도 가평군 조종면 신상리 262-36번지<NA>4<NA><NA><NA><NA><NA>37.851344127.3486592024-02-20
6가르텐하임 애견 동반 펜션민박내국인+외국인없음경기도 가평군 북면 백둔로 549-91경기도 가평군 북면 백둔리 579-9번지<NA>5<NA><NA><NA><NA><NA>37.904727127.4489642024-02-20
7별내리는 펜션민박내국인+외국인없음경기도 가평군 청평면 남이터길 52-49경기도 가평군 청평면 대성리 430-10번지<NA>3<NA><NA><NA><NA><NA>37.689827127.37422024-02-20
8산아래펜션민박내국인+외국인없음경기도 가평군 설악면 유명산길 110경기도 가평군 설악면 가일리 226-3번지<NA>4<NA><NA><NA><NA><NA>37.592963127.488342024-02-20
9흙집펜션민박내국인+외국인없음경기도 가평군 가평읍 태봉두밀로 87경기도 가평군 가평읍 하색리 701-15번지<NA>2<NA><NA><NA><NA><NA>37.806184127.477282024-02-20
업소명업종명서비스대상구분외국어안내서비스소재지도로명주소소재지지번주소전화번호객실수부대시설주차장보유여부결제방법홈페이지주소주변관광정보위도경도데이터기준일자
2770굿모닝펜션민박내국인+외국인<NA>경기도 포천시 영북면 우물목길 156경기도 포천시 영북면 산정리 716번지031-534-73134<NA><NA><NA><NA><NA>38.051559127.3079692022-05-20
2771렛잇비민박내국인+외국인<NA>경기도 포천시 영북면 우물목1길 32-8경기도 포천시 영북면 산정리 723-1번지031-531-88896<NA><NA><NA><NA><NA>38.049393127.3064472022-05-20
2772화이트하우스민박내국인+외국인<NA>경기도 포천시 영북면 우물목1길 32-4경기도 포천시 영북면 산정리 723-10번지<NA>2<NA><NA><NA><NA><NA>38.049196127.3069042022-05-20
2773산골민박민박내국인+외국인<NA>경기도 포천시 영북면 우물목1길 27경기도 포천시 영북면 산정리 723-17번지<NA>2<NA><NA><NA><NA><NA>38.049341127.3074162022-05-20
2774샘골민박민박내국인+외국인<NA>경기도 포천시 영북면 우물목1길 24-3경기도 포천시 영북면 산정리 723-6번지031-532-11092<NA><NA><NA><NA><NA>38.049728127.3071082022-05-20
2775억새꽃 (아일랜드)민박내국인+외국인<NA>경기도 포천시 영북면 산정호수로 911경기도 포천시 영북면 산정리 425-2번지 억새꽃펜션031-533-24902<NA><NA><NA><NA><NA>38.081166127.3192372022-05-20
2776휴가펜션(레드콩)민박내국인+외국인<NA>경기도 포천시 일동면 운악청계로1480번길 90-114경기도 포천시 일동면 기산리 1-81번지031-531-31215<NA><NA><NA><NA><NA>37.936406127.3480542022-05-20
2777다은이네 민박민박내국인+외국인<NA>경기도 포천시 관인면 지장산길 123-8경기도 포천시 관인면 중리 898-1번지<NA>4<NA><NA><NA><NA><NA>38.102488127.1924782022-05-20
2778삼밭골민박내국인+외국인<NA>경기도 포천시 가산면 마전길 291경기도 포천시 가산면 마전리 73-1번지<NA>2<NA><NA><NA><NA><NA>37.845319127.2274542022-05-20
2779이뉴펜션민박내국인+외국인<NA>경기도 포천시 신북면 탑신로 1070경기도 포천시 신북면 금동리 155-2번지 C동<NA>1<NA><NA><NA><NA><NA>37.941711127.1336512022-05-20