Overview

Dataset statistics

Number of variables14
Number of observations100
Missing cells4
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.6 KiB
Average record size in memory118.3 B

Variable types

Numeric4
Categorical6
Text4

Alerts

title_nm is highly overall correlated with seq_no and 2 other fieldsHigh correlation
media_ty is highly overall correlated with title_nm and 1 other fieldsHigh correlation
last_updt_de is highly overall correlated with lc_la and 3 other fieldsHigh correlation
seq_no is highly overall correlated with title_nmHigh correlation
lc_la is highly overall correlated with last_updt_deHigh correlation
lc_lo is highly overall correlated with last_updt_deHigh correlation
rest_time is highly imbalanced (82.8%)Imbalance
rstde_guid_cn is highly imbalanced (56.8%)Imbalance
tel_no has 4 (4.0%) missing valuesMissing
seq_no has unique valuesUnique
relate_place_dc has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:43:55.212481
Analysis finished2023-12-10 09:44:01.208294
Duration6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

seq_no
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean501.07
Minimum1
Maximum15034
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:44:01.380952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.95
Q127.75
median53.5
Q378.25
95-th percentile98.05
Maximum15034
Range15033
Interquartile range (IQR)50.5

Descriptive statistics

Standard deviation2568.66
Coefficient of variation (CV)5.1263496
Kurtosis29.88985
Mean501.07
Median Absolute Deviation (MAD)25.5
Skewness5.5935738
Sum50107
Variance6598014.3
MonotonicityNot monotonic
2023-12-10T18:44:01.769010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
9 1
1.0%
10 1
1.0%
11 1
1.0%
12 1
1.0%
ValueCountFrequency (%)
15034 1
1.0%
15033 1
1.0%
15032 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%

media_ty
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
drama
61 
show
31 
movie

Length

Max length5
Median length5
Mean length4.69
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
drama 61
61.0%
show 31
31.0%
movie 8
 
8.0%

Length

2023-12-10T18:44:02.053950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:44:02.274837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
drama 61
61.0%
show 31
31.0%
movie 8
 
8.0%

title_nm
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
18 어게인
27 
1박2일 시즌1
26 
(아는 건 별로 없지만) 가족입니다
22 
1987
#좋맛탱: 좋은 맛에 취하다
Other values (4)
12 

Length

Max length27
Median length19
Mean length10.44
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row(아는 건 별로 없지만) 가족입니다
2nd rowYou Raise Me Up (유 레이즈 미 업)
3rd row(아는 건 별로 없지만) 가족입니다
4th row(아는 건 별로 없지만) 가족입니다
5th row(아는 건 별로 없지만) 가족입니다

Common Values

ValueCountFrequency (%)
18 어게인 27
27.0%
1박2일 시즌1 26
26.0%
(아는 건 별로 없지만) 가족입니다 22
22.0%
1987 8
 
8.0%
#좋맛탱: 좋은 맛에 취하다 5
 
5.0%
1박2일 시즌4 5
 
5.0%
You Raise Me Up (유 레이즈 미 업) 3
 
3.0%
1%의 어떤것 3
 
3.0%
17세의 조건 1
 
1.0%

Length

2023-12-10T18:44:02.501385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:44:02.711321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1박2일 31
10.8%
18 27
9.4%
어게인 27
9.4%
시즌1 26
9.1%
아는 22
 
7.7%
22
 
7.7%
별로 22
 
7.7%
없지만 22
 
7.7%
가족입니다 22
 
7.7%
1987 8
 
2.8%
Other values (17) 57
19.9%
Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:44:03.174562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length6.47
Min length2

Characters and Unicode

Total characters647
Distinct characters246
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row커피파머
2nd row해밀톤 호텔별관
3rd row카페 그루비
4th row미리내 성지
5th row초은당
ValueCountFrequency (%)
청계천 2
 
1.5%
청담점 2
 
1.5%
해수욕장 2
 
1.5%
본점 2
 
1.5%
서울대교구 1
 
0.7%
주교좌명동대성당 1
 
0.7%
서울특별시청 1
 
0.7%
연희네 1
 
0.7%
슈퍼 1
 
0.7%
옛날초당순두부 1
 
0.7%
Other values (122) 122
89.7%
2023-12-10T18:44:03.930618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
 
5.6%
14
 
2.2%
11
 
1.7%
10
 
1.5%
10
 
1.5%
10
 
1.5%
10
 
1.5%
9
 
1.4%
9
 
1.4%
9
 
1.4%
Other values (236) 519
80.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 595
92.0%
Space Separator 36
 
5.6%
Decimal Number 13
 
2.0%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
14
 
2.4%
11
 
1.8%
10
 
1.7%
10
 
1.7%
10
 
1.7%
10
 
1.7%
9
 
1.5%
9
 
1.5%
9
 
1.5%
9
 
1.5%
Other values (226) 494
83.0%
Decimal Number
ValueCountFrequency (%)
1 3
23.1%
3 3
23.1%
5 2
15.4%
9 2
15.4%
2 2
15.4%
6 1
 
7.7%
Space Separator
ValueCountFrequency (%)
36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 595
92.0%
Common 51
 
7.9%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
14
 
2.4%
11
 
1.8%
10
 
1.7%
10
 
1.7%
10
 
1.7%
10
 
1.7%
9
 
1.5%
9
 
1.5%
9
 
1.5%
9
 
1.5%
Other values (226) 494
83.0%
Common
ValueCountFrequency (%)
36
70.6%
1 3
 
5.9%
3 3
 
5.9%
5 2
 
3.9%
9 2
 
3.9%
2 2
 
3.9%
) 1
 
2.0%
( 1
 
2.0%
6 1
 
2.0%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 595
92.0%
ASCII 52
 
8.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
69.2%
1 3
 
5.8%
3 3
 
5.8%
5 2
 
3.8%
9 2
 
3.8%
2 2
 
3.8%
) 1
 
1.9%
( 1
 
1.9%
6 1
 
1.9%
C 1
 
1.9%
Hangul
ValueCountFrequency (%)
14
 
2.4%
11
 
1.8%
10
 
1.7%
10
 
1.7%
10
 
1.7%
10
 
1.7%
9
 
1.5%
9
 
1.5%
9
 
1.5%
9
 
1.5%
Other values (226) 494
83.0%

place_ty
Categorical

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
playground
57 
restaurant
25 
cafe
stay
station
 
1

Length

Max length10
Median length10
Mean length8.96
Min length4

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st rowcafe
2nd rowstay
3rd rowcafe
4th rowplayground
5th rowplayground

Common Values

ValueCountFrequency (%)
playground 57
57.0%
restaurant 25
25.0%
cafe 8
 
8.0%
stay 8
 
8.0%
station 1
 
1.0%
store 1
 
1.0%

Length

2023-12-10T18:44:04.226398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:44:04.422339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
playground 57
57.0%
restaurant 25
25.0%
cafe 8
 
8.0%
stay 8
 
8.0%
station 1
 
1.0%
store 1
 
1.0%

relate_place_dc
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:44:05.090149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length245
Median length85
Mean length56
Min length14

Characters and Unicode

Total characters5600
Distinct characters488
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row6회에서 김은희(한예리)와 안효석(이종원)이 윤태형(김태호)의 은신처에서 서울로 돌아갈 때 이 카페에 들린다.
2nd row7회에서 도지혁(박기웅)이 이 술집에서 술을 마신다.
3rd row안효석(이종원)은 바리스타로, 김은주(추자현)는 단골손님이다. 1화에서 이진숙(원미경)이 자녀와 사위에게 폭탄을 떨어뜨리는 장면이 나온다.
4th row시누이 도혜지(황우슬혜)는 남편이 가문의 회사를 상속받을 수 있도록 그녀가 길을 잃지 않기를 바라는 한편, 세리의 비서 홍씨(고규필)과 동시에 그녀가 가능한 한 빨리 발견되기를 기도한다.
5th row김은희(한예리)와 동료 서경옥(가득희)은 1회에서 작가 의뢰인을 만나기 위해 이 한옥을 방문한다. 추후 은희는 여기로 돌아와 작가의 명상 세션에 참여합니다. 은희는 눈을 감고 자신의 인생에서 가장 긴 날인 2016년 3월 10일을 회상한다. 세션이 끝난 후 동생 김지우(신재하)와 소원해진 절친 박찬을 보고 놀란다.
ValueCountFrequency (%)
38
 
3.1%
촬영한 11
 
0.9%
위해 10
 
0.8%
함께 10
 
0.8%
방문한 10
 
0.8%
맛집 9
 
0.7%
1박2일 8
 
0.6%
8
 
0.6%
8회에서 7
 
0.6%
12회에서 7
 
0.6%
Other values (879) 1115
90.4%
2023-12-10T18:44:06.079618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1133
 
20.2%
181
 
3.2%
132
 
2.4%
131
 
2.3%
( 125
 
2.2%
) 125
 
2.2%
100
 
1.8%
100
 
1.8%
. 91
 
1.6%
84
 
1.5%
Other values (478) 3398
60.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3927
70.1%
Space Separator 1133
 
20.2%
Decimal Number 153
 
2.7%
Open Punctuation 125
 
2.2%
Close Punctuation 125
 
2.2%
Other Punctuation 119
 
2.1%
Uppercase Letter 17
 
0.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
181
 
4.6%
132
 
3.4%
131
 
3.3%
100
 
2.5%
100
 
2.5%
84
 
2.1%
81
 
2.1%
72
 
1.8%
62
 
1.6%
60
 
1.5%
Other values (449) 2924
74.5%
Decimal Number
ValueCountFrequency (%)
1 54
35.3%
2 29
19.0%
8 22
14.4%
7 13
 
8.5%
9 10
 
6.5%
5 7
 
4.6%
4 6
 
3.9%
0 6
 
3.9%
6 4
 
2.6%
3 2
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
S 3
17.6%
L 2
11.8%
E 2
11.8%
N 2
11.8%
P 2
11.8%
F 2
11.8%
O 1
 
5.9%
H 1
 
5.9%
V 1
 
5.9%
U 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 91
76.5%
, 22
 
18.5%
' 2
 
1.7%
/ 2
 
1.7%
& 2
 
1.7%
Space Separator
ValueCountFrequency (%)
1133
100.0%
Open Punctuation
ValueCountFrequency (%)
( 125
100.0%
Close Punctuation
ValueCountFrequency (%)
) 125
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3927
70.1%
Common 1656
29.6%
Latin 17
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
181
 
4.6%
132
 
3.4%
131
 
3.3%
100
 
2.5%
100
 
2.5%
84
 
2.1%
81
 
2.1%
72
 
1.8%
62
 
1.6%
60
 
1.5%
Other values (449) 2924
74.5%
Common
ValueCountFrequency (%)
1133
68.4%
( 125
 
7.5%
) 125
 
7.5%
. 91
 
5.5%
1 54
 
3.3%
2 29
 
1.8%
, 22
 
1.3%
8 22
 
1.3%
7 13
 
0.8%
9 10
 
0.6%
Other values (9) 32
 
1.9%
Latin
ValueCountFrequency (%)
S 3
17.6%
L 2
11.8%
E 2
11.8%
N 2
11.8%
P 2
11.8%
F 2
11.8%
O 1
 
5.9%
H 1
 
5.9%
V 1
 
5.9%
U 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3927
70.1%
ASCII 1673
29.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1133
67.7%
( 125
 
7.5%
) 125
 
7.5%
. 91
 
5.4%
1 54
 
3.2%
2 29
 
1.7%
, 22
 
1.3%
8 22
 
1.3%
7 13
 
0.8%
9 10
 
0.6%
Other values (19) 49
 
2.9%
Hangul
ValueCountFrequency (%)
181
 
4.6%
132
 
3.4%
131
 
3.3%
100
 
2.5%
100
 
2.5%
84
 
2.1%
81
 
2.1%
72
 
1.8%
62
 
1.6%
60
 
1.5%
Other values (449) 2924
74.5%
Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:44:06.438483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length12
Mean length16.89
Min length4

Characters and Unicode

Total characters1689
Distinct characters64
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

Unique54 ?
Unique (%)54.0%

Sample

1st row매일 09시 - 21시
2nd row가게별 상이
3rd row매일 12시 - 22시
4th row매일 09시 - 17시
5th row매일 11시 - 20시
ValueCountFrequency (%)
114
22.0%
매일 74
14.3%
24시 38
 
7.3%
00시 34
 
6.6%
11시 20
 
3.9%
10시 19
 
3.7%
30분 19
 
3.7%
09시 17
 
3.3%
22시 16
 
3.1%
21시 16
 
3.1%
Other values (52) 152
29.3%
2023-12-10T18:44:07.063257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
421
24.9%
237
14.0%
0 144
 
8.5%
- 138
 
8.2%
1 128
 
7.6%
2 110
 
6.5%
101
 
6.0%
74
 
4.4%
4 42
 
2.5%
, 28
 
1.7%
Other values (54) 266
15.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 573
33.9%
Decimal Number 509
30.1%
Space Separator 421
24.9%
Dash Punctuation 138
 
8.2%
Other Punctuation 28
 
1.7%
Close Punctuation 10
 
0.6%
Open Punctuation 10
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
237
41.4%
101
17.6%
74
 
12.9%
19
 
3.3%
13
 
2.3%
13
 
2.3%
9
 
1.6%
7
 
1.2%
7
 
1.2%
6
 
1.0%
Other values (39) 87
 
15.2%
Decimal Number
ValueCountFrequency (%)
0 144
28.3%
1 128
25.1%
2 110
21.6%
4 42
 
8.3%
3 26
 
5.1%
9 26
 
5.1%
8 12
 
2.4%
5 8
 
1.6%
7 8
 
1.6%
6 5
 
1.0%
Space Separator
ValueCountFrequency (%)
421
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 138
100.0%
Other Punctuation
ValueCountFrequency (%)
, 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1116
66.1%
Hangul 573
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
237
41.4%
101
17.6%
74
 
12.9%
19
 
3.3%
13
 
2.3%
13
 
2.3%
9
 
1.6%
7
 
1.2%
7
 
1.2%
6
 
1.0%
Other values (39) 87
 
15.2%
Common
ValueCountFrequency (%)
421
37.7%
0 144
 
12.9%
- 138
 
12.4%
1 128
 
11.5%
2 110
 
9.9%
4 42
 
3.8%
, 28
 
2.5%
3 26
 
2.3%
9 26
 
2.3%
8 12
 
1.1%
Other values (5) 41
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1116
66.1%
Hangul 573
33.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
421
37.7%
0 144
 
12.9%
- 138
 
12.4%
1 128
 
11.5%
2 110
 
9.9%
4 42
 
3.8%
, 28
 
2.5%
3 26
 
2.3%
9 26
 
2.3%
8 12
 
1.1%
Other values (5) 41
 
3.7%
Hangul
ValueCountFrequency (%)
237
41.4%
101
17.6%
74
 
12.9%
19
 
3.3%
13
 
2.3%
13
 
2.3%
9
 
1.6%
7
 
1.2%
7
 
1.2%
6
 
1.0%
Other values (39) 87
 
15.2%

rest_time
Categorical

IMBALANCE 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
정보없음
94 
화-목 15시 - 17시, 주말 15시 30분 - 16시 30분
 
1
15시 - 17시
 
1
14시 30분 - 17시 30분
 
1
12시 - 13시
 
1
Other values (2)
 
2

Length

Max length35
Median length4
Mean length4.72
Min length4

Unique

Unique6 ?
Unique (%)6.0%

Sample

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

Common Values

ValueCountFrequency (%)
정보없음 94
94.0%
화-목 15시 - 17시, 주말 15시 30분 - 16시 30분 1
 
1.0%
15시 - 17시 1
 
1.0%
14시 30분 - 17시 30분 1
 
1.0%
12시 - 13시 1
 
1.0%
15시 30분 - 16시 1
 
1.0%
15시 20분 - 16시 1
 
1.0%

Length

2023-12-10T18:44:07.315210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:44:07.521864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정보없음 94
76.4%
7
 
5.7%
15시 5
 
4.1%
30분 5
 
4.1%
17시 3
 
2.4%
16시 3
 
2.4%
화-목 1
 
0.8%
주말 1
 
0.8%
14시 1
 
0.8%
12시 1
 
0.8%
Other values (2) 2
 
1.6%

rstde_guid_cn
Categorical

IMBALANCE 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
연중무휴
74 
월요일
일요일
 
4
명절(당일)
 
2
주말
 
2
Other values (9)

Length

Max length16
Median length4
Mean length4.32
Min length2

Unique

Unique9 ?
Unique (%)9.0%

Sample

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

Common Values

ValueCountFrequency (%)
연중무휴 74
74.0%
월요일 9
 
9.0%
일요일 4
 
4.0%
명절(당일) 2
 
2.0%
주말 2
 
2.0%
정보없음 1
 
1.0%
월요일, 명절, 공휴일 다음날 1
 
1.0%
화요일 1
 
1.0%
평일 1
 
1.0%
임시휴업(~ 2023년 6월) 1
 
1.0%
Other values (4) 4
 
4.0%

Length

2023-12-10T18:44:07.751277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연중무휴 74
65.5%
월요일 11
 
9.7%
일요일 5
 
4.4%
3번째 4
 
3.5%
1 4
 
3.5%
명절(당일 2
 
1.8%
주말 2
 
1.8%
화요일 2
 
1.8%
임시휴업 1
 
0.9%
6월 1
 
0.9%
Other values (7) 7
 
6.2%

addr
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:44:08.168059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length19.56
Min length13

Characters and Unicode

Total characters1956
Distinct characters181
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

Unique98 ?
Unique (%)98.0%

Sample

1st row경기도 고양시 일산서구 대화로 61
2nd row서울특별시 용산구 이태원로27가길 26
3rd row경기도 수원시 영통구 센트럴파크로127번길 148
4th row경기도 안성시 양성면 미리내성지로 420
5th row경기도 양평군 서종면 북한강로814번길 46-6
ValueCountFrequency (%)
서울특별시 46
 
10.5%
경기도 16
 
3.7%
강원도 14
 
3.2%
종로구 13
 
3.0%
마포구 12
 
2.7%
중구 10
 
2.3%
용산구 8
 
1.8%
파주시 7
 
1.6%
전라남도 5
 
1.1%
부산광역시 4
 
0.9%
Other values (261) 302
69.1%
2023-12-10T18:44:08.926990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
337
 
17.2%
84
 
4.3%
75
 
3.8%
1 73
 
3.7%
61
 
3.1%
54
 
2.8%
51
 
2.6%
50
 
2.6%
50
 
2.6%
49
 
2.5%
Other values (171) 1072
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1269
64.9%
Space Separator 337
 
17.2%
Decimal Number 329
 
16.8%
Dash Punctuation 20
 
1.0%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
84
 
6.6%
75
 
5.9%
61
 
4.8%
54
 
4.3%
51
 
4.0%
50
 
3.9%
50
 
3.9%
49
 
3.9%
47
 
3.7%
28
 
2.2%
Other values (158) 720
56.7%
Decimal Number
ValueCountFrequency (%)
1 73
22.2%
2 42
12.8%
4 34
10.3%
6 30
9.1%
5 28
 
8.5%
3 28
 
8.5%
7 27
 
8.2%
0 26
 
7.9%
8 21
 
6.4%
9 20
 
6.1%
Space Separator
ValueCountFrequency (%)
337
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1269
64.9%
Common 686
35.1%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
84
 
6.6%
75
 
5.9%
61
 
4.8%
54
 
4.3%
51
 
4.0%
50
 
3.9%
50
 
3.9%
49
 
3.9%
47
 
3.7%
28
 
2.2%
Other values (158) 720
56.7%
Common
ValueCountFrequency (%)
337
49.1%
1 73
 
10.6%
2 42
 
6.1%
4 34
 
5.0%
6 30
 
4.4%
5 28
 
4.1%
3 28
 
4.1%
7 27
 
3.9%
0 26
 
3.8%
8 21
 
3.1%
Other values (2) 40
 
5.8%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1269
64.9%
ASCII 687
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
337
49.1%
1 73
 
10.6%
2 42
 
6.1%
4 34
 
4.9%
6 30
 
4.4%
5 28
 
4.1%
3 28
 
4.1%
7 27
 
3.9%
0 26
 
3.8%
8 21
 
3.1%
Other values (3) 41
 
6.0%
Hangul
ValueCountFrequency (%)
84
 
6.6%
75
 
5.9%
61
 
4.8%
54
 
4.3%
51
 
4.0%
50
 
3.9%
50
 
3.9%
49
 
3.9%
47
 
3.7%
28
 
2.2%
Other values (158) 720
56.7%

lc_la
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.084996
Minimum33.119912
Maximum38.202626
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:44:09.280489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.119912
5-th percentile34.718039
Q137.289172
median37.549555
Q337.581089
95-th percentile37.895913
Maximum38.202626
Range5.082714
Interquartile range (IQR)0.2919175

Descriptive statistics

Standard deviation1.12949
Coefficient of variation (CV)0.030456792
Kurtosis3.4168808
Mean37.084996
Median Absolute Deviation (MAD)0.113537
Skewness-2.0729751
Sum3708.4996
Variance1.2757476
MonotonicityNot monotonic
2023-12-10T18:44:09.641390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.569205 2
 
2.0%
37.667523 1
 
1.0%
37.5632772 1
 
1.0%
37.51688 1
 
1.0%
37.952463 1
 
1.0%
37.274739 1
 
1.0%
37.198816 1
 
1.0%
38.202626 1
 
1.0%
37.786707 1
 
1.0%
36.46255 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
33.119912 1
1.0%
33.394065 1
1.0%
33.503296 1
1.0%
33.518829 1
1.0%
34.585051 1
1.0%
34.725038 1
1.0%
34.78168 1
1.0%
34.808882 1
1.0%
34.88597 1
1.0%
35.096659 1
1.0%
ValueCountFrequency (%)
38.202626 1
1.0%
38.076823 1
1.0%
38.029391 1
1.0%
37.952463 1
1.0%
37.951966 1
1.0%
37.892963 1
1.0%
37.889542 1
1.0%
37.866729 1
1.0%
37.846843 1
1.0%
37.842094 1
1.0%

lc_lo
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.30908
Minimum126.13356
Maximum129.16037
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:44:10.051597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.13356
5-th percentile126.45346
Q1126.92079
median126.98494
Q3127.49653
95-th percentile128.89966
Maximum129.16037
Range3.026805
Interquartile range (IQR)0.575732

Descriptive statistics

Standard deviation0.78308478
Coefficient of variation (CV)0.0061510518
Kurtosis0.043748983
Mean127.30908
Median Absolute Deviation (MAD)0.1225905
Skewness1.1407607
Sum12730.908
Variance0.61322177
MonotonicityNot monotonic
2023-12-10T18:44:10.760273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.97791 2
 
2.0%
126.72817 1
 
1.0%
126.986827 1
 
1.0%
128.727662 1
 
1.0%
128.358508 1
 
1.0%
128.014985 1
 
1.0%
128.486792 1
 
1.0%
128.593672 1
 
1.0%
128.892774 1
 
1.0%
127.4906 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
126.13356 1
1.0%
126.239527 1
1.0%
126.267075 1
1.0%
126.372515 1
1.0%
126.377325 1
1.0%
126.45747 1
1.0%
126.492183 1
1.0%
126.52777 1
1.0%
126.567914 1
1.0%
126.637203 1
1.0%
ValueCountFrequency (%)
129.160365 1
1.0%
129.061529 1
1.0%
129.049232 1
1.0%
129.042622 1
1.0%
129.030502 1
1.0%
128.892774 1
1.0%
128.892121 1
1.0%
128.874568 1
1.0%
128.86688 1
1.0%
128.727802 1
1.0%

tel_no
Real number (ℝ)

MISSING 

Distinct90
Distinct (%)93.8%
Missing4
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean5.726426 × 109
Minimum15449053
Maximum5.0713801 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:44:11.042202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15449053
5-th percentile24596790
Q12.2248619 × 108
median3.215147 × 108
Q35.4856543 × 108
95-th percentile5.0713335 × 1010
Maximum5.0713801 × 1010
Range5.0698352 × 1010
Interquartile range (IQR)3.2607923 × 108

Descriptive statistics

Standard deviation1.5454495 × 1010
Coefficient of variation (CV)2.6988029
Kurtosis4.967846
Mean5.726426 × 109
Median Absolute Deviation (MAD)1.0023814 × 108
Skewness2.6129861
Sum5.497369 × 1011
Variance2.3884142 × 1020
MonotonicityNot monotonic
2023-12-10T18:44:11.316090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
221481114 4
 
4.0%
222906114 2
 
2.0%
231538114 2
 
2.0%
221996114 2
 
2.0%
50713330557 1
 
1.0%
318852502 1
 
1.0%
334356035 1
 
1.0%
15449053 1
 
1.0%
335638787 1
 
1.0%
334610419 1
 
1.0%
Other values (80) 80
80.0%
(Missing) 4
 
4.0%
ValueCountFrequency (%)
15449053 1
1.0%
16703856 1
1.0%
23005500 1
1.0%
23255353 1
1.0%
23365157 1
1.0%
25007335 1
1.0%
25424073 1
1.0%
25486020 1
1.0%
25957148 1
1.0%
27251481 1
1.0%
ValueCountFrequency (%)
50713801301 1
1.0%
50713770887 1
1.0%
50713641888 1
1.0%
50713571970 1
1.0%
50713350144 1
1.0%
50713330557 1
1.0%
50713305416 1
1.0%
50713292501 1
1.0%
50713149449 1
1.0%
50713110060 1
1.0%

last_updt_de
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20221125
61 
20221118
39 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20221125
2nd row20221125
3rd row20221125
4th row20221125
5th row20221125

Common Values

ValueCountFrequency (%)
20221125 61
61.0%
20221118 39
39.0%

Length

2023-12-10T18:44:11.580438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:44:11.840369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20221125 61
61.0%
20221118 39
39.0%

Interactions

2023-12-10T18:43:59.835065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:43:57.369761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:43:58.070170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:43:58.758581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:44:00.029668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:43:57.552469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:43:58.237951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:43:58.936609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:44:00.200460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:43:57.725339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:43:58.381678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:43:59.206085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:44:00.392037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:43:57.896029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:43:58.597308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:43:59.623035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:44:11.996554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
seq_nomedia_tytitle_nmplace_nmplace_tyrelate_place_dcoper_timerest_timerstde_guid_cnaddrlc_lalc_lotel_nolast_updt_de
seq_no1.0000.0001.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.000
media_ty0.0001.0001.0001.0000.4631.0000.5520.2560.3641.0000.7390.6400.2771.000
title_nm1.0001.0001.0000.0000.7351.0000.0000.0000.0000.0000.5550.3920.2941.000
place_nm0.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
place_ty0.0000.4630.7351.0001.0001.0000.8530.0000.0001.0000.0000.0000.4660.432
relate_place_dc1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
oper_time0.0000.5520.0001.0000.8531.0001.0000.9850.9921.0000.6200.7540.9990.444
rest_time0.0000.2560.0001.0000.0001.0000.9851.0000.6891.0000.0000.2930.0000.076
rstde_guid_cn0.0000.3640.0001.0000.0001.0000.9920.6891.0001.0000.6740.3630.2930.074
addr0.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
lc_la0.0000.7390.5551.0000.0001.0000.6200.0000.6741.0001.0000.6410.0000.611
lc_lo0.0000.6400.3921.0000.0001.0000.7540.2930.3631.0000.6411.0000.0000.792
tel_no0.0000.2770.2941.0000.4661.0000.9990.0000.2931.0000.0000.0001.0000.117
last_updt_de0.0001.0001.0001.0000.4321.0000.4440.0760.0741.0000.6110.7920.1171.000
2023-12-10T18:44:12.299745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
title_nmplace_tyrest_timemedia_tyrstde_guid_cnlast_updt_de
title_nm1.0000.4660.0000.9690.0000.964
place_ty0.4661.0000.0000.2110.0000.304
rest_time0.0000.0001.0000.1720.3130.076
media_ty0.9690.2110.1721.0000.2020.995
rstde_guid_cn0.0000.0000.3130.2021.0000.040
last_updt_de0.9640.3040.0760.9950.0401.000
2023-12-10T18:44:12.512501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
seq_nolc_lalc_lotel_nomedia_tytitle_nmplace_tyrest_timerstde_guid_cnlast_updt_de
seq_no1.000-0.3210.2550.2130.0000.9640.0000.0000.0000.000
lc_la-0.3211.000-0.089-0.2590.4290.2040.0000.0000.3520.594
lc_lo0.255-0.0891.0000.0910.4690.1860.0000.1470.1470.601
tel_no0.213-0.2590.0911.0000.0950.1330.2150.0000.1640.196
media_ty0.0000.4290.4690.0951.0000.9690.2110.1720.2020.995
title_nm0.9640.2040.1860.1330.9691.0000.4660.0000.0000.964
place_ty0.0000.0000.0000.2150.2110.4661.0000.0000.0000.304
rest_time0.0000.0000.1470.0000.1720.0000.0001.0000.3130.076
rstde_guid_cn0.0000.3520.1470.1640.2020.0000.0000.3131.0000.040
last_updt_de0.0000.5940.6010.1960.9950.9640.3040.0760.0401.000

Missing values

2023-12-10T18:44:00.688219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:44:01.071913image/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

seq_nomedia_tytitle_nmplace_nmplace_tyrelate_place_dcoper_timerest_timerstde_guid_cnaddrlc_lalc_lotel_nolast_updt_de
01drama(아는 건 별로 없지만) 가족입니다커피파머cafe6회에서 김은희(한예리)와 안효석(이종원)이 윤태형(김태호)의 은신처에서 서울로 돌아갈 때 이 카페에 들린다.매일 09시 - 21시정보없음연중무휴경기도 고양시 일산서구 대화로 6137.667523126.72817311899890320221125
115032dramaYou Raise Me Up (유 레이즈 미 업)해밀톤 호텔별관stay7회에서 도지혁(박기웅)이 이 술집에서 술을 마신다.가게별 상이정보없음연중무휴서울특별시 용산구 이태원로27가길 2637.535099126.9937723786600020221125
23drama(아는 건 별로 없지만) 가족입니다카페 그루비cafe안효석(이종원)은 바리스타로, 김은주(추자현)는 단골손님이다. 1화에서 이진숙(원미경)이 자녀와 사위에게 폭탄을 떨어뜨리는 장면이 나온다.매일 12시 - 22시정보없음연중무휴경기도 수원시 영통구 센트럴파크로127번길 14837.293983127.0553831214128820221125
34drama(아는 건 별로 없지만) 가족입니다미리내 성지playground시누이 도혜지(황우슬혜)는 남편이 가문의 회사를 상속받을 수 있도록 그녀가 길을 잃지 않기를 바라는 한편, 세리의 비서 홍씨(고규필)과 동시에 그녀가 가능한 한 빨리 발견되기를 기도한다.매일 09시 - 17시정보없음연중무휴경기도 안성시 양성면 미리내성지로 42037.146102127.2586531674125620221125
45drama(아는 건 별로 없지만) 가족입니다초은당playground김은희(한예리)와 동료 서경옥(가득희)은 1회에서 작가 의뢰인을 만나기 위해 이 한옥을 방문한다. 추후 은희는 여기로 돌아와 작가의 명상 세션에 참여합니다. 은희는 눈을 감고 자신의 인생에서 가장 긴 날인 2016년 3월 10일을 회상한다. 세션이 끝난 후 동생 김지우(신재하)와 소원해진 절친 박찬을 보고 놀란다.매일 11시 - 20시정보없음연중무휴경기도 양평군 서종면 북한강로814번길 46-637.611484127.35397704118077020221125
56drama(아는 건 별로 없지만) 가족입니다임진각평화누리playground10회 P&F에서 계약 체결 후 박찬혁(김석)은 김은희(한예리)에게 그가 가고 싶은 곳이 있다고 말한다. 은희는 찬혁에게 함께 가자고 말한다.매일 00시 - 24시정보없음연중무휴경기도 파주시 문산읍 마정리 135537.892963126.744351670385620221125
67drama(아는 건 별로 없지만) 가족입니다지혜의 숲playground15회에서 김은희(한예리)가 이 도서관에서 독립출판사 되기 세미나에 참석하는 모습과 건주 (신동욱)이 화자로 밝혀졌다. 세미나가 끝난 후 두 사람은 대화를 나누는데, 건주는 자신이 그녀의 계획을 따랐다고 말하며 그녀는 이를 반박한다. 그런 다음 그는 그녀가 직장을 그만두기 전에 미국에서 교육 프로그램을 신청해야 한다고 제안합니다. 그들은 밖으로 나갔고 건주는 은희가 해명하지 않으면 기분이 나쁠까 걱정하며 하라와 함께 그 주를 언급한다.매일 10시 - 20시정보없음연중무휴경기도 파주시 회동길 14537.708249126.6866745071335014420221125
715033dramaYou Raise Me Up (유 레이즈 미 업)북촌로5가길playground8화에서 두라와 데이트를 하며 이 거리를 걷는다.매일 00시 - 24시정보없음연중무휴서울특별시 종로구 북촌로5가길 12-737.580327126.9823722148111420221125
89drama(아는 건 별로 없지만) 가족입니다퀸즈파크 청담점restaurant김은희(한예리), 그녀의 동료 친구 서경옥(가득희), 그리고 그녀의 새로운 지인 전하라(배윤경)는 8회에서 쇼핑을 마치고 이 식당에서 저녁을 먹기로 결정했다.월-수 11시 - 21시, 목-금 11시 - 22시, 토 10시 - 22시, 일 10시 - 21시정보없음연중무휴서울특별시 강남구 압구정로60길 2237.52592127.041592542407320221125
910drama(아는 건 별로 없지만) 가족입니다혜심정restaurant13회에서 쉬는 날 박찬혁(김지석 분)을 자발적으로 초대해 이 식당에 함께 간다.매일 10시 - 22시정보없음연중무휴서울특별시 강북구 삼양로181길 17837.67139127.006982993155020221125
seq_nomedia_tytitle_nmplace_nmplace_tyrelate_place_dcoper_timerest_timerstde_guid_cnaddrlc_lalc_lotel_nolast_updt_de
9091show1박2일 시즌1마라도해녀촌짜장restaurant제주도를 가다 편을 촬영한 짜장면 맛집매일 09시 - 16시정보없음연중무휴제주특별자치도 서귀포시 대정읍 가파리 58833.119912126.26707564794070120221118
9192show1박2일 시즌1토끼와거북이restaurant가파도여행 2편을 촬영한 한식당매일 08시 - 22시정보없음연중무휴제주특별자치도 제주시 서해안로 498-633.518829126.49218364713444420221118
9293show1박2일 시즌1감초식당restaurant5대섬 특집편에서 방문한 순대 맛집매일 11시 30분 - 21시 30분정보없음1, 3번째 일요일제주특별자치도 제주시 이도1동 동광로1길 3233.503296126.5277764753746220221118
9394show1박2일 시즌1협재해수욕장playground이승기가 오토바이를 타고 방문한 협재해수욕장매일 00시 - 24시정보없음연중무휴제주특별자치도 제주시 한림읍 한림로 329-1033.394065126.23952764728398120221118
9495show1박2일 시즌1공산성playground박찬호의 야간 훈련 장소였던 공산성매일 09시 - 18시정보없음명절(당일)충청남도 공주시 웅진로 28036.465013127.1236141856770020221118
9596show1박2일 시즌4미인폭포playground딘딘, 라비, 연정훈이 추가촬영미션을 하러 간 곳매일 00시 - 24시정보없음연중무휴강원도 삼척시 도계읍 심포리 미인폭포37.182597129.04923233573409620221118
9697show1박2일 시즌4곰배령 (점봉산)playground수제 지팡이를 대여해 주는 곳매일 입산 09시 - 11시, 정상에서 14시까지 하산정보없음연중무휴강원도 인제군 기린면 진동리38.029391128.43258633463816620221118
9798show1박2일 시즌4오개장계곡playground김종민, 유세윤이 입수 벌칙 했던 장소매일 00시 - 24시정보없음연중무휴강원도 인제군 남면 어론리37.951966128.06269933461630120221118
9899show1박2일 시즌4재인폭포playground1박2일 시즌4 러블리즈 미주가 출연했던 점심 복불복 장소하절기 매일 10시 - 17시 30분, 동절기 매일 10시 - 16시정보없음연중무휴경기도 연천군 연천읍 부곡리 19338.076823127.1431831839227720221118
99100show1박2일 시즌4고산정playground1박2일 시즌 4 8회차 촬영지매일 00시 - 24시정보없음연중무휴경상북도 안동시 도산면 가송길 177-4236.767715128.89212154856301320221118