Overview

Dataset statistics

Number of variables24
Number of observations1262
Missing cells8956
Missing cells (%)29.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory242.9 KiB
Average record size in memory197.1 B

Variable types

Numeric5
Categorical6
Text13

Dataset

Description경기도 고양시 전자관광지도의 스마트 관광 전자지도 목록 데이터로 카테고리명, 장소명, 설명, 필드제목, 필드내용, 위도, 경도, 보여지는 레벨, 사진장수, 해시태그 등의 항목을 제공합니다.
Author경기도 고양시
URLhttps://www.data.go.kr/data/15126284/fileData.do

Alerts

필드제목_영어(en) has a high cardinality: 51 distinct valuesHigh cardinality
필드제목_중국어(cn) has a high cardinality: 51 distinct valuesHigh cardinality
카테고리명_영어(en) is highly imbalanced (50.9%)Imbalance
카테고리명_중국어(cn) is highly imbalanced (53.8%)Imbalance
필드제목_영어(en) is highly imbalanced (61.6%)Imbalance
필드제목_중국어(cn) is highly imbalanced (61.6%)Imbalance
해시태그 is highly imbalanced (73.0%)Imbalance
장소명_영어(en) has 773 (61.3%) missing valuesMissing
장소명_중국어(cn) has 775 (61.4%) missing valuesMissing
주소_영어(en) has 780 (61.8%) missing valuesMissing
주소_중국어(cn) has 783 (62.0%) missing valuesMissing
설명_한국어(ko) has 984 (78.0%) missing valuesMissing
설명_영어(en) has 1065 (84.4%) missing valuesMissing
설명_중국어(cn) has 1065 (84.4%) missing valuesMissing
필드제목_한국어(ko) has 526 (41.7%) missing valuesMissing
필드내용_한국어(ko) has 526 (41.7%) missing valuesMissing
필드내용_영어(en) has 834 (66.1%) missing valuesMissing
필드내용_중국어(cn) has 836 (66.2%) missing valuesMissing
번호(pid) has unique valuesUnique
사진장수(최대5장) has 912 (72.3%) zerosZeros

Reproduction

Analysis started2024-03-23 06:21:10.270812
Analysis finished2024-03-23 06:21:18.197884
Duration7.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호(pid)
Real number (ℝ)

UNIQUE 

Distinct1262
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1067.9247
Minimum1
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-03-23T06:21:18.568633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile65.05
Q1326.25
median1192.5
Q31692.75
95-th percentile1944.95
Maximum2017
Range2016
Interquartile range (IQR)1366.5

Descriptive statistics

Standard deviation678.16378
Coefficient of variation (CV)0.63502957
Kurtosis-1.5005399
Mean1067.9247
Median Absolute Deviation (MAD)637
Skewness-0.24306223
Sum1347721
Variance459906.11
MonotonicityStrictly increasing
2024-03-23T06:21:19.133578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1586 1
 
0.1%
1593 1
 
0.1%
1592 1
 
0.1%
1591 1
 
0.1%
1590 1
 
0.1%
1589 1
 
0.1%
1588 1
 
0.1%
1587 1
 
0.1%
1585 1
 
0.1%
Other values (1252) 1252
99.2%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
2017 1
0.1%
2016 1
0.1%
2015 1
0.1%
2014 1
0.1%
2013 1
0.1%
2012 1
0.1%
2011 1
0.1%
2010 1
0.1%
2009 1
0.1%
2008 1
0.1%

카테고리명_한국어(ko)
Categorical

Distinct40
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
바탕
424 
모범음식점
145 
기타
129 
관광협의회 추천맛집
125 
향토문화재
46 
Other values (35)
393 

Length

Max length10
Median length7
Mean length3.9152139
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st row추천관광
2nd row추천관광
3rd row추천관광
4th row고양누리길
5th row고양누리길

Common Values

ValueCountFrequency (%)
바탕 424
33.6%
모범음식점 145
 
11.5%
기타 129
 
10.2%
관광협의회 추천맛집 125
 
9.9%
향토문화재 46
 
3.6%
행정복지센터 39
 
3.1%
체육시설 38
 
3.0%
도서관 36
 
2.9%
체험 35
 
2.8%
도지정문화재 28
 
2.2%
Other values (30) 217
17.2%

Length

2024-03-23T06:21:19.689295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
바탕 424
30.6%
모범음식점 145
 
10.5%
기타 129
 
9.3%
관광협의회 125
 
9.0%
추천맛집 125
 
9.0%
향토문화재 46
 
3.3%
행정복지센터 39
 
2.8%
체육시설 38
 
2.7%
도서관 36
 
2.6%
체험 35
 
2.5%
Other values (31) 245
17.7%

카테고리명_영어(en)
Categorical

IMBALANCE 

Distinct32
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
772 
Restaurants
145 
Local Cultural Heritage
 
46
Administration & Welfare Centers
 
39
Sports Facilities
 
38
Other values (27)
222 

Length

Max length36
Median length4
Mean length9.0895404
Min length4

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st rowRecommended Tourist Spots
2nd rowRecommended Tourist Spots
3rd rowRecommended Tourist Spots
4th rowGoyang Course
5th rowGoyang Course

Common Values

ValueCountFrequency (%)
<NA> 772
61.2%
Restaurants 145
 
11.5%
Local Cultural Heritage 46
 
3.6%
Administration & Welfare Centers 39
 
3.1%
Sports Facilities 38
 
3.0%
Libraries 36
 
2.9%
Provincial Cultural Heritage 28
 
2.2%
Recommended Tourist Spots 17
 
1.3%
Goyang Course 14
 
1.1%
Youth Facilities 13
 
1.0%
Other values (22) 114
 
9.0%

Length

2024-03-23T06:21:20.211275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 772
43.8%
restaurants 145
 
8.2%
cultural 88
 
5.0%
heritage 88
 
5.0%
62
 
3.5%
facilities 51
 
2.9%
centers 48
 
2.7%
local 46
 
2.6%
administration 39
 
2.2%
welfare 39
 
2.2%
Other values (39) 383
21.7%

카테고리명_중국어(cn)
Categorical

IMBALANCE 

Distinct30
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
810 
模范餐
145 
土文化
 
46
行政福利中心
 
39
育施
 
38
Other values (25)
184 

Length

Max length7
Median length4
Mean length3.725832
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st row推旅游
2nd row推旅游
3rd row推旅游
4th row高世界路
5th row高世界路

Common Values

ValueCountFrequency (%)
<NA> 810
64.2%
模范餐 145
 
11.5%
土文化 46
 
3.6%
行政福利中心 39
 
3.1%
育施 38
 
3.0%
道指定文化 28
 
2.2%
推旅游 17
 
1.3%
高世界路 14
 
1.1%
少年施 13
 
1.0%
博物 11
 
0.9%
Other values (20) 101
 
8.0%

Length

2024-03-23T06:21:20.774769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 810
64.2%
模范餐 145
 
11.5%
土文化 46
 
3.6%
行政福利中心 39
 
3.1%
育施 38
 
3.0%
道指定文化 28
 
2.2%
推旅游 17
 
1.3%
高世界路 14
 
1.1%
少年施 13
 
1.0%
博物 11
 
0.9%
Other values (20) 101
 
8.0%

장소명_한국어(ko)
Text

Distinct1229
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
2024-03-23T06:21:21.541889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length6.0372425
Min length1

Characters and Unicode

Total characters7619
Distinct characters568
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

Unique1196 ?
Unique (%)94.8%

Sample

1st row킨텍스
2nd row세계문화유산 서오릉
3rd row세계문화유산 서삼릉/서삼릉태실
4th row고양북한산누리길
5th row고양한북누리길
ValueCountFrequency (%)
작은도서관 8
 
0.6%
우편취급국 4
 
0.3%
황치제국 2
 
0.1%
남궁 2
 
0.1%
빅토리아 2
 
0.1%
본일산오리구이 2
 
0.1%
본가갈비 2
 
0.1%
청목 2
 
0.1%
세계문화유산 2
 
0.1%
삼보가든 2
 
0.1%
Other values (1278) 1320
97.9%
2024-03-23T06:21:22.912913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 265
 
3.5%
유 192
 
2.5%
치 185
 
2.4%
교 182
 
2.4%
학 172
 
2.3%
산 163
 
2.1%
초 152
 
2.0%
고 137
 
1.8%
동 132
 
1.7%
등 122
 
1.6%
Other values (558) 5917
77.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7359
96.6%
Decimal Number 90
 
1.2%
Space Separator 86
 
1.1%
Uppercase Letter 37
 
0.5%
Lowercase Letter 19
 
0.2%
Other Punctuation 14
 
0.2%
Open Punctuation 7
 
0.1%
Close Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 265
 
3.6%
유 192
 
2.6%
치 185
 
2.5%
교 182
 
2.5%
학 172
 
2.3%
산 163
 
2.2%
초 152
 
2.1%
고 137
 
1.9%
동 132
 
1.8%
등 122
 
1.7%
Other values (512) 5657
76.9%
Uppercase Letter
ValueCountFrequency (%)
C 12
32.4%
I 3
 
8.1%
K 3
 
8.1%
S 3
 
8.1%
X 2
 
5.4%
M 2
 
5.4%
B 2
 
5.4%
E 2
 
5.4%
T 2
 
5.4%
N 1
 
2.7%
Other values (5) 5
13.5%
Lowercase Letter
ValueCountFrequency (%)
t 2
 
10.5%
e 2
 
10.5%
u 2
 
10.5%
o 2
 
10.5%
c 1
 
5.3%
s 1
 
5.3%
m 1
 
5.3%
y 1
 
5.3%
a 1
 
5.3%
k 1
 
5.3%
Other values (5) 5
26.3%
Decimal Number
ValueCountFrequency (%)
1 42
46.7%
2 17
18.9%
9 14
 
15.6%
3 6
 
6.7%
8 3
 
3.3%
5 3
 
3.3%
0 2
 
2.2%
4 2
 
2.2%
6 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 8
57.1%
& 3
 
21.4%
@ 2
 
14.3%
/ 1
 
7.1%
Space Separator
ValueCountFrequency (%)
86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7359
96.6%
Common 204
 
2.7%
Latin 56
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 265
 
3.6%
유 192
 
2.6%
치 185
 
2.5%
교 182
 
2.5%
학 172
 
2.3%
산 163
 
2.2%
초 152
 
2.1%
고 137
 
1.9%
동 132
 
1.8%
등 122
 
1.7%
Other values (512) 5657
76.9%
Latin
ValueCountFrequency (%)
C 12
21.4%
I 3
 
5.4%
K 3
 
5.4%
S 3
 
5.4%
t 2
 
3.6%
e 2
 
3.6%
u 2
 
3.6%
o 2
 
3.6%
X 2
 
3.6%
M 2
 
3.6%
Other values (20) 23
41.1%
Common
ValueCountFrequency (%)
86
42.2%
1 42
20.6%
2 17
 
8.3%
9 14
 
6.9%
. 8
 
3.9%
( 7
 
3.4%
) 7
 
3.4%
3 6
 
2.9%
& 3
 
1.5%
8 3
 
1.5%
Other values (6) 11
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7359
96.6%
ASCII 260
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 265
 
3.6%
유 192
 
2.6%
치 185
 
2.5%
교 182
 
2.5%
학 172
 
2.3%
산 163
 
2.2%
초 152
 
2.1%
고 137
 
1.9%
동 132
 
1.8%
등 122
 
1.7%
Other values (512) 5657
76.9%
ASCII
ValueCountFrequency (%)
86
33.1%
1 42
16.2%
2 17
 
6.5%
9 14
 
5.4%
C 12
 
4.6%
. 8
 
3.1%
( 7
 
2.7%
) 7
 
2.7%
3 6
 
2.3%
I 3
 
1.2%
Other values (36) 58
22.3%

장소명_영어(en)
Text

MISSING 

Distinct477
Distinct (%)97.5%
Missing773
Missing (%)61.3%
Memory size10.0 KiB
2024-03-23T06:21:23.785638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length135
Median length46
Mean length25.204499
Min length2

Characters and Unicode

Total characters12325
Distinct characters67
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique465 ?
Unique (%)95.1%

Sample

1st rowKINTEX
2nd rowSeooreung Royal Tombs (World Heritage Site)
3rd rowSeosamneung Royal Tombs & Placenta Chamber
4th rowGoyang Bukhansan Trail
5th rowGoyang Hanbuk Trail
ValueCountFrequency (%)
of 65
 
3.8%
center 64
 
3.7%
49
 
2.9%
goyang 43
 
2.5%
tomb 41
 
2.4%
administration 39
 
2.3%
welfare 39
 
2.3%
library 33
 
1.9%
and 25
 
1.5%
ilsan 24
 
1.4%
Other values (725) 1290
75.4%
2024-03-23T06:21:25.363062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1241
 
10.1%
n 1114
 
9.0%
a 1043
 
8.5%
e 938
 
7.6%
o 912
 
7.4%
i 657
 
5.3%
g 556
 
4.5%
r 529
 
4.3%
t 459
 
3.7%
l 456
 
3.7%
Other values (57) 4420
35.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9242
75.0%
Uppercase Letter 1579
 
12.8%
Space Separator 1241
 
10.1%
Dash Punctuation 74
 
0.6%
Other Punctuation 53
 
0.4%
Open Punctuation 49
 
0.4%
Close Punctuation 49
 
0.4%
Decimal Number 32
 
0.3%
Final Punctuation 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1114
12.1%
a 1043
11.3%
e 938
10.1%
o 912
9.9%
i 657
 
7.1%
g 556
 
6.0%
r 529
 
5.7%
t 459
 
5.0%
l 456
 
4.9%
u 424
 
4.6%
Other values (16) 2154
23.3%
Uppercase Letter
ValueCountFrequency (%)
S 194
12.3%
C 145
 
9.2%
T 129
 
8.2%
G 128
 
8.1%
H 114
 
7.2%
M 109
 
6.9%
A 76
 
4.8%
B 75
 
4.7%
P 71
 
4.5%
W 66
 
4.2%
Other values (16) 472
29.9%
Decimal Number
ValueCountFrequency (%)
1 13
40.6%
2 11
34.4%
5 3
 
9.4%
8 2
 
6.2%
3 2
 
6.2%
0 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
& 48
90.6%
, 3
 
5.7%
/ 1
 
1.9%
@ 1
 
1.9%
Space Separator
ValueCountFrequency (%)
1241
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10821
87.8%
Common 1504
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1114
 
10.3%
a 1043
 
9.6%
e 938
 
8.7%
o 912
 
8.4%
i 657
 
6.1%
g 556
 
5.1%
r 529
 
4.9%
t 459
 
4.2%
l 456
 
4.2%
u 424
 
3.9%
Other values (42) 3733
34.5%
Common
ValueCountFrequency (%)
1241
82.5%
- 74
 
4.9%
( 49
 
3.3%
) 49
 
3.3%
& 48
 
3.2%
1 13
 
0.9%
2 11
 
0.7%
’ 6
 
0.4%
, 3
 
0.2%
5 3
 
0.2%
Other values (5) 7
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12319
> 99.9%
Punctuation 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1241
 
10.1%
n 1114
 
9.0%
a 1043
 
8.5%
e 938
 
7.6%
o 912
 
7.4%
i 657
 
5.3%
g 556
 
4.5%
r 529
 
4.3%
t 459
 
3.7%
l 456
 
3.7%
Other values (56) 4414
35.8%
Punctuation
ValueCountFrequency (%)
’ 6
100.0%

장소명_중국어(cn)
Text

MISSING 

Distinct473
Distinct (%)97.1%
Missing775
Missing (%)61.4%
Memory size10.0 KiB
2024-03-23T06:21:26.346594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length5.3983573
Min length1

Characters and Unicode

Total characters2629
Distinct characters512
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique460 ?
Unique (%)94.5%

Sample

1st row展中心（KINTEX）
2nd row世界文化西五陵
3rd row世界文化西三陵/西三陵胎室
4th row高北山世界路
5th row高北世界路
ValueCountFrequency (%)
寺 3
 
0.6%
onemount 2
 
0.4%
pan 2
 
0.4%
平醒酒 2
 
0.4%
展中心（kintex） 2
 
0.4%
中南美文化院博物 2
 
0.4%
政府部 2
 
0.4%
幸州山城 2
 
0.4%
高童博物 2
 
0.4%
ok刀切面 2
 
0.4%
Other values (472) 476
95.8%
2024-03-23T06:21:28.027698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
山 85
 
3.2%
中 67
 
2.5%
洞 66
 
2.5%
心 57
 
2.2%
高 57
 
2.2%
行 42
 
1.6%
福 42
 
1.6%
利 42
 
1.6%
墓 41
 
1.6%
政 41
 
1.6%
Other values (502) 2089
79.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2261
86.0%
Lowercase Letter 216
 
8.2%
Uppercase Letter 104
 
4.0%
Decimal Number 12
 
0.5%
Space Separator 11
 
0.4%
Close Punctuation 10
 
0.4%
Open Punctuation 10
 
0.4%
Other Punctuation 3
 
0.1%
Final Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
山 85
 
3.8%
中 67
 
3.0%
洞 66
 
2.9%
心 57
 
2.5%
高 57
 
2.5%
行 42
 
1.9%
福 42
 
1.9%
利 42
 
1.9%
墓 41
 
1.8%
政 41
 
1.8%
Other values (441) 1721
76.1%
Uppercase Letter
ValueCountFrequency (%)
O 12
 
11.5%
A 9
 
8.7%
B 8
 
7.7%
L 8
 
7.7%
C 7
 
6.7%
S 6
 
5.8%
T 6
 
5.8%
N 6
 
5.8%
I 5
 
4.8%
H 4
 
3.8%
Other values (14) 33
31.7%
Lowercase Letter
ValueCountFrequency (%)
a 32
14.8%
e 23
10.6%
n 21
9.7%
o 21
9.7%
r 17
7.9%
t 13
 
6.0%
i 12
 
5.6%
m 12
 
5.6%
u 12
 
5.6%
l 12
 
5.6%
Other values (13) 41
19.0%
Decimal Number
ValueCountFrequency (%)
5 3
25.0%
2 3
25.0%
4 2
16.7%
1 2
16.7%
0 1
 
8.3%
8 1
 
8.3%
Close Punctuation
ValueCountFrequency (%)
） 9
90.0%
》 1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
（ 9
90.0%
《 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
66.7%
@ 1
33.3%
Space Separator
ValueCountFrequency (%)
11
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 2261
86.0%
Latin 320
 
12.2%
Common 48
 
1.8%

Most frequent character per script

Han
ValueCountFrequency (%)
山 85
 
3.8%
中 67
 
3.0%
洞 66
 
2.9%
心 57
 
2.5%
高 57
 
2.5%
行 42
 
1.9%
福 42
 
1.9%
利 42
 
1.9%
墓 41
 
1.8%
政 41
 
1.8%
Other values (441) 1721
76.1%
Latin
ValueCountFrequency (%)
a 32
 
10.0%
e 23
 
7.2%
n 21
 
6.6%
o 21
 
6.6%
r 17
 
5.3%
t 13
 
4.1%
O 12
 
3.8%
i 12
 
3.8%
m 12
 
3.8%
u 12
 
3.8%
Other values (37) 145
45.3%
Common
ValueCountFrequency (%)
11
22.9%
） 9
18.8%
（ 9
18.8%
5 3
 
6.2%
2 3
 
6.2%
4 2
 
4.2%
’ 2
 
4.2%
1 2
 
4.2%
/ 2
 
4.2%
0 1
 
2.1%
Other values (4) 4
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
CJK 2260
86.0%
ASCII 346
 
13.2%
None 20
 
0.8%
Punctuation 2
 
0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

CJK
ValueCountFrequency (%)
山 85
 
3.8%
中 67
 
3.0%
洞 66
 
2.9%
心 57
 
2.5%
高 57
 
2.5%
行 42
 
1.9%
福 42
 
1.9%
利 42
 
1.9%
墓 41
 
1.8%
政 41
 
1.8%
Other values (440) 1720
76.1%
ASCII
ValueCountFrequency (%)
a 32
 
9.2%
e 23
 
6.6%
n 21
 
6.1%
o 21
 
6.1%
r 17
 
4.9%
t 13
 
3.8%
O 12
 
3.5%
i 12
 
3.5%
m 12
 
3.5%
u 12
 
3.5%
Other values (46) 171
49.4%
None
ValueCountFrequency (%)
） 9
45.0%
（ 9
45.0%
《 1
 
5.0%
》 1
 
5.0%
Punctuation
ValueCountFrequency (%)
’ 2
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
履 1
100.0%

주소_한국어(ko)
Text

Distinct1104
Distinct (%)88.1%
Missing9
Missing (%)0.7%
Memory size10.0 KiB
2024-03-23T06:21:28.998478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length35
Mean length20.007981
Min length12

Characters and Unicode

Total characters25070
Distinct characters218
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

Unique995 ?
Unique (%)79.4%

Sample

1st row경기도 고양시 일산서구 킨텍스로 217-60(대화동)
2nd row경기도 고양시 덕양구 서오릉로 334-92(용두동)
3rd row경기도 고양시 덕양구 서삼릉길 233-126(원당동)
4th row경기도 고양시 덕양구 효자동
5th row경기도 고양시 덕양구 오금동
ValueCountFrequency (%)
고양시 1220
21.5%
덕양구 592
 
10.4%
경기도 481
 
8.5%
일산동구 358
 
6.3%
일산서구 297
 
5.2%
중앙로 64
 
1.1%
일산로 33
 
0.6%
주교동 24
 
0.4%
성사동 23
 
0.4%
호수로 23
 
0.4%
Other values (1226) 2563
45.1%
2024-03-23T06:21:31.012603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4445
17.7%
양 1879
 
7.5%
고 1294
 
5.2%
구 1253
 
5.0%
시 1245
 
5.0%
로 924
 
3.7%
1 911
 
3.6%
산 873
 
3.5%
동 797
 
3.2%
일 788
 
3.1%
Other values (208) 10661
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15375
61.3%
Decimal Number 4509
 
18.0%
Space Separator 4445
 
17.7%
Dash Punctuation 319
 
1.3%
Close Punctuation 185
 
0.7%
Open Punctuation 184
 
0.7%
Other Punctuation 46
 
0.2%
Uppercase Letter 6
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 1879
 
12.2%
고 1294
 
8.4%
구 1253
 
8.1%
시 1245
 
8.1%
로 924
 
6.0%
산 873
 
5.7%
동 797
 
5.2%
일 788
 
5.1%
덕 618
 
4.0%
도 514
 
3.3%
Other values (188) 5190
33.8%
Decimal Number
ValueCountFrequency (%)
1 911
20.2%
2 607
13.5%
3 529
11.7%
5 414
9.2%
6 403
8.9%
4 375
8.3%
7 350
 
7.8%
8 341
 
7.6%
0 314
 
7.0%
9 265
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
A 2
33.3%
C 2
33.3%
E 1
16.7%
F 1
16.7%
Space Separator
ValueCountFrequency (%)
4445
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 319
100.0%
Close Punctuation
ValueCountFrequency (%)
) 185
100.0%
Open Punctuation
ValueCountFrequency (%)
( 184
100.0%
Other Punctuation
ValueCountFrequency (%)
, 46
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15375
61.3%
Common 9689
38.6%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 1879
 
12.2%
고 1294
 
8.4%
구 1253
 
8.1%
시 1245
 
8.1%
로 924
 
6.0%
산 873
 
5.7%
동 797
 
5.2%
일 788
 
5.1%
덕 618
 
4.0%
도 514
 
3.3%
Other values (188) 5190
33.8%
Common
ValueCountFrequency (%)
4445
45.9%
1 911
 
9.4%
2 607
 
6.3%
3 529
 
5.5%
5 414
 
4.3%
6 403
 
4.2%
4 375
 
3.9%
7 350
 
3.6%
8 341
 
3.5%
- 319
 
3.3%
Other values (6) 995
 
10.3%
Latin
ValueCountFrequency (%)
A 2
33.3%
C 2
33.3%
E 1
16.7%
F 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15375
61.3%
ASCII 9695
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4445
45.8%
1 911
 
9.4%
2 607
 
6.3%
3 529
 
5.5%
5 414
 
4.3%
6 403
 
4.2%
4 375
 
3.9%
7 350
 
3.6%
8 341
 
3.5%
- 319
 
3.3%
Other values (10) 1001
 
10.3%
Hangul
ValueCountFrequency (%)
양 1879
 
12.2%
고 1294
 
8.4%
구 1253
 
8.1%
시 1245
 
8.1%
로 924
 
6.0%
산 873
 
5.7%
동 797
 
5.2%
일 788
 
5.1%
덕 618
 
4.0%
도 514
 
3.3%
Other values (188) 5190
33.8%

주소_영어(en)
Text

MISSING 

Distinct412
Distinct (%)85.5%
Missing780
Missing (%)61.8%
Memory size10.0 KiB
2024-03-23T06:21:32.165108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length65
Mean length55.923237
Min length35

Characters and Unicode

Total characters26955
Distinct characters54
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique373 ?
Unique (%)77.4%

Sample

1st row217-60, Kintex-ro, Ilsanseo-gu, Goyang-si, Gyeonggi-do
2nd row334-92, Seooreung-ro, Deogyang-gu, Goyang-si, Gyeonggi-do
3rd row233-126, Seosamneung-gil, Deogyang-gu, Goyang-si, Gyeonggi-do
4th rowHyoja-dong, Deogyang-gu, Goyang-si,Gyeonggi-do
5th rowOgeum-dong, Deogyang-gu, Goyang-si,Gyeonggi-do
ValueCountFrequency (%)
goyang-si 468
18.5%
gyeonggi-do 468
18.5%
deogyang-gu 229
 
9.1%
ilsandong-gu 147
 
5.8%
ilsanseo-gu 104
 
4.1%
jungang-ro 36
 
1.4%
hosu-ro 25
 
1.0%
ilsan-ro 20
 
0.8%
san 15
 
0.6%
daeseomun-gil 15
 
0.6%
Other values (568) 998
39.5%
2024-03-23T06:21:33.688954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
g 3137
11.6%
o 2760
 
10.2%
n 2315
 
8.6%
- 2189
 
8.1%
2048
 
7.6%
, 1885
 
7.0%
a 1380
 
5.1%
y 1272
 
4.7%
e 1228
 
4.6%
i 1211
 
4.5%
Other values (44) 7530
27.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17175
63.7%
Dash Punctuation 2189
 
8.1%
Space Separator 2048
 
7.6%
Uppercase Letter 1937
 
7.2%
Other Punctuation 1885
 
7.0%
Decimal Number 1721
 
6.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
g 3137
18.3%
o 2760
16.1%
n 2315
13.5%
a 1380
8.0%
y 1272
7.4%
e 1228
 
7.1%
i 1211
 
7.1%
s 1031
 
6.0%
u 749
 
4.4%
d 747
 
4.3%
Other values (12) 1345
7.8%
Uppercase Letter
ValueCountFrequency (%)
G 1016
52.5%
D 283
 
14.6%
I 280
 
14.5%
H 109
 
5.6%
S 68
 
3.5%
J 67
 
3.5%
M 18
 
0.9%
T 17
 
0.9%
W 17
 
0.9%
B 14
 
0.7%
Other values (9) 48
 
2.5%
Decimal Number
ValueCountFrequency (%)
1 344
20.0%
2 228
13.2%
3 191
11.1%
5 168
9.8%
6 165
9.6%
4 147
8.5%
8 138
8.0%
7 131
 
7.6%
0 111
 
6.4%
9 98
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 2189
100.0%
Space Separator
ValueCountFrequency (%)
2048
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1885
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 19112
70.9%
Common 7843
29.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
g 3137
16.4%
o 2760
14.4%
n 2315
12.1%
a 1380
7.2%
y 1272
6.7%
e 1228
 
6.4%
i 1211
 
6.3%
s 1031
 
5.4%
G 1016
 
5.3%
u 749
 
3.9%
Other values (31) 3013
15.8%
Common
ValueCountFrequency (%)
- 2189
27.9%
2048
26.1%
, 1885
24.0%
1 344
 
4.4%
2 228
 
2.9%
3 191
 
2.4%
5 168
 
2.1%
6 165
 
2.1%
4 147
 
1.9%
8 138
 
1.8%
Other values (3) 340
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26955
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
g 3137
11.6%
o 2760
 
10.2%
n 2315
 
8.6%
- 2189
 
8.1%
2048
 
7.6%
, 1885
 
7.0%
a 1380
 
5.1%
y 1272
 
4.7%
e 1228
 
4.6%
i 1211
 
4.5%
Other values (44) 7530
27.9%

주소_중국어(cn)
Text

MISSING 

Distinct404
Distinct (%)84.3%
Missing783
Missing (%)62.0%
Memory size10.0 KiB
2024-03-23T06:21:34.548872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length65
Mean length55.791232
Min length3

Characters and Unicode

Total characters26724
Distinct characters57
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

Unique361 ?
Unique (%)75.4%

Sample

1st row217-60, Kintex-ro, Ilsanseo-gu, Goyang-si, Gyeonggi-do
2nd row334-92, Seooreung-ro, Deogyang-gu, Goyang-si, Gyeonggi-do
3rd row233-126, Seosamneung-gil, Deogyang-gu, Goyang-si, Gyeonggi-do
4th rowHyoja-dong, Deogyang-gu, Goyang-si,Gyeonggi-do
5th rowOgeum-dong, Deogyang-gu, Goyang-si,Gyeonggi-do
ValueCountFrequency (%)
goyang-si 464
18.6%
gyeonggi-do 464
18.6%
deogyang-gu 227
 
9.1%
ilsandong-gu 145
 
5.8%
ilsanseo-gu 104
 
4.2%
jungang-ro 36
 
1.4%
hosu-ro 25
 
1.0%
ilsan-ro 19
 
0.8%
daeseomun-gil 17
 
0.7%
goyang-daero 13
 
0.5%
Other values (554) 984
39.4%
2024-03-23T06:21:35.879286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
g 3107
11.6%
o 2742
 
10.3%
n 2278
 
8.5%
- 2169
 
8.1%
2026
 
7.6%
, 1887
 
7.1%
a 1355
 
5.1%
y 1260
 
4.7%
e 1224
 
4.6%
i 1200
 
4.5%
Other values (47) 7476
28.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17011
63.7%
Dash Punctuation 2169
 
8.1%
Space Separator 2026
 
7.6%
Uppercase Letter 1912
 
7.2%
Other Punctuation 1887
 
7.1%
Decimal Number 1716
 
6.4%
Other Letter 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
g 3107
18.3%
o 2742
16.1%
n 2278
13.4%
a 1355
8.0%
y 1260
7.4%
e 1224
 
7.2%
i 1200
 
7.1%
s 1022
 
6.0%
u 745
 
4.4%
d 737
 
4.3%
Other values (12) 1341
7.9%
Uppercase Letter
ValueCountFrequency (%)
G 1006
52.6%
D 283
 
14.8%
I 276
 
14.4%
H 111
 
5.8%
J 66
 
3.5%
S 56
 
2.9%
M 18
 
0.9%
W 17
 
0.9%
T 17
 
0.9%
B 14
 
0.7%
Other values (9) 48
 
2.5%
Decimal Number
ValueCountFrequency (%)
1 345
20.1%
2 226
13.2%
3 184
10.7%
5 167
9.7%
6 162
9.4%
4 148
8.6%
8 141
8.2%
7 132
 
7.7%
0 108
 
6.3%
9 103
 
6.0%
Other Letter
ValueCountFrequency (%)
元 1
33.3%
堂 1
33.3%
市 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2169
100.0%
Space Separator
ValueCountFrequency (%)
2026
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1887
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18923
70.8%
Common 7798
29.2%
Han 3
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
g 3107
16.4%
o 2742
14.5%
n 2278
12.0%
a 1355
7.2%
y 1260
6.7%
e 1224
 
6.5%
i 1200
 
6.3%
s 1022
 
5.4%
G 1006
 
5.3%
u 745
 
3.9%
Other values (31) 2984
15.8%
Common
ValueCountFrequency (%)
- 2169
27.8%
2026
26.0%
, 1887
24.2%
1 345
 
4.4%
2 226
 
2.9%
3 184
 
2.4%
5 167
 
2.1%
6 162
 
2.1%
4 148
 
1.9%
8 141
 
1.8%
Other values (3) 343
 
4.4%
Han
ValueCountFrequency (%)
元 1
33.3%
堂 1
33.3%
市 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26721
> 99.9%
CJK 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
g 3107
11.6%
o 2742
 
10.3%
n 2278
 
8.5%
- 2169
 
8.1%
2026
 
7.6%
, 1887
 
7.1%
a 1355
 
5.1%
y 1260
 
4.7%
e 1224
 
4.6%
i 1200
 
4.5%
Other values (44) 7473
28.0%
CJK
ValueCountFrequency (%)
元 1
33.3%
堂 1
33.3%
市 1
33.3%

설명_한국어(ko)
Text

MISSING 

Distinct268
Distinct (%)96.4%
Missing984
Missing (%)78.0%
Memory size10.0 KiB
2024-03-23T06:21:36.986951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length349
Mean length252.3777
Min length25

Characters and Unicode

Total characters70161
Distinct characters1487
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique259 ?
Unique (%)93.2%

Sample

1st row대한민국 대표 전시장 킨텍스는 국내 최대 규모로 국내 12개 전시장 총면적의 41%를 차지하고 있습니다. 서울모토쇼 등 5대 메이저 전시회를 성공적으로 개최한 바 있으며 국내유일 대규모 국제 전시가 가능한 전시장으로 세계 수준의 전시컨벤션 문화공간입니다.
2nd row서오릉이란 조선왕조의 다섯 능 즉 경릉(敬陵,덕종과 소혜왕후의 능), 창릉(昌陵, 예종과 계비 안순왕후의 능), 익릉(翼陵, 숙종의 원비인 인경왕후의 능), 명릉(明陵, 숙종과 인현왕후, 인원왕후의 능), 홍릉(弘陵, 정성왕후의 능)이 이곳에 모여 있어서 일컫는 명칭이다. 서오릉 지역이 왕실묘역으로 선택된 이유는 세조 3년(1457)에 세자 장(덕종)이 사망하자, 풍수지리설에 의해 경릉을 쓰고부터이다. 서오릉에는 이 5개의 능 외에도 조선왕조 최초의 ‘원’으로 명종의 첫째 아들인 순회세자의 무덤인 순창원과 숙종의 추궁으로 많은 역사적 일화를 남긴 희빈 장씨의 대빈묘가 있다. 서오릉은 동구릉 다음으로 큰 면적의 조선왕조 왕실의 가족무덤이며 고양시청에서 서울시 은평구 갈현동으로 이어진 55번 지방도로변에 위치하고 있다.
3rd row서삼릉이란 고양시 원당동에 소재한 孝陵, 禧陵, 睿陵을 아울러 일컫는 말이다. 총 면적은 약 7만여 평이며 중종의 계비인 章敬王后 尹氏의 희릉자리로 택해지면서 처음 능자리로 사용되었다. 본래는 130여만여평에 이르는 광대한 면적을 차지하였으나 지금은 여러 곳으로 분할되어 약 7만여 평이 남았으며 이 중 절반가량이 비공개 지역으로 지정되어 있다. 이곳에는 3기의 능 이외에도 태실, 공주·옹주묘, 소경원, 효창원 등이 있다.
4th row고양시 최고봉! 북한산을 품고 걷는 역사의 길! 북한산둘레길 중 내시묘역길에서 충의길로 이어지는 코스이다. 국내 최대 내시묘가 위치한 내시묘역길은 오르막이 전혀 없고 호젓한 시골길을 거니는 듯 조용하고 맑은 공기를 마시며 산책할 수 있는 길이다. 효자길, 백운대, 인수봉 등 고양시 관할 명봉들이 한눈에 보이는 충의길까지 다양한 스토리텔링과 아름다운 풍경을 간직한 고양시의 아름다운 숲길이다.
5th row한북정맥의 기운을 느낄 수 있는 숲속 오솔길! 한북정맥의 산줄기로 북한산 효자계곡에서 발원하여 한강까지 흐르는 창릉천을 따라 고즈넉한 마을길이 열리고, 고양시 최초의 북한산 일대 유일한 온천이 손님들을 맞고 있다. 스님들이 넘나들었다는 중고개를 너머 하늘에서 선녀가 내려왔다는 옥녀봉에 숨 가쁘게 오르면 북한산의 장엄한 비경에 또 한번 놀란다. 걷는 내내 단풍이 아름다운 복자기나무와 참나무 숲길은 마음속 깊은 곳까지 힐링의 연속이다.
ValueCountFrequency (%)
있다 339
 
2.2%
수 144
 
0.9%
있는 110
 
0.7%
있으며 82
 
0.5%
이 77
 
0.5%
등 67
 
0.4%
것으로 55
 
0.4%
있어 51
 
0.3%
그 50
 
0.3%
조선 44
 
0.3%
Other values (8685) 14569
93.5%
2024-03-23T06:21:38.623025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15358
 
21.9%
이 1613
 
2.3%
다 1290
 
1.8%
의 1120
 
1.6%
. 1115
 
1.6%
에 1050
 
1.5%
는 1049
 
1.5%
, 948
 
1.4%
로 909
 
1.3%
고 817
 
1.2%
Other values (1477) 44892
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48637
69.3%
Space Separator 15358
 
21.9%
Decimal Number 2775
 
4.0%
Other Punctuation 2135
 
3.0%
Open Punctuation 357
 
0.5%
Close Punctuation 356
 
0.5%
Lowercase Letter 190
 
0.3%
Math Symbol 152
 
0.2%
Other Symbol 83
 
0.1%
Uppercase Letter 38
 
0.1%
Other values (3) 80
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1613
 
3.3%
다 1290
 
2.7%
의 1120
 
2.3%
에 1050
 
2.2%
는 1049
 
2.2%
로 909
 
1.9%
고 817
 
1.7%
을 796
 
1.6%
있 785
 
1.6%
하 746
 
1.5%
Other values (1397) 38462
79.1%
Lowercase Letter
ValueCountFrequency (%)
m 87
45.8%
c 26
 
13.7%
a 10
 
5.3%
n 10
 
5.3%
e 9
 
4.7%
t 9
 
4.7%
k 9
 
4.7%
i 6
 
3.2%
r 6
 
3.2%
o 5
 
2.6%
Other values (7) 13
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
M 8
21.1%
S 6
15.8%
B 4
10.5%
K 3
 
7.9%
V 3
 
7.9%
T 2
 
5.3%
G 2
 
5.3%
E 2
 
5.3%
I 2
 
5.3%
C 1
 
2.6%
Other values (5) 5
13.2%
Decimal Number
ValueCountFrequency (%)
1 687
24.8%
0 385
13.9%
2 275
9.9%
5 247
 
8.9%
3 232
 
8.4%
9 216
 
7.8%
4 194
 
7.0%
6 191
 
6.9%
8 186
 
6.7%
7 162
 
5.8%
Math Symbol
ValueCountFrequency (%)
< 46
30.3%
> 46
30.3%
~ 43
28.3%
～ 6
 
3.9%
∼ 4
 
2.6%
→ 3
 
2.0%
× 2
 
1.3%
+ 2
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 1115
52.2%
, 948
44.4%
· 39
 
1.8%
! 16
 
0.7%
% 7
 
0.3%
: 6
 
0.3%
/ 4
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 327
91.6%
「 15
 
4.2%
『 10
 
2.8%
《 2
 
0.6%
[ 2
 
0.6%
〔 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 326
91.6%
」 15
 
4.2%
』 10
 
2.8%
》 2
 
0.6%
] 2
 
0.6%
〕 1
 
0.3%
Other Symbol
ValueCountFrequency (%)
㎝ 69
83.1%
㎡ 9
 
10.8%
° 2
 
2.4%
㎞ 2
 
2.4%
┼ 1
 
1.2%
Final Punctuation
ValueCountFrequency (%)
’ 36
97.3%
” 1
 
2.7%
Initial Punctuation
ValueCountFrequency (%)
‘ 36
97.3%
“ 1
 
2.7%
Space Separator
ValueCountFrequency (%)
15358
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47171
67.2%
Common 21296
30.4%
Han 1466
 
2.1%
Latin 228
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1613
 
3.4%
다 1290
 
2.7%
의 1120
 
2.4%
에 1050
 
2.2%
는 1049
 
2.2%
로 909
 
1.9%
고 817
 
1.7%
을 796
 
1.7%
있 785
 
1.7%
하 746
 
1.6%
Other values (858) 36996
78.4%
Han
ValueCountFrequency (%)
氏 32
 
2.2%
夫 27
 
1.8%
人 23
 
1.6%
墓 20
 
1.4%
州 19
 
1.3%
大 18
 
1.2%
敬 18
 
1.2%
陵 17
 
1.2%
李 16
 
1.1%
府 15
 
1.0%
Other values (529) 1261
86.0%
Common
ValueCountFrequency (%)
15358
72.1%
. 1115
 
5.2%
, 948
 
4.5%
1 687
 
3.2%
0 385
 
1.8%
( 327
 
1.5%
) 326
 
1.5%
2 275
 
1.3%
5 247
 
1.2%
3 232
 
1.1%
Other values (38) 1396
 
6.6%
Latin
ValueCountFrequency (%)
m 87
38.2%
c 26
 
11.4%
a 10
 
4.4%
n 10
 
4.4%
e 9
 
3.9%
t 9
 
3.9%
k 9
 
3.9%
M 8
 
3.5%
i 6
 
2.6%
r 6
 
2.6%
Other values (22) 48
21.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47162
67.2%
ASCII 21257
30.3%
CJK 1414
 
2.0%
None 105
 
0.1%
CJK Compat 80
 
0.1%
Punctuation 74
 
0.1%
CJK Compat Ideographs 52
 
0.1%
Compat Jamo 9
 
< 0.1%
Math Operators 4
 
< 0.1%
Arrows 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15358
72.2%
. 1115
 
5.2%
, 948
 
4.5%
1 687
 
3.2%
0 385
 
1.8%
( 327
 
1.5%
) 326
 
1.5%
2 275
 
1.3%
5 247
 
1.2%
3 232
 
1.1%
Other values (48) 1357
 
6.4%
Hangul
ValueCountFrequency (%)
이 1613
 
3.4%
다 1290
 
2.7%
의 1120
 
2.4%
에 1050
 
2.2%
는 1049
 
2.2%
로 909
 
1.9%
고 817
 
1.7%
을 796
 
1.7%
있 785
 
1.7%
하 746
 
1.6%
Other values (855) 36987
78.4%
CJK Compat
ValueCountFrequency (%)
㎝ 69
86.2%
㎡ 9
 
11.2%
㎞ 2
 
2.5%
None
ValueCountFrequency (%)
· 39
37.1%
「 15
 
14.3%
」 15
 
14.3%
『 10
 
9.5%
』 10
 
9.5%
～ 6
 
5.7%
× 2
 
1.9%
《 2
 
1.9%
》 2
 
1.9%
° 2
 
1.9%
Other values (2) 2
 
1.9%
Punctuation
ValueCountFrequency (%)
’ 36
48.6%
‘ 36
48.6%
“ 1
 
1.4%
” 1
 
1.4%
CJK
ValueCountFrequency (%)
氏 32
 
2.3%
夫 27
 
1.9%
人 23
 
1.6%
墓 20
 
1.4%
州 19
 
1.3%
大 18
 
1.3%
敬 18
 
1.3%
陵 17
 
1.2%
府 15
 
1.1%
公 14
 
1.0%
Other values (508) 1211
85.6%
CJK Compat Ideographs
ValueCountFrequency (%)
李 16
30.8%
金 8
15.4%
領 3
 
5.8%
寧 3
 
5.8%
吏 2
 
3.8%
柳 2
 
3.8%
樂 2
 
3.8%
露 2
 
3.8%
立 2
 
3.8%
烈 1
 
1.9%
Other values (11) 11
21.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 7
77.8%
ㅡ 1
 
11.1%
ㅁ 1
 
11.1%
Math Operators
ValueCountFrequency (%)
∼ 4
100.0%
Arrows
ValueCountFrequency (%)
→ 3
100.0%
Box Drawing
ValueCountFrequency (%)
┼ 1
100.0%

설명_영어(en)
Text

MISSING 

Distinct188
Distinct (%)95.4%
Missing1065
Missing (%)84.4%
Memory size10.0 KiB
2024-03-23T06:21:39.460278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length738
Median length276
Mean length229.25381
Min length10

Characters and Unicode

Total characters45163
Distinct characters79
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique181 ?
Unique (%)91.9%

Sample

1st rowKINTEX is one of the biggest convention centers in Korea that hosts and organizes international MICE events.
2nd rowSeooreung Royal Tombs, a cluster of five Joseon-era tombs, is the second largest tomb site after Donggureung Royal Tombs.
3rd rowSeosamneung Royal Tombs is a cluster of three Joseon-era tombs, which are located in Wondang-dong, Goyang. It was first used as a tomb of Queen Janggyeong, the second wife of King Jungjong. Besides the three tombs, there is a placenta chamber of the prince as well as the tombs of royal princesses and daughters of concubines along with Hyochangwon of Crown Prince Munhyo and Sogyeongwon of Crown Prince Sohyeon.
4th rowThis is the same course as Chungui-gil, Hyoja-gil, and Naesimyoyeok-gil, and it does not have any specific indicators.
5th rowThis course starts at Sagokgyo Bridge, and passes through the Changneung Stream, Bukhansan Hot Springs and Ogeum Sangchon Park, finally arriving at Samsong Station.
ValueCountFrequency (%)
the 546
 
7.4%
of 318
 
4.3%
and 303
 
4.1%
is 223
 
3.0%
a 178
 
2.4%
in 176
 
2.4%
to 120
 
1.6%
was 95
 
1.3%
it 87
 
1.2%
with 64
 
0.9%
Other values (1959) 5305
71.5%
2024-03-23T06:21:41.196064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7316
16.2%
e 4008
 
8.9%
a 3254
 
7.2%
n 3209
 
7.1%
t 2841
 
6.3%
o 2784
 
6.2%
i 2614
 
5.8%
s 2297
 
5.1%
r 1972
 
4.4%
h 1495
 
3.3%
Other values (69) 13373
29.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34566
76.5%
Space Separator 7316
 
16.2%
Uppercase Letter 1832
 
4.1%
Other Punctuation 781
 
1.7%
Decimal Number 434
 
1.0%
Dash Punctuation 107
 
0.2%
Open Punctuation 52
 
0.1%
Close Punctuation 51
 
0.1%
Final Punctuation 17
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4008
11.6%
a 3254
 
9.4%
n 3209
 
9.3%
t 2841
 
8.2%
o 2784
 
8.1%
i 2614
 
7.6%
s 2297
 
6.6%
r 1972
 
5.7%
h 1495
 
4.3%
d 1315
 
3.8%
Other values (16) 8777
25.4%
Uppercase Letter
ValueCountFrequency (%)
T 178
 
9.7%
G 163
 
8.9%
S 157
 
8.6%
H 145
 
7.9%
J 131
 
7.2%
I 119
 
6.5%
C 114
 
6.2%
M 108
 
5.9%
K 97
 
5.3%
B 96
 
5.2%
Other values (16) 524
28.6%
Decimal Number
ValueCountFrequency (%)
1 104
24.0%
0 69
15.9%
9 46
10.6%
4 38
 
8.8%
2 33
 
7.6%
5 33
 
7.6%
3 29
 
6.7%
8 29
 
6.7%
7 27
 
6.2%
6 26
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 384
49.2%
, 362
46.4%
" 26
 
3.3%
! 3
 
0.4%
% 2
 
0.3%
; 2
 
0.3%
' 2
 
0.3%
Math Symbol
ValueCountFrequency (%)
< 3
42.9%
> 3
42.9%
+ 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 51
98.1%
[ 1
 
1.9%
Close Punctuation
ValueCountFrequency (%)
) 50
98.0%
] 1
 
2.0%
Space Separator
ValueCountFrequency (%)
7316
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 107
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36398
80.6%
Common 8765
 
19.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4008
 
11.0%
a 3254
 
8.9%
n 3209
 
8.8%
t 2841
 
7.8%
o 2784
 
7.6%
i 2614
 
7.2%
s 2297
 
6.3%
r 1972
 
5.4%
h 1495
 
4.1%
d 1315
 
3.6%
Other values (42) 10609
29.1%
Common
ValueCountFrequency (%)
7316
83.5%
. 384
 
4.4%
, 362
 
4.1%
- 107
 
1.2%
1 104
 
1.2%
0 69
 
0.8%
( 51
 
0.6%
) 50
 
0.6%
9 46
 
0.5%
4 38
 
0.4%
Other values (17) 238
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45146
> 99.9%
Punctuation 17
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7316
16.2%
e 4008
 
8.9%
a 3254
 
7.2%
n 3209
 
7.1%
t 2841
 
6.3%
o 2784
 
6.2%
i 2614
 
5.8%
s 2297
 
5.1%
r 1972
 
4.4%
h 1495
 
3.3%
Other values (68) 13356
29.6%
Punctuation
ValueCountFrequency (%)
’ 17
100.0%

설명_중국어(cn)
Text

MISSING 

Distinct187
Distinct (%)94.9%
Missing1065
Missing (%)84.4%
Memory size10.0 KiB
2024-03-23T06:21:41.987356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length127
Median length60
Mean length44.959391
Min length14

Characters and Unicode

Total characters8857
Distinct characters862
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179 ?
Unique (%)90.9%

Sample

1st row展中心是代表性展，模之最，展、，是展目的代表所。
2nd row西五陵是面次于九陵的朝王朝王室的家族墓地，因朝王朝的五座陵墓聚集于此而得名。
3rd row西三陵是指位于高市元堂洞的三座陵墓。其首次作陵地使用是在被中宗妃章敬王后尹氏的禧陵所在地后。除了三座陵墓之外，里有胎室、公主和翁主墓、昭、孝昌等。
4th row北山世界路北山步道中的忠路、孝子路、侍墓域路相同，有行置高世界路的。
5th row一路段昌陵川寺谷始，北山泉和梧琴上村公，到三松站。
ValueCountFrequency (%)
展中心是代表性展，模之最，展、，是展目的代表所。 3
 
1.5%
里是最大的知名家具企云集的地方，不有展、品牌家具常折，有著名的廊、中小企的自有品牌。 3
 
1.5%
里是一集物和文化于一的合空，有物中心、多影院、餐等，是充美食、看点、目的最大的街型物中心。 2
 
1.0%
西五陵是面次于九陵的朝王朝王室的家族墓地，因朝王朝的五座陵墓聚集于此而得名。 2
 
1.0%
中南美文化分土器、石器、木器、面具、民俗工、生活6主行展示。在土器中可以欣到印第安文化的代表性品；在石器和木器中可以了解中南美古代文明的宗式。 2
 
1.0%
是一家非利性文化、育机，通提供激童好奇心、予机的展和活等，努力足童和家人的需要心。 2
 
1.0%
幸州山城是一座山式山城，建在德山第7、8座山脊上，是利用泥土修建的土筑山城，重，由德山山的小型城和向北延伸的山谷的外城成，利用江岸峻的崖，、北、西展的平原，三代初期的山城式相同。 2
 
1.0%
西三陵是指位于高市元堂洞的三座陵墓。其首次作陵地使用是在被中宗妃章敬王后尹氏的禧陵所在地后。除了三座陵墓之外，里有胎室、公主和翁主墓、昭、孝昌等。 2
 
1.0%
岩刻文刻在北山主峰白云峰山的花岩岩石上。立家在了三一的史事后代，在平坦的岩石上刻上了“敬天人”四字，用正楷在其中岩刻下“《立宣言文》由崔南善于2月10日撰，3月1日在塔洞公自己唱了立宣言万”的容。 1
 
0.5%
朝中期的文臣沈喜在宣祖期文科及第，后任了右政。在元洞一偏僻的村庄里敬夫人光州氏的墓形成。 1
 
0.5%
Other values (185) 185
90.2%
2024-03-23T06:21:43.407989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
的 473
 
5.3%
， 390
 
4.4%
。 292
 
3.3%
是 170
 
1.9%
、 159
 
1.8%
山 151
 
1.7%
106
 
1.2%
一 101
 
1.1%
1 100
 
1.1%
年 99
 
1.1%
Other values (852) 6816
77.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7260
82.0%
Other Punctuation 855
 
9.7%
Decimal Number 435
 
4.9%
Space Separator 106
 
1.2%
Close Punctuation 49
 
0.6%
Open Punctuation 49
 
0.6%
Lowercase Letter 43
 
0.5%
Uppercase Letter 21
 
0.2%
Math Symbol 14
 
0.2%
Final Punctuation 13
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
的 473
 
6.5%
是 170
 
2.3%
山 151
 
2.1%
一 101
 
1.4%
年 99
 
1.4%
和 94
 
1.3%
在 85
 
1.2%
高 83
 
1.1%
中 78
 
1.1%
朝 71
 
1.0%
Other values (798) 5855
80.6%
Lowercase Letter
ValueCountFrequency (%)
e 7
16.3%
t 6
14.0%
a 6
14.0%
s 5
11.6%
m 4
9.3%
r 4
9.3%
n 3
7.0%
o 2
 
4.7%
f 1
 
2.3%
k 1
 
2.3%
Other values (4) 4
9.3%
Uppercase Letter
ValueCountFrequency (%)
D 3
14.3%
S 3
14.3%
W 2
9.5%
B 2
9.5%
L 2
9.5%
A 2
9.5%
P 1
 
4.8%
Y 1
 
4.8%
V 1
 
4.8%
F 1
 
4.8%
Other values (3) 3
14.3%
Decimal Number
ValueCountFrequency (%)
1 100
23.0%
0 68
15.6%
9 39
 
9.0%
3 37
 
8.5%
2 37
 
8.5%
5 36
 
8.3%
4 34
 
7.8%
6 33
 
7.6%
7 27
 
6.2%
8 24
 
5.5%
Other Punctuation
ValueCountFrequency (%)
， 390
45.6%
。 292
34.2%
、 159
18.6%
. 6
 
0.7%
； 3
 
0.4%
% 2
 
0.2%
！ 2
 
0.2%
· 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
） 43
87.8%
》 6
 
12.2%
Open Punctuation
ValueCountFrequency (%)
（ 43
87.8%
《 6
 
12.2%
Final Punctuation
ValueCountFrequency (%)
” 12
92.3%
’ 1
 
7.7%
Space Separator
ValueCountFrequency (%)
106
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 7260
82.0%
Common 1533
 
17.3%
Latin 64
 
0.7%

Most frequent character per script

Han
ValueCountFrequency (%)
的 473
 
6.5%
是 170
 
2.3%
山 151
 
2.1%
一 101
 
1.4%
年 99
 
1.4%
和 94
 
1.3%
在 85
 
1.2%
高 83
 
1.1%
中 78
 
1.1%
朝 71
 
1.0%
Other values (798) 5855
80.6%
Common
ValueCountFrequency (%)
， 390
25.4%
。 292
19.0%
、 159
10.4%
106
 
6.9%
1 100
 
6.5%
0 68
 
4.4%
） 43
 
2.8%
（ 43
 
2.8%
9 39
 
2.5%
3 37
 
2.4%
Other values (17) 256
16.7%
Latin
ValueCountFrequency (%)
e 7
 
10.9%
t 6
 
9.4%
a 6
 
9.4%
s 5
 
7.8%
m 4
 
6.2%
r 4
 
6.2%
n 3
 
4.7%
D 3
 
4.7%
S 3
 
4.7%
o 2
 
3.1%
Other values (17) 21
32.8%

Most occurring blocks

ValueCountFrequency (%)
CJK 7260
82.0%
None 945
 
10.7%
ASCII 627
 
7.1%
Punctuation 25
 
0.3%

Most frequent character per block

CJK
ValueCountFrequency (%)
的 473
 
6.5%
是 170
 
2.3%
山 151
 
2.1%
一 101
 
1.4%
年 99
 
1.4%
和 94
 
1.3%
在 85
 
1.2%
高 83
 
1.1%
中 78
 
1.1%
朝 71
 
1.0%
Other values (798) 5855
80.6%
None
ValueCountFrequency (%)
， 390
41.3%
。 292
30.9%
、 159
16.8%
） 43
 
4.6%
（ 43
 
4.6%
《 6
 
0.6%
》 6
 
0.6%
； 3
 
0.3%
！ 2
 
0.2%
· 1
 
0.1%
ASCII
ValueCountFrequency (%)
106
16.9%
1 100
15.9%
0 68
10.8%
9 39
 
6.2%
3 37
 
5.9%
2 37
 
5.9%
5 36
 
5.7%
4 34
 
5.4%
6 33
 
5.3%
7 27
 
4.3%
Other values (31) 110
17.5%
Punctuation
ValueCountFrequency (%)
“ 12
48.0%
” 12
48.0%
’ 1
 
4.0%

필드제목_한국어(ko)
Text

MISSING 

Distinct53
Distinct (%)7.2%
Missing526
Missing (%)41.7%
Memory size10.0 KiB
2024-03-23T06:21:43.911904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length55
Mean length12.629076
Min length6

Characters and Unicode

Total characters9295
Distinct characters95
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

Unique23 ?
Unique (%)3.1%

Sample

1st row["홈페이지#weblink","시설안내","w","h","name_display"]
2nd row["홈페이지#weblink"," 지정번호 ","이용시간","w","h","name_display"]
3rd row[" 지정번호 ","이용시간","w","h","name_display","서삼릉","희릉","효릉","예릉"]
4th row["홈페이지","코스안내"]
5th row["홈페이지","코스안내"]
ValueCountFrequency (%)
180
19.0%
메뉴 144
15.2%
대표자 125
13.2%
지정번호 101
10.7%
홈페이지 83
8.8%
text_direction 72
 
7.6%
name_display 63
 
6.7%
w","h","name_display 21
 
2.2%
메뉴","대표자 21
 
2.2%
운영시간","정기휴관일 16
 
1.7%
Other values (40) 121
12.8%
2024-03-23T06:21:45.727684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 2058
22.1%
[ 736
 
7.9%
] 736
 
7.9%
e 310
 
3.3%
i 310
 
3.3%
, 293
 
3.2%
t 270
 
2.9%
a 240
 
2.6%
지 240
 
2.6%
n 220
 
2.4%
Other values (85) 3882
41.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2674
28.8%
Other Punctuation 2361
25.4%
Other Letter 2354
25.3%
Open Punctuation 742
 
8.0%
Close Punctuation 742
 
8.0%
Space Separator 212
 
2.3%
Connector Punctuation 210
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 240
 
10.2%
뉴 165
 
7.0%
메 165
 
7.0%
이 148
 
6.3%
자 146
 
6.2%
표 146
 
6.2%
대 146
 
6.2%
정 138
 
5.9%
페 137
 
5.8%
홈 137
 
5.8%
Other values (57) 786
33.4%
Lowercase Letter
ValueCountFrequency (%)
e 310
11.6%
i 310
11.6%
t 270
10.1%
a 240
 
9.0%
n 220
 
8.2%
d 210
 
7.9%
l 130
 
4.9%
p 120
 
4.5%
y 120
 
4.5%
m 120
 
4.5%
Other values (9) 624
23.3%
Other Punctuation
ValueCountFrequency (%)
" 2058
87.2%
, 293
 
12.4%
# 10
 
0.4%
Open Punctuation
ValueCountFrequency (%)
[ 736
99.2%
( 6
 
0.8%
Close Punctuation
ValueCountFrequency (%)
] 736
99.2%
) 6
 
0.8%
Space Separator
ValueCountFrequency (%)
212
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 210
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4267
45.9%
Latin 2674
28.8%
Hangul 2354
25.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 240
 
10.2%
뉴 165
 
7.0%
메 165
 
7.0%
이 148
 
6.3%
자 146
 
6.2%
표 146
 
6.2%
대 146
 
6.2%
정 138
 
5.9%
페 137
 
5.8%
홈 137
 
5.8%
Other values (57) 786
33.4%
Latin
ValueCountFrequency (%)
e 310
11.6%
i 310
11.6%
t 270
10.1%
a 240
 
9.0%
n 220
 
8.2%
d 210
 
7.9%
l 130
 
4.9%
p 120
 
4.5%
y 120
 
4.5%
m 120
 
4.5%
Other values (9) 624
23.3%
Common
ValueCountFrequency (%)
" 2058
48.2%
[ 736
 
17.2%
] 736
 
17.2%
, 293
 
6.9%
212
 
5.0%
_ 210
 
4.9%
# 10
 
0.2%
) 6
 
0.1%
( 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6941
74.7%
Hangul 2354
 
25.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 2058
29.6%
[ 736
 
10.6%
] 736
 
10.6%
e 310
 
4.5%
i 310
 
4.5%
, 293
 
4.2%
t 270
 
3.9%
a 240
 
3.5%
n 220
 
3.2%
212
 
3.1%
Other values (18) 1556
22.4%
Hangul
ValueCountFrequency (%)
지 240
 
10.2%
뉴 165
 
7.0%
메 165
 
7.0%
이 148
 
6.3%
자 146
 
6.2%
표 146
 
6.2%
대 146
 
6.2%
정 138
 
5.9%
페 137
 
5.8%
홈 137
 
5.8%
Other values (57) 786
33.4%

필드제목_영어(en)
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct51
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
834 
["Menu"]
142 
["Designation"]
 
80
["Website"]
 
45
["Closed"]
 
16
Other values (46)
145 

Length

Max length104
Median length4
Mean length8.322504
Min length4

Unique

Unique21 ?
Unique (%)1.7%

Sample

1st row["Website#weblink","Information","w","h","name_display"]
2nd row["Website#weblink","Designation","Hours","w","h","name_display"]
3rd row["Designation","Hours","w","h","name_display","Seosamneung Royal Tombs","Huireung","Hyoreung","Yereung"]
4th row["Website","Course"]
5th row["Website","Course"]

Common Values

ValueCountFrequency (%)
<NA> 834
66.1%
["Menu"] 142
 
11.3%
["Designation"] 80
 
6.3%
["Website"] 45
 
3.6%
["Closed"] 16
 
1.3%
["Hours","Closed"] 16
 
1.3%
["Website","Course"] 14
 
1.1%
["Operator","Program(s)","w","h","name_display"] 9
 
0.7%
["Schedule"] 7
 
0.6%
["Website","w","h","name_display"] 6
 
0.5%
Other values (41) 93
 
7.4%

Length

2024-03-23T06:21:46.314254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 834
65.9%
menu 142
 
11.2%
designation 82
 
6.5%
website 45
 
3.6%
closed 16
 
1.3%
hours","closed 16
 
1.3%
website","course 14
 
1.1%
operator","program(s)","w","h","name_display 9
 
0.7%
schedule 7
 
0.6%
website#weblink 6
 
0.5%
Other values (44) 95
 
7.5%

필드제목_중국어(cn)
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct51
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
834 
["Menu"]
142 
["Designation"]
 
80
["Website"]
 
45
["Closed"]
 
16
Other values (46)
145 

Length

Max length104
Median length4
Mean length8.322504
Min length4

Unique

Unique21 ?
Unique (%)1.7%

Sample

1st row["Website#weblink","Information","w","h","name_display"]
2nd row["Website#weblink","Designation","Hours","w","h","name_display"]
3rd row["Designation","Hours","w","h","name_display","Seosamneung Royal Tombs","Huireung","Hyoreung","Yereung"]
4th row["Website","Course"]
5th row["Website","Course"]

Common Values

ValueCountFrequency (%)
<NA> 834
66.1%
["Menu"] 142
 
11.3%
["Designation"] 80
 
6.3%
["Website"] 45
 
3.6%
["Closed"] 16
 
1.3%
["Hours","Closed"] 16
 
1.3%
["Website","Course"] 14
 
1.1%
["Operator","Program(s)","w","h","name_display"] 9
 
0.7%
["Schedule"] 7
 
0.6%
["Website","w","h","name_display"] 6
 
0.5%
Other values (41) 93
 
7.4%

Length

2024-03-23T06:21:46.940517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 834
65.9%
menu 142
 
11.2%
designation 82
 
6.5%
website 45
 
3.6%
closed 16
 
1.3%
hours","closed 16
 
1.3%
website","course 14
 
1.1%
operator","program(s)","w","h","name_display 9
 
0.7%
schedule 7
 
0.6%
website#weblink 6
 
0.5%
Other values (44) 95
 
7.5%

필드내용_한국어(ko)
Text

MISSING 

Distinct526
Distinct (%)71.5%
Missing526
Missing (%)41.7%
Memory size10.0 KiB
2024-03-23T06:21:47.636903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length228
Mean length27.407609
Min length6

Characters and Unicode

Total characters20172
Distinct characters541
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique481 ?
Unique (%)65.4%

Sample

1st row["http://www.kintex.com/","전시홀 : 총 10개홀 전용 주차장 4,000대, 임시 주차장 4,000대 회의실 : 중회의실 25개, 대회의실 12개 부대시설 : 식음시설 및 농협중앙회 킨텍스점 등 편의시설 제공","75","45","true"]
2nd row["https://royaltombs.cha.go.kr/html/HtmlPage.dopg=/new/html/portal_01_10_01.jsp&mn=RT_01_10","사적 제198호","3~10월 06:00~18:30 11~2월 06:30~17:30 (매주 월요일 휴무)","60","60","true"]
3rd row["사적 제200호","3~10월 06:00~18:30 11~2월 06:30~17:30 (매주 월요일 휴무)","60","60","true","중종의 계비 장경왕후 윤씨의 희릉을 조성하면서 서삼릉의 역사가 시작됨. 중종의 정릉이 조성되었으나 서울 삼성동 선릉 곁으로 옮겨갔고, 중종의 아들인 인종과 비 인성왕후 박씨의 효릉, 철종과 비 철인왕후 김씨의 예릉이 있다. 그밖에 소경원 의령원 효창원 등 세자의 園 3기와 폐비 윤씨의 회묘를 비롯한 45기의 묘가 조성되어 있다.","11대 중종의 계비 장경왕후 윤씨(1491~1515,25)의 단릉이다. 영돈녕부사 윤여필의 딸로 8세 때 어머니를 여의고 월산대군의 부인 박씨에 의하여 양육되었다. 중종반정으로 단경왕후 신씨가 폐위되자 왕비에 책봉되었다. 1515년 인종을 낳고 산후병을 얻어 7일 만에 사망하였다. 능은 원래 헌릉(서울 서초동)에 있었으나 22년 뒤 김안로의 술책(정광필, 남곤 등이 조성한 묘자리에 큰 돌이 깔려있어서 좋지 않다는) 때문에 지금의 자리로 이장했다.","12대 인종(1515~1545,31)과 인성왕후 박씨(1514~1577,64)의 쌍릉이다. 인종은 효성이 지극하여 어머니인 장경왕후가 죽자 대왕대비인 정현왕후 윤씨(제9대 성종의 계비)를 더욱 섬겼으며, 아버지인 중종이 위독하자 반드시 먼저 약의 맛을 보고, 겨울철인데도 목욕하고 분향하며 한데 서서 저녁부터 새벽까지 하늘에 빌 정도 였다. 중종이 죽자 8개월만에 승하하였는데 부모의 곁에 묻어줄 것과 장사를 소박하게 해달라고 부탁하였다. 그래서일까 그의 능은 원래 병풍석이 없다가 인성왕후가 승하한 후 인종 곁에 묻히면서 현재 왕릉에서 볼 수 있는 병풍석을 둘렀다고 한다.","25대 철종(1831~1863,33)과 철인왕후 김씨(1837~1878,42)의 쌍릉이다. ‘강화도령’으로 널리 알려진 철종은 강화도에 살던 중 1848년 24대 헌종이 후사 없이 승하하자 뒤를 이어 왕위에 올랐다. 당시 영조의 유일한 혈손이었기 때문이다. 철종의 조부인 은언군은 그 아들 상계군 담이 반역을 꾀했다고
4th row["https://nuri.goyang.go.kr/","거리 : 총 6.97km 시간 : 약 2시간 20분 코스 : 고양시계 ▶ 사기막골삼거리 ▶ 효자비입구 ▶ 북한산성탐방지원센터 ▶ 북한산입구"]
5th row["https://nuri.goyang.go.kr/","거리 : 6.5km 시간 : 2시간 10분 코스 : 북한산부근 ▶ 북한산온천 ▶ 옥녀봉 ▶ 오금상촌공원 ▶ 오동나무쉼터 ▶ 여석정 ▶ 등산로입구 ▶ 삼송역"]
ValueCountFrequency (%)
167
 
7.0%
번째 69
 
2.9%
▶ 69
 
2.9%
false 63
 
2.7%
right 40
 
1.7%
향토문화재 33
 
1.4%
월요일 30
 
1.3%
두 24
 
1.0%
10:00 21
 
0.9%
네 20
 
0.8%
Other values (1220) 1835
77.4%
2024-03-23T06:21:49.237028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 2057
 
10.2%
1651
 
8.2%
[ 738
 
3.7%
] 737
 
3.7%
/ 655
 
3.2%
t 583
 
2.9%
0 529
 
2.6%
. 493
 
2.4%
, 468
 
2.3%
r 418
 
2.1%
Other values (531) 11843
58.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5523
27.4%
Lowercase Letter 5305
26.3%
Other Punctuation 4111
20.4%
Space Separator 1651
 
8.2%
Decimal Number 1544
 
7.7%
Close Punctuation 804
 
4.0%
Open Punctuation 798
 
4.0%
Math Symbol 160
 
0.8%
Uppercase Letter 129
 
0.6%
Other Symbol 70
 
0.3%
Other values (4) 77
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 152
 
2.8%
시 129
 
2.3%
제 119
 
2.2%
호 119
 
2.2%
화 108
 
2.0%
문 104
 
1.9%
재 98
 
1.8%
월 96
 
1.7%
이 91
 
1.6%
요 83
 
1.5%
Other values (446) 4424
80.1%
Lowercase Letter
ValueCountFrequency (%)
t 583
 
11.0%
r 418
 
7.9%
e 392
 
7.4%
s 386
 
7.3%
p 368
 
6.9%
o 333
 
6.3%
a 330
 
6.2%
h 291
 
5.5%
g 289
 
5.4%
i 282
 
5.3%
Other values (16) 1633
30.8%
Uppercase Letter
ValueCountFrequency (%)
F 18
14.0%
R 11
 
8.5%
D 10
 
7.8%
A 9
 
7.0%
E 9
 
7.0%
V 8
 
6.2%
C 8
 
6.2%
B 7
 
5.4%
I 7
 
5.4%
T 6
 
4.7%
Other values (14) 36
27.9%
Other Punctuation
ValueCountFrequency (%)
" 2057
50.0%
/ 655
 
15.9%
. 493
 
12.0%
, 468
 
11.4%
: 341
 
8.3%
% 50
 
1.2%
& 35
 
0.9%
※ 5
 
0.1%
· 3
 
0.1%
* 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 529
34.3%
1 262
17.0%
2 139
 
9.0%
3 109
 
7.1%
5 101
 
6.5%
6 100
 
6.5%
4 88
 
5.7%
7 79
 
5.1%
8 76
 
4.9%
9 61
 
4.0%
Math Symbol
ValueCountFrequency (%)
~ 106
66.2%
= 41
 
25.6%
→ 12
 
7.5%
+ 1
 
0.6%
Open Punctuation
ValueCountFrequency (%)
[ 738
92.5%
( 60
 
7.5%
Close Punctuation
ValueCountFrequency (%)
] 737
91.7%
) 67
 
8.3%
Space Separator
ValueCountFrequency (%)
1651
100.0%
Other Symbol
ValueCountFrequency (%)
▶ 70
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 45
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 4
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9215
45.7%
Hangul 5520
27.4%
Latin 5434
26.9%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 152
 
2.8%
시 129
 
2.3%
제 119
 
2.2%
호 119
 
2.2%
화 108
 
2.0%
문 104
 
1.9%
재 98
 
1.8%
월 96
 
1.7%
이 91
 
1.6%
요 83
 
1.5%
Other values (443) 4421
80.1%
Latin
ValueCountFrequency (%)
t 583
 
10.7%
r 418
 
7.7%
e 392
 
7.2%
s 386
 
7.1%
p 368
 
6.8%
o 333
 
6.1%
a 330
 
6.1%
h 291
 
5.4%
g 289
 
5.3%
i 282
 
5.2%
Other values (40) 1762
32.4%
Common
ValueCountFrequency (%)
" 2057
22.3%
1651
17.9%
[ 738
 
8.0%
] 737
 
8.0%
/ 655
 
7.1%
0 529
 
5.7%
. 493
 
5.3%
, 468
 
5.1%
: 341
 
3.7%
1 262
 
2.8%
Other values (25) 1284
13.9%
Han
ValueCountFrequency (%)
市 1
33.3%
花 1
33.3%
園 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14551
72.1%
Hangul 5520
 
27.4%
Geometric Shapes 70
 
0.3%
Punctuation 13
 
0.1%
Arrows 12
 
0.1%
None 3
 
< 0.1%
CJK 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 2057
 
14.1%
1651
 
11.3%
[ 738
 
5.1%
] 737
 
5.1%
/ 655
 
4.5%
t 583
 
4.0%
0 529
 
3.6%
. 493
 
3.4%
, 468
 
3.2%
r 418
 
2.9%
Other values (69) 6222
42.8%
Hangul
ValueCountFrequency (%)
일 152
 
2.8%
시 129
 
2.3%
제 119
 
2.2%
호 119
 
2.2%
화 108
 
2.0%
문 104
 
1.9%
재 98
 
1.8%
월 96
 
1.7%
이 91
 
1.6%
요 83
 
1.5%
Other values (443) 4421
80.1%
Geometric Shapes
ValueCountFrequency (%)
▶ 70
100.0%
Arrows
ValueCountFrequency (%)
→ 12
100.0%
Punctuation
ValueCountFrequency (%)
※ 5
38.5%
‘ 4
30.8%
’ 4
30.8%
None
ValueCountFrequency (%)
· 3
100.0%
CJK
ValueCountFrequency (%)
市 1
33.3%
花 1
33.3%
園 1
33.3%

필드내용_영어(en)
Text

MISSING 

Distinct339
Distinct (%)79.2%
Missing834
Missing (%)66.1%
Memory size10.0 KiB
2024-03-23T06:21:50.340393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length177
Mean length52.544393
Min length7

Characters and Unicode

Total characters22489
Distinct characters88
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique299 ?
Unique (%)69.9%

Sample

1st row["http://www.kintex.com/","Exhibition hall: 4,000 parking spaces for customers at 10 halls only; Temporary parking space for 4,000 vehicles / Conference rooms: 25 medium & 12 large / Amenities: F&B, NH KINTEX branch, etc.","75","45","true"]
2nd row["royaltombs.cha.go.kr/html/HtmlPage.dopg=/new/html/portal_01_10_01.jsp&mn=RT_01_10","Historic Site No.198","6AM6:30PM (MarOct); 6:30AM5:30PM (NovFeb) (Closed Mon)","60","60","true"]
3rd row["Historic Site No.200","6AM6:30PM (MarOct); 6:30AM5:30PM (NovFeb) (Closed Mon)","60","60","true","The history of the Seosamneung Royal Tombs begins with Huineung of Queen Janggyeong, the second wife of King Jungjong. Later, Jeongneung of King Jungjong was built and transported next to the Seolleung Royal Tomb in Samseong-dong, Seoul. There are also Hyoneung of King Injong and Queen Inseong, and Yeneung of King Cheoljong and Queen Cheorin. Plus, there are a total of 45 tombs including of Hyochangwon of Crown Prince Munhyo, Sogyeongwon of Crown Prince Sohyeon, and Uiryeongwon of Crown Prince Uiso.","Danneung is the tomb of Queen Janggyeong (14911515; aged 25), the second wife of King Jungjong, the 11th ruler of Joseon. Her father, Yun Yeo-pil was a member of the Papyeong Yun clan (Donnyeongbu: Office of Royal Relatives) and her mother died at the age of 8. So she was raised by her maternal aunt, Grand Princess Consort Seungpyeong of the Suncheon Park clan. After Queen Dangyeong was deposed due to Jungjong-banj
4th row["nuri.goyang.go.kr","Distance: 6.97km / Duration: 2 hr 20 min / Course: Goyangsigye ▶ Sagimakgol Samgeori ▶ Hyojabi Entrace ▶ Bukhansan Tourist Information Center ▶ Bukhansan Mountain Entrance"]
5th row["nuri.goyang.go.kr","Distance: 6.5 km / Duration: 2 hr 10 min / Course: Bukhansan Mountain ▶ Bukhansan Hot Spring ▶ Oknyeobong Peak ▶ Ogeum Sangchon Park▶ Odong Namu Shelter ▶ Yeoseokjeong Pavilion ▶ Trail Entrance ▶ Samsong Station"]
ValueCountFrequency (%)
158
 
6.3%
heritage 73
 
2.9%
cultural 73
 
2.9%
▶ 62
 
2.5%
local 48
 
1.9%
and 40
 
1.6%
mon 35
 
1.4%
soup 33
 
1.3%
pork 31
 
1.2%
of 28
 
1.1%
Other values (863) 1939
76.9%
2024-03-23T06:21:52.251418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2092
 
9.3%
e 1410
 
6.3%
" 1369
 
6.1%
o 1293
 
5.7%
a 1164
 
5.2%
r 1022
 
4.5%
t 988
 
4.4%
n 906
 
4.0%
i 888
 
3.9%
s 728
 
3.2%
Other values (78) 10629
47.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13273
59.0%
Other Punctuation 2873
 
12.8%
Space Separator 2092
 
9.3%
Uppercase Letter 1975
 
8.8%
Decimal Number 1038
 
4.6%
Open Punctuation 529
 
2.4%
Close Punctuation 528
 
2.3%
Other Symbol 65
 
0.3%
Connector Punctuation 47
 
0.2%
Dash Punctuation 38
 
0.2%
Other values (3) 31
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1410
 
10.6%
o 1293
 
9.7%
a 1164
 
8.8%
r 1022
 
7.7%
t 988
 
7.4%
n 906
 
6.8%
i 888
 
6.7%
s 728
 
5.5%
l 722
 
5.4%
u 594
 
4.5%
Other values (16) 3558
26.8%
Uppercase Letter
ValueCountFrequency (%)
S 243
12.3%
M 242
12.3%
C 174
 
8.8%
P 152
 
7.7%
N 147
 
7.4%
H 128
 
6.5%
A 99
 
5.0%
F 95
 
4.8%
B 91
 
4.6%
T 83
 
4.2%
Other values (16) 521
26.4%
Other Punctuation
ValueCountFrequency (%)
" 1369
47.7%
. 469
 
16.3%
/ 458
 
15.9%
, 374
 
13.0%
: 149
 
5.2%
& 23
 
0.8%
; 19
 
0.7%
% 5
 
0.2%
※ 2
 
0.1%
\ 2
 
0.1%
Other values (3) 3
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 290
27.9%
1 149
14.4%
2 115
 
11.1%
6 100
 
9.6%
3 90
 
8.7%
4 85
 
8.2%
5 74
 
7.1%
7 58
 
5.6%
9 41
 
3.9%
8 36
 
3.5%
Math Symbol
ValueCountFrequency (%)
→ 12
57.1%
= 8
38.1%
+ 1
 
4.8%
Open Punctuation
ValueCountFrequency (%)
[ 432
81.7%
( 97
 
18.3%
Close Punctuation
ValueCountFrequency (%)
] 431
81.6%
) 97
 
18.4%
Space Separator
ValueCountFrequency (%)
2092
100.0%
Other Symbol
ValueCountFrequency (%)
▶ 65
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 9
100.0%
Other Letter
ValueCountFrequency (%)
가 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15248
67.8%
Common 7240
32.2%
Hangul 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1410
 
9.2%
o 1293
 
8.5%
a 1164
 
7.6%
r 1022
 
6.7%
t 988
 
6.5%
n 906
 
5.9%
i 888
 
5.8%
s 728
 
4.8%
l 722
 
4.7%
u 594
 
3.9%
Other values (42) 5533
36.3%
Common
ValueCountFrequency (%)
2092
28.9%
" 1369
18.9%
. 469
 
6.5%
/ 458
 
6.3%
[ 432
 
6.0%
] 431
 
6.0%
, 374
 
5.2%
0 290
 
4.0%
: 149
 
2.1%
1 149
 
2.1%
Other values (25) 1027
14.2%
Hangul
ValueCountFrequency (%)
가 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22399
99.6%
Geometric Shapes 65
 
0.3%
Arrows 12
 
0.1%
Punctuation 11
 
< 0.1%
Hangul 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2092
 
9.3%
e 1410
 
6.3%
" 1369
 
6.1%
o 1293
 
5.8%
a 1164
 
5.2%
r 1022
 
4.6%
t 988
 
4.4%
n 906
 
4.0%
i 888
 
4.0%
s 728
 
3.3%
Other values (72) 10539
47.1%
Geometric Shapes
ValueCountFrequency (%)
▶ 65
100.0%
Arrows
ValueCountFrequency (%)
→ 12
100.0%
Punctuation
ValueCountFrequency (%)
’ 9
81.8%
※ 2
 
18.2%
Hangul
ValueCountFrequency (%)
가 1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

필드내용_중국어(cn)
Text

MISSING 

Distinct341
Distinct (%)80.0%
Missing836
Missing (%)66.2%
Memory size10.0 KiB
2024-03-23T06:21:52.781876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length784
Median length111
Mean length29.85446
Min length4

Characters and Unicode

Total characters12718
Distinct characters547
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique298 ?
Unique (%)70.0%

Sample

1st row["http://www.kintex.com","展：共10，用停有4000位，停有4000位，室：中型室25、大型室12 附施：提供餐施及中央展中心店等便利施","75","45","true"]
2nd row["https://royaltombs.cha.go.kr/html/HtmlPage.dopg=/new/html/portal_01_10_01.jsp&mn=RT_01_10","史迹第198\r\n","3月~10月06:00~18:30 11月~2月06:30~17:30（每周一休息）","60","60","TRUE"]
3rd row["史迹第200","3月~10月06:00~18:30 11月~2月06:30~17:30（每周一休息）\r\n","60","60","TRUE","中宗妃章敬王后尹氏的禧陵建成后，西三陵的史由此始。中宗的靖陵然建成，但至首三成洞宣陵旁，有中宗的子仁宗和仁王后朴氏的孝陵、哲宗和哲仁王后金氏的睿陵。此外，建有昭、懿、孝昌等三座世子的墓以及包括妃尹氏的墓在的45座墓。","是第11代王中宗的妃庄敬王后尹氏（1491~1515，25）的人陵墓。是敦府事尹汝弼的女，8失去母，由月山大君的妻子朴某。由于中宗反正，端敬王后氏被，其被封王妃。1515年下仁宗，后生病，于7天后去世。陵墓原先位于陵（首瑞草洞），但22年后，因金安老策（因光弼、南等建造的墓地上有大石，地理位置不好），所以被移葬到了在的位置","是第12代王仁宗（1515~1545，31）和仁王后朴氏（1514~1577，64）合葬的人陵墓。仁宗非常孝，母章敬王后去世后，更加心侍奉大王大妃王后尹氏（第9代王成宗的妃）。父中宗病危后，一定要自己先味，在冬季也洗香，站着傍祈到凌晨。中宗去世后，他隔8月崩，拜托其埋葬在父母身，葬。也正因如此，他的陵墓原有石，仁王后死后埋葬在仁宗身，上了在在王陵中可以看到的石。","是第25代王哲宗（1831~1863，33）和哲仁王后金氏（1837~1878，42）合葬的人陵墓。被‘江公子’而人知的哲宗生活在江，第24代王宗无后，1848年崩后，哲宗位登上王位。因他是唯一一有英祖血的子。因其子常溪君李湛反，哲宗的祖父恩彦君于1786年被流放到江。1801年，因是天主徒，恩彦君的妻子宋某和申某也被死。再加上哲宗的兄元因反被而被死，所以哲宗周的人大部分都死了。就上王的哲宗生活，于在位14年去世睿陵是哲宗和哲仁王后合葬的人陵墓，是按照朝王朝常制度修建的最后一座陵墓。"]
4th row["https://nuri.goyang.go.kr/","距：6.97公里 ：2小20分 路：高▶沙器幕谷三路口▶孝子碑入口▶北山城探支援中心▶北山入口"]
5th row["https://nuri.goyang.go.kr/","距：6.5公里 ：2小10分 路：北山附近▶北山泉▶玉女峰▶梧琴上村公▶梧桐休息▶石亭▶登山路入口▶三松站"]
ValueCountFrequency (%)
66
 
10.5%
10:00 11
 
1.8%
定食 9
 
1.4%
刀切面 8
 
1.3%
→ 8
 
1.3%
第一、第三周一 7
 
1.1%
五花肉 6
 
1.0%
周一到周五 6
 
1.0%
第二、第四周一 6
 
1.0%
中菜 5
 
0.8%
Other values (432) 495
78.9%
2024-03-23T06:21:54.231117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 1368
 
10.8%
0 501
 
3.9%
/ 458
 
3.6%
[ 426
 
3.3%
] 426
 
3.3%
t 407
 
3.2%
. 358
 
2.8%
r 318
 
2.5%
p 286
 
2.2%
, 268
 
2.1%
Other values (537) 7902
62.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3606
28.4%
Other Letter 3163
24.9%
Other Punctuation 3117
24.5%
Decimal Number 1361
 
10.7%
Open Punctuation 490
 
3.9%
Close Punctuation 490
 
3.9%
Space Separator 203
 
1.6%
Math Symbol 99
 
0.8%
Other Symbol 65
 
0.5%
Uppercase Letter 55
 
0.4%
Other values (4) 69
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
第 175
 
5.5%
周 140
 
4.4%
文 80
 
2.5%
化 78
 
2.5%
一 78
 
2.5%
日 72
 
2.3%
土 54
 
1.7%
公 50
 
1.6%
月 44
 
1.4%
肉 44
 
1.4%
Other values (451) 2348
74.2%
Lowercase Letter
ValueCountFrequency (%)
t 407
 
11.3%
r 318
 
8.8%
p 286
 
7.9%
s 263
 
7.3%
o 240
 
6.7%
e 223
 
6.2%
g 213
 
5.9%
a 212
 
5.9%
i 205
 
5.7%
h 192
 
5.3%
Other values (16) 1047
29.0%
Uppercase Letter
ValueCountFrequency (%)
R 7
12.7%
D 5
 
9.1%
F 4
 
7.3%
A 4
 
7.3%
V 4
 
7.3%
E 4
 
7.3%
T 4
 
7.3%
G 3
 
5.5%
U 3
 
5.5%
L 2
 
3.6%
Other values (10) 15
27.3%
Other Punctuation
ValueCountFrequency (%)
" 1368
43.9%
/ 458
 
14.7%
. 358
 
11.5%
, 268
 
8.6%
: 223
 
7.2%
、 201
 
6.4%
： 77
 
2.5%
， 68
 
2.2%
\ 50
 
1.6%
。 31
 
1.0%
Other values (4) 15
 
0.5%
Decimal Number
ValueCountFrequency (%)
0 501
36.8%
1 234
17.2%
2 115
 
8.4%
3 94
 
6.9%
6 85
 
6.2%
7 76
 
5.6%
5 74
 
5.4%
4 73
 
5.4%
8 63
 
4.6%
9 46
 
3.4%
Close Punctuation
ValueCountFrequency (%)
] 426
86.9%
） 61
 
12.4%
) 3
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 81
81.8%
→ 12
 
12.1%
= 6
 
6.1%
Open Punctuation
ValueCountFrequency (%)
[ 426
86.9%
（ 64
 
13.1%
Initial Punctuation
ValueCountFrequency (%)
“ 1
50.0%
‘ 1
50.0%
Final Punctuation
ValueCountFrequency (%)
” 1
50.0%
’ 1
50.0%
Space Separator
ValueCountFrequency (%)
203
100.0%
Other Symbol
ValueCountFrequency (%)
▶ 65
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5894
46.3%
Latin 3661
28.8%
Han 3163
24.9%

Most frequent character per script

Han
ValueCountFrequency (%)
第 175
 
5.5%
周 140
 
4.4%
文 80
 
2.5%
化 78
 
2.5%
一 78
 
2.5%
日 72
 
2.3%
土 54
 
1.7%
公 50
 
1.6%
月 44
 
1.4%
肉 44
 
1.4%
Other values (451) 2348
74.2%
Latin
ValueCountFrequency (%)
t 407
 
11.1%
r 318
 
8.7%
p 286
 
7.8%
s 263
 
7.2%
o 240
 
6.6%
e 223
 
6.1%
g 213
 
5.8%
a 212
 
5.8%
i 205
 
5.6%
h 192
 
5.2%
Other values (36) 1102
30.1%
Common
ValueCountFrequency (%)
" 1368
23.2%
0 501
 
8.5%
/ 458
 
7.8%
[ 426
 
7.2%
] 426
 
7.2%
. 358
 
6.1%
, 268
 
4.5%
1 234
 
4.0%
: 223
 
3.8%
203
 
3.4%
Other values (30) 1429
24.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8967
70.5%
CJK 3163
 
24.9%
None 502
 
3.9%
Geometric Shapes 65
 
0.5%
Arrows 12
 
0.1%
Punctuation 9
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 1368
 
15.3%
0 501
 
5.6%
/ 458
 
5.1%
[ 426
 
4.8%
] 426
 
4.8%
t 407
 
4.5%
. 358
 
4.0%
r 318
 
3.5%
p 286
 
3.2%
, 268
 
3.0%
Other values (63) 4151
46.3%
None
ValueCountFrequency (%)
、 201
40.0%
： 77
 
15.3%
， 68
 
13.5%
（ 64
 
12.7%
） 61
 
12.2%
。 31
 
6.2%
CJK
ValueCountFrequency (%)
第 175
 
5.5%
周 140
 
4.4%
文 80
 
2.5%
化 78
 
2.5%
一 78
 
2.5%
日 72
 
2.3%
土 54
 
1.7%
公 50
 
1.6%
月 44
 
1.4%
肉 44
 
1.4%
Other values (451) 2348
74.2%
Geometric Shapes
ValueCountFrequency (%)
▶ 65
100.0%
Arrows
ValueCountFrequency (%)
→ 12
100.0%
Punctuation
ValueCountFrequency (%)
※ 5
55.6%
“ 1
 
11.1%
” 1
 
11.1%
‘ 1
 
11.1%
’ 1
 
11.1%

위도(lat)
Real number (ℝ)

Distinct1196
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.661293
Minimum37.578797
Maximum37.72759
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-03-23T06:21:55.078160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.578797
5-th percentile37.605215
Q137.645061
median37.663663
Q337.681198
95-th percentile37.703593
Maximum37.72759
Range0.14879256
Interquartile range (IQR)0.036136978

Descriptive statistics

Standard deviation0.028381169
Coefficient of variation (CV)0.00075358987
Kurtosis-0.20331751
Mean37.661293
Median Absolute Deviation (MAD)0.018172725
Skewness-0.36163267
Sum47528.552
Variance0.00080549077
MonotonicityNot monotonic
2024-03-23T06:21:55.591851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6637026 9
 
0.7%
37.5958911 5
 
0.4%
37.6961374 4
 
0.3%
37.6491928 4
 
0.3%
37.658391 4
 
0.3%
37.62584825 3
 
0.2%
37.6155207 3
 
0.2%
37.6693071 3
 
0.2%
37.6602946 2
 
0.2%
37.67237362 2
 
0.2%
Other values (1186) 1223
96.9%
ValueCountFrequency (%)
37.57879738 1
0.1%
37.5854306 1
0.1%
37.5855075 1
0.1%
37.5894654 1
0.1%
37.591659 1
0.1%
37.5924741 1
0.1%
37.5937959 1
0.1%
37.59403669 1
0.1%
37.5944086 1
0.1%
37.5950313 1
0.1%
ValueCountFrequency (%)
37.72758994 1
0.1%
37.72639719 1
0.1%
37.72615238 1
0.1%
37.7256187 1
0.1%
37.725345 1
0.1%
37.7235877 1
0.1%
37.72312895 1
0.1%
37.7226017 1
0.1%
37.7220154 1
0.1%
37.72181296 1
0.1%

경도(lng)
Real number (ℝ)

Distinct1198
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.81462
Minimum126.70691
Maximum126.98112
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-03-23T06:21:56.253774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.70691
5-th percentile126.74599
Q1126.77134
median126.81271
Q3126.84441
95-th percentile126.90459
Maximum126.98112
Range0.2742101
Interquartile range (IQR)0.073062775

Descriptive statistics

Standard deviation0.053737795
Coefficient of variation (CV)0.00042375077
Kurtosis-0.0023205249
Mean126.81462
Median Absolute Deviation (MAD)0.038657
Skewness0.62948784
Sum160040.06
Variance0.0028877506
MonotonicityNot monotonic
2024-03-23T06:21:56.953457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9397543 9
 
0.7%
126.826499 5
 
0.4%
126.7661857 4
 
0.3%
126.8477846 4
 
0.3%
126.7642233 4
 
0.3%
126.8297775 3
 
0.2%
126.8287686 3
 
0.2%
126.7456845 3
 
0.2%
126.7754213 2
 
0.2%
126.7673379 2
 
0.2%
Other values (1188) 1223
96.9%
ValueCountFrequency (%)
126.7069143 1
0.1%
126.7075904 1
0.1%
126.7156769 1
0.1%
126.7159721 1
0.1%
126.7163286 1
0.1%
126.7170506 1
0.1%
126.7201911 1
0.1%
126.7202446 1
0.1%
126.7203594 1
0.1%
126.7206606 1
0.1%
ValueCountFrequency (%)
126.9811244 1
0.1%
126.9799151 1
0.1%
126.9783542 1
0.1%
126.9772315 1
0.1%
126.9768057 1
0.1%
126.9766961 1
0.1%
126.9760309 1
0.1%
126.9757991 1
0.1%
126.9747911 2
0.2%
126.9739938 1
0.1%

보여지는레벨
Real number (ℝ)

Distinct9
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.878764
Minimum11
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-03-23T06:21:57.364464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile14
Q116
median17
Q318
95-th percentile19
Maximum19
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7533136
Coefficient of variation (CV)0.1038769
Kurtosis0.055659054
Mean16.878764
Median Absolute Deviation (MAD)1
Skewness-0.65265886
Sum21301
Variance3.0741085
MonotonicityNot monotonic
2024-03-23T06:21:57.834340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
17 363
28.8%
19 311
24.6%
16 165
13.1%
15 149
11.8%
18 146
11.6%
14 85
 
6.7%
12 19
 
1.5%
13 18
 
1.4%
11 6
 
0.5%
ValueCountFrequency (%)
11 6
 
0.5%
12 19
 
1.5%
13 18
 
1.4%
14 85
 
6.7%
15 149
11.8%
16 165
13.1%
17 363
28.8%
18 146
11.6%
19 311
24.6%
ValueCountFrequency (%)
19 311
24.6%
18 146
11.6%
17 363
28.8%
16 165
13.1%
15 149
11.8%
14 85
 
6.7%
13 18
 
1.4%
12 19
 
1.5%
11 6
 
0.5%

사진장수(최대5장)
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.87242472
Minimum0
Maximum5
Zeros912
Zeros (%)72.3%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-03-23T06:21:58.417219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.5771114
Coefficient of variation (CV)1.8077335
Kurtosis0.67142977
Mean0.87242472
Median Absolute Deviation (MAD)0
Skewness1.5121414
Sum1101
Variance2.4872802
MonotonicityNot monotonic
2024-03-23T06:21:58.968599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 912
72.3%
4 112
 
8.9%
3 93
 
7.4%
1 75
 
5.9%
5 53
 
4.2%
2 17
 
1.3%
ValueCountFrequency (%)
0 912
72.3%
1 75
 
5.9%
2 17
 
1.3%
3 93
 
7.4%
4 112
 
8.9%
5 53
 
4.2%
ValueCountFrequency (%)
5 53
 
4.2%
4 112
 
8.9%
3 93
 
7.4%
2 17
 
1.3%
1 75
 
5.9%
0 912
72.3%

해시태그
Categorical

IMBALANCE 

Distinct48
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
1017 
역사,동상
 
54
체험,가족,자연,이색체험
 
33
역사
 
30
체험,운동
 
21
Other values (43)
107 

Length

Max length16
Median length4
Mean length4.451664
Min length2

Unique

Unique29 ?
Unique (%)2.3%

Sample

1st row전시,체험,가족,데이트
2nd row역사,가족
3rd row역사,가족
4th row누리길,자연,산책
5th row누리길,자연,산책

Common Values

ValueCountFrequency (%)
<NA> 1017
80.6%
역사,동상 54
 
4.3%
체험,가족,자연,이색체험 33
 
2.6%
역사 30
 
2.4%
체험,운동 21
 
1.7%
역사,가족 13
 
1.0%
자연,가족 12
 
1.0%
종교 12
 
1.0%
운동,가족,체험 8
 
0.6%
전시,체험,가족 8
 
0.6%
Other values (38) 54
 
4.3%

Length

2024-03-23T06:21:59.455063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1017
80.6%
역사,동상 54
 
4.3%
체험,가족,자연,이색체험 33
 
2.6%
역사 30
 
2.4%
체험,운동 21
 
1.7%
역사,가족 13
 
1.0%
자연,가족 12
 
1.0%
종교 12
 
1.0%
전시,체험,가족 8
 
0.6%
운동,가족,체험 8
 
0.6%
Other values (38) 54
 
4.3%

Sample

번호(pid)카테고리명_한국어(ko)카테고리명_영어(en)카테고리명_중국어(cn)장소명_한국어(ko)장소명_영어(en)장소명_중국어(cn)주소_한국어(ko)주소_영어(en)주소_중국어(cn)설명_한국어(ko)설명_영어(en)설명_중국어(cn)필드제목_한국어(ko)필드제목_영어(en)필드제목_중국어(cn)필드내용_한국어(ko)필드내용_영어(en)필드내용_중국어(cn)위도(lat)경도(lng)보여지는레벨사진장수(최대5장)해시태그
01추천관광Recommended Tourist Spots推旅游킨텍스KINTEX展中心（KINTEX）경기도 고양시 일산서구 킨텍스로 217-60(대화동)217-60, Kintex-ro, Ilsanseo-gu, Goyang-si, Gyeonggi-do217-60, Kintex-ro, Ilsanseo-gu, Goyang-si, Gyeonggi-do대한민국 대표 전시장 킨텍스는 국내 최대 규모로 국내 12개 전시장 총면적의 41%를 차지하고 있습니다. 서울모토쇼 등 5대 메이저 전시회를 성공적으로 개최한 바 있으며 국내유일 대규모 국제 전시가 가능한 전시장으로 세계 수준의 전시컨벤션 문화공간입니다.KINTEX is one of the biggest convention centers in Korea that hosts and organizes international MICE events.展中心是代表性展，模之最，展、，是展目的代表所。["홈페이지#weblink","시설안내","w","h","name_display"]["Website#weblink","Information","w","h","name_display"]["Website#weblink","Information","w","h","name_display"]["http://www.kintex.com/","전시홀 : 총 10개홀 전용 주차장 4,000대, 임시 주차장 4,000대 회의실 : 중회의실 25개, 대회의실 12개 부대시설 : 식음시설 및 농협중앙회 킨텍스점 등 편의시설 제공","75","45","true"]["http://www.kintex.com/","Exhibition hall: 4,000 parking spaces for customers at 10 halls only; Temporary parking space for 4,000 vehicles / Conference rooms: 25 medium & 12 large / Amenities: F&B, NH KINTEX branch, etc.","75","45","true"]["http://www.kintex.com","展：共10，用停有4000位，停有4000位，室：中型室25、大型室12 附施：提供餐施及中央展中心店等便利施","75","45","true"]37.669307126.745684124전시,체험,가족,데이트
12추천관광Recommended Tourist Spots推旅游세계문화유산 서오릉Seooreung Royal Tombs (World Heritage Site)世界文化西五陵경기도 고양시 덕양구 서오릉로 334-92(용두동)334-92, Seooreung-ro, Deogyang-gu, Goyang-si, Gyeonggi-do334-92, Seooreung-ro, Deogyang-gu, Goyang-si, Gyeonggi-do서오릉이란 조선왕조의 다섯 능 즉 경릉(敬陵,덕종과 소혜왕후의 능), 창릉(昌陵, 예종과 계비 안순왕후의 능), 익릉(翼陵, 숙종의 원비인 인경왕후의 능), 명릉(明陵, 숙종과 인현왕후, 인원왕후의 능), 홍릉(弘陵, 정성왕후의 능)이 이곳에 모여 있어서 일컫는 명칭이다. 서오릉 지역이 왕실묘역으로 선택된 이유는 세조 3년(1457)에 세자 장(덕종)이 사망하자, 풍수지리설에 의해 경릉을 쓰고부터이다. 서오릉에는 이 5개의 능 외에도 조선왕조 최초의 ‘원’으로 명종의 첫째 아들인 순회세자의 무덤인 순창원과 숙종의 추궁으로 많은 역사적 일화를 남긴 희빈 장씨의 대빈묘가 있다. 서오릉은 동구릉 다음으로 큰 면적의 조선왕조 왕실의 가족무덤이며 고양시청에서 서울시 은평구 갈현동으로 이어진 55번 지방도로변에 위치하고 있다.Seooreung Royal Tombs, a cluster of five Joseon-era tombs, is the second largest tomb site after Donggureung Royal Tombs.西五陵是面次于九陵的朝王朝王室的家族墓地，因朝王朝的五座陵墓聚集于此而得名。["홈페이지#weblink"," 지정번호 ","이용시간","w","h","name_display"]["Website#weblink","Designation","Hours","w","h","name_display"]["Website#weblink","Designation","Hours","w","h","name_display"]["https://royaltombs.cha.go.kr/html/HtmlPage.dopg=/new/html/portal_01_10_01.jsp&mn=RT_01_10","사적 제198호","3~10월 06:00~18:30 11~2월 06:30~17:30 (매주 월요일 휴무)","60","60","true"]["royaltombs.cha.go.kr/html/HtmlPage.dopg=/new/html/portal_01_10_01.jsp&mn=RT_01_10","Historic Site No.198","6AM6:30PM (MarOct); 6:30AM5:30PM (NovFeb) (Closed Mon)","60","60","true"]["https://royaltombs.cha.go.kr/html/HtmlPage.dopg=/new/html/portal_01_10_01.jsp&mn=RT_01_10","史迹第198\r\n","3月~10月06:00~18:30 11月~2月06:30~17:30（每周一休息）","60","60","TRUE"]37.625658126.898636114역사,가족
23추천관광Recommended Tourist Spots推旅游세계문화유산 서삼릉/서삼릉태실Seosamneung Royal Tombs & Placenta Chamber世界文化西三陵/西三陵胎室경기도 고양시 덕양구 서삼릉길 233-126(원당동)233-126, Seosamneung-gil, Deogyang-gu, Goyang-si, Gyeonggi-do233-126, Seosamneung-gil, Deogyang-gu, Goyang-si, Gyeonggi-do서삼릉이란 고양시 원당동에 소재한 孝陵, 禧陵, 睿陵을 아울러 일컫는 말이다. 총 면적은 약 7만여 평이며 중종의 계비인 章敬王后 尹氏의 희릉자리로 택해지면서 처음 능자리로 사용되었다. 본래는 130여만여평에 이르는 광대한 면적을 차지하였으나 지금은 여러 곳으로 분할되어 약 7만여 평이 남았으며 이 중 절반가량이 비공개 지역으로 지정되어 있다. 이곳에는 3기의 능 이외에도 태실, 공주·옹주묘, 소경원, 효창원 등이 있다.Seosamneung Royal Tombs is a cluster of three Joseon-era tombs, which are located in Wondang-dong, Goyang. It was first used as a tomb of Queen Janggyeong, the second wife of King Jungjong. Besides the three tombs, there is a placenta chamber of the prince as well as the tombs of royal princesses and daughters of concubines along with Hyochangwon of Crown Prince Munhyo and Sogyeongwon of Crown Prince Sohyeon.西三陵是指位于高市元堂洞的三座陵墓。其首次作陵地使用是在被中宗妃章敬王后尹氏的禧陵所在地后。除了三座陵墓之外，里有胎室、公主和翁主墓、昭、孝昌等。[" 지정번호 ","이용시간","w","h","name_display","서삼릉","희릉","효릉","예릉"]["Designation","Hours","w","h","name_display","Seosamneung Royal Tombs","Huireung","Hyoreung","Yereung"]["Designation","Hours","w","h","name_display","Seosamneung Royal Tombs","Huireung","Hyoreung","Yereung"]["사적 제200호","3~10월 06:00~18:30 11~2월 06:30~17:30 (매주 월요일 휴무)","60","60","true","중종의 계비 장경왕후 윤씨의 희릉을 조성하면서 서삼릉의 역사가 시작됨. 중종의 정릉이 조성되었으나 서울 삼성동 선릉 곁으로 옮겨갔고, 중종의 아들인 인종과 비 인성왕후 박씨의 효릉, 철종과 비 철인왕후 김씨의 예릉이 있다. 그밖에 소경원 의령원 효창원 등 세자의 園 3기와 폐비 윤씨의 회묘를 비롯한 45기의 묘가 조성되어 있다.","11대 중종의 계비 장경왕후 윤씨(1491~1515,25)의 단릉이다. 영돈녕부사 윤여필의 딸로 8세 때 어머니를 여의고 월산대군의 부인 박씨에 의하여 양육되었다. 중종반정으로 단경왕후 신씨가 폐위되자 왕비에 책봉되었다. 1515년 인종을 낳고 산후병을 얻어 7일 만에 사망하였다. 능은 원래 헌릉(서울 서초동)에 있었으나 22년 뒤 김안로의 술책(정광필, 남곤 등이 조성한 묘자리에 큰 돌이 깔려있어서 좋지 않다는) 때문에 지금의 자리로 이장했다.","12대 인종(1515~1545,31)과 인성왕후 박씨(1514~1577,64)의 쌍릉이다. 인종은 효성이 지극하여 어머니인 장경왕후가 죽자 대왕대비인 정현왕후 윤씨(제9대 성종의 계비)를 더욱 섬겼으며, 아버지인 중종이 위독하자 반드시 먼저 약의 맛을 보고, 겨울철인데도 목욕하고 분향하며 한데 서서 저녁부터 새벽까지 하늘에 빌 정도 였다. 중종이 죽자 8개월만에 승하하였는데 부모의 곁에 묻어줄 것과 장사를 소박하게 해달라고 부탁하였다. 그래서일까 그의 능은 원래 병풍석이 없다가 인성왕후가 승하한 후 인종 곁에 묻히면서 현재 왕릉에서 볼 수 있는 병풍석을 둘렀다고 한다.","25대 철종(1831~1863,33)과 철인왕후 김씨(1837~1878,42)의 쌍릉이다. ‘강화도령’으로 널리 알려진 철종은 강화도에 살던 중 1848년 24대 헌종이 후사 없이 승하하자 뒤를 이어 왕위에 올랐다. 당시 영조의 유일한 혈손이었기 때문이다. 철종의 조부인 은언군은 그 아들 상계군 담이 반역을 꾀했다고["Historic Site No.200","6AM6:30PM (MarOct); 6:30AM5:30PM (NovFeb) (Closed Mon)","60","60","true","The history of the Seosamneung Royal Tombs begins with Huineung of Queen Janggyeong, the second wife of King Jungjong. Later, Jeongneung of King Jungjong was built and transported next to the Seolleung Royal Tomb in Samseong-dong, Seoul. There are also Hyoneung of King Injong and Queen Inseong, and Yeneung of King Cheoljong and Queen Cheorin. Plus, there are a total of 45 tombs including of Hyochangwon of Crown Prince Munhyo, Sogyeongwon of Crown Prince Sohyeon, and Uiryeongwon of Crown Prince Uiso.","Danneung is the tomb of Queen Janggyeong (14911515; aged 25), the second wife of King Jungjong, the 11th ruler of Joseon. Her father, Yun Yeo-pil was a member of the Papyeong Yun clan (Donnyeongbu: Office of Royal Relatives) and her mother died at the age of 8. So she was raised by her maternal aunt, Grand Princess Consort Seungpyeong of the Suncheon Park clan. After Queen Dangyeong was deposed due to Jungjong-banj["史迹第200","3月~10月06:00~18:30 11月~2月06:30~17:30（每周一休息）\r\n","60","60","TRUE","中宗妃章敬王后尹氏的禧陵建成后，西三陵的史由此始。中宗的靖陵然建成，但至首三成洞宣陵旁，有中宗的子仁宗和仁王后朴氏的孝陵、哲宗和哲仁王后金氏的睿陵。此外，建有昭、懿、孝昌等三座世子的墓以及包括妃尹氏的墓在的45座墓。","是第11代王中宗的妃庄敬王后尹氏（1491~1515，25）的人陵墓。是敦府事尹汝弼的女，8失去母，由月山大君的妻子朴某。由于中宗反正，端敬王后氏被，其被封王妃。1515年下仁宗，后生病，于7天后去世。陵墓原先位于陵（首瑞草洞），但22年后，因金安老策（因光弼、南等建造的墓地上有大石，地理位置不好），所以被移葬到了在的位置","是第12代王仁宗（1515~1545，31）和仁王后朴氏（1514~1577，64）合葬的人陵墓。仁宗非常孝，母章敬王后去世后，更加心侍奉大王大妃王后尹氏（第9代王成宗的妃）。父中宗病危后，一定要自己先味，在冬季也洗香，站着傍祈到凌晨。中宗去世后，他隔8月崩，拜托其埋葬在父母身，葬。也正因如此，他的陵墓原有石，仁王后死后埋葬在仁宗身，上了在在王陵中可以看到的石。","是第25代王哲宗（1831~1863，33）和哲仁王后金氏（1837~1878，42）合葬的人陵墓。被‘江公子’而人知的哲宗生活在江，第24代王宗无后，1848年崩后，哲宗位登上王位。因他是唯一一有英祖血的子。因其子常溪君李湛反，哲宗的祖父恩彦君于1786年被流放到江。1801年，因是天主徒，恩彦君的妻子宋某和申某也被死。再加上哲宗的兄元因反被而被死，所以哲宗周的人大部分都死了。就上王的哲宗生活，于在位14年去世睿陵是哲宗和哲仁王后合葬的人陵墓，是按照朝王朝常制度修建的最后一座陵墓。"]37.663663126.867973114역사,가족
34고양누리길Goyang Course高世界路고양북한산누리길Goyang Bukhansan Trail高北山世界路경기도 고양시 덕양구 효자동Hyoja-dong, Deogyang-gu, Goyang-si,Gyeonggi-doHyoja-dong, Deogyang-gu, Goyang-si,Gyeonggi-do고양시 최고봉! 북한산을 품고 걷는 역사의 길! 북한산둘레길 중 내시묘역길에서 충의길로 이어지는 코스이다. 국내 최대 내시묘가 위치한 내시묘역길은 오르막이 전혀 없고 호젓한 시골길을 거니는 듯 조용하고 맑은 공기를 마시며 산책할 수 있는 길이다. 효자길, 백운대, 인수봉 등 고양시 관할 명봉들이 한눈에 보이는 충의길까지 다양한 스토리텔링과 아름다운 풍경을 간직한 고양시의 아름다운 숲길이다.This is the same course as Chungui-gil, Hyoja-gil, and Naesimyoyeok-gil, and it does not have any specific indicators.北山世界路北山步道中的忠路、孝子路、侍墓域路相同，有行置高世界路的。["홈페이지","코스안내"]["Website","Course"]["Website","Course"]["https://nuri.goyang.go.kr/","거리 : 총 6.97km 시간 : 약 2시간 20분 코스 : 고양시계 ▶ 사기막골삼거리 ▶ 효자비입구 ▶ 북한산성탐방지원센터 ▶ 북한산입구"]["nuri.goyang.go.kr","Distance: 6.97km / Duration: 2 hr 20 min / Course: Goyangsigye ▶ Sagimakgol Samgeori ▶ Hyojabi Entrace ▶ Bukhansan Tourist Information Center ▶ Bukhansan Mountain Entrance"]["https://nuri.goyang.go.kr/","距：6.97公里 ：2小20分 路：高▶沙器幕谷三路口▶孝子碑入口▶北山城探支援中心▶北山入口"]37.651746126.920556153누리길,자연,산책
45고양누리길Goyang Course高世界路고양한북누리길Goyang Hanbuk Trail高北世界路경기도 고양시 덕양구 오금동Ogeum-dong, Deogyang-gu, Goyang-si,Gyeonggi-doOgeum-dong, Deogyang-gu, Goyang-si,Gyeonggi-do한북정맥의 기운을 느낄 수 있는 숲속 오솔길! 한북정맥의 산줄기로 북한산 효자계곡에서 발원하여 한강까지 흐르는 창릉천을 따라 고즈넉한 마을길이 열리고, 고양시 최초의 북한산 일대 유일한 온천이 손님들을 맞고 있다. 스님들이 넘나들었다는 중고개를 너머 하늘에서 선녀가 내려왔다는 옥녀봉에 숨 가쁘게 오르면 북한산의 장엄한 비경에 또 한번 놀란다. 걷는 내내 단풍이 아름다운 복자기나무와 참나무 숲길은 마음속 깊은 곳까지 힐링의 연속이다.This course starts at Sagokgyo Bridge, and passes through the Changneung Stream, Bukhansan Hot Springs and Ogeum Sangchon Park, finally arriving at Samsong Station.一路段昌陵川寺谷始，北山泉和梧琴上村公，到三松站。["홈페이지","코스안내"]["Website","Course"]["Website","Course"]["https://nuri.goyang.go.kr/","거리 : 6.5km 시간 : 2시간 10분 코스 : 북한산부근 ▶ 북한산온천 ▶ 옥녀봉 ▶ 오금상촌공원 ▶ 오동나무쉼터 ▶ 여석정 ▶ 등산로입구 ▶ 삼송역"]["nuri.goyang.go.kr","Distance: 6.5 km / Duration: 2 hr 10 min / Course: Bukhansan Mountain ▶ Bukhansan Hot Spring ▶ Oknyeobong Peak ▶ Ogeum Sangchon Park▶ Odong Namu Shelter ▶ Yeoseokjeong Pavilion ▶ Trail Entrance ▶ Samsong Station"]["https://nuri.goyang.go.kr/","距：6.5公里 ：2小10分 路：北山附近▶北山泉▶玉女峰▶梧琴上村公▶梧桐休息▶石亭▶登山路入口▶三松站"]37.66532126.905139153누리길,자연,산책
56고양누리길Goyang Course高世界路고양서삼릉누리길Goyang Seosamneung Trail高西三陵世界路경기도 고양시 덕양구 성사동Seongsa-dong, Deogyang-gu, Goyang-si,Gyeonggi-doSeongsa-dong, Deogyang-gu, Goyang-si,Gyeonggi-do연인과 함께 걷고 싶은 아름다운 길! 한적한 산길을 걷는 평화로움과 세계문화유산 서삼릉을 답사하는 체험학습도 겸할 수 있다. 원당역 인근 행주기씨 제실 앞을 지나면 서삼릉으로 이어지는 아름다운 숲길이 나오고 넓고 평평한 서삼릉 진입로가 나온다. 솔개약수터에서 시원한 약수 한잔 마시고 한북정맥 산길에 오르면 푸근한 숲길이 시작된다.This course starts at Samsong Station, passing through Seosamneung Royal Tombs and Let’s Run Farm, and arriving at Wondang Station.一三松站到元堂站的路，西三陵和Let’s Run Farm元堂。["홈페이지","코스안내"]["Website","Course"]["Website","Course"]["https://nuri.goyang.go.kr/","거리 : 8.28km 시간 : 2시간 15분 코스 : 삼송역 ▶ 솔개약수터 ▶ 서삼릉,원당종마목장,농협대학 ▶ 한국스카우트연맹 중앙훈련원 ▶ 수역이마을먹거리촌 ▶ 원당역"]["nuri.goyang.go.kr","Distance: 8.28 km / Duration: 2 hr 15 min / Course: Samsong Station ▶ Solgae Mineral Spring ▶ Seosamneung Royal Tombs, Let's Run Farm, NongHyup University ▶ Korea Scout Association Training Center ▶ Suyeogi Village Food Village ▶ Wondang Station"]["https://nuri.goyang.go.kr/","距：8.28公里 ：2小15分 路：三松站▶老泉▶西三陵、元堂牧、大▶童子盟中央院▶水逆村美食村▶元堂站"]37.649193126.847785153누리길,역사,산책
67고양누리길Goyang Course高世界路고양행주누리길Goyang Haengju Trail高幸州世界路경기도 고양시 덕양구 성사동Seongsa-dong, Deogyang-gu, Goyang-si,Gyeonggi-doSeongsa-dong, Deogyang-gu, Goyang-si,Gyeonggi-do산, 들, 하천이 이어지는 낭만의 길! 숲길과 물길, 도시와 농촌이 이어지는 아름다운 길이다. 성라공원 숲을 지나 성사천 물길을 따라가면 임진왜란의 3대 첩지인 행주산성과 고양시에서 가장 오래된 다리인 강매석교 등 다양한 명소들이 걷기의 여정을 풍성하게 한다. 11.9km에 이르는 다소 긴 길이지만 행주산성에 담긴 역사 이야기까지 고루 담아볼 수 있는 길이다.If you walk through Seongna Park along the Seongsacheon Stream, you will encounter Haengjusanseong Fortress, one of the three major Korean victories against the enemy during the Imjin War, and Gangmaeseokgyo, the oldest stone bridge in Goyang.穿星公的林，沿着星沙川走，就能看到壬辰倭三大捷地之一的幸州山城和高市史最悠久的江梅石。["홈페이지","코스안내"]["Website","Course"]["Website","Course"]["https://nuri.goyang.go.kr/","거리 : 11.9 Km 시간 : 3시간 20분 코스 : 원당역 ▶ 성라공원(국사봉) ▶ 배다골테마파크 ▶ 성사천 ▶ 강매동(봉대산) ▶ 강매석교 ▶ 행주산성"]["nuri.goyang.go.kr","Distance : 11.9 km / Duration : 3 hr 20 min / Course: Wondang Station ▶ Seongna Park (Guksabong Peak) ▶ Baedagol Theme Park ▶ Seongsacheon Stream ▶ Gangmae-dong (Bongdaesan Mountain) ▶ Gangmaeseokgyo Stone Bridge ▶ Haengjusanseong Fortress"]["https://nuri.goyang.go.kr/","距：11.9公里 ：3小20分 路：元堂站▶星公（峰）▶Baedagol主公▶星沙川▶江梅洞（峰台山）▶江梅石▶幸州山城"]37.649193126.847785153누리길,산책,자연
78고양누리길Goyang Course高世界路고양행주산성역사누리길Goyang Hangjusanseong History Trail高幸州山城史世界路경기도 고양시 덕양구 행주내동Haengjunae-dong, Deogyang-gu, Goyang-si,Gyeonggi-doHaengjunae-dong, Deogyang-gu, Goyang-si,Gyeonggi-do가족과 함께 걷고 싶은 사랑나눔 길! 대첩문에서 출발해 충장사, 충의정, 대첩비, 진강정, 팔각초소전망대, 고양시정연수원(인재개발원)을 거쳐 다시 대첩문으로 돌아오는 순환코스이다. 분단 반세기만에 일반인에게 공개된 한강변 철책선의 아름다운 오솔길과 한강의 풍광을 직접 경험할 수 있다.SBS방송 <잘 먹고 잘 사는 법, 식사하셨어요> 촬영지로 더욱 유명하다. [출연진 : 요리연구가 임지호, 영화배우 김수로, 소녀시대 유리]This is a circular course starting and coming back to Daecheopmun Gate passing through Chungjangsa Temple, Chunguijeong Pavilion, Memorial Stone, Jingangjeong Pavilion, Octagonal Post Observatory, and Goyang HR Development Center.是一，大捷出，忠寺、忠亭、大捷碑、江亭、八角哨所瞭望台、高人才院，重新回到大捷。["홈페이지","코스안내"]["Website","Course"]["Website","Course"]["https://nuri.goyang.go.kr/","거리 : 3.7km 시간 : 1시간 30분 코스 : 대첩문 ▶충의정 ▶ 대첩비 ▶ 진강정 ▶ 팔각초소 전망대 ▶ 고양시정연수원(인재개발원) ▶ 대첩문"]["nuri.goyang.go.kr","Distance: 3.7 km / Duration: 1 hr 30 min / Course: Daecheopmun Gate ▶ Chunguijeong Pavilion ▶ Memorial Stone ▶ Jingangjeong Pavilion ▶ Octagonal Post Observatory ▶ Goyang HR Development Center ▶ Daecheopmun Gate"]["https://nuri.goyang.go.kr/","距：3.7公里 ：1小30分 路：大捷▶忠亭▶大捷碑▶江亭▶八角哨所瞭望台▶高市政修院（人才院）▶大捷"]37.603791126.827053153누리길,역사,산책,자연
89고양누리길Goyang Course高世界路고양고봉누리길Goyang Gobong Trail高高峰世界路경기도 고양시 일산동구 중산동Jungsan-dong, Ilsandong-gu, Goyang-si,Gyeonggi-doJungsan-dong, Ilsandong-gu, Goyang-si,Gyeonggi-do<전국 10대 아름다운 숲길>에 빛나는 이야기 길! 고봉산을 넘어 황룡산까지, 나지막한 두 산을 넘는 길이다. 자연의 보고인 안곡습지공원을 지나면 깔끔하게 정리된 숲속공연장이 나오고 고봉산 등산로가 시작된다. 산으로 오르는 길에 만경사, 영천사 등 오래된 사찰을 둘러볼 수 있고 고봉산 정상을 넘어 큰 도로를 건너면 황룡산이다. 고려 명장 박서장군과 조선 충신 박순선생을 모신 용강서원을 지나면 시골정취 가득한 상감천마을이 나온다.This is a course for hiking from Gobongsan Mountain to Hwangnyongsan Mountain. You can visit old shrines, such as Mangyeongsa and Yeongcheonsa Temples on your way up. You can reach Hwangnyongsan Mountain after hiking Gobongsan Mountain and crossing a big path.越高峰山到山，路要越座低矮的山。在上山的路上可以游万景寺、泉寺等古老的寺，越高峰山山，穿大路就是山。["홈페이지","코스안내"]["Website","Course"]["Website","Course"]["https://nuri.goyang.go.kr/","거리 : 6.72km 시간 : 2시간 30분 코스 : 안곡초등학교 ▶ 안곡습지공원 ▶ 안동장씨모역(장희빈가족묘역) ▶ 만경사 ▶ 영천사 ▶ 금정굴 ▶ 용강서원 ▶ 상감천마을"]["nuri.goyang.go.kr","Distance: 6.72 km / Duration: 2 hr 30 min / Course: Angok Elementary School ▶ Angok Wetland Park ▶ Tomb of Jang Huibin & Family ▶ Mangyeongsa Temple ▶ Yeongcheonsa Temple ▶ Geumjeong Cave ▶ Yonggangseowon Confucian Academy ▶ Sanggamcheon Village"]["https://nuri.goyang.go.kr/","距：6.72公里 ：2小30分 路：安谷小▶安谷地公▶安氏墓地（禧家族墓地）▶万景寺▶泉寺▶金井窟▶江院▶上甘川村"]37.685527126.78398153누리길,자연,산책
910고양누리길Goyang Course高世界路고양송강누리길Goyang Songgang Trail高松江世界路경기도 고양시 일산동구 사리현동Sarihyeon-dong, Ilsandong-gu, Goyang-si,Gyeonggi-doSarihyeon-dong, Ilsandong-gu, Goyang-si,Gyeonggi-do풍광이 아름다운 하천변 메타세콰이어 길! 북한산과 어우러진 풍경이 장관인 공릉천 물줄기를 따라 걷는 평화로운 길이다. 쥬라리움에서 출발해 공릉천 원당교를 지나면 아름드리 메타세쿼이아가 장관을 이루는 가로수길을 걸을 수 있다. 공릉천 물길과 전원마을을 따라 걷다보면 조선조 가사문학의 대가 송강정철 선생이 시를 지었던 송강마을과 월산대군사당을 볼 수 있다When you walk along the Gongneungcheon Stream and Jeonwon Village, you can visit Songgang Village where Songgang Jeong Cheol wrote poems.沿着恭陵川和田村走，可以看到松江澈先生作的松江村和月山大君祠堂。["홈페이지","코스안내"]["Website","Course"]["Website","Course"]["https://nuri.goyang.go.kr/","거리 : 6.6km 시간 : 1시간 40분 코스 : 쥬라리움 ▶ 원당교 ▶ 메타세콰이어길 ▶ 송강문학관 ▶ 월산대군사당"]["nuri.goyang.go.kr","Distance: 6.6 km / Duration: 1 hr 40 min / Course: Zoorarium ▶ Wondanggyo Bridge ▶ Metasequoia Road ▶ Songgang Literature House▶ Shrine of Grand Prince Wolsan"]["https://nuri.goyang.go.kr/","距：6.6公里 ：小40分 路：Zoorarium▶元堂▶水杉道▶松江文▶月山大君祠堂"]37.693891126.839838153누리길,산책,자연
번호(pid)카테고리명_한국어(ko)카테고리명_영어(en)카테고리명_중국어(cn)장소명_한국어(ko)장소명_영어(en)장소명_중국어(cn)주소_한국어(ko)주소_영어(en)주소_중국어(cn)설명_한국어(ko)설명_영어(en)설명_중국어(cn)필드제목_한국어(ko)필드제목_영어(en)필드제목_중국어(cn)필드내용_한국어(ko)필드내용_영어(en)필드내용_중국어(cn)위도(lat)경도(lng)보여지는레벨사진장수(최대5장)해시태그
12522008착한가격업소<NA><NA>맛있는집<NA><NA>일산서구 중앙로 1388, 403호(주엽동)<NA><NA><NA><NA><NA>["메뉴","대표자"]<NA><NA>["한식","김금순"]<NA><NA>37.668444126.765506180<NA>
12532009착한가격업소<NA><NA>삼송순대국<NA><NA>덕양구 삼송로193번길 1-2<NA><NA><NA><NA><NA>["메뉴","대표자"]<NA><NA>["한식","김자영"]<NA><NA>37.653983126.895311170<NA>
12542010착한가격업소<NA><NA>정병장부대찌개<NA><NA>일산서구 강성로 115, 금강주차빌딩 121호 (주엽동)<NA><NA><NA><NA><NA>["메뉴","대표자"]<NA><NA>["한식","정태영"]<NA><NA>37.67024126.762877180<NA>
12552011착한가격업소<NA><NA>먹거리횟집<NA><NA>일산동구 백석로108번길 6-14 (백석동)<NA><NA><NA><NA><NA>["메뉴","대표자"]<NA><NA>["한식","선미향"]<NA><NA>37.648583126.788603170<NA>
12562012착한가격업소<NA><NA>후s돈<NA><NA>덕양구 마상로140번길 81(주교동)<NA><NA><NA><NA><NA>["메뉴","대표자"]<NA><NA>["한식","류후남"]<NA><NA>37.656333126.835147180<NA>
12572013고양명소Goyang Attractions高名킨텍스 2전시장KINTEX 2展中心第二展고양시 일산서구 한류월드로 408 킨텍스217-60, Kintex-ro, Ilsanseo-gu, Goyang-si, Gyeonggi-do217-60, Kintex-ro, Ilsanseo-gu, Goyang-si, Gyeonggi-do대한민국 대표 전시장 킨텍스는 국내 최대 규모로 국내 12개 전시장 총면적의 41%를 차지하고 있습니다. 서울모토쇼 등 5대 메이저 전시회를 성공적으로 개최한바 있으며 국내유일 대규모 국제 전시가 가능한 전시장으로 세계 수준의 전시컨벤션 문화공간입니다.KINTEX is one of the biggest convention centers in Korea that hosts and organizes international MICE events.展中心是代表性展，模之最，展、，是展目的代表所。["홈페이지#weblink","시설안내","w","h","name_display"]["Website#weblink","Information","w","h","name_display"]["Website#weblink","Information","w","h","name_display"]["http://www.kintex.com/","전시홀 : 총 10개홀 전용 주차장 4,000대, 임시 주차장 4,000대 회의실 : 중회의실 25개, 대회의실 12개 부대시설 : 식음시설 및 농협중앙회 킨텍스점 등 편의시설 제공","75","75","true"]["kintex.com","Exhibition hall: 4,000 parking spaces for customers at 10 halls only; Temporary parking space for 4,000 vehicles / Conference rooms: 25 medium & 12 large / Amenities: F&B, NH KINTEX branch, etc.","75","75","TRUE"]["http://www.kintex.com/\r\n","展：共10，用停有4000位，停有4000位，室：中型室25、大型室12 附施：提供餐施及中央展中心店等便利施","75","75","true"]37.664849126.741454144<NA>
12582014바탕<NA><NA>토당문화플랫폼<NA><NA>고양시 덕양구 토당로 61<NA><NA><NA><NA><NA>["w","h","name_display"]<NA><NA>["60","45","true"]<NA><NA>37.620752126.819077130<NA>
12592015백화점/쇼핑몰Department Stores / Shopping Centers百商店、物中心벨라시타Bella CitaBellacitta경기도 고양시 일산동구 강송로 3333, Gangsong-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do33, Gangsong-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do<NA><NA><NA><NA><NA><NA><NA><NA><NA>37.642185126.791815150<NA>
12602016바탕<NA><NA>비석거리와 느티나무<NA><NA><NA><NA><NA><NA><NA><NA>["w","h","name_display"]<NA><NA>["50","50","false"]<NA><NA>37.701849126.900464150<NA>
12612017바탕<NA><NA>은행나무<NA><NA><NA><NA><NA><NA><NA><NA>["w","h","name_display"]<NA><NA>["60","50","false"]<NA><NA>37.703414126.898127160<NA>