Overview

Dataset statistics

Number of variables16
Number of observations1556
Missing cells1335
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory194.6 KiB
Average record size in memory128.1 B

Variable types

Text15
DateTime1

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실) 각 기관에서 등록한 표준데이터를 취합하여 제공하기 때문에 갱신주기는 개별 파일마다 다릅니다.(기관에서 등록한 데이터를 취합한 것으로 개별 파일별 갱신시점이 다름)
Author지방자치단체
URLhttps://www.data.go.kr/data/15017321/standard.do

Alerts

시작지점도로명주소 has 515 (33.1%) missing valuesMissing
시작지점소재지지번주소 has 152 (9.8%) missing valuesMissing
종료지점소재지도로명주소 has 516 (33.2%) missing valuesMissing
종료지점소재지지번주소 has 152 (9.8%) missing valuesMissing

Reproduction

Analysis started2024-05-11 10:23:58.832628
Analysis finished2024-05-11 10:24:07.339477
Duration8.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

길명
Text

Distinct1308
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2024-05-11T10:24:07.883567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length23
Mean length9.9479434
Min length2

Characters and Unicode

Total characters15479
Distinct characters520
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1085 ?
Unique (%)69.7%

Sample

1st row원주굽이길 원11코스 다둔인벌길
2nd row원주굽이길 원12코스 북원역사길
3rd row원주굽이길 원13코스 무실과수원길
4th row해파랑길(제23구간)
5th row해파랑길(제24구간)
ValueCountFrequency (%)
경기둘레길 61
 
2.1%
원주굽이길 60
 
2.0%
41
 
1.4%
1코스 41
 
1.4%
2코스 41
 
1.4%
둘레길 37
 
1.3%
올레길 37
 
1.3%
바우길 34
 
1.2%
3코스 28
 
1.0%
제주 28
 
1.0%
Other values (1518) 2525
86.1%
2024-05-11T10:24:09.076712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1704
 
11.0%
1378
 
8.9%
582
 
3.8%
572
 
3.7%
445
 
2.9%
310
 
2.0%
( 303
 
2.0%
) 302
 
2.0%
1 294
 
1.9%
268
 
1.7%
Other values (510) 9321
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12278
79.3%
Space Separator 1378
 
8.9%
Decimal Number 1015
 
6.6%
Open Punctuation 304
 
2.0%
Close Punctuation 303
 
2.0%
Dash Punctuation 84
 
0.5%
Uppercase Letter 38
 
0.2%
Connector Punctuation 34
 
0.2%
Other Punctuation 24
 
0.2%
Math Symbol 13
 
0.1%
Other values (2) 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1704
 
13.9%
582
 
4.7%
572
 
4.7%
445
 
3.6%
310
 
2.5%
268
 
2.2%
241
 
2.0%
208
 
1.7%
159
 
1.3%
155
 
1.3%
Other values (473) 7634
62.2%
Decimal Number
ValueCountFrequency (%)
1 294
29.0%
2 166
16.4%
3 117
 
11.5%
4 100
 
9.9%
5 84
 
8.3%
0 65
 
6.4%
6 64
 
6.3%
7 53
 
5.2%
8 44
 
4.3%
9 28
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
A 13
34.2%
B 11
28.9%
D 3
 
7.9%
C 3
 
7.9%
T 2
 
5.3%
R 2
 
5.3%
Z 1
 
2.6%
M 1
 
2.6%
O 1
 
2.6%
I 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 15
62.5%
. 6
 
25.0%
/ 1
 
4.2%
· 1
 
4.2%
& 1
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 303
99.7%
1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 302
99.7%
1
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 11
84.6%
+ 2
 
15.4%
Lowercase Letter
ValueCountFrequency (%)
m 2
50.0%
k 2
50.0%
Space Separator
ValueCountFrequency (%)
1378
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 34
100.0%
Final Punctuation
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12277
79.3%
Common 3159
 
20.4%
Latin 42
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1704
 
13.9%
582
 
4.7%
572
 
4.7%
445
 
3.6%
310
 
2.5%
268
 
2.2%
241
 
2.0%
208
 
1.7%
159
 
1.3%
155
 
1.3%
Other values (472) 7633
62.2%
Common
ValueCountFrequency (%)
1378
43.6%
( 303
 
9.6%
) 302
 
9.6%
1 294
 
9.3%
2 166
 
5.3%
3 117
 
3.7%
4 100
 
3.2%
5 84
 
2.7%
- 84
 
2.7%
0 65
 
2.1%
Other values (15) 266
 
8.4%
Latin
ValueCountFrequency (%)
A 13
31.0%
B 11
26.2%
D 3
 
7.1%
C 3
 
7.1%
m 2
 
4.8%
T 2
 
4.8%
R 2
 
4.8%
k 2
 
4.8%
Z 1
 
2.4%
M 1
 
2.4%
Other values (2) 2
 
4.8%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12277
79.3%
ASCII 3194
 
20.6%
Punctuation 4
 
< 0.1%
None 3
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1704
 
13.9%
582
 
4.7%
572
 
4.7%
445
 
3.6%
310
 
2.5%
268
 
2.2%
241
 
2.0%
208
 
1.7%
159
 
1.3%
155
 
1.3%
Other values (472) 7633
62.2%
ASCII
ValueCountFrequency (%)
1378
43.1%
( 303
 
9.5%
) 302
 
9.5%
1 294
 
9.2%
2 166
 
5.2%
3 117
 
3.7%
4 100
 
3.1%
5 84
 
2.6%
- 84
 
2.6%
0 65
 
2.0%
Other values (23) 301
 
9.4%
Punctuation
ValueCountFrequency (%)
4
100.0%
None
ValueCountFrequency (%)
1
33.3%
1
33.3%
· 1
33.3%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct1193
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2024-05-11T10:24:10.015003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length522
Median length236
Mean length47.339332
Min length3

Characters and Unicode

Total characters73660
Distinct characters950
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1014 ?
Unique (%)65.2%

Sample

1st row원주의 수려한 자연경관과 문화·역사·생태 탐방 코스
2nd row원주의 수려한 자연경관과 문화·역사·생태 탐방 코스
3rd row원주의 수려한 자연경관과 문화·역사·생태 탐방 코스
4th row바다를 배경으로 어촌마을과 해변을 지나는 조용한 코스
5th row해안 도로를 따라 숲길과 갯벌, 백사장과 온천이 조성된 힐링 코스
ValueCountFrequency (%)
있는 355
 
2.1%
309
 
1.8%
272
 
1.6%
코스 184
 
1.1%
따라 132
 
0.8%
수려한 105
 
0.6%
탐방 96
 
0.6%
걷는 95
 
0.6%
자연경관과 89
 
0.5%
87
 
0.5%
Other values (7113) 15437
90.0%
2024-05-11T10:24:11.465620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15618
 
21.2%
1549
 
2.1%
1457
 
2.0%
1403
 
1.9%
1263
 
1.7%
1182
 
1.6%
962
 
1.3%
888
 
1.2%
816
 
1.1%
783
 
1.1%
Other values (940) 47739
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54744
74.3%
Space Separator 15620
 
21.2%
Other Punctuation 1527
 
2.1%
Decimal Number 989
 
1.3%
Lowercase Letter 183
 
0.2%
Math Symbol 163
 
0.2%
Open Punctuation 121
 
0.2%
Close Punctuation 120
 
0.2%
Uppercase Letter 67
 
0.1%
Connector Punctuation 35
 
< 0.1%
Other values (4) 91
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1549
 
2.8%
1457
 
2.7%
1403
 
2.6%
1263
 
2.3%
1182
 
2.2%
962
 
1.8%
888
 
1.6%
816
 
1.5%
783
 
1.4%
735
 
1.3%
Other values (872) 43706
79.8%
Uppercase Letter
ValueCountFrequency (%)
K 35
52.2%
S 5
 
7.5%
N 4
 
6.0%
P 3
 
4.5%
A 3
 
4.5%
E 3
 
4.5%
L 2
 
3.0%
D 2
 
3.0%
C 2
 
3.0%
M 2
 
3.0%
Other values (6) 6
 
9.0%
Other Punctuation
ValueCountFrequency (%)
. 669
43.8%
, 644
42.2%
· 175
 
11.5%
14
 
0.9%
: 10
 
0.7%
/ 5
 
0.3%
2
 
0.1%
* 2
 
0.1%
? 2
 
0.1%
2
 
0.1%
Other values (2) 2
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
m 129
70.5%
k 43
 
23.5%
c 2
 
1.1%
y 1
 
0.5%
u 1
 
0.5%
i 1
 
0.5%
n 1
 
0.5%
g 1
 
0.5%
w 1
 
0.5%
a 1
 
0.5%
Other values (2) 2
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 216
21.8%
0 192
19.4%
2 115
11.6%
4 99
10.0%
3 91
9.2%
5 82
 
8.3%
6 59
 
6.0%
8 57
 
5.8%
7 39
 
3.9%
9 39
 
3.9%
Math Symbol
ValueCountFrequency (%)
65
39.9%
~ 55
33.7%
+ 35
21.5%
> 4
 
2.5%
< 4
 
2.5%
Other Symbol
ValueCountFrequency (%)
16
80.0%
2
 
10.0%
2
 
10.0%
Space Separator
ValueCountFrequency (%)
15618
> 99.9%
  2
 
< 0.1%
Final Punctuation
ValueCountFrequency (%)
29
96.7%
1
 
3.3%
Initial Punctuation
ValueCountFrequency (%)
13
92.9%
1
 
7.1%
Open Punctuation
ValueCountFrequency (%)
( 121
100.0%
Close Punctuation
ValueCountFrequency (%)
) 120
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54687
74.2%
Common 18666
 
25.3%
Latin 250
 
0.3%
Han 57
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1549
 
2.8%
1457
 
2.7%
1403
 
2.6%
1263
 
2.3%
1182
 
2.2%
962
 
1.8%
888
 
1.6%
816
 
1.5%
783
 
1.4%
735
 
1.3%
Other values (852) 43649
79.8%
Common
ValueCountFrequency (%)
15618
83.7%
. 669
 
3.6%
, 644
 
3.5%
1 216
 
1.2%
0 192
 
1.0%
· 175
 
0.9%
( 121
 
0.6%
) 120
 
0.6%
2 115
 
0.6%
4 99
 
0.5%
Other values (30) 697
 
3.7%
Latin
ValueCountFrequency (%)
m 129
51.6%
k 43
 
17.2%
K 35
 
14.0%
S 5
 
2.0%
N 4
 
1.6%
P 3
 
1.2%
A 3
 
1.2%
E 3
 
1.2%
L 2
 
0.8%
D 2
 
0.8%
Other values (18) 21
 
8.4%
Han
ValueCountFrequency (%)
10
17.5%
10
17.5%
10
17.5%
10
17.5%
2
 
3.5%
1
 
1.8%
1
 
1.8%
1
 
1.8%
1
 
1.8%
1
 
1.8%
Other values (10) 10
17.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54687
74.2%
ASCII 18592
 
25.2%
None 195
 
0.3%
Arrows 65
 
0.1%
CJK 57
 
0.1%
Punctuation 44
 
0.1%
Geometric Shapes 16
 
< 0.1%
CJK Compat 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15618
84.0%
. 669
 
3.6%
, 644
 
3.5%
1 216
 
1.2%
0 192
 
1.0%
m 129
 
0.7%
( 121
 
0.7%
) 120
 
0.6%
2 115
 
0.6%
4 99
 
0.5%
Other values (45) 669
 
3.6%
Hangul
ValueCountFrequency (%)
1549
 
2.8%
1457
 
2.7%
1403
 
2.6%
1263
 
2.3%
1182
 
2.2%
962
 
1.8%
888
 
1.6%
816
 
1.5%
783
 
1.4%
735
 
1.3%
Other values (852) 43649
79.8%
None
ValueCountFrequency (%)
· 175
89.7%
14
 
7.2%
2
 
1.0%
2
 
1.0%
  2
 
1.0%
Arrows
ValueCountFrequency (%)
65
100.0%
Punctuation
ValueCountFrequency (%)
29
65.9%
13
29.5%
1
 
2.3%
1
 
2.3%
Geometric Shapes
ValueCountFrequency (%)
16
100.0%
CJK
ValueCountFrequency (%)
10
17.5%
10
17.5%
10
17.5%
10
17.5%
2
 
3.5%
1
 
1.8%
1
 
1.8%
1
 
1.8%
1
 
1.8%
1
 
1.8%
Other values (10) 10
17.5%
CJK Compat
ValueCountFrequency (%)
2
50.0%
2
50.0%
Distinct362
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2024-05-11T10:24:12.437689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length2.8020566
Min length1

Characters and Unicode

Total characters4360
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique153 ?
Unique (%)9.8%

Sample

1st row18.0
2nd row11.8
3rd row10.7
4th row11.9
5th row18.2
ValueCountFrequency (%)
10 41
 
2.6%
2 33
 
2.1%
3 33
 
2.1%
5 33
 
2.1%
4 31
 
2.0%
7 29
 
1.9%
11 29
 
1.9%
8 29
 
1.9%
13 27
 
1.7%
1.5 25
 
1.6%
Other values (352) 1246
80.1%
2024-05-11T10:24:14.083263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1004
23.0%
1 793
18.2%
2 400
 
9.2%
5 386
 
8.9%
3 378
 
8.7%
4 335
 
7.7%
7 251
 
5.8%
6 236
 
5.4%
8 229
 
5.3%
0 173
 
4.0%
Other values (2) 175
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3353
76.9%
Other Punctuation 1004
 
23.0%
Math Symbol 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 793
23.7%
2 400
11.9%
5 386
11.5%
3 378
11.3%
4 335
10.0%
7 251
 
7.5%
6 236
 
7.0%
8 229
 
6.8%
0 173
 
5.2%
9 172
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 1004
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4360
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1004
23.0%
1 793
18.2%
2 400
 
9.2%
5 386
 
8.9%
3 378
 
8.7%
4 335
 
7.7%
7 251
 
5.8%
6 236
 
5.4%
8 229
 
5.3%
0 173
 
4.0%
Other values (2) 175
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1004
23.0%
1 793
18.2%
2 400
 
9.2%
5 386
 
8.9%
3 378
 
8.7%
4 335
 
7.7%
7 251
 
5.8%
6 236
 
5.4%
8 229
 
5.3%
0 173
 
4.0%
Other values (2) 175
 
4.0%
Distinct313
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2024-05-11T10:24:14.918433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length29
Mean length4.4228792
Min length1

Characters and Unicode

Total characters6882
Distinct characters72
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique149 ?
Unique (%)9.6%

Sample

1st row4~5시간
2nd row3시간
3rd row3시간
4th row4
5th row6
ValueCountFrequency (%)
2시간 201
 
11.0%
1시간 162
 
8.9%
3시간 143
 
7.8%
4시간 122
 
6.7%
30분 119
 
6.5%
5시간 75
 
4.1%
6시간 57
 
3.1%
40분 56
 
3.1%
4~5시간 38
 
2.1%
3~4시간 34
 
1.9%
Other values (254) 819
44.9%
2024-05-11T10:24:16.230262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1264
18.4%
1263
18.4%
0 604
8.8%
566
8.2%
3 555
8.1%
2 451
 
6.6%
1 417
 
6.1%
5 370
 
5.4%
4 366
 
5.3%
270
 
3.9%
Other values (62) 756
11.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3219
46.8%
Decimal Number 3061
44.5%
Space Separator 270
 
3.9%
Other Punctuation 173
 
2.5%
Math Symbol 143
 
2.1%
Close Punctuation 6
 
0.1%
Open Punctuation 6
 
0.1%
Uppercase Letter 2
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1264
39.3%
1263
39.2%
566
17.6%
25
 
0.8%
10
 
0.3%
10
 
0.3%
7
 
0.2%
6
 
0.2%
5
 
0.2%
4
 
0.1%
Other values (43) 59
 
1.8%
Decimal Number
ValueCountFrequency (%)
0 604
19.7%
3 555
18.1%
2 451
14.7%
1 417
13.6%
5 370
12.1%
4 366
12.0%
6 150
 
4.9%
7 80
 
2.6%
8 48
 
1.6%
9 20
 
0.7%
Math Symbol
ValueCountFrequency (%)
~ 134
93.7%
+ 9
 
6.3%
Other Punctuation
ValueCountFrequency (%)
: 91
52.6%
. 82
47.4%
Space Separator
ValueCountFrequency (%)
270
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
H 2
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3661
53.2%
Hangul 3219
46.8%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1264
39.3%
1263
39.2%
566
17.6%
25
 
0.8%
10
 
0.3%
10
 
0.3%
7
 
0.2%
6
 
0.2%
5
 
0.2%
4
 
0.1%
Other values (43) 59
 
1.8%
Common
ValueCountFrequency (%)
0 604
16.5%
3 555
15.2%
2 451
12.3%
1 417
11.4%
5 370
10.1%
4 366
10.0%
270
7.4%
6 150
 
4.1%
~ 134
 
3.7%
: 91
 
2.5%
Other values (8) 253
6.9%
Latin
ValueCountFrequency (%)
H 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3661
53.2%
Hangul 3219
46.8%
CJK Compat 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1264
39.3%
1263
39.2%
566
17.6%
25
 
0.8%
10
 
0.3%
10
 
0.3%
7
 
0.2%
6
 
0.2%
5
 
0.2%
4
 
0.1%
Other values (43) 59
 
1.8%
ASCII
ValueCountFrequency (%)
0 604
16.5%
3 555
15.2%
2 451
12.3%
1 417
11.4%
5 370
10.1%
4 366
10.0%
270
7.4%
6 150
 
4.1%
~ 134
 
3.7%
: 91
 
2.5%
Other values (8) 253
6.9%
CJK Compat
ValueCountFrequency (%)
2
100.0%
Distinct1210
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2024-05-11T10:24:17.528033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length6.5134961
Min length2

Characters and Unicode

Total characters10135
Distinct characters527
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique929 ?
Unique (%)59.7%

Sample

1st row귀래면행정복지센터
2nd row원주역사박물관
3rd row종합경기장 삼거리
4th row고래불해변
5th row후포항
ValueCountFrequency (%)
주차장 46
 
2.2%
입구 27
 
1.3%
양양군 12
 
0.6%
8
 
0.4%
출구 7
 
0.3%
관광안내소 7
 
0.3%
강원도 6
 
0.3%
선착장 6
 
0.3%
마을회관 6
 
0.3%
6
 
0.3%
Other values (1438) 1918
93.6%
2024-05-11T10:24:19.229645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
495
 
4.9%
259
 
2.6%
226
 
2.2%
187
 
1.8%
179
 
1.8%
174
 
1.7%
170
 
1.7%
157
 
1.5%
156
 
1.5%
154
 
1.5%
Other values (517) 7978
78.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9297
91.7%
Space Separator 495
 
4.9%
Decimal Number 135
 
1.3%
Close Punctuation 84
 
0.8%
Open Punctuation 83
 
0.8%
Uppercase Letter 20
 
0.2%
Other Punctuation 17
 
0.2%
Math Symbol 2
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
259
 
2.8%
226
 
2.4%
187
 
2.0%
179
 
1.9%
174
 
1.9%
170
 
1.8%
157
 
1.7%
156
 
1.7%
154
 
1.7%
148
 
1.6%
Other values (488) 7487
80.5%
Decimal Number
ValueCountFrequency (%)
1 42
31.1%
2 25
18.5%
3 18
13.3%
4 12
 
8.9%
8 9
 
6.7%
5 8
 
5.9%
0 7
 
5.2%
6 6
 
4.4%
9 5
 
3.7%
7 3
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
C 4
20.0%
S 3
15.0%
N 2
10.0%
K 2
10.0%
G 2
10.0%
M 2
10.0%
T 2
10.0%
U 1
 
5.0%
D 1
 
5.0%
B 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/ 11
64.7%
. 3
 
17.6%
, 2
 
11.8%
& 1
 
5.9%
Space Separator
ValueCountFrequency (%)
495
100.0%
Close Punctuation
ValueCountFrequency (%)
) 84
100.0%
Open Punctuation
ValueCountFrequency (%)
( 83
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9296
91.7%
Common 818
 
8.1%
Latin 20
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
259
 
2.8%
226
 
2.4%
187
 
2.0%
179
 
1.9%
174
 
1.9%
170
 
1.8%
157
 
1.7%
156
 
1.7%
154
 
1.7%
148
 
1.6%
Other values (487) 7486
80.5%
Common
ValueCountFrequency (%)
495
60.5%
) 84
 
10.3%
( 83
 
10.1%
1 42
 
5.1%
2 25
 
3.1%
3 18
 
2.2%
4 12
 
1.5%
/ 11
 
1.3%
8 9
 
1.1%
5 8
 
1.0%
Other values (9) 31
 
3.8%
Latin
ValueCountFrequency (%)
C 4
20.0%
S 3
15.0%
N 2
10.0%
K 2
10.0%
G 2
10.0%
M 2
10.0%
T 2
10.0%
U 1
 
5.0%
D 1
 
5.0%
B 1
 
5.0%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9296
91.7%
ASCII 838
 
8.3%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
495
59.1%
) 84
 
10.0%
( 83
 
9.9%
1 42
 
5.0%
2 25
 
3.0%
3 18
 
2.1%
4 12
 
1.4%
/ 11
 
1.3%
8 9
 
1.1%
5 8
 
1.0%
Other values (19) 51
 
6.1%
Hangul
ValueCountFrequency (%)
259
 
2.8%
226
 
2.4%
187
 
2.0%
179
 
1.9%
174
 
1.9%
170
 
1.8%
157
 
1.7%
156
 
1.7%
154
 
1.7%
148
 
1.6%
Other values (487) 7486
80.5%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct864
Distinct (%)83.0%
Missing515
Missing (%)33.1%
Memory size12.3 KiB
2024-05-11T10:24:20.355050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length30
Mean length20.043228
Min length3

Characters and Unicode

Total characters20865
Distinct characters378
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

Unique716 ?
Unique (%)68.8%

Sample

1st row강원도 원주시 귀래면 북원로 106
2nd row강원도 원주시 봉산로 134
3rd row강원도 원주시 서원대로 311
4th row경상북도 영덕군 병곡면 고래불로 394
5th row경상북도 울진군 죽변면 등대길 52
ValueCountFrequency (%)
강원도 156
 
3.3%
서울특별시 151
 
3.2%
경기도 101
 
2.1%
원주시 76
 
1.6%
전라북도 65
 
1.4%
강원특별자치도 60
 
1.3%
경상북도 60
 
1.3%
전라남도 56
 
1.2%
전북특별자치도 55
 
1.2%
경상남도 49
 
1.0%
Other values (1675) 3919
82.5%
2024-05-11T10:24:21.522476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3707
 
17.8%
773
 
3.7%
770
 
3.7%
1 671
 
3.2%
656
 
3.1%
472
 
2.3%
425
 
2.0%
423
 
2.0%
2 407
 
2.0%
398
 
1.9%
Other values (368) 12163
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13764
66.0%
Space Separator 3707
 
17.8%
Decimal Number 3109
 
14.9%
Dash Punctuation 201
 
1.0%
Close Punctuation 39
 
0.2%
Open Punctuation 39
 
0.2%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
773
 
5.6%
770
 
5.6%
656
 
4.8%
472
 
3.4%
425
 
3.1%
423
 
3.1%
398
 
2.9%
332
 
2.4%
326
 
2.4%
323
 
2.3%
Other values (351) 8866
64.4%
Decimal Number
ValueCountFrequency (%)
1 671
21.6%
2 407
13.1%
3 352
11.3%
5 308
9.9%
4 295
9.5%
7 243
 
7.8%
0 232
 
7.5%
9 211
 
6.8%
6 202
 
6.5%
8 188
 
6.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
66.7%
. 1
 
16.7%
, 1
 
16.7%
Space Separator
ValueCountFrequency (%)
3707
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 201
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13764
66.0%
Common 7101
34.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
773
 
5.6%
770
 
5.6%
656
 
4.8%
472
 
3.4%
425
 
3.1%
423
 
3.1%
398
 
2.9%
332
 
2.4%
326
 
2.4%
323
 
2.3%
Other values (351) 8866
64.4%
Common
ValueCountFrequency (%)
3707
52.2%
1 671
 
9.4%
2 407
 
5.7%
3 352
 
5.0%
5 308
 
4.3%
4 295
 
4.2%
7 243
 
3.4%
0 232
 
3.3%
9 211
 
3.0%
6 202
 
2.8%
Other values (7) 473
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13764
66.0%
ASCII 7101
34.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3707
52.2%
1 671
 
9.4%
2 407
 
5.7%
3 352
 
5.0%
5 308
 
4.3%
4 295
 
4.2%
7 243
 
3.4%
0 232
 
3.3%
9 211
 
3.0%
6 202
 
2.8%
Other values (7) 473
 
6.7%
Hangul
ValueCountFrequency (%)
773
 
5.6%
770
 
5.6%
656
 
4.8%
472
 
3.4%
425
 
3.1%
423
 
3.1%
398
 
2.9%
332
 
2.4%
326
 
2.4%
323
 
2.3%
Other values (351) 8866
64.4%
Distinct1184
Distinct (%)84.3%
Missing152
Missing (%)9.8%
Memory size12.3 KiB
2024-05-11T10:24:22.248445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length33
Mean length20.434473
Min length11

Characters and Unicode

Total characters28690
Distinct characters315
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1001 ?
Unique (%)71.3%

Sample

1st row강원도 원주시 귀래면 운남리 555-5
2nd row강원도 원주시 봉산동 836-1
3rd row강원도 원주시 명륜동 343
4th row경상북도 영덕군 병곡면 병곡리 58-26
5th row경상북도 울진군 죽변면 죽변리 1-23
ValueCountFrequency (%)
경기도 237
 
3.6%
강원도 175
 
2.7%
서울특별시 147
 
2.2%
경상북도 114
 
1.7%
전라북도 88
 
1.3%
전북특별자치도 87
 
1.3%
원주시 78
 
1.2%
강원특별자치도 73
 
1.1%
전라남도 72
 
1.1%
경상남도 63
 
1.0%
Other values (2423) 5441
82.8%
2024-05-11T10:24:23.463170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5176
 
18.0%
1 1109
 
3.9%
1098
 
3.8%
1015
 
3.5%
- 907
 
3.2%
814
 
2.8%
763
 
2.7%
2 625
 
2.2%
616
 
2.1%
592
 
2.1%
Other values (305) 15975
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17569
61.2%
Space Separator 5176
 
18.0%
Decimal Number 4988
 
17.4%
Dash Punctuation 907
 
3.2%
Open Punctuation 20
 
0.1%
Close Punctuation 20
 
0.1%
Other Punctuation 8
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1098
 
6.2%
1015
 
5.8%
814
 
4.6%
763
 
4.3%
616
 
3.5%
592
 
3.4%
568
 
3.2%
486
 
2.8%
433
 
2.5%
418
 
2.4%
Other values (288) 10766
61.3%
Decimal Number
ValueCountFrequency (%)
1 1109
22.2%
2 625
12.5%
3 549
11.0%
4 497
10.0%
5 447
9.0%
6 410
 
8.2%
8 382
 
7.7%
7 352
 
7.1%
0 325
 
6.5%
9 292
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/ 7
87.5%
, 1
 
12.5%
Space Separator
ValueCountFrequency (%)
5176
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 907
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17569
61.2%
Common 11121
38.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1098
 
6.2%
1015
 
5.8%
814
 
4.6%
763
 
4.3%
616
 
3.5%
592
 
3.4%
568
 
3.2%
486
 
2.8%
433
 
2.5%
418
 
2.4%
Other values (288) 10766
61.3%
Common
ValueCountFrequency (%)
5176
46.5%
1 1109
 
10.0%
- 907
 
8.2%
2 625
 
5.6%
3 549
 
4.9%
4 497
 
4.5%
5 447
 
4.0%
6 410
 
3.7%
8 382
 
3.4%
7 352
 
3.2%
Other values (7) 667
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17569
61.2%
ASCII 11121
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5176
46.5%
1 1109
 
10.0%
- 907
 
8.2%
2 625
 
5.6%
3 549
 
4.9%
4 497
 
4.5%
5 447
 
4.0%
6 410
 
3.7%
8 382
 
3.4%
7 352
 
3.2%
Other values (7) 667
 
6.0%
Hangul
ValueCountFrequency (%)
1098
 
6.2%
1015
 
5.8%
814
 
4.6%
763
 
4.3%
616
 
3.5%
592
 
3.4%
568
 
3.2%
486
 
2.8%
433
 
2.5%
418
 
2.4%
Other values (288) 10766
61.3%
Distinct1211
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2024-05-11T10:24:23.997493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length6.1818766
Min length2

Characters and Unicode

Total characters9619
Distinct characters536
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique930 ?
Unique (%)59.8%

Sample

1st row귀래면행정복지센터
2nd row원주역사박물관
3rd row종합경기장 삼거리
4th row후포항
5th row기성버스터미널
ValueCountFrequency (%)
주차장 39
 
1.9%
입구 26
 
1.3%
정상 17
 
0.8%
12
 
0.6%
10
 
0.5%
논골카페 8
 
0.4%
출구 8
 
0.4%
평창 6
 
0.3%
물치해수욕장 6
 
0.3%
옥계시장 6
 
0.3%
Other values (1446) 1907
93.3%
2024-05-11T10:24:24.935854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
490
 
5.1%
252
 
2.6%
203
 
2.1%
184
 
1.9%
169
 
1.8%
163
 
1.7%
156
 
1.6%
154
 
1.6%
152
 
1.6%
150
 
1.6%
Other values (526) 7546
78.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8868
92.2%
Space Separator 490
 
5.1%
Decimal Number 94
 
1.0%
Open Punctuation 66
 
0.7%
Close Punctuation 66
 
0.7%
Other Punctuation 15
 
0.2%
Uppercase Letter 12
 
0.1%
Math Symbol 4
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Other Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
252
 
2.8%
203
 
2.3%
184
 
2.1%
169
 
1.9%
163
 
1.8%
156
 
1.8%
154
 
1.7%
152
 
1.7%
150
 
1.7%
140
 
1.6%
Other values (497) 7145
80.6%
Decimal Number
ValueCountFrequency (%)
1 28
29.8%
2 25
26.6%
4 12
12.8%
3 8
 
8.5%
8 5
 
5.3%
9 4
 
4.3%
0 4
 
4.3%
5 3
 
3.2%
7 3
 
3.2%
6 2
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
C 3
25.0%
T 2
16.7%
S 2
16.7%
U 1
 
8.3%
I 1
 
8.3%
K 1
 
8.3%
B 1
 
8.3%
M 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
/ 7
46.7%
. 4
26.7%
, 2
 
13.3%
· 2
 
13.3%
Other Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
490
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8867
92.2%
Common 739
 
7.7%
Latin 12
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
252
 
2.8%
203
 
2.3%
184
 
2.1%
169
 
1.9%
163
 
1.8%
156
 
1.8%
154
 
1.7%
152
 
1.7%
150
 
1.7%
140
 
1.6%
Other values (496) 7144
80.6%
Common
ValueCountFrequency (%)
490
66.3%
( 66
 
8.9%
) 66
 
8.9%
1 28
 
3.8%
2 25
 
3.4%
4 12
 
1.6%
3 8
 
1.1%
/ 7
 
0.9%
8 5
 
0.7%
9 4
 
0.5%
Other values (11) 28
 
3.8%
Latin
ValueCountFrequency (%)
C 3
25.0%
T 2
16.7%
S 2
16.7%
U 1
 
8.3%
I 1
 
8.3%
K 1
 
8.3%
B 1
 
8.3%
M 1
 
8.3%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8867
92.2%
ASCII 747
 
7.8%
None 2
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
490
65.6%
( 66
 
8.8%
) 66
 
8.8%
1 28
 
3.7%
2 25
 
3.3%
4 12
 
1.6%
3 8
 
1.1%
/ 7
 
0.9%
8 5
 
0.7%
9 4
 
0.5%
Other values (16) 36
 
4.8%
Hangul
ValueCountFrequency (%)
252
 
2.8%
203
 
2.3%
184
 
2.1%
169
 
1.9%
163
 
1.8%
156
 
1.8%
154
 
1.7%
152
 
1.7%
150
 
1.7%
140
 
1.6%
Other values (496) 7144
80.6%
None
ValueCountFrequency (%)
· 2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
50.0%
1
50.0%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct859
Distinct (%)82.6%
Missing516
Missing (%)33.2%
Memory size12.3 KiB
2024-05-11T10:24:25.751029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length30
Mean length20.039423
Min length1

Characters and Unicode

Total characters20841
Distinct characters372
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique725 ?
Unique (%)69.7%

Sample

1st row강원도 원주시 귀래면 북원로 106
2nd row강원도 원주시 봉산로 134
3rd row강원도 원주시 서원대로 311
4th row경상북도 울진군 후포면 울진대게로 236-14
5th row경상북도 울진군 기성면 척산3길 17
ValueCountFrequency (%)
강원도 164
 
3.5%
서울특별시 145
 
3.1%
경기도 105
 
2.2%
원주시 76
 
1.6%
경상북도 64
 
1.4%
전라북도 62
 
1.3%
강원특별자치도 59
 
1.2%
전라남도 58
 
1.2%
경상남도 51
 
1.1%
전북특별자치도 51
 
1.1%
Other values (1707) 3888
82.3%
2024-05-11T10:24:27.402140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3684
 
17.7%
775
 
3.7%
768
 
3.7%
1 683
 
3.3%
650
 
3.1%
483
 
2.3%
435
 
2.1%
2 429
 
2.1%
412
 
2.0%
406
 
1.9%
Other values (362) 12116
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13644
65.5%
Space Separator 3684
 
17.7%
Decimal Number 3205
 
15.4%
Dash Punctuation 235
 
1.1%
Close Punctuation 32
 
0.2%
Open Punctuation 32
 
0.2%
Other Punctuation 7
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
775
 
5.7%
768
 
5.6%
650
 
4.8%
483
 
3.5%
435
 
3.2%
412
 
3.0%
406
 
3.0%
332
 
2.4%
328
 
2.4%
310
 
2.3%
Other values (344) 8745
64.1%
Decimal Number
ValueCountFrequency (%)
1 683
21.3%
2 429
13.4%
5 333
10.4%
3 324
10.1%
4 306
9.5%
7 284
8.9%
0 228
 
7.1%
6 223
 
7.0%
8 201
 
6.3%
9 194
 
6.1%
Other Punctuation
ValueCountFrequency (%)
/ 4
57.1%
. 2
28.6%
, 1
 
14.3%
Space Separator
ValueCountFrequency (%)
3684
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 235
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13644
65.5%
Common 7197
34.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
775
 
5.7%
768
 
5.6%
650
 
4.8%
483
 
3.5%
435
 
3.2%
412
 
3.0%
406
 
3.0%
332
 
2.4%
328
 
2.4%
310
 
2.3%
Other values (344) 8745
64.1%
Common
ValueCountFrequency (%)
3684
51.2%
1 683
 
9.5%
2 429
 
6.0%
5 333
 
4.6%
3 324
 
4.5%
4 306
 
4.3%
7 284
 
3.9%
- 235
 
3.3%
0 228
 
3.2%
6 223
 
3.1%
Other values (8) 468
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13644
65.5%
ASCII 7197
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3684
51.2%
1 683
 
9.5%
2 429
 
6.0%
5 333
 
4.6%
3 324
 
4.5%
4 306
 
4.3%
7 284
 
3.9%
- 235
 
3.3%
0 228
 
3.2%
6 223
 
3.1%
Other values (8) 468
 
6.5%
Hangul
ValueCountFrequency (%)
775
 
5.7%
768
 
5.6%
650
 
4.8%
483
 
3.5%
435
 
3.2%
412
 
3.0%
406
 
3.0%
332
 
2.4%
328
 
2.4%
310
 
2.3%
Other values (344) 8745
64.1%
Distinct1188
Distinct (%)84.6%
Missing152
Missing (%)9.8%
Memory size12.3 KiB
2024-05-11T10:24:28.320607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length32
Mean length20.418091
Min length10

Characters and Unicode

Total characters28667
Distinct characters315
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1010 ?
Unique (%)71.9%

Sample

1st row강원도 원주시 귀래면 운남리 555-5
2nd row강원도 원주시 봉산동 836-1
3rd row강원도 원주시 명륜동 343
4th row경상북도 울진군 후포면 후포리 1056
5th row경상북도 울진군 기성면 척산리 86-1
ValueCountFrequency (%)
경기도 236
 
3.6%
강원도 173
 
2.6%
서울특별시 149
 
2.3%
경상북도 115
 
1.8%
전라북도 85
 
1.3%
전북특별자치도 84
 
1.3%
원주시 78
 
1.2%
76
 
1.2%
전라남도 74
 
1.1%
강원특별자치도 74
 
1.1%
Other values (2440) 5426
82.6%
2024-05-11T10:24:29.710668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5183
 
18.1%
1110
 
3.9%
1 1086
 
3.8%
1011
 
3.5%
- 922
 
3.2%
813
 
2.8%
774
 
2.7%
2 664
 
2.3%
646
 
2.3%
583
 
2.0%
Other values (305) 15875
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17565
61.3%
Space Separator 5183
 
18.1%
Decimal Number 4953
 
17.3%
Dash Punctuation 922
 
3.2%
Open Punctuation 16
 
0.1%
Close Punctuation 16
 
0.1%
Other Punctuation 10
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1110
 
6.3%
1011
 
5.8%
813
 
4.6%
774
 
4.4%
646
 
3.7%
583
 
3.3%
579
 
3.3%
482
 
2.7%
431
 
2.5%
407
 
2.3%
Other values (288) 10729
61.1%
Decimal Number
ValueCountFrequency (%)
1 1086
21.9%
2 664
13.4%
3 547
11.0%
4 477
9.6%
5 460
9.3%
6 417
 
8.4%
7 373
 
7.5%
8 336
 
6.8%
0 314
 
6.3%
9 279
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/ 7
70.0%
, 3
30.0%
Space Separator
ValueCountFrequency (%)
5183
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 922
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17565
61.3%
Common 11102
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1110
 
6.3%
1011
 
5.8%
813
 
4.6%
774
 
4.4%
646
 
3.7%
583
 
3.3%
579
 
3.3%
482
 
2.7%
431
 
2.5%
407
 
2.3%
Other values (288) 10729
61.1%
Common
ValueCountFrequency (%)
5183
46.7%
1 1086
 
9.8%
- 922
 
8.3%
2 664
 
6.0%
3 547
 
4.9%
4 477
 
4.3%
5 460
 
4.1%
6 417
 
3.8%
7 373
 
3.4%
8 336
 
3.0%
Other values (7) 637
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17565
61.3%
ASCII 11102
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5183
46.7%
1 1086
 
9.8%
- 922
 
8.3%
2 664
 
6.0%
3 547
 
4.9%
4 477
 
4.3%
5 460
 
4.1%
6 417
 
3.8%
7 373
 
3.4%
8 336
 
3.0%
Other values (7) 637
 
5.7%
Hangul
ValueCountFrequency (%)
1110
 
6.3%
1011
 
5.8%
813
 
4.6%
774
 
4.4%
646
 
3.7%
583
 
3.3%
579
 
3.3%
482
 
2.7%
431
 
2.5%
407
 
2.3%
Other values (288) 10729
61.1%
Distinct1336
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2024-05-11T10:24:30.571681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length373
Median length142
Mean length50.375964
Min length3

Characters and Unicode

Total characters78385
Distinct characters857
Distinct categories15 ?
Distinct scripts3 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1133 ?
Unique (%)72.8%

Sample

1st row귀래면행정복지센터 → 운계교차로 → 사방댐 → 운남저수지 → 귀래교차로 → 귀래면행정복지센터
2nd row원주역사박물관 → 학봉정 → 원주역급수탑 → 남산공원 → 원주향교 → 연희반점 → 원주역사박물관
3rd row종합경기장삼거리 → 무실체육공원 → 남송골프클럽 입구 → 명륜한의원 → 종합경기장삼거리
4th row고래불해변 → 병곡휴게소 → 금곡교 → 백암휴게소 → 후포항
5th row후포항 → 등기산공원 → 울진대게유래비 → 월송정 → 대풍헌 → 기성버스터미널
ValueCountFrequency (%)
2346
 
23.7%
476
 
4.8%
59
 
0.6%
입구 56
 
0.6%
정상 51
 
0.5%
44
 
0.4%
주차장 30
 
0.3%
전망대 17
 
0.2%
마을회관 15
 
0.2%
가옥 15
 
0.2%
Other values (5002) 6799
68.6%
2024-05-11T10:24:31.890326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8395
 
10.7%
6608
 
8.4%
- 1935
 
2.5%
1223
 
1.6%
1133
 
1.4%
1128
 
1.4%
1125
 
1.4%
1011
 
1.3%
1005
 
1.3%
963
 
1.2%
Other values (847) 53859
68.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56030
71.5%
Space Separator 8396
 
10.7%
Math Symbol 7411
 
9.5%
Dash Punctuation 1935
 
2.5%
Decimal Number 1500
 
1.9%
Close Punctuation 839
 
1.1%
Open Punctuation 831
 
1.1%
Lowercase Letter 620
 
0.8%
Other Punctuation 592
 
0.8%
Uppercase Letter 161
 
0.2%
Other values (5) 70
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1223
 
2.2%
1133
 
2.0%
1128
 
2.0%
1125
 
2.0%
1011
 
1.8%
1005
 
1.8%
963
 
1.7%
926
 
1.7%
863
 
1.5%
845
 
1.5%
Other values (766) 45808
81.8%
Uppercase Letter
ValueCountFrequency (%)
C 18
11.2%
K 17
10.6%
S 17
10.6%
A 15
 
9.3%
N 13
 
8.1%
D 11
 
6.8%
B 9
 
5.6%
E 8
 
5.0%
T 7
 
4.3%
M 7
 
4.3%
Other values (11) 39
24.2%
Lowercase Letter
ValueCountFrequency (%)
m 169
27.3%
k 140
22.6%
t 45
 
7.3%
o 37
 
6.0%
n 27
 
4.4%
w 27
 
4.4%
u 27
 
4.4%
c 20
 
3.2%
e 19
 
3.1%
h 18
 
2.9%
Other values (7) 91
14.7%
Decimal Number
ValueCountFrequency (%)
1 359
23.9%
2 224
14.9%
3 209
13.9%
0 179
11.9%
5 132
 
8.8%
4 113
 
7.5%
6 81
 
5.4%
8 79
 
5.3%
7 63
 
4.2%
9 61
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 271
45.8%
, 136
23.0%
: 89
 
15.0%
/ 65
 
11.0%
? 10
 
1.7%
· 9
 
1.5%
& 8
 
1.4%
3
 
0.5%
* 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
6608
89.2%
~ 361
 
4.9%
226
 
3.0%
> 181
 
2.4%
+ 22
 
0.3%
= 9
 
0.1%
3
 
< 0.1%
1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
8395
> 99.9%
  1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 829
98.8%
] 10
 
1.2%
Open Punctuation
ValueCountFrequency (%)
( 821
98.8%
[ 10
 
1.2%
Other Symbol
ValueCountFrequency (%)
59
96.7%
2
 
3.3%
Final Punctuation
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Initial Punctuation
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 1935
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 56032
71.5%
Common 21572
 
27.5%
Latin 781
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1223
 
2.2%
1133
 
2.0%
1128
 
2.0%
1125
 
2.0%
1011
 
1.8%
1005
 
1.8%
963
 
1.7%
926
 
1.7%
863
 
1.5%
845
 
1.5%
Other values (767) 45810
81.8%
Common
ValueCountFrequency (%)
8395
38.9%
6608
30.6%
- 1935
 
9.0%
) 829
 
3.8%
( 821
 
3.8%
~ 361
 
1.7%
1 359
 
1.7%
. 271
 
1.3%
226
 
1.0%
2 224
 
1.0%
Other values (32) 1543
 
7.2%
Latin
ValueCountFrequency (%)
m 169
21.6%
k 140
17.9%
t 45
 
5.8%
o 37
 
4.7%
n 27
 
3.5%
w 27
 
3.5%
u 27
 
3.5%
c 20
 
2.6%
e 19
 
2.4%
C 18
 
2.3%
Other values (28) 252
32.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 56028
71.5%
ASCII 15435
 
19.7%
Arrows 6834
 
8.7%
CJK Compat 59
 
0.1%
None 16
 
< 0.1%
Punctuation 6
 
< 0.1%
Math Operators 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8395
54.4%
- 1935
 
12.5%
) 829
 
5.4%
( 821
 
5.3%
~ 361
 
2.3%
1 359
 
2.3%
. 271
 
1.8%
2 224
 
1.5%
3 209
 
1.4%
> 181
 
1.2%
Other values (56) 1850
 
12.0%
Arrows
ValueCountFrequency (%)
6608
96.7%
226
 
3.3%
Hangul
ValueCountFrequency (%)
1223
 
2.2%
1133
 
2.0%
1128
 
2.0%
1125
 
2.0%
1011
 
1.8%
1005
 
1.8%
963
 
1.7%
926
 
1.7%
863
 
1.5%
845
 
1.5%
Other values (765) 45806
81.8%
CJK Compat
ValueCountFrequency (%)
59
100.0%
None
ValueCountFrequency (%)
· 9
56.2%
3
 
18.8%
2
 
12.5%
1
 
6.2%
  1
 
6.2%
Math Operators
ValueCountFrequency (%)
3
100.0%
Punctuation
ValueCountFrequency (%)
3
50.0%
1
 
16.7%
1
 
16.7%
1
 
16.7%
Compat Jamo
ValueCountFrequency (%)
2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct282
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2024-05-11T10:24:32.601784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.992931
Min length9

Characters and Unicode

Total characters18661
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)6.3%

Sample

1st row033-737-5135
2nd row033-737-5135
3rd row033-737-5135
4th row054-789-6901
5th row054-789-6901
ValueCountFrequency (%)
033-737-5135 82
 
5.3%
031-259-4715 60
 
3.9%
033-640-5126 44
 
2.8%
054-480-5863 34
 
2.2%
063-290-3991 34
 
2.2%
063-433-5191 32
 
2.1%
02-2148-1854 31
 
2.0%
064-762-2190 28
 
1.8%
053-662-3502 27
 
1.7%
063-560-2687 26
 
1.7%
Other values (272) 1158
74.4%
2024-05-11T10:24:33.760092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 3111
16.7%
0 2995
16.0%
3 2509
13.4%
5 1720
9.2%
2 1609
8.6%
4 1417
7.6%
6 1383
7.4%
1 1316
7.1%
8 937
 
5.0%
7 879
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15550
83.3%
Dash Punctuation 3111
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2995
19.3%
3 2509
16.1%
5 1720
11.1%
2 1609
10.3%
4 1417
9.1%
6 1383
8.9%
1 1316
8.5%
8 937
 
6.0%
7 879
 
5.7%
9 785
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 3111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18661
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 3111
16.7%
0 2995
16.0%
3 2509
13.4%
5 1720
9.2%
2 1609
8.6%
4 1417
7.6%
6 1383
7.4%
1 1316
7.1%
8 937
 
5.0%
7 879
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18661
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 3111
16.7%
0 2995
16.0%
3 2509
13.4%
5 1720
9.2%
2 1609
8.6%
4 1417
7.6%
6 1383
7.4%
1 1316
7.1%
8 937
 
5.0%
7 879
 
4.7%
Distinct232
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2024-05-11T10:24:34.519416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length9.375964
Min length3

Characters and Unicode

Total characters14589
Distinct characters192
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)3.5%

Sample

1st row강원도 원주시청
2nd row강원도 원주시청
3rd row강원도 원주시청
4th row경상북도 울진군청
5th row경상북도 울진군청
ValueCountFrequency (%)
강원도 178
 
5.9%
서울특별시 171
 
5.7%
경기도 142
 
4.7%
경상북도 113
 
3.8%
전라북도 88
 
2.9%
전북특별자치도 87
 
2.9%
원주시청 82
 
2.7%
전라남도 80
 
2.7%
강원특별자치도 77
 
2.6%
경기관광공사 73
 
2.4%
Other values (236) 1916
63.7%
2024-05-11T10:24:36.130633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1451
 
9.9%
1302
 
8.9%
998
 
6.8%
967
 
6.6%
452
 
3.1%
443
 
3.0%
428
 
2.9%
423
 
2.9%
414
 
2.8%
363
 
2.5%
Other values (182) 7348
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13123
90.0%
Space Separator 1451
 
9.9%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Math Symbol 3
 
< 0.1%
Decimal Number 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1302
 
9.9%
998
 
7.6%
967
 
7.4%
452
 
3.4%
443
 
3.4%
428
 
3.3%
423
 
3.2%
414
 
3.2%
363
 
2.8%
359
 
2.7%
Other values (174) 6974
53.1%
Decimal Number
ValueCountFrequency (%)
8 1
33.3%
1 1
33.3%
5 1
33.3%
Space Separator
ValueCountFrequency (%)
1451
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13123
90.0%
Common 1466
 
10.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1302
 
9.9%
998
 
7.6%
967
 
7.4%
452
 
3.4%
443
 
3.4%
428
 
3.3%
423
 
3.2%
414
 
3.2%
363
 
2.8%
359
 
2.7%
Other values (174) 6974
53.1%
Common
ValueCountFrequency (%)
1451
99.0%
( 4
 
0.3%
) 4
 
0.3%
+ 3
 
0.2%
· 1
 
0.1%
8 1
 
0.1%
1 1
 
0.1%
5 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13123
90.0%
ASCII 1465
 
10.0%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1451
99.0%
( 4
 
0.3%
) 4
 
0.3%
+ 3
 
0.2%
8 1
 
0.1%
1 1
 
0.1%
5 1
 
0.1%
Hangul
ValueCountFrequency (%)
1302
 
9.9%
998
 
7.6%
967
 
7.4%
452
 
3.4%
443
 
3.4%
428
 
3.3%
423
 
3.2%
414
 
3.2%
363
 
2.8%
359
 
2.7%
Other values (174) 6974
53.1%
None
ValueCountFrequency (%)
· 1
100.0%
Distinct149
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
Minimum2019-09-30 00:00:00
Maximum2024-03-28 00:00:00
2024-05-11T10:24:36.764399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:24:37.250461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct221
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2024-05-11T10:24:38.284804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters10892
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)3.0%

Sample

1st row4190000
2nd row4190000
3rd row4190000
4th row5250000
5th row5250000
ValueCountFrequency (%)
b551328 72
 
4.6%
6500000 53
 
3.4%
4190000 41
 
2.6%
4191000 41
 
2.6%
5080000 34
 
2.2%
3000000 31
 
2.0%
3420000 27
 
1.7%
6300000 26
 
1.7%
3020000 22
 
1.4%
4200000 22
 
1.4%
Other values (211) 1187
76.3%
2024-05-11T10:24:39.926261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6131
56.3%
4 1015
 
9.3%
3 751
 
6.9%
1 622
 
5.7%
5 610
 
5.6%
2 431
 
4.0%
6 344
 
3.2%
8 319
 
2.9%
7 298
 
2.7%
9 293
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10814
99.3%
Uppercase Letter 78
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6131
56.7%
4 1015
 
9.4%
3 751
 
6.9%
1 622
 
5.8%
5 610
 
5.6%
2 431
 
4.0%
6 344
 
3.2%
8 319
 
2.9%
7 298
 
2.8%
9 293
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
B 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10814
99.3%
Latin 78
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6131
56.7%
4 1015
 
9.4%
3 751
 
6.9%
1 622
 
5.8%
5 610
 
5.6%
2 431
 
4.0%
6 344
 
3.2%
8 319
 
2.9%
7 298
 
2.8%
9 293
 
2.7%
Latin
ValueCountFrequency (%)
B 78
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10892
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6131
56.3%
4 1015
 
9.3%
3 751
 
6.9%
1 622
 
5.7%
5 610
 
5.6%
2 431
 
4.0%
6 344
 
3.2%
8 319
 
2.9%
7 298
 
2.7%
9 293
 
2.7%
Distinct221
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2024-05-11T10:24:40.975768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.1632391
Min length5

Characters and Unicode

Total characters12702
Distinct characters128
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)3.0%

Sample

1st row강원도 원주시
2nd row강원도 원주시
3rd row강원도 원주시
4th row경상북도 울진군
5th row경상북도 울진군
ValueCountFrequency (%)
서울특별시 175
 
6.0%
경기도 174
 
6.0%
강원도 134
 
4.6%
강원특별자치도 126
 
4.3%
경상북도 117
 
4.0%
전북특별자치도 94
 
3.2%
전라북도 94
 
3.2%
전라남도 83
 
2.8%
원주시 82
 
2.8%
경기관광공사 72
 
2.5%
Other values (183) 1762
60.5%
2024-05-11T10:24:42.287380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1357
 
10.7%
1077
 
8.5%
1030
 
8.1%
478
 
3.8%
473
 
3.7%
473
 
3.7%
436
 
3.4%
428
 
3.4%
368
 
2.9%
367
 
2.9%
Other values (118) 6215
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11345
89.3%
Space Separator 1357
 
10.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1077
 
9.5%
1030
 
9.1%
478
 
4.2%
473
 
4.2%
473
 
4.2%
436
 
3.8%
428
 
3.8%
368
 
3.2%
367
 
3.2%
366
 
3.2%
Other values (117) 5849
51.6%
Space Separator
ValueCountFrequency (%)
1357
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11345
89.3%
Common 1357
 
10.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1077
 
9.5%
1030
 
9.1%
478
 
4.2%
473
 
4.2%
473
 
4.2%
436
 
3.8%
428
 
3.8%
368
 
3.2%
367
 
3.2%
366
 
3.2%
Other values (117) 5849
51.6%
Common
ValueCountFrequency (%)
1357
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11345
89.3%
ASCII 1357
 
10.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1357
100.0%
Hangul
ValueCountFrequency (%)
1077
 
9.5%
1030
 
9.1%
478
 
4.2%
473
 
4.2%
473
 
4.2%
436
 
3.8%
428
 
3.8%
368
 
3.2%
367
 
3.2%
366
 
3.2%
Other values (117) 5849
51.6%

Missing values

2024-05-11T10:24:05.518350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T10:24:06.303960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-11T10:24:07.087439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

길명길소개총길이총소요시간시작지점명시작지점도로명주소시작지점소재지지번주소종료지점명종료지점소재지도로명주소종료지점소재지지번주소경로정보관리기관전화번호관리기관명데이터기준일자제공기관코드제공기관명
0원주굽이길 원11코스 다둔인벌길원주의 수려한 자연경관과 문화·역사·생태 탐방 코스18.04~5시간귀래면행정복지센터강원도 원주시 귀래면 북원로 106강원도 원주시 귀래면 운남리 555-5귀래면행정복지센터강원도 원주시 귀래면 북원로 106강원도 원주시 귀래면 운남리 555-5귀래면행정복지센터 → 운계교차로 → 사방댐 → 운남저수지 → 귀래교차로 → 귀래면행정복지센터033-737-5135강원도 원주시청2022-11-224190000강원도 원주시
1원주굽이길 원12코스 북원역사길원주의 수려한 자연경관과 문화·역사·생태 탐방 코스11.83시간원주역사박물관강원도 원주시 봉산로 134강원도 원주시 봉산동 836-1원주역사박물관강원도 원주시 봉산로 134강원도 원주시 봉산동 836-1원주역사박물관 → 학봉정 → 원주역급수탑 → 남산공원 → 원주향교 → 연희반점 → 원주역사박물관033-737-5135강원도 원주시청2022-11-224190000강원도 원주시
2원주굽이길 원13코스 무실과수원길원주의 수려한 자연경관과 문화·역사·생태 탐방 코스10.73시간종합경기장 삼거리강원도 원주시 서원대로 311강원도 원주시 명륜동 343종합경기장 삼거리강원도 원주시 서원대로 311강원도 원주시 명륜동 343종합경기장삼거리 → 무실체육공원 → 남송골프클럽 입구 → 명륜한의원 → 종합경기장삼거리033-737-5135강원도 원주시청2022-11-224190000강원도 원주시
3해파랑길(제23구간)바다를 배경으로 어촌마을과 해변을 지나는 조용한 코스11.94고래불해변경상북도 영덕군 병곡면 고래불로 394경상북도 영덕군 병곡면 병곡리 58-26후포항경상북도 울진군 후포면 울진대게로 236-14경상북도 울진군 후포면 후포리 1056고래불해변 → 병곡휴게소 → 금곡교 → 백암휴게소 → 후포항054-789-6901경상북도 울진군청2023-01-315250000경상북도 울진군
4해파랑길(제24구간)해안 도로를 따라 숲길과 갯벌, 백사장과 온천이 조성된 힐링 코스18.26후포항경상북도 울진군 죽변면 등대길 52경상북도 울진군 죽변면 죽변리 1-23기성버스터미널경상북도 울진군 기성면 척산3길 17경상북도 울진군 기성면 척산리 86-1후포항 → 등기산공원 → 울진대게유래비 → 월송정 → 대풍헌 → 기성버스터미널054-789-6901경상북도 울진군청2023-01-315250000경상북도 울진군
5해파랑길(제25구간)동해안을 벗삼아 시를 읊던 묵객들의 발자취를 따라가는 해안길23.27.5기성버스터미널경상북도 울진군 기성면 척산3길 17경상북도 울진군 기성면 척산리 86-1수산교경상북도 울진군 근남면 노음2길 일원경상북도 울진군 근남면 노음리 356-1기성버스터미널 → 기성망양해수욕장 → 망양휴게소 → 망양정 → 수산교054-789-6901경상북도 울진군청2023-01-315250000경상북도 울진군
6해파랑길(제26구간)두 개의 공원과 해변과 숲길, 등대 등 다채로운 볼거리가 있는 길12.95수산교경상북도 울진군 근남면 노음2길 일원경상북도 울진군 근남면 노음리 356-1죽변항입구경상북도 울진군 죽변면 죽변항길 124경상북도 울진군 죽변면 죽변리 36-88수산교 → 울진엑스포공원 → 연호공원 → 봉평해수욕장 → 죽변항입구054-789-6901경상북도 울진군청2023-01-315250000경상북도 울진군
7해파랑길(제27구간)어촌마을과 유적지, 울진도심 등 다양한 울진의 모습을 발견할 수 있는 길11.43.5죽변항입구경상북도 울진군 죽변면 죽변항길 124경상북도 울진군 죽변면 죽변리 36-88부구삼거리경상북도 울진군 북면 울진북로 2067 일원경상북도 울진군 북면 부구리 126-2죽변항입구 → 폭풍속으로 드라마세트장&하트해변 → 국립해양과학관 → 부구삼거리054-789-6901경상북도 울진군청2023-01-315250000경상북도 울진군
8왕피천 은어길왕피천 계곡을 따라 연결된 탐방로2.21성산지<NA>경상북도 울진군 근남면 구산리 산95물병골<NA>경상북도 울진군 근남면 구산리 산175구산2리(성산지) → (2.2Km)구산3리(물병골)054-789-6811경상북도 울진군청2023-01-315250000경상북도 울진군
9불영사계곡 녹색길(3코스)일부 하천을 가로지르는 길과 마을안길, 농로로 이루어진 비교적 평이한 구간114불영주차장<NA>경상북도 울진군 금강송면 하원리 130-20광천교<NA>경상북도 울진군 금강송면 쌍전리 산 225불영사주차장 → (1.2Km)불영사 → (9.8Km)광천교054-789-6811경상북도 울진군청2023-01-315250000경상북도 울진군
길명길소개총길이총소요시간시작지점명시작지점도로명주소시작지점소재지지번주소종료지점명종료지점소재지도로명주소종료지점소재지지번주소경로정보관리기관전화번호관리기관명데이터기준일자제공기관코드제공기관명
1546외국인이 즐겨찾는 여행자 거리포근한 한옥과 천변 억새에 안겨 사부작사부작 산책 하기4.11시간 30분전동성당전북특별자치도 전주시 완산구 태조로 51전북특별자치도 전주시 완산구 전동 200-1남부시장<NA>전북특별자치도 전주시 완산구 전동 303-237전동성당→경기전→자만벽화마을→전주향교→전주천 동로→남부시장063-282-1330전북특별자치도 전주시청2024-01-174641000전북특별자치도 전주시
1547남고산성이 품은 아기자기 예술 동네전주 예술인들의 소박한 삶터 서학동 예술마을. 그야말로 터벅터벅 걷는데 제격입니다. 이곳을 품고 있는 남고산성은 아늑한 이 전주를 넉넉하게 한눈에 내려다 볼 수 있는 선물 같은 곳입니다.3.81시간 30분오목교전북특별자치도 전주시 완산구 전주천서로 43-13전북특별자치도 전주시 완산구 동서학동 880남고산성전북특별자치도 전주시 완산구 남고산성1길 53-88전북특별자치도 전주시 완산구 동서학동 724오목교→국립무형유산원→서학동예술마을→시나브로길→충경사→삼경사→관성묘→남고산성063-282-1330전북특별자치도 전주시청2024-01-174641000전북특별자치도 전주시
1548연분홍 꽃바람 사랑이 이루어지는 길담벼락이 없어 고운 풍경 어디로든 스며들기 좋은 도심 속 아름다운 호수 덕진공원 누구나 한번쯤은 거닐었던 전주 사람들의 데이트 명소입니다. 여름이면 한가득 피어나는 연꽃 향을 머금고 숲길까지 걷다 보면 어느새 마음에는 설렘이 가득합니다.82시간 30분전북대학교전북특별자치도 전주시 덕진구 백제대로 567전북특별자치도 전주시 덕진구 덕진동1가 664-14조경단<NA>전북특별자치도 전주시 덕진구 덕진동1가 640-9전북대학교→덕진공원→혼불문학공원→연화마을→단풍나무 숲길→장군봉→편백나무숲→오송제→대지마을→동물원→건지산→조경단063-282-1330전북특별자치도 전주시청2024-01-174641000전북특별자치도 전주시
1549푸른 하늘과 별빛 호수가 하나 되는 길밤이 되면 하늘의 별빛이 잔잔한 호수에 그대로 내려앉아 하늘과 호수가 하나가 됩니다. 호수를 밝히는 불빛들은 여기가 꿈속이 아닌가 하는 착각을 불러일으키고 어느덧 나도 몰래 발걸음을 하나 둘 옮깁니다.2.41시간 30분아중호수 수변산책로 주차장<NA>전북특별자치도 전주시 덕진구 우아동1가 1111-5호동골 자연생태 체험학습관<NA>전북특별자치도 전주시 덕진구 우아동1가 856-1아중호수 수변산책로 주차장→수상데크 광장→수상데크 쉼터→호동골어린이공원→호동골 자연생태체험학습관063-282-1330전북특별자치도 전주시청2024-01-174641000전북특별자치도 전주시
1550박경리 토지길총 31km로 <토지> 실제 배경이 되었던 평사리를 지나 화개장터까지 18km를 따라 거의 모든 구간에서 섬진강이 보이는 것은 물론 곳곳에 <토지>와 녹차에 얽힌 이야기들이 남아 있어 걷는 동안 한눈 팔 겨를이 없다.11.8+135시간+3시간30분평사리공원경상남도 하동군 악양면 섬진강대로 3145-1경상남도 하동군 악양면 평사리 74-2화개장터경상남도 하동군 화개면 쌍계로 15경상남도 하동군 화개면 탑리 726-46제1코스 : 평사리공원 → 평사리들판 → 동정호 → 고소성 → 최참판댁 → 조씨고가 → 취간림 → 문암송 → 악양천제방 → 평사리공원 → 화개장터055-880-2371경상남도 하동군청2024-01-175440000경상남도 하동군
1551하동 섬진강변길소설 <토지>의 배경으로 익숙한 섬진강변에 친환경 생태 트레킹코스로 벚꽃과 매화꽃의 아름다운 풍광 + 청정하천의 원형을 보전하고 있는 길이다. 구간별 주차장과 휴게쉼터 + 전망공간 + 수변산책로 + 도보길이 조성되어 있다20.95시간10분화개장터경상남도 하동군 화개면 쌍계로 15경상남도 하동군 화개면 탑리 726-46송림공원경상남도 하동군 하동읍 섬진강대로 2107-8경상남도 하동군 하동읍 광평리 443-10(야생차 ZONE) 화개장터 → 천년녹차쉼터 → 은모래쉼터 → 제1쉼터(두꺼비바위쉼터) (문학 ZONE) 제1쉼터(두꺼비바위쉼터) → 제2쉼터(대나무쉼터) → 팽나무쉼터 → 지리산생태과학관 → 전망쉼터 → 평사리공원(두꺼비 ZONE) 평사리공원 → 개치나루터 → 버드나무쉼터 → 두꺼비나루쉼터 → 흥룡/먹점마을 → 밤나무쉼터 → 돌티미전망대 → 하동이화 스마트 복합쉼터(재첩 ZONE) 하동이화 스마트 복합쉼터 → 만지배밭 → 재첩쉼터 → 하동나루쉼터 → 하동공원 → 송림공원055-880-2381경상남도 하동군청2024-01-175440000경상남도 하동군
1552이순신 백의종군로 탐방로이순신 장군이 관직을 박탈당한 뒤 백의종군 하기 위해 권율 도원수 진영(합천)으로 가던 길로 한성~아산~순천~구례~하동~진주~산청~합천~진주(초계)~하동~구례로 이어진다.287시간북천모성마을경상남도 하동군 북천면 모성길 49경상남도 하동군 북천면 사평리 628이홍훈가(이순신유숙지)경상남도 하동군 옥종면 청안길 38경상남도 하동군 옥종면 청룡리 338-1제4코스: 북천모성마을 → 중촌(경현당) → 화정(백토재) → 청수삼거리 → 옥산서원(청수역쉼터) → 영당사거리 → 동곡마을 → 불무 → 북방 → 추동(정티움) → 산성교 → 문암정 → 옥천관 → 이홍훈가(이순신유숙지)055-880-2366경상남도 하동군청2024-01-175440000경상남도 하동군
1553십리벚꽃길화개장터에서 쌍계사까지의 시오리길은 전국에서 가장 아름다운 가로수길 100선 가운데 최우수상을 수상한 아름다운 길로 / 사랑하는 청춘남녀가 함께 걸으면 사랑이 이뤄지고 영원하다고해서 혼례길이라고도 불린다.41시간 30분화개장터경상남도 하동군 화개면 쌍계로 15경상남도 하동군 화개면 탑리 726-46쌍계사경상남도 하동군 화개면 쌍계사길 59경상남도 하동군 화개면 운수리 208화개장터 → 삼신마을 → 야생차박물관 → 쌍계사055-880-2491경상남도 하동군청2024-01-175440000경상남도 하동군
1554서산대사 옛길지리산 화엄동 일대는 서산대사가 불법을 연구하기 시작하고 깨달음을 얻어 출가한 곳이다. 서산대사 옛길은 지리산 대성계곡을 따라 걷는 코스로 / 옛길의 자취가 잘 보존 되어 있고 군데군데 적당한 쉼터와 기암괴석이 잘 배치되어있다.62시간신흥마을경상남도 하동군 화개면 범왕길 15경상남도 하동군 화개면 범왕리 산122-1의신마을경상남도 하동군 화개면 의신길 19-3경상남도 하동군 화개면 대성리 1988신흥 → 쇠점터 → 단천 → 대성교 → 의신마을055-880-2366경상남도 하동군청2024-01-175440000경상남도 하동군
1555회남재 숲길남명 조식 선생이 산청 덕산에서 후학을 양성하던 중 악양이 명승지라는 말을 듣고 1560년경 이곳을 찾았다가 돌아갔다고해서 붙여진 이름으로 하동시장을 연결하는 산업활동 통로이자 산청과 함양 등 지리산 주변 주민들이 널이 이용하던 소통의 길임8.7+10+122시간+2시간30분+3시간삼성궁 주차장경상남도 하동군 청암면 삼성궁길 86-15경상남도 하동군 청암면 묵계리 1561-1악양 등촌 청학선사+묵계초등학교+삼성궁 주차장경상남도 하동군 악양면 회남재로 529-56+경상남도 하동군 청암면 청학로 2220+경상남도 하동군 청암면 삼성궁길 86-15경상남도 하동군 악양면 등촌리 760+경상남도 하동군 청암면 묵계리 550+경상남도 하동군 청암면 묵계리 1561-1제1코스 : 삼성궁 주차장→ 회남재→악양 등촌 청학선사+제2코스 : 삼성궁 주차장→회남재→묵계초등학교+제3코스 : 삼성궁 주차장→회남재→삼성궁 주차장055-880-2481경상남도 하동군청2024-01-175440000경상남도 하동군