Overview

Dataset statistics

Number of variables20
Number of observations4510
Missing cells12384
Missing cells (%)13.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory718.0 KiB
Average record size in memory163.0 B

Variable types

Text13
Categorical2
Numeric3
DateTime2

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/15021147/standard.do

Alerts

위도 is highly overall correlated with 제공기관코드High correlation
제공기관코드 is highly overall correlated with 위도High correlation
소재지도로명주소 has 2549 (56.5%) missing valuesMissing
소재지지번주소 has 248 (5.5%) missing valuesMissing
소유자명 has 1630 (36.1%) missing valuesMissing
규모 has 2176 (48.2%) missing valuesMissing
조성시대 has 1886 (41.8%) missing valuesMissing
이미지정보 has 3895 (86.4%) missing valuesMissing

Reproduction

Analysis started2024-05-11 10:39:45.475078
Analysis finished2024-05-11 10:40:01.831600
Duration16.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct4132
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size35.4 KiB
2024-05-11T10:40:02.501713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length29
Mean length8.5288248
Min length2

Characters and Unicode

Total characters38465
Distinct characters1043
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3817 ?
Unique (%)84.6%

Sample

1st row쌍청리선돌
2nd row병마산성
3rd row저산성
4th row동림산성
5th row목령산성
ValueCountFrequency (%)
189
 
2.0%
진주 128
 
1.4%
117
 
1.3%
신도비 93
 
1.0%
정려 90
 
1.0%
묘역 81
 
0.9%
제주 74
 
0.8%
의령 58
 
0.6%
남원 55
 
0.6%
선생 53
 
0.6%
Other values (5595) 8367
89.9%
2024-05-11T10:40:04.184811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4806
 
12.5%
931
 
2.4%
760
 
2.0%
684
 
1.8%
630
 
1.6%
531
 
1.4%
486
 
1.3%
479
 
1.2%
476
 
1.2%
465
 
1.2%
Other values (1033) 28217
73.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32644
84.9%
Space Separator 4806
 
12.5%
Close Punctuation 374
 
1.0%
Open Punctuation 373
 
1.0%
Decimal Number 165
 
0.4%
Other Punctuation 69
 
0.2%
Dash Punctuation 19
 
< 0.1%
Math Symbol 7
 
< 0.1%
Uppercase Letter 7
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
931
 
2.9%
760
 
2.3%
684
 
2.1%
630
 
1.9%
531
 
1.6%
486
 
1.5%
479
 
1.5%
476
 
1.5%
465
 
1.4%
451
 
1.4%
Other values (1006) 26751
81.9%
Decimal Number
ValueCountFrequency (%)
1 45
27.3%
2 33
20.0%
3 26
15.8%
4 17
 
10.3%
7 9
 
5.5%
5 8
 
4.8%
9 7
 
4.2%
6 7
 
4.2%
0 7
 
4.2%
8 6
 
3.6%
Other Punctuation
ValueCountFrequency (%)
, 27
39.1%
· 20
29.0%
. 16
23.2%
/ 6
 
8.7%
Uppercase Letter
ValueCountFrequency (%)
M 4
57.1%
Y 1
 
14.3%
C 1
 
14.3%
A 1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 370
98.9%
4
 
1.1%
Open Punctuation
ValueCountFrequency (%)
( 369
98.9%
4
 
1.1%
Math Symbol
ValueCountFrequency (%)
~ 6
85.7%
+ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
4806
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31010
80.6%
Common 5813
 
15.1%
Han 1634
 
4.2%
Latin 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
931
 
3.0%
760
 
2.5%
684
 
2.2%
630
 
2.0%
531
 
1.7%
486
 
1.6%
479
 
1.5%
476
 
1.5%
465
 
1.5%
451
 
1.5%
Other values (540) 25117
81.0%
Han
ValueCountFrequency (%)
116
 
7.1%
53
 
3.2%
49
 
3.0%
32
 
2.0%
29
 
1.8%
26
 
1.6%
24
 
1.5%
22
 
1.3%
22
 
1.3%
22
 
1.3%
Other values (456) 1239
75.8%
Common
ValueCountFrequency (%)
4806
82.7%
) 370
 
6.4%
( 369
 
6.3%
1 45
 
0.8%
2 33
 
0.6%
, 27
 
0.5%
3 26
 
0.4%
· 20
 
0.3%
- 19
 
0.3%
4 17
 
0.3%
Other values (12) 81
 
1.4%
Latin
ValueCountFrequency (%)
M 4
50.0%
Y 1
 
12.5%
C 1
 
12.5%
A 1
 
12.5%
1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31005
80.6%
ASCII 5792
 
15.1%
CJK 1585
 
4.1%
CJK Compat Ideographs 49
 
0.1%
None 28
 
0.1%
Compat Jamo 5
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4806
83.0%
) 370
 
6.4%
( 369
 
6.4%
1 45
 
0.8%
2 33
 
0.6%
, 27
 
0.5%
3 26
 
0.4%
- 19
 
0.3%
4 17
 
0.3%
. 16
 
0.3%
Other values (13) 64
 
1.1%
Hangul
ValueCountFrequency (%)
931
 
3.0%
760
 
2.5%
684
 
2.2%
630
 
2.0%
531
 
1.7%
486
 
1.6%
479
 
1.5%
476
 
1.5%
465
 
1.5%
451
 
1.5%
Other values (539) 25112
81.0%
CJK
ValueCountFrequency (%)
116
 
7.3%
53
 
3.3%
49
 
3.1%
32
 
2.0%
29
 
1.8%
26
 
1.6%
24
 
1.5%
22
 
1.4%
22
 
1.4%
22
 
1.4%
Other values (438) 1190
75.1%
CJK Compat Ideographs
ValueCountFrequency (%)
20
40.8%
7
 
14.3%
3
 
6.1%
3
 
6.1%
2
 
4.1%
2
 
4.1%
1
 
2.0%
1
 
2.0%
1
 
2.0%
1
 
2.0%
Other values (8) 8
 
16.3%
None
ValueCountFrequency (%)
· 20
71.4%
4
 
14.3%
4
 
14.3%
Compat Jamo
ValueCountFrequency (%)
5
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct3059
Distinct (%)67.8%
Missing0
Missing (%)0.0%
Memory size35.4 KiB
2024-05-11T10:40:05.093242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length8.0505543
Min length1

Characters and Unicode

Total characters36308
Distinct characters112
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2630 ?
Unique (%)58.3%

Sample

1st row청주시 향토기념 제19호
2nd row청주시 향토기념 제20호
3rd row청주시 향토기념 제21호
4th row청주시 향토기념 제22호
5th row청주시 향토기념 제23호
ValueCountFrequency (%)
향토문화유산 453
 
5.5%
향토유적 326
 
4.0%
청주시 201
 
2.4%
향토유형 167
 
2.0%
문화재자료 127
 
1.5%
부여군 125
 
1.5%
유형문화재 122
 
1.5%
기념물 121
 
1.5%
영양군 116
 
1.4%
문화유적 99
 
1.2%
Other values (1514) 6367
77.4%
2024-05-11T10:40:06.879738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3723
 
10.3%
2854
 
7.9%
2379
 
6.6%
1 2048
 
5.6%
1766
 
4.9%
1536
 
4.2%
2 1502
 
4.1%
1450
 
4.0%
1339
 
3.7%
1333
 
3.7%
Other values (102) 16378
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22825
62.9%
Decimal Number 9425
26.0%
Space Separator 3723
 
10.3%
Dash Punctuation 306
 
0.8%
Open Punctuation 14
 
< 0.1%
Close Punctuation 14
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2854
 
12.5%
2379
 
10.4%
1766
 
7.7%
1536
 
6.7%
1450
 
6.4%
1339
 
5.9%
1333
 
5.8%
823
 
3.6%
756
 
3.3%
699
 
3.1%
Other values (87) 7890
34.6%
Decimal Number
ValueCountFrequency (%)
1 2048
21.7%
2 1502
15.9%
3 1076
11.4%
4 927
9.8%
5 774
 
8.2%
6 706
 
7.5%
0 667
 
7.1%
8 584
 
6.2%
9 574
 
6.1%
7 567
 
6.0%
Space Separator
ValueCountFrequency (%)
3723
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 306
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22813
62.8%
Common 13483
37.1%
Han 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2854
 
12.5%
2379
 
10.4%
1766
 
7.7%
1536
 
6.7%
1450
 
6.4%
1339
 
5.9%
1333
 
5.8%
823
 
3.6%
756
 
3.3%
699
 
3.1%
Other values (86) 7878
34.5%
Common
ValueCountFrequency (%)
3723
27.6%
1 2048
15.2%
2 1502
11.1%
3 1076
 
8.0%
4 927
 
6.9%
5 774
 
5.7%
6 706
 
5.2%
0 667
 
4.9%
8 584
 
4.3%
9 574
 
4.3%
Other values (5) 902
 
6.7%
Han
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22813
62.8%
ASCII 13483
37.1%
CJK 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3723
27.6%
1 2048
15.2%
2 1502
11.1%
3 1076
 
8.0%
4 927
 
6.9%
5 774
 
5.7%
6 706
 
5.2%
0 667
 
4.9%
8 584
 
4.3%
9 574
 
4.3%
Other values (5) 902
 
6.7%
Hangul
ValueCountFrequency (%)
2854
 
12.5%
2379
 
10.4%
1766
 
7.7%
1536
 
6.7%
1450
 
6.4%
1339
 
5.9%
1333
 
5.8%
823
 
3.6%
756
 
3.3%
699
 
3.1%
Other values (86) 7878
34.5%
CJK
ValueCountFrequency (%)
12
100.0%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.4 KiB
유형문화유적
3196 
기념물
907 
무형문화유적
 
230
민속자료
 
176
기념물+유형문화유적
 
1

Length

Max length10
Median length6
Mean length5.3195122
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
유형문화유적 3196
70.9%
기념물 907
 
20.1%
무형문화유적 230
 
5.1%
민속자료 176
 
3.9%
기념물+유형문화유적 1
 
< 0.1%

Length

2024-05-11T10:40:07.476829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:40:07.832819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유형문화유적 3196
70.9%
기념물 907
 
20.1%
무형문화유적 230
 
5.1%
민속자료 176
 
3.9%
기념물+유형문화유적 1
 
< 0.1%
Distinct397
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size35.4 KiB
2024-05-11T10:40:08.758551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length3.3536585
Min length1

Characters and Unicode

Total characters15125
Distinct characters213
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

Unique171 ?
Unique (%)3.8%

Sample

1st row석조물
2nd row성터
3rd row성터
4th row성터
5th row성터
ValueCountFrequency (%)
건조물 1556
31.2%
333
 
6.7%
기념물 229
 
4.6%
옛무덤 175
 
3.5%
123
 
2.5%
조각 111
 
2.2%
비석 87
 
1.7%
무덤 86
 
1.7%
민속문화재 84
 
1.7%
금석문 72
 
1.4%
Other values (371) 2137
42.8%
2024-05-11T10:40:10.330678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2059
 
13.6%
1817
 
12.0%
1692
 
11.2%
517
 
3.4%
483
 
3.2%
463
 
3.1%
455
 
3.0%
417
 
2.8%
386
 
2.6%
361
 
2.4%
Other values (203) 6475
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14524
96.0%
Space Separator 483
 
3.2%
Math Symbol 58
 
0.4%
Other Punctuation 32
 
0.2%
Open Punctuation 13
 
0.1%
Close Punctuation 13
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2059
 
14.2%
1817
 
12.5%
1692
 
11.6%
517
 
3.6%
463
 
3.2%
455
 
3.1%
417
 
2.9%
386
 
2.7%
361
 
2.5%
353
 
2.4%
Other values (195) 6004
41.3%
Other Punctuation
ValueCountFrequency (%)
/ 13
40.6%
, 12
37.5%
· 7
21.9%
Space Separator
ValueCountFrequency (%)
483
100.0%
Math Symbol
ValueCountFrequency (%)
+ 58
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14524
96.0%
Common 601
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2059
 
14.2%
1817
 
12.5%
1692
 
11.6%
517
 
3.6%
463
 
3.2%
455
 
3.1%
417
 
2.9%
386
 
2.7%
361
 
2.5%
353
 
2.4%
Other values (195) 6004
41.3%
Common
ValueCountFrequency (%)
483
80.4%
+ 58
 
9.7%
( 13
 
2.2%
/ 13
 
2.2%
) 13
 
2.2%
, 12
 
2.0%
· 7
 
1.2%
- 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14524
96.0%
ASCII 594
 
3.9%
None 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2059
 
14.2%
1817
 
12.5%
1692
 
11.6%
517
 
3.6%
463
 
3.2%
455
 
3.1%
417
 
2.9%
386
 
2.7%
361
 
2.5%
353
 
2.4%
Other values (195) 6004
41.3%
ASCII
ValueCountFrequency (%)
483
81.3%
+ 58
 
9.8%
( 13
 
2.2%
/ 13
 
2.2%
) 13
 
2.2%
, 12
 
2.0%
- 2
 
0.3%
None
ValueCountFrequency (%)
· 7
100.0%
Distinct1513
Distinct (%)77.2%
Missing2549
Missing (%)56.5%
Memory size35.4 KiB
2024-05-11T10:40:11.444124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length43
Mean length21.428863
Min length12

Characters and Unicode

Total characters42022
Distinct characters373
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

Unique1321 ?
Unique (%)67.4%

Sample

1st row경상남도 남해군 미조면 남해대로 14-11 무민사지방문화재제1호
2nd row경상남도 남해군 남해읍 남해대로 2745 남해유배문학관
3rd row경상남도 남해군 남해읍 화전로 45 영모문
4th row전라북도 무주군 설천면 상평지길 38-14
5th row전라북도 무주군 무풍면 원촌길 35
ValueCountFrequency (%)
전라남도 270
 
2.9%
경상북도 254
 
2.7%
경기도 245
 
2.6%
경상남도 240
 
2.5%
진주시 172
 
1.8%
전라북도 159
 
1.7%
강원도 158
 
1.7%
충청남도 156
 
1.7%
영양군 116
 
1.2%
전북특별자치도 110
 
1.2%
Other values (2774) 7551
80.1%
2024-05-11T10:40:13.062168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7470
 
17.8%
1915
 
4.6%
1 1554
 
3.7%
1242
 
3.0%
1096
 
2.6%
1054
 
2.5%
1039
 
2.5%
2 972
 
2.3%
935
 
2.2%
920
 
2.2%
Other values (363) 23825
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26374
62.8%
Space Separator 7470
 
17.8%
Decimal Number 7053
 
16.8%
Dash Punctuation 786
 
1.9%
Close Punctuation 156
 
0.4%
Open Punctuation 156
 
0.4%
Other Punctuation 24
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1915
 
7.3%
1242
 
4.7%
1096
 
4.2%
1054
 
4.0%
1039
 
3.9%
935
 
3.5%
920
 
3.5%
773
 
2.9%
640
 
2.4%
616
 
2.3%
Other values (347) 16144
61.2%
Decimal Number
ValueCountFrequency (%)
1 1554
22.0%
2 972
13.8%
3 796
11.3%
6 636
9.0%
4 630
8.9%
5 598
 
8.5%
7 526
 
7.5%
0 486
 
6.9%
8 428
 
6.1%
9 427
 
6.1%
Space Separator
ValueCountFrequency (%)
7470
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 786
100.0%
Close Punctuation
ValueCountFrequency (%)
) 156
100.0%
Open Punctuation
ValueCountFrequency (%)
( 156
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26374
62.8%
Common 15648
37.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1915
 
7.3%
1242
 
4.7%
1096
 
4.2%
1054
 
4.0%
1039
 
3.9%
935
 
3.5%
920
 
3.5%
773
 
2.9%
640
 
2.4%
616
 
2.3%
Other values (347) 16144
61.2%
Common
ValueCountFrequency (%)
7470
47.7%
1 1554
 
9.9%
2 972
 
6.2%
3 796
 
5.1%
- 786
 
5.0%
6 636
 
4.1%
4 630
 
4.0%
5 598
 
3.8%
7 526
 
3.4%
0 486
 
3.1%
Other values (6) 1194
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26374
62.8%
ASCII 15648
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7470
47.7%
1 1554
 
9.9%
2 972
 
6.2%
3 796
 
5.1%
- 786
 
5.0%
6 636
 
4.1%
4 630
 
4.0%
5 598
 
3.8%
7 526
 
3.4%
0 486
 
3.1%
Other values (6) 1194
 
7.6%
Hangul
ValueCountFrequency (%)
1915
 
7.3%
1242
 
4.7%
1096
 
4.2%
1054
 
4.0%
1039
 
3.9%
935
 
3.5%
920
 
3.5%
773
 
2.9%
640
 
2.4%
616
 
2.3%
Other values (347) 16144
61.2%

소재지지번주소
Text

MISSING 

Distinct3665
Distinct (%)86.0%
Missing248
Missing (%)5.5%
Memory size35.4 KiB
2024-05-11T10:40:14.117679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length46
Mean length21.533318
Min length10

Characters and Unicode

Total characters91775
Distinct characters364
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

Unique3354 ?
Unique (%)78.7%

Sample

1st row충청북도 청주시 흥덕구 오송읍 쌍청리 산49-5
2nd row충청북도 청주시 흥덕구 오송읍 정중리 산36
3rd row충청북도 청주시 흥덕구 강내면 저산리 산7
4th row충청북도 청주시 흥덕구 옥산면 장동리 산81-1
5th row충청북도 청주시 청원구 오창읍 양지리 산20-1
ValueCountFrequency (%)
경기도 635
 
3.0%
전라남도 478
 
2.3%
제주특별자치도 448
 
2.1%
충청남도 425
 
2.0%
경상북도 369
 
1.8%
충청북도 367
 
1.7%
전라북도 364
 
1.7%
경상남도 302
 
1.4%
제주시 268
 
1.3%
강원도 238
 
1.1%
Other values (5423) 17094
81.4%
2024-05-11T10:40:15.582494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16744
 
18.2%
4283
 
4.7%
1 3291
 
3.6%
3081
 
3.4%
2599
 
2.8%
2300
 
2.5%
- 2299
 
2.5%
2172
 
2.4%
1877
 
2.0%
2 1866
 
2.0%
Other values (354) 51263
55.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57991
63.2%
Space Separator 16744
 
18.2%
Decimal Number 14425
 
15.7%
Dash Punctuation 2299
 
2.5%
Open Punctuation 126
 
0.1%
Close Punctuation 125
 
0.1%
Other Punctuation 52
 
0.1%
Uppercase Letter 10
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4283
 
7.4%
3081
 
5.3%
2599
 
4.5%
2300
 
4.0%
2172
 
3.7%
1877
 
3.2%
1830
 
3.2%
1756
 
3.0%
1520
 
2.6%
1483
 
2.6%
Other values (332) 35090
60.5%
Decimal Number
ValueCountFrequency (%)
1 3291
22.8%
2 1866
12.9%
3 1570
10.9%
4 1289
 
8.9%
5 1283
 
8.9%
6 1180
 
8.2%
7 1067
 
7.4%
0 967
 
6.7%
9 962
 
6.7%
8 950
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
K 2
20.0%
H 2
20.0%
L 2
20.0%
B 2
20.0%
S 2
20.0%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
~ 1
33.3%
Space Separator
ValueCountFrequency (%)
16744
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2299
100.0%
Open Punctuation
ValueCountFrequency (%)
( 126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 125
100.0%
Other Punctuation
ValueCountFrequency (%)
, 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57991
63.2%
Common 33774
36.8%
Latin 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4283
 
7.4%
3081
 
5.3%
2599
 
4.5%
2300
 
4.0%
2172
 
3.7%
1877
 
3.2%
1830
 
3.2%
1756
 
3.0%
1520
 
2.6%
1483
 
2.6%
Other values (332) 35090
60.5%
Common
ValueCountFrequency (%)
16744
49.6%
1 3291
 
9.7%
- 2299
 
6.8%
2 1866
 
5.5%
3 1570
 
4.6%
4 1289
 
3.8%
5 1283
 
3.8%
6 1180
 
3.5%
7 1067
 
3.2%
0 967
 
2.9%
Other values (7) 2218
 
6.6%
Latin
ValueCountFrequency (%)
K 2
20.0%
H 2
20.0%
L 2
20.0%
B 2
20.0%
S 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57991
63.2%
ASCII 33784
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16744
49.6%
1 3291
 
9.7%
- 2299
 
6.8%
2 1866
 
5.5%
3 1570
 
4.6%
4 1289
 
3.8%
5 1283
 
3.8%
6 1180
 
3.5%
7 1067
 
3.2%
0 967
 
2.9%
Other values (12) 2228
 
6.6%
Hangul
ValueCountFrequency (%)
4283
 
7.4%
3081
 
5.3%
2599
 
4.5%
2300
 
4.0%
2172
 
3.7%
1877
 
3.2%
1830
 
3.2%
1756
 
3.0%
1520
 
2.6%
1483
 
2.6%
Other values (332) 35090
60.5%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct3675
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.981368
Minimum33.121969
Maximum38.283275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.8 KiB
2024-05-11T10:40:15.983146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.121969
5-th percentile33.451398
Q135.190809
median36.121542
Q336.862143
95-th percentile37.771908
Maximum38.283275
Range5.1613055
Interquartile range (IQR)1.6713334

Descriptive statistics

Standard deviation1.2614443
Coefficient of variation (CV)0.035058264
Kurtosis-0.43591443
Mean35.981368
Median Absolute Deviation (MAD)0.89747555
Skewness-0.45456781
Sum162275.97
Variance1.5912417
MonotonicityNot monotonic
2024-05-11T10:40:16.566585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.718848 45
 
1.0%
35.15670948 32
 
0.7%
35.18901467 26
 
0.6%
36.5760673 20
 
0.4%
35.19043672 15
 
0.3%
37.66192496 13
 
0.3%
35.07856349 12
 
0.3%
35.41595402 12
 
0.3%
33.388926 12
 
0.3%
37.371557 10
 
0.2%
Other values (3665) 4313
95.6%
ValueCountFrequency (%)
33.121969 1
< 0.1%
33.196374 1
< 0.1%
33.203317 1
< 0.1%
33.204661 1
< 0.1%
33.205467 1
< 0.1%
33.205727 1
< 0.1%
33.210561 1
< 0.1%
33.219108 1
< 0.1%
33.221531 1
< 0.1%
33.222804 1
< 0.1%
ValueCountFrequency (%)
38.28327451 2
< 0.1%
38.2825022 2
< 0.1%
38.271413 2
< 0.1%
38.255453 2
< 0.1%
38.24028768 2
< 0.1%
38.2394409 2
< 0.1%
38.2256389 2
< 0.1%
38.2096687 2
< 0.1%
38.15986237 1
< 0.1%
38.14864592 2
< 0.1%

경도
Real number (ℝ)

Distinct3665
Distinct (%)81.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.44696
Minimum124.733
Maximum129.5616
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.8 KiB
2024-05-11T10:40:17.030836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124.733
5-th percentile126.36849
Q1126.82006
median127.27625
Q3128.07685
95-th percentile129.07043
Maximum129.5616
Range4.8286009
Interquartile range (IQR)1.2567928

Descriptive statistics

Standard deviation0.82619407
Coefficient of variation (CV)0.00648265
Kurtosis-0.51321107
Mean127.44696
Median Absolute Deviation (MAD)0.49227465
Skewness0.61108807
Sum574785.81
Variance0.68259665
MonotonicityNot monotonic
2024-05-11T10:40:17.927934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6029578 41
 
0.9%
128.0980016 32
 
0.7%
128.0768483 26
 
0.6%
128.7644396 20
 
0.4%
128.0802208 15
 
0.3%
127.084979 13
 
0.3%
126.788539 12
 
0.3%
129.0802456 12
 
0.3%
127.6352423 12
 
0.3%
128.261359 10
 
0.2%
Other values (3655) 4317
95.7%
ValueCountFrequency (%)
124.7330033 1
< 0.1%
125.4090517223 1
< 0.1%
125.4179261107 1
< 0.1%
125.4236374323 1
< 0.1%
125.4268830737 1
< 0.1%
125.4645809262 1
< 0.1%
125.7012498 1
< 0.1%
125.8261498421 1
< 0.1%
125.8429338362 1
< 0.1%
125.8524943062 1
< 0.1%
ValueCountFrequency (%)
129.5616042 1
< 0.1%
129.5614562 1
< 0.1%
129.5491833764 1
< 0.1%
129.5365101 1
< 0.1%
129.5356179 1
< 0.1%
129.5192332 1
< 0.1%
129.5135782 1
< 0.1%
129.5131284 1
< 0.1%
129.5029087 1
< 0.1%
129.4982682 1
< 0.1%
Distinct1245
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Memory size35.4 KiB
Minimum1900-01-01 00:00:00
Maximum2023-12-05 00:00:00
2024-05-11T10:40:18.333982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:40:19.149576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.4 KiB
사유
3345 
국유
1163 
국유+사유
 
2

Length

Max length5
Median length2
Mean length2.0013304
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사유
2nd row사유
3rd row국유
4th row사유
5th row사유

Common Values

ValueCountFrequency (%)
사유 3345
74.2%
국유 1163
 
25.8%
국유+사유 2
 
< 0.1%

Length

2024-05-11T10:40:19.784573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:40:20.292693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사유 3345
74.2%
국유 1163
 
25.8%
국유+사유 2
 
< 0.1%

소유자명
Text

MISSING 

Distinct1690
Distinct (%)58.7%
Missing1630
Missing (%)36.1%
Memory size35.4 KiB
2024-05-11T10:40:21.054932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length5.8659722
Min length2

Characters and Unicode

Total characters16894
Distinct characters392
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1252 ?
Unique (%)43.5%

Sample

1st row화림사
2nd row전의이씨도사공파종중
3rd row마상학
4th row마상학
5th row마상혜
ValueCountFrequency (%)
미상 133
 
3.7%
종중 96
 
2.7%
월정사 58
 
1.6%
36
 
1.0%
경기도 30
 
0.8%
진주시 28
 
0.8%
문중 23
 
0.6%
임실군수 20
 
0.6%
경상남도 20
 
0.6%
창녕군청 18
 
0.5%
Other values (1844) 3138
87.2%
2024-05-11T10:40:22.316514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
831
 
4.9%
720
 
4.3%
655
 
3.9%
602
 
3.6%
389
 
2.3%
388
 
2.3%
380
 
2.2%
369
 
2.2%
312
 
1.8%
277
 
1.6%
Other values (382) 11971
70.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15796
93.5%
Space Separator 720
 
4.3%
Close Punctuation 130
 
0.8%
Open Punctuation 129
 
0.8%
Decimal Number 60
 
0.4%
Other Punctuation 35
 
0.2%
Math Symbol 9
 
0.1%
Uppercase Letter 8
 
< 0.1%
Other Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
831
 
5.3%
655
 
4.1%
602
 
3.8%
389
 
2.5%
388
 
2.5%
380
 
2.4%
369
 
2.3%
312
 
2.0%
277
 
1.8%
276
 
1.7%
Other values (358) 11317
71.6%
Decimal Number
ValueCountFrequency (%)
1 19
31.7%
2 12
20.0%
3 11
18.3%
4 7
 
11.7%
6 3
 
5.0%
0 3
 
5.0%
5 2
 
3.3%
7 2
 
3.3%
8 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 15
42.9%
* 13
37.1%
: 5
 
14.3%
/ 1
 
2.9%
· 1
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
C 2
25.0%
B 2
25.0%
D 2
25.0%
H 1
12.5%
S 1
12.5%
Space Separator
ValueCountFrequency (%)
720
100.0%
Close Punctuation
ValueCountFrequency (%)
) 130
100.0%
Open Punctuation
ValueCountFrequency (%)
( 129
100.0%
Math Symbol
ValueCountFrequency (%)
+ 9
100.0%
Other Symbol
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15802
93.5%
Common 1083
 
6.4%
Latin 8
 
< 0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
831
 
5.3%
655
 
4.1%
602
 
3.8%
389
 
2.5%
388
 
2.5%
380
 
2.4%
369
 
2.3%
312
 
2.0%
277
 
1.8%
276
 
1.7%
Other values (358) 11323
71.7%
Common
ValueCountFrequency (%)
720
66.5%
) 130
 
12.0%
( 129
 
11.9%
1 19
 
1.8%
, 15
 
1.4%
* 13
 
1.2%
2 12
 
1.1%
3 11
 
1.0%
+ 9
 
0.8%
4 7
 
0.6%
Other values (8) 18
 
1.7%
Latin
ValueCountFrequency (%)
C 2
25.0%
B 2
25.0%
D 2
25.0%
H 1
12.5%
S 1
12.5%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15795
93.5%
ASCII 1090
 
6.5%
None 8
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
831
 
5.3%
655
 
4.1%
602
 
3.8%
389
 
2.5%
388
 
2.5%
380
 
2.4%
369
 
2.3%
312
 
2.0%
277
 
1.8%
276
 
1.7%
Other values (357) 11316
71.6%
ASCII
ValueCountFrequency (%)
720
66.1%
) 130
 
11.9%
( 129
 
11.8%
1 19
 
1.7%
, 15
 
1.4%
* 13
 
1.2%
2 12
 
1.1%
3 11
 
1.0%
+ 9
 
0.8%
4 7
 
0.6%
Other values (12) 25
 
2.3%
None
ValueCountFrequency (%)
7
87.5%
· 1
 
12.5%
CJK
ValueCountFrequency (%)
1
100.0%

규모
Text

MISSING 

Distinct636
Distinct (%)27.2%
Missing2176
Missing (%)48.2%
Memory size35.4 KiB
2024-05-11T10:40:23.238864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length2
Mean length3.8106255
Min length1

Characters and Unicode

Total characters8894
Distinct characters235
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

Unique501 ?
Unique (%)21.5%

Sample

1st row1기
2nd row1곽
3rd row1곽
4th row1곽
5th row1곽
ValueCountFrequency (%)
1동 526
 
18.7%
1기 343
 
12.2%
미상 116
 
4.1%
일원 72
 
2.6%
1곽 70
 
2.5%
1점 66
 
2.3%
2기 43
 
1.5%
1구 41
 
1.5%
2동 41
 
1.5%
1식 39
 
1.4%
Other values (773) 1459
51.8%
2024-05-11T10:40:24.545883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1727
19.4%
668
 
7.5%
512
 
5.8%
484
 
5.4%
2 365
 
4.1%
0 319
 
3.6%
236
 
2.7%
3 223
 
2.5%
5 210
 
2.4%
4 200
 
2.2%
Other values (225) 3950
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3776
42.5%
Decimal Number 3621
40.7%
Space Separator 484
 
5.4%
Other Punctuation 266
 
3.0%
Other Symbol 240
 
2.7%
Lowercase Letter 218
 
2.5%
Math Symbol 166
 
1.9%
Open Punctuation 57
 
0.6%
Close Punctuation 57
 
0.6%
Uppercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
668
 
17.7%
512
 
13.6%
135
 
3.6%
122
 
3.2%
117
 
3.1%
112
 
3.0%
99
 
2.6%
75
 
2.0%
75
 
2.0%
66
 
1.7%
Other values (191) 1795
47.5%
Decimal Number
ValueCountFrequency (%)
1 1727
47.7%
2 365
 
10.1%
0 319
 
8.8%
3 223
 
6.2%
5 210
 
5.8%
4 200
 
5.5%
6 174
 
4.8%
7 154
 
4.3%
8 130
 
3.6%
9 119
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
m 125
57.3%
c 76
34.9%
w 6
 
2.8%
h 6
 
2.8%
k 3
 
1.4%
p 1
 
0.5%
x 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 119
44.7%
. 97
36.5%
: 40
 
15.0%
/ 10
 
3.8%
Other Symbol
ValueCountFrequency (%)
236
98.3%
3
 
1.2%
1
 
0.4%
Math Symbol
ValueCountFrequency (%)
+ 112
67.5%
× 50
30.1%
= 4
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
L 2
40.0%
X 1
20.0%
Space Separator
ValueCountFrequency (%)
484
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4895
55.0%
Hangul 3776
42.5%
Latin 223
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
668
 
17.7%
512
 
13.6%
135
 
3.6%
122
 
3.2%
117
 
3.1%
112
 
3.0%
99
 
2.6%
75
 
2.0%
75
 
2.0%
66
 
1.7%
Other values (191) 1795
47.5%
Common
ValueCountFrequency (%)
1 1727
35.3%
484
 
9.9%
2 365
 
7.5%
0 319
 
6.5%
236
 
4.8%
3 223
 
4.6%
5 210
 
4.3%
4 200
 
4.1%
6 174
 
3.6%
7 154
 
3.1%
Other values (14) 803
16.4%
Latin
ValueCountFrequency (%)
m 125
56.1%
c 76
34.1%
w 6
 
2.7%
h 6
 
2.7%
k 3
 
1.3%
B 2
 
0.9%
L 2
 
0.9%
p 1
 
0.4%
X 1
 
0.4%
x 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4828
54.3%
Hangul 3776
42.5%
CJK Compat 240
 
2.7%
None 50
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1727
35.8%
484
 
10.0%
2 365
 
7.6%
0 319
 
6.6%
3 223
 
4.6%
5 210
 
4.3%
4 200
 
4.1%
6 174
 
3.6%
7 154
 
3.2%
8 130
 
2.7%
Other values (20) 842
17.4%
Hangul
ValueCountFrequency (%)
668
 
17.7%
512
 
13.6%
135
 
3.6%
122
 
3.2%
117
 
3.1%
112
 
3.0%
99
 
2.6%
75
 
2.0%
75
 
2.0%
66
 
1.7%
Other values (191) 1795
47.5%
CJK Compat
ValueCountFrequency (%)
236
98.3%
3
 
1.2%
1
 
0.4%
None
ValueCountFrequency (%)
× 50
100.0%

조성시대
Text

MISSING 

Distinct562
Distinct (%)21.4%
Missing1886
Missing (%)41.8%
Memory size35.4 KiB
2024-05-11T10:40:25.353489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length4.2370427
Min length2

Characters and Unicode

Total characters11118
Distinct characters134
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique400 ?
Unique (%)15.2%

Sample

1st row조선시대
2nd row조선시대
3rd row조선시대
4th row일제강점기
5th row조선시대
ValueCountFrequency (%)
조선시대 724
25.5%
조선 456
 
16.1%
고려시대 80
 
2.8%
조선후기 79
 
2.8%
근대 73
 
2.6%
건립 71
 
2.5%
고려 67
 
2.4%
일제강점기 52
 
1.8%
미상 44
 
1.6%
삼국시대 39
 
1.4%
Other values (543) 1151
40.6%
2024-05-11T10:40:26.956146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1363
 
12.3%
1360
 
12.2%
1186
 
10.7%
953
 
8.6%
1 763
 
6.9%
9 466
 
4.2%
462
 
4.2%
328
 
3.0%
0 289
 
2.6%
8 220
 
2.0%
Other values (124) 3728
33.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7888
70.9%
Decimal Number 2711
 
24.4%
Space Separator 212
 
1.9%
Open Punctuation 105
 
0.9%
Close Punctuation 105
 
0.9%
Math Symbol 47
 
0.4%
Other Punctuation 28
 
0.3%
Dash Punctuation 16
 
0.1%
Lowercase Letter 4
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1363
17.3%
1360
17.2%
1186
15.0%
953
12.1%
462
 
5.9%
328
 
4.2%
197
 
2.5%
187
 
2.4%
117
 
1.5%
107
 
1.4%
Other values (100) 1628
20.6%
Decimal Number
ValueCountFrequency (%)
1 763
28.1%
9 466
17.2%
0 289
 
10.7%
8 220
 
8.1%
6 186
 
6.9%
2 182
 
6.7%
7 173
 
6.4%
5 170
 
6.3%
4 139
 
5.1%
3 123
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 13
46.4%
, 10
35.7%
/ 4
 
14.3%
· 1
 
3.6%
Math Symbol
ValueCountFrequency (%)
~ 27
57.4%
+ 14
29.8%
6
 
12.8%
Lowercase Letter
ValueCountFrequency (%)
a 2
50.0%
r 2
50.0%
Space Separator
ValueCountFrequency (%)
212
100.0%
Open Punctuation
ValueCountFrequency (%)
( 105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7888
70.9%
Common 3224
29.0%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1363
17.3%
1360
17.2%
1186
15.0%
953
12.1%
462
 
5.9%
328
 
4.2%
197
 
2.5%
187
 
2.4%
117
 
1.5%
107
 
1.4%
Other values (100) 1628
20.6%
Common
ValueCountFrequency (%)
1 763
23.7%
9 466
14.5%
0 289
 
9.0%
8 220
 
6.8%
212
 
6.6%
6 186
 
5.8%
2 182
 
5.6%
7 173
 
5.4%
5 170
 
5.3%
4 139
 
4.3%
Other values (11) 424
13.2%
Latin
ValueCountFrequency (%)
M 2
33.3%
a 2
33.3%
r 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7888
70.9%
ASCII 3223
29.0%
None 7
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1363
17.3%
1360
17.2%
1186
15.0%
953
12.1%
462
 
5.9%
328
 
4.2%
197
 
2.5%
187
 
2.4%
117
 
1.5%
107
 
1.4%
Other values (100) 1628
20.6%
ASCII
ValueCountFrequency (%)
1 763
23.7%
9 466
14.5%
0 289
 
9.0%
8 220
 
6.8%
212
 
6.6%
6 186
 
5.8%
2 182
 
5.6%
7 173
 
5.4%
5 170
 
5.3%
4 139
 
4.3%
Other values (12) 423
13.1%
None
ValueCountFrequency (%)
6
85.7%
· 1
 
14.3%

이미지정보
Text

MISSING 

Distinct422
Distinct (%)68.6%
Missing3895
Missing (%)86.4%
Memory size35.4 KiB
2024-05-11T10:40:27.581163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length250
Median length205
Mean length107.46829
Min length8

Characters and Unicode

Total characters66093
Distinct characters113
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique412 ?
Unique (%)67.0%

Sample

1st rowhttps://blog.naver.com/il0202/222199515693
2nd rowhttps://www.heritage.go.kr/heri/cul/culSelectDetail.do?culPageNo=1&region=1&searchCondition=ECA784ECA3BC+EB8C80ECB29CEBA6AC+EC9E85EC849D&searchCondition2=&ccbaKdcd=31&ccbaAsno=01770000&ccbaCtcd=38&ccbaCpno=3413801770000&ccbaCndt=&ccbaLcto=&stCcbaAsdt
3rd rowhttps://www.heritage.go.kr/heri/cul/culSelectDetail.do?culPageNo=1&region=1&searchCondition=ECA784ECA3BC+EB9190EBACB8EBA6AC+EC9DB4ECA095ED919CEC849D&searchCondition2=&ccbaKdcd=31&ccbaAsno=01790000&ccbaCtcd=38&ccbaCpno=3413801790000&ccbaCndt=&ccbaLcto
4th rowhttps://www.heritage.go.kr/heri/cul/culSelectDetail.do?culPageNo=1&region=1&searchCondition=ECA784ECA3BC+EB8389ECA095EBA6AC+EC9DB4ECA095ED919CEC849D&searchCondition2=&ccbaKdcd=31&ccbaAsno=01800000&ccbaCtcd=38&ccbaCpno=3413801800000&ccbaCndt=&ccbaLcto
5th rowhttps://www.heritage.go.kr/heri/cul/culSelectDetail.do?culPageNo=1&region=1&searchCondition=ECA784ECA3BC+EBB680EC82ACECA095&searchCondition2=&ccbaKdcd=31&ccbaAsno=01970000&ccbaCtcd=38&ccbaCpno=3413801970000&ccbaCndt=&ccbaLcto=&stCcbaAsdt=&endCcbaAsdt
ValueCountFrequency (%)
https://www.yyg.go.kr/tour/attractions/cultural_relics 116
 
17.9%
참고 33
 
5.1%
문화재정보 33
 
5.1%
http://tour.yeoncheon.go.kr 30
 
4.6%
http://tour.jeonju.go.kr 12
 
1.9%
https://www.heritage.go.kr/heri/cul/culselectdetail.do?culpageno=1&region=1&searchcondition=ed9884ec9e90ecb49ded86b5&searchcondition2=&ccbakdcd=12&ccbaasno=08850000&ccbactcd=38&ccbacpno=1123808850000&ccbacndt=&ccbalcto=&stccbaasdt=&endccbaasdt=&heade 2
 
0.3%
https://blog.naver.com/press2026/222595995721 2
 
0.3%
https://terms.naver.com/entry.naver?docid=1324778&cid=40942&categoryid=38271 2
 
0.3%
https://www.jinju.go.kr/02793/02258/02283.web?amode=view&idx=175 2
 
0.3%
http://gangneung.grandculture.net/gangneung/toc/gc00303286 2
 
0.3%
Other values (413) 414
63.9%
2024-05-11T10:40:28.909111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 3768
 
5.7%
e 3330
 
5.0%
c 3306
 
5.0%
o 3064
 
4.6%
/ 3023
 
4.6%
r 2809
 
4.3%
0 2636
 
4.0%
a 2613
 
4.0%
n 2179
 
3.3%
. 2139
 
3.2%
Other values (103) 37226
56.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 38664
58.5%
Decimal Number 10526
 
15.9%
Other Punctuation 7831
 
11.8%
Uppercase Letter 5869
 
8.9%
Math Symbol 2176
 
3.3%
Connector Punctuation 489
 
0.7%
Other Letter 277
 
0.4%
Dash Punctuation 227
 
0.3%
Space Separator 33
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
37
13.4%
34
12.3%
33
11.9%
33
11.9%
33
11.9%
33
11.9%
33
11.9%
3
 
1.1%
3
 
1.1%
2
 
0.7%
Other values (28) 33
11.9%
Lowercase Letter
ValueCountFrequency (%)
t 3768
 
9.7%
e 3330
 
8.6%
c 3306
 
8.6%
o 3064
 
7.9%
r 2809
 
7.3%
a 2613
 
6.8%
n 2179
 
5.6%
s 2048
 
5.3%
w 1762
 
4.6%
i 1688
 
4.4%
Other values (16) 12097
31.3%
Uppercase Letter
ValueCountFrequency (%)
C 1525
26.0%
E 900
15.3%
A 803
13.7%
B 733
12.5%
D 343
 
5.8%
N 249
 
4.2%
P 219
 
3.7%
S 211
 
3.6%
I 192
 
3.3%
K 146
 
2.5%
Other values (16) 548
 
9.3%
Decimal Number
ValueCountFrequency (%)
0 2636
25.0%
2 1376
13.1%
1 1351
12.8%
8 1214
11.5%
9 887
 
8.4%
3 863
 
8.2%
4 709
 
6.7%
5 626
 
5.9%
7 461
 
4.4%
6 403
 
3.8%
Other Punctuation
ValueCountFrequency (%)
/ 3023
38.6%
. 2139
27.3%
& 1719
22.0%
: 582
 
7.4%
? 351
 
4.5%
; 11
 
0.1%
, 6
 
0.1%
Math Symbol
ValueCountFrequency (%)
= 2001
92.0%
+ 175
 
8.0%
Connector Punctuation
ValueCountFrequency (%)
_ 489
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 227
100.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Other Symbol
ValueCountFrequency (%)
® 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 44533
67.4%
Common 21283
32.2%
Hangul 277
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 3768
 
8.5%
e 3330
 
7.5%
c 3306
 
7.4%
o 3064
 
6.9%
r 2809
 
6.3%
a 2613
 
5.9%
n 2179
 
4.9%
s 2048
 
4.6%
w 1762
 
4.0%
i 1688
 
3.8%
Other values (42) 17966
40.3%
Hangul
ValueCountFrequency (%)
37
13.4%
34
12.3%
33
11.9%
33
11.9%
33
11.9%
33
11.9%
33
11.9%
3
 
1.1%
3
 
1.1%
2
 
0.7%
Other values (28) 33
11.9%
Common
ValueCountFrequency (%)
/ 3023
14.2%
0 2636
12.4%
. 2139
10.1%
= 2001
9.4%
& 1719
8.1%
2 1376
 
6.5%
1 1351
 
6.3%
8 1214
 
5.7%
9 887
 
4.2%
3 863
 
4.1%
Other values (13) 4074
19.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65815
99.6%
Hangul 277
 
0.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 3768
 
5.7%
e 3330
 
5.1%
c 3306
 
5.0%
o 3064
 
4.7%
/ 3023
 
4.6%
r 2809
 
4.3%
0 2636
 
4.0%
a 2613
 
4.0%
n 2179
 
3.3%
. 2139
 
3.3%
Other values (64) 36948
56.1%
Hangul
ValueCountFrequency (%)
37
13.4%
34
12.3%
33
11.9%
33
11.9%
33
11.9%
33
11.9%
33
11.9%
3
 
1.1%
3
 
1.1%
2
 
0.7%
Other values (28) 33
11.9%
None
ValueCountFrequency (%)
® 1
100.0%
Distinct3972
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Memory size35.4 KiB
2024-05-11T10:40:29.857745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length538
Mean length115.51264
Min length2

Characters and Unicode

Total characters520962
Distinct characters2810
Distinct categories17 ?
Distinct scripts5 ?
Distinct blocks14 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3645 ?
Unique (%)80.8%

Sample

1st row청동기시대 청주지역의 문화상을 연구하는데 귀중한 자료임
2nd row백제가 청주지역 서쪽을 지키기 위해 쌓은 산성임
3rd row삼국시대 청주 서쪽을 방어하기 위해 내외성으로 쌓여진 산성임
4th row삼국시대 청주 서북쪽을 방어하기 위해 쌓여진 산성임
5th row백제가 청주지역 북쪽을 지키기 위해 쌓은 산성임
ValueCountFrequency (%)
있다 1419
 
1.2%
있는 852
 
0.7%
603
 
0.5%
위해 504
 
0.4%
조선 437
 
0.4%
434
 
0.4%
것으로 430
 
0.4%
406
 
0.4%
있으며 405
 
0.4%
있음 343
 
0.3%
Other values (44604) 108537
94.9%
2024-05-11T10:40:31.508941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
110363
 
21.2%
10748
 
2.1%
8702
 
1.7%
8339
 
1.6%
. 7101
 
1.4%
7087
 
1.4%
6691
 
1.3%
6554
 
1.3%
1 6122
 
1.2%
6084
 
1.2%
Other values (2800) 343171
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 361857
69.5%
Space Separator 110363
 
21.2%
Decimal Number 23661
 
4.5%
Other Punctuation 12529
 
2.4%
Close Punctuation 4674
 
0.9%
Open Punctuation 4672
 
0.9%
Lowercase Letter 989
 
0.2%
Math Symbol 819
 
0.2%
Final Punctuation 389
 
0.1%
Other Symbol 374
 
0.1%
Other values (7) 635
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10748
 
3.0%
8702
 
2.4%
8339
 
2.3%
7087
 
2.0%
6691
 
1.8%
6554
 
1.8%
6084
 
1.7%
5595
 
1.5%
5444
 
1.5%
5078
 
1.4%
Other values (2685) 291535
80.6%
Lowercase Letter
ValueCountFrequency (%)
m 688
69.6%
c 166
 
16.8%
e 24
 
2.4%
k 15
 
1.5%
r 14
 
1.4%
a 12
 
1.2%
t 9
 
0.9%
p 8
 
0.8%
i 8
 
0.8%
s 8
 
0.8%
Other values (11) 37
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
M 11
15.9%
C 10
14.5%
B 7
10.1%
R 6
8.7%
T 5
 
7.2%
A 4
 
5.8%
Y 3
 
4.3%
P 3
 
4.3%
S 3
 
4.3%
U 3
 
4.3%
Other values (10) 14
20.3%
Other Punctuation
ValueCountFrequency (%)
. 7101
56.7%
, 4320
34.5%
· 949
 
7.6%
: 47
 
0.4%
? 46
 
0.4%
/ 34
 
0.3%
' 10
 
0.1%
* 9
 
0.1%
; 7
 
0.1%
3
 
< 0.1%
Other values (2) 3
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 6122
25.9%
2 2578
10.9%
9 2223
 
9.4%
0 2099
 
8.9%
5 1970
 
8.3%
3 1909
 
8.1%
8 1788
 
7.6%
6 1780
 
7.5%
4 1668
 
7.0%
7 1524
 
6.4%
Math Symbol
ValueCountFrequency (%)
~ 379
46.3%
161
19.7%
+ 109
 
13.3%
< 54
 
6.6%
> 53
 
6.5%
29
 
3.5%
× 26
 
3.2%
6
 
0.7%
1
 
0.1%
1
 
0.1%
Other Symbol
ValueCountFrequency (%)
174
46.5%
145
38.8%
21
 
5.6%
17
 
4.5%
° 10
 
2.7%
3
 
0.8%
2
 
0.5%
2
 
0.5%
Other Number
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Close Punctuation
ValueCountFrequency (%)
) 4340
92.9%
236
 
5.0%
52
 
1.1%
] 39
 
0.8%
5
 
0.1%
1
 
< 0.1%
1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 4340
92.9%
234
 
5.0%
51
 
1.1%
[ 40
 
0.9%
5
 
0.1%
1
 
< 0.1%
1
 
< 0.1%
Modifier Symbol
ValueCountFrequency (%)
` 2
50.0%
1
25.0%
´ 1
25.0%
Final Punctuation
ValueCountFrequency (%)
347
89.2%
42
 
10.8%
Initial Punctuation
ValueCountFrequency (%)
266
86.1%
43
 
13.9%
Dash Punctuation
ValueCountFrequency (%)
- 239
99.6%
1
 
0.4%
Space Separator
ValueCountFrequency (%)
110363
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 351893
67.5%
Common 158045
30.3%
Han 9964
 
1.9%
Latin 1058
 
0.2%
Greek 2
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
109
 
1.1%
104
 
1.0%
89
 
0.9%
88
 
0.9%
76
 
0.8%
76
 
0.8%
75
 
0.8%
75
 
0.8%
73
 
0.7%
68
 
0.7%
Other values (1578) 9131
91.6%
Hangul
ValueCountFrequency (%)
10748
 
3.1%
8702
 
2.5%
8339
 
2.4%
7087
 
2.0%
6691
 
1.9%
6554
 
1.9%
6084
 
1.7%
5595
 
1.6%
5444
 
1.5%
5078
 
1.4%
Other values (1097) 281571
80.0%
Common
ValueCountFrequency (%)
110363
69.8%
. 7101
 
4.5%
1 6122
 
3.9%
) 4340
 
2.7%
( 4340
 
2.7%
, 4320
 
2.7%
2 2578
 
1.6%
9 2223
 
1.4%
0 2099
 
1.3%
5 1970
 
1.2%
Other values (63) 12589
 
8.0%
Latin
ValueCountFrequency (%)
m 688
65.0%
c 166
 
15.7%
e 24
 
2.3%
k 15
 
1.4%
r 14
 
1.3%
a 12
 
1.1%
M 11
 
1.0%
C 10
 
0.9%
t 9
 
0.9%
p 8
 
0.8%
Other values (30) 101
 
9.5%
Greek
ValueCountFrequency (%)
1
50.0%
α 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 351785
67.5%
ASCII 156252
30.0%
CJK 9624
 
1.8%
None 1607
 
0.3%
Punctuation 702
 
0.1%
CJK Compat Ideographs 340
 
0.1%
CJK Compat 183
 
< 0.1%
Geometric Shapes 179
 
< 0.1%
Math Operators 163
 
< 0.1%
Compat Jamo 108
 
< 0.1%
Other values (4) 19
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
110363
70.6%
. 7101
 
4.5%
1 6122
 
3.9%
) 4340
 
2.8%
( 4340
 
2.8%
, 4320
 
2.8%
2 2578
 
1.6%
9 2223
 
1.4%
0 2099
 
1.3%
5 1970
 
1.3%
Other values (59) 10796
 
6.9%
Hangul
ValueCountFrequency (%)
10748
 
3.1%
8702
 
2.5%
8339
 
2.4%
7087
 
2.0%
6691
 
1.9%
6554
 
1.9%
6084
 
1.7%
5595
 
1.6%
5444
 
1.5%
5078
 
1.4%
Other values (1087) 281463
80.0%
None
ValueCountFrequency (%)
· 949
59.1%
236
 
14.7%
234
 
14.6%
52
 
3.2%
51
 
3.2%
29
 
1.8%
× 26
 
1.6%
° 10
 
0.6%
5
 
0.3%
5
 
0.3%
Other values (9) 10
 
0.6%
Punctuation
ValueCountFrequency (%)
347
49.4%
266
37.9%
43
 
6.1%
42
 
6.0%
3
 
0.4%
1
 
0.1%
Geometric Shapes
ValueCountFrequency (%)
174
97.2%
3
 
1.7%
2
 
1.1%
Math Operators
ValueCountFrequency (%)
161
98.8%
1
 
0.6%
1
 
0.6%
CJK Compat
ValueCountFrequency (%)
145
79.2%
21
 
11.5%
17
 
9.3%
CJK
ValueCountFrequency (%)
109
 
1.1%
104
 
1.1%
89
 
0.9%
88
 
0.9%
76
 
0.8%
75
 
0.8%
75
 
0.8%
68
 
0.7%
65
 
0.7%
65
 
0.7%
Other values (1517) 8810
91.5%
CJK Compat Ideographs
ValueCountFrequency (%)
76
22.4%
73
21.5%
14
 
4.1%
12
 
3.5%
11
 
3.2%
10
 
2.9%
10
 
2.9%
9
 
2.6%
8
 
2.4%
8
 
2.4%
Other values (51) 109
32.1%
Compat Jamo
ValueCountFrequency (%)
52
48.1%
19
 
17.6%
14
 
13.0%
8
 
7.4%
7
 
6.5%
4
 
3.7%
1
 
0.9%
1
 
0.9%
1
 
0.9%
1
 
0.9%
Arrows
ValueCountFrequency (%)
6
100.0%
Letterlike Symbols
ValueCountFrequency (%)
2
66.7%
1
33.3%
Number Forms
ValueCountFrequency (%)
2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Distinct360
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size35.4 KiB
2024-05-11T10:40:32.225132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.028825
Min length9

Characters and Unicode

Total characters54250
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

Unique132 ?
Unique (%)2.9%

Sample

1st row043-201-2437
2nd row043-201-2437
3rd row043-201-2437
4th row043-201-2437
5th row043-201-2437
ValueCountFrequency (%)
064-710-6702 359
 
8.0%
043-201-2437 201
 
4.5%
055-749-8579 139
 
3.1%
041-830-2622 125
 
2.8%
063-640-2315 120
 
2.7%
054-840-5227 118
 
2.6%
054-680-6422 116
 
2.6%
033-370-2931 78
 
1.7%
044-300-4515 73
 
1.6%
061-430-3362 71
 
1.6%
Other values (350) 3110
69.0%
2024-05-11T10:40:33.406943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9156
16.9%
- 9019
16.6%
3 6021
11.1%
2 4961
9.1%
4 4870
9.0%
6 4416
8.1%
5 4203
7.7%
1 4096
7.6%
7 3377
 
6.2%
8 2405
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 45231
83.4%
Dash Punctuation 9019
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9156
20.2%
3 6021
13.3%
2 4961
11.0%
4 4870
10.8%
6 4416
9.8%
5 4203
9.3%
1 4096
9.1%
7 3377
 
7.5%
8 2405
 
5.3%
9 1726
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 9019
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54250
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9156
16.9%
- 9019
16.6%
3 6021
11.1%
2 4961
9.1%
4 4870
9.0%
6 4416
8.1%
5 4203
7.7%
1 4096
7.6%
7 3377
 
6.2%
8 2405
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9156
16.9%
- 9019
16.6%
3 6021
11.1%
2 4961
9.1%
4 4870
9.0%
6 4416
8.1%
5 4203
7.7%
1 4096
7.6%
7 3377
 
6.2%
8 2405
 
4.4%
Distinct743
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Memory size35.4 KiB
2024-05-11T10:40:34.247443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length8.9532151
Min length2

Characters and Unicode

Total characters40379
Distinct characters321
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique463 ?
Unique (%)10.3%

Sample

1st row충청북도 청주시
2nd row충청북도 청주시
3rd row충청북도 청주시
4th row충청북도 청주시
5th row충청북도 청주시
ValueCountFrequency (%)
경기도 509
 
6.0%
제주특별자치도 448
 
5.3%
세계유산본부 448
 
5.3%
충청남도 415
 
4.9%
전라남도 378
 
4.5%
충청북도 366
 
4.3%
경상북도 302
 
3.6%
전라북도 212
 
2.5%
청주시 201
 
2.4%
전북특별자치도 146
 
1.7%
Other values (810) 5021
59.4%
2024-05-11T10:40:35.575600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3938
 
9.8%
3502
 
8.7%
3224
 
8.0%
1795
 
4.4%
1502
 
3.7%
1090
 
2.7%
1088
 
2.7%
1065
 
2.6%
977
 
2.4%
835
 
2.1%
Other values (311) 21363
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36367
90.1%
Space Separator 3940
 
9.8%
Close Punctuation 20
 
< 0.1%
Open Punctuation 20
 
< 0.1%
Other Punctuation 16
 
< 0.1%
Decimal Number 6
 
< 0.1%
Uppercase Letter 6
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3502
 
9.6%
3224
 
8.9%
1795
 
4.9%
1502
 
4.1%
1090
 
3.0%
1088
 
3.0%
1065
 
2.9%
977
 
2.7%
835
 
2.3%
805
 
2.2%
Other values (294) 20484
56.3%
Other Punctuation
ValueCountFrequency (%)
* 13
81.2%
: 1
 
6.2%
· 1
 
6.2%
, 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
3 2
33.3%
4 1
16.7%
1 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
D 2
33.3%
B 2
33.3%
S 1
16.7%
H 1
16.7%
Space Separator
ValueCountFrequency (%)
3938
99.9%
  2
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36367
90.1%
Common 4006
 
9.9%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3502
 
9.6%
3224
 
8.9%
1795
 
4.9%
1502
 
4.1%
1090
 
3.0%
1088
 
3.0%
1065
 
2.9%
977
 
2.7%
835
 
2.3%
805
 
2.2%
Other values (294) 20484
56.3%
Common
ValueCountFrequency (%)
3938
98.3%
) 20
 
0.5%
( 20
 
0.5%
* 13
 
0.3%
+ 4
 
0.1%
  2
 
< 0.1%
2 2
 
< 0.1%
3 2
 
< 0.1%
: 1
 
< 0.1%
· 1
 
< 0.1%
Other values (3) 3
 
0.1%
Latin
ValueCountFrequency (%)
D 2
33.3%
B 2
33.3%
S 1
16.7%
H 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36367
90.1%
ASCII 4009
 
9.9%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3938
98.2%
) 20
 
0.5%
( 20
 
0.5%
* 13
 
0.3%
+ 4
 
0.1%
2 2
 
< 0.1%
3 2
 
< 0.1%
D 2
 
< 0.1%
B 2
 
< 0.1%
: 1
 
< 0.1%
Other values (5) 5
 
0.1%
Hangul
ValueCountFrequency (%)
3502
 
9.6%
3224
 
8.9%
1795
 
4.9%
1502
 
4.1%
1090
 
3.0%
1088
 
3.0%
1065
 
2.9%
977
 
2.7%
835
 
2.3%
805
 
2.2%
Other values (294) 20484
56.3%
None
ValueCountFrequency (%)
  2
66.7%
· 1
33.3%
Distinct120
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size35.4 KiB
Minimum2018-05-15 00:00:00
Maximum2024-04-26 00:00:00
2024-05-11T10:40:36.129261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:40:36.747310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Real number (ℝ)

HIGH CORRELATION 

Distinct161
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4855600.8
Minimum3030000
Maximum6500000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.8 KiB
2024-05-11T10:40:37.228346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3030000
5-th percentile3510500
Q14301000
median4761000
Q35310000
95-th percentile6500000
Maximum6500000
Range3470000
Interquartile range (IQR)1009000

Descriptive statistics

Standard deviation809243.92
Coefficient of variation (CV)0.16666195
Kurtosis-0.15807279
Mean4855600.8
Median Absolute Deviation (MAD)490000
Skewness0.3119517
Sum2.189876 × 1010
Variance6.5487572 × 1011
MonotonicityNot monotonic
2024-05-11T10:40:37.686271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6500000 448
 
9.9%
5310000 219
 
4.9%
5710000 201
 
4.5%
4700000 131
 
2.9%
4570000 125
 
2.8%
5070000 125
 
2.8%
5170000 116
 
2.6%
5690000 73
 
1.6%
4280000 72
 
1.6%
4920000 71
 
1.6%
Other values (151) 2929
64.9%
ValueCountFrequency (%)
3030000 2
 
< 0.1%
3090000 19
0.4%
3100000 14
0.3%
3110000 3
 
0.1%
3170000 2
 
< 0.1%
3200000 5
 
0.1%
3210000 7
 
0.2%
3220000 1
 
< 0.1%
3240000 3
 
0.1%
3280000 25
0.6%
ValueCountFrequency (%)
6500000 448
9.9%
5710000 201
4.5%
5700000 21
 
0.5%
5690000 73
 
1.6%
5680000 18
 
0.4%
5670000 4
 
0.1%
5600000 51
 
1.1%
5590000 15
 
0.3%
5570000 15
 
0.3%
5540000 18
 
0.4%
Distinct161
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size35.4 KiB
2024-05-11T10:40:38.434275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length7.9614191
Min length7

Characters and Unicode

Total characters35906
Distinct characters116
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

Unique6 ?
Unique (%)0.1%

Sample

1st row충청북도 청주시
2nd row충청북도 청주시
3rd row충청북도 청주시
4th row충청북도 청주시
5th row충청북도 청주시
ValueCountFrequency (%)
경기도 652
 
7.7%
전라남도 528
 
6.2%
충청남도 461
 
5.4%
제주특별자치도 448
 
5.3%
경상북도 413
 
4.9%
충청북도 369
 
4.3%
경상남도 348
 
4.1%
전라북도 331
 
3.9%
진주시 219
 
2.6%
전북특별자치도 215
 
2.5%
Other values (141) 4515
53.1%
2024-05-11T10:40:39.590301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4175
 
11.6%
3989
 
11.1%
2235
 
6.2%
1910
 
5.3%
1585
 
4.4%
1418
 
3.9%
1385
 
3.9%
1143
 
3.2%
1111
 
3.1%
1092
 
3.0%
Other values (106) 15863
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31917
88.9%
Space Separator 3989
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4175
 
13.1%
2235
 
7.0%
1910
 
6.0%
1585
 
5.0%
1418
 
4.4%
1385
 
4.3%
1143
 
3.6%
1111
 
3.5%
1092
 
3.4%
882
 
2.8%
Other values (105) 14981
46.9%
Space Separator
ValueCountFrequency (%)
3989
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31917
88.9%
Common 3989
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4175
 
13.1%
2235
 
7.0%
1910
 
6.0%
1585
 
5.0%
1418
 
4.4%
1385
 
4.3%
1143
 
3.6%
1111
 
3.5%
1092
 
3.4%
882
 
2.8%
Other values (105) 14981
46.9%
Common
ValueCountFrequency (%)
3989
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31917
88.9%
ASCII 3989
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4175
 
13.1%
2235
 
7.0%
1910
 
6.0%
1585
 
5.0%
1418
 
4.4%
1385
 
4.3%
1143
 
3.6%
1111
 
3.5%
1092
 
3.4%
882
 
2.8%
Other values (105) 14981
46.9%
ASCII
ValueCountFrequency (%)
3989
100.0%

Interactions

2024-05-11T10:39:58.473953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:39:56.359652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:39:57.400646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:39:58.837906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:39:56.714568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:39:57.740236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:39:59.205996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:39:57.053409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:39:58.067623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T10:40:39.845275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
향토문화유적구분위도경도소유주체구분제공기관코드
향토문화유적구분1.0000.5010.3880.1990.365
위도0.5011.0000.7040.3650.816
경도0.3880.7041.0000.2770.691
소유주체구분0.1990.3650.2771.0000.476
제공기관코드0.3650.8160.6910.4761.000
2024-05-11T10:40:40.167242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
향토문화유적구분소유주체구분
향토문화유적구분1.0000.153
소유주체구분0.1531.000
2024-05-11T10:40:40.451711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도제공기관코드향토문화유적구분소유주체구분
위도1.0000.317-0.5120.2310.236
경도0.3171.000-0.1330.1710.172
제공기관코드-0.512-0.1331.0000.2190.238
향토문화유적구분0.2310.1710.2191.0000.153
소유주체구분0.2360.1720.2380.1531.000

Missing values

2024-05-11T10:39:59.894782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T10:40:00.815291image/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.
2024-05-11T10:40:01.494733image/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

향토문화유적명문화유적지정번호향토문화유적구분향토문화유적종류소재지도로명주소소재지지번주소위도경도지정일자소유주체구분소유자명규모조성시대이미지정보향토문화유적소개관리기관전화번호관리기관명데이터기준일자제공기관코드제공기관명
0쌍청리선돌청주시 향토기념 제19호기념물석조물<NA>충청북도 청주시 흥덕구 오송읍 쌍청리 산49-536.637182127.3396422015-04-17사유<NA>1기<NA><NA>청동기시대 청주지역의 문화상을 연구하는데 귀중한 자료임043-201-2437충청북도 청주시2023-11-285710000충청북도 청주시
1병마산성청주시 향토기념 제20호기념물성터<NA>충청북도 청주시 흥덕구 오송읍 정중리 산3636.636811127.2958612015-04-17사유<NA>1곽<NA><NA>백제가 청주지역 서쪽을 지키기 위해 쌓은 산성임043-201-2437충청북도 청주시2023-11-285710000충청북도 청주시
2저산성청주시 향토기념 제21호기념물성터<NA>충청북도 청주시 흥덕구 강내면 저산리 산736.571924127.3735432015-04-17국유<NA>1곽<NA><NA>삼국시대 청주 서쪽을 방어하기 위해 내외성으로 쌓여진 산성임043-201-2437충청북도 청주시2023-11-285710000충청북도 청주시
3동림산성청주시 향토기념 제22호기념물성터<NA>충청북도 청주시 흥덕구 옥산면 장동리 산81-136.685616127.3045732015-04-17사유<NA>1곽<NA><NA>삼국시대 청주 서북쪽을 방어하기 위해 쌓여진 산성임043-201-2437충청북도 청주시2023-11-285710000충청북도 청주시
4목령산성청주시 향토기념 제23호기념물성터<NA>충청북도 청주시 청원구 오창읍 양지리 산20-136.737306127.4372482015-04-17사유<NA>1곽<NA><NA>백제가 청주지역 북쪽을 지키기 위해 쌓은 산성임043-201-2437충청북도 청주시2023-11-285710000충청북도 청주시
5노고성청주시 향토기념 제24호기념물성터<NA>충청북도 청주시 청원구 북이면 영하리 산4336.734079127.5756732015-04-17국유<NA>1곽<NA><NA>삼국시대말 신라가 보은에서 진천으로 가는 교통 요충지에 쌓은 산성임043-201-2437충청북도 청주시2023-11-285710000충청북도 청주시
6영하리 고분군청주시 향토기념 제25호기념물옛무덤<NA>충청북도 청주시 청원구 북이면 영하리 산4336.734079127.5756732015-04-17사유<NA>1곽<NA><NA>삼국시대 청주 북쪽의 문화를 연구하는데 귀중한 유적임043-201-2437충청북도 청주시2023-11-285710000충청북도 청주시
7낭비성청주시 향토기념 제26호기념물성터<NA>충청북도 청주시 청원구 북이면 부연리 산4136.748406127.5831042015-04-17국유<NA>1곽<NA><NA>삼국시대말 신라가 보은에서 진천으로 가는 교통 요충지에 쌓은 산성임043-201-2437충청북도 청주시2023-11-285710000충청북도 청주시
8용계리 고분청주시 향토기념 제27호기념물옛무덤<NA>충청북도 청주시 청원구 북이면 용계리 504-536.750333127.5148872015-04-17사유<NA>1곽<NA><NA>청주지역에서 희귀한 평지 봉토분으로 당시 문화를 연구하는데 귀중한 자료임043-201-2437충청북도 청주시2023-11-285710000충청북도 청주시
9문의 샘봉산성청주시 향토기념 제26호기념물성터<NA>충청북도 청주시 상당구 문의면 문덕리 산82-136.464721127.5310782017-03-17사유<NA>1곽<NA><NA>2가지 이상의 석재를 이용한 테뫼식 석축 산성으로 문의-회인간 교통로를 방어한 산성.043-201-2437충청북도 청주시2023-11-285710000충청북도 청주시
향토문화유적명문화유적지정번호향토문화유적구분향토문화유적종류소재지도로명주소소재지지번주소위도경도지정일자소유주체구분소유자명규모조성시대이미지정보향토문화유적소개관리기관전화번호관리기관명데이터기준일자제공기관코드제공기관명
4500불당골 마애여래입상제7호유형문화유적건조물<NA>울산광역시 동구 서부동 산3035.542853129.4172952018-01-30국유동구청1기8세기 후반(통일신라시대)<NA>통일신라시대 말기에 제작된 불상052-209-3324울산광역시 동구청2024-02-233710000울산광역시 동구
4501월성이씨 열행비제8호유형문화유적건조물울산광역시 동구 방어진순환도로1170(서부동)<NA>35.539286129.4207532018-01-30국유동구청1기1929년<NA>죽은 남편과 자녀 교육에 대한 열행비052-209-3324울산광역시 동구청2024-02-233710000울산광역시 동구
4502감목관 황경 영세불망비제9호유형문화유적건조물<NA>울산광역시 동구 서부동 676-135.534738129.4161592018-01-30국유동구청1기1755년<NA>울산 감목관 역임052-209-3324울산광역시 동구청2024-02-233710000울산광역시 동구
4503서천 당정리 고분군도지정기념물 제180호유형문화유적옛무덤<NA>충청남도 서천군 종천면 당정리 17-436.102777126.6552522010-02-22국유서천군<NA><NA><NA>당정리 고분군의 축조시기는 6세기 후반에서 7세기 전반을 중심으로 한 시기에 조성된 것으로 일부 지역에 대한 조사결과 백제시대 고분 21기가 상당히 밀집된 상태로 횡혈식석실분, 횡구식석실분, 수혈식석곽분 등 다양한 묘제가 확인되었으며 내부에서는 단경호, 직구단경호, 소형 병, 개배, 금동세환이식, 철부, 철겸, 방추차, 관못 등이 출토되었음. 백제 사비기는 분묘의 규격화나 유물의 박장화 등을 통한 묘장제까지 통제하는 등 지방통치 질서의 강화로 지역의 토착기반이 와해되는 시기임에도 불구하고 당정리 고분군은 등고선 방향의 장축방향, 유물의 부장 등 지역집단의 토착적 문화전통이 유지되고 있어 당시 서천지역의 고분 조영양상과 성격, 전통적 문화상을 밝히는데 중요한 자료이며, 또한 유사한 시기로 판단되는 서천 봉선리 유적과 추동리 유적과는 달리 중앙묘제적 성격보다는 지역의 토착적 성격이 강한 것으로 보아 서천지역 내에서도 백제시대 중앙과의 관련성이나, 문화적 이행과정에서 지역적 차이를 보이고 있어 당시 백제 지방통치의 성격을 고찰할 수 있는 중요한 유적으로 도 기념물로 지정하여 보존관리하고자 함.041-950-4764충청남도 서천군청2024-04-174580000충청남도 서천군
4504서천읍성도지정 문화재자료 제132호유형문화유적성터<NA>충청남도 서천군 서천읍 군사리 산4-136.079779126.6907571984-05-17국유서천군<NA><NA><NA>읍성이란 군이나 현의 주민을 보호하고, 군사적·행정적인 기능을 함께하는 성을 말한다.흙으로 쌓아 만든 서천읍성은 한 도읍 전체를 둘러싸고 군데군데 문을 만들어 바깥과 통하게 만든 성이다. 전설에 의하면 여자 100명이 성을 쌓고 장사 1명이 홍여다리를 짓는 내기를 하였는데, 여자들이 성을 다 쌓고 즐거운 함성을 지를 때 장사가 급히 마지막 돌을 끼워서 똑같이 끝나 무승부가 되었다고 한다.성벽의 길이는 1,068m, 높이는 3m로, 현재는 동문터의 성벽 일부만 남아 있고, 현재의 성은 조선 영조 27년(1751)에 쌓은 것으로 기록되어 있다. 성을 쌓은 시기는 정확히 알 수 없으나, 서해안으로 침입해 오는 왜구들로부터 양민들을 보호하기 위하여, 조선 초기에 쌓은 것으로 추정된다.041-950-4764충청남도 서천군청2024-04-174580000충청남도 서천군
4505비인읍성도지정 문화재자료 제133호유형문화유적성터<NA>충청남도 서천군 비인면 성내리 544-136.142866126.5990361984-05-17국유서천군<NA><NA><NA>읍성이란 군이나 현의 주민을 보호하고, 군사적·행정적인 기능을 함께하는 성을 말한다.충남 서천군 비인면 성내리에 있는 비인읍성은 한 도읍 전체를 둘러싸고 군데군데 문을 만들어 바깥과 통하게 만든 성이다.『동국여지승람』에 의하면 세종 3년(1421) 왜구의 침입을 막기 위하여, 고려 중기에 흙으로 쌓은 성을 돌로 다시 쌓았다고 기록되어 있다. 성의 높이는 2m, 길이는 3,000m 정도이며, 지금은 성의 형태만 남아있고 대부분 훼손되었다.041-950-4764충청남도 서천군청2024-04-174580000충청남도 서천군
4506한산읍성도지정 문화재자료 제134호유형문화유적성터<NA>충청남도 서천군 한산면 지현리 152-336.084573126.8008381984-05-17국유서천군<NA><NA><NA>읍성이란 군이나 현의 주민을 보호하고 군사적·행정적인 기능을 수행하기 위해 소재지를 둘러싸은 것을 말한다.한산읍성에 대해서는 『신증동국여지승람』에 돌로 쌓은 성이며, 성의 둘레가 4,070척(1,233m), 높이가 11척(3m)이고, 성 안에 도랑 1개와 우물 4곳이 있었다고 기록되어 있다.현재 남아있는 성의 둘레는 1,820m이며, 평면형은 서벽이 동벽보다 긴 사다리꼴 형태이다. 서쪽과 북쪽의 성벽은 돌로 쌓았고, 남벽은 흙으로 쌓았으며, 동벽은 흙과 돌을 섞어 쌓았다. 남쪽 벽의 중간에 서천-한산간 지방도로가 통과하고 있어서 성벽이 잘린 것을 빼고는, 나머지 대부분의 성벽이 원래의 모습을 잘 간직하고 있다.고려 중기에 왜구가 강을 끼고 자주 침범해오자, 고을의 백성을 안전하게 지키고자 성을 쌓았던 것으로 짐작된다.041-950-4764충청남도 서천군청2024-04-174580000충청남도 서천군
4507권성선생영정도지정 문화재자료 제325호유형문화유적회화<NA>충청남도 서천군 기산면 화산리 15336.078677126.7696391993-11-12사유안동권씨종중<NA><NA><NA>이것은 권성(權?, 1653~1730)선생의 영정이다. 華山祠는 원래 權?과 權?을 제사 지내던 사당으로 이들의 영정을 봉안해 왔는데, 1871년 대원군의 서원철폐령으로 헐려서 宗家에 옮겼다가 근년에 화산리에 影堂을 짓고 이곳에 영정을 봉안하였다.041-950-4764충청남도 서천군청2024-04-174580000충청남도 서천군
4508문헌서원도지정 문화재자료 제125호유형문화유적건조물<NA>충청남도 서천군 기산면 영모리 1036.091597126.785311984-05-17사유한산이씨종중<NA><NA><NA>가정 이곡(1298∼1351)과 목은 이색(1328∼1396)의 학문과 덕행을 추모하기 위해 세운 서원이다.이곡은 고려 후기 학자로서 이색의 아버지이다. 원나라의 과거에 급제하여 실력을 인정받았고, 문명을 떨쳤다.이색은 고려 후기 문신이며 학자이다. 원·명교체기에 친명정책을 지지하였고, 유교의 입장에서 불교를 이해하고자 하였다. 그의 문하에서 권근, 김종직, 변계량 등을 배출하여 조선 성리학의 주류를 이루게 하였다.문헌서원은 선조 27년(1594)에 세웠으나, 임진왜란 때 불타버렸다. 그 뒤 광해군 2년(1610)에 한산고촌으로 옮겨 다시 세웠다. 이듬해에 나라에서 문헌이라는 현판을 받아 사액서원이 되고 인재 이종학·음애 이자·배옥헌 이개 등을 추가로 모시게 되었다. 고종 8년(1871)에는 흥선대원군의 서원철폐령으로 폐쇄되었다.그 후에도 처음 문헌서원이 있던 곳에 단(壇)을 만들고 분향해 오다가 1969년 지금 있는 자리에 다시 짓고 문양공 이종덕 한 분을 더하여 여섯 분의 위패를 모시고 있다. 해마다 음력 3월과 9월에 제사를 올리고 있다.041-950-4764충청남도 서천군청2024-04-174580000충청남도 서천군
4509이색신도비도지정 문화재자료 제127호유형문화유적건조물<NA>충청남도 서천군 기산면 영모리 31236.091224126.7838121984-05-17사유한산이씨종중<NA><NA><NA>신도비란 왕이나 고관 등의 평생업적을 비석에 기록하여 그의 묘 남동쪽에 세워두는 것으로, 이 비는 고려 후기의 문신이자 학자인 목은(牧隱) 이색 선생을 기리고 있다.이색(1328∼1396)은 고려 후기 조선을 건국한 이성계를 따르지 않고 충절을 지켰던 삼은(三隱)의 한 사람으로, 공민왕 때에는 전제의 개혁, 국방계획, 교육의 진흥, 불교의 억제 등 여러 개혁정책에 관한 건의문을 올리기도 하였다. 또한 중국의 원·명교체기에 있어서는 친명정책을 지지하였으며, 고려 후기 유교가 들어오면서 불교를 배척하자는 의견이 대두되자, 유교의 입장에서 불교를 이해하여 점진적인 개혁을 통해 불교의 폐단을 없애고자 하였다. 조선 태조 4년(1395) 조정에 머물라는 왕의 권유를 끝내 거절하고 여강지역으로 가던 중 생을 마치었다.비는 낮은 받침돌 위로 비몸을 세우고 지붕돌을 올린 모습이며, 비문에는 ‘선생은 후에 죄를 얻어 폐출되었으나, 하늘과 땅만이 그의 고결한 마음을 알리라’라는 내용을 새겨 놓았다. 세종 15년(1433)에 처음 세워졌으나 임진왜란 때 잃어버리고, 현종 7년(1666) 후손들이 다시 세워 지금에 이르고 있다.041-950-4764충청남도 서천군청2024-04-174580000충청남도 서천군