Overview

Dataset statistics

Number of variables5
Number of observations625
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.5 KiB
Average record size in memory40.2 B

Variable types

Text3
Categorical1
DateTime1

Dataset

Description경상남도 문화재 자료 현황 자료입니다. 문화재명칭, 문화쟈수량, 문화재면적, 문화재소재지, 문화재지정일 등의 데이터를 포함하고있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15056109

Alerts

지정번호 has unique valuesUnique

Reproduction

Analysis started2024-04-16 16:52:58.298793
Analysis finished2024-04-16 16:52:58.690433
Duration0.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지정번호
Text

UNIQUE 

Distinct625
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-04-17T01:52:58.887938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10.8608
Min length9

Characters and Unicode

Total characters6788
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique625 ?
Unique (%)100.0%

Sample

1st row문화재자료 제2호
2nd row문화재자료 제3호
3rd row문화재자료 제4호
4th row문화재자료 제5호
5th row문화재자료 제6호
ValueCountFrequency (%)
문화재자료 625
50.0%
제432호 1
 
0.1%
제426호 1
 
0.1%
제442호 1
 
0.1%
제427호 1
 
0.1%
제428호 1
 
0.1%
제429호 1
 
0.1%
제430호 1
 
0.1%
제431호 1
 
0.1%
제433호 1
 
0.1%
Other values (616) 616
49.3%
2024-04-17T01:52:59.315443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
문 625
9.2%
재 625
9.2%
자 625
9.2%
료 625
9.2%
625
9.2%
제 625
9.2%
호 625
9.2%
화 625
9.2%
3 235
 
3.5%
2 234
 
3.4%
Other values (9) 1319
19.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4375
64.5%
Decimal Number 1782
26.3%
Space Separator 625
 
9.2%
Dash Punctuation 6
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 235
13.2%
2 234
13.1%
1 228
12.8%
5 222
12.5%
4 220
12.3%
6 164
9.2%
7 120
6.7%
8 120
6.7%
0 120
6.7%
9 119
6.7%
Other Letter
ValueCountFrequency (%)
문 625
14.3%
재 625
14.3%
자 625
14.3%
료 625
14.3%
제 625
14.3%
호 625
14.3%
화 625
14.3%
Space Separator
ValueCountFrequency (%)
625
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4375
64.5%
Common 2413
35.5%

Most frequent character per script

Common
ValueCountFrequency (%)
625
25.9%
3 235
 
9.7%
2 234
 
9.7%
1 228
 
9.4%
5 222
 
9.2%
4 220
 
9.1%
6 164
 
6.8%
7 120
 
5.0%
8 120
 
5.0%
0 120
 
5.0%
Other values (2) 125
 
5.2%
Hangul
ValueCountFrequency (%)
문 625
14.3%
재 625
14.3%
자 625
14.3%
료 625
14.3%
제 625
14.3%
호 625
14.3%
화 625
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4375
64.5%
ASCII 2413
35.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
문 625
14.3%
재 625
14.3%
자 625
14.3%
료 625
14.3%
제 625
14.3%
호 625
14.3%
화 625
14.3%
ASCII
ValueCountFrequency (%)
625
25.9%
3 235
 
9.7%
2 234
 
9.7%
1 228
 
9.4%
5 222
 
9.2%
4 220
 
9.1%
6 164
 
6.8%
7 120
 
5.0%
8 120
 
5.0%
0 120
 
5.0%
Other values (2) 125
 
5.2%

명칭
Text

Distinct622
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-04-17T01:52:59.563792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length8.8784
Min length2

Characters and Unicode

Total characters5549
Distinct characters337
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

Unique619 ?
Unique (%)99.0%

Sample

1st row관해정
2nd row영남포정사문루
3rd row북장대
4th row창열사
5th row서장대
ValueCountFrequency (%)
의령 23
 
2.0%
진주 19
 
1.7%
창원 17
 
1.5%
김해 17
 
1.5%
합천 15
 
1.3%
소장 15
 
1.3%
하동 14
 
1.2%
거창 13
 
1.2%
남해 12
 
1.1%
밀양 11
 
1.0%
Other values (790) 972
86.2%
2024-04-17T01:52:59.906447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
504
 
9.1%
사 211
 
3.8%
리 144
 
2.6%
정 128
 
2.3%
산 115
 
2.1%
서 102
 
1.8%
고 98
 
1.8%
원 97
 
1.7%
양 95
 
1.7%
도 75
 
1.4%
Other values (327) 3980
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5012
90.3%
Space Separator 504
 
9.1%
Decimal Number 19
 
0.3%
Other Punctuation 8
 
0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 211
 
4.2%
리 144
 
2.9%
정 128
 
2.6%
산 115
 
2.3%
서 102
 
2.0%
고 98
 
2.0%
원 97
 
1.9%
양 95
 
1.9%
도 75
 
1.5%
동 66
 
1.3%
Other values (312) 3881
77.4%
Decimal Number
ValueCountFrequency (%)
2 7
36.8%
1 4
21.1%
3 4
21.1%
9 1
 
5.3%
6 1
 
5.3%
8 1
 
5.3%
7 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 3
37.5%
. 3
37.5%
· 2
25.0%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
504
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5012
90.3%
Common 537
 
9.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 211
 
4.2%
리 144
 
2.9%
정 128
 
2.6%
산 115
 
2.3%
서 102
 
2.0%
고 98
 
2.0%
원 97
 
1.9%
양 95
 
1.9%
도 75
 
1.5%
동 66
 
1.3%
Other values (312) 3881
77.4%
Common
ValueCountFrequency (%)
504
93.9%
2 7
 
1.3%
1 4
 
0.7%
3 4
 
0.7%
, 3
 
0.6%
. 3
 
0.6%
· 2
 
0.4%
) 2
 
0.4%
( 2
 
0.4%
> 1
 
0.2%
Other values (5) 5
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5012
90.3%
ASCII 535
 
9.6%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
504
94.2%
2 7
 
1.3%
1 4
 
0.7%
3 4
 
0.7%
, 3
 
0.6%
. 3
 
0.6%
) 2
 
0.4%
( 2
 
0.4%
> 1
 
0.2%
< 1
 
0.2%
Other values (4) 4
 
0.7%
Hangul
ValueCountFrequency (%)
사 211
 
4.2%
리 144
 
2.9%
정 128
 
2.6%
산 115
 
2.3%
서 102
 
2.0%
고 98
 
2.0%
원 97
 
1.9%
양 95
 
1.9%
도 75
 
1.5%
동 66
 
1.3%
Other values (312) 3881
77.4%
None
ValueCountFrequency (%)
· 2
100.0%

소재지
Categorical

Distinct38
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
밀양
 
37
진주시
 
36
합천
 
35
진주
 
34
남해군
 
32
Other values (33)
451 

Length

Max length3
Median length2
Mean length2.496
Min length2

Unique

Unique3 ?
Unique (%)0.5%

Sample

1st row창원
2nd row진주
3rd row진주
4th row진주
5th row진주

Common Values

ValueCountFrequency (%)
밀양 37
 
5.9%
진주시 36
 
5.8%
합천 35
 
5.6%
진주 34
 
5.4%
남해군 32
 
5.1%
창녕 28
 
4.5%
합천군 26
 
4.2%
산청 25
 
4.0%
밀양시 24
 
3.8%
창원시 24
 
3.8%
Other values (28) 324
51.8%

Length

2024-04-17T01:53:00.051910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
밀양 37
 
5.9%
진주시 36
 
5.8%
합천 36
 
5.8%
진주 34
 
5.4%
남해군 32
 
5.1%
창녕 28
 
4.5%
합천군 26
 
4.2%
산청 25
 
4.0%
창원시 24
 
3.8%
밀양시 24
 
3.8%
Other values (27) 323
51.7%

수량_면적
Text

Distinct281
Distinct (%)45.0%
Missing1
Missing (%)0.2%
Memory size5.0 KiB
2024-04-17T01:53:00.302938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length2
Mean length5.7916667
Min length2

Characters and Unicode

Total characters3614
Distinct characters94
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

Unique238 ?
Unique (%)38.1%

Sample

1st row1동
2nd row1동, 133.3(㎡)
3rd row1동, 134(㎡)
4th row7동, 440.5(㎡)
5th row1동, 64.6(㎡)
ValueCountFrequency (%)
1동 161
 
18.5%
1기 61
 
7.0%
1점 50
 
5.8%
2동 44
 
5.1%
1폭 30
 
3.5%
1구 27
 
3.1%
1책 25
 
2.9%
5동 25
 
2.9%
4동 23
 
2.6%
3동 18
 
2.1%
Other values (322) 405
46.6%
2024-04-17T01:53:00.704093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 569
15.7%
동 298
 
8.2%
, 288
 
8.0%
) 260
 
7.2%
( 260
 
7.2%
248
 
6.9%
㎡ 192
 
5.3%
2 164
 
4.5%
3 140
 
3.9%
4 118
 
3.3%
Other values (84) 1077
29.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1490
41.2%
Other Letter 784
21.7%
Other Punctuation 380
 
10.5%
Close Punctuation 260
 
7.2%
Open Punctuation 260
 
7.2%
Space Separator 248
 
6.9%
Other Symbol 192
 
5.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 298
38.0%
점 87
 
11.1%
기 81
 
10.3%
책 51
 
6.5%
매 41
 
5.2%
구 31
 
4.0%
폭 31
 
4.0%
장 14
 
1.8%
권 11
 
1.4%
곽 8
 
1.0%
Other values (66) 131
16.7%
Decimal Number
ValueCountFrequency (%)
1 569
38.2%
2 164
 
11.0%
3 140
 
9.4%
4 118
 
7.9%
5 105
 
7.0%
7 90
 
6.0%
6 79
 
5.3%
8 78
 
5.2%
9 76
 
5.1%
0 71
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 288
75.8%
. 83
 
21.8%
: 8
 
2.1%
/ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 260
100.0%
Open Punctuation
ValueCountFrequency (%)
( 260
100.0%
Space Separator
ValueCountFrequency (%)
248
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 192
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2830
78.3%
Hangul 784
 
21.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 298
38.0%
점 87
 
11.1%
기 81
 
10.3%
책 51
 
6.5%
매 41
 
5.2%
구 31
 
4.0%
폭 31
 
4.0%
장 14
 
1.8%
권 11
 
1.4%
곽 8
 
1.0%
Other values (66) 131
16.7%
Common
ValueCountFrequency (%)
1 569
20.1%
, 288
10.2%
) 260
9.2%
( 260
9.2%
248
8.8%
㎡ 192
 
6.8%
2 164
 
5.8%
3 140
 
4.9%
4 118
 
4.2%
5 105
 
3.7%
Other values (8) 486
17.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2638
73.0%
Hangul 784
 
21.7%
CJK Compat 192
 
5.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 569
21.6%
, 288
10.9%
) 260
9.9%
( 260
9.9%
248
9.4%
2 164
 
6.2%
3 140
 
5.3%
4 118
 
4.5%
5 105
 
4.0%
7 90
 
3.4%
Other values (7) 396
15.0%
Hangul
ValueCountFrequency (%)
동 298
38.0%
점 87
 
11.1%
기 81
 
10.3%
책 51
 
6.5%
매 41
 
5.2%
구 31
 
4.0%
폭 31
 
4.0%
장 14
 
1.8%
권 11
 
1.4%
곽 8
 
1.0%
Other values (66) 131
16.7%
CJK Compat
ValueCountFrequency (%)
㎡ 192
100.0%

지정일
Date

Distinct122
Distinct (%)19.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum1983-07-20 00:00:00
Maximum2017-09-28 00:00:00
2024-04-17T01:53:00.834848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:53:00.987749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Missing values

2024-04-17T01:52:58.575009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T01:52:58.657674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

지정번호명칭소재지수량_면적지정일
0문화재자료 제2호관해정창원1동1983-07-20
1문화재자료 제3호영남포정사문루진주1동, 133.3(㎡)1983-07-20
2문화재자료 제4호북장대진주1동, 134(㎡)1983-07-20
3문화재자료 제5호창열사진주7동, 440.5(㎡)1983-07-20
4문화재자료 제6호서장대진주1동, 64.6(㎡)1983-07-20
5문화재자료 제7호의기사진주1동, 56.1(㎡)1983-07-20
6문화재자료 제8호촉석루진주1동, 508.6(㎡)1983-07-20
7문화재자료 제9호통영 백운서재통영1동1983-07-20
8문화재자료 제10호통영 용화사통영3동1983-07-20
9문화재자료 제12호남악서원진주7동, 2,381.7(㎡)1983-07-20
지정번호명칭소재지수량_면적지정일
615문화재자료 제629호밀양 삼원정밀양시1책2016-07-28
616문화재자료 제630호양산 안적암 아미타불회도양산시3권1책2016-09-29
617문화재자료 제631호진해향교 공자위패 매안지 비석창원시2권1책2016-10-13
618문화재자료 제632호산청 망추정산청군10권5책2016-12-01
619문화재자료 제633호밀양 완재정밀양시1책2017-03-30
620문화재자료 제634호사명당 유정 교첩김해시3권3책2017-04-13
621문화재자료 제635호창원향교 전적류창원시16권13책2017-04-13
622문화재자료 제636호사천 김해김씨 삼현파 문중 호구단자사천시1폭2017-04-13
623문화재자료 제637호선무원종공신녹권(이희급)남해군14쌍(28장)2017-07-20
624문화재자료 제638호진주 허만선 고가진주시1동, (53.55(㎡))2017-09-28