Overview

Dataset statistics

Number of variables14
Number of observations42
Missing cells42
Missing cells (%)7.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory117.1 B

Variable types

Categorical6
Text4
Numeric2
DateTime2

Dataset

Description경상남도 양산시 문화재 국가지정 현황에 대한 파일 데이터입니다. 유형, 지정번호, 문화재명 등의 정보를 포함하고 있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15074059

Alerts

출처 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연락처 is highly overall correlated with 위도 and 4 other fieldsHigh correlation
소유자 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
관리단체 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
위도 is highly overall correlated with 소유자 and 3 other fieldsHigh correlation
경도 is highly overall correlated with 소유자 and 3 other fieldsHigh correlation
유형 is highly overall correlated with 소유자 and 2 other fieldsHigh correlation
소재지 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
유형 is highly imbalanced (54.4%)Imbalance
면적(m2) has 35 (83.3%) missing valuesMissing
수량 has 7 (16.7%) missing valuesMissing
지정번호 has unique valuesUnique
문화재명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:15:24.150508
Analysis finished2023-12-10 23:15:25.978973
Duration1.83 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size468.0 B
보물
33 
사적
6 
국보
 
1
등록문화재
 
1
천연기념물
 
1

Length

Max length5
Median length2
Mean length2.1428571
Min length2

Unique

Unique3 ?
Unique (%)7.1%

Sample

1st row국보
2nd row보물
3rd row보물
4th row보물
5th row보물

Common Values

ValueCountFrequency (%)
보물 33
78.6%
사적 6
 
14.3%
국보 1
 
2.4%
등록문화재 1
 
2.4%
천연기념물 1
 
2.4%

Length

2023-12-11T08:15:26.058569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:15:26.189553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보물 33
78.6%
사적 6
 
14.3%
국보 1
 
2.4%
등록문화재 1
 
2.4%
천연기념물 1
 
2.4%

지정번호
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-11T08:15:26.408989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.5238095
Min length2

Characters and Unicode

Total characters148
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

Unique42 ?
Unique (%)100.0%

Sample

1st row290
2nd row11_6
3rd row74
4th row334
5th row471
ValueCountFrequency (%)
290 1
 
2.4%
1747 1
 
2.4%
617 1
 
2.4%
1354 1
 
2.4%
1373 1
 
2.4%
1471 1
 
2.4%
1472 1
 
2.4%
1711 1
 
2.4%
1734 1
 
2.4%
1735 1
 
2.4%
Other values (32) 32
76.2%
2023-12-11T08:15:26.864332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 39
26.4%
7 19
12.8%
3 15
 
10.1%
4 15
 
10.1%
9 13
 
8.8%
5 12
 
8.1%
2 11
 
7.4%
0 10
 
6.8%
8 6
 
4.1%
6 5
 
3.4%
Other values (2) 3
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 145
98.0%
Dash Punctuation 2
 
1.4%
Connector Punctuation 1
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 39
26.9%
7 19
13.1%
3 15
 
10.3%
4 15
 
10.3%
9 13
 
9.0%
5 12
 
8.3%
2 11
 
7.6%
0 10
 
6.9%
8 6
 
4.1%
6 5
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 148
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 39
26.4%
7 19
12.8%
3 15
 
10.1%
4 15
 
10.1%
9 13
 
8.8%
5 12
 
8.1%
2 11
 
7.4%
0 10
 
6.8%
8 6
 
4.1%
6 5
 
3.4%
Other values (2) 3
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 39
26.4%
7 19
12.8%
3 15
 
10.1%
4 15
 
10.1%
9 13
 
8.8%
5 12
 
8.1%
2 11
 
7.4%
0 10
 
6.8%
8 6
 
4.1%
6 5
 
3.4%
Other values (2) 3
 
2.0%

문화재명
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-11T08:15:27.130190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length16
Mean length11.642857
Min length4

Characters and Unicode

Total characters489
Distinct characters120
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row통도사 대웅전 및 금강계단
2nd row통도사 동종
3rd row양산 통도사 국장생석표
4th row통도사 청동은입사 향완
5th row양산 통도사 봉발탑
ValueCountFrequency (%)
양산 23
21.5%
통도사 19
17.8%
영산전 3
 
2.8%
고분군 3
 
2.8%
묘법연화경 3
 
2.8%
산성 2
 
1.9%
대광명전 2
 
1.9%
신기리 2
 
1.9%
신흥사 2
 
1.9%
통도사청동은입사봉황문향완 1
 
0.9%
Other values (47) 47
43.9%
2023-12-11T08:15:27.461829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67
 
13.7%
산 31
 
6.3%
사 29
 
5.9%
도 27
 
5.5%
양 25
 
5.1%
통 21
 
4.3%
전 9
 
1.8%
화 9
 
1.8%
상 8
 
1.6%
동 7
 
1.4%
Other values (110) 256
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 409
83.6%
Space Separator 67
 
13.7%
Decimal Number 10
 
2.0%
Math Symbol 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 31
 
7.6%
사 29
 
7.1%
도 27
 
6.6%
양 25
 
6.1%
통 21
 
5.1%
전 9
 
2.2%
화 9
 
2.2%
상 8
 
2.0%
동 7
 
1.7%
경 7
 
1.7%
Other values (100) 236
57.7%
Decimal Number
ValueCountFrequency (%)
1 2
20.0%
4 2
20.0%
3 1
10.0%
7 1
10.0%
0 1
10.0%
9 1
10.0%
2 1
10.0%
6 1
10.0%
Space Separator
ValueCountFrequency (%)
67
100.0%
Math Symbol
ValueCountFrequency (%)
∼ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 409
83.6%
Common 80
 
16.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 31
 
7.6%
사 29
 
7.1%
도 27
 
6.6%
양 25
 
6.1%
통 21
 
5.1%
전 9
 
2.2%
화 9
 
2.2%
상 8
 
2.0%
동 7
 
1.7%
경 7
 
1.7%
Other values (100) 236
57.7%
Common
ValueCountFrequency (%)
67
83.8%
∼ 3
 
3.8%
1 2
 
2.5%
4 2
 
2.5%
3 1
 
1.2%
7 1
 
1.2%
0 1
 
1.2%
9 1
 
1.2%
2 1
 
1.2%
6 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 409
83.6%
ASCII 77
 
15.7%
Math Operators 3
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67
87.0%
1 2
 
2.6%
4 2
 
2.6%
3 1
 
1.3%
7 1
 
1.3%
0 1
 
1.3%
9 1
 
1.3%
2 1
 
1.3%
6 1
 
1.3%
Hangul
ValueCountFrequency (%)
산 31
 
7.6%
사 29
 
7.1%
도 27
 
6.6%
양 25
 
6.1%
통 21
 
5.1%
전 9
 
2.2%
화 9
 
2.2%
상 8
 
2.0%
동 7
 
1.7%
경 7
 
1.7%
Other values (100) 236
57.7%
Math Operators
ValueCountFrequency (%)
∼ 3
100.0%

면적(m2)
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing35
Missing (%)83.3%
Memory size468.0 B
2023-12-11T08:15:27.639203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6
Min length4

Characters and Unicode

Total characters42
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st row25994
2nd row101242
3rd row142909
4th row145366
5th row205834
ValueCountFrequency (%)
25994 1
12.5%
101242 1
12.5%
142909 1
12.5%
145366 1
12.5%
205834 1
12.5%
1814 1
12.5%
6433 1
12.5%
1주 1
12.5%
2023-12-11T08:15:27.908841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 7
16.7%
1 7
16.7%
2 5
11.9%
9 4
9.5%
3 4
9.5%
5 3
7.1%
0 3
7.1%
6 3
7.1%
8 2
 
4.8%
1
 
2.4%
Other values (3) 3
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38
90.5%
Space Separator 1
 
2.4%
Open Punctuation 1
 
2.4%
Other Letter 1
 
2.4%
Close Punctuation 1
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 7
18.4%
1 7
18.4%
2 5
13.2%
9 4
10.5%
3 4
10.5%
5 3
7.9%
0 3
7.9%
6 3
7.9%
8 2
 
5.3%
Space Separator
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Letter
ValueCountFrequency (%)
주 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41
97.6%
Hangul 1
 
2.4%

Most frequent character per script

Common
ValueCountFrequency (%)
4 7
17.1%
1 7
17.1%
2 5
12.2%
9 4
9.8%
3 4
9.8%
5 3
7.3%
0 3
7.3%
6 3
7.3%
8 2
 
4.9%
1
 
2.4%
Other values (2) 2
 
4.9%
Hangul
ValueCountFrequency (%)
주 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41
97.6%
Hangul 1
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 7
17.1%
1 7
17.1%
2 5
12.2%
9 4
9.8%
3 4
9.8%
5 3
7.3%
0 3
7.3%
6 3
7.3%
8 2
 
4.9%
1
 
2.4%
Other values (2) 2
 
4.9%
Hangul
ValueCountFrequency (%)
주 1
100.0%

수량
Text

MISSING 

Distinct18
Distinct (%)51.4%
Missing7
Missing (%)16.7%
Memory size468.0 B
2023-12-11T08:15:28.095395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.4
Min length2

Characters and Unicode

Total characters84
Distinct characters21
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

Unique11 ?
Unique (%)31.4%

Sample

1st row1곽
2nd row1구
3rd row1기
4th row1점
5th row1기
ValueCountFrequency (%)
1구 6
17.1%
1폭 5
14.3%
1기 3
 
8.6%
1점 3
 
8.6%
1동 3
 
8.6%
2권1책 2
 
5.7%
1책 2
 
5.7%
일괄 1
 
2.9%
1곽 1
 
2.9%
52점 1
 
2.9%
Other values (8) 8
22.9%
2023-12-11T08:15:28.433468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 30
35.7%
폭 7
 
8.3%
구 6
 
7.1%
책 6
 
7.1%
권 5
 
6.0%
점 5
 
6.0%
3 4
 
4.8%
2 3
 
3.6%
동 3
 
3.6%
기 3
 
3.6%
Other values (11) 12
 
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42
50.0%
Other Letter 42
50.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폭 7
16.7%
구 6
14.3%
책 6
14.3%
권 5
11.9%
점 5
11.9%
동 3
7.1%
기 3
7.1%
첩 1
 
2.4%
축 1
 
2.4%
종 1
 
2.4%
Other values (4) 4
9.5%
Decimal Number
ValueCountFrequency (%)
1 30
71.4%
3 4
 
9.5%
2 3
 
7.1%
6 2
 
4.8%
8 1
 
2.4%
7 1
 
2.4%
5 1
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 42
50.0%
Hangul 42
50.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폭 7
16.7%
구 6
14.3%
책 6
14.3%
권 5
11.9%
점 5
11.9%
동 3
7.1%
기 3
7.1%
첩 1
 
2.4%
축 1
 
2.4%
종 1
 
2.4%
Other values (4) 4
9.5%
Common
ValueCountFrequency (%)
1 30
71.4%
3 4
 
9.5%
2 3
 
7.1%
6 2
 
4.8%
8 1
 
2.4%
7 1
 
2.4%
5 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
50.0%
Hangul 42
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 30
71.4%
3 4
 
9.5%
2 3
 
7.1%
6 2
 
4.8%
8 1
 
2.4%
7 1
 
2.4%
5 1
 
2.4%
Hangul
ValueCountFrequency (%)
폭 7
16.7%
구 6
14.3%
책 6
14.3%
권 5
11.9%
점 5
11.9%
동 3
7.1%
기 3
7.1%
첩 1
 
2.4%
축 1
 
2.4%
종 1
 
2.4%
Other values (4) 4
9.5%

소유자
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size468.0 B
통도사
25 
<NA>
7 
신흥사
 
2
양산시
 
1
용화사
 
1
Other values (6)
6 

Length

Max length7
Median length3
Mean length3.2619048
Min length3

Unique

Unique8 ?
Unique (%)19.0%

Sample

1st row통도사
2nd row통도사
3rd row양산시
4th row통도사
5th row통도사

Common Values

ValueCountFrequency (%)
통도사 25
59.5%
<NA> 7
 
16.7%
신흥사 2
 
4.8%
양산시 1
 
2.4%
용화사 1
 
2.4%
김찬호 1
 
2.4%
서왕모 1
 
2.4%
미타암 1
 
2.4%
이근수 1
 
2.4%
내원사 1
 
2.4%

Length

2023-12-11T08:15:28.568066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
통도사 26
60.5%
na 7
 
16.3%
신흥사 2
 
4.7%
양산시 1
 
2.3%
용화사 1
 
2.3%
김찬호 1
 
2.3%
서왕모 1
 
2.3%
미타암 1
 
2.3%
이근수 1
 
2.3%
내원사 1
 
2.3%

소재지
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size468.0 B
경상남도 양산시 하북면 통도사로 108
27 
경상남도 양산시 하북면 통도사로 108
 
1
경상남도 양산시 하북면 백록리 718-1
 
1
경상남도 양산시 물금읍 원동로 19 -13
 
1
경상남도 양산시 탑골길 208-208
 
1
Other values (11)
11 

Length

Max length26
Median length21
Mean length20.904762
Min length17

Unique

Unique15 ?
Unique (%)35.7%

Sample

1st row경상남도 양산시 하북면 통도사로 108
2nd row경상남도 양산시 하북면 통도사로 108
3rd row경상남도 양산시 하북면 백록리 718-1
4th row경상남도 양산시 하북면 통도사로 108
5th row경상남도 양산시 하북면 통도사로 108

Common Values

ValueCountFrequency (%)
경상남도 양산시 하북면 통도사로 108 27
64.3%
경상남도 양산시 하북면 통도사로 108 1
 
2.4%
경상남도 양산시 하북면 백록리 718-1 1
 
2.4%
경상남도 양산시 물금읍 원동로 19 -13 1
 
2.4%
경상남도 양산시 탑골길 208-208 1
 
2.4%
경상남도 양산시 물금읍 범어리 675-5 정각사 1
 
2.4%
경상남도 양산시 주진로 379-61 1
 
2.4%
경상남도 양산시 북정동 북정로78양산시립박물관 1
 
2.4%
경상남도 양산시 원동면 원동로 2282-111 1
 
2.4%
경상남도 양산시 북정 697 일원 1
 
2.4%
Other values (6) 6
 
14.3%

Length

2023-12-11T08:15:28.691278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경상남도 42
19.9%
양산시 42
19.9%
하북면 29
13.7%
통도사로 28
13.3%
108 28
13.3%
일원 3
 
1.4%
북부 2
 
0.9%
신기 2
 
0.9%
중부 2
 
0.9%
북정 2
 
0.9%
Other values (29) 31
14.7%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)35.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.453297
Minimum35.316998
Maximum35.487915
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-11T08:15:28.789408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.316998
5-th percentile35.341711
Q135.427461
median35.487915
Q335.487915
95-th percentile35.487915
Maximum35.487915
Range0.170917
Interquartile range (IQR)0.0604535

Descriptive statistics

Standard deviation0.056614972
Coefficient of variation (CV)0.0015968887
Kurtosis0.056406603
Mean35.453297
Median Absolute Deviation (MAD)0
Skewness-1.3031829
Sum1489.0385
Variance0.003205255
MonotonicityNot monotonic
2023-12-11T08:15:28.918328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
35.487915 28
66.7%
35.474267 1
 
2.4%
35.316998 1
 
2.4%
35.416601 1
 
2.4%
35.450302 1
 
2.4%
35.406129 1
 
2.4%
35.35838 1
 
2.4%
35.426395 1
 
2.4%
35.356928 1
 
2.4%
35.354075 1
 
2.4%
Other values (5) 5
 
11.9%
ValueCountFrequency (%)
35.316998 1
2.4%
35.336658 1
2.4%
35.341334 1
2.4%
35.348875 1
2.4%
35.354075 1
2.4%
35.356928 1
2.4%
35.35838 1
2.4%
35.359271 1
2.4%
35.406129 1
2.4%
35.416601 1
2.4%
ValueCountFrequency (%)
35.487915 28
66.7%
35.474267 1
 
2.4%
35.450302 1
 
2.4%
35.430661 1
 
2.4%
35.426395 1
 
2.4%
35.416601 1
 
2.4%
35.406129 1
 
2.4%
35.359271 1
 
2.4%
35.35838 1
 
2.4%
35.356928 1
 
2.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)35.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.06552
Minimum128.95087
Maximum129.21183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-11T08:15:29.028157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.95087
5-th percentile129.04068
Q1129.06434
median129.06434
Q3129.06434
95-th percentile129.12785
Maximum129.21183
Range0.260957
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.037095816
Coefficient of variation (CV)0.00028741848
Kurtosis7.7811323
Mean129.06552
Median Absolute Deviation (MAD)0
Skewness0.79150993
Sum5420.7519
Variance0.0013760996
MonotonicityNot monotonic
2023-12-11T08:15:29.139440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
129.064337 28
66.7%
129.086674 1
 
2.4%
128.976313 1
 
2.4%
129.211826 1
 
2.4%
129.130973 1
 
2.4%
129.128215 1
 
2.4%
129.048972 1
 
2.4%
128.950869 1
 
2.4%
129.049948 1
 
2.4%
129.052986 1
 
2.4%
Other values (5) 5
 
11.9%
ValueCountFrequency (%)
128.950869 1
 
2.4%
128.976313 1
 
2.4%
129.04056 1
 
2.4%
129.042895 1
 
2.4%
129.047688 1
 
2.4%
129.048972 1
 
2.4%
129.049948 1
 
2.4%
129.052986 1
 
2.4%
129.061618 1
 
2.4%
129.064337 28
66.7%
ValueCountFrequency (%)
129.211826 1
 
2.4%
129.130973 1
 
2.4%
129.128215 1
 
2.4%
129.120918 1
 
2.4%
129.086674 1
 
2.4%
129.064337 28
66.7%
129.061618 1
 
2.4%
129.052986 1
 
2.4%
129.049948 1
 
2.4%
129.048972 1
 
2.4%

연락처
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size468.0 B
055-382-7182
27 
055-392-2119
9 
<NA>
3 
055-384-5111
 
1
055-365-4184
 
1

Length

Max length12
Median length12
Mean length11.428571
Min length4

Unique

Unique3 ?
Unique (%)7.1%

Sample

1st row055-382-7182
2nd row055-382-7182
3rd row055-392-2119
4th row055-382-7182
5th row055-382-7182

Common Values

ValueCountFrequency (%)
055-382-7182 27
64.3%
055-392-2119 9
 
21.4%
<NA> 3
 
7.1%
055-384-5111 1
 
2.4%
055-365-4184 1
 
2.4%
055-384-0108 1
 
2.4%

Length

2023-12-11T08:15:29.264603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:15:29.412937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
055-382-7182 27
64.3%
055-392-2119 9
 
21.4%
na 3
 
7.1%
055-384-5111 1
 
2.4%
055-365-4184 1
 
2.4%
055-384-0108 1
 
2.4%

지정일
Date

Distinct25
Distinct (%)59.5%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum1963-01-21 00:00:00
Maximum2014-10-29 00:00:00
2023-12-11T08:15:29.543978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:15:29.675915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

관리단체
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
통도사
26 
양산시
9 
신흥사
 
2
용화사
 
1
대성암
 
1
Other values (3)
3 

Length

Max length7
Median length3
Mean length3.1190476
Min length3

Unique

Unique5 ?
Unique (%)11.9%

Sample

1st row통도사
2nd row통도사
3rd row양산시
4th row통도사
5th row통도사

Common Values

ValueCountFrequency (%)
통도사 26
61.9%
양산시 9
 
21.4%
신흥사 2
 
4.8%
용화사 1
 
2.4%
대성암 1
 
2.4%
<NA> 1
 
2.4%
미타암 1
 
2.4%
통도사 자장암 1
 
2.4%

Length

2023-12-11T08:15:29.823796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:15:30.021837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
통도사 27
62.8%
양산시 9
 
20.9%
신흥사 2
 
4.7%
용화사 1
 
2.3%
대성암 1
 
2.3%
na 1
 
2.3%
미타암 1
 
2.3%
자장암 1
 
2.3%

출처
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
기본현황
42 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기본현황 42
100.0%

Length

2023-12-11T08:15:30.141092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:15:30.224948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기본현황 42
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum2020-11-30 00:00:00
Maximum2020-11-30 00:00:00
2023-12-11T08:15:30.297707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:15:30.386763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T08:15:24.987667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:15:24.773420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:15:25.098629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:15:24.879131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:15:30.461872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형지정번호문화재명면적(m2)수량소유자소재지위도경도연락처지정일관리단체
유형1.0001.0001.0001.0001.0000.7170.9240.6350.3670.6630.9960.727
지정번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
문화재명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
면적(m2)1.0001.0001.0001.000NaNNaN1.0001.0001.000NaN1.000NaN
수량1.0001.0001.000NaN1.0000.1490.1820.0000.0000.0000.9350.728
소유자0.7171.0001.000NaN0.1491.0000.9620.9741.0001.0000.9321.000
소재지0.9241.0001.0001.0000.1820.9621.0001.0001.0000.9150.0000.937
위도0.6351.0001.0001.0000.0000.9741.0001.0000.8620.8870.9010.865
경도0.3671.0001.0001.0000.0001.0001.0000.8621.0000.9630.8040.888
연락처0.6631.0001.000NaN0.0001.0000.9150.8870.9631.0000.9351.000
지정일0.9961.0001.0001.0000.9350.9320.0000.9010.8040.9351.0000.969
관리단체0.7271.0001.000NaN0.7281.0000.9370.8650.8881.0000.9691.000
2023-12-11T08:15:30.635600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지연락처소유자유형관리단체
소재지1.0000.6970.8450.6540.684
연락처0.6971.0000.9430.2980.985
소유자0.8450.9431.0000.5060.962
유형0.6540.2980.5061.0000.562
관리단체0.6840.9850.9620.5621.000
2023-12-11T08:15:30.737476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도유형소유자소재지연락처관리단체
위도1.0000.3600.4600.8610.8620.8070.723
경도0.3601.0000.2570.8940.8500.7250.723
유형0.4600.2571.0000.5060.6540.2980.562
소유자0.8610.8940.5061.0000.8450.9430.962
소재지0.8620.8500.6540.8451.0000.6970.684
연락처0.8070.7250.2980.9430.6971.0000.985
관리단체0.7230.7230.5620.9620.6840.9851.000

Missing values

2023-12-11T08:15:25.210659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:15:25.432615image/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.
2023-12-11T08:15:25.916205image/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

유형지정번호문화재명면적(m2)수량소유자소재지위도경도연락처지정일관리단체출처데이터기준일자
0국보290통도사 대웅전 및 금강계단<NA>1곽통도사경상남도 양산시 하북면 통도사로 10835.487915129.064337055-382-71821997-01-01통도사기본현황2020-11-30
1보물11_6통도사 동종<NA>1구통도사경상남도 양산시 하북면 통도사로 10835.487915129.064337055-382-71822000-02-15통도사기본현황2020-11-30
2보물74양산 통도사 국장생석표<NA>1기양산시경상남도 양산시 하북면 백록리 718-135.474267129.086674055-392-21191963-01-21양산시기본현황2020-11-30
3보물334통도사 청동은입사 향완<NA>1점통도사경상남도 양산시 하북면 통도사로 10835.487915129.064337055-382-71821963-01-21통도사기본현황2020-11-30
4보물471양산 통도사 봉발탑<NA>1기통도사경상남도 양산시 하북면 통도사로 10835.487915129.064337055-382-71821968-12-19통도사기본현황2020-11-30
5보물491양산 용화사석조여래좌상<NA>1구용화사경상남도 양산시 물금읍 원동로 19 -1335.316998128.976313055-384-51111969-12-19용화사기본현황2020-11-30
6보물738문수사리보살최상승무생계경<NA>3권1책통도사경상남도 양산시 하북면 통도사로 10835.487915129.064337055-382-71821982-11-09통도사기본현황2020-11-30
7보물757감지금니대방광불화엄경주본 권46<NA>1축통도사경상남도 양산시 하북면 통도사로 10835.487915129.064337055-382-71821984-05-23통도사기본현황2020-11-30
8보물758-2남명천화상송증도가<NA>1책김찬호경상남도 양산시 탑골길 208-20835.416601129.211826<NA>2012-06-29대성암기본현황2020-11-30
9보물965-2육경합부<NA>1책서왕모경상남도 양산시 물금읍 범어리 675-5 정각사35.450302129.130973<NA>2006-01-17<NA>기본현황2020-11-30
유형지정번호문화재명면적(m2)수량소유자소재지위도경도연락처지정일관리단체출처데이터기준일자
32보물1826양산 통도사 영산전<NA>1동통도사경상남도 양산시 하북면 통도사로 10835.487915129.064337055-382-71822014-06-05통도사기본현황2020-11-30
33보물1827양산 통도사 대광명전<NA>1동통도사경상남도 양산시 하북면 통도사로 10835.487915129.064337055-382-71822014-06-05통도사기본현황2020-11-30
34사적93양산 북정리 고분군25994<NA><NA>경상남도 양산시 북정 697 일원35.356928129.049948055-392-21191963-01-21양산시기본현황2020-11-30
35사적94양산 신기리 고분군101242<NA><NA>경상남도 양산시 신기 산29 일원35.354075129.052986055-392-21191963-01-21양산시기본현황2020-11-30
36사적95양산 중부동 고분군142909<NA><NA>경상남도 양산시 중부 산1 일원35.341334129.047688055-392-21191963-01-21양산시기본현황2020-11-30
37사적97양산 신기리 산성145366<NA><NA>경상남도 양산시 호계 신기 북정 북부35.359271129.042895055-392-21191963-01-21양산시기본현황2020-11-30
38사적98양산 북부리 산성205834<NA><NA>경상남도 양산시 북부 남부 중부 다방35.348875129.04056055-392-21191963-01-21양산시기본현황2020-11-30
39사적100양산 법기리 요지1814<NA><NA>경상남도 양산시 동면 법기 78235.336658129.120918055-392-21191963-01-21양산시기본현황2020-11-30
40등록문화재617양산 통도사 자장암 마애아미타여래삼존상<NA>3좌통도사 자장암경상남도 양산시 하북면 통도사로 10835.487915129.064337055-382-71822014-10-29통도사 자장암기본현황2020-11-30
41천연기념물234양산 신전리 이팝나무6433 (1주)<NA><NA>경상남도 양산시 상북면 신전 9535.430661129.061618055-392-21191971-09-13양산시기본현황2020-11-30