Overview

Dataset statistics

Number of variables11
Number of observations132
Missing cells47
Missing cells (%)3.2%
Duplicate rows1
Duplicate rows (%)0.8%
Total size in memory11.9 KiB
Average record size in memory92.0 B

Variable types

Numeric3
Categorical3
Text4
DateTime1

Dataset

Description강릉시에서 관리하는 문화재에 대한 데이터로 번호, 종별, 지정번호, 명칭, 소재지, 위도, 경도, 지정일자, 비고, 데이터기준일자 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/3044169/fileData.do

Alerts

Dataset has 1 (0.8%) duplicate rowsDuplicates
비고 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
종별 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
데이터기준일자 is highly overall correlated with 번호 and 4 other fieldsHigh correlation
번호 is highly overall correlated with 종별 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 비고 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 비고 and 1 other fieldsHigh correlation
데이터기준일자 is highly imbalanced (88.7%)Imbalance
번호 has 2 (1.5%) missing valuesMissing
지정번호 has 2 (1.5%) missing valuesMissing
명칭 has 2 (1.5%) missing valuesMissing
소재지 has 33 (25.0%) missing valuesMissing
지번주소 has 2 (1.5%) missing valuesMissing
위도 has 2 (1.5%) missing valuesMissing
경도 has 2 (1.5%) missing valuesMissing
지정일자 has 2 (1.5%) missing valuesMissing

Reproduction

Analysis started2023-12-12 04:31:53.600348
Analysis finished2023-12-12 04:31:56.475812
Duration2.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct130
Distinct (%)100.0%
Missing2
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean65.5
Minimum1
Maximum130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T13:31:56.573419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.45
Q133.25
median65.5
Q397.75
95-th percentile123.55
Maximum130
Range129
Interquartile range (IQR)64.5

Descriptive statistics

Standard deviation37.671829
Coefficient of variation (CV)0.57514242
Kurtosis-1.2
Mean65.5
Median Absolute Deviation (MAD)32.5
Skewness0
Sum8515
Variance1419.1667
MonotonicityStrictly increasing
2023-12-12T13:31:56.769603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99 1
 
0.8%
97 1
 
0.8%
96 1
 
0.8%
95 1
 
0.8%
94 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
Other values (120) 120
90.9%
(Missing) 2
 
1.5%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
130 1
0.8%
129 1
0.8%
128 1
0.8%
127 1
0.8%
126 1
0.8%
125 1
0.8%
124 1
0.8%
123 1
0.8%
122 1
0.8%
121 1
0.8%

종별
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
강원특별자치도 유형문화재
36 
강원특별자치도 문화재자료
36 
보물
19 
강원특별자치도 기념물
14 
천연기념물
6 
Other values (8)
21 

Length

Max length13
Median length13
Mean length9.8106061
Min length2

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
강원특별자치도 유형문화재 36
27.3%
강원특별자치도 문화재자료 36
27.3%
보물 19
14.4%
강원특별자치도 기념물 14
 
10.6%
천연기념물 6
 
4.5%
강원특별자치도 무형문화재 6
 
4.5%
명승 4
 
3.0%
사적 3
 
2.3%
국가무형문화재 2
 
1.5%
국가등록문화재 2
 
1.5%
Other values (3) 4
 
3.0%

Length

2023-12-12T13:31:56.960519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강원특별자치도 92
41.1%
유형문화재 36
 
16.1%
문화재자료 36
 
16.1%
보물 19
 
8.5%
기념물 14
 
6.2%
천연기념물 6
 
2.7%
무형문화재 6
 
2.7%
명승 4
 
1.8%
사적 3
 
1.3%
국가무형문화재 2
 
0.9%
Other values (4) 6
 
2.7%

지정번호
Text

MISSING 

Distinct106
Distinct (%)81.5%
Missing2
Missing (%)1.5%
Memory size1.2 KiB
2023-12-12T13:31:57.290958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.3384615
Min length1

Characters and Unicode

Total characters304
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)65.4%

Sample

1st row51
2nd row81
3rd row82
4th row83
5th row84
ValueCountFrequency (%)
5 3
 
2.3%
37 3
 
2.3%
81 3
 
2.3%
62 2
 
1.5%
57 2
 
1.5%
10 2
 
1.5%
12 2
 
1.5%
36 2
 
1.5%
47 2
 
1.5%
55 2
 
1.5%
Other values (96) 107
82.3%
2023-12-12T13:31:57.799110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 59
19.4%
4 35
11.5%
5 34
11.2%
8 30
9.9%
2 29
9.5%
6 29
9.5%
3 27
8.9%
9 24
7.9%
0 18
 
5.9%
7 16
 
5.3%
Other values (2) 3
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 301
99.0%
Dash Punctuation 2
 
0.7%
Other Letter 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 59
19.6%
4 35
11.6%
5 34
11.3%
8 30
10.0%
2 29
9.6%
6 29
9.6%
3 27
9.0%
9 24
8.0%
0 18
 
6.0%
7 16
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Letter
ValueCountFrequency (%)
라 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 303
99.7%
Hangul 1
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 59
19.5%
4 35
11.6%
5 34
11.2%
8 30
9.9%
2 29
9.6%
6 29
9.6%
3 27
8.9%
9 24
7.9%
0 18
 
5.9%
7 16
 
5.3%
Hangul
ValueCountFrequency (%)
라 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 303
99.7%
Hangul 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 59
19.5%
4 35
11.6%
5 34
11.2%
8 30
9.9%
2 29
9.6%
6 29
9.6%
3 27
8.9%
9 24
7.9%
0 18
 
5.9%
7 16
 
5.3%
Hangul
ValueCountFrequency (%)
라 1
100.0%

명칭
Text

MISSING 

Distinct130
Distinct (%)100.0%
Missing2
Missing (%)1.5%
Memory size1.2 KiB
2023-12-12T13:31:58.105305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length8.9384615
Min length3

Characters and Unicode

Total characters1162
Distinct characters203
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)100.0%

Sample

1st row강릉 임영관 삼문
2nd row강릉 한송사지 석조보살좌상
3rd row강릉 대창리 당간지주
4th row강릉 수문리 당간지주
5th row강릉 신복사지 석조보살좌상
ValueCountFrequency (%)
강릉 48
 
19.8%
고택 7
 
2.9%
소장 6
 
2.5%
보현사 4
 
1.6%
강릉향교 4
 
1.6%
굴산사지 3
 
1.2%
청학사 3
 
1.2%
당간지주 3
 
1.2%
및 3
 
1.2%
신복사지 2
 
0.8%
Other values (154) 160
65.8%
2023-12-12T13:31:58.580110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
174
 
15.0%
강 91
 
7.8%
릉 90
 
7.7%
사 35
 
3.0%
석 19
 
1.6%
장 17
 
1.5%
산 17
 
1.5%
동 16
 
1.4%
리 16
 
1.4%
당 16
 
1.4%
Other values (193) 671
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 982
84.5%
Space Separator 174
 
15.0%
Other Punctuation 3
 
0.3%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 91
 
9.3%
릉 90
 
9.2%
사 35
 
3.6%
석 19
 
1.9%
장 17
 
1.7%
산 17
 
1.7%
동 16
 
1.6%
리 16
 
1.6%
당 16
 
1.6%
지 16
 
1.6%
Other values (187) 649
66.1%
Other Punctuation
ValueCountFrequency (%)
· 2
66.7%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
174
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 982
84.5%
Common 180
 
15.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
강 91
 
9.3%
릉 90
 
9.2%
사 35
 
3.6%
석 19
 
1.9%
장 17
 
1.7%
산 17
 
1.7%
동 16
 
1.6%
리 16
 
1.6%
당 16
 
1.6%
지 16
 
1.6%
Other values (187) 649
66.1%
Common
ValueCountFrequency (%)
174
96.7%
· 2
 
1.1%
) 1
 
0.6%
, 1
 
0.6%
( 1
 
0.6%
- 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 979
84.3%
ASCII 178
 
15.3%
Compat Jamo 3
 
0.3%
None 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
174
97.8%
) 1
 
0.6%
, 1
 
0.6%
( 1
 
0.6%
- 1
 
0.6%
Hangul
ValueCountFrequency (%)
강 91
 
9.3%
릉 90
 
9.2%
사 35
 
3.6%
석 19
 
1.9%
장 17
 
1.7%
산 17
 
1.7%
동 16
 
1.6%
리 16
 
1.6%
당 16
 
1.6%
지 16
 
1.6%
Other values (186) 646
66.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 3
100.0%
None
ValueCountFrequency (%)
· 2
100.0%

소재지
Text

MISSING 

Distinct64
Distinct (%)64.6%
Missing33
Missing (%)25.0%
Memory size1.2 KiB
2023-12-12T13:31:58.971485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length30
Mean length26.636364
Min length18

Characters and Unicode

Total characters2637
Distinct characters133
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)54.5%

Sample

1st row강원특별자치도 강릉시 임영로131번길 6 (용강동)
2nd row강원특별자치도 강릉시 율곡로3139번길 24 (죽헌동)
3rd row강원특별자치도 강릉시 옥가로50번길 7(옥천동)
4th row강원특별자치도 강릉시 구정면 오독떼기길 41-19
5th row강원특별자치도 강릉시 율곡로3139번길 24 (죽헌동)
ValueCountFrequency (%)
강원특별자치도 99
20.2%
강릉시 98
20.0%
죽헌동 23
 
4.7%
율곡로3139번길 21
 
4.3%
24 21
 
4.3%
성산면 12
 
2.4%
구정면 7
 
1.4%
교동 7
 
1.4%
보현길 6
 
1.2%
396 6
 
1.2%
Other values (131) 190
38.8%
2023-12-12T13:31:59.509978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
391
 
14.8%
강 208
 
7.9%
릉 101
 
3.8%
원 101
 
3.8%
시 100
 
3.8%
특 99
 
3.8%
별 99
 
3.8%
자 99
 
3.8%
치 99
 
3.8%
도 99
 
3.8%
Other values (123) 1241
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1680
63.7%
Decimal Number 413
 
15.7%
Space Separator 391
 
14.8%
Close Punctuation 59
 
2.2%
Open Punctuation 59
 
2.2%
Dash Punctuation 33
 
1.3%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 208
 
12.4%
릉 101
 
6.0%
원 101
 
6.0%
시 100
 
6.0%
특 99
 
5.9%
별 99
 
5.9%
자 99
 
5.9%
치 99
 
5.9%
도 99
 
5.9%
길 81
 
4.8%
Other values (108) 594
35.4%
Decimal Number
ValueCountFrequency (%)
3 75
18.2%
1 67
16.2%
2 66
16.0%
9 54
13.1%
6 40
9.7%
4 36
8.7%
8 23
 
5.6%
7 22
 
5.3%
5 20
 
4.8%
0 10
 
2.4%
Space Separator
ValueCountFrequency (%)
391
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1680
63.7%
Common 957
36.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
강 208
 
12.4%
릉 101
 
6.0%
원 101
 
6.0%
시 100
 
6.0%
특 99
 
5.9%
별 99
 
5.9%
자 99
 
5.9%
치 99
 
5.9%
도 99
 
5.9%
길 81
 
4.8%
Other values (108) 594
35.4%
Common
ValueCountFrequency (%)
391
40.9%
3 75
 
7.8%
1 67
 
7.0%
2 66
 
6.9%
) 59
 
6.2%
( 59
 
6.2%
9 54
 
5.6%
6 40
 
4.2%
4 36
 
3.8%
- 33
 
3.4%
Other values (5) 77
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1680
63.7%
ASCII 957
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
391
40.9%
3 75
 
7.8%
1 67
 
7.0%
2 66
 
6.9%
) 59
 
6.2%
( 59
 
6.2%
9 54
 
5.6%
6 40
 
4.2%
4 36
 
3.8%
- 33
 
3.4%
Other values (5) 77
 
8.0%
Hangul
ValueCountFrequency (%)
강 208
 
12.4%
릉 101
 
6.0%
원 101
 
6.0%
시 100
 
6.0%
특 99
 
5.9%
별 99
 
5.9%
자 99
 
5.9%
치 99
 
5.9%
도 99
 
5.9%
길 81
 
4.8%
Other values (108) 594
35.4%

지번주소
Text

MISSING 

Distinct90
Distinct (%)69.2%
Missing2
Missing (%)1.5%
Memory size1.2 KiB
2023-12-12T13:31:59.873604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length21.661538
Min length11

Characters and Unicode

Total characters2816
Distinct characters93
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

Unique77 ?
Unique (%)59.2%

Sample

1st row강원특별자치도 강릉시 용강동 58-1
2nd row강원특별자치도 강릉시 죽헌동 177-4
3rd row강원특별자치도 강릉시 옥천동 334
4th row강원특별자치도 강릉시 옥천동 43-9
5th row강원특별자치도 강릉시 내곡동 403-2
ValueCountFrequency (%)
강원특별자치도 130
22.2%
강릉시 129
22.1%
죽헌동 23
 
3.9%
177-4 21
 
3.6%
성산면 15
 
2.6%
구정면 11
 
1.9%
보광리 9
 
1.5%
옥계면 8
 
1.4%
사천면 7
 
1.2%
산계리 7
 
1.2%
Other values (136) 225
38.5%
2023-12-12T13:32:00.351524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
455
16.2%
강 267
 
9.5%
원 131
 
4.7%
별 131
 
4.7%
시 131
 
4.7%
특 130
 
4.6%
자 130
 
4.6%
치 130
 
4.6%
도 130
 
4.6%
릉 129
 
4.6%
Other values (83) 1052
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1879
66.7%
Space Separator 455
 
16.2%
Decimal Number 426
 
15.1%
Dash Punctuation 56
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 267
14.2%
원 131
 
7.0%
별 131
 
7.0%
시 131
 
7.0%
특 130
 
6.9%
자 130
 
6.9%
치 130
 
6.9%
도 130
 
6.9%
릉 129
 
6.9%
동 84
 
4.5%
Other values (71) 486
25.9%
Decimal Number
ValueCountFrequency (%)
1 90
21.1%
7 69
16.2%
4 65
15.3%
3 48
11.3%
2 43
10.1%
5 29
 
6.8%
9 22
 
5.2%
0 21
 
4.9%
8 20
 
4.7%
6 19
 
4.5%
Space Separator
ValueCountFrequency (%)
455
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1879
66.7%
Common 937
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
강 267
14.2%
원 131
 
7.0%
별 131
 
7.0%
시 131
 
7.0%
특 130
 
6.9%
자 130
 
6.9%
치 130
 
6.9%
도 130
 
6.9%
릉 129
 
6.9%
동 84
 
4.5%
Other values (71) 486
25.9%
Common
ValueCountFrequency (%)
455
48.6%
1 90
 
9.6%
7 69
 
7.4%
4 65
 
6.9%
- 56
 
6.0%
3 48
 
5.1%
2 43
 
4.6%
5 29
 
3.1%
9 22
 
2.3%
0 21
 
2.2%
Other values (2) 39
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1879
66.7%
ASCII 937
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
455
48.6%
1 90
 
9.6%
7 69
 
7.4%
4 65
 
6.9%
- 56
 
6.0%
3 48
 
5.1%
2 43
 
4.6%
5 29
 
3.1%
9 22
 
2.3%
0 21
 
2.2%
Other values (2) 39
 
4.2%
Hangul
ValueCountFrequency (%)
강 267
14.2%
원 131
 
7.0%
별 131
 
7.0%
시 131
 
7.0%
특 130
 
6.9%
자 130
 
6.9%
치 130
 
6.9%
도 130
 
6.9%
릉 129
 
6.9%
동 84
 
4.5%
Other values (71) 486
25.9%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct91
Distinct (%)70.0%
Missing2
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean37.754029
Minimum37.564788
Maximum37.878737
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T13:32:00.479485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.564788
5-th percentile37.590848
Q137.736935
median37.760965
Q337.77831
95-th percentile37.85881
Maximum37.878737
Range0.3139498
Interquartile range (IQR)0.04137507

Descriptive statistics

Standard deviation0.060414712
Coefficient of variation (CV)0.0016002189
Kurtosis2.7768671
Mean37.754029
Median Absolute Deviation (MAD)0.024029815
Skewness-1.1262807
Sum4908.0238
Variance0.0036499375
MonotonicityNot monotonic
2023-12-12T13:32:00.607630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.77830977 21
 
15.9%
37.7369347 6
 
4.5%
37.69360033 4
 
3.0%
37.76325895 4
 
3.0%
37.75294766 2
 
1.5%
37.74492189 2
 
1.5%
37.79000424 2
 
1.5%
37.57734485 2
 
1.5%
37.75379479 2
 
1.5%
37.78727455 2
 
1.5%
Other values (81) 83
62.9%
ValueCountFrequency (%)
37.56478766 1
 
0.8%
37.5692027 1
 
0.8%
37.57499485 1
 
0.8%
37.57587536 1
 
0.8%
37.57645456 1
 
0.8%
37.57734485 2
1.5%
37.60735201 1
 
0.8%
37.69285878 1
 
0.8%
37.69360033 4
3.0%
37.69624087 1
 
0.8%
ValueCountFrequency (%)
37.87873746 1
0.8%
37.87853852 1
0.8%
37.87767193 1
0.8%
37.86602651 1
0.8%
37.86113749 1
0.8%
37.86040381 1
0.8%
37.85980854 1
0.8%
37.8575901 1
0.8%
37.83910768 1
0.8%
37.83030939 1
0.8%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct91
Distinct (%)70.0%
Missing2
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean128.87515
Minimum128.63113
Maximum129.03207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T13:32:00.734620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.63113
5-th percentile128.76989
Q1128.86778
median128.88559
Q3128.89897
95-th percentile128.96015
Maximum129.03207
Range0.400941
Interquartile range (IQR)0.031193925

Descriptive statistics

Standard deviation0.058326255
Coefficient of variation (CV)0.00045257954
Kurtosis2.7539557
Mean128.87515
Median Absolute Deviation (MAD)0.0156405
Skewness-0.81969777
Sum16753.769
Variance0.0034019521
MonotonicityNot monotonic
2023-12-12T13:32:00.880039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8767136 21
 
15.9%
128.7698883 6
 
4.5%
128.8720137 4
 
3.0%
128.8951425 4
 
3.0%
128.8919068 2
 
1.5%
128.889991 2
 
1.5%
128.7805257 2
 
1.5%
128.9311012 2
 
1.5%
128.8961445 2
 
1.5%
128.8846364 2
 
1.5%
Other values (81) 83
62.9%
ValueCountFrequency (%)
128.6311332 1
 
0.8%
128.6978221 1
 
0.8%
128.7500337 1
 
0.8%
128.7547032 1
 
0.8%
128.7698883 6
4.5%
128.7805257 2
 
1.5%
128.7831452 1
 
0.8%
128.7838642 1
 
0.8%
128.7859673 1
 
0.8%
128.7909525 1
 
0.8%
ValueCountFrequency (%)
129.0320742 1
0.8%
129.016291 1
0.8%
129.0098531 1
0.8%
129.0068312 1
0.8%
128.9705415 1
0.8%
128.9637102 1
0.8%
128.9621072 1
0.8%
128.9577533 1
0.8%
128.9576697 1
0.8%
128.9444717 1
0.8%

지정일자
Date

MISSING 

Distinct57
Distinct (%)43.8%
Missing2
Missing (%)1.5%
Memory size1.2 KiB
Minimum1962-12-20 00:00:00
Maximum2020-12-28 00:00:00
2023-12-12T13:32:01.041560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:32:01.201050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

비고
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
73 
오죽헌시립박물관
21 
보현사
 
5
굴산사지
 
3
청학사
 
3
Other values (24)
27 

Length

Max length29
Median length4
Mean length5.8484848
Min length3

Unique

Unique21 ?
Unique (%)15.9%

Sample

1st row강릉대도호부관아
2nd row오죽헌시립박물관
3rd row<NA>
4th row<NA>
5th row신복사지

Common Values

ValueCountFrequency (%)
<NA> 73
55.3%
오죽헌시립박물관 21
 
15.9%
보현사 5
 
3.8%
굴산사지 3
 
2.3%
청학사 3
 
2.3%
관음사 2
 
1.5%
신복사지 2
 
1.5%
용연사 2
 
1.5%
※ 경포(기념물 제2호:2014.02.07.지정해제) 1
 
0.8%
심상진가옥 1
 
0.8%
Other values (19) 19
 
14.4%

Length

2023-12-12T13:32:01.359206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 73
45.9%
오죽헌시립박물관 21
 
13.2%
강릉 6
 
3.8%
보현사 5
 
3.1%
가옥 4
 
2.5%
굴산사지 3
 
1.9%
청학사 3
 
1.9%
관음사 2
 
1.3%
신복사지 2
 
1.3%
용연사 2
 
1.3%
Other values (38) 38
23.9%

데이터기준일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-08-28
130 
<NA>
 
2

Length

Max length10
Median length10
Mean length9.9090909
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-28
2nd row2023-08-28
3rd row2023-08-28
4th row2023-08-28
5th row2023-08-28

Common Values

ValueCountFrequency (%)
2023-08-28 130
98.5%
<NA> 2
 
1.5%

Length

2023-12-12T13:32:01.483459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:32:01.577024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-28 130
98.5%
na 2
 
1.5%

Interactions

2023-12-12T13:31:55.173873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:31:54.460189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:31:54.841071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:31:55.275385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:31:54.582659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:31:54.936800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:31:55.735900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:31:54.705284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:31:55.045521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:32:01.636543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호종별소재지지번주소위도경도지정일자비고
번호1.0000.8910.5340.8180.0660.2460.9750.853
종별0.8911.0000.6950.8950.4040.4150.9960.956
소재지0.5340.6951.0001.0001.0001.0000.8631.000
지번주소0.8180.8951.0001.0001.0001.0000.9601.000
위도0.0660.4041.0001.0001.0000.7020.9151.000
경도0.2460.4151.0001.0000.7021.0000.7911.000
지정일자0.9750.9960.8630.9600.9150.7911.0000.800
비고0.8530.9561.0001.0001.0001.0000.8001.000
2023-12-12T13:32:01.729853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고종별데이터기준일자
비고1.0000.6071.000
종별0.6071.0001.000
데이터기준일자1.0001.0001.000
2023-12-12T13:32:01.813163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호위도경도종별비고데이터기준일자
번호1.0000.012-0.0640.6490.4021.000
위도0.0121.000-0.3470.1790.7511.000
경도-0.064-0.3471.0000.2010.7651.000
종별0.6490.1790.2011.0000.6071.000
비고0.4020.7510.7650.6071.0001.000
데이터기준일자1.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T13:31:55.906508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:31:56.101922image/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.
2023-12-12T13:31:56.308001image/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

번호종별지정번호명칭소재지지번주소위도경도지정일자비고데이터기준일자
01국보51강릉 임영관 삼문강원특별자치도 강릉시 임영로131번길 6 (용강동)강원특별자치도 강릉시 용강동 58-137.752948128.8919071962-12-20강릉대도호부관아2023-08-28
12보물81강릉 한송사지 석조보살좌상강원특별자치도 강릉시 율곡로3139번길 24 (죽헌동)강원특별자치도 강릉시 죽헌동 177-437.77831128.8767141963-01-21오죽헌시립박물관2023-08-28
23보물82강릉 대창리 당간지주강원특별자치도 강릉시 옥가로50번길 7(옥천동)강원특별자치도 강릉시 옥천동 33437.76083128.9012251963-01-21<NA>2023-08-28
34보물83강릉 수문리 당간지주<NA>강원특별자치도 강릉시 옥천동 43-937.756467128.9038391963-01-21<NA>2023-08-28
45보물84강릉 신복사지 석조보살좌상<NA>강원특별자치도 강릉시 내곡동 403-237.742793128.8855861963-01-21신복사지2023-08-28
56보물85강릉 굴산사지 승탑강원특별자치도 강릉시 구정면 오독떼기길 41-19강원특별자치도 강릉시 구정면 학산리 634-437.70535128.8910141963-01-21굴산사지2023-08-28
67보물86강릉 굴산사지 당간지주<NA>강원특별자치도 강릉시 구정면 학산리 118137.70729128.8918311963-01-21굴산사지2023-08-28
78보물87강릉 신복사지 삼층석탑<NA>강원특별자치도 강릉시 내곡동 403-237.742793128.8855861963-01-21신복사지2023-08-28
89보물165강릉 오죽헌강원특별자치도 강릉시 율곡로3139번길 24 (죽헌동)강원특별자치도 강릉시 죽헌동 177-437.77831128.8767141963-01-21오죽헌시립박물관2023-08-28
910보물183강릉 해운정강원특별자치도 강릉시 운정길 125 (운정동)강원특별자치도 강릉시 운정동 25637.786107128.8914131963-01-21<NA>2023-08-28
번호종별지정번호명칭소재지지번주소위도경도지정일자비고데이터기준일자
122123강원특별자치도 문화재자료143강릉 청학사 소장 청동보살입상강원특별자치도 강릉시 구정면 청파로 176-38강원특별자치도 강릉시 구정면 구정리 2937.6936128.8720142007-01-19청학사2023-08-28
123124강원특별자치도 문화재자료152강릉 청학사 소장 석불좌상ㆍ광배 및 중대석강원특별자치도 강릉시 구정면 청파로 176-38강원특별자치도 강릉시 구정면 구정리 2937.6936128.8720142011-08-12청학사2023-08-28
124125강원특별자치도 문화재자료153강릉 보현사 소조보살좌상강원특별자치도 강릉시 성산면 보현길 396강원특별자치도 강릉시 성산면 보광리 117137.736935128.7698882013-01-11보현사2023-08-28
125126강원특별자치도 문화재자료155강릉 오죽헌ㆍ박물관 소장 임영족회첩강원특별자치도 강릉시 율곡로3139번길 24 (죽헌동)강원특별자치도 강릉시 죽헌동 177-437.77831128.8767142013-01-11오죽헌시립박물관2023-08-28
126127강원특별자치도 문화재자료156강릉 오죽헌ㆍ박물관 소장 미타계첩강원특별자치도 강릉시 율곡로3139번길 24 (죽헌동)강원특별자치도 강릉시 죽헌동 177-437.77831128.8767142013-01-11오죽헌시립박물관2023-08-28
127128강원특별자치도 문화재자료165경락첩강원특별자치도 강릉시 율곡로3139번길 24 (죽헌동)강원특별자치도 강릉시 죽헌동 177-437.77831128.8767142015-03-06오죽헌시립박물관2023-08-28
128129국가등록문화재457강릉 임당동성당강원특별자치도 강릉시 임영로 148 (임당동)강원특별자치도 강릉시 임당동 15937.75462128.8925622010-02-19<NA>2023-08-28
129130국가등록문화재648강릉 선교장 소장 태극기강원특별자치도 강릉시 운정길 63 (운정동)강원특별자치도 강릉시 운정동 43137.787275128.8846362015-04-27선교장2023-08-28
130<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

번호종별지정번호명칭소재지지번주소위도경도지정일자비고데이터기준일자# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2