Overview

Dataset statistics

Number of variables11
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory96.7 B

Variable types

Numeric5
Text4
DateTime2

Dataset

Description부산광역시 전통사찰 현황에 대한 데이터로 지정호수, 사찰명, 법명, 도로명주소, 전화번호, 건물동수, 면적, 등록일자, 위도, 경도, 데이터기준일자 항목 정보를 제공합니다.
Author부산광역시
URLhttps://www.data.go.kr/data/15065487/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
지정호수 has unique valuesUnique
사찰명 has unique valuesUnique
법명 has unique valuesUnique
도로명주소 has unique valuesUnique
전화번호 has unique valuesUnique
면적_제곱미터 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:35:19.202382
Analysis finished2023-12-12 17:35:23.232451
Duration4.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지정호수
Real number (ℝ)

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.5
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-13T02:35:23.328344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.75
Q19.75
median18.5
Q327.25
95-th percentile34.25
Maximum36
Range35
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation10.535654
Coefficient of variation (CV)0.5694948
Kurtosis-1.2
Mean18.5
Median Absolute Deviation (MAD)9
Skewness0
Sum666
Variance111
MonotonicityStrictly increasing
2023-12-13T02:35:23.513820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 1
 
2.8%
20 1
 
2.8%
22 1
 
2.8%
23 1
 
2.8%
24 1
 
2.8%
25 1
 
2.8%
26 1
 
2.8%
27 1
 
2.8%
28 1
 
2.8%
29 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
1 1
2.8%
2 1
2.8%
3 1
2.8%
4 1
2.8%
5 1
2.8%
6 1
2.8%
7 1
2.8%
8 1
2.8%
9 1
2.8%
10 1
2.8%
ValueCountFrequency (%)
36 1
2.8%
35 1
2.8%
34 1
2.8%
33 1
2.8%
32 1
2.8%
31 1
2.8%
30 1
2.8%
29 1
2.8%
28 1
2.8%
27 1
2.8%

사찰명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-13T02:35:23.789390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.3611111
Min length7

Characters and Unicode

Total characters301
Distinct characters114
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row梵魚寺(범어사)
2nd row摩訶寺(마하사)
3rd row光明寺(광명사)
4th row燃燈寺(연등사)
5th row雲水寺(운수사)
ValueCountFrequency (%)
梵魚寺(범어사 1
 
2.8%
摩訶寺(마하사 1
 
2.8%
玉蓮禪院(옥련선원 1
 
2.8%
淸寺(청량사 1
 
2.8%
安寂寺(안적사 1
 
2.8%
月明寺(월명사 1
 
2.8%
擲阪庵(척판암 1
 
2.8%
長安寺(장안사 1
 
2.8%
慧苑精舍(혜원정사 1
 
2.8%
妙觀音寺(묘관음사 1
 
2.8%
Other values (26) 26
72.2%
2023-12-13T02:35:24.227982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 36
 
12.0%
) 36
 
12.0%
사 29
 
9.6%
寺 26
 
8.6%
암 8
 
2.7%
정 6
 
2.0%
庵 6
 
2.0%
수 4
 
1.3%
水 4
 
1.3%
금 3
 
1.0%
Other values (104) 143
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 229
76.1%
Open Punctuation 36
 
12.0%
Close Punctuation 36
 
12.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 29
 
12.7%
寺 26
 
11.4%
암 8
 
3.5%
정 6
 
2.6%
庵 6
 
2.6%
수 4
 
1.7%
水 4
 
1.7%
금 3
 
1.3%
舍 3
 
1.3%
해 3
 
1.3%
Other values (102) 137
59.8%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 115
38.2%
Han 114
37.9%
Common 72
23.9%

Most frequent character per script

Han
ValueCountFrequency (%)
寺 26
22.8%
庵 6
 
5.3%
水 4
 
3.5%
舍 3
 
2.6%
精 3
 
2.6%
光 3
 
2.6%
海 3
 
2.6%
金 3
 
2.6%
淸 2
 
1.8%
妙 2
 
1.8%
Other values (49) 59
51.8%
Hangul
ValueCountFrequency (%)
사 29
25.2%
암 8
 
7.0%
정 6
 
5.2%
수 4
 
3.5%
금 3
 
2.6%
해 3
 
2.6%
광 3
 
2.6%
선 3
 
2.6%
원 3
 
2.6%
청 2
 
1.7%
Other values (43) 51
44.3%
Common
ValueCountFrequency (%)
( 36
50.0%
) 36
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 115
38.2%
CJK 114
37.9%
ASCII 72
23.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 36
50.0%
) 36
50.0%
Hangul
ValueCountFrequency (%)
사 29
25.2%
암 8
 
7.0%
정 6
 
5.2%
수 4
 
3.5%
금 3
 
2.6%
해 3
 
2.6%
광 3
 
2.6%
선 3
 
2.6%
원 3
 
2.6%
청 2
 
1.7%
Other values (43) 51
44.3%
CJK
ValueCountFrequency (%)
寺 26
22.8%
庵 6
 
5.3%
水 4
 
3.5%
舍 3
 
2.6%
精 3
 
2.6%
光 3
 
2.6%
海 3
 
2.6%
金 3
 
2.6%
淸 2
 
1.8%
妙 2
 
1.8%
Other values (49) 59
51.8%

법명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-13T02:35:24.464763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters252
Distinct characters92
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

Unique36 ?
Unique (%)100.0%

Sample

1st row정혁수(보운)
2nd row곽치영(정산)
3rd row남후남(무아)
4th row강덕용(덕륜)
5th row유인상(범일)
ValueCountFrequency (%)
정혁수(보운 1
 
2.8%
곽치영(정산 1
 
2.8%
정일오(일오 1
 
2.8%
김상문(현엽 1
 
2.8%
황용성(원여 1
 
2.8%
김미영(묘산 1
 
2.8%
이명구(보일 1
 
2.8%
정기성(무관 1
 
2.8%
정일현(효명 1
 
2.8%
조찬구(서강 1
 
2.8%
Other values (26) 26
72.2%
2023-12-13T02:35:24.941839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 36
 
14.3%
( 36
 
14.3%
일 8
 
3.2%
이 7
 
2.8%
김 7
 
2.8%
상 6
 
2.4%
정 6
 
2.4%
성 5
 
2.0%
최 4
 
1.6%
지 4
 
1.6%
Other values (82) 133
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 180
71.4%
Close Punctuation 36
 
14.3%
Open Punctuation 36
 
14.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 8
 
4.4%
이 7
 
3.9%
김 7
 
3.9%
상 6
 
3.3%
정 6
 
3.3%
성 5
 
2.8%
최 4
 
2.2%
지 4
 
2.2%
문 4
 
2.2%
현 4
 
2.2%
Other values (80) 125
69.4%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 180
71.4%
Common 72
 
28.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 8
 
4.4%
이 7
 
3.9%
김 7
 
3.9%
상 6
 
3.3%
정 6
 
3.3%
성 5
 
2.8%
최 4
 
2.2%
지 4
 
2.2%
문 4
 
2.2%
현 4
 
2.2%
Other values (80) 125
69.4%
Common
ValueCountFrequency (%)
) 36
50.0%
( 36
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 180
71.4%
ASCII 72
 
28.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 36
50.0%
( 36
50.0%
Hangul
ValueCountFrequency (%)
일 8
 
4.4%
이 7
 
3.9%
김 7
 
3.9%
상 6
 
3.3%
정 6
 
3.3%
성 5
 
2.8%
최 4
 
2.2%
지 4
 
2.2%
문 4
 
2.2%
현 4
 
2.2%
Other values (80) 125
69.4%

도로명주소
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-13T02:35:25.284129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length20.138889
Min length16

Characters and Unicode

Total characters725
Distinct characters90
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

Unique36 ?
Unique (%)100.0%

Sample

1st row부산광역시 금정구 범어사로 250
2nd row부산광역시 연제구 봉수로 138
3rd row부산광역시 부산진구 안창로14번길 46
4th row부산광역시 동구 좌천동로 17-3
5th row부산광역시 사상구 모라로219번길 173
ValueCountFrequency (%)
부산광역시 36
24.0%
기장군 5
 
3.3%
금정구 4
 
2.7%
연제구 4
 
2.7%
동구 3
 
2.0%
장안읍 3
 
2.0%
북문로 3
 
2.0%
사상구 3
 
2.0%
기장읍 3
 
2.0%
부산진구 2
 
1.3%
Other values (76) 84
56.0%
2023-12-13T02:35:25.931374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
119
 
16.4%
산 44
 
6.1%
광 40
 
5.5%
부 38
 
5.2%
역 36
 
5.0%
시 36
 
5.0%
1 31
 
4.3%
로 30
 
4.1%
구 27
 
3.7%
2 19
 
2.6%
Other values (80) 305
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 449
61.9%
Decimal Number 144
 
19.9%
Space Separator 119
 
16.4%
Dash Punctuation 13
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 44
 
9.8%
광 40
 
8.9%
부 38
 
8.5%
역 36
 
8.0%
시 36
 
8.0%
로 30
 
6.7%
구 27
 
6.0%
길 16
 
3.6%
장 15
 
3.3%
번 11
 
2.4%
Other values (68) 156
34.7%
Decimal Number
ValueCountFrequency (%)
1 31
21.5%
2 19
13.2%
4 16
11.1%
6 14
9.7%
5 14
9.7%
8 12
 
8.3%
3 12
 
8.3%
0 11
 
7.6%
7 10
 
6.9%
9 5
 
3.5%
Space Separator
ValueCountFrequency (%)
119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 449
61.9%
Common 276
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 44
 
9.8%
광 40
 
8.9%
부 38
 
8.5%
역 36
 
8.0%
시 36
 
8.0%
로 30
 
6.7%
구 27
 
6.0%
길 16
 
3.6%
장 15
 
3.3%
번 11
 
2.4%
Other values (68) 156
34.7%
Common
ValueCountFrequency (%)
119
43.1%
1 31
 
11.2%
2 19
 
6.9%
4 16
 
5.8%
6 14
 
5.1%
5 14
 
5.1%
- 13
 
4.7%
8 12
 
4.3%
3 12
 
4.3%
0 11
 
4.0%
Other values (2) 15
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 449
61.9%
ASCII 276
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
119
43.1%
1 31
 
11.2%
2 19
 
6.9%
4 16
 
5.8%
6 14
 
5.1%
5 14
 
5.1%
- 13
 
4.7%
8 12
 
4.3%
3 12
 
4.3%
0 11
 
4.0%
Other values (2) 15
 
5.4%
Hangul
ValueCountFrequency (%)
산 44
 
9.8%
광 40
 
8.9%
부 38
 
8.5%
역 36
 
8.0%
시 36
 
8.0%
로 30
 
6.7%
구 27
 
6.0%
길 16
 
3.6%
장 15
 
3.3%
번 11
 
2.4%
Other values (68) 156
34.7%

전화번호
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-13T02:35:26.237419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters432
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

Unique36 ?
Unique (%)100.0%

Sample

1st row051-508-3122
2nd row051-852-2436
3rd row051-646-0843
4th row051-632-0546
5th row051-317-5671
ValueCountFrequency (%)
051-508-3122 1
 
2.8%
051-852-2436 1
 
2.8%
051-757-9067 1
 
2.8%
051-271-2774 1
 
2.8%
051-543-7700 1
 
2.8%
051-721-0123 1
 
2.8%
051-727-3547 1
 
2.8%
051-727-2393 1
 
2.8%
051-866-7777 1
 
2.8%
051-727-2035 1
 
2.8%
Other values (26) 26
72.2%
2023-12-13T02:35:26.606030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 72
16.7%
5 67
15.5%
0 64
14.8%
1 56
13.0%
7 51
11.8%
2 32
7.4%
3 27
 
6.2%
6 24
 
5.6%
4 22
 
5.1%
8 11
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 360
83.3%
Dash Punctuation 72
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 67
18.6%
0 64
17.8%
1 56
15.6%
7 51
14.2%
2 32
8.9%
3 27
7.5%
6 24
 
6.7%
4 22
 
6.1%
8 11
 
3.1%
9 6
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 432
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 72
16.7%
5 67
15.5%
0 64
14.8%
1 56
13.0%
7 51
11.8%
2 32
7.4%
3 27
 
6.2%
6 24
 
5.6%
4 22
 
5.1%
8 11
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 72
16.7%
5 67
15.5%
0 64
14.8%
1 56
13.0%
7 51
11.8%
2 32
7.4%
3 27
 
6.2%
6 24
 
5.6%
4 22
 
5.1%
8 11
 
2.5%

건물동수
Real number (ℝ)

Distinct15
Distinct (%)41.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1666667
Minimum2
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-13T02:35:26.747913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q14
median6
Q310
95-th percentile16.25
Maximum45
Range43
Interquartile range (IQR)6

Descriptive statistics

Standard deviation7.5422619
Coefficient of variation (CV)0.92354227
Kurtosis16.272363
Mean8.1666667
Median Absolute Deviation (MAD)2
Skewness3.5617657
Sum294
Variance56.885714
MonotonicityNot monotonic
2023-12-13T02:35:26.864316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
4 7
19.4%
5 6
16.7%
6 4
11.1%
2 3
8.3%
10 3
8.3%
16 2
 
5.6%
7 2
 
5.6%
9 2
 
5.6%
45 1
 
2.8%
3 1
 
2.8%
Other values (5) 5
13.9%
ValueCountFrequency (%)
2 3
8.3%
3 1
 
2.8%
4 7
19.4%
5 6
16.7%
6 4
11.1%
7 2
 
5.6%
8 1
 
2.8%
9 2
 
5.6%
10 3
8.3%
11 1
 
2.8%
ValueCountFrequency (%)
45 1
 
2.8%
17 1
 
2.8%
16 2
5.6%
15 1
 
2.8%
13 1
 
2.8%
11 1
 
2.8%
10 3
8.3%
9 2
5.6%
8 1
 
2.8%
7 2
5.6%

면적_제곱미터
Real number (ℝ)

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3850.4225
Minimum131.56
Maximum58738
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-13T02:35:27.026006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum131.56
5-th percentile172
Q1314.325
median617.205
Q31486.75
95-th percentile17520.5
Maximum58738
Range58606.44
Interquartile range (IQR)1172.425

Descriptive statistics

Standard deviation11298.073
Coefficient of variation (CV)2.9342424
Kurtosis18.091664
Mean3850.4225
Median Absolute Deviation (MAD)390.705
Skewness4.2063667
Sum138615.21
Variance1.2764645 × 108
MonotonicityNot monotonic
2023-12-13T02:35:27.284112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
3981.5 1
 
2.8%
383.0 1
 
2.8%
748.72 1
 
2.8%
338.61 1
 
2.8%
131.56 1
 
2.8%
694.48 1
 
2.8%
3535.0 1
 
2.8%
1082.6 1
 
2.8%
620.53 1
 
2.8%
58738.0 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
131.56 1
2.8%
160.0 1
2.8%
176.0 1
2.8%
198.0 1
2.8%
206.0 1
2.8%
247.0 1
2.8%
248.0 1
2.8%
260.0 1
2.8%
267.3 1
2.8%
330.0 1
2.8%
ValueCountFrequency (%)
58738.0 1
2.8%
36821.0 1
2.8%
11087.0 1
2.8%
4708.0 1
2.8%
3981.5 1
2.8%
3535.0 1
2.8%
2523.0 1
2.8%
1522.83 1
2.8%
1501.0 1
2.8%
1482.0 1
2.8%

등록일자
Date

Distinct21
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum1988-07-19 00:00:00
Maximum2023-02-06 00:00:00
2023-12-13T02:35:27.418804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:27.553965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

위도
Real number (ℝ)

Distinct34
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.184685
Minimum35.08251
Maximum35.311487
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-13T02:35:27.703952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.08251
5-th percentile35.113695
Q135.157602
median35.177731
Q335.204205
95-th percentile35.283495
Maximum35.311487
Range0.22897711
Interquartile range (IQR)0.046603233

Descriptive statistics

Standard deviation0.053905765
Coefficient of variation (CV)0.0015320804
Kurtosis0.00425865
Mean35.184685
Median Absolute Deviation (MAD)0.02691806
Skewness0.55462281
Sum1266.6486
Variance0.0029058315
MonotonicityNot monotonic
2023-12-13T02:35:27.847862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
35.16234629 3
 
8.3%
35.28304107 1
 
2.8%
35.10151142 1
 
2.8%
35.11775627 1
 
2.8%
35.179928 1
 
2.8%
35.28485665 1
 
2.8%
35.18412581 1
 
2.8%
35.16136947 1
 
2.8%
35.08250989 1
 
2.8%
35.27397579 1
 
2.8%
Other values (24) 24
66.7%
ValueCountFrequency (%)
35.08250989 1
2.8%
35.10151142 1
2.8%
35.11775627 1
2.8%
35.12023471 1
2.8%
35.12670634 1
2.8%
35.12850636 1
2.8%
35.13307653 1
2.8%
35.14548194 1
2.8%
35.14629972 1
2.8%
35.16136947 1
2.8%
ValueCountFrequency (%)
35.311487 1
2.8%
35.28485665 1
2.8%
35.28304107 1
2.8%
35.27397579 1
2.8%
35.2603461 1
2.8%
35.25395022 1
2.8%
35.24544591 1
2.8%
35.22161795 1
2.8%
35.20553743 1
2.8%
35.20376121 1
2.8%

경도
Real number (ℝ)

Distinct34
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.08052
Minimum128.91905
Maximum129.23553
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-13T02:35:27.974658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.91905
5-th percentile128.99619
Q1129.04787
median129.06143
Q3129.09369
95-th percentile129.22391
Maximum129.23553
Range0.3164831
Interquartile range (IQR)0.0458288

Descriptive statistics

Standard deviation0.069769025
Coefficient of variation (CV)0.00054050779
Kurtosis0.73320677
Mean129.08052
Median Absolute Deviation (MAD)0.0293296
Skewness0.66696725
Sum4646.8986
Variance0.0048677168
MonotonicityNot monotonic
2023-12-13T02:35:28.093349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
129.0552449 3
 
8.3%
129.0676164 1
 
2.8%
129.0194264 1
 
2.8%
128.9190509 1
 
2.8%
129.075091 1
 
2.8%
129.235534 1
 
2.8%
129.0905948 1
 
2.8%
129.126589 1
 
2.8%
129.0510452 1
 
2.8%
129.0488008 1
 
2.8%
Other values (24) 24
66.7%
ValueCountFrequency (%)
128.9190509 1
2.8%
128.9953964 1
2.8%
128.9964509 1
2.8%
129.0134786 1
2.8%
129.0194264 1
2.8%
129.0282155 1
2.8%
129.0299396 1
2.8%
129.0394788 1
2.8%
129.0450617 1
2.8%
129.0488008 1
2.8%
ValueCountFrequency (%)
129.235534 1
2.8%
129.225731 1
2.8%
129.223298 1
2.8%
129.222308 1
2.8%
129.1697356 1
2.8%
129.1597131 1
2.8%
129.1366103 1
2.8%
129.126589 1
2.8%
129.0987727 1
2.8%
129.0920022 1
2.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2023-09-14 00:00:00
Maximum2023-09-14 00:00:00
2023-12-13T02:35:28.200786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:28.619756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T02:35:22.187155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:19.676210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:20.323712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:20.925997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:21.604865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:22.342677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:19.780466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:20.438488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:21.073498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:21.746822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:22.445882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:19.889410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:20.547016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:21.200925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:21.869878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:22.563892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:20.031948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:20.665587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:21.352778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:21.971254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:22.699456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:20.146673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:20.791325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:21.484061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:35:22.080111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:35:28.703588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정호수사찰명법명도로명주소전화번호건물동수면적_제곱미터등록일자위도경도
지정호수1.0001.0001.0001.0001.0000.3060.0000.9570.7200.375
사찰명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
법명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
건물동수0.3061.0001.0001.0001.0001.0000.4490.3940.5220.000
면적_제곱미터0.0001.0001.0001.0001.0000.4491.0001.0000.6910.000
등록일자0.9571.0001.0001.0001.0000.3941.0001.0000.8560.658
위도0.7201.0001.0001.0001.0000.5220.6910.8561.0000.334
경도0.3751.0001.0001.0001.0000.0000.0000.6580.3341.000
2023-12-13T02:35:28.864557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정호수건물동수면적_제곱미터위도경도
지정호수1.0000.1230.3880.1010.486
건물동수0.1231.0000.4340.039-0.115
면적_제곱미터0.3880.4341.0000.1120.325
위도0.1010.0390.1121.0000.404
경도0.486-0.1150.3250.4041.000

Missing values

2023-12-13T02:35:22.902702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:35:23.155574image/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

지정호수사찰명법명도로명주소전화번호건물동수면적_제곱미터등록일자위도경도데이터기준일자
01梵魚寺(범어사)정혁수(보운)부산광역시 금정구 범어사로 250051-508-3122453981.51988-07-1935.283041129.0676162023-09-14
12摩訶寺(마하사)곽치영(정산)부산광역시 연제구 봉수로 138051-852-24366641.01988-07-1935.163827129.0875792023-09-14
23光明寺(광명사)남후남(무아)부산광역시 부산진구 안창로14번길 46051-646-08434363.91988-07-1935.1463129.0450622023-09-14
34燃燈寺(연등사)강덕용(덕륜)부산광역시 동구 좌천동로 17-3051-632-05464247.01988-07-1935.133077129.0491942023-09-14
45雲水寺(운수사)유인상(범일)부산광역시 사상구 모라로219번길 173051-317-56715248.01988-07-1935.184373129.0134792023-09-14
56仙岩寺(선암사)최광환(원타)부산광역시 부산진구 백양산로 138051-803-7573161361.51988-07-1935.175857129.0282152023-09-14
67甘泉寺(감천사)이은자(현일)부산광역시 연제구 묘봉산로 40051-852-690421148.81988-11-3035.18342129.0909262023-09-14
78瀛洲庵(영주암)이상융(범산)부산광역시 수영구 망미배산로76번나길 15051-754-22105613.881988-12-0535.176669129.0987732023-09-14
89金蓉庵(금용암)최지택(범수)부산광역시 연제구 성지곡로 111051-501-63004364.01988-12-0535.191591129.0496392023-09-14
910金水寺(금수사)안종명(상천)부산광역시 동구 망양로 533-1051-467-33167568.01988-12-0535.120235129.029942023-09-14
지정호수사찰명법명도로명주소전화번호건물동수면적_제곱미터등록일자위도경도데이터기준일자
2627玉蓮禪院(옥련선원)정일오(일오)부산광역시 수영구 광남로 257번길 58051-757-9067111082.61998-12-1735.161369129.1265892023-09-14
2728妙觀音寺(묘관음사)조찬구(서강)부산광역시 장안읍 해맞이로 253-38051-727-203517620.532008-01-1135.162346129.0552452023-09-14
2829內院精舍(내원정사)안희관(지일)부산광역시 서구 엄광산로40번길 21-22051-242-06911558738.02009-01-2235.101511129.0194262023-09-14
2930福泉寺(복천사)이혜문(혜문)부산광역시 영도구 산정길 41051-417-55511336821.02009-01-2935.08251129.0510452023-09-14
3031海雲精舍(해운정사)박창규(지삼)부산광역시 해운대구 우동2로 40-6051-746-225621501.02015-01-2235.168168129.1597132023-09-14
3132仁智寺(인지사)최갑성(법성)부산광역시 해운대구 반여3동 산131-5051-783-087661522.832015-01-2235.202325129.136612023-09-14
3233古佛寺(고불사)김계준(정오)부산광역시 기장군 철마면 고촌로28번길 77051-721-29272368.02017-01-1135.245446129.1697362023-09-14
3334海光寺(해광사)김영태(태공)부산광역시 기장군 기장읍 기장해안로 340051-721-3167511087.02018-01-1735.205537129.2257312023-09-14
3435玉井寺(옥정사)박행화(초삼)부산광역시 기장군 일광읍 달음길 101051-727-015092523.02023-02-0635.311487129.2223082023-09-14
3536海東龍宮寺(해동용궁사)김각모(덕림)부산광역시 기장군 기장읍 용궁길 86051-722-774444708.02023-02-0635.18839129.2232982023-09-14