Overview

Dataset statistics

Number of variables36
Number of observations39
Missing cells462
Missing cells (%)32.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.9 KiB
Average record size in memory311.4 B

Variable types

Numeric9
Categorical10
Text8
Unsupported9

Dataset

Description22년09월_6270000_대구광역시_03_07_11_P_전통사찰
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000096572&dataSetDetailId=DDI_0000096588&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
영업상태구분코드 has constant value ""Constant
영업상태명 has constant value ""Constant
지정취소일자 is highly imbalanced (82.8%)Imbalance
인허가취소일자 has 39 (100.0%) missing valuesMissing
폐업일자 has 39 (100.0%) missing valuesMissing
휴업시작일자 has 39 (100.0%) missing valuesMissing
휴업종료일자 has 39 (100.0%) missing valuesMissing
재개업일자 has 39 (100.0%) missing valuesMissing
소재지전화 has 4 (10.3%) missing valuesMissing
소재지면적 has 39 (100.0%) missing valuesMissing
소재지우편번호 has 39 (100.0%) missing valuesMissing
도로명전체주소 has 4 (10.3%) missing valuesMissing
도로명우편번호 has 32 (82.1%) missing valuesMissing
업태구분명 has 39 (100.0%) missing valuesMissing
좌표정보(X) has 2 (5.1%) missing valuesMissing
좌표정보(Y) has 2 (5.1%) missing valuesMissing
승려수 has 17 (43.6%) missing valuesMissing
신도수 has 17 (43.6%) missing valuesMissing
창립연대 has 19 (48.7%) missing valuesMissing
유래연혁 has 14 (35.9%) missing valuesMissing
지정취소사유 has 39 (100.0%) missing valuesMissing
번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지정취소사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
승려수 has 12 (30.8%) zerosZeros
신도수 has 13 (33.3%) zerosZeros

Reproduction

Analysis started2023-12-10 19:53:02.646918
Analysis finished2023-12-10 19:53:03.340163
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T04:53:03.417183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.9
Q110.5
median20
Q329.5
95-th percentile37.1
Maximum39
Range38
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.401754
Coefficient of variation (CV)0.57008771
Kurtosis-1.2
Mean20
Median Absolute Deviation (MAD)10
Skewness0
Sum780
Variance130
MonotonicityStrictly increasing
2023-12-11T04:53:03.559450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 1
 
2.6%
2 1
 
2.6%
23 1
 
2.6%
24 1
 
2.6%
25 1
 
2.6%
26 1
 
2.6%
27 1
 
2.6%
28 1
 
2.6%
29 1
 
2.6%
30 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
1 1
2.6%
2 1
2.6%
3 1
2.6%
4 1
2.6%
5 1
2.6%
6 1
2.6%
7 1
2.6%
8 1
2.6%
9 1
2.6%
10 1
2.6%
ValueCountFrequency (%)
39 1
2.6%
38 1
2.6%
37 1
2.6%
36 1
2.6%
35 1
2.6%
34 1
2.6%
33 1
2.6%
32 1
2.6%
31 1
2.6%
30 1
2.6%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
전통사찰
39 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전통사찰 39
100.0%

Length

2023-12-11T04:53:03.745967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:53:03.863143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전통사찰 39
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
03_07_11_P
39 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03_07_11_P
2nd row03_07_11_P
3rd row03_07_11_P
4th row03_07_11_P
5th row03_07_11_P

Common Values

ValueCountFrequency (%)
03_07_11_P 39
100.0%

Length

2023-12-11T04:53:03.969649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:53:04.063206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_07_11_p 39
100.0%

개방자치단체코드
Real number (ℝ)

Distinct6
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4896410.3
Minimum3410000
Maximum6270000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T04:53:04.143205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3420000
Q13455000
median6270000
Q36270000
95-th percentile6270000
Maximum6270000
Range2860000
Interquartile range (IQR)2815000

Descriptive statistics

Standard deviation1427833.3
Coefficient of variation (CV)0.29160818
Kurtosis-2.1071613
Mean4896410.3
Median Absolute Deviation (MAD)0
Skewness-0.053974632
Sum1.9096 × 108
Variance2.0387078 × 1012
MonotonicityIncreasing
2023-12-11T04:53:04.239526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6270000 20
51.3%
3480000 8
 
20.5%
3420000 6
 
15.4%
3440000 3
 
7.7%
3410000 1
 
2.6%
3470000 1
 
2.6%
ValueCountFrequency (%)
3410000 1
 
2.6%
3420000 6
 
15.4%
3440000 3
 
7.7%
3470000 1
 
2.6%
3480000 8
 
20.5%
6270000 20
51.3%
ValueCountFrequency (%)
6270000 20
51.3%
3480000 8
 
20.5%
3470000 1
 
2.6%
3440000 3
 
7.7%
3420000 6
 
15.4%
3410000 1
 
2.6%

관리번호
Text

Distinct28
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-11T04:53:04.430792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length9.5384615
Min length8

Characters and Unicode

Total characters372
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)56.4%

Sample

1st rowCDFD1001
2nd rowCDFD1001
3rd rowCDFD1002
4th rowCDFD1003
5th rowCDFD1004
ValueCountFrequency (%)
cdfd1001 5
 
12.8%
cdfd1003 3
 
7.7%
cdfd1002 3
 
7.7%
cdfd1004 2
 
5.1%
cdfd1005 2
 
5.1%
cdfd1006 2
 
5.1%
3480000-009 1
 
2.6%
3420000-006 1
 
2.6%
3480000-008 1
 
2.6%
3480000-004 1
 
2.6%
Other values (18) 18
46.2%
2023-12-11T04:53:04.798386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 158
42.5%
D 38
 
10.2%
1 31
 
8.3%
4 26
 
7.0%
3 25
 
6.7%
- 20
 
5.4%
C 19
 
5.1%
F 19
 
5.1%
2 13
 
3.5%
8 10
 
2.7%
Other values (4) 13
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 276
74.2%
Uppercase Letter 76
 
20.4%
Dash Punctuation 20
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 158
57.2%
1 31
 
11.2%
4 26
 
9.4%
3 25
 
9.1%
2 13
 
4.7%
8 10
 
3.6%
5 4
 
1.4%
6 4
 
1.4%
7 4
 
1.4%
9 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
D 38
50.0%
C 19
25.0%
F 19
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 296
79.6%
Latin 76
 
20.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 158
53.4%
1 31
 
10.5%
4 26
 
8.8%
3 25
 
8.4%
- 20
 
6.8%
2 13
 
4.4%
8 10
 
3.4%
5 4
 
1.4%
6 4
 
1.4%
7 4
 
1.4%
Latin
ValueCountFrequency (%)
D 38
50.0%
C 19
25.0%
F 19
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 158
42.5%
D 38
 
10.2%
1 31
 
8.3%
4 26
 
7.0%
3 25
 
6.7%
- 20
 
5.4%
C 19
 
5.1%
F 19
 
5.1%
2 13
 
3.5%
8 10
 
2.7%
Other values (4) 13
 
3.5%

인허가일자
Real number (ℝ)

Distinct12
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19886660
Minimum19620917
Maximum20220106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T04:53:04.946926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19620917
5-th percentile19880702
Q119880721
median19880728
Q319880913
95-th percentile19935202
Maximum20220106
Range599189
Interquartile range (IQR)192

Descriptive statistics

Standard deviation71386.746
Coefficient of variation (CV)0.00358968
Kurtosis17.432747
Mean19886660
Median Absolute Deviation (MAD)7
Skewness1.4641083
Sum7.7557974 × 108
Variance5.0960674 × 109
MonotonicityNot monotonic
2023-12-11T04:53:05.068708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
19880721 12
30.8%
19880728 10
25.6%
19880913 5
12.8%
19881012 3
 
7.7%
19881207 2
 
5.1%
19620917 1
 
2.6%
19980202 1
 
2.6%
19930202 1
 
2.6%
19880819 1
 
2.6%
19880528 1
 
2.6%
Other values (2) 2
 
5.1%
ValueCountFrequency (%)
19620917 1
 
2.6%
19880528 1
 
2.6%
19880721 12
30.8%
19880728 10
25.6%
19880819 1
 
2.6%
19880913 5
12.8%
19881012 3
 
7.7%
19881021 1
 
2.6%
19881207 2
 
5.1%
19930202 1
 
2.6%
ValueCountFrequency (%)
20220106 1
 
2.6%
19980202 1
 
2.6%
19930202 1
 
2.6%
19881207 2
 
5.1%
19881021 1
 
2.6%
19881012 3
 
7.7%
19880913 5
12.8%
19880819 1
 
2.6%
19880728 10
25.6%
19880721 12
30.8%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing39
Missing (%)100.0%
Memory size483.0 B

영업상태구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
1
39 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 39
100.0%

Length

2023-12-11T04:53:05.204267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:53:05.313288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 39
100.0%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
영업/정상
39 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 39
100.0%

Length

2023-12-11T04:53:05.430545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:53:05.550521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 39
100.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
BBBB
20 
05
19 

Length

Max length4
Median length4
Mean length3.025641
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05
2nd row05
3rd row05
4th row05
5th row05

Common Values

ValueCountFrequency (%)
BBBB 20
51.3%
05 19
48.7%

Length

2023-12-11T04:53:05.690635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:53:05.801054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bbbb 20
51.3%
05 19
48.7%

상세영업상태명
Categorical

Distinct2
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
<NA>
20 
지정
19 

Length

Max length4
Median length4
Mean length3.025641
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 20
51.3%
지정 19
48.7%

Length

2023-12-11T04:53:05.918513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:53:06.050451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
51.3%
지정 19
48.7%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing39
Missing (%)100.0%
Memory size483.0 B

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing39
Missing (%)100.0%
Memory size483.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing39
Missing (%)100.0%
Memory size483.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing39
Missing (%)100.0%
Memory size483.0 B

소재지전화
Text

MISSING 

Distinct34
Distinct (%)97.1%
Missing4
Missing (%)10.3%
Memory size444.0 B
2023-12-11T04:53:06.317205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.8
Min length8

Characters and Unicode

Total characters378
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

Unique33 ?
Unique (%)94.3%

Sample

1st row256-9651
2nd row053-984-2255
3rd row053-985-5214
4th row053-984-9940
5th row053-655-0225
ValueCountFrequency (%)
053-614-3115 2
 
5.7%
0539849940 1
 
2.9%
0539820511 1
 
2.9%
0536143115 1
 
2.9%
0539825006 1
 
2.9%
0539844550 1
 
2.9%
0539820505 1
 
2.9%
0536650225 1
 
2.9%
0536531572 1
 
2.9%
053-984-2255 1
 
2.9%
Other values (24) 24
68.6%
2023-12-11T04:53:06.772557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 66
17.5%
3 54
14.3%
0 53
14.0%
6 37
9.8%
1 33
8.7%
- 31
8.2%
4 28
7.4%
9 21
 
5.6%
8 21
 
5.6%
2 21
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 347
91.8%
Dash Punctuation 31
 
8.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 66
19.0%
3 54
15.6%
0 53
15.3%
6 37
10.7%
1 33
9.5%
4 28
8.1%
9 21
 
6.1%
8 21
 
6.1%
2 21
 
6.1%
7 13
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 378
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 66
17.5%
3 54
14.3%
0 53
14.0%
6 37
9.8%
1 33
8.7%
- 31
8.2%
4 28
7.4%
9 21
 
5.6%
8 21
 
5.6%
2 21
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 378
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 66
17.5%
3 54
14.3%
0 53
14.0%
6 37
9.8%
1 33
8.7%
- 31
8.2%
4 28
7.4%
9 21
 
5.6%
8 21
 
5.6%
2 21
 
5.6%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing39
Missing (%)100.0%
Memory size483.0 B

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing39
Missing (%)100.0%
Memory size483.0 B

소재지전체주소
Text

Distinct38
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-11T04:53:07.082039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length19.871795
Min length14

Characters and Unicode

Total characters775
Distinct characters63
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

Unique37 ?
Unique (%)94.9%

Sample

1st row대구광역시 중구 서야동 1-1번지
2nd row대구광역시 동구 도학동 35
3rd row대구광역시 동구 중대동 7번지
4th row대구광역시 동구 신무동 356-1번지
5th row대구광역시 동구 능성동 산 1-3번지
ValueCountFrequency (%)
대구광역시 39
21.5%
달성군 16
 
8.8%
동구 12
 
6.6%
남구 7
 
3.9%
산 6
 
3.3%
4
 
2.2%
1 4
 
2.2%
화원읍 4
 
2.2%
가창면 4
 
2.2%
봉덕동 4
 
2.2%
Other values (55) 81
44.8%
2023-12-11T04:53:07.506750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
181
23.4%
구 62
 
8.0%
대 43
 
5.5%
광 39
 
5.0%
역 39
 
5.0%
시 39
 
5.0%
동 35
 
4.5%
1 24
 
3.1%
달 18
 
2.3%
지 18
 
2.3%
Other values (53) 277
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 491
63.4%
Space Separator 181
 
23.4%
Decimal Number 94
 
12.1%
Dash Punctuation 9
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 62
 
12.6%
대 43
 
8.8%
광 39
 
7.9%
역 39
 
7.9%
시 39
 
7.9%
동 35
 
7.1%
달 18
 
3.7%
지 18
 
3.7%
번 18
 
3.7%
리 18
 
3.7%
Other values (41) 162
33.0%
Decimal Number
ValueCountFrequency (%)
1 24
25.5%
2 16
17.0%
5 12
12.8%
3 9
 
9.6%
8 8
 
8.5%
6 8
 
8.5%
4 7
 
7.4%
7 7
 
7.4%
0 2
 
2.1%
9 1
 
1.1%
Space Separator
ValueCountFrequency (%)
181
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 491
63.4%
Common 284
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 62
 
12.6%
대 43
 
8.8%
광 39
 
7.9%
역 39
 
7.9%
시 39
 
7.9%
동 35
 
7.1%
달 18
 
3.7%
지 18
 
3.7%
번 18
 
3.7%
리 18
 
3.7%
Other values (41) 162
33.0%
Common
ValueCountFrequency (%)
181
63.7%
1 24
 
8.5%
2 16
 
5.6%
5 12
 
4.2%
- 9
 
3.2%
3 9
 
3.2%
8 8
 
2.8%
6 8
 
2.8%
4 7
 
2.5%
7 7
 
2.5%
Other values (2) 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 491
63.4%
ASCII 284
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
181
63.7%
1 24
 
8.5%
2 16
 
5.6%
5 12
 
4.2%
- 9
 
3.2%
3 9
 
3.2%
8 8
 
2.8%
6 8
 
2.8%
4 7
 
2.5%
7 7
 
2.5%
Other values (2) 3
 
1.1%
Hangul
ValueCountFrequency (%)
구 62
 
12.6%
대 43
 
8.8%
광 39
 
7.9%
역 39
 
7.9%
시 39
 
7.9%
동 35
 
7.1%
달 18
 
3.7%
지 18
 
3.7%
번 18
 
3.7%
리 18
 
3.7%
Other values (41) 162
33.0%

도로명전체주소
Text

MISSING 

Distinct19
Distinct (%)54.3%
Missing4
Missing (%)10.3%
Memory size444.0 B
2023-12-11T04:53:07.727707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length23.742857
Min length21

Characters and Unicode

Total characters831
Distinct characters77
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

Unique3 ?
Unique (%)8.6%

Sample

1st row대구광역시 중구 북성로 19-1 (서야동)
2nd row대구광역시 동구 동화사1길 1 (도학동)
3rd row대구광역시 동구 파계로 741 (중대동)
4th row대구광역시 동구 팔공산로 967-28 (신무동)
5th row대구광역시 동구 갓바위로 350 (능성동)
ValueCountFrequency (%)
대구광역시 35
20.0%
달성군 13
 
7.4%
동구 11
 
6.3%
남구 7
 
4.0%
앞산순환로 6
 
3.4%
가창면 4
 
2.3%
봉덕동 4
 
2.3%
도학동 4
 
2.3%
유가면 3
 
1.7%
옥포면 2
 
1.1%
Other values (47) 86
49.1%
2023-12-11T04:53:08.107681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
140
 
16.8%
구 57
 
6.9%
대 39
 
4.7%
동 37
 
4.5%
광 35
 
4.2%
역 35
 
4.2%
시 35
 
4.2%
2 24
 
2.9%
( 22
 
2.6%
) 22
 
2.6%
Other values (67) 385
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 508
61.1%
Space Separator 140
 
16.8%
Decimal Number 125
 
15.0%
Open Punctuation 22
 
2.6%
Close Punctuation 22
 
2.6%
Dash Punctuation 13
 
1.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 57
 
11.2%
대 39
 
7.7%
동 37
 
7.3%
광 35
 
6.9%
역 35
 
6.9%
시 35
 
6.9%
로 20
 
3.9%
길 18
 
3.5%
성 16
 
3.1%
달 15
 
3.0%
Other values (52) 201
39.6%
Decimal Number
ValueCountFrequency (%)
2 24
19.2%
1 20
16.0%
4 16
12.8%
5 12
9.6%
6 11
8.8%
0 10
8.0%
3 10
8.0%
7 10
8.0%
8 6
 
4.8%
9 6
 
4.8%
Space Separator
ValueCountFrequency (%)
140
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 508
61.1%
Common 323
38.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 57
 
11.2%
대 39
 
7.7%
동 37
 
7.3%
광 35
 
6.9%
역 35
 
6.9%
시 35
 
6.9%
로 20
 
3.9%
길 18
 
3.5%
성 16
 
3.1%
달 15
 
3.0%
Other values (52) 201
39.6%
Common
ValueCountFrequency (%)
140
43.3%
2 24
 
7.4%
( 22
 
6.8%
) 22
 
6.8%
1 20
 
6.2%
4 16
 
5.0%
- 13
 
4.0%
5 12
 
3.7%
6 11
 
3.4%
0 10
 
3.1%
Other values (5) 33
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 508
61.1%
ASCII 323
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
140
43.3%
2 24
 
7.4%
( 22
 
6.8%
) 22
 
6.8%
1 20
 
6.2%
4 16
 
5.0%
- 13
 
4.0%
5 12
 
3.7%
6 11
 
3.4%
0 10
 
3.1%
Other values (5) 33
 
10.2%
Hangul
ValueCountFrequency (%)
구 57
 
11.2%
대 39
 
7.7%
동 37
 
7.3%
광 35
 
6.9%
역 35
 
6.9%
시 35
 
6.9%
로 20
 
3.9%
길 18
 
3.5%
성 16
 
3.1%
달 15
 
3.0%
Other values (52) 201
39.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)100.0%
Missing32
Missing (%)82.1%
Infinite0
Infinite (%)0.0%
Mean703315.57
Minimum700330
Maximum705827
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T04:53:08.251005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700330
5-th percentile700585
Q1701315
median704370
Q3705026
95-th percentile705587.9
Maximum705827
Range5497
Interquartile range (IQR)3711

Descriptive statistics

Standard deviation2244.4344
Coefficient of variation (CV)0.0031912196
Kurtosis-2.264492
Mean703315.57
Median Absolute Deviation (MAD)1457
Skewness-0.32656847
Sum4923209
Variance5037486
MonotonicityNot monotonic
2023-12-11T04:53:08.350098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
700330 1
 
2.6%
701450 1
 
2.6%
701180 1
 
2.6%
705030 1
 
2.6%
705022 1
 
2.6%
705827 1
 
2.6%
704370 1
 
2.6%
(Missing) 32
82.1%
ValueCountFrequency (%)
700330 1
2.6%
701180 1
2.6%
701450 1
2.6%
704370 1
2.6%
705022 1
2.6%
705030 1
2.6%
705827 1
2.6%
ValueCountFrequency (%)
705827 1
2.6%
705030 1
2.6%
705022 1
2.6%
704370 1
2.6%
701450 1
2.6%
701180 1
2.6%
700330 1
2.6%

사업장명
Text

Distinct20
Distinct (%)51.3%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-11T04:53:08.541575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.2051282
Min length3

Characters and Unicode

Total characters125
Distinct characters39
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.6%

Sample

1st row대성사
2nd row동화사
3rd row파계사
4th row부인사
5th row관암사
ValueCountFrequency (%)
대성사 2
 
5.1%
동화사 2
 
5.1%
용연사 2
 
5.1%
소재사 2
 
5.1%
현풍포교당 2
 
5.1%
용문사 2
 
5.1%
화장사 2
 
5.1%
운흥사 2
 
5.1%
남지장사 2
 
5.1%
유가사 2
 
5.1%
Other values (10) 19
48.7%
2023-12-11T04:53:08.887681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 37
29.6%
장 8
 
6.4%
지 4
 
3.2%
화 4
 
3.2%
용 4
 
3.2%
관 4
 
3.2%
대 2
 
1.6%
남 2
 
1.6%
운 2
 
1.6%
흥 2
 
1.6%
Other values (29) 56
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 37
29.6%
장 8
 
6.4%
지 4
 
3.2%
화 4
 
3.2%
용 4
 
3.2%
관 4
 
3.2%
대 2
 
1.6%
남 2
 
1.6%
운 2
 
1.6%
흥 2
 
1.6%
Other values (29) 56
44.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 37
29.6%
장 8
 
6.4%
지 4
 
3.2%
화 4
 
3.2%
용 4
 
3.2%
관 4
 
3.2%
대 2
 
1.6%
남 2
 
1.6%
운 2
 
1.6%
흥 2
 
1.6%
Other values (29) 56
44.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 37
29.6%
장 8
 
6.4%
지 4
 
3.2%
화 4
 
3.2%
용 4
 
3.2%
관 4
 
3.2%
대 2
 
1.6%
남 2
 
1.6%
운 2
 
1.6%
흥 2
 
1.6%
Other values (29) 56
44.8%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0137164 × 1013
Minimum2.0051221 × 1013
Maximum2.0220106 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T04:53:09.038447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0051221 × 1013
5-th percentile2.0051221 × 1013
Q12.0085509 × 1013
median2.0150403 × 1013
Q32.0195315 × 1013
95-th percentile2.0210236 × 1013
Maximum2.0220106 × 1013
Range1.6888486 × 1011
Interquartile range (IQR)1.0980551 × 1011

Descriptive statistics

Standard deviation5.7926149 × 1010
Coefficient of variation (CV)0.0028765793
Kurtosis-1.2917662
Mean2.0137164 × 1013
Median Absolute Deviation (MAD)4.9914051 × 1010
Skewness-0.33927933
Sum7.8534938 × 1014
Variance3.3554387 × 1021
MonotonicityNot monotonic
2023-12-11T04:53:09.197634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
20111030140918 1
 
2.6%
20210205150228 1
 
2.6%
20150403101845 1
 
2.6%
20200518094320 1
 
2.6%
20151105192834 1
 
2.6%
20160622175608 1
 
2.6%
20121213101918 1
 
2.6%
20200331151703 1
 
2.6%
20121213101529 1
 
2.6%
20190312094332 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
20051221140355 1
2.6%
20051221141352 1
2.6%
20051221141738 1
2.6%
20051221142541 1
2.6%
20051221142633 1
2.6%
20051221162322 1
2.6%
20051221162641 1
2.6%
20051221163053 1
2.6%
20061208102716 1
2.6%
20080912114802 1
2.6%
ValueCountFrequency (%)
20220106000000 1
2.6%
20210510180358 1
2.6%
20210205150228 1
2.6%
20200518094320 1
2.6%
20200331151703 1
2.6%
20200317153519 1
2.6%
20200317153405 1
2.6%
20200317153310 1
2.6%
20200317153234 1
2.6%
20200317153148 1
2.6%

데이터갱신구분
Categorical

Distinct2
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
I
29 
U
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowU
3rd rowU
4th rowU
5th rowU

Common Values

ValueCountFrequency (%)
I 29
74.4%
U 10
 
25.6%

Length

2023-12-11T04:53:09.359223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:53:09.483535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 29
74.4%
u 10
 
25.6%

데이터갱신일자
Categorical

Distinct8
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size444.0 B
2018-08-31 23:59:59.0
28 
2020-03-19 02:40:00.0
5 
2021-02-07 02:40:00.0
 
1
2021-05-12 02:40:00.0
 
1
2020-05-20 02:40:00.0
 
1
Other values (3)
3 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique6 ?
Unique (%)15.4%

Sample

1st row2018-08-31 23:59:59.0
2nd row2021-02-07 02:40:00.0
3rd row2020-03-19 02:40:00.0
4th row2020-03-19 02:40:00.0
5th row2020-03-19 02:40:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 28
71.8%
2020-03-19 02:40:00.0 5
 
12.8%
2021-02-07 02:40:00.0 1
 
2.6%
2021-05-12 02:40:00.0 1
 
2.6%
2020-05-20 02:40:00.0 1
 
2.6%
2020-04-02 02:40:00.0 1
 
2.6%
2019-03-14 02:40:00.0 1
 
2.6%
2022-01-08 00:22:40.0 1
 
2.6%

Length

2023-12-11T04:53:09.602247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:53:09.731621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 28
35.9%
23:59:59.0 28
35.9%
02:40:00.0 10
 
12.8%
2020-03-19 5
 
6.4%
2021-02-07 1
 
1.3%
2021-05-12 1
 
1.3%
2020-05-20 1
 
1.3%
2020-04-02 1
 
1.3%
2019-03-14 1
 
1.3%
2022-01-08 1
 
1.3%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing39
Missing (%)100.0%
Memory size483.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)59.5%
Missing2
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean344403.71
Minimum330723.05
Maximum356375.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T04:53:09.881113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum330723.05
5-th percentile334730.26
Q1339089.28
median344224.75
Q3350157.19
95-th percentile354879.69
Maximum356375.98
Range25652.933
Interquartile range (IQR)11067.909

Descriptive statistics

Standard deviation6822.6794
Coefficient of variation (CV)0.019810122
Kurtosis-0.61212687
Mean344403.71
Median Absolute Deviation (MAD)5135.4739
Skewness-0.036603341
Sum12742937
Variance46548954
MonotonicityNot monotonic
2023-12-11T04:53:10.042418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
343018.505397 2
 
5.1%
344232.429015 2
 
5.1%
337386.221764 2
 
5.1%
336523.874176 2
 
5.1%
330723.051179 2
 
5.1%
339089.278771 2
 
5.1%
344870.203207 2
 
5.1%
353559.370847 2
 
5.1%
347429.163283 2
 
5.1%
343584.798955 2
 
5.1%
Other values (12) 17
43.6%
ValueCountFrequency (%)
330723.051179 2
5.1%
335732.065324 1
2.6%
336235.347314 1
2.6%
336523.874176 2
5.1%
337386.221764 2
5.1%
339089.278771 2
5.1%
341009.613914 1
2.6%
341174.720263 1
2.6%
342290.305769 2
5.1%
343018.505397 2
5.1%
ValueCountFrequency (%)
356375.983882 1
2.6%
356116.38018 1
2.6%
354570.520602 2
5.1%
353559.370847 2
5.1%
350755.990556 2
5.1%
350157.187814 2
5.1%
347843.237937 2
5.1%
347429.163283 2
5.1%
344870.203207 2
5.1%
344232.429015 2
5.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)62.2%
Missing2
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean261670.52
Minimum244475.07
Maximum279147.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T04:53:10.216273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum244475.07
5-th percentile245073.35
Q1253176.94
median259308.72
Q3276486.01
95-th percentile278641.49
Maximum279147.54
Range34672.479
Interquartile range (IQR)23309.061

Descriptive statistics

Standard deviation11783.333
Coefficient of variation (CV)0.045031183
Kurtosis-1.2810012
Mean261670.52
Median Absolute Deviation (MAD)9804.0161
Skewness0.23873877
Sum9681809.4
Variance1.3884694 × 108
MonotonicityNot monotonic
2023-12-11T04:53:10.399077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
264890.836446 2
 
5.1%
259325.080735 2
 
5.1%
250825.607729 2
 
5.1%
245205.639346 2
 
5.1%
253176.944325 2
 
5.1%
278336.223852 2
 
5.1%
249504.70629 2
 
5.1%
259296.038621 2
 
5.1%
254464.698414 2
 
5.1%
259308.722436 2
 
5.1%
Other values (13) 17
43.6%
ValueCountFrequency (%)
244475.06508 1
2.6%
244544.21045 1
2.6%
245205.639346 2
5.1%
246861.633568 1
2.6%
249504.70629 2
5.1%
250825.607729 2
5.1%
253176.944325 2
5.1%
254464.698414 2
5.1%
256935.198813 1
2.6%
257841.782022 1
2.6%
ValueCountFrequency (%)
279147.544285 2
5.1%
278514.970334 2
5.1%
278336.223852 2
5.1%
276798.979491 1
2.6%
276567.03897 1
2.6%
276486.00514 2
5.1%
270023.293347 2
5.1%
264890.836446 2
5.1%
262722.859418 1
2.6%
259325.080735 2
5.1%

승려수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)31.8%
Missing17
Missing (%)43.6%
Infinite0
Infinite (%)0.0%
Mean7.0909091
Minimum0
Maximum100
Zeros12
Zeros (%)30.8%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T04:53:10.570195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile28.75
Maximum100
Range100
Interquartile range (IQR)4

Descriptive statistics

Standard deviation21.705626
Coefficient of variation (CV)3.0610498
Kurtosis17.892609
Mean7.0909091
Median Absolute Deviation (MAD)0
Skewness4.1443593
Sum156
Variance471.1342
MonotonicityNot monotonic
2023-12-11T04:53:10.735167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 12
30.8%
4 4
 
10.3%
1 2
 
5.1%
100 1
 
2.6%
30 1
 
2.6%
5 1
 
2.6%
3 1
 
2.6%
(Missing) 17
43.6%
ValueCountFrequency (%)
0 12
30.8%
1 2
 
5.1%
3 1
 
2.6%
4 4
 
10.3%
5 1
 
2.6%
30 1
 
2.6%
100 1
 
2.6%
ValueCountFrequency (%)
100 1
 
2.6%
30 1
 
2.6%
5 1
 
2.6%
4 4
 
10.3%
3 1
 
2.6%
1 2
 
5.1%
0 12
30.8%

신도수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)45.5%
Missing17
Missing (%)43.6%
Infinite0
Infinite (%)0.0%
Mean2254.5455
Minimum0
Maximum30000
Zeros13
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T04:53:10.906904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31025
95-th percentile5950
Maximum30000
Range30000
Interquartile range (IQR)1025

Descriptive statistics

Standard deviation6444.6898
Coefficient of variation (CV)2.8585317
Kurtosis18.324372
Mean2254.5455
Median Absolute Deviation (MAD)0
Skewness4.1606111
Sum49600
Variance41534026
MonotonicityNot monotonic
2023-12-11T04:53:11.081814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 13
33.3%
30000 1
 
2.6%
500 1
 
2.6%
300 1
 
2.6%
3000 1
 
2.6%
100 1
 
2.6%
5000 1
 
2.6%
6000 1
 
2.6%
3500 1
 
2.6%
1200 1
 
2.6%
(Missing) 17
43.6%
ValueCountFrequency (%)
0 13
33.3%
100 1
 
2.6%
300 1
 
2.6%
500 1
 
2.6%
1200 1
 
2.6%
3000 1
 
2.6%
3500 1
 
2.6%
5000 1
 
2.6%
6000 1
 
2.6%
30000 1
 
2.6%
ValueCountFrequency (%)
30000 1
 
2.6%
6000 1
 
2.6%
5000 1
 
2.6%
3500 1
 
2.6%
3000 1
 
2.6%
1200 1
 
2.6%
500 1
 
2.6%
300 1
 
2.6%
100 1
 
2.6%
0 13
33.3%

창립연대
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing19
Missing (%)48.7%
Memory size444.0 B
2023-12-11T04:53:11.354582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9.5
Mean length4.05
Min length3

Characters and Unicode

Total characters81
Distinct characters24
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

Unique20 ?
Unique (%)100.0%

Sample

1st row912
2nd row827
3rd row1922
4th row670
5th row493
ValueCountFrequency (%)
912 1
 
5.0%
827 1
 
5.0%
1358 1
 
5.0%
1930 1
 
5.0%
1525 1
 
5.0%
826 1
 
5.0%
684 1
 
5.0%
921 1
 
5.0%
연대미상(신라말추정 1
 
5.0%
926 1
 
5.0%
Other values (10) 10
50.0%
2023-12-11T04:53:11.867894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
14.8%
9 11
13.6%
1 11
13.6%
8 6
 
7.4%
6 5
 
6.2%
0 5
 
6.2%
3 3
 
3.7%
5 3
 
3.7%
4 3
 
3.7%
7 3
 
3.7%
Other values (14) 19
23.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
76.5%
Other Letter 15
 
18.5%
Open Punctuation 2
 
2.5%
Close Punctuation 2
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
신 2
13.3%
라 2
13.3%
대 2
13.3%
시 1
6.7%
중 1
6.7%
수 1
6.7%
연 1
6.7%
미 1
6.7%
상 1
6.7%
말 1
6.7%
Other values (2) 2
13.3%
Decimal Number
ValueCountFrequency (%)
2 12
19.4%
9 11
17.7%
1 11
17.7%
8 6
9.7%
6 5
8.1%
0 5
8.1%
3 3
 
4.8%
5 3
 
4.8%
4 3
 
4.8%
7 3
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66
81.5%
Hangul 15
 
18.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
18.2%
9 11
16.7%
1 11
16.7%
8 6
9.1%
6 5
7.6%
0 5
7.6%
3 3
 
4.5%
5 3
 
4.5%
4 3
 
4.5%
7 3
 
4.5%
Other values (2) 4
 
6.1%
Hangul
ValueCountFrequency (%)
신 2
13.3%
라 2
13.3%
대 2
13.3%
시 1
6.7%
중 1
6.7%
수 1
6.7%
연 1
6.7%
미 1
6.7%
상 1
6.7%
말 1
6.7%
Other values (2) 2
13.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
81.5%
Hangul 15
 
18.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
18.2%
9 11
16.7%
1 11
16.7%
8 6
9.1%
6 5
7.6%
0 5
7.6%
3 3
 
4.5%
5 3
 
4.5%
4 3
 
4.5%
7 3
 
4.5%
Other values (2) 4
 
6.1%
Hangul
ValueCountFrequency (%)
신 2
13.3%
라 2
13.3%
대 2
13.3%
시 1
6.7%
중 1
6.7%
수 1
6.7%
연 1
6.7%
미 1
6.7%
상 1
6.7%
말 1
6.7%
Other values (2) 2
13.3%

유래연혁
Text

MISSING 

Distinct25
Distinct (%)100.0%
Missing14
Missing (%)35.9%
Memory size444.0 B
2023-12-11T04:53:12.274652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length254
Median length142
Mean length125.76
Min length21

Characters and Unicode

Total characters3144
Distinct characters344
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

Unique25 ?
Unique (%)100.0%

Sample

1st row신라소지왕15년 (493년)극달화상이 창건하여 유가사라 불렀으나 832년 심지왕사가 중건하면서 겨울에도 절 주위에 오동나무꽃이 만발하여 동화사라 불렀음
2nd row파계사는 신라804년(애장왕 5년) 심지왕사가 창건 하였으며, 조선1605년(선조 38년) 계관법사가 임진왜란으로 소실된 것을 중창 하였고, 조선1695년(숙종21년) 현흥대사가 삼창하였다고 함. 절의 좌석 계곡에서 흐르는 물줄기가9군데나 되므로 이물이 흩어지지 못하게 잡아 모은다는 뜻에서 파계사라 함.
3rd row부인사는 선덕여왕 27년인 7세기경 창건하였다는 사전이 있고 또 선덕여왕의 묘가 있으며 그안에 선덕여왕의 영정을 모시고 해마다 음력3월 보름에 동민과 신도들이 사찰에서 선덕제를 지내는 것을 볼 때 부인이란 선덕여왕을 지칭하는 듯하며, 신라시대에는 왕비를 인이라 칭했기 때문에 선덕여왕의 원당이었던 듯하다.
4th row신라 고찰터에 전 종정 백암스님이 1962년 기도중 본 사찰을 복원함.
5th row도동 측백나무숲 인근에 위치한 전통사찰로 관음전, 3층석탑, 관음보살입상 등의 유물이 있음
ValueCountFrequency (%)
있음 7
 
1.0%
신라 7
 
1.0%
창건 7
 
1.0%
이 6
 
0.9%
그 6
 
0.9%
후 6
 
0.9%
함 5
 
0.7%
정면 5
 
0.7%
영조 4
 
0.6%
3칸 3
 
0.4%
Other values (551) 627
91.8%
2023-12-11T04:53:12.882499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
673
 
21.4%
사 69
 
2.2%
에 64
 
2.0%
이 64
 
2.0%
하 50
 
1.6%
년 49
 
1.6%
고 46
 
1.5%
가 45
 
1.4%
건 42
 
1.3%
. 41
 
1.3%
Other values (334) 2001
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2151
68.4%
Space Separator 673
 
21.4%
Decimal Number 194
 
6.2%
Other Punctuation 72
 
2.3%
Close Punctuation 18
 
0.6%
Open Punctuation 18
 
0.6%
Control 15
 
0.5%
Uppercase Letter 2
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 69
 
3.2%
에 64
 
3.0%
이 64
 
3.0%
하 50
 
2.3%
년 49
 
2.3%
고 46
 
2.1%
가 45
 
2.1%
건 42
 
2.0%
으 34
 
1.6%
왕 34
 
1.6%
Other values (315) 1654
76.9%
Decimal Number
ValueCountFrequency (%)
1 37
19.1%
2 27
13.9%
5 24
12.4%
3 23
11.9%
4 16
8.2%
9 16
8.2%
8 15
7.7%
7 14
 
7.2%
6 13
 
6.7%
0 9
 
4.6%
Other Punctuation
ValueCountFrequency (%)
. 41
56.9%
, 31
43.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
673
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Control
ValueCountFrequency (%)
15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2151
68.4%
Common 991
31.5%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 69
 
3.2%
에 64
 
3.0%
이 64
 
3.0%
하 50
 
2.3%
년 49
 
2.3%
고 46
 
2.1%
가 45
 
2.1%
건 42
 
2.0%
으 34
 
1.6%
왕 34
 
1.6%
Other values (315) 1654
76.9%
Common
ValueCountFrequency (%)
673
67.9%
. 41
 
4.1%
1 37
 
3.7%
, 31
 
3.1%
2 27
 
2.7%
5 24
 
2.4%
3 23
 
2.3%
) 18
 
1.8%
( 18
 
1.8%
4 16
 
1.6%
Other values (7) 83
 
8.4%
Latin
ValueCountFrequency (%)
A 1
50.0%
D 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2151
68.4%
ASCII 993
31.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
673
67.8%
. 41
 
4.1%
1 37
 
3.7%
, 31
 
3.1%
2 27
 
2.7%
5 24
 
2.4%
3 23
 
2.3%
) 18
 
1.8%
( 18
 
1.8%
4 16
 
1.6%
Other values (9) 85
 
8.6%
Hangul
ValueCountFrequency (%)
사 69
 
3.2%
에 64
 
3.0%
이 64
 
3.0%
하 50
 
2.3%
년 49
 
2.3%
고 46
 
2.1%
가 45
 
2.1%
건 42
 
2.0%
으 34
 
1.6%
왕 34
 
1.6%
Other values (315) 1654
76.9%

지정취소
Categorical

Distinct3
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size444.0 B
N
19 
A
19 
<NA>
 
1

Length

Max length4
Median length1
Mean length1.0769231
Min length1

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
N 19
48.7%
A 19
48.7%
<NA> 1
 
2.6%

Length

2023-12-11T04:53:13.095630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:53:13.289439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 19
48.7%
a 19
48.7%
na 1
 
2.6%

지정취소일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
<NA>
38 
19880728
 
1

Length

Max length8
Median length4
Mean length4.1025641
Min length4

Unique

Unique1 ?
Unique (%)2.6%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row19880728

Common Values

ValueCountFrequency (%)
<NA> 38
97.4%
19880728 1
 
2.6%

Length

2023-12-11T04:53:13.506384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:53:13.709755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 38
97.4%
19880728 1
 
2.6%

지정취소사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing39
Missing (%)100.0%
Memory size483.0 B

전통사찰명
Text

Distinct20
Distinct (%)51.3%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-11T04:53:13.957330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.2051282
Min length3

Characters and Unicode

Total characters125
Distinct characters39
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.6%

Sample

1st row대성사
2nd row동화사
3rd row파계사
4th row부인사
5th row관암사
ValueCountFrequency (%)
대성사 2
 
5.1%
동화사 2
 
5.1%
용연사 2
 
5.1%
소재사 2
 
5.1%
현풍포교당 2
 
5.1%
용문사 2
 
5.1%
화장사 2
 
5.1%
운흥사 2
 
5.1%
남지장사 2
 
5.1%
유가사 2
 
5.1%
Other values (10) 19
48.7%
2023-12-11T04:53:14.494743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 37
29.6%
장 8
 
6.4%
지 4
 
3.2%
화 4
 
3.2%
용 4
 
3.2%
관 4
 
3.2%
대 2
 
1.6%
남 2
 
1.6%
운 2
 
1.6%
흥 2
 
1.6%
Other values (29) 56
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 37
29.6%
장 8
 
6.4%
지 4
 
3.2%
화 4
 
3.2%
용 4
 
3.2%
관 4
 
3.2%
대 2
 
1.6%
남 2
 
1.6%
운 2
 
1.6%
흥 2
 
1.6%
Other values (29) 56
44.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 37
29.6%
장 8
 
6.4%
지 4
 
3.2%
화 4
 
3.2%
용 4
 
3.2%
관 4
 
3.2%
대 2
 
1.6%
남 2
 
1.6%
운 2
 
1.6%
흥 2
 
1.6%
Other values (29) 56
44.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 37
29.6%
장 8
 
6.4%
지 4
 
3.2%
화 4
 
3.2%
용 4
 
3.2%
관 4
 
3.2%
대 2
 
1.6%
남 2
 
1.6%
운 2
 
1.6%
흥 2
 
1.6%
Other values (29) 56
44.8%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)승려수신도수창립연대유래연혁지정취소지정취소일자지정취소사유전통사찰명
01전통사찰03_07_11_P3410000CDFD100119620917<NA>1영업/정상05지정<NA><NA><NA><NA>256-9651<NA><NA>대구광역시 중구 서야동 1-1번지대구광역시 중구 북성로 19-1 (서야동)700330대성사20111030140918I2018-08-31 23:59:59.0<NA>343018.505397264890.83644600<NA><NA>N<NA><NA>대성사
12전통사찰03_07_11_P3420000CDFD100119880728<NA>1영업/정상05지정<NA><NA><NA><NA><NA><NA><NA>대구광역시 동구 도학동 35대구광역시 동구 동화사1길 1 (도학동)<NA>동화사20210205150228U2021-02-07 02:40:00.0<NA>353559.370847278336.22385210030000<NA>신라소지왕15년 (493년)극달화상이 창건하여 유가사라 불렀으나 832년 심지왕사가 중건하면서 겨울에도 절 주위에 오동나무꽃이 만발하여 동화사라 불렀음N<NA><NA>동화사
23전통사찰03_07_11_P3420000CDFD100219880728<NA>1영업/정상05지정<NA><NA><NA><NA><NA><NA><NA>대구광역시 동구 중대동 7번지대구광역시 동구 파계로 741 (중대동)<NA>파계사20200317153405U2020-03-19 02:40:00.0<NA>347843.237937279147.54428530500<NA>파계사는 신라804년(애장왕 5년) 심지왕사가 창건 하였으며, 조선1605년(선조 38년) 계관법사가 임진왜란으로 소실된 것을 중창 하였고, 조선1695년(숙종21년) 현흥대사가 삼창하였다고 함. 절의 좌석 계곡에서 흐르는 물줄기가9군데나 되므로 이물이 흩어지지 못하게 잡아 모은다는 뜻에서 파계사라 함.N<NA><NA>파계사
34전통사찰03_07_11_P3420000CDFD100319880728<NA>1영업/정상05지정<NA><NA><NA><NA><NA><NA><NA>대구광역시 동구 신무동 356-1번지대구광역시 동구 팔공산로 967-28 (신무동)701450부인사20200317153310U2020-03-19 02:40:00.0<NA>350755.990556278514.9703345300<NA>부인사는 선덕여왕 27년인 7세기경 창건하였다는 사전이 있고 또 선덕여왕의 묘가 있으며 그안에 선덕여왕의 영정을 모시고 해마다 음력3월 보름에 동민과 신도들이 사찰에서 선덕제를 지내는 것을 볼 때 부인이란 선덕여왕을 지칭하는 듯하며, 신라시대에는 왕비를 인이라 칭했기 때문에 선덕여왕의 원당이었던 듯하다.N<NA><NA>부인사
45전통사찰03_07_11_P3420000CDFD100419980202<NA>1영업/정상05지정<NA><NA><NA><NA>053-984-2255<NA><NA>대구광역시 동구 능성동 산 1-3번지대구광역시 동구 갓바위로 350 (능성동)<NA>관암사20200317153234U2020-03-19 02:40:00.0<NA>356375.983882276798.97949143000<NA>신라 고찰터에 전 종정 백암스님이 1962년 기도중 본 사찰을 복원함.N19880728<NA>관암사
56전통사찰03_07_11_P3420000CDFD100519880728<NA>1영업/정상05지정<NA><NA><NA><NA>053-985-5214<NA><NA>대구광역시 동구 도학동 620번지대구광역시 동구 도장길 243 (도학동)<NA>북지장사20200317153519U2020-03-19 02:40:00.0<NA>354570.520602276486.0051400<NA><NA>N<NA><NA>북지장사
67전통사찰03_07_11_P3420000CDFD100619880913<NA>1영업/정상05지정<NA><NA><NA><NA>053-984-9940<NA><NA>대구광역시 동구 도동 672번지대구광역시 동구 둔산로 535 (도동)701180관음사20200317153148U2020-03-19 02:40:00.0<NA>350157.187814270023.29334700<NA>도동 측백나무숲 인근에 위치한 전통사찰로 관음전, 3층석탑, 관음보살입상 등의 유물이 있음N<NA><NA>관음사
78전통사찰03_07_11_P3440000CDFD100119880913<NA>1영업/정상05지정<NA><NA><NA><NA>053-655-0225<NA><NA>대구광역시 남구 대명동 산 225번지대구광역시 남구 앞산순환로 440 (대명동)705030안일사20111030154757I2018-08-31 23:59:59.0<NA>342290.305769259308.72243600<NA><NA>N<NA><NA>안일사
89전통사찰03_07_11_P3440000CDFD100219880913<NA>1영업/정상05지정<NA><NA><NA><NA>053-653-1572<NA><NA>대구광역시 남구 봉덕동 1572번지대구광역시 남구 앞산순환로 574-120 (봉덕동)705022은적사20150107164435I2018-08-31 23:59:59.0<NA>343584.798955259325.08073510<NA><NA>N<NA><NA>은적사
910전통사찰03_07_11_P3440000CDFD100319880728<NA>1영업/정상05지정<NA><NA><NA><NA>053-471-0414<NA><NA>대구광역시 남구 봉덕동 산 148번지대구광역시 남구 고산3길 96-4 (봉덕동)705827법장사20140402114430I2018-08-31 23:59:59.0<NA>344232.429015259296.0386211100<NA><NA>N<NA><NA>법장사
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)승려수신도수창립연대유래연혁지정취소지정취소일자지정취소사유전통사찰명
2930전통사찰03_07_11_P62700003440000-00119880819<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>0536650225<NA><NA>대구광역시 남구 대명동 산 225대구광역시 남구 앞산순환로 440 (대명동)<NA>안일사20190312094332U2019-03-14 02:40:00.0<NA>342290.305769259308.72243646000927옛날에 어느 임금이 길가다가 물좋고 정자 좋은곳이라 앉아서 쉬어간자리라 해서 안일사라 명하였다고 함A<NA><NA>안일사
3031전통사찰03_07_11_P62700003440000-00219880913<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>0536531572<NA><NA>대구광역시 남구 봉덕동 1572대구광역시 남구 앞산순환로 574-120 (봉덕동)<NA>은적사20061208102716I2018-08-31 23:59:59.0<NA>343584.798955259325.080735<NA><NA>926서기926년 신라55대 경애왕 3년 고려태조 8년에 창건한 유서 깊은 고찰로서 많은 불자들에게 영험삼찰로 이름이 나 있는 절이다. 후삼국말 후백제의 견훤이 신라를 침공, 국운이 위태로워 지자 경애왕이 왕건에게 도움을 청하나 왕건이 견훤에게 대패 한후 이곳에서 피신하여 생명을 구한 인연으로 후일 영조대사에게 발원하여 은적사를 창건하게 됨A<NA><NA>은적사
3132전통사찰03_07_11_P62700003440000-00319880528<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>0534710414<NA><NA>대구광역시 남구 봉덕동 산 148대구광역시 남구 고산3길 96-4 (봉덕동)<NA>법장사20090106105810I2018-08-31 23:59:59.0<NA>344232.429015259296.038621<NA><NA>연대미상(신라말추정)신라말 어느 임금이 왕자가 없음을 근심하여 고산사를 창건하여 기도도량으로 기도후 두 왕자를 탄생한 기념으로 3층 석탑을 건립. 임진왜란으로 고산사는 불타버리고 석탑만 남아있음. 1961년경 폐허가 된 절터위에 불자들에 의해 석탑을 재건하고 범당과 승방을 건립하여 법장사로 개칭A<NA><NA>법장사
3233전통사찰03_07_11_P62700003470000-00119880721<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>0536324844<NA><NA>대구광역시 달서구 상인동대구광역시 달서구 앞산순환로 12-25 (상인동)<NA>임휴사20130812175017I2018-08-31 23:59:59.0<NA>341174.720263258049.96986143500921월배달비골 대덕산 중턱에 있으며 신라54대 경명왕 5년에 영조선사가 창건. 고려태조 왕건이 팔공산에서 견훤과 싸움에서 대패하여 반야원과 안일암을 거쳐 이곳에서 쉬어 갔다함.A<NA><NA>임휴사
3334전통사찰03_07_11_P62700003480000-00119880721<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>0537687373<NA><NA>대구광역시 달성군 가창면 우록리대구광역시 달성군 가창면 남지장사길 127<NA>남지장사20160712150045I2018-08-31 23:59:59.0<NA>347429.163283249504.70629<NA><NA>684신라 문무왕때 양개조사가 창건. 당시에는 대웅전, 극락전, 명부전, 만세루, 사천왕문 등과 8동의 암자가 있어 규모가 컸다고 함. 고려 충숙왕 복위 2년(1333) 왕사인 보각국사가 중수하였으며 조선시대 고승 무학대가사 수도하였고 임진왜란때에는 사명대사가 승병들의 훈련장으로 사용했으나 병화로 소실되었다. 그 후 효종4년(1653년)부터 영조 45년까지 인혜, 모계, 지월대사 등이 재건 및 중수하였음. 이 남지장사에 대해서 북지장사가 팔공산 동화사 부근A<NA><NA>남지장사
3435전통사찰03_07_11_P62700003480000-00219880721<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>0537673883<NA><NA>대구광역시 달성군 가창면 오리 151대구광역시 달성군 가창면 헐티로 1068<NA>운흥사20171011192710I2018-08-31 23:59:59.0<NA>344870.203207254464.698414<NA><NA>826정확한 창건 연혁은 전해지지 않고 있으나 조선 광해군 12년(1620년)에 무념스님이 중건하였고 영조 27년(1757)에 치화스님이 다시 재건하였다고 전해지고 있음. 첫 이름은 동림사였으나 수암사라고도 불리었으며 외말사가 되면서 운흥사로 불리게 되었음.A<NA><NA>운흥사
3536전통사찰03_07_11_P62700003480000-00319881021<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>0536325516<NA><NA>대구광역시 달성군 화원읍 천내리<NA><NA>화장사20171107141003I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA>15251525년에 김보연이 부처님의 계시를 받아 동화사 화원포교당으로 삼았다가 화장사로 했음. 꿈속에서 나타난 노인이 김보연에게 어느 산밑에 돌 일곱개가 있는데 제일 끝에 있는 돌 근처에 절을 지으라고 일러주어 그곳에 지체없이 절을 지어 열심히 불공을 올리며 일생을 보냈으며 죽은후 일곱개의 사리가 나왔다고 함. 화장이란 화장세계를 뜻하며 극락세계란 의미이다. 건물규모는 원통전 정면 3칸 측면2칸 팔작지붕으로 되어있음.A<NA><NA>화장사
3637전통사찰03_07_11_P62700003480000-00419881207<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>0536319390<NA><NA>대구광역시 달성군 화원읍 본리리대구광역시 달성군 화원읍 화원휴양림길 132<NA>용문사20170713194637I2018-08-31 23:59:59.0<NA>339089.278771253176.944325<NA><NA>1930즐비하게 흩어져 있는 기와편이나 주위에 심어지 감나무, 추자나무의 연륜으로 보아 인흥사와도 관계 깊은 고찰로 추측할 수 있음. 이 절에 간직된 유물은 법고뿐이데 법고의 몸통인 나무의 결이나 만든 솜씨로 보아 상당희 오래된 것으로 짐작됨. 절로 들어가는 오른쪽 산기슭에 부도 두기가 놓여있다. 극락전쪽으로 놓인 부도에는 용연사 창건주 수월당대사라고 기록되어 있어 이 절을 지은 수님의 부도임을 알 수 있음.A<NA><NA>용문사
3738전통사찰03_07_11_P62700003480000-00819880721<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>0536146637<NA><NA>대구광역시 달성군 유가면 용리 4대구광역시 달성군 유가면 휴양림길 228<NA>소재사20080912114802I2018-08-31 23:59:59.0<NA>336523.874176244475.06508<NA><NA>1358신라시대에 창건되었다고 전해오며 그 후 고려 공민왕 7년(1358)에 진보법사가 중창하였고 조선 세조 3년(1457)에 활륜선사가, 중조 5년(1510)에 선주 외암선사가, 철종 8년(1857)에 법로화상이 중수하였음. 경내에는 대웅전, 명부전, 산령각이 있음. 대웅전은 정면 3칸, 측면 3칸의 단층맞배집으로 내삼출목, 외이출목의 다포식 건축이고 명부전은 정면 3칸, 측면 2칸의 단층 맞배짐으로 이익공양식의 건축임.A<NA><NA>소재사
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