Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells15417
Missing cells (%)11.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory122.0 B

Variable types

Text8
Categorical2
DateTime2
Numeric2

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실)
Author지방자치단체
URLhttps://www.data.go.kr/data/15114136/standard.do

Alerts

영업상태명 is highly imbalanced (83.7%)Imbalance
소재지도로명주소 has 189 (1.9%) missing valuesMissing
소재지지번주소 has 4611 (46.1%) missing valuesMissing
전화번호 has 6075 (60.8%) missing valuesMissing
건물면적 has 4542 (45.4%) missing valuesMissing
건물면적 is highly skewed (γ1 = 71.58735565)Skewed
건물면적 has 279 (2.8%) zerosZeros

Reproduction

Analysis started2024-05-11 10:01:47.589400
Analysis finished2024-05-11 10:02:01.112404
Duration13.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct9024
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:02:01.557117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length7.1538
Min length2

Characters and Unicode

Total characters71538
Distinct characters626
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8416 ?
Unique (%)84.2%

Sample

1st row율곡
2nd row용죽아랫말
3rd row유금2리
4th row신전경로당
5th row구룡(19통)경로당
ValueCountFrequency (%)
경로당 1226
 
10.0%
마을회관 351
 
2.9%
다기능회관 83
 
0.7%
종합복지회관 45
 
0.4%
광천읍 21
 
0.2%
주민쉼터 20
 
0.2%
마을회 18
 
0.1%
마을회관(경로당 18
 
0.1%
홍성읍 18
 
0.1%
갈산면 17
 
0.1%
Other values (9034) 10402
85.1%
2024-05-11T10:02:02.612386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 6866
 
9.6%
로 6791
 
9.5%
경 6781
 
9.5%
리 2921
 
4.1%
2265
 
3.2%
마 1513
 
2.1%
아 1462
 
2.0%
회 1437
 
2.0%
1 1345
 
1.9%
관 1333
 
1.9%
Other values (616) 38824
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63452
88.7%
Decimal Number 3802
 
5.3%
Space Separator 2265
 
3.2%
Open Punctuation 707
 
1.0%
Close Punctuation 707
 
1.0%
Uppercase Letter 350
 
0.5%
Other Punctuation 148
 
0.2%
Lowercase Letter 44
 
0.1%
Dash Punctuation 33
 
< 0.1%
Other Symbol 24
 
< 0.1%
Other values (3) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 6866
 
10.8%
로 6791
 
10.7%
경 6781
 
10.7%
리 2921
 
4.6%
마 1513
 
2.4%
아 1462
 
2.3%
회 1437
 
2.3%
관 1333
 
2.1%
을 1332
 
2.1%
동 1164
 
1.8%
Other values (564) 31852
50.2%
Uppercase Letter
ValueCountFrequency (%)
A 136
38.9%
L 47
 
13.4%
H 38
 
10.9%
T 29
 
8.3%
P 27
 
7.7%
C 18
 
5.1%
S 17
 
4.9%
K 16
 
4.6%
G 11
 
3.1%
B 5
 
1.4%
Other values (4) 6
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
e 27
61.4%
a 3
 
6.8%
h 2
 
4.5%
c 2
 
4.5%
k 2
 
4.5%
t 2
 
4.5%
p 2
 
4.5%
f 1
 
2.3%
n 1
 
2.3%
l 1
 
2.3%
Decimal Number
ValueCountFrequency (%)
1 1345
35.4%
2 1261
33.2%
3 513
 
13.5%
4 200
 
5.3%
5 167
 
4.4%
6 101
 
2.7%
7 80
 
2.1%
8 50
 
1.3%
9 45
 
1.2%
0 40
 
1.1%
Other Punctuation
ValueCountFrequency (%)
@ 94
63.5%
, 33
 
22.3%
. 11
 
7.4%
· 6
 
4.1%
& 2
 
1.4%
/ 2
 
1.4%
Math Symbol
ValueCountFrequency (%)
+ 2
50.0%
> 1
25.0%
= 1
25.0%
Other Symbol
ValueCountFrequency (%)
㉵ 22
91.7%
ⓐ 2
 
8.3%
Space Separator
ValueCountFrequency (%)
2265
100.0%
Open Punctuation
ValueCountFrequency (%)
( 707
100.0%
Close Punctuation
ValueCountFrequency (%)
) 707
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63474
88.7%
Common 7669
 
10.7%
Latin 395
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 6866
 
10.8%
로 6791
 
10.7%
경 6781
 
10.7%
리 2921
 
4.6%
마 1513
 
2.4%
아 1462
 
2.3%
회 1437
 
2.3%
관 1333
 
2.1%
을 1332
 
2.1%
동 1164
 
1.8%
Other values (565) 31874
50.2%
Latin
ValueCountFrequency (%)
A 136
34.4%
L 47
 
11.9%
H 38
 
9.6%
T 29
 
7.3%
P 27
 
6.8%
e 27
 
6.8%
C 18
 
4.6%
S 17
 
4.3%
K 16
 
4.1%
G 11
 
2.8%
Other values (16) 29
 
7.3%
Common
ValueCountFrequency (%)
2265
29.5%
1 1345
17.5%
2 1261
16.4%
( 707
 
9.2%
) 707
 
9.2%
3 513
 
6.7%
4 200
 
2.6%
5 167
 
2.2%
6 101
 
1.3%
@ 94
 
1.2%
Other values (15) 309
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63452
88.7%
ASCII 8055
 
11.3%
None 28
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 6866
 
10.8%
로 6791
 
10.7%
경 6781
 
10.7%
리 2921
 
4.6%
마 1513
 
2.4%
아 1462
 
2.3%
회 1437
 
2.3%
관 1333
 
2.1%
을 1332
 
2.1%
동 1164
 
1.8%
Other values (564) 31852
50.2%
ASCII
ValueCountFrequency (%)
2265
28.1%
1 1345
16.7%
2 1261
15.7%
( 707
 
8.8%
) 707
 
8.8%
3 513
 
6.4%
4 200
 
2.5%
5 167
 
2.1%
A 136
 
1.7%
6 101
 
1.3%
Other values (38) 653
 
8.1%
None
ValueCountFrequency (%)
㉵ 22
78.6%
· 6
 
21.4%
Enclosed Alphanum
ValueCountFrequency (%)
ⓐ 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

시설유형
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경로당
7630 
마을회관
1288 
마을회관및경로당
1082 

Length

Max length8
Median length3
Mean length3.6698
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경로당
2nd row마을회관
3rd row마을회관및경로당
4th row경로당
5th row경로당

Common Values

ValueCountFrequency (%)
경로당 7630
76.3%
마을회관 1288
 
12.9%
마을회관및경로당 1082
 
10.8%

Length

2024-05-11T10:02:03.021874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:02:03.331300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경로당 7630
76.3%
마을회관 1288
 
12.9%
마을회관및경로당 1082
 
10.8%

소재지도로명주소
Text

MISSING 

Distinct9555
Distinct (%)97.4%
Missing189
Missing (%)1.9%
Memory size156.2 KiB
2024-05-11T10:02:04.043628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length46
Mean length22.594944
Min length13

Characters and Unicode

Total characters221679
Distinct characters634
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9301 ?
Unique (%)94.8%

Sample

1st row강원도 강릉시 하슬라로232번길 7-3 (교동)
2nd row충청북도 옥천군 동이면 적하길 151
3rd row경상북도 경주시 강동면 강동로 253-3
4th row경상남도 창원시 의창구 대산면 대산북로 279번길 25-1
5th row전라북도 남원시 구룡길 55
ValueCountFrequency (%)
경기도 1492
 
3.1%
경상북도 1255
 
2.6%
경상남도 1147
 
2.4%
전라남도 874
 
1.8%
전라북도 866
 
1.8%
충청북도 738
 
1.5%
충청남도 565
 
1.2%
부산광역시 495
 
1.0%
강원특별자치도 381
 
0.8%
전북특별자치도 336
 
0.7%
Other values (13087) 40187
83.1%
2024-05-11T10:02:05.212396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38529
 
17.4%
도 8511
 
3.8%
1 7344
 
3.3%
길 7097
 
3.2%
시 7057
 
3.2%
로 5225
 
2.4%
2 4991
 
2.3%
면 4442
 
2.0%
경 4335
 
2.0%
동 4101
 
1.8%
Other values (624) 130047
58.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 142078
64.1%
Space Separator 38531
 
17.4%
Decimal Number 32863
 
14.8%
Dash Punctuation 2607
 
1.2%
Open Punctuation 2339
 
1.1%
Close Punctuation 2336
 
1.1%
Other Punctuation 794
 
0.4%
Uppercase Letter 107
 
< 0.1%
Lowercase Letter 23
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 8511
 
6.0%
길 7097
 
5.0%
시 7057
 
5.0%
로 5225
 
3.7%
면 4442
 
3.1%
경 4335
 
3.1%
동 4101
 
2.9%
남 3922
 
2.8%
북 3867
 
2.7%
구 3522
 
2.5%
Other values (579) 89999
63.3%
Uppercase Letter
ValueCountFrequency (%)
A 57
53.3%
C 11
 
10.3%
L 7
 
6.5%
H 6
 
5.6%
K 5
 
4.7%
S 5
 
4.7%
E 4
 
3.7%
R 3
 
2.8%
B 3
 
2.8%
T 2
 
1.9%
Other values (4) 4
 
3.7%
Decimal Number
ValueCountFrequency (%)
1 7344
22.3%
2 4991
15.2%
3 3703
11.3%
4 3025
9.2%
5 2831
 
8.6%
6 2530
 
7.7%
7 2292
 
7.0%
0 2149
 
6.5%
8 2035
 
6.2%
9 1963
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
e 10
43.5%
t 3
 
13.0%
p 2
 
8.7%
s 2
 
8.7%
l 2
 
8.7%
b 1
 
4.3%
i 1
 
4.3%
h 1
 
4.3%
k 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 742
93.5%
@ 48
 
6.0%
. 3
 
0.4%
: 1
 
0.1%
Space Separator
ValueCountFrequency (%)
38529
> 99.9%
　 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2337
99.9%
[ 2
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 2334
99.9%
] 2
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 2607
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 142078
64.1%
Common 79470
35.8%
Latin 131
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 8511
 
6.0%
길 7097
 
5.0%
시 7057
 
5.0%
로 5225
 
3.7%
면 4442
 
3.1%
경 4335
 
3.1%
동 4101
 
2.9%
남 3922
 
2.8%
북 3867
 
2.7%
구 3522
 
2.5%
Other values (579) 89999
63.3%
Latin
ValueCountFrequency (%)
A 57
43.5%
C 11
 
8.4%
e 10
 
7.6%
L 7
 
5.3%
H 6
 
4.6%
K 5
 
3.8%
S 5
 
3.8%
E 4
 
3.1%
t 3
 
2.3%
R 3
 
2.3%
Other values (14) 20
 
15.3%
Common
ValueCountFrequency (%)
38529
48.5%
1 7344
 
9.2%
2 4991
 
6.3%
3 3703
 
4.7%
4 3025
 
3.8%
5 2831
 
3.6%
- 2607
 
3.3%
6 2530
 
3.2%
( 2337
 
2.9%
) 2334
 
2.9%
Other values (11) 9239
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 142078
64.1%
ASCII 79598
35.9%
None 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38529
48.4%
1 7344
 
9.2%
2 4991
 
6.3%
3 3703
 
4.7%
4 3025
 
3.8%
5 2831
 
3.6%
- 2607
 
3.3%
6 2530
 
3.2%
( 2337
 
2.9%
) 2334
 
2.9%
Other values (33) 9367
 
11.8%
Hangul
ValueCountFrequency (%)
도 8511
 
6.0%
길 7097
 
5.0%
시 7057
 
5.0%
로 5225
 
3.7%
면 4442
 
3.1%
경 4335
 
3.1%
동 4101
 
2.9%
남 3922
 
2.8%
북 3867
 
2.7%
구 3522
 
2.5%
Other values (579) 89999
63.3%
None
ValueCountFrequency (%)
　 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지지번주소
Text

MISSING 

Distinct5272
Distinct (%)97.8%
Missing4611
Missing (%)46.1%
Memory size156.2 KiB
2024-05-11T10:02:05.947833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length35
Mean length21.012433
Min length1

Characters and Unicode

Total characters113236
Distinct characters407
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5158 ?
Unique (%)95.7%

Sample

1st row충청북도 옥천군 동이면 적하리 472-3
2nd row경상북도 경주시 강동면 유금리 1402
3rd row경상북도 안동시 서후면 태장리 693
4th row부산광역시 강서구명지동 3343
5th row충청북도 청주시 흥덕구 남촌동 36-1
ValueCountFrequency (%)
경기도 955
 
3.7%
전라남도 827
 
3.2%
경상북도 562
 
2.2%
충청북도 427
 
1.7%
충청남도 416
 
1.6%
경상남도 365
 
1.4%
익산시 321
 
1.3%
부산광역시 315
 
1.2%
강원특별자치도 300
 
1.2%
청주시 254
 
1.0%
Other values (7056) 20837
81.5%
2024-05-11T10:02:07.223957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20200
 
17.8%
도 4679
 
4.1%
1 4223
 
3.7%
시 3881
 
3.4%
- 3545
 
3.1%
리 3279
 
2.9%
동 2909
 
2.6%
2 2663
 
2.4%
면 2443
 
2.2%
3 2286
 
2.0%
Other values (397) 63128
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68419
60.4%
Decimal Number 20887
 
18.4%
Space Separator 20203
 
17.8%
Dash Punctuation 3545
 
3.1%
Other Punctuation 166
 
0.1%
Uppercase Letter 7
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 4679
 
6.8%
시 3881
 
5.7%
리 3279
 
4.8%
동 2909
 
4.3%
면 2443
 
3.6%
남 2220
 
3.2%
경 2079
 
3.0%
구 1851
 
2.7%
산 1780
 
2.6%
북 1689
 
2.5%
Other values (376) 41609
60.8%
Decimal Number
ValueCountFrequency (%)
1 4223
20.2%
2 2663
12.7%
3 2286
10.9%
4 2021
9.7%
5 1880
9.0%
6 1832
8.8%
7 1621
 
7.8%
8 1511
 
7.2%
0 1426
 
6.8%
9 1424
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
L 2
28.6%
B 2
28.6%
A 2
28.6%
H 1
14.3%
Space Separator
ValueCountFrequency (%)
20200
> 99.9%
　 3
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 3545
100.0%
Other Punctuation
ValueCountFrequency (%)
, 166
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68419
60.4%
Common 44809
39.6%
Latin 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 4679
 
6.8%
시 3881
 
5.7%
리 3279
 
4.8%
동 2909
 
4.3%
면 2443
 
3.6%
남 2220
 
3.2%
경 2079
 
3.0%
구 1851
 
2.7%
산 1780
 
2.6%
북 1689
 
2.5%
Other values (376) 41609
60.8%
Common
ValueCountFrequency (%)
20200
45.1%
1 4223
 
9.4%
- 3545
 
7.9%
2 2663
 
5.9%
3 2286
 
5.1%
4 2021
 
4.5%
5 1880
 
4.2%
6 1832
 
4.1%
7 1621
 
3.6%
8 1511
 
3.4%
Other values (6) 3027
 
6.8%
Latin
ValueCountFrequency (%)
L 2
25.0%
B 2
25.0%
A 2
25.0%
H 1
12.5%
b 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68419
60.4%
ASCII 44814
39.6%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20200
45.1%
1 4223
 
9.4%
- 3545
 
7.9%
2 2663
 
5.9%
3 2286
 
5.1%
4 2021
 
4.5%
5 1880
 
4.2%
6 1832
 
4.1%
7 1621
 
3.6%
8 1511
 
3.4%
Other values (10) 3032
 
6.8%
Hangul
ValueCountFrequency (%)
도 4679
 
6.8%
시 3881
 
5.7%
리 3279
 
4.8%
동 2909
 
4.3%
면 2443
 
3.6%
남 2220
 
3.2%
경 2079
 
3.0%
구 1851
 
2.7%
산 1780
 
2.6%
북 1689
 
2.5%
Other values (376) 41609
60.8%
None
ValueCountFrequency (%)
　 3
100.0%

위도
Text

Distinct9631
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:02:07.850392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.1515
Min length1

Characters and Unicode

Total characters111515
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9267 ?
Unique (%)92.7%

Sample

1st row37.7708028186
2nd row36.2728166176
3rd row36.00536635
4th row35.3675445234
5th row35.4294235
ValueCountFrequency (%)
37.59447253 3
 
< 0.1%
38.2114302387 3
 
< 0.1%
36.04163448 3
 
< 0.1%
37.54716677 3
 
< 0.1%
35.33858688 2
 
< 0.1%
35.42459326 2
 
< 0.1%
35.48664915 2
 
< 0.1%
35.15812028 2
 
< 0.1%
35.87891808 2
 
< 0.1%
35.0987611482 2
 
< 0.1%
Other values (9620) 9973
99.8%
2024-05-11T10:02:09.062090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 17631
15.8%
5 12203
10.9%
7 10771
9.7%
6 10318
9.3%
. 9997
9.0%
1 9049
8.1%
2 8802
7.9%
9 8588
7.7%
4 8575
7.7%
8 8195
7.3%
Other values (2) 7386
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101515
91.0%
Other Punctuation 9997
 
9.0%
Space Separator 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 17631
17.4%
5 12203
12.0%
7 10771
10.6%
6 10318
10.2%
1 9049
8.9%
2 8802
8.7%
9 8588
8.5%
4 8575
8.4%
8 8195
8.1%
0 7383
7.3%
Other Punctuation
ValueCountFrequency (%)
. 9997
100.0%
Space Separator
ValueCountFrequency (%)
　 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 111515
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 17631
15.8%
5 12203
10.9%
7 10771
9.7%
6 10318
9.3%
. 9997
9.0%
1 9049
8.1%
2 8802
7.9%
9 8588
7.7%
4 8575
7.7%
8 8195
7.3%
Other values (2) 7386
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 111512
> 99.9%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 17631
15.8%
5 12203
10.9%
7 10771
9.7%
6 10318
9.3%
. 9997
9.0%
1 9049
8.1%
2 8802
7.9%
9 8588
7.7%
4 8575
7.7%
8 8195
7.3%
None
ValueCountFrequency (%)
　 3
100.0%

경도
Text

Distinct9640
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:02:09.652547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length11.5489
Min length1

Characters and Unicode

Total characters115489
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9285 ?
Unique (%)92.8%

Sample

1st row128.8766433791
2nd row127.6415957455
3rd row129.2733514
4th row128.6737710105
5th row127.3762703
ValueCountFrequency (%)
127.012706 3
 
< 0.1%
127.6639251754 3
 
< 0.1%
127.0056772 3
 
< 0.1%
129.3513838 3
 
< 0.1%
127.4840758 2
 
< 0.1%
126.6837151 2
 
< 0.1%
128.5802818395 2
 
< 0.1%
126.6507508 2
 
< 0.1%
127.01697 2
 
< 0.1%
126.7084537 2
 
< 0.1%
Other values (9629) 9973
99.8%
2024-05-11T10:02:10.974049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17312
15.0%
2 16769
14.5%
7 11633
10.1%
6 10354
9.0%
8 10294
8.9%
. 9997
8.7%
9 8761
7.6%
3 7898
6.8%
5 7648
6.6%
4 7614
6.6%
Other values (2) 7209
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 105489
91.3%
Other Punctuation 9997
 
8.7%
Space Separator 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17312
16.4%
2 16769
15.9%
7 11633
11.0%
6 10354
9.8%
8 10294
9.8%
9 8761
8.3%
3 7898
7.5%
5 7648
7.3%
4 7614
7.2%
0 7206
6.8%
Other Punctuation
ValueCountFrequency (%)
. 9997
100.0%
Space Separator
ValueCountFrequency (%)
　 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 115489
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17312
15.0%
2 16769
14.5%
7 11633
10.1%
6 10354
9.0%
8 10294
8.9%
. 9997
8.7%
9 8761
7.6%
3 7898
6.8%
5 7648
6.6%
4 7614
6.6%
Other values (2) 7209
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 115486
> 99.9%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17312
15.0%
2 16769
14.5%
7 11633
10.1%
6 10354
9.0%
8 10294
8.9%
. 9997
8.7%
9 8761
7.6%
3 7898
6.8%
5 7648
6.6%
4 7614
6.6%
None
ValueCountFrequency (%)
　 3
100.0%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업
9760 
폐업
 
240

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 9760
97.6%
폐업 240
 
2.4%

Length

2024-05-11T10:02:11.821033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:02:12.199881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 9760
97.6%
폐업 240
 
2.4%

전화번호
Text

MISSING 

Distinct3396
Distinct (%)86.5%
Missing6075
Missing (%)60.8%
Memory size156.2 KiB
2024-05-11T10:02:12.971475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.993885
Min length9

Characters and Unicode

Total characters47076
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

Unique3300 ?
Unique (%)84.1%

Sample

1st row054-000-0000
2nd row055-761-3645
3rd row031-216-5204
4th row031-655-8277
5th row062-962-2622
ValueCountFrequency (%)
043-871-3355 103
 
2.6%
054-000-0000 69
 
1.8%
053-665-2532 50
 
1.3%
033-670-2452 45
 
1.1%
02-879-0000 37
 
0.9%
000-0000-0000 37
 
0.9%
043-871-3973 34
 
0.9%
000-000-0000 33
 
0.8%
033-370-2439 28
 
0.7%
033-370-2315 8
 
0.2%
Other values (3386) 3481
88.7%
2024-05-11T10:02:14.331024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 7847
16.7%
0 7371
15.7%
3 5668
12.0%
5 4764
10.1%
1 3875
8.2%
4 3640
7.7%
2 3626
7.7%
6 3205
6.8%
7 2686
 
5.7%
8 2399
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39229
83.3%
Dash Punctuation 7847
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7371
18.8%
3 5668
14.4%
5 4764
12.1%
1 3875
9.9%
4 3640
9.3%
2 3626
9.2%
6 3205
8.2%
7 2686
 
6.8%
8 2399
 
6.1%
9 1995
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 7847
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47076
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 7847
16.7%
0 7371
15.7%
3 5668
12.0%
5 4764
10.1%
1 3875
8.2%
4 3640
7.7%
2 3626
7.7%
6 3205
6.8%
7 2686
 
5.7%
8 2399
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47076
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 7847
16.7%
0 7371
15.7%
3 5668
12.0%
5 4764
10.1%
1 3875
8.2%
4 3640
7.7%
2 3626
7.7%
6 3205
6.8%
7 2686
 
5.7%
8 2399
 
5.1%

건립일자
Date

Distinct4970
Distinct (%)49.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1900-01-01 00:00:00
Maximum2024-01-11 00:00:00
2024-05-11T10:02:14.902029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:02:15.470158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

건물면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct2787
Distinct (%)51.1%
Missing4542
Missing (%)45.4%
Infinite0
Infinite (%)0.0%
Mean129.37222
Minimum0
Maximum99036
Zeros279
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:02:16.139272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q167.235
median91.13
Q3130
95-th percentile239.018
Maximum99036
Range99036
Interquartile range (IQR)62.765

Descriptive statistics

Standard deviation1353.9968
Coefficient of variation (CV)10.4659
Kurtosis5221.4436
Mean129.37222
Median Absolute Deviation (MAD)27.55
Skewness71.587356
Sum706113.58
Variance1833307.3
MonotonicityNot monotonic
2024-05-11T10:02:17.133558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 279
 
2.8%
66.0 70
 
0.7%
99.0 64
 
0.6%
84.0 50
 
0.5%
83.0 38
 
0.4%
98.0 34
 
0.3%
90.0 32
 
0.3%
100.0 32
 
0.3%
30.0 29
 
0.3%
73.0 28
 
0.3%
Other values (2777) 4802
48.0%
(Missing) 4542
45.4%
ValueCountFrequency (%)
0.0 279
2.8%
12.0 1
 
< 0.1%
13.0 1
 
< 0.1%
14.81 1
 
< 0.1%
15.0 2
 
< 0.1%
17.0 1
 
< 0.1%
18.0 1
 
< 0.1%
20.0 7
 
0.1%
20.3 1
 
< 0.1%
20.5 1
 
< 0.1%
ValueCountFrequency (%)
99036.0 1
< 0.1%
11557.0 1
< 0.1%
6545.0 1
< 0.1%
3104.0 1
< 0.1%
2289.0 1
< 0.1%
1500.0 1
< 0.1%
1225.0 1
< 0.1%
1125.0 1
< 0.1%
824.94 1
< 0.1%
793.0 1
< 0.1%

관리기관명
Text

Distinct501
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:02:17.961444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length9.4647
Min length2

Characters and Unicode

Total characters94647
Distinct characters286
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique297 ?
Unique (%)3.0%

Sample

1st row강원도 강릉시청
2nd row충청북도 옥천군청
3rd row경상북도 경주시청
4th row대산면
5th row전라북도 남원시청
ValueCountFrequency (%)
경상북도 1255
 
6.1%
경기도 1223
 
6.0%
경상남도 898
 
4.4%
전라북도 866
 
4.2%
전라남도 819
 
4.0%
충청북도 805
 
3.9%
충청남도 511
 
2.5%
강원특별자치도 427
 
2.1%
부산광역시 396
 
1.9%
서울특별시 372
 
1.8%
Other values (535) 12948
63.1%
2024-05-11T10:02:19.104354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10520
 
11.1%
청 8643
 
9.1%
도 7505
 
7.9%
시 6285
 
6.6%
경 4179
 
4.4%
북 3586
 
3.8%
군 3220
 
3.4%
남 2870
 
3.0%
구 2359
 
2.5%
상 2231
 
2.4%
Other values (276) 43249
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83883
88.6%
Space Separator 10520
 
11.1%
Decimal Number 232
 
0.2%
Uppercase Letter 7
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 8643
 
10.3%
도 7505
 
8.9%
시 6285
 
7.5%
경 4179
 
5.0%
북 3586
 
4.3%
군 3220
 
3.8%
남 2870
 
3.4%
구 2359
 
2.8%
상 2231
 
2.7%
전 2174
 
2.6%
Other values (258) 40831
48.7%
Decimal Number
ValueCountFrequency (%)
1 78
33.6%
2 74
31.9%
4 23
 
9.9%
3 20
 
8.6%
5 12
 
5.2%
7 10
 
4.3%
6 6
 
2.6%
8 5
 
2.2%
9 3
 
1.3%
0 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
L 2
28.6%
H 2
28.6%
C 2
28.6%
K 1
14.3%
Space Separator
ValueCountFrequency (%)
10520
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83883
88.6%
Common 10757
 
11.4%
Latin 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 8643
 
10.3%
도 7505
 
8.9%
시 6285
 
7.5%
경 4179
 
5.0%
북 3586
 
4.3%
군 3220
 
3.8%
남 2870
 
3.4%
구 2359
 
2.8%
상 2231
 
2.7%
전 2174
 
2.6%
Other values (258) 40831
48.7%
Common
ValueCountFrequency (%)
10520
97.8%
1 78
 
0.7%
2 74
 
0.7%
4 23
 
0.2%
3 20
 
0.2%
5 12
 
0.1%
7 10
 
0.1%
6 6
 
0.1%
8 5
 
< 0.1%
9 3
 
< 0.1%
Other values (4) 6
 
0.1%
Latin
ValueCountFrequency (%)
L 2
28.6%
H 2
28.6%
C 2
28.6%
K 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83883
88.6%
ASCII 10764
 
11.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10520
97.7%
1 78
 
0.7%
2 74
 
0.7%
4 23
 
0.2%
3 20
 
0.2%
5 12
 
0.1%
7 10
 
0.1%
6 6
 
0.1%
8 5
 
< 0.1%
9 3
 
< 0.1%
Other values (8) 13
 
0.1%
Hangul
ValueCountFrequency (%)
청 8643
 
10.3%
도 7505
 
8.9%
시 6285
 
7.5%
경 4179
 
5.0%
북 3586
 
4.3%
군 3220
 
3.8%
남 2870
 
3.4%
구 2359
 
2.8%
상 2231
 
2.7%
전 2174
 
2.6%
Other values (258) 40831
48.7%

데이터기준일자
Date

Distinct58
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-05-31 00:00:00
Maximum2024-04-24 00:00:00
2024-05-11T10:02:19.663147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:02:20.169988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Real number (ℝ)

Distinct126
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4557901.2
Minimum3010000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:02:20.669232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3010000
5-th percentile3290000
Q13990000
median4680000
Q35100000
95-th percentile5680000
Maximum6520000
Range3510000
Interquartile range (IQR)1110000

Descriptive statistics

Standard deviation742773.86
Coefficient of variation (CV)0.16296401
Kurtosis-0.79946724
Mean4557901.2
Median Absolute Deviation (MAD)530000
Skewness-0.19537931
Sum4.5579012 × 1010
Variance5.5171301 × 1011
MonotonicityNot monotonic
2024-05-11T10:02:21.309709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5710000 254
 
2.5%
5670000 250
 
2.5%
4390000 226
 
2.3%
3910000 218
 
2.2%
4050000 209
 
2.1%
4810000 187
 
1.9%
4900000 186
 
1.9%
5310000 183
 
1.8%
5530000 181
 
1.8%
4680000 163
 
1.6%
Other values (116) 7943
79.4%
ValueCountFrequency (%)
3010000 13
 
0.1%
3020000 31
0.3%
3060000 28
0.3%
3070000 47
0.5%
3100000 55
0.5%
3140000 39
0.4%
3150000 51
0.5%
3200000 37
0.4%
3210000 33
0.3%
3220000 38
0.4%
ValueCountFrequency (%)
6520000 51
 
0.5%
5710000 254
2.5%
5700000 76
 
0.8%
5680000 142
1.4%
5670000 250
2.5%
5590000 84
 
0.8%
5530000 181
1.8%
5480000 128
1.3%
5470000 100
 
1.0%
5460000 103
1.0%

제공기관명
Text

Distinct126
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:02:22.109305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.3323
Min length7

Characters and Unicode

Total characters83323
Distinct characters100
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원도 강릉시
2nd row충청북도 옥천군
3rd row경상북도 경주시
4th row경상남도 창원시
5th row전북특별자치도 남원시
ValueCountFrequency (%)
경기도 1552
 
7.8%
경상북도 1255
 
6.3%
경상남도 1148
 
5.7%
전라남도 897
 
4.5%
충청북도 821
 
4.1%
전북특별자치도 608
 
3.0%
전라북도 594
 
3.0%
충청남도 565
 
2.8%
부산광역시 542
 
2.7%
강원특별자치도 465
 
2.3%
Other values (114) 11553
57.8%
2024-05-11T10:02:23.523945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10000
 
12.0%
도 8304
 
10.0%
시 7065
 
8.5%
경 4229
 
5.1%
북 3506
 
4.2%
군 3352
 
4.0%
남 3172
 
3.8%
상 2437
 
2.9%
전 2226
 
2.7%
구 2008
 
2.4%
Other values (90) 37024
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73323
88.0%
Space Separator 10000
 
12.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 8304
 
11.3%
시 7065
 
9.6%
경 4229
 
5.8%
북 3506
 
4.8%
군 3352
 
4.6%
남 3172
 
4.3%
상 2437
 
3.3%
전 2226
 
3.0%
구 2008
 
2.7%
주 1844
 
2.5%
Other values (89) 35180
48.0%
Space Separator
ValueCountFrequency (%)
10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73323
88.0%
Common 10000
 
12.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 8304
 
11.3%
시 7065
 
9.6%
경 4229
 
5.8%
북 3506
 
4.8%
군 3352
 
4.6%
남 3172
 
4.3%
상 2437
 
3.3%
전 2226
 
3.0%
구 2008
 
2.7%
주 1844
 
2.5%
Other values (89) 35180
48.0%
Common
ValueCountFrequency (%)
10000
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73323
88.0%
ASCII 10000
 
12.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10000
100.0%
Hangul
ValueCountFrequency (%)
도 8304
 
11.3%
시 7065
 
9.6%
경 4229
 
5.8%
북 3506
 
4.8%
군 3352
 
4.6%
남 3172
 
4.3%
상 2437
 
3.3%
전 2226
 
3.0%
구 2008
 
2.7%
주 1844
 
2.5%
Other values (89) 35180
48.0%

Interactions

2024-05-11T10:01:58.221239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:01:57.488328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:01:58.688129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:01:57.856898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T10:02:23.834488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형영업상태명건물면적데이터기준일자제공기관코드
시설유형1.0000.0530.0000.7960.568
영업상태명0.0531.0000.0000.5440.166
건물면적0.0000.0001.0000.0000.000
데이터기준일자0.7960.5440.0001.0000.964
제공기관코드0.5680.1660.0000.9641.000
2024-05-11T10:02:24.106746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형영업상태명
시설유형1.0000.087
영업상태명0.0871.000
2024-05-11T10:02:24.364736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물면적제공기관코드시설유형영업상태명
건물면적1.000-0.1430.0000.000
제공기관코드-0.1431.0000.3020.157
시설유형0.0000.3021.0000.087
영업상태명0.0000.1570.0871.000

Missing values

2024-05-11T10:01:59.131354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T10:02:00.127381image/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.
2024-05-11T10:02:00.787560image/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

시설명시설유형소재지도로명주소소재지지번주소위도경도영업상태명전화번호건립일자건물면적관리기관명데이터기준일자제공기관코드제공기관명
1044율곡경로당강원도 강릉시 하슬라로232번길 7-3 (교동)<NA>37.7708028186128.8766433791영업<NA>2011-12-01<NA>강원도 강릉시청2023-05-314200000강원도 강릉시
27655용죽아랫말마을회관충청북도 옥천군 동이면 적하길 151충청북도 옥천군 동이면 적하리 472-336.2728166176127.6415957455영업<NA>2008-10-22<NA>충청북도 옥천군청2023-07-044430000충청북도 옥천군
5795유금2리마을회관및경로당경상북도 경주시 강동면 강동로 253-3경상북도 경주시 강동면 유금리 140236.00536635129.2733514영업<NA>2005-03-11<NA>경상북도 경주시청2023-06-295050000경상북도 경주시
18753신전경로당경로당경상남도 창원시 의창구 대산면 대산북로 279번길 25-1<NA>35.3675445234128.6737710105영업<NA>1995-03-130.0대산면2023-07-105670000경상남도 창원시
39851구룡(19통)경로당경로당전라북도 남원시 구룡길 55<NA>35.4294235127.3762703영업<NA>2003-01-0167.5전라북도 남원시청2023-07-144701000전북특별자치도 남원시
37570상태장덕산경로당마을회관및경로당경상북도 안동시 서후면 국화향길 16경상북도 안동시 서후면 태장리 69336.63810156128.674289영업<NA>1997-09-24106.95경상북도 안동시2023-12-065070000경상북도 안동시
18816내감부인경로당경로당경상남도 창원시 의창구 북면 내감1길 20(북면)<NA>35.3010794992128.5908020871영업<NA>1999-10-190.0북면2023-07-105670000경상남도 창원시
19581명지2차금강경로당경로당부산광역시 강서구 명지국제5로109 (명지동,금강2차)부산광역시 강서구명지동 334335.10421503128.9191938영업<NA>2017-06-29179.08부산광역시 강서구청2023-07-073360000부산광역시 강서구
15978남촌경로당충청북도 청주시 흥덕구 남촌로 35충청북도 청주시 흥덕구 남촌동 36-136.65923438127.4215507영업<NA>1997-02-04<NA>충청북도 청주시청2023-07-135710000충청북도 청주시
27990교리 마을회관마을회관경상북도 청송군 청송읍 한실길 11경상북도 청송군 청송읍 교리 10736.40248439129.1154149영업054-000-00002009-09-02100.42경상북도 청송군청2023-07-135160000경상북도 청송군
시설명시설유형소재지도로명주소소재지지번주소위도경도영업상태명전화번호건립일자건물면적관리기관명데이터기준일자제공기관코드제공기관명
4945원범왕경로당마을회관및경로당경상남도 하동군 화개면 원범왕길 19-2<NA>35.2841673121127.6180160363영업<NA>2014-05-01<NA>경상남도 하동군청2023-07-135440000경상남도 하동군
22736구항면 장양경로당경로당충청남도 홍성군 구항면 구항서길100번길 2-3충청남도 홍성군 구항면 장양리 606-336.5798402857126.5870387157영업041-633-86612012-01-01214.0충청남도 홍성군청2023-07-034600000충청남도 홍성군
37402답곡1리마을회관마을회관경상북도 고령군 우곡면 답곡1길 84<NA>35.64403281128.377936영업<NA>2000-01-01<NA>경상북도 고령군청2024-01-035200000경상북도 고령군
31171마산리경로당경로당경상북도 포항시 북구 흥해읍 신흥로 889<NA>36.11189499129.3401918영업054-262-90871988-01-01<NA>경상북도 포항시 북구청2023-08-305020000경상북도 포항시
11520오향경로당경로당전라북도 군산시 설림5길 31(소룡동)<NA>35.97105556126.6838608영업<NA>2005-12-30<NA>전라북도 군산시 복지환경국 경로장애인2023-06-274670000전라북도 군산시
37716고란리모치경로당마을회관및경로당경상북도 안동시 길안면 고란길 353경상북도 안동시 길안면 고란리 산 18-236.40165204128.9570086영업<NA>2012-12-3069.9경상북도 안동시2023-12-065070000경상북도 안동시
272무평경로당경로당전라북도 익산시 망성면 무평2길 29전라북도 익산시 망성면 무형리 354-136.1241577127.0414654영업<NA>1979-03-18<NA>전라북도 익산시청2023-06-084680000전라북도 익산시
31674동부산동원로얄듀크경로당경로당부산광역시 기장군 기장읍 기장대로 67<NA>129.205687435.20396322영업<NA>2005-05-31<NA>동부산동원로얄듀크아파트2023-08-203400000부산광역시 기장군
10830서강APT경로당경로당광주광역시 북구 어매마을길17번길 16 (매곡동 매곡동 서강아파트)광주광역시 북구 매곡동 215-235.19190522126.8940237영업<NA>2004-03-2934.0광주광역시 북구청2023-07-103620000광주광역시 북구
25811노송 경로당경로당충청남도 부여군 규암면 왕흥로155번길 52충청남도 부여군 규암면 오수리 17936.2973778126.8900034영업041-835-81891998-12-3173.0충청남도 부여군청2023-07-114570000충청남도 부여군