Overview

Dataset statistics

Number of variables10
Number of observations135
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.9 KiB
Average record size in memory83.0 B

Variable types

Text3
Categorical3
Numeric2
DateTime2

Dataset

Description부산광역시 사상구의 2024년 3월 기준 등록 경로당 현황으로 경로당 명, 행정동, 소재지, 연락처 등의 항목을 제공합니다.
Author부산광역시 사상구
URLhttps://www.data.go.kr/data/15025707/fileData.do

Alerts

시설유형 has constant value ""Constant
영업상태명 has constant value ""Constant
관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
시설명 has unique valuesUnique

Reproduction

Analysis started2024-03-23 04:56:38.906903
Analysis finished2024-03-23 04:56:42.038107
Duration3.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-23T04:56:42.541648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length7.0888889
Min length5

Characters and Unicode

Total characters957
Distinct characters166
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

Unique135 ?
Unique (%)100.0%

Sample

1st row삼락강변경로당
2nd row동양한신경로당
3rd row삼락분회경로당
4th row삼락경로당
5th row부녀경로당
ValueCountFrequency (%)
경로당 5
 
3.6%
삼락강변경로당 1
 
0.7%
기호경로당 1
 
0.7%
학산경로당 1
 
0.7%
학송경로당 1
 
0.7%
한효경로당 1
 
0.7%
희망경로당 1
 
0.7%
진사경로당 1
 
0.7%
무지개경로당 1
 
0.7%
조양경로당 1
 
0.7%
Other values (126) 126
90.0%
2024-03-23T04:56:43.800618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 138
 
14.4%
로 137
 
14.3%
당 135
 
14.1%
동 26
 
2.7%
아 23
 
2.4%
파 20
 
2.1%
트 18
 
1.9%
학 15
 
1.6%
신 15
 
1.6%
지 12
 
1.3%
Other values (156) 418
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 938
98.0%
Decimal Number 14
 
1.5%
Space Separator 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 138
 
14.7%
로 137
 
14.6%
당 135
 
14.4%
동 26
 
2.8%
아 23
 
2.5%
파 20
 
2.1%
트 18
 
1.9%
학 15
 
1.6%
신 15
 
1.6%
지 12
 
1.3%
Other values (151) 399
42.5%
Decimal Number
ValueCountFrequency (%)
2 8
57.1%
1 4
28.6%
3 1
 
7.1%
4 1
 
7.1%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 938
98.0%
Common 19
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 138
 
14.7%
로 137
 
14.6%
당 135
 
14.4%
동 26
 
2.8%
아 23
 
2.5%
파 20
 
2.1%
트 18
 
1.9%
학 15
 
1.6%
신 15
 
1.6%
지 12
 
1.3%
Other values (151) 399
42.5%
Common
ValueCountFrequency (%)
2 8
42.1%
5
26.3%
1 4
21.1%
3 1
 
5.3%
4 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 938
98.0%
ASCII 19
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 138
 
14.7%
로 137
 
14.6%
당 135
 
14.4%
동 26
 
2.8%
아 23
 
2.5%
파 20
 
2.1%
트 18
 
1.9%
학 15
 
1.6%
신 15
 
1.6%
지 12
 
1.3%
Other values (151) 399
42.5%
ASCII
ValueCountFrequency (%)
2 8
42.1%
5
26.3%
1 4
21.1%
3 1
 
5.3%
4 1
 
5.3%

시설유형
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
경로당
135 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경로당 135
100.0%

Length

2024-03-23T04:56:44.382969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T04:56:44.794756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경로당 135
100.0%

소재지도로명주소
Text

Distinct132
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-23T04:56:45.319833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length35
Mean length27.866667
Min length17

Characters and Unicode

Total characters3762
Distinct characters156
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique129 ?
Unique (%)95.6%

Sample

1st row부산 사상구 낙동대로 1258번길 30 (삼락동)
2nd row 부산 사상구 운산로 25(삼락동,동양한신아파트)
3rd row부산 사상구 삼덕로 46번길 76-10(삼락동)
4th row부산 사상구 낙동대로 1530번길 5(삼락동)
5th row부산 사상구 삼덕로 46번길 76-10(삼락동)
ValueCountFrequency (%)
사상구 134
21.4%
부산 129
20.6%
백양대로 34
 
5.4%
사상로 12
 
1.9%
대동로 12
 
1.9%
학감대로 11
 
1.8%
모라로 8
 
1.3%
엄궁로 7
 
1.1%
낙동대로 6
 
1.0%
부산광역시 6
 
1.0%
Other values (215) 266
42.6%
2024-03-23T04:56:46.486562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
499
 
13.3%
동 171
 
4.5%
상 154
 
4.1%
사 150
 
4.0%
산 144
 
3.8%
구 141
 
3.7%
로 137
 
3.6%
부 136
 
3.6%
( 135
 
3.6%
) 135
 
3.6%
Other values (146) 1960
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2266
60.2%
Decimal Number 593
 
15.8%
Space Separator 499
 
13.3%
Open Punctuation 135
 
3.6%
Close Punctuation 135
 
3.6%
Other Punctuation 87
 
2.3%
Dash Punctuation 43
 
1.1%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 171
 
7.5%
상 154
 
6.8%
사 150
 
6.6%
산 144
 
6.4%
구 141
 
6.2%
로 137
 
6.0%
부 136
 
6.0%
번 76
 
3.4%
길 76
 
3.4%
대 74
 
3.3%
Other values (128) 1007
44.4%
Decimal Number
ValueCountFrequency (%)
1 96
16.2%
2 88
14.8%
3 72
12.1%
4 63
10.6%
0 61
10.3%
5 50
8.4%
6 47
7.9%
9 42
7.1%
8 40
6.7%
7 34
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 84
96.6%
. 3
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
L 2
50.0%
G 2
50.0%
Space Separator
ValueCountFrequency (%)
499
100.0%
Open Punctuation
ValueCountFrequency (%)
( 135
100.0%
Close Punctuation
ValueCountFrequency (%)
) 135
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2266
60.2%
Common 1492
39.7%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 171
 
7.5%
상 154
 
6.8%
사 150
 
6.6%
산 144
 
6.4%
구 141
 
6.2%
로 137
 
6.0%
부 136
 
6.0%
번 76
 
3.4%
길 76
 
3.4%
대 74
 
3.3%
Other values (128) 1007
44.4%
Common
ValueCountFrequency (%)
499
33.4%
( 135
 
9.0%
) 135
 
9.0%
1 96
 
6.4%
2 88
 
5.9%
, 84
 
5.6%
3 72
 
4.8%
4 63
 
4.2%
0 61
 
4.1%
5 50
 
3.4%
Other values (6) 209
14.0%
Latin
ValueCountFrequency (%)
L 2
50.0%
G 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2266
60.2%
ASCII 1496
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
499
33.4%
( 135
 
9.0%
) 135
 
9.0%
1 96
 
6.4%
2 88
 
5.9%
, 84
 
5.6%
3 72
 
4.8%
4 63
 
4.2%
0 61
 
4.1%
5 50
 
3.3%
Other values (8) 213
14.2%
Hangul
ValueCountFrequency (%)
동 171
 
7.5%
상 154
 
6.8%
사 150
 
6.6%
산 144
 
6.4%
구 141
 
6.2%
로 137
 
6.0%
부 136
 
6.0%
번 76
 
3.4%
길 76
 
3.4%
대 74
 
3.3%
Other values (128) 1007
44.4%

위도
Real number (ℝ)

Distinct132
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.158832
Minimum35.12392
Maximum35.194795
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-23T04:56:46.982306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.12392
5-th percentile35.128528
Q135.143002
median35.155072
Q335.172901
95-th percentile35.190738
Maximum35.194795
Range0.07087459
Interquartile range (IQR)0.02989857

Descriptive statistics

Standard deviation0.01972568
Coefficient of variation (CV)0.00056104481
Kurtosis-1.0206327
Mean35.158832
Median Absolute Deviation (MAD)0.01588276
Skewness0.18794424
Sum4746.4423
Variance0.00038910246
MonotonicityNot monotonic
2024-03-23T04:56:47.581693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.18916268 2
 
1.5%
35.17107671 2
 
1.5%
35.15462889 2
 
1.5%
35.1461918 1
 
0.7%
35.15563805 1
 
0.7%
35.15211653 1
 
0.7%
35.1468221 1
 
0.7%
35.14496258 1
 
0.7%
35.14513143 1
 
0.7%
35.14823869 1
 
0.7%
Other values (122) 122
90.4%
ValueCountFrequency (%)
35.12392024 1
0.7%
35.12452232 1
0.7%
35.12502612 1
0.7%
35.12503062 1
0.7%
35.12607161 1
0.7%
35.12749355 1
0.7%
35.12780307 1
0.7%
35.12883809 1
0.7%
35.12893895 1
0.7%
35.1295078 1
0.7%
ValueCountFrequency (%)
35.19479483 1
0.7%
35.19434849 1
0.7%
35.19284622 1
0.7%
35.19273454 1
0.7%
35.19252913 1
0.7%
35.19168182 1
0.7%
35.19098783 1
0.7%
35.19063081 1
0.7%
35.19000896 1
0.7%
35.18996124 1
0.7%

경도
Real number (ℝ)

Distinct132
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.99115
Minimum128.96819
Maximum129.01642
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-23T04:56:48.233462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.96819
5-th percentile128.97499
Q1128.98341
median128.98975
Q3128.99809
95-th percentile129.01312
Maximum129.01642
Range0.0482377
Interquartile range (IQR)0.01468285

Descriptive statistics

Standard deviation0.011206599
Coefficient of variation (CV)8.6878814 × 10-5
Kurtosis-0.41234373
Mean128.99115
Median Absolute Deviation (MAD)0.0076232
Skewness0.38817947
Sum17413.806
Variance0.00012558785
MonotonicityNot monotonic
2024-03-23T04:56:48.975054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.9880204 2
 
1.5%
128.9807536 2
 
1.5%
128.9793046 2
 
1.5%
129.0013277 1
 
0.7%
129.0143619 1
 
0.7%
129.0140108 1
 
0.7%
129.014395 1
 
0.7%
129.004989 1
 
0.7%
129.0009306 1
 
0.7%
129.005589 1
 
0.7%
Other values (122) 122
90.4%
ValueCountFrequency (%)
128.9681865 1
0.7%
128.96919 1
0.7%
128.9707393 1
0.7%
128.9734507 1
0.7%
128.9735996 1
0.7%
128.9742211 1
0.7%
128.9748465 1
0.7%
128.9750454 1
0.7%
128.9758324 1
0.7%
128.9765206 1
0.7%
ValueCountFrequency (%)
129.0164242 1
0.7%
129.0157343 1
0.7%
129.0146426 1
0.7%
129.014395 1
0.7%
129.0143619 1
0.7%
129.0140108 1
0.7%
129.0132629 1
0.7%
129.0130597 1
0.7%
129.0128473 1
0.7%
129.0101461 1
0.7%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
영업
135 

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 135
100.0%

Length

2024-03-23T04:56:49.615729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T04:56:49.922399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 135
100.0%

전화번호
Text

Distinct134
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-23T04:56:50.589797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.007407
Min length12

Characters and Unicode

Total characters1621
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique133 ?
Unique (%)98.5%

Sample

1st row051-305-5963
2nd row051-304-4672
3rd row051-303-3668
4th row051-302-8605
5th row051-305-6617
ValueCountFrequency (%)
051-999-9999 2
 
1.5%
051-305-5963 1
 
0.7%
051-326-7293 1
 
0.7%
051-316-3232 1
 
0.7%
051-328-7333 1
 
0.7%
051-314-5848 1
 
0.7%
051-322-9955 1
 
0.7%
051-311-4312 1
 
0.7%
051-313-3243 1
 
0.7%
051-323-6670 1
 
0.7%
Other values (124) 124
91.9%
2024-03-23T04:56:51.899793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 270
16.7%
1 258
15.9%
0 213
13.1%
5 211
13.0%
3 196
12.1%
2 115
7.1%
9 95
 
5.9%
6 78
 
4.8%
4 70
 
4.3%
7 57
 
3.5%
Other values (2) 58
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1350
83.3%
Dash Punctuation 270
 
16.7%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 258
19.1%
0 213
15.8%
5 211
15.6%
3 196
14.5%
2 115
8.5%
9 95
 
7.0%
6 78
 
5.8%
4 70
 
5.2%
7 57
 
4.2%
8 57
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 270
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1621
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 270
16.7%
1 258
15.9%
0 213
13.1%
5 211
13.0%
3 196
12.1%
2 115
7.1%
9 95
 
5.9%
6 78
 
4.8%
4 70
 
4.3%
7 57
 
3.5%
Other values (2) 58
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1621
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 270
16.7%
1 258
15.9%
0 213
13.1%
5 211
13.0%
3 196
12.1%
2 115
7.1%
9 95
 
5.9%
6 78
 
4.8%
4 70
 
4.3%
7 57
 
3.5%
Other values (2) 58
 
3.6%

건립일자
Date

Distinct102
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1989-05-20 00:00:00
Maximum2023-12-07 00:00:00
2024-03-23T04:56:52.515868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:56:53.320215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
부산광역시 사상구청
135 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 사상구청
2nd row부산광역시 사상구청
3rd row부산광역시 사상구청
4th row부산광역시 사상구청
5th row부산광역시 사상구청

Common Values

ValueCountFrequency (%)
부산광역시 사상구청 135
100.0%

Length

2024-03-23T04:56:53.934368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T04:56:54.368832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 135
50.0%
사상구청 135
50.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2024-03-18 00:00:00
Maximum2024-03-18 00:00:00
2024-03-23T04:56:54.740518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:56:55.140246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-23T04:56:40.462957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:56:39.765835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:56:40.804034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T04:56:40.132224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T04:56:55.291953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.838
경도0.8381.000
2024-03-23T04:56:55.583494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.230
경도0.2301.000

Missing values

2024-03-23T04:56:41.276429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T04:56:41.851976image/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

시설명시설유형소재지도로명주소위도경도영업상태명전화번호건립일자관리기관명데이터기준일자
0삼락강변경로당경로당부산 사상구 낙동대로 1258번길 30 (삼락동)35.172113128.978526영업051-305-59631993-03-23부산광역시 사상구청2024-03-18
1동양한신경로당경로당부산 사상구 운산로 25(삼락동,동양한신아파트)35.169606128.979858영업051-304-46721997-04-10부산광역시 사상구청2024-03-18
2삼락분회경로당경로당부산 사상구 삼덕로 46번길 76-10(삼락동)35.171077128.980754영업051-303-36681991-11-14부산광역시 사상구청2024-03-18
3삼락경로당경로당부산 사상구 낙동대로 1530번길 5(삼락동)35.194348128.98547영업051-302-86051989-05-20부산광역시 사상구청2024-03-18
4부녀경로당경로당부산 사상구 삼덕로 46번길 76-10(삼락동)35.171077128.980754영업051-305-66171991-11-14부산광역시 사상구청2024-03-18
5고동바위경로당경로당부산 사상구 백양대로 907번다길 6(모라동)35.188207128.990293영업051-324-59331998-11-10부산광역시 사상구청2024-03-18
6삼정그린코아아파트경로당경로당부산 사상구 백양대로 934번길 20(모라동,삼정그린코아아파트)35.188897128.992914영업051-314-62591993-11-27부산광역시 사상구청2024-03-18
7동원타운경로당경로당부산 사상구 백양대로 887-31(모라동,모라동원타운)35.185556128.989239영업051-312-60581990-06-18부산광역시 사상구청2024-03-18
8무학아파트경로당경로당부산 사상구 백양대로 846(모라동,무학아파트)35.181937128.988723영업051-325-62491991-06-24부산광역시 사상구청2024-03-18
9모라벽산경로당경로당부산 사상구 백양대로 934번길 84(모라동,모라벽산아파트)35.191682128.994101영업051-987-03592001-01-01부산광역시 사상구청2024-03-18
시설명시설유형소재지도로명주소위도경도영업상태명전화번호건립일자관리기관명데이터기준일자
125무학다솜경로당경로당부산 사상구 대동로 64번길 22(엄궁동,무학다솜타운)35.135677128.976521영업051-311-13332006-08-11부산광역시 사상구청2024-03-18
126엄궁본동경로당경로당부산 사상구 엄궁북로 4번가길 27(엄궁동)35.127494128.970739영업051-315-11331989-05-20부산광역시 사상구청2024-03-18
127삼성타워경로당경로당부산 사상구 대동로 64번길 40(엄궁동,삼성타워아파트)35.134901128.977696영업051-328-14861994-07-21부산광역시 사상구청2024-03-18
128신흥동백경로당경로당부산 사상구 엄궁로 172(엄궁동,신흥동백아파트)35.129508128.975832영업051-326-00171999-03-27부산광역시 사상구청2024-03-18
129엄궁쌍용스윗닷홈경로당경로당부산 사상구 엄궁로 100(엄궁동,엄궁동쌍용스윗닷홈)35.125031128.976602영업051-961-94092007-06-05부산광역시 사상구청2024-03-18
130엄궁아파트경로당경로당부산 사상구 엄궁로 202(엄궁동,엄궁아파트)35.130566128.974221영업051-311-50231989-05-20부산광역시 사상구청2024-03-18
131지불경로당경로당부산 사상구 대동로 27-5(엄궁동)35.133654128.9736영업051-326-92641995-09-30부산광역시 사상구청2024-03-18
132코오롱경로당경로당부산 사상구 엄궁로 142(엄궁동,코오롱아파트)35.126072128.978293영업051-311-93921999-09-19부산광역시 사상구청2024-03-18
133엄궁1차한신경로당경로당부산 사상구 낙동대로 712-17(엄궁동, 엄궁한신1차아파트)35.125026128.968187영업051-322-17601999-08-18부산광역시 사상구청2024-03-18
134엄궁2차한신경로당경로당부산 사상구 엄궁로 40(엄궁동, 엄궁2차한신아파트)35.124522128.96919영업051-324-38882000-04-15부산광역시 사상구청2024-03-18