Overview

Dataset statistics

Number of variables8
Number of observations39
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory70.4 B

Variable types

Text3
Numeric3
DateTime1
Categorical1

Dataset

Description부산광역시 연제구 관내 공공기관 현황 (연제구 행정복지센터, 부산지방경찰청, 부산소방본부, 부산지방고용노동청, 연제경찰서, 동래세무서 등 관내 공공공기관 현황)
URLhttps://www.data.go.kr/data/15025212/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
구군명 has constant value ""Constant
위도 is highly overall correlated with 우편번호High correlation
경도 is highly overall correlated with 우편번호High correlation
우편번호 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
행정공공기관명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:06:40.167417
Analysis finished2023-12-12 18:06:41.948414
Duration1.78 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정공공기관명
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-13T03:06:42.137460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length16
Mean length11.051282
Min length5

Characters and Unicode

Total characters431
Distinct characters92
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

Unique39 ?
Unique (%)100.0%

Sample

1st row거제1동 행정복지센터
2nd row거제2동 행정복지센터
3rd row거제3동 행정복지센터
4th row거제4동 행정복지센터
5th row연산1동 행정복지센터
ValueCountFrequency (%)
행정복지센터 12
 
17.4%
부산 5
 
7.2%
부산광역시 3
 
4.3%
경남지원 1
 
1.4%
국립농산물품질관리원 1
 
1.4%
부산고용노동청 1
 
1.4%
푸른도시가꾸기사업소 1
 
1.4%
부산광역시청 1
 
1.4%
부산광역시의회 1
 
1.4%
부산지방우정청 1
 
1.4%
Other values (42) 42
60.9%
2023-12-13T03:06:42.657730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 36
 
8.4%
30
 
7.0%
부 27
 
6.3%
지 21
 
4.9%
연 16
 
3.7%
동 16
 
3.7%
정 14
 
3.2%
센 14
 
3.2%
터 14
 
3.2%
행 12
 
2.8%
Other values (82) 231
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 381
88.4%
Space Separator 30
 
7.0%
Decimal Number 15
 
3.5%
Other Punctuation 5
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 36
 
9.4%
부 27
 
7.1%
지 21
 
5.5%
연 16
 
4.2%
동 16
 
4.2%
정 14
 
3.7%
센 14
 
3.7%
터 14
 
3.7%
행 12
 
3.1%
복 12
 
3.1%
Other values (72) 199
52.2%
Decimal Number
ValueCountFrequency (%)
1 4
26.7%
2 2
13.3%
9 2
13.3%
4 2
13.3%
3 2
13.3%
5 1
 
6.7%
8 1
 
6.7%
6 1
 
6.7%
Space Separator
ValueCountFrequency (%)
30
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 381
88.4%
Common 50
 
11.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 36
 
9.4%
부 27
 
7.1%
지 21
 
5.5%
연 16
 
4.2%
동 16
 
4.2%
정 14
 
3.7%
센 14
 
3.7%
터 14
 
3.7%
행 12
 
3.1%
복 12
 
3.1%
Other values (72) 199
52.2%
Common
ValueCountFrequency (%)
30
60.0%
, 5
 
10.0%
1 4
 
8.0%
2 2
 
4.0%
9 2
 
4.0%
4 2
 
4.0%
3 2
 
4.0%
5 1
 
2.0%
8 1
 
2.0%
6 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 381
88.4%
ASCII 50
 
11.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 36
 
9.4%
부 27
 
7.1%
지 21
 
5.5%
연 16
 
4.2%
동 16
 
4.2%
정 14
 
3.7%
센 14
 
3.7%
터 14
 
3.7%
행 12
 
3.1%
복 12
 
3.1%
Other values (72) 199
52.2%
ASCII
ValueCountFrequency (%)
30
60.0%
, 5
 
10.0%
1 4
 
8.0%
2 2
 
4.0%
9 2
 
4.0%
4 2
 
4.0%
3 2
 
4.0%
5 1
 
2.0%
8 1
 
2.0%
6 1
 
2.0%

도로명주소
Text

Distinct34
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-13T03:06:42.996625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length30
Mean length19.538462
Min length15

Characters and Unicode

Total characters762
Distinct characters61
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)79.5%

Sample

1st row부산광역시 연제구 법원북로 88
2nd row부산광역시 연제구 아시아드대로22번길 19
3rd row부산광역시 연제구 거제대로 180
4th row부산광역시 연제구 화지로52번길 33
5th row부산광역시 연제구 연동로8번길 66
ValueCountFrequency (%)
부산광역시 39
24.7%
연제구 39
24.7%
중앙대로 6
 
3.8%
33 4
 
2.5%
연제로 4
 
2.5%
1000 4
 
2.5%
216 3
 
1.9%
법원북로 3
 
1.9%
고분로 3
 
1.9%
거제대로 3
 
1.9%
Other values (44) 50
31.6%
2023-12-13T03:06:43.499443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
122
16.0%
제 49
 
6.4%
연 45
 
5.9%
부 42
 
5.5%
산 42
 
5.5%
시 40
 
5.2%
구 39
 
5.1%
로 39
 
5.1%
역 39
 
5.1%
광 39
 
5.1%
Other values (51) 266
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 508
66.7%
Decimal Number 126
 
16.5%
Space Separator 122
 
16.0%
Open Punctuation 3
 
0.4%
Close Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 49
9.6%
연 45
 
8.9%
부 42
 
8.3%
산 42
 
8.3%
시 40
 
7.9%
구 39
 
7.7%
로 39
 
7.7%
역 39
 
7.7%
광 39
 
7.7%
대 13
 
2.6%
Other values (39) 121
23.8%
Decimal Number
ValueCountFrequency (%)
2 30
23.8%
1 26
20.6%
0 16
12.7%
3 14
11.1%
6 11
 
8.7%
8 9
 
7.1%
9 9
 
7.1%
5 7
 
5.6%
4 4
 
3.2%
Space Separator
ValueCountFrequency (%)
122
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 508
66.7%
Common 254
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 49
9.6%
연 45
 
8.9%
부 42
 
8.3%
산 42
 
8.3%
시 40
 
7.9%
구 39
 
7.7%
로 39
 
7.7%
역 39
 
7.7%
광 39
 
7.7%
대 13
 
2.6%
Other values (39) 121
23.8%
Common
ValueCountFrequency (%)
122
48.0%
2 30
 
11.8%
1 26
 
10.2%
0 16
 
6.3%
3 14
 
5.5%
6 11
 
4.3%
8 9
 
3.5%
9 9
 
3.5%
5 7
 
2.8%
4 4
 
1.6%
Other values (2) 6
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 508
66.7%
ASCII 254
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122
48.0%
2 30
 
11.8%
1 26
 
10.2%
0 16
 
6.3%
3 14
 
5.5%
6 11
 
4.3%
8 9
 
3.5%
9 9
 
3.5%
5 7
 
2.8%
4 4
 
1.6%
Other values (2) 6
 
2.4%
Hangul
ValueCountFrequency (%)
제 49
9.6%
연 45
 
8.9%
부 42
 
8.3%
산 42
 
8.3%
시 40
 
7.9%
구 39
 
7.7%
로 39
 
7.7%
역 39
 
7.7%
광 39
 
7.7%
대 13
 
2.6%
Other values (39) 121
23.8%

전화번호
Text

Distinct38
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-13T03:06:43.786716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.205128
Min length3

Characters and Unicode

Total characters437
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

Unique37 ?
Unique (%)94.9%

Sample

1st row051-665-5711
2nd row051-665-5731
3rd row051-665-5751
4th row051-665-5771
5th row051-665-5791
ValueCountFrequency (%)
182 2
 
5.1%
051-559-3003 2
 
5.1%
051-503-7788 1
 
2.6%
051-868-6060 1
 
2.6%
051-500-0888 1
 
2.6%
051-850-3300 1
 
2.6%
051-853-0009 1
 
2.6%
051-756-2831 1
 
2.6%
051-120 1
 
2.6%
051-550-8000 1
 
2.6%
Other values (27) 27
69.2%
2023-12-13T03:06:44.280323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 90
20.6%
5 80
18.3%
- 70
16.0%
1 68
15.6%
6 40
9.2%
7 24
 
5.5%
8 22
 
5.0%
3 17
 
3.9%
2 10
 
2.3%
9 10
 
2.3%
Other values (2) 6
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 364
83.3%
Dash Punctuation 70
 
16.0%
Space Separator 3
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 90
24.7%
5 80
22.0%
1 68
18.7%
6 40
11.0%
7 24
 
6.6%
8 22
 
6.0%
3 17
 
4.7%
2 10
 
2.7%
9 10
 
2.7%
4 3
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 437
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 90
20.6%
5 80
18.3%
- 70
16.0%
1 68
15.6%
6 40
9.2%
7 24
 
5.5%
8 22
 
5.0%
3 17
 
3.9%
2 10
 
2.3%
9 10
 
2.3%
Other values (2) 6
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 437
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 90
20.6%
5 80
18.3%
- 70
16.0%
1 68
15.6%
6 40
9.2%
7 24
 
5.5%
8 22
 
5.0%
3 17
 
3.9%
2 10
 
2.3%
9 10
 
2.3%
Other values (2) 6
 
1.4%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.184278
Minimum35.173348
Maximum35.194121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-13T03:06:44.470996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.173348
5-th percentile35.176742
Q135.178589
median35.184281
Q335.187616
95-th percentile35.193905
Maximum35.194121
Range0.02077207
Interquartile range (IQR)0.00902675

Descriptive statistics

Standard deviation0.0058496749
Coefficient of variation (CV)0.00016625821
Kurtosis-1.045515
Mean35.184278
Median Absolute Deviation (MAD)0.00517612
Skewness0.13356311
Sum1372.1868
Variance3.4218696 × 10-5
MonotonicityNot monotonic
2023-12-13T03:06:44.654478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
35.17785982 4
 
10.3%
35.18343838 2
 
5.1%
35.19412054 2
 
5.1%
35.1918765 1
 
2.6%
35.18741703 1
 
2.6%
35.17807302 1
 
2.6%
35.18517264 1
 
2.6%
35.17992893 1
 
2.6%
35.19120606 1
 
2.6%
35.1907988 1
 
2.6%
Other values (24) 24
61.5%
ValueCountFrequency (%)
35.17334847 1
 
2.6%
35.17620985 1
 
2.6%
35.17680067 1
 
2.6%
35.17741821 1
 
2.6%
35.17762082 1
 
2.6%
35.17785982 4
10.3%
35.17807302 1
 
2.6%
35.17910501 1
 
2.6%
35.17985362 1
 
2.6%
35.17992893 1
 
2.6%
ValueCountFrequency (%)
35.19412054 2
5.1%
35.193881 1
2.6%
35.19342035 1
2.6%
35.19253748 1
2.6%
35.1918765 1
2.6%
35.19120606 1
2.6%
35.1907988 1
2.6%
35.18998638 1
2.6%
35.18775953 1
2.6%
35.187472 1
2.6%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.08107
Minimum129.04242
Maximum129.1094
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-13T03:06:44.873183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.04242
5-th percentile129.05941
Q1129.07331
median129.07607
Q3129.09008
95-th percentile129.10585
Maximum129.1094
Range0.0669843
Interquartile range (IQR)0.01676695

Descriptive statistics

Standard deviation0.015462012
Coefficient of variation (CV)0.00011978528
Kurtosis0.048455375
Mean129.08107
Median Absolute Deviation (MAD)0.0054729
Skewness0.17159117
Sum5034.1617
Variance0.00023907381
MonotonicityNot monotonic
2023-12-13T03:06:45.021833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
129.0756461 4
 
10.3%
129.1057479 2
 
5.1%
129.0706009 2
 
5.1%
129.0756334 1
 
2.6%
129.0600491 1
 
2.6%
129.0770102 1
 
2.6%
129.1053542 1
 
2.6%
129.0750915 1
 
2.6%
129.0719571 1
 
2.6%
129.0536806 1
 
2.6%
Other values (24) 24
61.5%
ValueCountFrequency (%)
129.04242 1
2.6%
129.0536806 1
2.6%
129.0600491 1
2.6%
129.0652645 1
2.6%
129.0702868 1
2.6%
129.0706009 2
5.1%
129.0711963 1
2.6%
129.0719571 1
2.6%
129.0732703 1
2.6%
129.073353 1
2.6%
ValueCountFrequency (%)
129.1094043 1
2.6%
129.1059322 1
2.6%
129.1058448 1
2.6%
129.1057479 2
5.1%
129.1053542 1
2.6%
129.1045129 1
2.6%
129.1009998 1
2.6%
129.094227 1
2.6%
129.0904206 1
2.6%
129.0897366 1
2.6%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)61.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47559.051
Minimum47500
Maximum47614
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-13T03:06:45.177248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47500
5-th percentile47502
Q147535
median47552
Q347594
95-th percentile47606
Maximum47614
Range114
Interquartile range (IQR)59

Descriptive statistics

Standard deviation36.359281
Coefficient of variation (CV)0.00076450812
Kurtosis-1.3303285
Mean47559.051
Median Absolute Deviation (MAD)34
Skewness2.8504774 × 10-5
Sum1854803
Variance1321.9973
MonotonicityNot monotonic
2023-12-13T03:06:45.340686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
47606 4
 
10.3%
47605 4
 
10.3%
47586 4
 
10.3%
47537 3
 
7.7%
47545 2
 
5.1%
47510 2
 
5.1%
47502 2
 
5.1%
47558 2
 
5.1%
47500 1
 
2.6%
47527 1
 
2.6%
Other values (14) 14
35.9%
ValueCountFrequency (%)
47500 1
 
2.6%
47502 2
5.1%
47510 2
5.1%
47511 1
 
2.6%
47517 1
 
2.6%
47526 1
 
2.6%
47527 1
 
2.6%
47533 1
 
2.6%
47537 3
7.7%
47539 1
 
2.6%
ValueCountFrequency (%)
47614 1
 
2.6%
47606 4
10.3%
47605 4
10.3%
47599 1
 
2.6%
47589 1
 
2.6%
47586 4
10.3%
47569 1
 
2.6%
47558 2
5.1%
47557 1
 
2.6%
47552 1
 
2.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
Minimum2023-05-18 00:00:00
Maximum2023-05-18 00:00:00
2023-12-13T03:06:45.454889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:06:45.570239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

구군명
Categorical

CONSTANT 

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

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 연제구 39
100.0%

Length

2023-12-13T03:06:45.697933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:06:45.800627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 39
50.0%
연제구 39
50.0%

Interactions

2023-12-13T03:06:41.328535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:06:40.582671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:06:40.950160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:06:41.434266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:06:40.694047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:06:41.077335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:06:41.562877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:06:40.836334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:06:41.206200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:06:45.872348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정공공기관명도로명주소전화번호위도경도우편번호
행정공공기관명1.0001.0001.0001.0001.0001.000
도로명주소1.0001.0000.9750.9841.0001.000
전화번호1.0000.9751.0000.9160.9810.967
위도1.0000.9840.9161.0000.7300.715
경도1.0001.0000.9810.7301.0000.728
우편번호1.0001.0000.9670.7150.7281.000
2023-12-13T03:06:45.979209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도우편번호
위도1.000-0.335-0.864
경도-0.3351.0000.584
우편번호-0.8640.5841.000

Missing values

2023-12-13T03:06:41.723863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:06:41.878773image/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

행정공공기관명도로명주소전화번호위도경도우편번호데이터기준일자구군명
0거제1동 행정복지센터부산광역시 연제구 법원북로 88051-665-571135.191876129.075633475112023-05-18부산광역시 연제구
1거제2동 행정복지센터부산광역시 연제구 아시아드대로22번길 19051-665-573135.18776129.070287475262023-05-18부산광역시 연제구
2거제3동 행정복지센터부산광역시 연제구 거제대로 180051-665-575135.184281129.071196475432023-05-18부산광역시 연제구
3거제4동 행정복지센터부산광역시 연제구 화지로52번길 33051-665-577135.179854129.065265475332023-05-18부산광역시 연제구
4연산1동 행정복지센터부산광역시 연제구 연동로8번길 66051-665-579135.189986129.090421475522023-05-18부산광역시 연제구
5연산2동 행정복지센터부산광역시 연제구 중앙대로1038번길 39051-665-581135.179973129.079297475992023-05-18부산광역시 연제구
6연산3동 행정복지센터부산광역시 연제구 연수로218번길 4051-665-583135.173348129.094227476142023-05-18부산광역시 연제구
7연산4동 행정복지센터부산광역시 연제구 쌍미천로151번길 42051-665-585135.186286129.084925475502023-05-18부산광역시 연제구
8연산5동 행정복지센터부산광역시 연제구 거제천로124번길 15051-665-587135.184481129.076074475392023-05-18부산광역시 연제구
9연산6동 행정복지센터부산광역시 연제구 쌍미천로52번길 2051-665-589135.177418129.089737475892023-05-18부산광역시 연제구
행정공공기관명도로명주소전화번호위도경도우편번호데이터기준일자구군명
29부산 연제우체국부산광역시 연제구 법원북로 33051-500-088835.194121129.070601475022023-05-18부산광역시 연제구
30국가기록원역사기록관부산광역시 연제구 경기장로 28051-550-800035.190799129.053681475002023-05-18부산광역시 연제구
31부산지방법원, 부산고등법원부산광역시 연제구 법원로 31051-590-111435.192537129.07327475102023-05-18부산광역시 연제구
32부산광역시 선거관리위원회부산광역시 연제구 연제로 28051-851-779135.177621129.07718476052023-05-18부산광역시 연제구
33국민연금공단 부산지사부산광역시 연제구 중앙대로 1000135535.17786129.075646476062023-05-18부산광역시 연제구
34부산광역시 연제구청, 연제구보건소, 연제구의회부산광역시 연제구 연제로 2051-665-400035.17621129.079741476052023-05-18부산광역시 연제구
35부산광역시 교통정보서비스센터부산광역시 연제구 고분로221051-600-020035.184916129.105845475582023-05-18부산광역시 연제구
36부산지방식품의약품안전청부산광역시 연제구 거제대로 222(나라키움 부산통합청사)051-602-610035.193881129.074202475372023-05-18부산광역시 연제구
37국립농산물품질관리원 경남지원 부산사무소부산광역시 연제구 거제대로 222 (나라키움 부산통합청사)051-868-606035.187472129.04242475372023-05-18부산광역시 연제구
38연산119안전센터부산광역시 연제구 고분로 216051-760-631235.183873129.105932475862023-05-18부산광역시 연제구