Overview

Dataset statistics

Number of variables6
Number of observations320
Missing cells4
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.4 KiB
Average record size in memory49.4 B

Variable types

Text3
Categorical2
Numeric1

Dataset

Description군산시에 소재하는 집단급식소에 대한 현황 및 데이터로 업소명, 소재지(도로명), 소재지(지번) 등의 항목을 제공합니다.
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=3&menuCd=DOM_000000103007001000&pListTypeStr=&pId=3080325

Alerts

업태명 is highly overall correlated with 운영형태High correlation
운영형태 is highly overall correlated with 업태명High correlation
평균급식인원수 has 22 (6.9%) zerosZeros

Reproduction

Analysis started2024-03-14 03:13:52.881848
Analysis finished2024-03-14 03:13:53.572385
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct319
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-03-14T12:13:53.725132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length8.690625
Min length3

Characters and Unicode

Total characters2781
Distinct characters325
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

Unique318 ?
Unique (%)99.4%

Sample

1st row삼성애육원
2nd row사회복지법인일맥원
3rd row구세군군산후생원
4th row한국유리공업(주)
5th row페이퍼코리아(주)
ValueCountFrequency (%)
어린이집 11
 
3.0%
군산공장 4
 
1.1%
주식회사 4
 
1.1%
의료법인 3
 
0.8%
군산 2
 
0.5%
페이퍼코리아(주 2
 
0.5%
사회복지법인 2
 
0.5%
지혜의 1
 
0.3%
군산바다유치원 1
 
0.3%
햇님어린이집 1
 
0.3%
Other values (337) 337
91.6%
2024-03-14T12:13:54.040199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 128
 
4.6%
군 117
 
4.2%
이 100
 
3.6%
학 91
 
3.3%
교 83
 
3.0%
주 80
 
2.9%
어 77
 
2.8%
집 75
 
2.7%
린 72
 
2.6%
원 72
 
2.6%
Other values (315) 1886
67.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2584
92.9%
Close Punctuation 60
 
2.2%
Open Punctuation 60
 
2.2%
Space Separator 48
 
1.7%
Uppercase Letter 17
 
0.6%
Decimal Number 10
 
0.4%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 128
 
5.0%
군 117
 
4.5%
이 100
 
3.9%
학 91
 
3.5%
교 83
 
3.2%
주 80
 
3.1%
어 77
 
3.0%
집 75
 
2.9%
린 72
 
2.8%
원 72
 
2.8%
Other values (296) 1689
65.4%
Uppercase Letter
ValueCountFrequency (%)
C 4
23.5%
S 3
17.6%
G 2
11.8%
I 2
11.8%
O 2
11.8%
D 1
 
5.9%
L 1
 
5.9%
H 1
 
5.9%
R 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 4
40.0%
9 2
20.0%
3 1
 
10.0%
1 1
 
10.0%
0 1
 
10.0%
6 1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2584
92.9%
Common 178
 
6.4%
Latin 19
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 128
 
5.0%
군 117
 
4.5%
이 100
 
3.9%
학 91
 
3.5%
교 83
 
3.2%
주 80
 
3.1%
어 77
 
3.0%
집 75
 
2.9%
린 72
 
2.8%
원 72
 
2.8%
Other values (296) 1689
65.4%
Latin
ValueCountFrequency (%)
C 4
21.1%
S 3
15.8%
e 2
10.5%
G 2
10.5%
I 2
10.5%
O 2
10.5%
D 1
 
5.3%
L 1
 
5.3%
H 1
 
5.3%
R 1
 
5.3%
Common
ValueCountFrequency (%)
) 60
33.7%
( 60
33.7%
48
27.0%
2 4
 
2.2%
9 2
 
1.1%
3 1
 
0.6%
1 1
 
0.6%
0 1
 
0.6%
6 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2584
92.9%
ASCII 197
 
7.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 128
 
5.0%
군 117
 
4.5%
이 100
 
3.9%
학 91
 
3.5%
교 83
 
3.2%
주 80
 
3.1%
어 77
 
3.0%
집 75
 
2.9%
린 72
 
2.8%
원 72
 
2.8%
Other values (296) 1689
65.4%
ASCII
ValueCountFrequency (%)
) 60
30.5%
( 60
30.5%
48
24.4%
2 4
 
2.0%
C 4
 
2.0%
S 3
 
1.5%
e 2
 
1.0%
G 2
 
1.0%
9 2
 
1.0%
I 2
 
1.0%
Other values (9) 10
 
5.1%

소재지(도로명)
Text

Distinct305
Distinct (%)96.2%
Missing3
Missing (%)0.9%
Memory size2.6 KiB
2024-03-14T12:13:54.352182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length45
Mean length27.618297
Min length22

Characters and Unicode

Total characters8755
Distinct characters250
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

Unique299 ?
Unique (%)94.3%

Sample

1st row전북특별자치도 군산시 석치2길 14 (문화동)
2nd row전북특별자치도 군산시 월명로 514 (신흥동)
3rd row전북특별자치도 군산시 외항1길 296 (소룡동)
4th row전북특별자치도 군산시 외항로 1245, 페이퍼코리아 주식회사 (비응도동)
5th row전북특별자치도 군산시 외항로 82 (소룡동)
ValueCountFrequency (%)
군산시 318
 
18.7%
전북특별자치도 317
 
18.7%
소룡동 42
 
2.5%
나운동 31
 
1.8%
오식도동 30
 
1.8%
조촌동 26
 
1.5%
1층 21
 
1.2%
수송동 18
 
1.1%
외항로 16
 
0.9%
문화동 12
 
0.7%
Other values (490) 866
51.0%
2024-03-14T12:13:54.779684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1380
 
15.8%
산 392
 
4.5%
도 360
 
4.1%
군 345
 
3.9%
북 335
 
3.8%
자 333
 
3.8%
시 323
 
3.7%
치 322
 
3.7%
동 321
 
3.7%
전 318
 
3.6%
Other values (240) 4326
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5724
65.4%
Space Separator 1380
 
15.8%
Decimal Number 976
 
11.1%
Open Punctuation 271
 
3.1%
Close Punctuation 271
 
3.1%
Other Punctuation 78
 
0.9%
Dash Punctuation 49
 
0.6%
Uppercase Letter 4
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 392
 
6.8%
도 360
 
6.3%
군 345
 
6.0%
북 335
 
5.9%
자 333
 
5.8%
시 323
 
5.6%
치 322
 
5.6%
동 321
 
5.6%
전 318
 
5.6%
특 317
 
5.5%
Other values (219) 2358
41.2%
Decimal Number
ValueCountFrequency (%)
1 218
22.3%
2 173
17.7%
3 128
13.1%
4 88
9.0%
5 88
9.0%
0 62
 
6.4%
7 58
 
5.9%
8 56
 
5.7%
6 54
 
5.5%
9 51
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
L 1
25.0%
D 1
25.0%
M 1
25.0%
S 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 74
94.9%
. 4
 
5.1%
Space Separator
ValueCountFrequency (%)
1380
100.0%
Open Punctuation
ValueCountFrequency (%)
( 271
100.0%
Close Punctuation
ValueCountFrequency (%)
) 271
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5724
65.4%
Common 3025
34.6%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 392
 
6.8%
도 360
 
6.3%
군 345
 
6.0%
북 335
 
5.9%
자 333
 
5.8%
시 323
 
5.6%
치 322
 
5.6%
동 321
 
5.6%
전 318
 
5.6%
특 317
 
5.5%
Other values (219) 2358
41.2%
Common
ValueCountFrequency (%)
1380
45.6%
( 271
 
9.0%
) 271
 
9.0%
1 218
 
7.2%
2 173
 
5.7%
3 128
 
4.2%
4 88
 
2.9%
5 88
 
2.9%
, 74
 
2.4%
0 62
 
2.0%
Other values (6) 272
 
9.0%
Latin
ValueCountFrequency (%)
e 2
33.3%
L 1
16.7%
D 1
16.7%
M 1
16.7%
S 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5724
65.4%
ASCII 3031
34.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1380
45.5%
( 271
 
8.9%
) 271
 
8.9%
1 218
 
7.2%
2 173
 
5.7%
3 128
 
4.2%
4 88
 
2.9%
5 88
 
2.9%
, 74
 
2.4%
0 62
 
2.0%
Other values (11) 278
 
9.2%
Hangul
ValueCountFrequency (%)
산 392
 
6.8%
도 360
 
6.3%
군 345
 
6.0%
북 335
 
5.9%
자 333
 
5.8%
시 323
 
5.6%
치 322
 
5.6%
동 321
 
5.6%
전 318
 
5.6%
특 317
 
5.5%
Other values (219) 2358
41.2%

소재지(지번)
Text

Distinct308
Distinct (%)96.6%
Missing1
Missing (%)0.3%
Memory size2.6 KiB
2024-03-14T12:13:55.147238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length38
Mean length23.645768
Min length18

Characters and Unicode

Total characters7543
Distinct characters195
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

Unique301 ?
Unique (%)94.4%

Sample

1st row전북특별자치도 군산시 신창동 7
2nd row전북특별자치도 군산시 문화동 824-7
3rd row전북특별자치도 군산시 신흥동 58-10
4th row전북특별자치도 군산시 소룡동 77
5th row전북특별자치도 군산시 비응도동 36-20 페이퍼코리아 주식회사
ValueCountFrequency (%)
군산시 320
22.9%
전북특별자치도 319
22.8%
소룡동 42
 
3.0%
오식도동 32
 
2.3%
나운동 32
 
2.3%
조촌동 26
 
1.9%
수송동 20
 
1.4%
지곡동 13
 
0.9%
문화동 12
 
0.9%
산북동 10
 
0.7%
Other values (429) 571
40.9%
2024-03-14T12:13:55.600374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1394
18.5%
산 363
 
4.8%
도 363
 
4.8%
군 333
 
4.4%
북 332
 
4.4%
시 323
 
4.3%
자 321
 
4.3%
치 321
 
4.3%
전 320
 
4.2%
별 319
 
4.2%
Other values (185) 3154
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4697
62.3%
Space Separator 1394
 
18.5%
Decimal Number 1219
 
16.2%
Dash Punctuation 214
 
2.8%
Uppercase Letter 7
 
0.1%
Close Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 363
 
7.7%
도 363
 
7.7%
군 333
 
7.1%
북 332
 
7.1%
시 323
 
6.9%
자 321
 
6.8%
치 321
 
6.8%
전 320
 
6.8%
별 319
 
6.8%
특 319
 
6.8%
Other values (164) 1383
29.4%
Decimal Number
ValueCountFrequency (%)
1 209
17.1%
3 160
13.1%
5 141
11.6%
8 135
11.1%
2 118
9.7%
4 106
8.7%
6 102
8.4%
7 85
7.0%
9 82
 
6.7%
0 81
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
S 2
28.6%
O 1
14.3%
C 1
14.3%
I 1
14.3%
E 1
14.3%
M 1
14.3%
Space Separator
ValueCountFrequency (%)
1394
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 214
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4697
62.3%
Common 2837
37.6%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 363
 
7.7%
도 363
 
7.7%
군 333
 
7.1%
북 332
 
7.1%
시 323
 
6.9%
자 321
 
6.8%
치 321
 
6.8%
전 320
 
6.8%
별 319
 
6.8%
특 319
 
6.8%
Other values (164) 1383
29.4%
Common
ValueCountFrequency (%)
1394
49.1%
- 214
 
7.5%
1 209
 
7.4%
3 160
 
5.6%
5 141
 
5.0%
8 135
 
4.8%
2 118
 
4.2%
4 106
 
3.7%
6 102
 
3.6%
7 85
 
3.0%
Other values (4) 173
 
6.1%
Latin
ValueCountFrequency (%)
S 2
22.2%
e 2
22.2%
O 1
11.1%
C 1
11.1%
I 1
11.1%
E 1
11.1%
M 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4697
62.3%
ASCII 2846
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1394
49.0%
- 214
 
7.5%
1 209
 
7.3%
3 160
 
5.6%
5 141
 
5.0%
8 135
 
4.7%
2 118
 
4.1%
4 106
 
3.7%
6 102
 
3.6%
7 85
 
3.0%
Other values (11) 182
 
6.4%
Hangul
ValueCountFrequency (%)
산 363
 
7.7%
도 363
 
7.7%
군 333
 
7.1%
북 332
 
7.1%
시 323
 
6.9%
자 321
 
6.8%
치 321
 
6.8%
전 320
 
6.8%
별 319
 
6.8%
특 319
 
6.8%
Other values (164) 1383
29.4%

업태명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
학교
105 
산업체
82 
어린이집
73 
사회복지시설
23 
병원
20 
Other values (4)
17 

Length

Max length8
Median length6
Mean length3.13125
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row사회복지시설
2nd row사회복지시설
3rd row사회복지시설
4th row산업체
5th row산업체

Common Values

ValueCountFrequency (%)
학교 105
32.8%
산업체 82
25.6%
어린이집 73
22.8%
사회복지시설 23
 
7.2%
병원 20
 
6.2%
공공기관 10
 
3.1%
기숙사 3
 
0.9%
기타 집단급식소 3
 
0.9%
수련원 1
 
0.3%

Length

2024-03-14T12:13:55.705425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:13:55.800897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
학교 105
32.5%
산업체 82
25.4%
어린이집 73
22.6%
사회복지시설 23
 
7.1%
병원 20
 
6.2%
공공기관 10
 
3.1%
기숙사 3
 
0.9%
기타 3
 
0.9%
집단급식소 3
 
0.9%
수련원 1
 
0.3%

평균급식인원수
Real number (ℝ)

ZEROS 

Distinct149
Distinct (%)46.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.97813
Minimum0
Maximum1771
Zeros22
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-14T12:13:55.909267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q152
median86
Q3197.25
95-th percentile801.8
Maximum1771
Range1771
Interquartile range (IQR)145.25

Descriptive statistics

Standard deviation267.60083
Coefficient of variation (CV)1.38669
Kurtosis7.1865837
Mean192.97813
Median Absolute Deviation (MAD)44
Skewness2.5713748
Sum61753
Variance71610.203
MonotonicityNot monotonic
2024-03-14T12:13:56.013162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22
 
6.9%
80 9
 
2.8%
52 8
 
2.5%
50 8
 
2.5%
75 8
 
2.5%
100 8
 
2.5%
130 7
 
2.2%
45 6
 
1.9%
90 6
 
1.9%
55 5
 
1.6%
Other values (139) 233
72.8%
ValueCountFrequency (%)
0 22
6.9%
18 1
 
0.3%
27 4
 
1.2%
29 1
 
0.3%
30 1
 
0.3%
31 3
 
0.9%
32 1
 
0.3%
33 2
 
0.6%
34 1
 
0.3%
35 2
 
0.6%
ValueCountFrequency (%)
1771 1
0.3%
1340 1
0.3%
1300 1
0.3%
1181 1
0.3%
1100 1
0.3%
1060 1
0.3%
1020 1
0.3%
1000 2
0.6%
996 1
0.3%
980 1
0.3%

운영형태
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
직영
226 
위탁
87 
<NA>
 
7

Length

Max length4
Median length2
Mean length2.04375
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row직영
2nd row직영
3rd row직영
4th row위탁
5th row위탁

Common Values

ValueCountFrequency (%)
직영 226
70.6%
위탁 87
 
27.2%
<NA> 7
 
2.2%

Length

2024-03-14T12:13:56.124357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:13:56.210655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
직영 226
70.6%
위탁 87
 
27.2%
na 7
 
2.2%

Interactions

2024-03-14T12:13:53.263431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T12:13:56.267681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태명평균급식인원수운영형태
업태명1.0000.4790.841
평균급식인원수0.4791.0000.124
운영형태0.8410.1241.000
2024-03-14T12:13:56.342457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태명운영형태
업태명1.0000.861
운영형태0.8611.000
2024-03-14T12:13:56.409736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평균급식인원수업태명운영형태
평균급식인원수1.0000.1700.122
업태명0.1701.0000.861
운영형태0.1220.8611.000

Missing values

2024-03-14T12:13:53.371718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T12:13:53.453400image/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.
2024-03-14T12:13:53.530565image/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

업소명소재지(도로명)소재지(지번)업태명평균급식인원수운영형태
0삼성애육원<NA>전북특별자치도 군산시 신창동 7사회복지시설79직영
1사회복지법인일맥원전북특별자치도 군산시 석치2길 14 (문화동)전북특별자치도 군산시 문화동 824-7사회복지시설86직영
2구세군군산후생원전북특별자치도 군산시 월명로 514 (신흥동)전북특별자치도 군산시 신흥동 58-10사회복지시설52직영
3한국유리공업(주)전북특별자치도 군산시 외항1길 296 (소룡동)전북특별자치도 군산시 소룡동 77산업체188위탁
4페이퍼코리아(주)전북특별자치도 군산시 외항로 1245, 페이퍼코리아 주식회사 (비응도동)전북특별자치도 군산시 비응도동 36-20 페이퍼코리아 주식회사산업체227위탁
5OCI군산콘서트점전북특별자치도 군산시 외항로 82 (소룡동)전북특별자치도 군산시 소룡동 233산업체177위탁
6씨제이피드앤케어주식회사전북특별자치도 군산시 외항1길 426 (소룡동)전북특별자치도 군산시 소룡동 43산업체61위탁
7대상(주)군산공장전북특별자치도 군산시 외항1길 208 (소룡동)전북특별자치도 군산시 소룡동 228-1산업체153위탁
8군산대학교학생생활관전북특별자치도 군산시 대학로 558 (미룡동)전북특별자치도 군산시 미룡동 산 68기숙사735직영
9군산대학교제1식당전북특별자치도 군산시 대학로 558 (미룡동)전북특별자치도 군산시 미룡동 290-2학교840위탁
업소명소재지(도로명)소재지(지번)업태명평균급식인원수운영형태
310(주)뉴인텍전북특별자치도 군산시 임피면 항쟁로 43-10, 2동 1층전북특별자치도 군산시 임피면 축산리 631산업체48위탁
311대야노인복지관전북특별자치도 군산시 대야면 우덕2길 7, 1동 1층전북특별자치도 군산시 대야면 지경리 731-21사회복지시설150직영
312전주지방검찰청 군산지청전북특별자치도 군산시 법원로 70, 전주지방검찰청군산지청 (조촌동)전북특별자치도 군산시 조촌동 880 전주지방검찰청군산지청공공기관0<NA>
313현대중공업군산비응관전북특별자치도 군산시 서해로 625, 현대중공업군산조선소 (비응도동)전북특별자치도 군산시 비응도동 13 현대중공업군산조선소산업체180위탁
314군산영광중학교전북특별자치도 군산시 구영신창길 60-6 (금동)전북특별자치도 군산시 금동 26-83학교500직영
315에이치디현대중공업(주) 군산기숙사전북특별자치도 군산시 자유로 238, 1층 (소룡동)전북특별자치도 군산시 소룡동 1588-8산업체27<NA>
316은혜요양원 구내식당전북특별자치도 군산시 조촌2길 14, 2층 (조촌동)전북특별자치도 군산시 조촌동 890-5사회복지시설47<NA>
317센트럴파크어린이집전북특별자치도 군산시 번영로 190, 1층 (조촌동, 센트럴파크 아파트)전북특별자치도 군산시 조촌동 769-4 관리동어린이집0<NA>
318온누리재활재가 노인복지센터전북특별자치도 군산시 수송로 10, 1층 (나운동)전북특별자치도 군산시 나운동 830-8사회복지시설75<NA>
319군산베스트한방병원전북특별자치도 군산시 공단대로 417, 5층 (나운동)전북특별자치도 군산시 나운동 844-5병원38<NA>