Overview

Dataset statistics

Number of variables10
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory88.6 B

Variable types

Text2
Categorical7
Numeric1

Dataset

Description2020년도에 추가설치된 계룡시 관내 공공와이파이 시설 현황에 대한 데이터로 설치장소, 설치일시, 설치유형에 관한 정보를 공공데이터로 제공합니다.
Author충청남도 계룡시
URLhttps://www.data.go.kr/data/15093849/fileData.do

Alerts

서비스유형 has constant value ""Constant
AP 종류 is highly overall correlated with 옥내/수량High correlation
계 is highly overall correlated with 옥내/수량High correlation
옥외/모델명 is highly overall correlated with 개통일 and 1 other fieldsHigh correlation
옥외/수량 is highly overall correlated with 옥내/수량High correlation
회선/수량 is highly overall correlated with 옥외/모델명High correlation
옥내/수량 is highly overall correlated with AP 종류 and 2 other fieldsHigh correlation
개통일 is highly overall correlated with 옥외/모델명High correlation
AP 종류 is highly imbalanced (82.1%)Imbalance
옥외/수량 is highly imbalanced (82.1%)Imbalance
장소명 has unique valuesUnique
관리 Naming has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:52:28.074667
Analysis finished2023-12-12 23:52:28.801724
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

장소명
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-13T08:52:28.922535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length9.4594595
Min length6

Characters and Unicode

Total characters350
Distinct characters90
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

Unique37 ?
Unique (%)100.0%

Sample

1st row계룡대림 e-편한세상아파트 경로당
2nd row계룡더샾(아) 경로당
3rd row신성2차미소지움아파트경로당
4th row우림루미아트(아)경로당
5th row경남아파트 경로당
ValueCountFrequency (%)
경로당 18
30.5%
계룡대림 1
 
1.7%
동아아파트 1
 
1.7%
성원아파트경로당 1
 
1.7%
광석1리경로당 1
 
1.7%
광석2리 1
 
1.7%
농소1리 1
 
1.7%
도곡1리 1
 
1.7%
도곡2리 1
 
1.7%
유동1리 1
 
1.7%
Other values (32) 32
54.2%
2023-12-13T08:52:29.220447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 31
 
8.9%
당 30
 
8.6%
로 30
 
8.6%
22
 
6.3%
리 18
 
5.1%
아 14
 
4.0%
1 10
 
2.9%
트 10
 
2.9%
2 9
 
2.6%
사 9
 
2.6%
Other values (80) 167
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 288
82.3%
Space Separator 22
 
6.3%
Decimal Number 22
 
6.3%
Dash Punctuation 4
 
1.1%
Open Punctuation 4
 
1.1%
Close Punctuation 4
 
1.1%
Other Punctuation 3
 
0.9%
Uppercase Letter 2
 
0.6%
Lowercase Letter 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 31
 
10.8%
당 30
 
10.4%
로 30
 
10.4%
리 18
 
6.2%
아 14
 
4.9%
트 10
 
3.5%
사 9
 
3.1%
파 9
 
3.1%
계 7
 
2.4%
엄 5
 
1.7%
Other values (67) 125
43.4%
Decimal Number
ValueCountFrequency (%)
1 10
45.5%
2 9
40.9%
3 2
 
9.1%
4 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 288
82.3%
Common 59
 
16.9%
Latin 3
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 31
 
10.8%
당 30
 
10.4%
로 30
 
10.4%
리 18
 
6.2%
아 14
 
4.9%
트 10
 
3.5%
사 9
 
3.1%
파 9
 
3.1%
계 7
 
2.4%
엄 5
 
1.7%
Other values (67) 125
43.4%
Common
ValueCountFrequency (%)
22
37.3%
1 10
16.9%
2 9
15.3%
- 4
 
6.8%
( 4
 
6.8%
) 4
 
6.8%
, 2
 
3.4%
3 2
 
3.4%
4 1
 
1.7%
. 1
 
1.7%
Latin
ValueCountFrequency (%)
e 1
33.3%
A 1
33.3%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 288
82.3%
ASCII 62
 
17.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 31
 
10.8%
당 30
 
10.4%
로 30
 
10.4%
리 18
 
6.2%
아 14
 
4.9%
트 10
 
3.5%
사 9
 
3.1%
파 9
 
3.1%
계 7
 
2.4%
엄 5
 
1.7%
Other values (67) 125
43.4%
ASCII
ValueCountFrequency (%)
22
35.5%
1 10
16.1%
2 9
14.5%
- 4
 
6.5%
( 4
 
6.5%
) 4
 
6.5%
, 2
 
3.2%
3 2
 
3.2%
e 1
 
1.6%
A 1
 
1.6%
Other values (3) 3
 
4.8%

서비스유형
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
1Gbps
37 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1Gbps
2nd row1Gbps
3rd row1Gbps
4th row1Gbps
5th row1Gbps

Common Values

ValueCountFrequency (%)
1Gbps 37
100.0%

Length

2023-12-13T08:52:29.334602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:52:29.412628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1gbps 37
100.0%

개통일
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)51.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20200590
Minimum20200527
Maximum20200617
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T08:52:29.496674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200527
5-th percentile20200527
Q120200602
median20200603
Q320200610
95-th percentile20200615
Maximum20200617
Range90
Interquartile range (IQR)8

Descriptive statistics

Standard deviation33.277047
Coefficient of variation (CV)1.6473305 × 10-6
Kurtosis-0.0044759716
Mean20200590
Median Absolute Deviation (MAD)6
Skewness-1.3732327
Sum7.4742182 × 108
Variance1107.3619
MonotonicityIncreasing
2023-12-13T08:52:29.597074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
20200603 8
21.6%
20200602 5
13.5%
20200527 4
10.8%
20200529 3
 
8.1%
20200610 3
 
8.1%
20200611 1
 
2.7%
20200617 1
 
2.7%
20200616 1
 
2.7%
20200615 1
 
2.7%
20200614 1
 
2.7%
Other values (9) 9
24.3%
ValueCountFrequency (%)
20200527 4
10.8%
20200528 1
 
2.7%
20200529 3
 
8.1%
20200602 5
13.5%
20200603 8
21.6%
20200604 1
 
2.7%
20200605 1
 
2.7%
20200606 1
 
2.7%
20200607 1
 
2.7%
20200608 1
 
2.7%
ValueCountFrequency (%)
20200617 1
 
2.7%
20200616 1
 
2.7%
20200615 1
 
2.7%
20200614 1
 
2.7%
20200613 1
 
2.7%
20200612 1
 
2.7%
20200611 1
 
2.7%
20200610 3
8.1%
20200609 1
 
2.7%
20200608 1
 
2.7%

회선/수량
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size428.0 B
1
22 
2
13 
8
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)5.4%

Sample

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

Common Values

ValueCountFrequency (%)
1 22
59.5%
2 13
35.1%
8 1
 
2.7%
4 1
 
2.7%

Length

2023-12-13T08:52:29.698139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:52:29.807586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 22
59.5%
2 13
35.1%
8 1
 
2.7%
4 1
 
2.7%

AP 종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
옥내
36 
옥외
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
옥내 36
97.3%
옥외 1
 
2.7%

Length

2023-12-13T08:52:29.909210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:52:29.991488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
옥내 36
97.3%
옥외 1
 
2.7%

옥내/수량
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size428.0 B
1
27 
2
7 
3
 
2
0
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.7%

Sample

1st row2
2nd row2
3rd row2
4th row3
5th row1

Common Values

ValueCountFrequency (%)
1 27
73.0%
2 7
 
18.9%
3 2
 
5.4%
0 1
 
2.7%

Length

2023-12-13T08:52:30.091223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:52:30.174602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 27
73.0%
2 7
 
18.9%
3 2
 
5.4%
0 1
 
2.7%

옥외/수량
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
0
36 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 36
97.3%
2 1
 
2.7%

Length

2023-12-13T08:52:30.285967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:52:30.369660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 36
97.3%
2 1
 
2.7%

계
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
1
27 
2
8 
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row3
5th row1

Common Values

ValueCountFrequency (%)
1 27
73.0%
2 8
 
21.6%
3 2
 
5.4%

Length

2023-12-13T08:52:30.451759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:52:30.536293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 27
73.0%
2 8
 
21.6%
3 2
 
5.4%

옥외/모델명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
WIFI-AP-IGDW2
22 
R710
15 

Length

Max length13
Median length13
Mean length9.3513514
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWIFI-AP-IGDW2
2nd rowWIFI-AP-IGDW2
3rd rowWIFI-AP-IGDW2
4th rowWIFI-AP-IGDW2
5th rowWIFI-AP-IGDW2

Common Values

ValueCountFrequency (%)
WIFI-AP-IGDW2 22
59.5%
R710 15
40.5%

Length

2023-12-13T08:52:30.630383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:52:30.760514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
wifi-ap-igdw2 22
59.5%
r710 15
40.5%

관리 Naming
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-13T08:52:30.947817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length28
Mean length25.432432
Min length19

Characters and Unicode

Total characters941
Distinct characters114
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st row과공W_계룡대림 e-편한세상아파트 경로당_N0260004_옥내2
2nd row과공W_계룡더샾(아) 경로당_N0260005_옥내2
3rd row과공W_신성2차미소지움아파트경로당_N0260010_옥내2
4th row과공W_우림루미아트(아)경로당_N0260016_옥내2
5th row과공W_경남아파트 경로당_N0260045_옥내2
ValueCountFrequency (%)
계룡시 15
 
13.4%
충청남도 15
 
13.4%
엄사면 8
 
7.1%
두마면 5
 
4.5%
금암동 3
 
2.7%
과공w_계룡대림 1
 
0.9%
버들골길 1
 
0.9%
과공w_동아아파트 1
 
0.9%
143 1
 
0.9%
입암길 1
 
0.9%
Other values (61) 61
54.5%
2023-12-13T08:52:31.295000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
 
9.5%
0 67
 
7.1%
_ 66
 
7.0%
2 55
 
5.8%
6 28
 
3.0%
1 27
 
2.9%
옥 24
 
2.6%
공 24
 
2.6%
내 22
 
2.3%
과 22
 
2.3%
Other values (104) 517
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 492
52.3%
Decimal Number 224
23.8%
Space Separator 89
 
9.5%
Connector Punctuation 66
 
7.0%
Uppercase Letter 46
 
4.9%
Dash Punctuation 9
 
1.0%
Close Punctuation 6
 
0.6%
Open Punctuation 6
 
0.6%
Other Punctuation 2
 
0.2%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
옥 24
 
4.9%
공 24
 
4.9%
내 22
 
4.5%
과 22
 
4.5%
계 20
 
4.1%
로 20
 
4.1%
룡 18
 
3.7%
경 18
 
3.7%
당 17
 
3.5%
청 16
 
3.3%
Other values (81) 291
59.1%
Decimal Number
ValueCountFrequency (%)
0 67
29.9%
2 55
24.6%
6 28
12.5%
1 27
12.1%
4 16
 
7.1%
5 13
 
5.8%
8 7
 
3.1%
3 6
 
2.7%
7 3
 
1.3%
9 2
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
W 22
47.8%
N 20
43.5%
R 2
 
4.3%
A 1
 
2.2%
B 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
89
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 492
52.3%
Common 402
42.7%
Latin 47
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
옥 24
 
4.9%
공 24
 
4.9%
내 22
 
4.5%
과 22
 
4.5%
계 20
 
4.1%
로 20
 
4.1%
룡 18
 
3.7%
경 18
 
3.7%
당 17
 
3.5%
청 16
 
3.3%
Other values (81) 291
59.1%
Common
ValueCountFrequency (%)
89
22.1%
0 67
16.7%
_ 66
16.4%
2 55
13.7%
6 28
 
7.0%
1 27
 
6.7%
4 16
 
4.0%
5 13
 
3.2%
- 9
 
2.2%
8 7
 
1.7%
Other values (7) 25
 
6.2%
Latin
ValueCountFrequency (%)
W 22
46.8%
N 20
42.6%
R 2
 
4.3%
e 1
 
2.1%
A 1
 
2.1%
B 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 492
52.3%
ASCII 449
47.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89
19.8%
0 67
14.9%
_ 66
14.7%
2 55
12.2%
6 28
 
6.2%
1 27
 
6.0%
W 22
 
4.9%
N 20
 
4.5%
4 16
 
3.6%
5 13
 
2.9%
Other values (13) 46
10.2%
Hangul
ValueCountFrequency (%)
옥 24
 
4.9%
공 24
 
4.9%
내 22
 
4.5%
과 22
 
4.5%
계 20
 
4.1%
로 20
 
4.1%
룡 18
 
3.7%
경 18
 
3.7%
당 17
 
3.5%
청 16
 
3.3%
Other values (81) 291
59.1%

Interactions

2023-12-13T08:52:28.514332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:52:31.408169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
장소명개통일회선/수량AP 종류옥내/수량옥외/수량계옥외/모델명관리 Naming
장소명1.0001.0001.0001.0001.0001.0001.0001.0001.000
개통일1.0001.0000.3290.0000.0000.0000.0610.3211.000
회선/수량1.0000.3291.0000.0000.1460.0000.2331.0001.000
AP 종류1.0000.0000.0001.0001.0000.6660.1340.0001.000
옥내/수량1.0000.0000.1461.0001.0001.0001.0000.6221.000
옥외/수량1.0000.0000.0000.6661.0001.0000.1340.0001.000
계1.0000.0610.2330.1341.0000.1341.0000.2831.000
옥외/모델명1.0000.3211.0000.0000.6220.0000.2831.0001.000
관리 Naming1.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-13T08:52:31.528132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
AP 종류계옥외/모델명옥외/수량회선/수량옥내/수량
AP 종류1.0000.2150.0000.4630.0000.971
계0.2151.0000.4500.2150.2130.985
옥외/모델명0.0000.4501.0000.0000.9710.417
옥외/수량0.4630.2150.0001.0000.0000.971
회선/수량0.0000.2130.9710.0001.0000.030
옥내/수량0.9710.9850.4170.9710.0301.000
2023-12-13T08:52:31.625064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개통일회선/수량AP 종류옥내/수량옥외/수량계옥외/모델명
개통일1.0000.3680.0000.2650.0000.2690.567
회선/수량0.3681.0000.0000.0300.0000.2130.971
AP 종류0.0000.0001.0000.9710.4630.2150.000
옥내/수량0.2650.0300.9711.0000.9710.9850.417
옥외/수량0.0000.0000.4630.9711.0000.2150.000
계0.2690.2130.2150.9850.2151.0000.450
옥외/모델명0.5670.9710.0000.4170.0000.4501.000

Missing values

2023-12-13T08:52:28.619265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:52:28.754126image/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

장소명서비스유형개통일회선/수량AP 종류옥내/수량옥외/수량계옥외/모델명관리 Naming
0계룡대림 e-편한세상아파트 경로당1Gbps202005271옥내202WIFI-AP-IGDW2과공W_계룡대림 e-편한세상아파트 경로당_N0260004_옥내2
1계룡더샾(아) 경로당1Gbps202005271옥내202WIFI-AP-IGDW2과공W_계룡더샾(아) 경로당_N0260005_옥내2
2신성2차미소지움아파트경로당1Gbps202005271옥내202WIFI-AP-IGDW2과공W_신성2차미소지움아파트경로당_N0260010_옥내2
3우림루미아트(아)경로당1Gbps202005271옥내303WIFI-AP-IGDW2과공W_우림루미아트(아)경로당_N0260016_옥내2
4경남아파트 경로당1Gbps202005281옥내101WIFI-AP-IGDW2과공W_경남아파트 경로당_N0260045_옥내2
5엄사1.4리 경로당1Gbps202005291옥내101WIFI-AP-IGDW2과공W_엄사1.4리 경로당_N0260011_옥내2
6금암2통 경로당1Gbps202005291옥내101WIFI-AP-IGDW2과공W_금암2통 경로당_N0260048_옥내2
7신성1차미소지움(아)경로당1Gbps202005291옥내202WIFI-AP-IGDW2과공W_신성1차미소지움(아)경로당_N0260057_옥내2
8계룡시청(브리핑실)1Gbps202006021옥내101WIFI-AP-IGDW2과공W_계룡시청(브리핑실)_N0260046_옥내1
9농소2리경로당1Gbps202006021옥내101WIFI-AP-IGDW2과공W_농소2리경로당_N0260049_옥내2
장소명서비스유형개통일회선/수량AP 종류옥내/수량옥외/수량계옥외/모델명관리 Naming
27동아아파트 경로당1Gbps202006101옥내101WIFI-AP-IGDW2과공W_동아아파트 경로당_N0260051_옥내2
28두산,신성아파트 경로당1Gbps202006101옥내101WIFI-AP-IGDW2과공W_두산,신성아파트 경로당_N0260052_옥내2
29금암1통경로당1Gbps202006102옥내101R710충청남도 계룡시 금암동 금암로 182 (금암동)
30대한노인회계룡시지회1Gbps202006114옥내101R710충청남도 계룡시 금암동 16-1(증축동)
31두계1,3리경로당1Gbps202006122옥내101R710충청남도 계룡시 두마면 팥거리1길 9
32두계2리 경로당1Gbps202006132옥내101R710충청남도 계룡시 두마면 팥거리로 114
33사계고택-옥외형1Gbps202006142옥내101R710충청남도 계룡시 두마면 두계 두계리 122-4
34유동2리 경로당1Gbps202006152옥내101R710충청남도 계룡시 엄사면 소라실안길 57-4
35향한1리 경로당1Gbps202006162옥내101R710충청남도 계룡시 엄사면 양정향한길 218-2
36향한2리경로당1Gbps202006172옥내101R710충청남도 계룡시 엄사면 광석향한길 220