Overview

Dataset statistics

Number of variables7
Number of observations260
Missing cells0
Missing cells (%)0.0%
Duplicate rows2
Duplicate rows (%)0.8%
Total size in memory14.9 KiB
Average record size in memory58.5 B

Variable types

Text3
Categorical2
Numeric2

Dataset

Description한국산업안전보건공단에서 제공 중인 기초안전보건교육 강의실 정보에 대한 내용으로 강의실 이름, 면적, 우편번호, 주소 등에 대한 컬럼을 제공합니다.
URLhttps://www.data.go.kr/data/15066073/fileData.do

Alerts

Dataset has 2 (0.8%) duplicate rowsDuplicates
강의실 면적 is highly imbalanced (53.1%)Imbalance

Reproduction

Analysis started2023-12-12 23:15:49.879161
Analysis finished2023-12-12 23:15:50.784996
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

강의실 이름
Text

Distinct162
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T08:15:50.935193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length8.2846154
Min length3

Characters and Unicode

Total characters2154
Distinct characters218
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)56.5%

Sample

1st row강의실1
2nd row출장교육장_LS전선
3rd row강의실1
4th row강의실
5th row강의실2(제주)
ValueCountFrequency (%)
강의실 32
 
9.1%
강의실1 27
 
7.7%
등록강의실 19
 
5.4%
제1강의실 10
 
2.9%
강의실2 7
 
2.0%
등록교육장 7
 
2.0%
시청각실 6
 
1.7%
방문교육장 5
 
1.4%
교육장 5
 
1.4%
강당 4
 
1.1%
Other values (200) 228
65.1%
2023-12-13T08:15:51.262418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
실 156
 
7.2%
강 141
 
6.5%
의 139
 
6.5%
교 106
 
4.9%
92
 
4.3%
등 75
 
3.5%
학 65
 
3.0%
1 55
 
2.6%
고 53
 
2.5%
육 50
 
2.3%
Other values (208) 1222
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1881
87.3%
Decimal Number 101
 
4.7%
Space Separator 92
 
4.3%
Open Punctuation 21
 
1.0%
Close Punctuation 21
 
1.0%
Dash Punctuation 16
 
0.7%
Uppercase Letter 11
 
0.5%
Connector Punctuation 9
 
0.4%
Letter Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
실 156
 
8.3%
강 141
 
7.5%
의 139
 
7.4%
교 106
 
5.6%
등 75
 
4.0%
학 65
 
3.5%
고 53
 
2.8%
육 50
 
2.7%
장 35
 
1.9%
업 30
 
1.6%
Other values (186) 1031
54.8%
Decimal Number
ValueCountFrequency (%)
1 55
54.5%
2 19
 
18.8%
3 8
 
7.9%
4 6
 
5.9%
6 4
 
4.0%
7 4
 
4.0%
5 3
 
3.0%
0 2
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
27.3%
A 2
18.2%
L 2
18.2%
H 1
 
9.1%
D 1
 
9.1%
C 1
 
9.1%
S 1
 
9.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%
Space Separator
ValueCountFrequency (%)
92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1880
87.3%
Common 260
 
12.1%
Latin 13
 
0.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
실 156
 
8.3%
강 141
 
7.5%
의 139
 
7.4%
교 106
 
5.6%
등 75
 
4.0%
학 65
 
3.5%
고 53
 
2.8%
육 50
 
2.7%
장 35
 
1.9%
업 30
 
1.6%
Other values (185) 1030
54.8%
Common
ValueCountFrequency (%)
92
35.4%
1 55
21.2%
( 21
 
8.1%
) 21
 
8.1%
2 19
 
7.3%
- 16
 
6.2%
_ 9
 
3.5%
3 8
 
3.1%
4 6
 
2.3%
6 4
 
1.5%
Other values (3) 9
 
3.5%
Latin
ValueCountFrequency (%)
B 3
23.1%
A 2
15.4%
L 2
15.4%
Ⅱ 1
 
7.7%
H 1
 
7.7%
D 1
 
7.7%
C 1
 
7.7%
Ⅰ 1
 
7.7%
S 1
 
7.7%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1880
87.3%
ASCII 271
 
12.6%
Number Forms 2
 
0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
실 156
 
8.3%
강 141
 
7.5%
의 139
 
7.4%
교 106
 
5.6%
등 75
 
4.0%
학 65
 
3.5%
고 53
 
2.8%
육 50
 
2.7%
장 35
 
1.9%
업 30
 
1.6%
Other values (185) 1030
54.8%
ASCII
ValueCountFrequency (%)
92
33.9%
1 55
20.3%
( 21
 
7.7%
) 21
 
7.7%
2 19
 
7.0%
- 16
 
5.9%
_ 9
 
3.3%
3 8
 
3.0%
4 6
 
2.2%
6 4
 
1.5%
Other values (10) 20
 
7.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%
CJK
ValueCountFrequency (%)
內 1
100.0%

강의실 면적
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
120이상
215 
60~80
 
17
100~120
 
14
80~100
 
14

Length

Max length7
Median length5
Mean length5.1615385
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row120이상
2nd row120이상
3rd row120이상
4th row120이상
5th row120이상

Common Values

ValueCountFrequency (%)
120이상 215
82.7%
60~80 17
 
6.5%
100~120 14
 
5.4%
80~100 14
 
5.4%

Length

2023-12-13T08:15:51.401993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:15:51.506109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
120이상 215
82.7%
60~80 17
 
6.5%
100~120 14
 
5.4%
80~100 14
 
5.4%

강의실 우편번호
Real number (ℝ)

Distinct195
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26806.946
Minimum1399
Maximum63093
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-13T08:15:51.599480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1399
5-th percentile2736
Q110377.25
median23962.5
Q343024.75
95-th percentile59649
Maximum63093
Range61694
Interquartile range (IQR)32647.5

Descriptive statistics

Standard deviation18605.211
Coefficient of variation (CV)0.69404441
Kurtosis-1.2043796
Mean26806.946
Median Absolute Deviation (MAD)16438.5
Skewness0.30778615
Sum6969806
Variance3.4615389 × 108
MonotonicityNot monotonic
2023-12-13T08:15:51.712294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5235 13
 
5.0%
2736 7
 
2.7%
59649 5
 
1.9%
34068 4
 
1.5%
34077 4
 
1.5%
61094 4
 
1.5%
14088 3
 
1.2%
33646 3
 
1.2%
16489 3
 
1.2%
22573 3
 
1.2%
Other values (185) 211
81.2%
ValueCountFrequency (%)
1399 1
 
0.4%
1773 1
 
0.4%
1832 1
 
0.4%
1890 1
 
0.4%
2086 1
 
0.4%
2511 1
 
0.4%
2582 1
 
0.4%
2736 7
2.7%
2859 2
 
0.8%
3192 2
 
0.8%
ValueCountFrequency (%)
63093 2
 
0.8%
61979 1
 
0.4%
61978 1
 
0.4%
61940 1
 
0.4%
61263 1
 
0.4%
61094 4
1.5%
59649 5
1.9%
59614 1
 
0.4%
58649 1
 
0.4%
58534 1
 
0.4%

강의실 주소
Text

Distinct207
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T08:15:51.989097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length17.092308
Min length9

Characters and Unicode

Total characters4444
Distinct characters218
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

Unique179 ?
Unique (%)68.8%

Sample

1st row강원 원주시 태장2동
2nd row강원도 동해시 대동로 215
3rd row전남 순천시 가곡동
4th row전남 순천시 조례동
5th row제주특별자치도 제주시 월산남길 98-2
ValueCountFrequency (%)
서울특별시 61
 
5.8%
경기도 45
 
4.3%
부산광역시 23
 
2.2%
충청남도 19
 
1.8%
강동구 15
 
1.4%
183 14
 
1.3%
고덕로 13
 
1.2%
경상북도 12
 
1.1%
유성구 12
 
1.1%
경기 11
 
1.0%
Other values (469) 828
78.6%
2023-12-13T08:15:52.700363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
793
 
17.8%
시 236
 
5.3%
로 220
 
5.0%
구 191
 
4.3%
1 152
 
3.4%
도 110
 
2.5%
2 99
 
2.2%
경 91
 
2.0%
서 89
 
2.0%
3 84
 
1.9%
Other values (208) 2379
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2901
65.3%
Space Separator 793
 
17.8%
Decimal Number 734
 
16.5%
Dash Punctuation 16
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 236
 
8.1%
로 220
 
7.6%
구 191
 
6.6%
도 110
 
3.8%
경 91
 
3.1%
서 89
 
3.1%
남 81
 
2.8%
광 79
 
2.7%
산 76
 
2.6%
동 75
 
2.6%
Other values (196) 1653
57.0%
Decimal Number
ValueCountFrequency (%)
1 152
20.7%
2 99
13.5%
3 84
11.4%
5 74
10.1%
4 65
8.9%
9 64
8.7%
8 52
 
7.1%
0 52
 
7.1%
6 47
 
6.4%
7 45
 
6.1%
Space Separator
ValueCountFrequency (%)
793
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2901
65.3%
Common 1543
34.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 236
 
8.1%
로 220
 
7.6%
구 191
 
6.6%
도 110
 
3.8%
경 91
 
3.1%
서 89
 
3.1%
남 81
 
2.8%
광 79
 
2.7%
산 76
 
2.6%
동 75
 
2.6%
Other values (196) 1653
57.0%
Common
ValueCountFrequency (%)
793
51.4%
1 152
 
9.9%
2 99
 
6.4%
3 84
 
5.4%
5 74
 
4.8%
4 65
 
4.2%
9 64
 
4.1%
8 52
 
3.4%
0 52
 
3.4%
6 47
 
3.0%
Other values (2) 61
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2901
65.3%
ASCII 1543
34.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
793
51.4%
1 152
 
9.9%
2 99
 
6.4%
3 84
 
5.4%
5 74
 
4.8%
4 65
 
4.2%
9 64
 
4.1%
8 52
 
3.4%
0 52
 
3.4%
6 47
 
3.0%
Other values (2) 61
 
4.0%
Hangul
ValueCountFrequency (%)
시 236
 
8.1%
로 220
 
7.6%
구 191
 
6.6%
도 110
 
3.8%
경 91
 
3.1%
서 89
 
3.1%
남 81
 
2.8%
광 79
 
2.7%
산 76
 
2.6%
동 75
 
2.6%
Other values (196) 1653
57.0%

강의실 상세주소
Text

Distinct224
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T08:15:52.997128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length12.726923
Min length1

Characters and Unicode

Total characters3309
Distinct characters278
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

Unique208 ?
Unique (%)80.0%

Sample

1st row1720-32 태장농공단지관리사무소 (2층)
2nd row(송정동) LS 전선
3rd row고지5길 3
4th row1735-12(2층)
5th row2층
ValueCountFrequency (%)
2층 35
 
5.8%
3층 28
 
4.6%
4층 17
 
2.8%
서울특별시 13
 
2.1%
동부기술교육원 13
 
2.1%
5층 11
 
1.8%
7층 8
 
1.3%
1층 6
 
1.0%
세미나실 5
 
0.8%
강의실 5
 
0.8%
Other values (367) 464
76.7%
2023-12-13T08:15:53.366544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
353
 
10.7%
동 129
 
3.9%
층 122
 
3.7%
) 121
 
3.7%
( 121
 
3.7%
교 91
 
2.8%
2 77
 
2.3%
학 75
 
2.3%
, 65
 
2.0%
고 62
 
1.9%
Other values (268) 2093
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2207
66.7%
Decimal Number 399
 
12.1%
Space Separator 353
 
10.7%
Close Punctuation 121
 
3.7%
Open Punctuation 121
 
3.7%
Other Punctuation 65
 
2.0%
Dash Punctuation 22
 
0.7%
Uppercase Letter 18
 
0.5%
Lowercase Letter 2
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 129
 
5.8%
층 122
 
5.5%
교 91
 
4.1%
학 75
 
3.4%
고 62
 
2.8%
등 57
 
2.6%
실 41
 
1.9%
호 40
 
1.8%
업 40
 
1.8%
공 38
 
1.7%
Other values (237) 1512
68.5%
Uppercase Letter
ValueCountFrequency (%)
L 3
16.7%
B 2
11.1%
S 2
11.1%
I 2
11.1%
N 1
 
5.6%
C 1
 
5.6%
T 1
 
5.6%
G 1
 
5.6%
K 1
 
5.6%
A 1
 
5.6%
Other values (3) 3
16.7%
Decimal Number
ValueCountFrequency (%)
2 77
19.3%
1 61
15.3%
3 58
14.5%
0 51
12.8%
4 49
12.3%
5 34
8.5%
6 25
 
6.3%
7 22
 
5.5%
9 14
 
3.5%
8 8
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
353
100.0%
Close Punctuation
ValueCountFrequency (%)
) 121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 121
100.0%
Other Punctuation
ValueCountFrequency (%)
, 65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2207
66.7%
Common 1082
32.7%
Latin 20
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 129
 
5.8%
층 122
 
5.5%
교 91
 
4.1%
학 75
 
3.4%
고 62
 
2.8%
등 57
 
2.6%
실 41
 
1.9%
호 40
 
1.8%
업 40
 
1.8%
공 38
 
1.7%
Other values (237) 1512
68.5%
Common
ValueCountFrequency (%)
353
32.6%
) 121
 
11.2%
( 121
 
11.2%
2 77
 
7.1%
, 65
 
6.0%
1 61
 
5.6%
3 58
 
5.4%
0 51
 
4.7%
4 49
 
4.5%
5 34
 
3.1%
Other values (6) 92
 
8.5%
Latin
ValueCountFrequency (%)
L 3
15.0%
B 2
 
10.0%
S 2
 
10.0%
I 2
 
10.0%
N 1
 
5.0%
C 1
 
5.0%
T 1
 
5.0%
G 1
 
5.0%
K 1
 
5.0%
A 1
 
5.0%
Other values (5) 5
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2207
66.7%
ASCII 1102
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
353
32.0%
) 121
 
11.0%
( 121
 
11.0%
2 77
 
7.0%
, 65
 
5.9%
1 61
 
5.5%
3 58
 
5.3%
0 51
 
4.6%
4 49
 
4.4%
5 34
 
3.1%
Other values (21) 112
 
10.2%
Hangul
ValueCountFrequency (%)
동 129
 
5.8%
층 122
 
5.5%
교 91
 
4.1%
학 75
 
3.4%
고 62
 
2.8%
등 57
 
2.6%
실 41
 
1.9%
호 40
 
1.8%
업 40
 
1.8%
공 38
 
1.7%
Other values (237) 1512
68.5%

사용 여부
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
미사용
162 
사용
98 

Length

Max length3
Median length3
Mean length2.6230769
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사용
2nd row미사용
3rd row사용
4th row미사용
5th row미사용

Common Values

ValueCountFrequency (%)
미사용 162
62.3%
사용 98
37.7%

Length

2023-12-13T08:15:53.493122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:15:53.578862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미사용 162
62.3%
사용 98
37.7%

강의실면적
Real number (ℝ)

Distinct193
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158.77365
Minimum60
Maximum1200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-13T08:15:53.671837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile70
Q1121.9
median129.215
Q3154.125
95-th percentile330.9
Maximum1200
Range1140
Interquartile range (IQR)32.225

Descriptive statistics

Standard deviation117.12831
Coefficient of variation (CV)0.73770619
Kurtosis47.657718
Mean158.77365
Median Absolute Deviation (MAD)9.785
Skewness5.9794074
Sum41281.15
Variance13719.04
MonotonicityNot monotonic
2023-12-13T08:15:53.787977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
120.0 10
 
3.8%
126.0 5
 
1.9%
130.0 5
 
1.9%
135.0 5
 
1.9%
125.0 5
 
1.9%
122.0 4
 
1.5%
70.0 4
 
1.5%
139.0 4
 
1.5%
143.4 3
 
1.2%
160.0 3
 
1.2%
Other values (183) 212
81.5%
ValueCountFrequency (%)
60.0 2
0.8%
60.1 1
 
0.4%
60.9 1
 
0.4%
61.0 2
0.8%
63.1 1
 
0.4%
64.0 1
 
0.4%
66.6 1
 
0.4%
67.0 1
 
0.4%
69.43 1
 
0.4%
70.0 4
1.5%
ValueCountFrequency (%)
1200.0 2
0.8%
502.0 1
0.4%
485.0 1
0.4%
480.0 1
0.4%
415.0 1
0.4%
400.0 1
0.4%
394.2 2
0.8%
378.8 1
0.4%
370.0 1
0.4%
354.0 1
0.4%

Interactions

2023-12-13T08:15:50.477201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:15:50.330025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:15:50.554354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:15:50.399243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:15:53.860100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강의실 면적강의실 우편번호사용 여부강의실면적
강의실 면적1.0000.1740.1830.000
강의실 우편번호0.1741.0000.3150.000
사용 여부0.1830.3151.0000.101
강의실면적0.0000.0000.1011.000
2023-12-13T08:15:53.948647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용 여부강의실 면적
사용 여부1.0000.121
강의실 면적0.1211.000
2023-12-13T08:15:54.038185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강의실 우편번호강의실면적강의실 면적사용 여부
강의실 우편번호1.000-0.0540.1040.228
강의실면적-0.0541.0000.0000.122
강의실 면적0.1040.0001.0000.121
사용 여부0.2280.1220.1211.000

Missing values

2023-12-13T08:15:50.646504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:15:50.746063image/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

강의실 이름강의실 면적강의실 우편번호강의실 주소강의실 상세주소사용 여부강의실면적
0강의실1120이상26311강원 원주시 태장2동1720-32 태장농공단지관리사무소 (2층)사용186.3
1출장교육장_LS전선120이상25812강원도 동해시 대동로 215(송정동) LS 전선미사용164.4
2강의실1120이상57924전남 순천시 가곡동고지5길 3사용122.0
3강의실120이상57933전남 순천시 조례동1735-12(2층)미사용121.8
4강의실2(제주)120이상63093제주특별자치도 제주시 월산남길 98-22층미사용126.0
51강의실120이상21358인천광역시 부평구 부평대로 138신일유스테이션 2층 (부평동)사용120.6
6강의실1120이상18405경기 화성시 병점동846(태안프라자 301호)미사용138.1
7등록강의실120이상21354인천 부평구 부평동부평대로 154미사용123.9
8한강신도시 택지지구내120이상10045경기도 김포시 황금로24번길 231-4양곡리 747-4미사용120.0
9강의실1120이상5248서울 강동구 천호동432-11(지하층)사용125.5
강의실 이름강의실 면적강의실 우편번호강의실 주소강의실 상세주소사용 여부강의실면적
250방문강의실5120이상21331인천광역시 부평구 주부토로 194부평공업고등학교 본관 4층 시청각실미사용121.58
251방문강의실6120이상14733경기도 부천시 경인로120번길 82부천공업고등학교 질서관 2층 강의실미사용170.4
252등록강의실120이상36621경상북도 안동시 유곡길 1331층사용138.24
253영풍제련소120이상36272경상북도 봉화군 승부길 9-3-미사용199.1
254강의실120이상54852전라북도 전주시 덕진구 유상로 47KT팔복빌딩 3층사용125.0
255등록강의실120이상44720울산광역시 남구 달삼로84번길 82층사용122.87
256등록강의실120이상10071경기도 김포시 김포한강10로133번길 127디원시티 1004호사용124.98
257제1강의실120이상7413서울특별시 영등포구 도림로 153동아빌딩 3층 304호사용122.0
258등록교육장120이상11929경기도 구리시 검배로 5(수택동, 우진빌딩) 5층사용124.99
2594층 강의장120이상44985울산광역시 울주군 삼정로 824401호사용128.7

Duplicate rows

Most frequently occurring

강의실 이름강의실 면적강의실 우편번호강의실 주소강의실 상세주소사용 여부강의실면적# duplicates
0강의실2120이상59649전라남도 여수시 무선로 4512층 (소라면)미사용143.42
1제1강의실120이상10908경기도 파주시 경의로 1114에펠타워 505호 (야당동 1076)미사용121.92