Overview

Dataset statistics

Number of variables8
Number of observations1104
Missing cells190
Missing cells (%)2.2%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory70.2 KiB
Average record size in memory65.1 B

Variable types

Text4
Categorical1
Numeric1
DateTime2

Dataset

Description한국자산관리공사에서 주관하는 교육과정을 진행하는 강사들의 지금까지 진행한 강의명, 차수, 과목명, 시작일, 종료일에 대한 데이터를 제공합니다.
Author한국자산관리공사
URLhttps://www.data.go.kr/data/15111486/fileData.do

Alerts

Dataset has 1 (0.1%) duplicate rowsDuplicates
과목명 has 190 (17.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 13:20:16.449830
Analysis finished2023-12-12 13:20:17.254595
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

강사번호
Text

Distinct290
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2023-12-12T22:20:17.526076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4416
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)11.8%

Sample

1st rowP055
2nd rowP114
3rd rowP185
4th rowP151
5th rowP171
ValueCountFrequency (%)
p151 52
 
4.7%
p149 41
 
3.7%
p171 31
 
2.8%
p042 29
 
2.6%
p081 25
 
2.3%
p080 22
 
2.0%
p134 20
 
1.8%
p166 20
 
1.8%
p078 19
 
1.7%
p090 18
 
1.6%
Other values (280) 827
74.9%
2023-12-12T22:20:17.978262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 1104
25.0%
1 808
18.3%
0 644
14.6%
2 337
 
7.6%
4 246
 
5.6%
8 246
 
5.6%
6 241
 
5.5%
5 215
 
4.9%
9 208
 
4.7%
3 189
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3312
75.0%
Uppercase Letter 1104
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 808
24.4%
0 644
19.4%
2 337
10.2%
4 246
 
7.4%
8 246
 
7.4%
6 241
 
7.3%
5 215
 
6.5%
9 208
 
6.3%
3 189
 
5.7%
7 178
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
P 1104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3312
75.0%
Latin 1104
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 808
24.4%
0 644
19.4%
2 337
10.2%
4 246
 
7.4%
8 246
 
7.4%
6 241
 
7.3%
5 215
 
6.5%
9 208
 
6.3%
3 189
 
5.7%
7 178
 
5.4%
Latin
ValueCountFrequency (%)
P 1104
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4416
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 1104
25.0%
1 808
18.3%
0 644
14.6%
2 337
 
7.6%
4 246
 
5.6%
8 246
 
5.6%
6 241
 
5.5%
5 215
 
4.9%
9 208
 
4.7%
3 189
 
4.3%

강사이름
Categorical

Distinct50
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
김**
183 
이**
172 
정**
90 
박**
65 
전**
60 
Other values (45)
534 

Length

Max length8
Median length3
Mean length3.009058
Min length3

Unique

Unique8 ?
Unique (%)0.7%

Sample

1st row남**
2nd row이**
3rd row함**
4th row정**
5th row최**

Common Values

ValueCountFrequency (%)
김** 183
16.6%
이** 172
15.6%
정** 90
 
8.2%
박** 65
 
5.9%
전** 60
 
5.4%
최** 58
 
5.3%
백** 47
 
4.3%
조** 39
 
3.5%
장** 30
 
2.7%
한** 30
 
2.7%
Other values (40) 330
29.9%

Length

2023-12-12T22:20:18.113258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
김 183
16.6%
이 172
15.6%
정 90
 
8.2%
박 65
 
5.9%
전 60
 
5.4%
최 58
 
5.3%
백 47
 
4.3%
조 39
 
3.5%
장 30
 
2.7%
한 30
 
2.7%
Other values (40) 330
29.9%

과정번호
Text

Distinct255
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2023-12-12T22:20:18.524569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4416
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)5.3%

Sample

1st rowS001
2nd rowS001
3rd rowS001
4th rowS002
5th rowS002
ValueCountFrequency (%)
s239 18
 
1.6%
s260 17
 
1.5%
s265 14
 
1.3%
s264 12
 
1.1%
s168 9
 
0.8%
s130 9
 
0.8%
s185 9
 
0.8%
s234 9
 
0.8%
s211 9
 
0.8%
s162 9
 
0.8%
Other values (245) 989
89.6%
2023-12-12T22:20:19.093961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 1104
25.0%
2 641
14.5%
1 639
14.5%
0 547
12.4%
6 263
 
6.0%
3 262
 
5.9%
4 218
 
4.9%
5 211
 
4.8%
7 189
 
4.3%
9 185
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3312
75.0%
Uppercase Letter 1104
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 641
19.4%
1 639
19.3%
0 547
16.5%
6 263
7.9%
3 262
7.9%
4 218
 
6.6%
5 211
 
6.4%
7 189
 
5.7%
9 185
 
5.6%
8 157
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
S 1104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3312
75.0%
Latin 1104
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 641
19.4%
1 639
19.3%
0 547
16.5%
6 263
7.9%
3 262
7.9%
4 218
 
6.6%
5 211
 
6.4%
7 189
 
5.7%
9 185
 
5.6%
8 157
 
4.7%
Latin
ValueCountFrequency (%)
S 1104
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4416
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 1104
25.0%
2 641
14.5%
1 639
14.5%
0 547
12.4%
6 263
 
6.0%
3 262
 
5.9%
4 218
 
4.9%
5 211
 
4.8%
7 189
 
4.3%
9 185
 
4.2%

과정명
Text

Distinct165
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2023-12-12T22:20:19.436465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length27
Mean length16.621377
Min length4

Characters and Unicode

Total characters18350
Distinct characters215
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)2.3%

Sample

1st row(교육청)공유재산 관리실무
2nd row(교육청)공유재산 관리실무
3rd row(교육청)공유재산 관리실무
4th row(교육청)공유재산 관리실무
5th row(교육청)공유재산 관리실무
ValueCountFrequency (%)
관리실무 282
 
7.8%
국유재산 213
 
5.9%
교육 146
 
4.0%
공유재산 125
 
3.5%
담당자 98
 
2.7%
2018년 98
 
2.7%
2022년도 94
 
2.6%
취득사업 93
 
2.6%
맞춤형 90
 
2.5%
공용재산 87
 
2.4%
Other values (193) 2293
63.4%
2023-12-12T22:20:19.950536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2565
 
14.0%
무 745
 
4.1%
산 643
 
3.5%
재 637
 
3.5%
2 637
 
3.5%
공 548
 
3.0%
관 545
 
3.0%
교 544
 
3.0%
육 536
 
2.9%
리 485
 
2.6%
Other values (205) 10465
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13832
75.4%
Space Separator 2565
 
14.0%
Decimal Number 1453
 
7.9%
Close Punctuation 158
 
0.9%
Open Punctuation 158
 
0.9%
Uppercase Letter 76
 
0.4%
Other Number 57
 
0.3%
Lowercase Letter 35
 
0.2%
Other Punctuation 11
 
0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
무 745
 
5.4%
산 643
 
4.6%
재 637
 
4.6%
공 548
 
4.0%
관 545
 
3.9%
교 544
 
3.9%
육 536
 
3.9%
리 485
 
3.5%
국 458
 
3.3%
실 447
 
3.2%
Other values (158) 8244
59.6%
Lowercase Letter
ValueCountFrequency (%)
n 5
14.3%
s 4
11.4%
t 4
11.4%
a 3
8.6%
e 3
8.6%
o 3
8.6%
y 3
8.6%
h 2
 
5.7%
r 2
 
5.7%
g 1
 
2.9%
Other values (5) 5
14.3%
Uppercase Letter
ValueCountFrequency (%)
P 24
31.6%
D 17
22.4%
T 6
 
7.9%
I 6
 
7.9%
B 5
 
6.6%
M 5
 
6.6%
A 5
 
6.6%
R 2
 
2.6%
L 2
 
2.6%
S 2
 
2.6%
Decimal Number
ValueCountFrequency (%)
2 637
43.8%
0 400
27.5%
1 220
 
15.1%
8 114
 
7.8%
9 67
 
4.6%
6 5
 
0.3%
3 5
 
0.3%
5 5
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 149
94.3%
」 8
 
5.1%
] 1
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 149
94.3%
「 8
 
5.1%
[ 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
· 8
72.7%
: 2
 
18.2%
, 1
 
9.1%
Other Number
ValueCountFrequency (%)
① 42
73.7%
② 15
 
26.3%
Space Separator
ValueCountFrequency (%)
2565
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13832
75.4%
Common 4407
 
24.0%
Latin 111
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
무 745
 
5.4%
산 643
 
4.6%
재 637
 
4.6%
공 548
 
4.0%
관 545
 
3.9%
교 544
 
3.9%
육 536
 
3.9%
리 485
 
3.5%
국 458
 
3.3%
실 447
 
3.2%
Other values (158) 8244
59.6%
Latin
ValueCountFrequency (%)
P 24
21.6%
D 17
15.3%
T 6
 
5.4%
I 6
 
5.4%
B 5
 
4.5%
M 5
 
4.5%
n 5
 
4.5%
A 5
 
4.5%
s 4
 
3.6%
t 4
 
3.6%
Other values (16) 30
27.0%
Common
ValueCountFrequency (%)
2565
58.2%
2 637
 
14.5%
0 400
 
9.1%
1 220
 
5.0%
) 149
 
3.4%
( 149
 
3.4%
8 114
 
2.6%
9 67
 
1.5%
① 42
 
1.0%
② 15
 
0.3%
Other values (11) 49
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13830
75.4%
ASCII 4437
 
24.2%
Enclosed Alphanum 57
 
0.3%
None 24
 
0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2565
57.8%
2 637
 
14.4%
0 400
 
9.0%
1 220
 
5.0%
) 149
 
3.4%
( 149
 
3.4%
8 114
 
2.6%
9 67
 
1.5%
P 24
 
0.5%
D 17
 
0.4%
Other values (32) 95
 
2.1%
Hangul
ValueCountFrequency (%)
무 745
 
5.4%
산 643
 
4.6%
재 637
 
4.6%
공 548
 
4.0%
관 545
 
3.9%
교 544
 
3.9%
육 536
 
3.9%
리 485
 
3.5%
국 458
 
3.3%
실 447
 
3.2%
Other values (157) 8242
59.6%
Enclosed Alphanum
ValueCountFrequency (%)
① 42
73.7%
② 15
 
26.3%
None
ValueCountFrequency (%)
「 8
33.3%
· 8
33.3%
」 8
33.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%

차수
Real number (ℝ)

Distinct8
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9184783
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2023-12-12T22:20:20.100359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile4
Maximum8
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2262848
Coefficient of variation (CV)0.63919658
Kurtosis2.6462489
Mean1.9184783
Median Absolute Deviation (MAD)1
Skewness1.6422379
Sum2118
Variance1.5037743
MonotonicityNot monotonic
2023-12-12T22:20:20.231670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 542
49.1%
2 324
29.3%
3 109
 
9.9%
4 74
 
6.7%
5 31
 
2.8%
6 19
 
1.7%
7 4
 
0.4%
8 1
 
0.1%
ValueCountFrequency (%)
1 542
49.1%
2 324
29.3%
3 109
 
9.9%
4 74
 
6.7%
5 31
 
2.8%
6 19
 
1.7%
7 4
 
0.4%
8 1
 
0.1%
ValueCountFrequency (%)
8 1
 
0.1%
7 4
 
0.4%
6 19
 
1.7%
5 31
 
2.8%
4 74
 
6.7%
3 109
 
9.9%
2 324
29.3%
1 542
49.1%

과목명
Text

MISSING 

Distinct508
Distinct (%)55.6%
Missing190
Missing (%)17.2%
Memory size8.8 KiB
2023-12-12T22:20:20.515121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length128
Median length31
Mean length11.916849
Min length2

Characters and Unicode

Total characters10892
Distinct characters341
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique336 ?
Unique (%)36.8%

Sample

1st row공유재산 무단점유 변상금관리
2nd row공유재산 이론과 실무
3rd row공유재산 실태조사
4th row최근 도시정책 방향
5th row도시재생 뉴딜정책 사업
ValueCountFrequency (%)
및 225
 
8.6%
국유재산 113
 
4.3%
공유재산 98
 
3.8%
이해 85
 
3.3%
실무 68
 
2.6%
관리 52
 
2.0%
실태조사 41
 
1.6%
온비드 37
 
1.4%
무단점유 35
 
1.3%
관리실무 35
 
1.3%
Other values (621) 1817
69.7%
2023-12-12T22:20:20.985121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1706
 
15.7%
산 388
 
3.6%
무 346
 
3.2%
재 342
 
3.1%
유 330
 
3.0%
실 329
 
3.0%
사 285
 
2.6%
공 271
 
2.5%
리 239
 
2.2%
관 239
 
2.2%
Other values (331) 6417
58.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8757
80.4%
Space Separator 1706
 
15.7%
Other Punctuation 131
 
1.2%
Open Punctuation 84
 
0.8%
Close Punctuation 84
 
0.8%
Uppercase Letter 76
 
0.7%
Decimal Number 20
 
0.2%
Letter Number 16
 
0.1%
Lowercase Letter 8
 
0.1%
Initial Punctuation 5
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 388
 
4.4%
무 346
 
4.0%
재 342
 
3.9%
유 330
 
3.8%
실 329
 
3.8%
사 285
 
3.3%
공 271
 
3.1%
리 239
 
2.7%
관 239
 
2.7%
및 225
 
2.6%
Other values (287) 5763
65.8%
Uppercase Letter
ValueCountFrequency (%)
A 19
25.0%
Q 18
23.7%
I 7
 
9.2%
F 5
 
6.6%
T 4
 
5.3%
S 4
 
5.3%
B 4
 
5.3%
D 4
 
5.3%
L 3
 
3.9%
P 3
 
3.9%
Other values (5) 5
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
i 2
25.0%
e 1
12.5%
l 1
12.5%
n 1
12.5%
c 1
12.5%
y 1
12.5%
a 1
12.5%
Other Punctuation
ValueCountFrequency (%)
· 53
40.5%
, 51
38.9%
& 16
 
12.2%
/ 9
 
6.9%
' 1
 
0.8%
. 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
2 9
45.0%
1 7
35.0%
0 2
 
10.0%
9 1
 
5.0%
4 1
 
5.0%
Open Punctuation
ValueCountFrequency (%)
( 83
98.8%
[ 1
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 83
98.8%
] 1
 
1.2%
Letter Number
ValueCountFrequency (%)
Ⅱ 8
50.0%
Ⅰ 8
50.0%
Other Number
ValueCountFrequency (%)
② 1
50.0%
① 1
50.0%
Space Separator
ValueCountFrequency (%)
1706
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 5
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8757
80.4%
Common 2035
 
18.7%
Latin 100
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 388
 
4.4%
무 346
 
4.0%
재 342
 
3.9%
유 330
 
3.8%
실 329
 
3.8%
사 285
 
3.3%
공 271
 
3.1%
리 239
 
2.7%
관 239
 
2.7%
및 225
 
2.6%
Other values (287) 5763
65.8%
Latin
ValueCountFrequency (%)
A 19
19.0%
Q 18
18.0%
Ⅱ 8
8.0%
Ⅰ 8
8.0%
I 7
 
7.0%
F 5
 
5.0%
T 4
 
4.0%
S 4
 
4.0%
B 4
 
4.0%
D 4
 
4.0%
Other values (14) 19
19.0%
Common
ValueCountFrequency (%)
1706
83.8%
( 83
 
4.1%
) 83
 
4.1%
· 53
 
2.6%
, 51
 
2.5%
& 16
 
0.8%
2 9
 
0.4%
/ 9
 
0.4%
1 7
 
0.3%
‘ 5
 
0.2%
Other values (10) 13
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8756
80.4%
ASCII 2056
 
18.9%
None 53
 
0.5%
Number Forms 16
 
0.1%
Punctuation 8
 
0.1%
Enclosed Alphanum 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1706
83.0%
( 83
 
4.0%
) 83
 
4.0%
, 51
 
2.5%
A 19
 
0.9%
Q 18
 
0.9%
& 16
 
0.8%
2 9
 
0.4%
/ 9
 
0.4%
I 7
 
0.3%
Other values (27) 55
 
2.7%
Hangul
ValueCountFrequency (%)
산 388
 
4.4%
무 346
 
4.0%
재 342
 
3.9%
유 330
 
3.8%
실 329
 
3.8%
사 285
 
3.3%
공 271
 
3.1%
리 239
 
2.7%
관 239
 
2.7%
및 225
 
2.6%
Other values (286) 5762
65.8%
None
ValueCountFrequency (%)
· 53
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 8
50.0%
Ⅰ 8
50.0%
Punctuation
ValueCountFrequency (%)
‘ 5
62.5%
’ 3
37.5%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
② 1
50.0%
① 1
50.0%

시작일
Date

Distinct217
Distinct (%)19.7%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
Minimum2018-02-22 00:00:00
Maximum2022-11-18 00:00:00
2023-12-12T22:20:21.172339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:20:21.628742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

종료일
Date

Distinct222
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
Minimum2018-02-22 00:00:00
Maximum2022-11-18 00:00:00
2023-12-12T22:20:21.778136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:20:21.912147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T22:20:16.928411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:20:22.013082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강사이름차수
강사이름1.0000.000
차수0.0001.000
2023-12-12T22:20:22.090597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차수강사이름
차수1.0000.000
강사이름0.0001.000

Missing values

2023-12-12T22:20:17.075833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:20:17.206608image/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

강사번호강사이름과정번호과정명차수과목명시작일종료일
0P055남**S001(교육청)공유재산 관리실무1<NA>2022-01-212022-01-21
1P114이**S001(교육청)공유재산 관리실무1<NA>2022-01-212022-01-21
2P185함**S001(교육청)공유재산 관리실무1<NA>2022-01-212022-01-21
3P151정**S002(교육청)공유재산 관리실무2<NA>2022-02-232022-02-23
4P171최**S002(교육청)공유재산 관리실무2<NA>2022-02-232022-02-23
5P185함**S002(교육청)공유재산 관리실무2<NA>2022-02-232022-02-23
6P042김**S003(교육청)공유재산 관리실무4공유재산 무단점유 변상금관리2022-06-032022-06-03
7P063박**S003(교육청)공유재산 관리실무4공유재산 이론과 실무2022-06-032022-06-03
8P133이**S003(교육청)공유재산 관리실무4공유재산 실태조사2022-06-032022-06-03
9P084서**S004(맞춤형)국가철도공단 국유재산 직무교육(623~25)1<NA>2021-06-232021-06-25
강사번호강사이름과정번호과정명차수과목명시작일종료일
1094P292박**S2652022년도 직무역량 공통교육 국유재산관리과정2연체채권관리2022-09-162022-11-15
1095P293최**S2652022년도 직무역량 공통교육 국유재산관리과정2국유재산 실태조사2022-09-162022-11-15
1096P294강**S2652022년도 직무역량 공통교육 국유재산관리과정2국유회계.세무2022-09-162022-11-15
1097P144장**S2652022년도 직무역량 공통교육 국유재산관리과정2행정심판의 이해 (무단점유 심화과정)2022-09-162022-11-15
1098P296이**S2652022년도 직무역량 공통교육 국유재산관리과정2국유재산 법령2022-09-162022-11-15
1099P296이**S2652022년도 직무역량 공통교육 국유재산관리과정2국가소송2022-09-162022-11-15
1100P296이**S2652022년도 직무역량 공통교육 국유재산관리과정2행정대집행2022-09-162022-11-15
1101P299이**S2652022년도 직무역량 공통교육 국유재산관리과정2민원응대2022-09-162022-11-15
1102P300김**S2652022년도 직무역량 공통교육 국유재산관리과정2국유재산 실무 안전교육2022-09-162022-11-15
1103P301박**S2652022년도 직무역량 공통교육 국유재산관리과정2감사 매뉴얼 및 반복 지적사례2022-09-162022-11-15

Duplicate rows

Most frequently occurring

강사번호강사이름과정번호과정명차수과목명시작일종료일# duplicates
0P149전**S239신입입문교육1국유재산총론2022-08-012022-08-054