Overview

Dataset statistics

Number of variables5
Number of observations1182
Missing cells4
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory46.3 KiB
Average record size in memory40.1 B

Variable types

Text4
Categorical1

Dataset

Description장성군 홈페이지에서 제공하는 장성아카데미 현황, 문화재현황, 민원사무편람, 음식업소, 숙박업소, 업종별 현황 정보
Author전라남도 장성군
URLhttps://www.data.go.kr/data/15063704/fileData.do

Alerts

Unnamed: 4 is highly imbalanced (57.2%)Imbalance

Reproduction

Analysis started2024-04-17 10:56:45.427685
Analysis finished2024-04-17 10:56:46.175617
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

장성아카데미 강연 현황
Text

Distinct1177
Distinct (%)99.7%
Missing1
Missing (%)0.1%
Memory size9.4 KiB
2024-04-17T19:56:46.449159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0643522
Min length1

Characters and Unicode

Total characters3619
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1173 ?
Unique (%)99.3%

Sample

1st row강의회차
2nd row1179
3rd row1178
4th row1177
5th row1176
ValueCountFrequency (%)
884 2
 
0.2%
1120 2
 
0.2%
895 2
 
0.2%
1131 2
 
0.2%
393 1
 
0.1%
386 1
 
0.1%
387 1
 
0.1%
388 1
 
0.1%
389 1
 
0.1%
390 1
 
0.1%
Other values (1167) 1167
98.8%
2024-04-17T19:56:46.887897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 600
16.6%
4 339
9.4%
5 339
9.4%
3 338
9.3%
2 338
9.3%
7 338
9.3%
6 337
9.3%
8 328
9.1%
0 328
9.1%
9 328
9.1%
Other values (5) 6
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3613
99.8%
Other Letter 4
 
0.1%
Space Separator 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 600
16.6%
4 339
9.4%
5 339
9.4%
3 338
9.4%
2 338
9.4%
7 338
9.4%
6 337
9.3%
8 328
9.1%
0 328
9.1%
9 328
9.1%
Other Letter
ValueCountFrequency (%)
강 1
25.0%
의 1
25.0%
회 1
25.0%
차 1
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3615
99.9%
Hangul 4
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 600
16.6%
4 339
9.4%
5 339
9.4%
3 338
9.3%
2 338
9.3%
7 338
9.3%
6 337
9.3%
8 328
9.1%
0 328
9.1%
9 328
9.1%
Hangul
ValueCountFrequency (%)
강 1
25.0%
의 1
25.0%
회 1
25.0%
차 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3615
99.9%
Hangul 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 600
16.6%
4 339
9.4%
5 339
9.4%
3 338
9.3%
2 338
9.3%
7 338
9.3%
6 337
9.3%
8 328
9.1%
0 328
9.1%
9 328
9.1%
Hangul
ValueCountFrequency (%)
강 1
25.0%
의 1
25.0%
회 1
25.0%
차 1
25.0%

Unnamed: 1
Text

Distinct1177
Distinct (%)99.7%
Missing1
Missing (%)0.1%
Memory size9.4 KiB
2024-04-17T19:56:47.140263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length17.04149
Min length4

Characters and Unicode

Total characters20126
Distinct characters17
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

Unique1174 ?
Unique (%)99.4%

Sample

1st row강의일자
2nd row2024-02-01
3rd row2024-01-18
4th row2024-01-04
5th row2023-12-21
ValueCountFrequency (%)
00:00:00 521
 
24.7%
16:30:00 7
 
0.3%
06:30:45 4
 
0.2%
2017-04-06 3
 
0.1%
16:30:09 2
 
0.1%
2015-12-15 2
 
0.1%
18:16:01 2
 
0.1%
06:30:01 2
 
0.1%
16:30:43 2
 
0.1%
06:30:19 2
 
0.1%
Other values (1554) 1559
74.0%
2024-04-17T19:56:47.494185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6482
32.2%
- 2358
 
11.7%
1 2316
 
11.5%
2 2110
 
10.5%
: 1850
 
9.2%
925
 
4.6%
9 880
 
4.4%
3 659
 
3.3%
4 539
 
2.7%
5 536
 
2.7%
Other values (7) 1471
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14989
74.5%
Dash Punctuation 2358
 
11.7%
Other Punctuation 1850
 
9.2%
Space Separator 925
 
4.6%
Other Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6482
43.2%
1 2316
 
15.5%
2 2110
 
14.1%
9 880
 
5.9%
3 659
 
4.4%
4 539
 
3.6%
5 536
 
3.6%
6 509
 
3.4%
8 488
 
3.3%
7 470
 
3.1%
Other Letter
ValueCountFrequency (%)
강 1
25.0%
의 1
25.0%
일 1
25.0%
자 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 2358
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1850
100.0%
Space Separator
ValueCountFrequency (%)
925
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20122
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6482
32.2%
- 2358
 
11.7%
1 2316
 
11.5%
2 2110
 
10.5%
: 1850
 
9.2%
925
 
4.6%
9 880
 
4.4%
3 659
 
3.3%
4 539
 
2.7%
5 536
 
2.7%
Other values (3) 1467
 
7.3%
Hangul
ValueCountFrequency (%)
강 1
25.0%
의 1
25.0%
일 1
25.0%
자 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20122
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6482
32.2%
- 2358
 
11.7%
1 2316
 
11.5%
2 2110
 
10.5%
: 1850
 
9.2%
925
 
4.6%
9 880
 
4.4%
3 659
 
3.3%
4 539
 
2.7%
5 536
 
2.7%
Other values (3) 1467
 
7.3%
Hangul
ValueCountFrequency (%)
강 1
25.0%
의 1
25.0%
일 1
25.0%
자 1
25.0%

Unnamed: 2
Text

Distinct1179
Distinct (%)99.8%
Missing1
Missing (%)0.1%
Memory size9.4 KiB
2024-04-17T19:56:47.812440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length35
Mean length16.705334
Min length2

Characters and Unicode

Total characters19729
Distinct characters726
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1177 ?
Unique (%)99.7%

Sample

1st row제목
2nd row 나의 한국영화:자전적 성찰
3rd row에너지 전환과 원료(광물자원)시대의 도래
4th row100세 시대, 소통으로 더 즐겁게 사는 법
5th row한마디 말로 우리는
ValueCountFrequency (%)
위한 50
 
1.0%
21세기 43
 
0.9%
41
 
0.8%
과제 35
 
0.7%
어떻게 34
 
0.7%
전략 32
 
0.7%
이야기 26
 
0.5%
한국 26
 
0.5%
미래 24
 
0.5%
새로운 22
 
0.4%
Other values (2912) 4575
93.2%
2024-04-17T19:56:48.246314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3740
 
19.0%
의 670
 
3.4%
한 349
 
1.8%
과 286
 
1.4%
이 285
 
1.4%
지 279
 
1.4%
가 276
 
1.4%
기 271
 
1.4%
는 267
 
1.4%
전 242
 
1.2%
Other values (716) 13064
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15110
76.6%
Space Separator 3740
 
19.0%
Decimal Number 292
 
1.5%
Other Punctuation 287
 
1.5%
Lowercase Letter 85
 
0.4%
Uppercase Letter 71
 
0.4%
Open Punctuation 50
 
0.3%
Close Punctuation 50
 
0.3%
Dash Punctuation 41
 
0.2%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 670
 
4.4%
한 349
 
2.3%
과 286
 
1.9%
이 285
 
1.9%
지 279
 
1.8%
가 276
 
1.8%
기 271
 
1.8%
는 267
 
1.8%
전 242
 
1.6%
국 237
 
1.6%
Other values (647) 11948
79.1%
Lowercase Letter
ValueCountFrequency (%)
e 11
12.9%
o 10
11.8%
r 6
 
7.1%
s 6
 
7.1%
a 6
 
7.1%
n 6
 
7.1%
i 5
 
5.9%
w 5
 
5.9%
t 5
 
5.9%
l 4
 
4.7%
Other values (8) 21
24.7%
Uppercase Letter
ValueCountFrequency (%)
I 8
11.3%
C 7
9.9%
N 7
9.9%
F 7
9.9%
A 6
8.5%
M 5
 
7.0%
D 5
 
7.0%
G 5
 
7.0%
E 4
 
5.6%
O 4
 
5.6%
Other values (8) 13
18.3%
Other Punctuation
ValueCountFrequency (%)
. 134
46.7%
? 60
20.9%
, 43
 
15.0%
! 16
 
5.6%
: 11
 
3.8%
· 9
 
3.1%
' 9
 
3.1%
% 3
 
1.0%
/ 1
 
0.3%
& 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 93
31.8%
2 90
30.8%
0 65
22.3%
9 11
 
3.8%
3 10
 
3.4%
4 8
 
2.7%
5 7
 
2.4%
6 4
 
1.4%
7 4
 
1.4%
Open Punctuation
ValueCountFrequency (%)
【 23
46.0%
( 19
38.0%
「 4
 
8.0%
[ 3
 
6.0%
［ 1
 
2.0%
Close Punctuation
ValueCountFrequency (%)
】 23
46.0%
) 19
38.0%
」 4
 
8.0%
] 3
 
6.0%
］ 1
 
2.0%
Space Separator
ValueCountFrequency (%)
3740
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15080
76.4%
Common 4463
 
22.6%
Latin 156
 
0.8%
Han 30
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 670
 
4.4%
한 349
 
2.3%
과 286
 
1.9%
이 285
 
1.9%
지 279
 
1.9%
가 276
 
1.8%
기 271
 
1.8%
는 267
 
1.8%
전 242
 
1.6%
국 237
 
1.6%
Other values (624) 11918
79.0%
Latin
ValueCountFrequency (%)
e 11
 
7.1%
o 10
 
6.4%
I 8
 
5.1%
C 7
 
4.5%
N 7
 
4.5%
F 7
 
4.5%
r 6
 
3.8%
s 6
 
3.8%
a 6
 
3.8%
A 6
 
3.8%
Other values (26) 82
52.6%
Common
ValueCountFrequency (%)
3740
83.8%
. 134
 
3.0%
1 93
 
2.1%
2 90
 
2.0%
0 65
 
1.5%
? 60
 
1.3%
, 43
 
1.0%
- 41
 
0.9%
【 23
 
0.5%
】 23
 
0.5%
Other values (23) 151
 
3.4%
Han
ValueCountFrequency (%)
生 2
 
6.7%
命 2
 
6.7%
在 2
 
6.7%
天 2
 
6.7%
義 2
 
6.7%
仁 2
 
6.7%
史 2
 
6.7%
庚 1
 
3.3%
道 1
 
3.3%
美 1
 
3.3%
Other values (13) 13
43.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15079
76.4%
ASCII 4554
 
23.1%
None 65
 
0.3%
CJK 30
 
0.2%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3740
82.1%
. 134
 
2.9%
1 93
 
2.0%
2 90
 
2.0%
0 65
 
1.4%
? 60
 
1.3%
, 43
 
0.9%
- 41
 
0.9%
( 19
 
0.4%
) 19
 
0.4%
Other values (52) 250
 
5.5%
Hangul
ValueCountFrequency (%)
의 670
 
4.4%
한 349
 
2.3%
과 286
 
1.9%
이 285
 
1.9%
지 279
 
1.9%
가 276
 
1.8%
기 271
 
1.8%
는 267
 
1.8%
전 242
 
1.6%
국 237
 
1.6%
Other values (623) 11917
79.0%
None
ValueCountFrequency (%)
【 23
35.4%
】 23
35.4%
· 9
 
13.8%
」 4
 
6.2%
「 4
 
6.2%
［ 1
 
1.5%
］ 1
 
1.5%
CJK
ValueCountFrequency (%)
生 2
 
6.7%
命 2
 
6.7%
在 2
 
6.7%
天 2
 
6.7%
義 2
 
6.7%
仁 2
 
6.7%
史 2
 
6.7%
庚 1
 
3.3%
道 1
 
3.3%
美 1
 
3.3%
Other values (13) 13
43.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

Unnamed: 3
Text

Distinct1179
Distinct (%)99.8%
Missing1
Missing (%)0.1%
Memory size9.4 KiB
2024-04-17T19:56:48.502458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length36
Mean length14.648603
Min length2

Characters and Unicode

Total characters17300
Distinct characters564
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1177 ?
Unique (%)99.7%

Sample

1st row강사명
2nd row김홍준 한국영상자료원 원장
3rd row정경우 박사
4th row김민식 pd
5th row이금희 아나운서
ValueCountFrequency (%)
교수 211
 
5.6%
원장 89
 
2.4%
대표 68
 
1.8%
회장 58
 
1.5%
53
 
1.4%
박사 45
 
1.2%
이사장 35
 
0.9%
소장 33
 
0.9%
사장 32
 
0.9%
총장 26
 
0.7%
Other values (2390) 3093
82.6%
2024-04-17T19:56:48.886663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3431
 
19.8%
장 554
 
3.2%
교 524
 
3.0%
대 507
 
2.9%
원 414
 
2.4%
학 392
 
2.3%
수 359
 
2.1%
사 303
 
1.8%
이 302
 
1.7%
김 243
 
1.4%
Other values (554) 10271
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13347
77.2%
Space Separator 3431
 
19.8%
Uppercase Letter 165
 
1.0%
Other Punctuation 132
 
0.8%
Close Punctuation 69
 
0.4%
Open Punctuation 69
 
0.4%
Decimal Number 39
 
0.2%
Lowercase Letter 38
 
0.2%
Dash Punctuation 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 554
 
4.2%
교 524
 
3.9%
대 507
 
3.8%
원 414
 
3.1%
학 392
 
2.9%
수 359
 
2.7%
사 303
 
2.3%
이 302
 
2.3%
김 243
 
1.8%
국 233
 
1.7%
Other values (489) 9516
71.3%
Uppercase Letter
ValueCountFrequency (%)
S 17
 
10.3%
C 17
 
10.3%
K 15
 
9.1%
A 12
 
7.3%
B 12
 
7.3%
I 11
 
6.7%
M 10
 
6.1%
D 9
 
5.5%
T 8
 
4.8%
E 7
 
4.2%
Other values (13) 47
28.5%
Lowercase Letter
ValueCountFrequency (%)
o 5
13.2%
r 4
10.5%
d 4
10.5%
e 3
 
7.9%
l 3
 
7.9%
u 3
 
7.9%
s 3
 
7.9%
a 2
 
5.3%
h 1
 
2.6%
m 1
 
2.6%
Other values (9) 9
23.7%
Decimal Number
ValueCountFrequency (%)
1 15
38.5%
2 8
20.5%
8 4
 
10.3%
3 4
 
10.3%
0 4
 
10.3%
5 1
 
2.6%
7 1
 
2.6%
9 1
 
2.6%
6 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
/ 54
40.9%
. 26
19.7%
: 26
19.7%
, 16
 
12.1%
· 5
 
3.8%
' 2
 
1.5%
․ 2
 
1.5%
& 1
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 68
98.6%
」 1
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 68
98.6%
「 1
 
1.4%
Space Separator
ValueCountFrequency (%)
3431
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13308
76.9%
Common 3750
 
21.7%
Latin 203
 
1.2%
Han 39
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 554
 
4.2%
교 524
 
3.9%
대 507
 
3.8%
원 414
 
3.1%
학 392
 
2.9%
수 359
 
2.7%
사 303
 
2.3%
이 302
 
2.3%
김 243
 
1.8%
국 233
 
1.8%
Other values (487) 9477
71.2%
Latin
ValueCountFrequency (%)
S 17
 
8.4%
C 17
 
8.4%
K 15
 
7.4%
A 12
 
5.9%
B 12
 
5.9%
I 11
 
5.4%
M 10
 
4.9%
D 9
 
4.4%
T 8
 
3.9%
E 7
 
3.4%
Other values (32) 85
41.9%
Common
ValueCountFrequency (%)
3431
91.5%
) 68
 
1.8%
( 68
 
1.8%
/ 54
 
1.4%
. 26
 
0.7%
: 26
 
0.7%
, 16
 
0.4%
1 15
 
0.4%
- 10
 
0.3%
2 8
 
0.2%
Other values (13) 28
 
0.7%
Han
ValueCountFrequency (%)
前 38
97.4%
駐 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13308
76.9%
ASCII 3944
 
22.8%
CJK 39
 
0.2%
None 7
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3431
87.0%
) 68
 
1.7%
( 68
 
1.7%
/ 54
 
1.4%
. 26
 
0.7%
: 26
 
0.7%
S 17
 
0.4%
C 17
 
0.4%
, 16
 
0.4%
1 15
 
0.4%
Other values (51) 206
 
5.2%
Hangul
ValueCountFrequency (%)
장 554
 
4.2%
교 524
 
3.9%
대 507
 
3.8%
원 414
 
3.1%
학 392
 
2.9%
수 359
 
2.7%
사 303
 
2.3%
이 302
 
2.3%
김 243
 
1.8%
국 233
 
1.8%
Other values (487) 9477
71.2%
CJK
ValueCountFrequency (%)
前 38
97.4%
駐 1
 
2.6%
None
ValueCountFrequency (%)
· 5
71.4%
「 1
 
14.3%
」 1
 
14.3%
Punctuation
ValueCountFrequency (%)
․ 2
100.0%

Unnamed: 4
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
video
605 
none
562 
<NA>
 
7
audio
 
5
-
 
2

Length

Max length8
Median length5
Mean length4.5143824
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row미디어 제공여부
3rd rowvideo
4th rowvideo
5th rownone

Common Values

ValueCountFrequency (%)
video 605
51.2%
none 562
47.5%
<NA> 7
 
0.6%
audio 5
 
0.4%
- 2
 
0.2%
미디어 제공여부 1
 
0.1%

Length

2024-04-17T19:56:49.000725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:56:49.090716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
video 605
51.1%
none 562
47.5%
na 7
 
0.6%
audio 5
 
0.4%
2
 
0.2%
미디어 1
 
0.1%
제공여부 1
 
0.1%

Missing values

2024-04-17T19:56:45.970556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T19:56:46.041256image/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.
2024-04-17T19:56:46.122145image/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

장성아카데미 강연 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4
0<NA><NA><NA><NA><NA>
1강의회차강의일자제목강사명미디어 제공여부
211792024-02-01나의 한국영화:자전적 성찰김홍준 한국영상자료원 원장video
311782024-01-18에너지 전환과 원료(광물자원)시대의 도래정경우 박사video
411772024-01-04100세 시대, 소통으로 더 즐겁게 사는 법김민식 pdnone
511762023-12-21한마디 말로 우리는이금희 아나운서none
611752023-12-07규제개혁은 공감에서 시작된다강영철 KDI 국제정책대학원 초빙교수video
711742023-11-16당신의 삶은 안전하십니까?송창영 광주대학교 교수none
811732023-11-02생성형 AI 미래를 열다김필수 리더none
911722023-10-19인생을 바꾸는 퍼스널컬러 이야기팽정은 퍼스널 브랜딩 컨설턴트video
장성아카데미 강연 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4
1172101995-11-17 00:00:00지자제 시행 100일이 지난 오늘의 현황과 새로운 과제조창현 박사none
117391995-11-10 00:00:00대우전자의 세계화 경영전략과 지방자치의 경영화배순훈 회장none
117481995-11-03 00:00:00동북아 경제권 개발현황과 서남지역의 대응전략김영호 박사none
117571995-10-27 00:00:00한국 레제산업의 전망과 지역개발 전략김철호 회장none
117661995-10-20 00:00:00정보화와 지방화 시대의 대응책김용운 박사none
117751995-10-13 00:00:00한국경제와 지역경제 활성화 과제윤화진 박사none
117841995-10-06 00:00:00세계화 시대의 지역경제 발전 방향박 승 박사none
117931995-09-29 00:00:00세계화·지방화 시대 한국농촌의 생존전략허신행 원장none
118021995-09-22 00:00:00지방자치와 경영마인드안병균 회장none
118111995-09-15 00:00:0021세기를 향한 국토개발의 방향과 지역개발 구상이건영/교통개발연구원장none