Overview

Dataset statistics

Number of variables10
Number of observations304
Missing cells23
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.8 KiB
Average record size in memory83.4 B

Variable types

Numeric3
Text3
Categorical2
DateTime2

Dataset

Description재단에서 발행하고 있는 뉴스레터에 대한 데이터로 기사번호, 기사이름, 기사내용요약본, 이미지파일명 등에 대한 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15042289/fileData.do

Alerts

클릭된횟수 is highly overall correlated with 메일읽은횟수High correlation
메일읽은횟수 is highly overall correlated with 클릭된횟수High correlation
등록자아이디 is highly overall correlated with 수정자아이디High correlation
수정자아이디 is highly overall correlated with 등록자아이디High correlation
등록자아이디 is highly imbalanced (89.2%)Imbalance
수정자아이디 is highly imbalanced (65.0%)Imbalance
수정일자 has 20 (6.6%) missing valuesMissing
기사번호 has unique valuesUnique
기사이름 has unique valuesUnique
클릭된횟수 has 75 (24.7%) zerosZeros
메일읽은횟수 has 75 (24.7%) zerosZeros

Reproduction

Analysis started2023-12-12 09:36:05.147897
Analysis finished2023-12-12 09:36:07.672327
Duration2.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기사번호
Real number (ℝ)

UNIQUE 

Distinct304
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean172.88816
Minimum6
Maximum334
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T18:36:07.741441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile23.15
Q190.75
median173.5
Q3254.25
95-th percentile316.85
Maximum334
Range328
Interquartile range (IQR)163.5

Descriptive statistics

Standard deviation94.070372
Coefficient of variation (CV)0.54411114
Kurtosis-1.1945706
Mean172.88816
Median Absolute Deviation (MAD)82
Skewness-0.024941587
Sum52558
Variance8849.235
MonotonicityNot monotonic
2023-12-12T18:36:07.913236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53 1
 
0.3%
265 1
 
0.3%
51 1
 
0.3%
50 1
 
0.3%
49 1
 
0.3%
9 1
 
0.3%
267 1
 
0.3%
266 1
 
0.3%
261 1
 
0.3%
259 1
 
0.3%
Other values (294) 294
96.7%
ValueCountFrequency (%)
6 1
0.3%
8 1
0.3%
9 1
0.3%
11 1
0.3%
12 1
0.3%
13 1
0.3%
14 1
0.3%
15 1
0.3%
16 1
0.3%
17 1
0.3%
ValueCountFrequency (%)
334 1
0.3%
333 1
0.3%
331 1
0.3%
330 1
0.3%
329 1
0.3%
328 1
0.3%
327 1
0.3%
326 1
0.3%
325 1
0.3%
324 1
0.3%

기사이름
Text

UNIQUE 

Distinct304
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T18:36:08.278278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length48.5
Mean length31.25
Min length3

Characters and Unicode

Total characters9500
Distinct characters395
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique304 ?
Unique (%)100.0%

Sample

1st row한국사학진흥재단(KFPP) - 2014년 학교법인 수익용기본재산 집계 사전설명회 개최 -
2nd row한국사학진흥재단(KFPP), 벽성대학 학적이관 사업 완료 제 증명발급 서비스 개시
3rd row한국사학진흥재단(KFPP), 2014년 추석 명절 행동강령
4th row2015년 2월 전문가양성과정, KFPP-e러닝 개최
5th row2015년도 1차 정책연구과제 연구자 공모
ValueCountFrequency (%)
한국사학진흥재단 132
 
7.2%
개최 79
 
4.3%
36
 
2.0%
실시 28
 
1.5%
위한 22
 
1.2%
안내 21
 
1.1%
행복(연합)기숙사 19
 
1.0%
신청 19
 
1.0%
지원 17
 
0.9%
사학진흥기금 17
 
0.9%
Other values (720) 1448
78.8%
2023-12-12T18:36:08.854829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1544
 
16.3%
408
 
4.3%
329
 
3.5%
215
 
2.3%
214
 
2.3%
206
 
2.2%
205
 
2.2%
192
 
2.0%
173
 
1.8%
, 168
 
1.8%
Other values (385) 5846
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6681
70.3%
Space Separator 1544
 
16.3%
Decimal Number 565
 
5.9%
Other Punctuation 207
 
2.2%
Uppercase Letter 186
 
2.0%
Close Punctuation 98
 
1.0%
Open Punctuation 98
 
1.0%
Initial Punctuation 32
 
0.3%
Final Punctuation 30
 
0.3%
Dash Punctuation 29
 
0.3%
Other values (2) 30
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
408
 
6.1%
329
 
4.9%
215
 
3.2%
214
 
3.2%
206
 
3.1%
205
 
3.1%
192
 
2.9%
173
 
2.6%
160
 
2.4%
146
 
2.2%
Other values (325) 4433
66.4%
Uppercase Letter
ValueCountFrequency (%)
P 67
36.0%
K 35
18.8%
F 33
17.7%
S 7
 
3.8%
U 7
 
3.8%
O 6
 
3.2%
A 5
 
2.7%
I 4
 
2.2%
C 3
 
1.6%
M 3
 
1.6%
Other values (9) 16
 
8.6%
Decimal Number
ValueCountFrequency (%)
1 151
26.7%
2 147
26.0%
0 114
20.2%
5 39
 
6.9%
4 33
 
5.8%
6 28
 
5.0%
7 23
 
4.1%
3 12
 
2.1%
8 12
 
2.1%
9 6
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 168
81.2%
· 14
 
6.8%
. 10
 
4.8%
& 5
 
2.4%
; 4
 
1.9%
# 4
 
1.9%
? 1
 
0.5%
! 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
e 15
51.7%
i 5
 
17.2%
a 2
 
6.9%
s 2
 
6.9%
f 2
 
6.9%
v 1
 
3.4%
n 1
 
3.4%
w 1
 
3.4%
Close Punctuation
ValueCountFrequency (%)
) 76
77.6%
18
 
18.4%
] 3
 
3.1%
1
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 76
77.6%
18
 
18.4%
[ 3
 
3.1%
1
 
1.0%
Initial Punctuation
ValueCountFrequency (%)
18
56.2%
14
43.8%
Final Punctuation
ValueCountFrequency (%)
16
53.3%
14
46.7%
Space Separator
ValueCountFrequency (%)
1544
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6680
70.3%
Common 2604
 
27.4%
Latin 215
 
2.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
408
 
6.1%
329
 
4.9%
215
 
3.2%
214
 
3.2%
206
 
3.1%
205
 
3.1%
192
 
2.9%
173
 
2.6%
160
 
2.4%
146
 
2.2%
Other values (324) 4432
66.3%
Common
ValueCountFrequency (%)
1544
59.3%
, 168
 
6.5%
1 151
 
5.8%
2 147
 
5.6%
0 114
 
4.4%
) 76
 
2.9%
( 76
 
2.9%
5 39
 
1.5%
4 33
 
1.3%
- 29
 
1.1%
Other values (23) 227
 
8.7%
Latin
ValueCountFrequency (%)
P 67
31.2%
K 35
16.3%
F 33
15.3%
e 15
 
7.0%
S 7
 
3.3%
U 7
 
3.3%
O 6
 
2.8%
i 5
 
2.3%
A 5
 
2.3%
I 4
 
1.9%
Other values (17) 31
14.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6680
70.3%
ASCII 2705
28.5%
Punctuation 62
 
0.7%
None 52
 
0.5%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1544
57.1%
, 168
 
6.2%
1 151
 
5.6%
2 147
 
5.4%
0 114
 
4.2%
) 76
 
2.8%
( 76
 
2.8%
P 67
 
2.5%
5 39
 
1.4%
K 35
 
1.3%
Other values (41) 288
 
10.6%
Hangul
ValueCountFrequency (%)
408
 
6.1%
329
 
4.9%
215
 
3.2%
214
 
3.2%
206
 
3.1%
205
 
3.1%
192
 
2.9%
173
 
2.6%
160
 
2.4%
146
 
2.2%
Other values (324) 4432
66.3%
Punctuation
ValueCountFrequency (%)
18
29.0%
16
25.8%
14
22.6%
14
22.6%
None
ValueCountFrequency (%)
18
34.6%
18
34.6%
· 14
26.9%
1
 
1.9%
1
 
1.9%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct303
Distinct (%)100.0%
Missing1
Missing (%)0.3%
Memory size2.5 KiB
2023-12-12T18:36:09.383041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length152
Median length117
Mean length90.270627
Min length3

Characters and Unicode

Total characters27352
Distinct characters559
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique303 ?
Unique (%)100.0%

Sample

1st row한국사학진흥재단(이사장 이원희, 이하 케프)은 지난 6월 13일(금)과 16일(화) 이틀에 걸쳐 ‘2014년 학교법인 수익용 기본재산 집계 사전설명회’를 개최했다.
2nd row한국사학진흥재단(이사장 이원희, 이하 ‘케프’)은 ‘14년도 폐쇄대학 후속조치 지원관리사업의 일환으로 폐교가 확정된 벽성대학 학생을 위한 학적부 발급 및 교직원을 위한 경력증명서 등 제증명 발급 서비스를 ‘14년 7월 1일자로 전용사이트에서 지원한다고 밝혔다.
3rd row한국사학진흥재단(이사장 이원희, 이하 케프)은 2014년 추석 명절을 앞두고 케프 임직원 및 직무와 관련있는 업체들을 대상으로 행동강령 이행실태와 부패행위에 대한 집중 점검을 실시한다.
4th row한국사학진흥재단(이사장 김혜천, 이하‘재단’)은 사립교육의 부흥과 도약, 전체적인 균형화, 내실화를 위해 2015년 2월 전문가양성과정, 한국사학진흥재단 KFPP-e러닝, 위탁교육, 강사 파견 교육 등을 상시적으로 개최한다.
5th row한국사학진흥재단(이사장 김혜천, 이하 ‘케프’)은 1월 29일부터 2015년도 1차 정책연구과제 연구자 공모를 실시하였다.
ValueCountFrequency (%)
한국사학진흥재단(이사장 185
 
3.6%
이하 168
 
3.2%
김혜천 117
 
2.3%
92
 
1.8%
84
 
1.6%
이원희 62
 
1.2%
‘케프’)은 58
 
1.1%
위한 53
 
1.0%
케프)은 41
 
0.8%
2014년 33
 
0.6%
Other values (2296) 4289
82.8%
2023-12-12T18:36:10.059021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4930
 
18.0%
804
 
2.9%
617
 
2.3%
563
 
2.1%
457
 
1.7%
( 446
 
1.6%
) 446
 
1.6%
431
 
1.6%
1 419
 
1.5%
396
 
1.4%
Other values (549) 17843
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18117
66.2%
Space Separator 4930
 
18.0%
Decimal Number 1624
 
5.9%
Other Punctuation 759
 
2.8%
Open Punctuation 477
 
1.7%
Close Punctuation 476
 
1.7%
Initial Punctuation 228
 
0.8%
Uppercase Letter 213
 
0.8%
Final Punctuation 198
 
0.7%
Lowercase Letter 173
 
0.6%
Other values (4) 157
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
804
 
4.4%
617
 
3.4%
563
 
3.1%
457
 
2.5%
431
 
2.4%
396
 
2.2%
355
 
2.0%
316
 
1.7%
308
 
1.7%
305
 
1.7%
Other values (458) 13565
74.9%
Uppercase Letter
ValueCountFrequency (%)
P 62
29.1%
K 35
16.4%
F 31
14.6%
S 15
 
7.0%
U 9
 
4.2%
O 8
 
3.8%
C 8
 
3.8%
A 6
 
2.8%
N 5
 
2.3%
I 5
 
2.3%
Other values (12) 29
13.6%
Lowercase Letter
ValueCountFrequency (%)
e 38
22.0%
i 22
12.7%
t 13
 
7.5%
s 11
 
6.4%
a 11
 
6.4%
o 10
 
5.8%
c 10
 
5.8%
n 10
 
5.8%
r 9
 
5.2%
p 6
 
3.5%
Other values (12) 33
19.1%
Other Punctuation
ValueCountFrequency (%)
, 321
42.3%
. 284
37.4%
· 32
 
4.2%
& 26
 
3.4%
; 26
 
3.4%
# 25
 
3.3%
: 13
 
1.7%
% 10
 
1.3%
' 10
 
1.3%
? 4
 
0.5%
Other values (5) 8
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 419
25.8%
2 353
21.7%
0 237
14.6%
4 124
 
7.6%
5 103
 
6.3%
3 95
 
5.8%
8 80
 
4.9%
6 79
 
4.9%
9 68
 
4.2%
7 66
 
4.1%
Math Symbol
ValueCountFrequency (%)
~ 4
40.0%
< 2
20.0%
> 2
20.0%
1
 
10.0%
1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 446
93.5%
26
 
5.5%
3
 
0.6%
[ 2
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 446
93.7%
25
 
5.3%
3
 
0.6%
] 2
 
0.4%
Initial Punctuation
ValueCountFrequency (%)
192
84.2%
36
 
15.8%
Final Punctuation
ValueCountFrequency (%)
163
82.3%
35
 
17.7%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
4930
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 143
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18117
66.2%
Common 8848
32.3%
Latin 386
 
1.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
804
 
4.4%
617
 
3.4%
563
 
3.1%
457
 
2.5%
431
 
2.4%
396
 
2.2%
355
 
2.0%
316
 
1.7%
308
 
1.7%
305
 
1.7%
Other values (458) 13565
74.9%
Common
ValueCountFrequency (%)
4930
55.7%
( 446
 
5.0%
) 446
 
5.0%
1 419
 
4.7%
2 353
 
4.0%
, 321
 
3.6%
. 284
 
3.2%
0 237
 
2.7%
192
 
2.2%
163
 
1.8%
Other values (36) 1057
 
11.9%
Latin
ValueCountFrequency (%)
P 62
16.1%
e 38
 
9.8%
K 35
 
9.1%
F 31
 
8.0%
i 22
 
5.7%
S 15
 
3.9%
t 13
 
3.4%
s 11
 
2.8%
a 11
 
2.8%
o 10
 
2.6%
Other values (34) 138
35.8%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18116
66.2%
ASCII 8715
31.9%
Punctuation 427
 
1.6%
None 90
 
0.3%
Arrows 2
 
< 0.1%
CJK 1
 
< 0.1%
Geometric Shapes 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4930
56.6%
( 446
 
5.1%
) 446
 
5.1%
1 419
 
4.8%
2 353
 
4.1%
, 321
 
3.7%
. 284
 
3.3%
0 237
 
2.7%
- 143
 
1.6%
4 124
 
1.4%
Other values (67) 1012
 
11.6%
Hangul
ValueCountFrequency (%)
804
 
4.4%
617
 
3.4%
563
 
3.1%
457
 
2.5%
431
 
2.4%
396
 
2.2%
355
 
2.0%
316
 
1.7%
308
 
1.7%
305
 
1.7%
Other values (457) 13564
74.9%
Punctuation
ValueCountFrequency (%)
192
45.0%
163
38.2%
36
 
8.4%
35
 
8.2%
1
 
0.2%
None
ValueCountFrequency (%)
· 32
35.6%
26
28.9%
25
27.8%
3
 
3.3%
3
 
3.3%
1
 
1.1%
CJK
ValueCountFrequency (%)
1
100.0%
Arrows
ValueCountFrequency (%)
1
50.0%
1
50.0%
Geometric Shapes
ValueCountFrequency (%)
1
100.0%
Distinct302
Distinct (%)100.0%
Missing2
Missing (%)0.7%
Memory size2.5 KiB
2023-12-12T18:36:10.346768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length73
Mean length73
Min length73

Characters and Unicode

Total characters22046
Distinct characters33
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique302 ?
Unique (%)100.0%

Sample

1st row/html/mimevalue_image/2014-06-20/nl_news_title_20140620155150732031_1.jpg
2nd row/html/mimevalue_image/2014-06-30/nl_news_title_20140630191917928163_1.jpg
3rd row/html/mimevalue_image/2014-09-03/nl_news_title_20140903161745747005_1.jpg
4th row/html/mimevalue_image/2015-01-23/nl_news_title_20150123164557078015_1.jpg
5th row/html/mimevalue_image/2015-01-29/nl_news_title_20150129132118192033_1.JPG
ValueCountFrequency (%)
html/mimevalue_image/2015-01-16/nl_news_title_20150116154857307059_1.jpg 1
 
0.3%
html/mimevalue_image/2014-06-19/nl_news_title_20140619173130248026_1.jpg 1
 
0.3%
html/mimevalue_image/2017-01-03/nl_news_title_20170103103253579016_1.jpg 1
 
0.3%
html/mimevalue_image/2014-05-30/nl_news_title_20140530182425817035_1.jpg 1
 
0.3%
html/mimevalue_image/2013-12-11/nl_news_title_20131211141752605017_1.jpg 1
 
0.3%
html/mimevalue_image/2017-02-03/nl_news_title_20170203113954612061_1.jpg 1
 
0.3%
html/mimevalue_image/2017-02-01/nl_news_title_20170201134735559051_1.jpg 1
 
0.3%
html/mimevalue_image/2017-01-04/nl_news_title_20170104113032380020_1.jpg 1
 
0.3%
html/mimevalue_image/2017-02-01/nl_news_title_20170201091430783041_1.jpg 1
 
0.3%
html/mimevalue_image/2017-01-03/nl_news_title_20170103103628162017_1.jpg 1
 
0.3%
Other values (292) 292
96.7%
2023-12-12T18:36:10.819402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2076
 
9.4%
0 1926
 
8.7%
e 1510
 
6.8%
_ 1510
 
6.8%
2 1346
 
6.1%
/ 1208
 
5.5%
m 1208
 
5.5%
l 1208
 
5.5%
t 906
 
4.1%
i 906
 
4.1%
Other values (23) 8242
37.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9325
42.3%
Decimal Number 8758
39.7%
Connector Punctuation 1510
 
6.8%
Other Punctuation 1510
 
6.8%
Dash Punctuation 604
 
2.7%
Uppercase Letter 339
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1510
16.2%
m 1208
13.0%
l 1208
13.0%
t 906
9.7%
i 906
9.7%
n 608
6.5%
a 604
 
6.5%
g 491
 
5.3%
s 302
 
3.2%
u 302
 
3.2%
Other values (5) 1280
13.7%
Decimal Number
ValueCountFrequency (%)
1 2076
23.7%
0 1926
22.0%
2 1346
15.4%
4 597
 
6.8%
5 589
 
6.7%
3 535
 
6.1%
7 510
 
5.8%
6 485
 
5.5%
9 370
 
4.2%
8 324
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
P 113
33.3%
G 113
33.3%
J 112
33.0%
N 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
/ 1208
80.0%
. 302
 
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1510
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 604
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12382
56.2%
Latin 9664
43.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1510
15.6%
m 1208
12.5%
l 1208
12.5%
t 906
9.4%
i 906
9.4%
n 608
 
6.3%
a 604
 
6.2%
g 491
 
5.1%
s 302
 
3.1%
u 302
 
3.1%
Other values (9) 1619
16.8%
Common
ValueCountFrequency (%)
1 2076
16.8%
0 1926
15.6%
_ 1510
12.2%
2 1346
10.9%
/ 1208
9.8%
- 604
 
4.9%
4 597
 
4.8%
5 589
 
4.8%
3 535
 
4.3%
7 510
 
4.1%
Other values (4) 1481
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22046
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2076
 
9.4%
0 1926
 
8.7%
e 1510
 
6.8%
_ 1510
 
6.8%
2 1346
 
6.1%
/ 1208
 
5.5%
m 1208
 
5.5%
l 1208
 
5.5%
t 906
 
4.1%
i 906
 
4.1%
Other values (23) 8242
37.4%

등록자아이디
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
sahak01
297 
admin
 
6
kasfo012
 
1

Length

Max length8
Median length7
Mean length6.9638158
Min length5

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowsahak01
2nd rowsahak01
3rd rowsahak01
4th rowsahak01
5th rowsahak01

Common Values

ValueCountFrequency (%)
sahak01 297
97.7%
admin 6
 
2.0%
kasfo012 1
 
0.3%

Length

2023-12-12T18:36:10.990300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:36:11.100201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
sahak01 297
97.7%
admin 6
 
2.0%
kasfo012 1
 
0.3%
Distinct260
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2013-12-09 00:00:00
Maximum2022-11-02 00:00:00
2023-12-12T18:36:11.228815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:36:11.402420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정자아이디
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
sahak01
274 
<NA>
 
20
admin
 
10

Length

Max length7
Median length7
Mean length6.7368421
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowsahak01
2nd rowsahak01
3rd rowsahak01
4th rowsahak01
5th rowsahak01

Common Values

ValueCountFrequency (%)
sahak01 274
90.1%
<NA> 20
 
6.6%
admin 10
 
3.3%

Length

2023-12-12T18:36:11.586109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:36:11.706186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
sahak01 274
90.1%
na 20
 
6.6%
admin 10
 
3.3%

수정일자
Date

MISSING 

Distinct240
Distinct (%)84.5%
Missing20
Missing (%)6.6%
Memory size2.5 KiB
Minimum2013-12-11 00:00:00
Maximum2019-08-16 00:00:00
2023-12-12T18:36:11.845018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:36:12.051806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

클릭된횟수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct105
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.355263
Minimum0
Maximum3031
Zeros75
Zeros (%)24.7%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T18:36:12.208569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median19
Q350
95-th percentile185.7
Maximum3031
Range3031
Interquartile range (IQR)49

Descriptive statistics

Standard deviation182.69509
Coefficient of variation (CV)3.4895268
Kurtosis234.95517
Mean52.355263
Median Absolute Deviation (MAD)19
Skewness14.481492
Sum15916
Variance33377.497
MonotonicityNot monotonic
2023-12-12T18:36:12.355593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 75
24.7%
27 8
 
2.6%
8 8
 
2.6%
19 7
 
2.3%
7 7
 
2.3%
11 7
 
2.3%
4 6
 
2.0%
14 6
 
2.0%
9 5
 
1.6%
22 5
 
1.6%
Other values (95) 170
55.9%
ValueCountFrequency (%)
0 75
24.7%
1 2
 
0.7%
2 2
 
0.7%
3 3
 
1.0%
4 6
 
2.0%
5 3
 
1.0%
6 3
 
1.0%
7 7
 
2.3%
8 8
 
2.6%
9 5
 
1.6%
ValueCountFrequency (%)
3031 1
0.3%
380 1
0.3%
365 1
0.3%
318 1
0.3%
262 1
0.3%
253 2
0.7%
234 1
0.3%
229 1
0.3%
228 1
0.3%
217 1
0.3%

메일읽은횟수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct105
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.355263
Minimum0
Maximum3031
Zeros75
Zeros (%)24.7%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T18:36:12.506336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median19
Q350
95-th percentile185.7
Maximum3031
Range3031
Interquartile range (IQR)49

Descriptive statistics

Standard deviation182.69509
Coefficient of variation (CV)3.4895268
Kurtosis234.95517
Mean52.355263
Median Absolute Deviation (MAD)19
Skewness14.481492
Sum15916
Variance33377.497
MonotonicityNot monotonic
2023-12-12T18:36:12.679367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 75
24.7%
27 8
 
2.6%
8 8
 
2.6%
19 7
 
2.3%
7 7
 
2.3%
11 7
 
2.3%
4 6
 
2.0%
14 6
 
2.0%
9 5
 
1.6%
22 5
 
1.6%
Other values (95) 170
55.9%
ValueCountFrequency (%)
0 75
24.7%
1 2
 
0.7%
2 2
 
0.7%
3 3
 
1.0%
4 6
 
2.0%
5 3
 
1.0%
6 3
 
1.0%
7 7
 
2.3%
8 8
 
2.6%
9 5
 
1.6%
ValueCountFrequency (%)
3031 1
0.3%
380 1
0.3%
365 1
0.3%
318 1
0.3%
262 1
0.3%
253 2
0.7%
234 1
0.3%
229 1
0.3%
228 1
0.3%
217 1
0.3%

Interactions

2023-12-12T18:36:06.606944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:36:05.929850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:36:06.262174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:36:06.729539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:36:06.052943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:36:06.366781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:36:06.833415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:36:06.155414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:36:06.467929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:36:12.786119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기사번호등록자아이디수정자아이디클릭된횟수메일읽은횟수
기사번호1.0000.3890.2980.0000.000
등록자아이디0.3891.0000.8330.0000.000
수정자아이디0.2980.8331.0000.0000.000
클릭된횟수0.0000.0000.0001.0001.000
메일읽은횟수0.0000.0000.0001.0001.000
2023-12-12T18:36:12.909654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록자아이디수정자아이디
등록자아이디1.0000.626
수정자아이디0.6261.000
2023-12-12T18:36:13.025715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기사번호클릭된횟수메일읽은횟수등록자아이디수정자아이디
기사번호1.000-0.416-0.4160.2510.225
클릭된횟수-0.4161.0001.0000.0000.000
메일읽은횟수-0.4161.0001.0000.0000.000
등록자아이디0.2510.0000.0001.0000.626
수정자아이디0.2250.0000.0000.6261.000

Missing values

2023-12-12T18:36:07.310781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:36:07.486906image/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.
2023-12-12T18:36:07.607812image/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

기사번호기사이름기사 요약파일명등록자아이디등록일자수정자아이디수정일자클릭된횟수메일읽은횟수
053한국사학진흥재단(KFPP) - 2014년 학교법인 수익용기본재산 집계 사전설명회 개최 -한국사학진흥재단(이사장 이원희, 이하 케프)은 지난 6월 13일(금)과 16일(화) 이틀에 걸쳐 ‘2014년 학교법인 수익용 기본재산 집계 사전설명회’를 개최했다./html/mimevalue_image/2014-06-20/nl_news_title_20140620155150732031_1.jpgsahak012014-06-20sahak012014-06-254747
157한국사학진흥재단(KFPP), 벽성대학 학적이관 사업 완료 제 증명발급 서비스 개시한국사학진흥재단(이사장 이원희, 이하 ‘케프’)은 ‘14년도 폐쇄대학 후속조치 지원관리사업의 일환으로 폐교가 확정된 벽성대학 학생을 위한 학적부 발급 및 교직원을 위한 경력증명서 등 제증명 발급 서비스를 ‘14년 7월 1일자로 전용사이트에서 지원한다고 밝혔다./html/mimevalue_image/2014-06-30/nl_news_title_20140630191917928163_1.jpgsahak012014-06-30sahak012014-07-0377
271한국사학진흥재단(KFPP), 2014년 추석 명절 행동강령한국사학진흥재단(이사장 이원희, 이하 케프)은 2014년 추석 명절을 앞두고 케프 임직원 및 직무와 관련있는 업체들을 대상으로 행동강령 이행실태와 부패행위에 대한 집중 점검을 실시한다./html/mimevalue_image/2014-09-03/nl_news_title_20140903161745747005_1.jpgsahak012014-09-03sahak012014-09-031212
31032015년 2월 전문가양성과정, KFPP-e러닝 개최한국사학진흥재단(이사장 김혜천, 이하‘재단’)은 사립교육의 부흥과 도약, 전체적인 균형화, 내실화를 위해 2015년 2월 전문가양성과정, 한국사학진흥재단 KFPP-e러닝, 위탁교육, 강사 파견 교육 등을 상시적으로 개최한다./html/mimevalue_image/2015-01-23/nl_news_title_20150123164557078015_1.jpgsahak012015-01-23sahak012015-01-235555
41042015년도 1차 정책연구과제 연구자 공모한국사학진흥재단(이사장 김혜천, 이하 ‘케프’)은 1월 29일부터 2015년도 1차 정책연구과제 연구자 공모를 실시하였다./html/mimevalue_image/2015-01-29/nl_news_title_20150129132118192033_1.JPGsahak012015-01-29sahak012015-01-297575
5105제49대 이광구 우리은행장, 한국사학진흥재단 이사장 예방한국사학진흥재단(이사장 김혜천, 이하 ‘케프’)은 지난해 12. 30. 제49대 우리은행장으로 취임한 이광구 은행장이 1. 29.(목)에 이사장을 예방하였다고 밝혔다./html/mimevalue_image/2015-02-03/nl_news_title_20150203171924980054_1.JPGsahak012015-02-03<NA><NA>00
61302015년 국회정책토론회(사학진흥포럼) 개최결과케프는 6.29(월) 윤재옥 국회의원과 함께 "대학재정회계 투명성 제고 방향과 과제"라는 주제로100여명의 관계자들이 참석한 가운데 사학진흥포럼을 성공적으로 개최했습니다./html/mimevalue_image/2015-06-30/nl_news_title_20150630173630176139_1.JPGsahak012015-06-30sahak012015-06-308585
7127파리국제대학촌 한국관 설계업체 선정지난 6월 10일(수) 교육부와 한국사학진흥재단(이사장 김혜천)은 파리 국제대학촌 내 한국관 건립을 맡을 업체로 인사동 쌈지길 설계자 연세대최문규 건축가가 참여한 설계·감리업체를 최종 선정했다./html/mimevalue_image/2015-06-12/nl_news_title_20150612140636833004_1.jpgsahak012015-06-12sahak012015-06-124646
81362015년도 8월 전문가양성과정 및 KFPP-e러닝 교육과정 개최에 따른 신청 안내한국사학진흥재단(이사장 김혜천, 이하 ‘재단’)은 사립교육의 부흥과 도약, 내실화를 위해 2015년 8월 전문가양성과정 및 KFPP-e러닝(사이버연수)을 개최한다./html/mimevalue_image/2015-07-22/nl_news_title_20150722112635039020_1.JPGsahak012015-07-22<NA><NA>8686
91562015년 제 2차 사립대학 경영진 충청지역 간담회 성황리 개최한국사학진흥재단(이사장 김혜천, 이하 ‘케프’)은 21일(수) 충청지역 사립대학 총장 및 부총장을 대상으로 재단의 역할을 찾아 소통하고대학 발전에 도움이 되는 기관으로 거듭나고자 제 2차 사립대학 경영진 간담회를 개최하였다./html/mimevalue_image/2015-10-22/nl_news_title_20151022111455088028_1.jpgsahak012015-10-22sahak012015-10-22170170
기사번호기사이름기사 요약파일명등록자아이디등록일자수정자아이디수정일자클릭된횟수메일읽은횟수
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