Overview

Dataset statistics

Number of variables5
Number of observations127
Missing cells2
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory42.0 B

Variable types

DateTime1
Categorical1
Text2
Numeric1

Dataset

DescriptionAPEC 21개 회원국과 구축된 네트워크를 기반으로 우리 기관 및 중소기업의 글로벌화 지원 및 산업협력기회 창출목적으로 구축된 APEC 중소기업혁신센터 홈페이지의 Archive 게시판에 등록 자료 정보
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15071261/fileData.do

Reproduction

Analysis started2023-12-12 20:30:28.778428
Analysis finished2023-12-12 20:30:29.431969
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록일
Date

Distinct39
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2011-05-02 00:00:00
Maximum2022-12-06 00:00:00
2023-12-13T05:30:29.518672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:30:29.694526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)

구분
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Archive
94 
News Room
33 

Length

Max length9
Median length7
Mean length7.519685
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Archive 94
74.0%
News Room 33
 
26.0%

Length

2023-12-13T05:30:29.850418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:30:29.998982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
archive 94
58.8%
news 33
 
20.6%
room 33
 
20.6%

제목
Text

Distinct114
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T05:30:30.276211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length88
Median length70
Mean length51.102362
Min length9

Characters and Unicode

Total characters6490
Distinct characters68
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)81.1%

Sample

1st row2022 APEC SME Innovation Forum with ESG Business Strategy _Pathom Chaiyapruksaton
2nd row2022 APEC SME Innovation Forum with ESG Business Strategy _Park SooWon
3rd row2022 APEC SME Innovation Forum with ESG Business Strategy _Shin SukHo
4th row2022 APEC SME Innovation Forum with ESG Business Strategy _Jirarot Pojanavaraphan
5th row2022 APEC SME Innovation Forum with ESG Business Strategy_Lim Wee Fong
ValueCountFrequency (%)
apec 77
 
8.4%
green 49
 
5.4%
workshop 46
 
5.0%
initiative 35
 
3.8%
sme 32
 
3.5%
innovation 30
 
3.3%
with 29
 
3.2%
business 29
 
3.2%
forum 23
 
2.5%
the 16
 
1.8%
Other values (258) 547
59.9%
2023-12-13T05:30:30.784674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
793
 
12.2%
e 461
 
7.1%
n 448
 
6.9%
i 411
 
6.3%
o 353
 
5.4%
r 308
 
4.7%
t 300
 
4.6%
a 297
 
4.6%
s 259
 
4.0%
E 184
 
2.8%
Other values (58) 2676
41.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3872
59.7%
Uppercase Letter 1338
 
20.6%
Space Separator 793
 
12.2%
Decimal Number 375
 
5.8%
Connector Punctuation 89
 
1.4%
Dash Punctuation 12
 
0.2%
Other Punctuation 9
 
0.1%
Final Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 184
13.8%
C 156
11.7%
S 140
10.5%
P 117
8.7%
A 106
7.9%
M 105
7.8%
I 94
 
7.0%
G 79
 
5.9%
W 59
 
4.4%
B 49
 
3.7%
Other values (16) 249
18.6%
Lowercase Letter
ValueCountFrequency (%)
e 461
11.9%
n 448
11.6%
i 411
10.6%
o 353
9.1%
r 308
8.0%
t 300
 
7.7%
a 297
 
7.7%
s 259
 
6.7%
h 142
 
3.7%
u 133
 
3.4%
Other values (15) 760
19.6%
Decimal Number
ValueCountFrequency (%)
2 160
42.7%
0 95
25.3%
1 91
24.3%
9 11
 
2.9%
5 6
 
1.6%
7 3
 
0.8%
8 3
 
0.8%
3 3
 
0.8%
4 2
 
0.5%
6 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 5
55.6%
: 3
33.3%
& 1
 
11.1%
Space Separator
ValueCountFrequency (%)
793
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 89
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5210
80.3%
Common 1280
 
19.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 461
 
8.8%
n 448
 
8.6%
i 411
 
7.9%
o 353
 
6.8%
r 308
 
5.9%
t 300
 
5.8%
a 297
 
5.7%
s 259
 
5.0%
E 184
 
3.5%
C 156
 
3.0%
Other values (41) 2033
39.0%
Common
ValueCountFrequency (%)
793
62.0%
2 160
 
12.5%
0 95
 
7.4%
1 91
 
7.1%
_ 89
 
7.0%
- 12
 
0.9%
9 11
 
0.9%
5 6
 
0.5%
. 5
 
0.4%
7 3
 
0.2%
Other values (7) 15
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6488
> 99.9%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
793
 
12.2%
e 461
 
7.1%
n 448
 
6.9%
i 411
 
6.3%
o 353
 
5.4%
r 308
 
4.7%
t 300
 
4.6%
a 297
 
4.6%
s 259
 
4.0%
E 184
 
2.8%
Other values (57) 2674
41.2%
Punctuation
ValueCountFrequency (%)
’ 2
100.0%

파일명
Text

Distinct120
Distinct (%)95.2%
Missing1
Missing (%)0.8%
Memory size1.1 KiB
2023-12-13T05:30:31.092236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length122
Median length53
Mean length30.952381
Min length7

Characters and Unicode

Total characters3900
Distinct characters81
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)90.5%

Sample

1st rowPathom Chaiyapruksaton Profie Photo.jpg
2nd rowPark SooWonProfile Photo.jpg
3rd rowShin SukHo_ Profile Photo.jpg
4th rowJirarot Pojanavaraphan_지라랏 포자나바라판_ Profile Photo_0_.png
5th rowKim JuHern Profile Photo.jpg
ValueCountFrequency (%)
photo.jpg 17
 
4.1%
apec 15
 
3.6%
green 13
 
3.1%
profile 12
 
2.9%
sme 12
 
2.9%
7
 
1.7%
initiative 6
 
1.4%
2020 6
 
1.4%
cyber 6
 
1.4%
security 6
 
1.4%
Other values (271) 319
76.1%
2023-12-13T05:30:31.562781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
293
 
7.5%
e 212
 
5.4%
o 198
 
5.1%
i 194
 
5.0%
n 189
 
4.8%
. 163
 
4.2%
a 153
 
3.9%
p 151
 
3.9%
_ 149
 
3.8%
r 146
 
3.7%
Other values (71) 2052
52.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2092
53.6%
Uppercase Letter 804
 
20.6%
Decimal Number 331
 
8.5%
Space Separator 293
 
7.5%
Other Punctuation 168
 
4.3%
Connector Punctuation 149
 
3.8%
Dash Punctuation 44
 
1.1%
Other Letter 19
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 212
 
10.1%
o 198
 
9.5%
i 194
 
9.3%
n 189
 
9.0%
a 153
 
7.3%
p 151
 
7.2%
r 146
 
7.0%
t 141
 
6.7%
g 78
 
3.7%
s 76
 
3.6%
Other values (15) 554
26.5%
Uppercase Letter
ValueCountFrequency (%)
P 128
15.9%
G 73
 
9.1%
E 72
 
9.0%
A 68
 
8.5%
S 68
 
8.5%
C 65
 
8.1%
M 47
 
5.8%
I 40
 
5.0%
J 34
 
4.2%
R 24
 
3.0%
Other values (15) 185
23.0%
Other Letter
ValueCountFrequency (%)
라 3
15.8%
진 2
 
10.5%
단 2
 
10.5%
지 1
 
5.3%
사 1
 
5.3%
체 1
 
5.3%
나 1
 
5.3%
드 1
 
5.3%
바 1
 
5.3%
슬 1
 
5.3%
Other values (5) 5
26.3%
Decimal Number
ValueCountFrequency (%)
1 75
22.7%
0 75
22.7%
2 65
19.6%
3 24
 
7.3%
5 18
 
5.4%
7 17
 
5.1%
4 16
 
4.8%
8 15
 
4.5%
9 13
 
3.9%
6 13
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 163
97.0%
& 4
 
2.4%
@ 1
 
0.6%
Space Separator
ValueCountFrequency (%)
293
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2896
74.3%
Common 985
 
25.3%
Hangul 19
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 212
 
7.3%
o 198
 
6.8%
i 194
 
6.7%
n 189
 
6.5%
a 153
 
5.3%
p 151
 
5.2%
r 146
 
5.0%
t 141
 
4.9%
P 128
 
4.4%
g 78
 
2.7%
Other values (40) 1306
45.1%
Common
ValueCountFrequency (%)
293
29.7%
. 163
16.5%
_ 149
15.1%
1 75
 
7.6%
0 75
 
7.6%
2 65
 
6.6%
- 44
 
4.5%
3 24
 
2.4%
5 18
 
1.8%
7 17
 
1.7%
Other values (6) 62
 
6.3%
Hangul
ValueCountFrequency (%)
라 3
15.8%
진 2
 
10.5%
단 2
 
10.5%
지 1
 
5.3%
사 1
 
5.3%
체 1
 
5.3%
나 1
 
5.3%
드 1
 
5.3%
바 1
 
5.3%
슬 1
 
5.3%
Other values (5) 5
26.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3881
99.5%
Hangul 19
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
293
 
7.5%
e 212
 
5.5%
o 198
 
5.1%
i 194
 
5.0%
n 189
 
4.9%
. 163
 
4.2%
a 153
 
3.9%
p 151
 
3.9%
_ 149
 
3.8%
r 146
 
3.8%
Other values (56) 2033
52.4%
Hangul
ValueCountFrequency (%)
라 3
15.8%
진 2
 
10.5%
단 2
 
10.5%
지 1
 
5.3%
사 1
 
5.3%
체 1
 
5.3%
나 1
 
5.3%
드 1
 
5.3%
바 1
 
5.3%
슬 1
 
5.3%
Other values (5) 5
26.3%

파일크기
Real number (ℝ)

Distinct115
Distinct (%)91.3%
Missing1
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean2660425.3
Minimum9376
Maximum52415839
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T05:30:31.741084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9376
5-th percentile27797.5
Q1159869
median740826.5
Q32919433.2
95-th percentile8404932.5
Maximum52415839
Range52406463
Interquartile range (IQR)2759564.2

Descriptive statistics

Standard deviation5870789.4
Coefficient of variation (CV)2.2067109
Kurtosis45.636097
Mean2660425.3
Median Absolute Deviation (MAD)692698.5
Skewness6.05495
Sum3.3521358 × 108
Variance3.4466168 × 1013
MonotonicityNot monotonic
2023-12-13T05:30:31.916942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1191209 2
 
1.6%
6049330 2
 
1.6%
760493 2
 
1.6%
1093921 2
 
1.6%
48128 2
 
1.6%
1294208 2
 
1.6%
218155 2
 
1.6%
211968 2
 
1.6%
82623 2
 
1.6%
214109 2
 
1.6%
Other values (105) 106
83.5%
ValueCountFrequency (%)
9376 1
0.8%
10163 1
0.8%
13199 1
0.8%
17515 1
0.8%
19540 1
0.8%
22134 1
0.8%
27726 1
0.8%
28012 1
0.8%
29125 1
0.8%
29696 1
0.8%
ValueCountFrequency (%)
52415839 1
0.8%
31990735 1
0.8%
11589469 1
0.8%
11318979 1
0.8%
9626783 2
1.6%
8433858 1
0.8%
8318156 1
0.8%
7862870 1
0.8%
7823982 1
0.8%
7468228 1
0.8%

Interactions

2023-12-13T05:30:29.006616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:30:32.049068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록일구분파일크기
등록일1.0000.9200.163
구분0.9201.0000.000
파일크기0.1630.0001.000
2023-12-13T05:30:32.146099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
파일크기구분
파일크기1.0000.000
구분0.0001.000

Missing values

2023-12-13T05:30:29.127507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:30:29.252360image/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.
2023-12-13T05:30:29.367196image/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

등록일구분제목파일명파일크기
02022-12-06Archive2022 APEC SME Innovation Forum with ESG Business Strategy _Pathom ChaiyapruksatonPathom Chaiyapruksaton Profie Photo.jpg483101
12022-12-06Archive2022 APEC SME Innovation Forum with ESG Business Strategy _Park SooWonPark SooWonProfile Photo.jpg331909
22022-12-06Archive2022 APEC SME Innovation Forum with ESG Business Strategy _Shin SukHoShin SukHo_ Profile Photo.jpg210480
32022-12-06Archive2022 APEC SME Innovation Forum with ESG Business Strategy _Jirarot PojanavaraphanJirarot Pojanavaraphan_지라랏 포자나바라판_ Profile Photo_0_.png473063
42022-12-06Archive2022 APEC SME Innovation Forum with ESG Business Strategy_Lim Wee Fong<NA><NA>
52022-12-06Archive2022 APEC SME Innovation Forum with ESG Business Strategy_Kim JuHernKim JuHern Profile Photo.jpg39588
62022-12-06Archive2022 APEC SME Innovation Forum with ESG Business Strategy_LIU TingLIU Ting Profile Photo.jpg9376
72022-12-06Archive2022 APEC SME Innovation Forum with ESG Business Strategy_Kim YoungRokKim YoungRok Profile Photo.jpg167861
82022-12-06Archive2022 APEC SME Innovation Forum with ESG Business Strategy_Song KyungJinSong KyungJine Photo.jpg267743
92022-12-06Archive2022 APEC SME Innovation Forum with ESG Business Strategy_TERRAZOS AGUILAR Ana GeorginaTERRAZOS AGUILAR Ana Georgina Profile Photo.JPG39223
등록일구분제목파일명파일크기
1172011-11-21ArchiveGreen Initiative Interim ReportGreenInitiativeInterimReport.doc3674624
1182011-09-29News RoomInnovation Consulting for Peruvian SMEsP1010678.JPG157205
1192011-08-22News RoomAPEC SMEIC Completes Innovation Consulting in Indonesiaindonesia.jpg83006
1202011-06-08News RoomThe 18th APEC SME Ministerial Meeting in Montana02_SMEMM.jpg258200
1212011-06-03News RoomKorean Delegation Visits the US to Explore Areas of New Growth110603.jpg921654
1222011-05-02News RoomConference to Discuss Innovation as Growth Driver0125.JPG9626783
1232011-05-04ArchiveThe 2011 APEC SME Green Innovation Conference0125.JPG9626783
1242011-05-04ArchiveThe 2011 APEC SME Green Innovation Conference0024_0_.JPG11589469
1252011-05-04ArchiveThe 2011 APEC SME Green Innovation Conference0073.JPG7862870
1262011-05-04ArchiveThe 2011 APEC SME Green Innovation Conference0598.JPG11318979