Overview

Dataset statistics

Number of variables7
Number of observations132
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.6 KiB
Average record size in memory59.0 B

Variable types

Numeric2
Text2
Categorical3

Dataset

DescriptionKOTRA에서 개최한 설명회 연사 발표자료집 목록입니다. 자료명과 담당부서, 발간자료번호, 발간년도 등을 확인하실 수 있습니다.
Author대한무역투자진흥공사
URLhttps://www.data.go.kr/data/15044295/fileData.do

Alerts

내용 has constant value ""Constant
데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 발간년도High correlation
발간년도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
담당부서 is highly overall correlated with 발간년도High correlation
연번 has unique valuesUnique
발간자료번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:33:10.298180
Analysis finished2023-12-12 00:33:11.018044
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct132
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.5
Minimum1
Maximum132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T09:33:11.084427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.55
Q133.75
median66.5
Q399.25
95-th percentile125.45
Maximum132
Range131
Interquartile range (IQR)65.5

Descriptive statistics

Standard deviation38.249183
Coefficient of variation (CV)0.57517568
Kurtosis-1.2
Mean66.5
Median Absolute Deviation (MAD)33
Skewness0
Sum8778
Variance1463
MonotonicityStrictly increasing
2023-12-12T09:33:11.219959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
85 1
 
0.8%
99 1
 
0.8%
98 1
 
0.8%
97 1
 
0.8%
96 1
 
0.8%
95 1
 
0.8%
94 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
Other values (122) 122
92.4%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
132 1
0.8%
131 1
0.8%
130 1
0.8%
129 1
0.8%
128 1
0.8%
127 1
0.8%
126 1
0.8%
125 1
0.8%
124 1
0.8%
123 1
0.8%

자료명
Text

Distinct129
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T09:33:11.557155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length97
Median length55
Mean length36.416667
Min length11

Characters and Unicode

Total characters4807
Distinct characters358
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)96.2%

Sample

1st row2017 KOTRA 세계시장 진출전략 설명회
2nd row2017 中·美 시장 진출확대 설명회
3rd row이란 KSP 투자진출 세미나
4th row쿠바 KSP 투자진출 세미나
5th row제1차 한류콘텐츠 간접광고(PPL) 활용 상담회 : 매칭 페어
ValueCountFrequency (%)
56
 
5.6%
설명회 35
 
3.5%
2019 27
 
2.7%
세미나 23
 
2.3%
global 21
 
2.1%
project 20
 
2.0%
plaza 19
 
1.9%
kotra 19
 
1.9%
글로벌 18
 
1.8%
2017 18
 
1.8%
Other values (420) 739
74.3%
2023-12-12T09:33:12.032727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
864
 
18.0%
2 104
 
2.2%
a 98
 
2.0%
e 95
 
2.0%
0 92
 
1.9%
o 90
 
1.9%
r 77
 
1.6%
1 76
 
1.6%
l 73
 
1.5%
n 73
 
1.5%
Other values (348) 3165
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2049
42.6%
Lowercase Letter 896
18.6%
Space Separator 864
18.0%
Uppercase Letter 461
 
9.6%
Decimal Number 358
 
7.4%
Other Punctuation 120
 
2.5%
Close Punctuation 16
 
0.3%
Open Punctuation 16
 
0.3%
Dash Punctuation 14
 
0.3%
Math Symbol 13
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 57
 
2.8%
설 47
 
2.3%
출 46
 
2.2%
세 45
 
2.2%
로 44
 
2.1%
명 40
 
2.0%
미 39
 
1.9%
시 39
 
1.9%
외 38
 
1.9%
수 38
 
1.9%
Other values (272) 1616
78.9%
Lowercase Letter
ValueCountFrequency (%)
a 98
10.9%
e 95
10.6%
o 90
10.0%
r 77
 
8.6%
l 73
 
8.1%
n 73
 
8.1%
t 65
 
7.3%
i 49
 
5.5%
b 32
 
3.6%
c 31
 
3.5%
Other values (16) 213
23.8%
Uppercase Letter
ValueCountFrequency (%)
P 66
14.3%
K 46
 
10.0%
A 43
 
9.3%
G 33
 
7.2%
T 32
 
6.9%
O 29
 
6.3%
R 28
 
6.1%
S 26
 
5.6%
E 19
 
4.1%
D 18
 
3.9%
Other values (14) 121
26.2%
Decimal Number
ValueCountFrequency (%)
2 104
29.1%
0 92
25.7%
1 76
21.2%
9 33
 
9.2%
7 21
 
5.9%
8 15
 
4.2%
3 8
 
2.2%
5 4
 
1.1%
4 3
 
0.8%
6 2
 
0.6%
Other Punctuation
ValueCountFrequency (%)
: 41
34.2%
, 28
23.3%
· 21
17.5%
. 16
 
13.3%
/ 4
 
3.3%
! 3
 
2.5%
' 3
 
2.5%
? 3
 
2.5%
& 1
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 14
87.5%
] 2
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 14
87.5%
[ 2
 
12.5%
Space Separator
ValueCountFrequency (%)
864
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Math Symbol
ValueCountFrequency (%)
= 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2044
42.5%
Common 1401
29.1%
Latin 1357
28.2%
Han 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 57
 
2.8%
설 47
 
2.3%
출 46
 
2.3%
세 45
 
2.2%
로 44
 
2.2%
명 40
 
2.0%
미 39
 
1.9%
시 39
 
1.9%
외 38
 
1.9%
수 38
 
1.9%
Other values (269) 1611
78.8%
Latin
ValueCountFrequency (%)
a 98
 
7.2%
e 95
 
7.0%
o 90
 
6.6%
r 77
 
5.7%
l 73
 
5.4%
n 73
 
5.4%
P 66
 
4.9%
t 65
 
4.8%
i 49
 
3.6%
K 46
 
3.4%
Other values (40) 625
46.1%
Common
ValueCountFrequency (%)
864
61.7%
2 104
 
7.4%
0 92
 
6.6%
1 76
 
5.4%
: 41
 
2.9%
9 33
 
2.4%
, 28
 
2.0%
7 21
 
1.5%
· 21
 
1.5%
. 16
 
1.1%
Other values (16) 105
 
7.5%
Han
ValueCountFrequency (%)
中 2
40.0%
美 2
40.0%
企 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2737
56.9%
Hangul 2044
42.5%
None 21
 
0.4%
CJK 5
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
864
31.6%
2 104
 
3.8%
a 98
 
3.6%
e 95
 
3.5%
0 92
 
3.4%
o 90
 
3.3%
r 77
 
2.8%
1 76
 
2.8%
l 73
 
2.7%
n 73
 
2.7%
Other values (65) 1095
40.0%
Hangul
ValueCountFrequency (%)
회 57
 
2.8%
설 47
 
2.3%
출 46
 
2.3%
세 45
 
2.2%
로 44
 
2.2%
명 40
 
2.0%
미 39
 
1.9%
시 39
 
1.9%
외 38
 
1.9%
수 38
 
1.9%
Other values (269) 1611
78.8%
None
ValueCountFrequency (%)
· 21
100.0%
CJK
ValueCountFrequency (%)
中 2
40.0%
美 2
40.0%
企 1
20.0%

담당부서
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
프로젝트공공조달팀
22 
시장조사팀
11 
통상지원팀
10 
개발협력팀
 
6
투자MnA팀
 
6
Other values (40)
77 

Length

Max length11
Median length9
Mean length6.3257576
Min length3

Unique

Unique19 ?
Unique (%)14.4%

Sample

1st row동향분석팀
2nd row시장조사팀
3rd row개발협력팀
4th row개발협력팀
5th row콘텐츠융합팀

Common Values

ValueCountFrequency (%)
프로젝트공공조달팀 22
 
16.7%
시장조사팀 11
 
8.3%
통상지원팀 10
 
7.6%
개발협력팀 6
 
4.5%
투자MnA팀 6
 
4.5%
플랜트팀 5
 
3.8%
고객서비스실 4
 
3.0%
공공조달팀 4
 
3.0%
시장정보팀 4
 
3.0%
통상협력실 4
 
3.0%
Other values (35) 56
42.4%

Length

2023-12-12T09:33:12.177246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
프로젝트공공조달팀 22
 
16.5%
시장조사팀 11
 
8.3%
통상지원팀 10
 
7.5%
개발협력팀 6
 
4.5%
투자mna팀 6
 
4.5%
플랜트팀 5
 
3.8%
고객서비스실 4
 
3.0%
공공조달팀 4
 
3.0%
시장정보팀 4
 
3.0%
통상협력실 4
 
3.0%
Other values (36) 57
42.9%

발간자료번호
Text

UNIQUE 

Distinct132
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T09:33:12.447941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters1452
Distinct characters16
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

Unique132 ?
Unique (%)100.0%

Sample

1st row설명회자료17-001
2nd row설명회자료17-002
3rd row설명회자료17-003
4th row설명회자료17-004
5th row설명회자료17-005
ValueCountFrequency (%)
설명회자료17-001 1
 
0.8%
설명회자료19-016 1
 
0.8%
설명회자료19-031 1
 
0.8%
설명회자료19-030 1
 
0.8%
설명회자료19-029 1
 
0.8%
설명회자료19-028 1
 
0.8%
설명회자료19-027 1
 
0.8%
설명회자료19-026 1
 
0.8%
설명회자료19-025 1
 
0.8%
설명회자료19-024 1
 
0.8%
Other values (122) 122
92.4%
2023-12-12T09:33:12.829292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 194
13.4%
1 171
11.8%
설 132
9.1%
명 132
9.1%
회 132
9.1%
자 132
9.1%
료 132
9.1%
- 132
9.1%
2 66
 
4.5%
9 56
 
3.9%
Other values (6) 173
11.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 660
45.5%
Other Letter 660
45.5%
Dash Punctuation 132
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 194
29.4%
1 171
25.9%
2 66
 
10.0%
9 56
 
8.5%
7 52
 
7.9%
8 40
 
6.1%
3 34
 
5.2%
4 20
 
3.0%
5 14
 
2.1%
6 13
 
2.0%
Other Letter
ValueCountFrequency (%)
설 132
20.0%
명 132
20.0%
회 132
20.0%
자 132
20.0%
료 132
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 792
54.5%
Hangul 660
45.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 194
24.5%
1 171
21.6%
- 132
16.7%
2 66
 
8.3%
9 56
 
7.1%
7 52
 
6.6%
8 40
 
5.1%
3 34
 
4.3%
4 20
 
2.5%
5 14
 
1.8%
Hangul
ValueCountFrequency (%)
설 132
20.0%
명 132
20.0%
회 132
20.0%
자 132
20.0%
료 132
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 792
54.5%
Hangul 660
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 194
24.5%
1 171
21.6%
- 132
16.7%
2 66
 
8.3%
9 56
 
7.1%
7 52
 
6.6%
8 40
 
5.1%
3 34
 
4.3%
4 20
 
2.5%
5 14
 
1.8%
Hangul
ValueCountFrequency (%)
설 132
20.0%
명 132
20.0%
회 132
20.0%
자 132
20.0%
료 132
20.0%

발간년도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.4621
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T09:33:12.953903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12017
median2018
Q32019
95-th percentile2021
Maximum2022
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.2805372
Coefficient of variation (CV)0.00063441232
Kurtosis-0.12142325
Mean2018.4621
Median Absolute Deviation (MAD)1
Skewness0.65029193
Sum266437
Variance1.6397756
MonotonicityIncreasing
2023-12-12T09:33:13.047656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2019 45
34.1%
2017 39
29.5%
2018 28
21.2%
2021 11
 
8.3%
2020 7
 
5.3%
2022 2
 
1.5%
ValueCountFrequency (%)
2017 39
29.5%
2018 28
21.2%
2019 45
34.1%
2020 7
 
5.3%
2021 11
 
8.3%
2022 2
 
1.5%
ValueCountFrequency (%)
2022 2
 
1.5%
2021 11
 
8.3%
2020 7
 
5.3%
2019 45
34.1%
2018 28
21.2%
2017 39
29.5%

내용
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
표제 행사 연사 발표자료집
132 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row표제 행사 연사 발표자료집
2nd row표제 행사 연사 발표자료집
3rd row표제 행사 연사 발표자료집
4th row표제 행사 연사 발표자료집
5th row표제 행사 연사 발표자료집

Common Values

ValueCountFrequency (%)
표제 행사 연사 발표자료집 132
100.0%

Length

2023-12-12T09:33:13.147954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:33:13.237801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
표제 132
25.0%
행사 132
25.0%
연사 132
25.0%
발표자료집 132
25.0%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2022-06-30
132 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-06-30
2nd row2022-06-30
3rd row2022-06-30
4th row2022-06-30
5th row2022-06-30

Common Values

ValueCountFrequency (%)
2022-06-30 132
100.0%

Length

2023-12-12T09:33:13.324570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:33:13.424970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-06-30 132
100.0%

Interactions

2023-12-12T09:33:10.706059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:10.558994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:10.783128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:10.633167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:33:13.481314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번담당부서발간년도
연번1.0000.8150.838
담당부서0.8151.0000.884
발간년도0.8380.8841.000
2023-12-12T09:33:13.563059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번발간년도담당부서
연번1.0000.9610.365
발간년도0.9611.0000.551
담당부서0.3650.5511.000

Missing values

2023-12-12T09:33:10.880757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:33:10.977462image/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

연번자료명담당부서발간자료번호발간년도내용데이터기준일
012017 KOTRA 세계시장 진출전략 설명회동향분석팀설명회자료17-0012017표제 행사 연사 발표자료집2022-06-30
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