Overview

Dataset statistics

Number of variables4
Number of observations112
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory35.2 B

Variable types

Numeric2
Text1
DateTime1

Dataset

Description국민연금공단이 해당 분기 동안 자본시장과 금융투자업에 관한 법률 등에 따라 보고 사유(5% 이상 지분율 신규취득 및 5% 이상 지분율 취득 이후 1% 이상 변동)가 발생하여 전자공시시스템(DART)에 보고한 내역으로, 보고 전일까지의 변동 내역이 포함되어 해당 분기가 아닌 보고내역이 포함되어 있을 수 있음
Author국민연금공단
URLhttps://www.data.go.kr/data/15106890/fileData.do

Alerts

번호 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:21:11.935160
Analysis finished2024-04-06 08:21:13.651138
Duration1.72 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct112
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.5
Minimum1
Maximum112
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:21:13.798861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.55
Q128.75
median56.5
Q384.25
95-th percentile106.45
Maximum112
Range111
Interquartile range (IQR)55.5

Descriptive statistics

Standard deviation32.475632
Coefficient of variation (CV)0.57478994
Kurtosis-1.2
Mean56.5
Median Absolute Deviation (MAD)28
Skewness0
Sum6328
Variance1054.6667
MonotonicityStrictly increasing
2024-04-06T17:21:14.098696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
58 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
Other values (102) 102
91.1%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
Distinct108
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-04-06T17:21:14.604455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length7.4732143
Min length2

Characters and Unicode

Total characters837
Distinct characters189
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)92.9%

Sample

1st row한화오션
2nd row에스케이디스커버리(주)
3rd row한화솔루션(주)
4th row금호석유화학(주)
5th row한화에어로스페이스(주)
ValueCountFrequency (%)
한화오션 2
 
1.8%
레고켐바이오사이언스 2
 
1.8%
한화솔루션(주 2
 
1.8%
주)아프리카티비 2
 
1.8%
주식회사 2
 
1.8%
대한유화(주 1
 
0.9%
삼익thk(주 1
 
0.9%
삼양식품(주 1
 
0.9%
멕아이씨에스 1
 
0.9%
롯데지주(주 1
 
0.9%
Other values (99) 99
86.8%
2024-04-06T17:21:15.557163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84
 
10.0%
) 80
 
9.6%
( 80
 
9.6%
40
 
4.8%
34
 
4.1%
25
 
3.0%
12
 
1.4%
12
 
1.4%
12
 
1.4%
10
 
1.2%
Other values (179) 448
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 645
77.1%
Close Punctuation 80
 
9.6%
Open Punctuation 80
 
9.6%
Uppercase Letter 27
 
3.2%
Space Separator 2
 
0.2%
Lowercase Letter 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
84
 
13.0%
40
 
6.2%
34
 
5.3%
25
 
3.9%
12
 
1.9%
12
 
1.9%
12
 
1.9%
10
 
1.6%
9
 
1.4%
9
 
1.4%
Other values (161) 398
61.7%
Uppercase Letter
ValueCountFrequency (%)
S 6
22.2%
K 4
14.8%
L 4
14.8%
H 2
 
7.4%
C 2
 
7.4%
T 2
 
7.4%
D 2
 
7.4%
O 1
 
3.7%
J 1
 
3.7%
N 1
 
3.7%
Other values (2) 2
 
7.4%
Lowercase Letter
ValueCountFrequency (%)
i 1
50.0%
l 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 80
100.0%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 645
77.1%
Common 163
 
19.5%
Latin 29
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
84
 
13.0%
40
 
6.2%
34
 
5.3%
25
 
3.9%
12
 
1.9%
12
 
1.9%
12
 
1.9%
10
 
1.6%
9
 
1.4%
9
 
1.4%
Other values (161) 398
61.7%
Latin
ValueCountFrequency (%)
S 6
20.7%
K 4
13.8%
L 4
13.8%
H 2
 
6.9%
C 2
 
6.9%
T 2
 
6.9%
D 2
 
6.9%
O 1
 
3.4%
i 1
 
3.4%
l 1
 
3.4%
Other values (4) 4
13.8%
Common
ValueCountFrequency (%)
) 80
49.1%
( 80
49.1%
2
 
1.2%
- 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 645
77.1%
ASCII 192
 
22.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
84
 
13.0%
40
 
6.2%
34
 
5.3%
25
 
3.9%
12
 
1.9%
12
 
1.9%
12
 
1.9%
10
 
1.6%
9
 
1.4%
9
 
1.4%
Other values (161) 398
61.7%
ASCII
ValueCountFrequency (%)
) 80
41.7%
( 80
41.7%
S 6
 
3.1%
K 4
 
2.1%
L 4
 
2.1%
H 2
 
1.0%
C 2
 
1.0%
T 2
 
1.0%
D 2
 
1.0%
2
 
1.0%
Other values (8) 8
 
4.2%
Distinct46
Distinct (%)41.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum2023-10-04 00:00:00
Maximum2024-01-04 00:00:00
2024-04-06T17:21:15.911546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:16.232027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

지분율(퍼센트)
Real number (ℝ)

Distinct96
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3784821
Minimum2.49
Maximum13.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:21:16.541714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.49
5-th percentile3.99
Q15.1075
median7.195
Q39.27
95-th percentile11.8735
Maximum13.71
Range11.22
Interquartile range (IQR)4.1625

Descriptive statistics

Standard deviation2.5571526
Coefficient of variation (CV)0.34656892
Kurtosis-0.76060273
Mean7.3784821
Median Absolute Deviation (MAD)2.075
Skewness0.36851138
Sum826.39
Variance6.5390292
MonotonicityNot monotonic
2024-04-06T17:21:16.860125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.01 5
 
4.5%
9.27 3
 
2.7%
5.03 3
 
2.7%
4.02 2
 
1.8%
7.25 2
 
1.8%
5.0 2
 
1.8%
9.09 2
 
1.8%
6.02 2
 
1.8%
3.99 2
 
1.8%
8.29 2
 
1.8%
Other values (86) 87
77.7%
ValueCountFrequency (%)
2.49 1
0.9%
3.01 1
0.9%
3.65 1
0.9%
3.66 1
0.9%
3.96 1
0.9%
3.99 2
1.8%
4.0 1
0.9%
4.01 1
0.9%
4.02 2
1.8%
4.06 1
0.9%
ValueCountFrequency (%)
13.71 1
0.9%
12.72 1
0.9%
12.1 1
0.9%
12.09 1
0.9%
12.02 1
0.9%
11.89 1
0.9%
11.86 1
0.9%
11.53 2
1.8%
11.28 1
0.9%
11.22 1
0.9%

Interactions

2024-04-06T17:21:12.756539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:12.320028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:12.987104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:12.538878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:21:17.072491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호보고서 작성기준일지분율(퍼센트)
번호1.0000.3920.250
보고서 작성기준일0.3921.0000.342
지분율(퍼센트)0.2500.3421.000
2024-04-06T17:21:17.240027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지분율(퍼센트)
번호1.0000.128
지분율(퍼센트)0.1281.000

Missing values

2024-04-06T17:21:13.252717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:21:13.581745image/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

번호발행기관명보고서 작성기준일지분율(퍼센트)
01한화오션2023-10-236.1
12에스케이디스커버리(주)2023-10-255.0
23한화솔루션(주)2023-10-047.25
34금호석유화학(주)2023-10-239.27
45한화에어로스페이스(주)2023-10-068.1
56(주)와이지엔터테인먼트2023-10-125.78
67포스코홀딩스2023-11-096.71
78지에스건설(주)2023-11-247.41
89한화오션2023-11-285.01
910(주)아프리카티비2023-11-167.57
번호발행기관명보고서 작성기준일지분율(퍼센트)
102103티와이홀딩스2023-11-164.24
103104티케이지휴켐스2023-12-2210.17
104105파미셀(주)2023-12-144.06
105106피엔에이치테크2023-10-316.11
106107하이록코리아(주)2023-10-248.31
107108한미약품(주)2023-10-1010.98
108109한올바이오파마(주)2023-11-0811.53
109110해성디에스(주)2024-01-029.33
110111효성중공업2023-12-2811.21
111112효성화학2023-11-154.61