Overview

Dataset statistics

Number of variables44
Number of observations52
Missing cells860
Missing cells (%)37.6%
Duplicate rows1
Duplicate rows (%)1.9%
Total size in memory19.0 KiB
Average record size in memory373.5 B

Variable types

Text13
Categorical24
Numeric3
Unsupported4

Dataset

Description샘플 데이터
Author나이스디앤비
URLhttps://kdx.kr/data/view/31236

Alerts

Dataset has 1 (1.9%) duplicate rowsDuplicates
뉴스식별번호 is highly imbalanced (55.8%)Imbalance
뉴스작성시간 is highly imbalanced (55.8%)Imbalance
법인번호 is highly imbalanced (52.2%)Imbalance
기업업태(대표) is highly imbalanced (51.6%)Imbalance
기업업태(상세) is highly imbalanced (51.6%)Imbalance
산업코드차수 is highly imbalanced (58.1%)Imbalance
산업대분류명 is highly imbalanced (55.0%)Imbalance
산업명 is highly imbalanced (55.0%)Imbalance
개인법인구분 is highly imbalanced (58.1%)Imbalance
종업원수기준일 is highly imbalanced (58.1%)Imbalance
주주기준일자 is highly imbalanced (56.6%)Imbalance
주주명1 is highly imbalanced (58.1%)Imbalance
주식비율1 is highly imbalanced (59.0%)Imbalance
주주명2 is highly imbalanced (59.0%)Imbalance
사업자등록번호 has 22 (42.3%) missing valuesMissing
언론사명 has 32 (61.5%) missing valuesMissing
뉴스제목 has 32 (61.5%) missing valuesMissing
뉴스요약 has 38 (73.1%) missing valuesMissing
뉴스작성자 has 42 (80.8%) missing valuesMissing
뉴스ESG관련도 has 42 (80.8%) missing valuesMissing
뉴스ESG스코어 has 42 (80.8%) missing valuesMissing
주요사업 has 48 (92.3%) missing valuesMissing
기업규모 has 48 (92.3%) missing valuesMissing
기업규모형태 has 48 (92.3%) missing valuesMissing
기업업종(대표) has 48 (92.3%) missing valuesMissing
산업대분류코드 has 42 (80.8%) missing valuesMissing
산업코드 has 42 (80.8%) missing valuesMissing
종업원수 has 42 (80.8%) missing valuesMissing
주주명3 has 42 (80.8%) missing valuesMissing
주식비율3 has 42 (80.8%) missing valuesMissing
결산일 has 52 (100.0%) missing valuesMissing
매출액 has 52 (100.0%) missing valuesMissing
영업이익 has 52 (100.0%) missing valuesMissing
Unnamed: 43 has 52 (100.0%) missing valuesMissing
결산일 is an unsupported type, check if it needs cleaning or further analysisUnsupported
매출액 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업이익 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 43 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주주명3 has 3 (5.8%) zerosZeros
주식비율3 has 3 (5.8%) zerosZeros

Reproduction

Analysis started2023-12-11 21:35:09.701743
Analysis finished2023-12-11 21:35:10.567137
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업자등록번호
Text

MISSING 

Distinct26
Distinct (%)86.7%
Missing22
Missing (%)42.3%
Memory size548.0 B
2023-12-12T06:35:10.791333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length137
Median length109
Mean length62.5
Min length10

Characters and Unicode

Total characters1875
Distinct characters327
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)76.7%

Sample

1st row2018******
2nd row두산밥캣(241560)은 1일(현지시간) 미국 노스캐롤라이나주에 있는 공장 1곳 가동을 4일부터, 미네소타·노스다코타주에 있는 공장 3곳 가동을 6일부터 각각 일시 중단한다고 밝혔다.
3rd row미국 공장 5곳 가운데 가장 규모가 작은 노스다코타주 와페튼 공장 1곳은 정상 가동한다.
4th row6098******
5th row정동익 현대증권 연구원은 "이번 수주는 국내 최초의 1000MW급 민자발전소 프로젝트에 핵심기기를 공급하는 건으로 향후 유사한 민자석탄 발전소용 주기기 수주입찰에서 유리한 고지를 선점했다"고 평가했다.
ValueCountFrequency (%)
4
 
1.0%
국내 4
 
1.0%
공장 4
 
1.0%
있는 4
 
1.0%
3988 3
 
0.7%
이번 3
 
0.7%
10 3
 
0.7%
밝혔다 3
 
0.7%
혜택을 2
 
0.5%
리조트 2
 
0.5%
Other values (349) 373
92.1%
2023-12-12T06:35:11.198516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
376
 
20.1%
* 60
 
3.2%
34
 
1.8%
31
 
1.7%
27
 
1.4%
. 25
 
1.3%
24
 
1.3%
22
 
1.2%
20
 
1.1%
20
 
1.1%
Other values (317) 1236
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1226
65.4%
Space Separator 376
 
20.1%
Other Punctuation 125
 
6.7%
Decimal Number 109
 
5.8%
Initial Punctuation 10
 
0.5%
Uppercase Letter 9
 
0.5%
Final Punctuation 7
 
0.4%
Open Punctuation 6
 
0.3%
Close Punctuation 6
 
0.3%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
34
 
2.8%
31
 
2.5%
27
 
2.2%
24
 
2.0%
22
 
1.8%
20
 
1.6%
20
 
1.6%
20
 
1.6%
19
 
1.5%
19
 
1.5%
Other values (284) 990
80.8%
Decimal Number
ValueCountFrequency (%)
0 19
17.4%
1 19
17.4%
8 16
14.7%
3 13
11.9%
2 13
11.9%
4 8
7.3%
5 7
 
6.4%
6 7
 
6.4%
9 6
 
5.5%
7 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
I 2
22.2%
P 1
11.1%
C 1
11.1%
B 1
11.1%
L 1
11.1%
O 1
11.1%
W 1
11.1%
M 1
11.1%
Other Punctuation
ValueCountFrequency (%)
* 60
48.0%
. 25
20.0%
, 13
 
10.4%
% 12
 
9.6%
" 8
 
6.4%
· 5
 
4.0%
' 2
 
1.6%
Initial Punctuation
ValueCountFrequency (%)
8
80.0%
2
 
20.0%
Final Punctuation
ValueCountFrequency (%)
5
71.4%
2
 
28.6%
Space Separator
ValueCountFrequency (%)
376
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1226
65.4%
Common 640
34.1%
Latin 9
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
34
 
2.8%
31
 
2.5%
27
 
2.2%
24
 
2.0%
22
 
1.8%
20
 
1.6%
20
 
1.6%
20
 
1.6%
19
 
1.5%
19
 
1.5%
Other values (284) 990
80.8%
Common
ValueCountFrequency (%)
376
58.8%
* 60
 
9.4%
. 25
 
3.9%
0 19
 
3.0%
1 19
 
3.0%
8 16
 
2.5%
, 13
 
2.0%
3 13
 
2.0%
2 13
 
2.0%
% 12
 
1.9%
Other values (15) 74
 
11.6%
Latin
ValueCountFrequency (%)
I 2
22.2%
P 1
11.1%
C 1
11.1%
B 1
11.1%
L 1
11.1%
O 1
11.1%
W 1
11.1%
M 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1226
65.4%
ASCII 627
33.4%
Punctuation 17
 
0.9%
None 5
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
376
60.0%
* 60
 
9.6%
. 25
 
4.0%
0 19
 
3.0%
1 19
 
3.0%
8 16
 
2.6%
, 13
 
2.1%
3 13
 
2.1%
2 13
 
2.1%
% 12
 
1.9%
Other values (18) 61
 
9.7%
Hangul
ValueCountFrequency (%)
34
 
2.8%
31
 
2.5%
27
 
2.2%
24
 
2.0%
22
 
1.8%
20
 
1.6%
20
 
1.6%
20
 
1.6%
19
 
1.5%
19
 
1.5%
Other values (284) 990
80.8%
Punctuation
ValueCountFrequency (%)
8
47.1%
5
29.4%
2
 
11.8%
2
 
11.8%
None
ValueCountFrequency (%)
· 5
100.0%

언론사명
Text

MISSING 

Distinct16
Distinct (%)80.0%
Missing32
Missing (%)61.5%
Memory size548.0 B
2023-12-12T06:35:11.353354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6.5
Mean length6.1
Min length3

Characters and Unicode

Total characters122
Distinct characters33
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)60.0%

Sample

1st row이데일리
2nd row8.97E+17
3rd row아시아경제
4th row3.23E+17
5th row아시아경제
ValueCountFrequency (%)
3.23e+17 2
 
10.0%
3.22e+17 2
 
10.0%
이데일리 2
 
10.0%
아시아경제 2
 
10.0%
kbs 1
 
5.0%
8.97e+17 1
 
5.0%
헤럴드경제 1
 
5.0%
3.84e+17 1
 
5.0%
한국경제v 1
 
5.0%
1.10e+18 1
 
5.0%
Other values (6) 6
30.0%
2023-12-12T06:35:11.584109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
 
13.1%
E 10
 
8.2%
+ 10
 
8.2%
. 10
 
8.2%
3 7
 
5.7%
7 7
 
5.7%
2 6
 
4.9%
8 6
 
4.9%
5
 
4.1%
5
 
4.1%
Other values (23) 40
32.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50
41.0%
Other Letter 38
31.1%
Uppercase Letter 14
 
11.5%
Math Symbol 10
 
8.2%
Other Punctuation 10
 
8.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
13.2%
5
13.2%
4
10.5%
4
10.5%
3
7.9%
3
7.9%
3
7.9%
2
 
5.3%
1
 
2.6%
1
 
2.6%
Other values (7) 7
18.4%
Decimal Number
ValueCountFrequency (%)
1 16
32.0%
3 7
14.0%
7 7
14.0%
2 6
 
12.0%
8 6
 
12.0%
0 4
 
8.0%
9 2
 
4.0%
6 1
 
2.0%
4 1
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
E 10
71.4%
V 1
 
7.1%
B 1
 
7.1%
S 1
 
7.1%
K 1
 
7.1%
Math Symbol
ValueCountFrequency (%)
+ 10
100.0%
Other Punctuation
ValueCountFrequency (%)
. 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
57.4%
Hangul 38
31.1%
Latin 14
 
11.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
13.2%
5
13.2%
4
10.5%
4
10.5%
3
7.9%
3
7.9%
3
7.9%
2
 
5.3%
1
 
2.6%
1
 
2.6%
Other values (7) 7
18.4%
Common
ValueCountFrequency (%)
1 16
22.9%
+ 10
14.3%
. 10
14.3%
3 7
10.0%
7 7
10.0%
2 6
 
8.6%
8 6
 
8.6%
0 4
 
5.7%
9 2
 
2.9%
6 1
 
1.4%
Latin
ValueCountFrequency (%)
E 10
71.4%
V 1
 
7.1%
B 1
 
7.1%
S 1
 
7.1%
K 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
68.9%
Hangul 38
31.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
19.0%
E 10
11.9%
+ 10
11.9%
. 10
11.9%
3 7
8.3%
7 7
8.3%
2 6
 
7.1%
8 6
 
7.1%
0 4
 
4.8%
9 2
 
2.4%
Other values (6) 6
 
7.1%
Hangul
ValueCountFrequency (%)
5
13.2%
5
13.2%
4
10.5%
4
10.5%
3
7.9%
3
7.9%
3
7.9%
2
 
5.3%
1
 
2.6%
1
 
2.6%
Other values (7) 7
18.4%

뉴스제목
Text

MISSING 

Distinct11
Distinct (%)55.0%
Missing32
Missing (%)61.5%
Memory size548.0 B
2023-12-12T06:35:11.794018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length34
Mean length18.75
Min length8

Characters and Unicode

Total characters375
Distinct characters144
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

Unique10 ?
Unique (%)50.0%

Sample

1st row두산밥캣, 코로나에 美공장 5곳 중 4곳 일시 가동중단
2nd row2.02E+13
3rd row"두산중공업, 올 1분기 누적수주액 1조5000억원 달성"
4th row2.02E+13
5th row신한카드, 스키장 10곳 할인·리조트 연계 이벤트 진행
ValueCountFrequency (%)
2.02e+13 10
 
12.8%
2
 
2.6%
예보 1
 
1.3%
포함 1
 
1.3%
18곳 1
 
1.3%
숏리스트에 1
 
1.3%
소수지분 1
 
1.3%
우리금융지주 1
 
1.3%
보유 1
 
1.3%
단독 1
 
1.3%
Other values (58) 58
74.4%
2023-12-12T06:35:12.082672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
59
 
15.7%
2 22
 
5.9%
1 17
 
4.5%
0 15
 
4.0%
. 11
 
2.9%
E 10
 
2.7%
+ 10
 
2.7%
3 10
 
2.7%
7
 
1.9%
, 6
 
1.6%
Other values (134) 208
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 195
52.0%
Decimal Number 69
 
18.4%
Space Separator 59
 
15.7%
Other Punctuation 27
 
7.2%
Uppercase Letter 10
 
2.7%
Math Symbol 10
 
2.7%
Open Punctuation 1
 
0.3%
Final Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7
 
3.6%
5
 
2.6%
5
 
2.6%
4
 
2.1%
4
 
2.1%
4
 
2.1%
4
 
2.1%
4
 
2.1%
4
 
2.1%
3
 
1.5%
Other values (112) 151
77.4%
Decimal Number
ValueCountFrequency (%)
2 22
31.9%
1 17
24.6%
0 15
21.7%
3 10
14.5%
5 2
 
2.9%
8 1
 
1.4%
4 1
 
1.4%
9 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 11
40.7%
, 6
22.2%
' 4
 
14.8%
" 2
 
7.4%
· 2
 
7.4%
2
 
7.4%
Space Separator
ValueCountFrequency (%)
59
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 10
100.0%
Math Symbol
ValueCountFrequency (%)
+ 10
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 193
51.5%
Common 170
45.3%
Latin 10
 
2.7%
Han 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7
 
3.6%
5
 
2.6%
5
 
2.6%
4
 
2.1%
4
 
2.1%
4
 
2.1%
4
 
2.1%
4
 
2.1%
4
 
2.1%
3
 
1.6%
Other values (110) 149
77.2%
Common
ValueCountFrequency (%)
59
34.7%
2 22
 
12.9%
1 17
 
10.0%
0 15
 
8.8%
. 11
 
6.5%
+ 10
 
5.9%
3 10
 
5.9%
, 6
 
3.5%
' 4
 
2.4%
" 2
 
1.2%
Other values (11) 14
 
8.2%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%
Latin
ValueCountFrequency (%)
E 10
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 193
51.5%
ASCII 174
46.4%
Punctuation 4
 
1.1%
None 2
 
0.5%
CJK 2
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
59
33.9%
2 22
 
12.6%
1 17
 
9.8%
0 15
 
8.6%
. 11
 
6.3%
E 10
 
5.7%
+ 10
 
5.7%
3 10
 
5.7%
, 6
 
3.4%
' 4
 
2.3%
Other values (8) 10
 
5.7%
Hangul
ValueCountFrequency (%)
7
 
3.6%
5
 
2.6%
5
 
2.6%
4
 
2.1%
4
 
2.1%
4
 
2.1%
4
 
2.1%
4
 
2.1%
4
 
2.1%
3
 
1.6%
Other values (110) 149
77.2%
None
ValueCountFrequency (%)
· 2
100.0%
Punctuation
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

뉴스요약
Text

MISSING 

Distinct14
Distinct (%)100.0%
Missing38
Missing (%)73.1%
Memory size548.0 B
2023-12-12T06:35:12.411965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length225
Median length77
Mean length63.714286
Min length3

Characters and Unicode

Total characters892
Distinct characters249
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)100.0%

Sample

1st row19일까지 2주가량 셧다운…1곳만 정상 가동 두산밥캣이 ‘코로나19’(신종 코로나바이러스 감염증) 확산한 데 따라 미국 공장 5곳 가운데 4곳 가동을 중단키로 했다.
2nd row경계*
3rd row최근 두산중공업은 대규모 수주 소식을 전하고 있다.
4th row이정*
5th row신한카드는 곤지암리조트, 비발디파크, 무주덕유산리조트, 용평리조트, 오크밸리리조트, 지산리조트, 엘리시안 강촌, 하이원리조트, 웰리힐리파크, 알페시아리조트 등 국내 10곳의 스키장과 제휴를 맺고 리프트·렌탈·강습 등 스키 관련 할인과 함께 리조트와 연계된 다양한 혜택을 제공하는 이벤트를 오는 29일부터 내년 2월까지 진행한다고 26일 밝혔다.
ValueCountFrequency (%)
관련 2
 
1.1%
2
 
1.1%
위한 2
 
1.1%
했다 2
 
1.1%
2
 
1.1%
위원장은 2
 
1.1%
있다 2
 
1.1%
예금보험공사(예보)가 1
 
0.5%
보유한 1
 
0.5%
중소기업·소상공인을 1
 
0.5%
Other values (170) 170
90.9%
2023-12-12T06:35:12.830481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
173
 
19.4%
20
 
2.2%
17
 
1.9%
16
 
1.8%
, 14
 
1.6%
13
 
1.5%
12
 
1.3%
12
 
1.3%
11
 
1.2%
11
 
1.2%
Other values (239) 593
66.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 628
70.4%
Space Separator 173
 
19.4%
Decimal Number 36
 
4.0%
Other Punctuation 34
 
3.8%
Close Punctuation 6
 
0.7%
Open Punctuation 6
 
0.7%
Initial Punctuation 3
 
0.3%
Final Punctuation 3
 
0.3%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20
 
3.2%
17
 
2.7%
16
 
2.5%
13
 
2.1%
12
 
1.9%
12
 
1.9%
11
 
1.8%
11
 
1.8%
9
 
1.4%
9
 
1.4%
Other values (214) 498
79.3%
Decimal Number
ValueCountFrequency (%)
1 9
25.0%
0 7
19.4%
9 5
13.9%
2 5
13.9%
3 3
 
8.3%
6 2
 
5.6%
4 2
 
5.6%
8 1
 
2.8%
5 1
 
2.8%
7 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 14
41.2%
. 10
29.4%
· 5
 
14.7%
* 4
 
11.8%
1
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
O 1
33.3%
I 1
33.3%
Initial Punctuation
ValueCountFrequency (%)
2
66.7%
1
33.3%
Final Punctuation
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
173
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 628
70.4%
Common 261
29.3%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20
 
3.2%
17
 
2.7%
16
 
2.5%
13
 
2.1%
12
 
1.9%
12
 
1.9%
11
 
1.8%
11
 
1.8%
9
 
1.4%
9
 
1.4%
Other values (214) 498
79.3%
Common
ValueCountFrequency (%)
173
66.3%
, 14
 
5.4%
. 10
 
3.8%
1 9
 
3.4%
0 7
 
2.7%
) 6
 
2.3%
( 6
 
2.3%
· 5
 
1.9%
9 5
 
1.9%
2 5
 
1.9%
Other values (12) 21
 
8.0%
Latin
ValueCountFrequency (%)
L 1
33.3%
O 1
33.3%
I 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 628
70.4%
ASCII 252
28.3%
Punctuation 7
 
0.8%
None 5
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
173
68.7%
, 14
 
5.6%
. 10
 
4.0%
1 9
 
3.6%
0 7
 
2.8%
) 6
 
2.4%
( 6
 
2.4%
9 5
 
2.0%
2 5
 
2.0%
* 4
 
1.6%
Other values (9) 13
 
5.2%
Hangul
ValueCountFrequency (%)
20
 
3.2%
17
 
2.7%
16
 
2.5%
13
 
2.1%
12
 
1.9%
12
 
1.9%
11
 
1.8%
11
 
1.8%
9
 
1.4%
9
 
1.4%
Other values (214) 498
79.3%
None
ValueCountFrequency (%)
· 5
100.0%
Punctuation
ValueCountFrequency (%)
2
28.6%
2
28.6%
1
14.3%
1
14.3%
1
14.3%

뉴스식별번호
Categorical

IMBALANCE 

Distinct4
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
U
G
 
1
S
 
1

Length

Max length4
Median length4
Mean length3.4230769
Min length1

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
U 8
 
15.4%
G 1
 
1.9%
S 1
 
1.9%

Length

2023-12-12T06:35:13.180264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:13.260753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
u 8
 
15.4%
g 1
 
1.9%
s 1
 
1.9%

뉴스작성시간
Categorical

IMBALANCE 

Distinct4
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
ESG아님
지배구조
 
1
사회
 
1

Length

Max length5
Median length4
Mean length4.1153846
Min length2

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
ESG아님 8
 
15.4%
지배구조 1
 
1.9%
사회 1
 
1.9%

Length

2023-12-12T06:35:13.354844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:13.438948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
esg아님 8
 
15.4%
지배구조 1
 
1.9%
사회 1
 
1.9%

뉴스작성자
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)80.0%
Missing42
Missing (%)80.8%
Infinite0
Infinite (%)0.0%
Mean0.9934
Minimum0.982
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T06:35:13.521704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.982
5-th percentile0.9829
Q10.98825
median0.9965
Q30.9985
95-th percentile1
Maximum1
Range0.018
Interquartile range (IQR)0.01025

Descriptive statistics

Standard deviation0.0067692113
Coefficient of variation (CV)0.006814185
Kurtosis-1.0609513
Mean0.9934
Median Absolute Deviation (MAD)0.0035
Skewness-0.76815537
Sum9.934
Variance4.5822222 × 10-5
MonotonicityNot monotonic
2023-12-12T06:35:13.607682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.997 2
 
3.8%
1.0 2
 
3.8%
0.982 1
 
1.9%
0.999 1
 
1.9%
0.987 1
 
1.9%
0.996 1
 
1.9%
0.984 1
 
1.9%
0.992 1
 
1.9%
(Missing) 42
80.8%
ValueCountFrequency (%)
0.982 1
1.9%
0.984 1
1.9%
0.987 1
1.9%
0.992 1
1.9%
0.996 1
1.9%
0.997 2
3.8%
0.999 1
1.9%
1.0 2
3.8%
ValueCountFrequency (%)
1.0 2
3.8%
0.999 1
1.9%
0.997 2
3.8%
0.996 1
1.9%
0.992 1
1.9%
0.987 1
1.9%
0.984 1
1.9%
0.982 1
1.9%

뉴스ESG분류
Categorical

Distinct3
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
1100000000000
2150000000000
 
2

Length

Max length13
Median length4
Mean length5.7307692
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
1100000000000 8
 
15.4%
2150000000000 2
 
3.8%

Length

2023-12-12T06:35:13.706216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:13.776378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
1100000000000 8
 
15.4%
2150000000000 2
 
3.8%

뉴스ESG관련도
Text

MISSING 

Distinct5
Distinct (%)50.0%
Missing42
Missing (%)80.8%
Memory size548.0 B
2023-12-12T06:35:13.857870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters30
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)30.0%

Sample

1st row진대*
2nd row유수*
3rd row손태*
4th row손태*
5th row손태*
ValueCountFrequency (%)
손태 5
50.0%
이휘 2
 
20.0%
진대 1
 
10.0%
유수 1
 
10.0%
홍종 1
 
10.0%
2023-12-12T06:35:14.045083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 10
33.3%
5
16.7%
5
16.7%
2
 
6.7%
2
 
6.7%
1
 
3.3%
1
 
3.3%
1
 
3.3%
1
 
3.3%
1
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20
66.7%
Other Punctuation 10
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
25.0%
5
25.0%
2
 
10.0%
2
 
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
* 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20
66.7%
Common 10
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
25.0%
5
25.0%
2
 
10.0%
2
 
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Common
ValueCountFrequency (%)
* 10
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20
66.7%
ASCII 10
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 10
100.0%
Hangul
ValueCountFrequency (%)
5
25.0%
5
25.0%
2
 
10.0%
2
 
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%

뉴스ESG스코어
Text

MISSING 

Distinct5
Distinct (%)50.0%
Missing42
Missing (%)80.8%
Memory size548.0 B
2023-12-12T06:35:14.194604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length40.5
Mean length19.1
Min length5

Characters and Unicode

Total characters191
Distinct characters47
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)30.0%

Sample

1st rowHBL 외
2nd row연료전지 및 신재생에너지 사업, 설비의 개발, 제조, 판매, 서비스업
3rd row경영관리에 관한 업무
4th row경영관리에 관한 업무
5th row경영관리에 관한 업무
ValueCountFrequency (%)
경영관리에 5
 
10.0%
업무 5
 
10.0%
관한 5
 
10.0%
3
 
6.0%
공구 2
 
4.0%
등의 2
 
4.0%
화학약품 2
 
4.0%
산소 2
 
4.0%
제조매매 2
 
4.0%
전기기기 2
 
4.0%
Other values (16) 20
40.0%
2023-12-12T06:35:14.464067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40
20.9%
, 16
 
8.4%
12
 
6.3%
8
 
4.2%
8
 
4.2%
6
 
3.1%
6
 
3.1%
5
 
2.6%
5
 
2.6%
5
 
2.6%
Other values (37) 80
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 132
69.1%
Space Separator 40
 
20.9%
Other Punctuation 16
 
8.4%
Uppercase Letter 3
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12
 
9.1%
8
 
6.1%
8
 
6.1%
6
 
4.5%
6
 
4.5%
5
 
3.8%
5
 
3.8%
5
 
3.8%
5
 
3.8%
5
 
3.8%
Other values (32) 67
50.8%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
B 1
33.3%
H 1
33.3%
Space Separator
ValueCountFrequency (%)
40
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 132
69.1%
Common 56
29.3%
Latin 3
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12
 
9.1%
8
 
6.1%
8
 
6.1%
6
 
4.5%
6
 
4.5%
5
 
3.8%
5
 
3.8%
5
 
3.8%
5
 
3.8%
5
 
3.8%
Other values (32) 67
50.8%
Latin
ValueCountFrequency (%)
L 1
33.3%
B 1
33.3%
H 1
33.3%
Common
ValueCountFrequency (%)
40
71.4%
, 16
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 132
69.1%
ASCII 59
30.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40
67.8%
, 16
 
27.1%
L 1
 
1.7%
B 1
 
1.7%
H 1
 
1.7%
Hangul
ValueCountFrequency (%)
12
 
9.1%
8
 
6.1%
8
 
6.1%
6
 
4.5%
6
 
4.5%
5
 
3.8%
5
 
3.8%
5
 
3.8%
5
 
3.8%
5
 
3.8%
Other values (32) 67
50.8%

법인번호
Categorical

IMBALANCE 

Distinct4
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
대기업
중견기업
 
3
중소기업
 
1

Length

Max length4
Median length4
Mean length3.8846154
Min length3

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
대기업 6
 
11.5%
중견기업 3
 
5.8%
중소기업 1
 
1.9%

Length

2023-12-12T06:35:14.569988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:14.647303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
대기업 6
 
11.5%
중견기업 3
 
5.8%
중소기업 1
 
1.9%

대표자
Categorical

Distinct3
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
거래소상장
코스닥등록
 
1

Length

Max length5
Median length4
Mean length4.1923077
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
거래소상장 9
 
17.3%
코스닥등록 1
 
1.9%

Length

2023-12-12T06:35:14.743003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:14.831320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
거래소상장 9
 
17.3%
코스닥등록 1
 
1.9%

주요사업
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing48
Missing (%)92.3%
Memory size548.0 B
2023-12-12T06:35:14.929694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length7.5
Mean length4.75
Min length2

Characters and Unicode

Total characters19
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row발광 다이오드 제조업
2nd row기타금융
3rd row강관
4th row강관
ValueCountFrequency (%)
강관 2
33.3%
발광 1
16.7%
다이오드 1
16.7%
제조업 1
16.7%
기타금융 1
16.7%
2023-12-12T06:35:15.129298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
 
10.5%
2
 
10.5%
2
 
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (6) 6
31.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17
89.5%
Space Separator 2
 
10.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
 
11.8%
2
 
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (5) 5
29.4%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17
89.5%
Common 2
 
10.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
 
11.8%
2
 
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (5) 5
29.4%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17
89.5%
ASCII 2
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2
 
11.8%
2
 
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (5) 5
29.4%
ASCII
ValueCountFrequency (%)
2
100.0%

기업규모
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing48
Missing (%)92.3%
Memory size548.0 B
2023-12-12T06:35:15.280729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length94
Median length49
Mean length25.5
Min length2

Characters and Unicode

Total characters102
Distinct characters45
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

Unique2 ?
Unique (%)50.0%

Sample

1st row건강 기능 식품 제조업/기타 식품 첨가물 제조업/동박 및 전지박 제조/발광 다이오드 제조업/사료 도매업/식물성 유지 제조업/의약용 화합물 및 항생물질 제조업/화장품 원료
2nd row기타금융
3rd row강관
4th row강관
ValueCountFrequency (%)
강관 2
 
8.7%
식품 2
 
8.7%
2
 
8.7%
제조업/사료 1
 
4.3%
원료 1
 
4.3%
제조업/화장품 1
 
4.3%
항생물질 1
 
4.3%
화합물 1
 
4.3%
제조업/의약용 1
 
4.3%
유지 1
 
4.3%
Other values (10) 10
43.5%
2023-12-12T06:35:15.529606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
18.6%
/ 7
 
6.9%
6
 
5.9%
6
 
5.9%
6
 
5.9%
4
 
3.9%
3
 
2.9%
3
 
2.9%
3
 
2.9%
3
 
2.9%
Other values (35) 42
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76
74.5%
Space Separator 19
 
18.6%
Other Punctuation 7
 
6.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6
 
7.9%
6
 
7.9%
6
 
7.9%
4
 
5.3%
3
 
3.9%
3
 
3.9%
3
 
3.9%
3
 
3.9%
2
 
2.6%
2
 
2.6%
Other values (33) 38
50.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76
74.5%
Common 26
 
25.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6
 
7.9%
6
 
7.9%
6
 
7.9%
4
 
5.3%
3
 
3.9%
3
 
3.9%
3
 
3.9%
3
 
3.9%
2
 
2.6%
2
 
2.6%
Other values (33) 38
50.0%
Common
ValueCountFrequency (%)
19
73.1%
/ 7
 
26.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76
74.5%
ASCII 26
 
25.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
73.1%
/ 7
 
26.9%
Hangul
ValueCountFrequency (%)
6
 
7.9%
6
 
7.9%
6
 
7.9%
4
 
5.3%
3
 
3.9%
3
 
3.9%
3
 
3.9%
3
 
3.9%
2
 
2.6%
2
 
2.6%
Other values (33) 38
50.0%

기업규모형태
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing48
Missing (%)92.3%
Memory size548.0 B
2023-12-12T06:35:15.621228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.75
Min length2

Characters and Unicode

Total characters11
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st row제조업
2nd row금융
3rd row제조업
4th row제조업
ValueCountFrequency (%)
제조업 3
75.0%
금융 1
 
25.0%
2023-12-12T06:35:15.829293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3
27.3%
3
27.3%
3
27.3%
1
 
9.1%
1
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
27.3%
3
27.3%
3
27.3%
1
 
9.1%
1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
27.3%
3
27.3%
3
27.3%
1
 
9.1%
1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3
27.3%
3
27.3%
3
27.3%
1
 
9.1%
1
 
9.1%

기업업종(대표)
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing48
Missing (%)92.3%
Memory size548.0 B
2023-12-12T06:35:15.980348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length94
Median length49
Mean length25.5
Min length2

Characters and Unicode

Total characters102
Distinct characters45
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

Unique2 ?
Unique (%)50.0%

Sample

1st row건강 기능 식품 제조업/기타 식품 첨가물 제조업/동박 및 전지박 제조/발광 다이오드 제조업/사료 도매업/식물성 유지 제조업/의약용 화합물 및 항생물질 제조업/화장품 원료
2nd row기타금융
3rd row강관
4th row강관
ValueCountFrequency (%)
강관 2
 
8.7%
식품 2
 
8.7%
2
 
8.7%
제조업/사료 1
 
4.3%
원료 1
 
4.3%
제조업/화장품 1
 
4.3%
항생물질 1
 
4.3%
화합물 1
 
4.3%
제조업/의약용 1
 
4.3%
유지 1
 
4.3%
Other values (10) 10
43.5%
2023-12-12T06:35:16.252281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
18.6%
/ 7
 
6.9%
6
 
5.9%
6
 
5.9%
6
 
5.9%
4
 
3.9%
3
 
2.9%
3
 
2.9%
3
 
2.9%
3
 
2.9%
Other values (35) 42
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76
74.5%
Space Separator 19
 
18.6%
Other Punctuation 7
 
6.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6
 
7.9%
6
 
7.9%
6
 
7.9%
4
 
5.3%
3
 
3.9%
3
 
3.9%
3
 
3.9%
3
 
3.9%
2
 
2.6%
2
 
2.6%
Other values (33) 38
50.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76
74.5%
Common 26
 
25.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6
 
7.9%
6
 
7.9%
6
 
7.9%
4
 
5.3%
3
 
3.9%
3
 
3.9%
3
 
3.9%
3
 
3.9%
2
 
2.6%
2
 
2.6%
Other values (33) 38
50.0%
Common
ValueCountFrequency (%)
19
73.1%
/ 7
 
26.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76
74.5%
ASCII 26
 
25.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
73.1%
/ 7
 
26.9%
Hangul
ValueCountFrequency (%)
6
 
7.9%
6
 
7.9%
6
 
7.9%
4
 
5.3%
3
 
3.9%
3
 
3.9%
3
 
3.9%
3
 
3.9%
2
 
2.6%
2
 
2.6%
Other values (33) 38
50.0%
Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
10
10 

Length

Max length4
Median length4
Mean length3.6153846
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
10 10
 
19.2%

Length

2023-12-12T06:35:16.356610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:16.436248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
10 10
 
19.2%

기업업태(대표)
Categorical

IMBALANCE 

Distinct4
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
K
C
 
4
D
 
1

Length

Max length4
Median length4
Mean length3.4230769
Min length1

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
K 5
 
9.6%
C 4
 
7.7%
D 1
 
1.9%

Length

2023-12-12T06:35:16.515634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:16.597455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
k 5
 
9.6%
c 4
 
7.7%
d 1
 
1.9%

기업업태(상세)
Categorical

IMBALANCE 

Distinct4
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
금융 및 보험업
제조업
 
4
전기, 가스, 증기 및 수도사업
 
1

Length

Max length17
Median length4
Mean length4.5576923
Min length3

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
금융 및 보험업 5
 
9.6%
제조업 4
 
7.7%
전기, 가스, 증기 및 수도사업 1
 
1.9%

Length

2023-12-12T06:35:16.684368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:16.766511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
63.6%
6
 
9.1%
금융 5
 
7.6%
보험업 5
 
7.6%
제조업 4
 
6.1%
전기 1
 
1.5%
가스 1
 
1.5%
증기 1
 
1.5%
수도사업 1
 
1.5%

산업코드차수
Categorical

IMBALANCE 

Distinct6
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
64992
24132
 
2
26121
 
1
35119
 
1

Length

Max length5
Median length4
Mean length4.1923077
Min length4

Unique

Unique3 ?
Unique (%)5.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
64992 5
 
9.6%
24132 2
 
3.8%
26121 1
 
1.9%
35119 1
 
1.9%
21200 1
 
1.9%

Length

2023-12-12T06:35:16.853909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:16.931233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
64992 5
 
9.6%
24132 2
 
3.8%
26121 1
 
1.9%
35119 1
 
1.9%
21200 1
 
1.9%

산업대분류코드
Text

MISSING 

Distinct5
Distinct (%)50.0%
Missing42
Missing (%)80.8%
Memory size548.0 B
2023-12-12T06:35:17.034362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.6
Min length4

Characters and Unicode

Total characters56
Distinct characters22
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)30.0%

Sample

1st row발광 다이오드 제조업
2nd row기타 발전업
3rd row지주회사
4th row지주회사
5th row지주회사
ValueCountFrequency (%)
지주회사 5
31.2%
제조업 4
25.0%
강관 2
 
12.5%
발광 1
 
6.2%
다이오드 1
 
6.2%
기타 1
 
6.2%
발전업 1
 
6.2%
의약품 1
 
6.2%
2023-12-12T06:35:17.253185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
10.7%
5
 
8.9%
5
 
8.9%
5
 
8.9%
5
 
8.9%
5
 
8.9%
4
 
7.1%
4
 
7.1%
2
 
3.6%
2
 
3.6%
Other values (12) 13
23.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50
89.3%
Space Separator 6
 
10.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
10.0%
5
10.0%
5
10.0%
5
10.0%
5
10.0%
4
 
8.0%
4
 
8.0%
2
 
4.0%
2
 
4.0%
2
 
4.0%
Other values (11) 11
22.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50
89.3%
Common 6
 
10.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
10.0%
5
10.0%
5
10.0%
5
10.0%
5
10.0%
4
 
8.0%
4
 
8.0%
2
 
4.0%
2
 
4.0%
2
 
4.0%
Other values (11) 11
22.0%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50
89.3%
ASCII 6
 
10.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
100.0%
Hangul
ValueCountFrequency (%)
5
10.0%
5
10.0%
5
10.0%
5
10.0%
5
10.0%
4
 
8.0%
4
 
8.0%
2
 
4.0%
2
 
4.0%
2
 
4.0%
Other values (11) 11
22.0%

산업대분류명
Categorical

IMBALANCE 

Distinct5
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
20190111
20191001
 
2
20180903
 
2
20180911
 
1

Length

Max length8
Median length4
Mean length4.7692308
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
20190111 5
 
9.6%
20191001 2
 
3.8%
20180903 2
 
3.8%
20180911 1
 
1.9%

Length

2023-12-12T06:35:17.367969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:17.454260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
20190111 5
 
9.6%
20191001 2
 
3.8%
20180903 2
 
3.8%
20180911 1
 
1.9%

산업코드
Text

MISSING 

Distinct5
Distinct (%)50.0%
Missing42
Missing (%)80.8%
Memory size548.0 B
2023-12-12T06:35:17.546832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters70
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)30.0%

Sample

1st rowA336370
2nd rowA336260
3rd rowA316140
4th rowA316140
5th rowA316140
ValueCountFrequency (%)
a316140 5
50.0%
a306200 2
 
20.0%
a336370 1
 
10.0%
a336260 1
 
10.0%
a307750 1
 
10.0%
2023-12-12T06:35:17.740065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
21.4%
3 13
18.6%
A 10
14.3%
1 10
14.3%
6 10
14.3%
4 5
 
7.1%
2 3
 
4.3%
7 3
 
4.3%
5 1
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
85.7%
Uppercase Letter 10
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
25.0%
3 13
21.7%
1 10
16.7%
6 10
16.7%
4 5
 
8.3%
2 3
 
5.0%
7 3
 
5.0%
5 1
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
A 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60
85.7%
Latin 10
 
14.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
25.0%
3 13
21.7%
1 10
16.7%
6 10
16.7%
4 5
 
8.3%
2 3
 
5.0%
7 3
 
5.0%
5 1
 
1.7%
Latin
ValueCountFrequency (%)
A 10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
21.4%
3 13
18.6%
A 10
14.3%
1 10
14.3%
6 10
14.3%
4 5
 
7.1%
2 3
 
4.3%
7 3
 
4.3%
5 1
 
1.4%

산업명
Categorical

IMBALANCE 

Distinct5
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
20190213
20191018
 
2
20181005
 
2
20181219
 
1

Length

Max length8
Median length4
Mean length4.7692308
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
20190213 5
 
9.6%
20191018 2
 
3.8%
20181005 2
 
3.8%
20181219 1
 
1.9%

Length

2023-12-12T06:35:17.869342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:17.955193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
20190213 5
 
9.6%
20191018 2
 
3.8%
20181005 2
 
3.8%
20181219 1
 
1.9%

설립일
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
일반기업
10 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
일반기업 10
 
19.2%

Length

2023-12-12T06:35:18.037242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:18.107842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
일반기업 10
 
19.2%

상장코드
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
법인
10 

Length

Max length4
Median length4
Mean length3.6153846
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
법인 10
 
19.2%

Length

2023-12-12T06:35:18.193422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:18.281226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
법인 10
 
19.2%

상장일
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
본점
10 

Length

Max length4
Median length4
Mean length3.6153846
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
본점 10
 
19.2%

Length

2023-12-12T06:35:18.368218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:18.449519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
본점 10
 
19.2%

공기업구분
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
10 

Length

Max length4
Median length4
Mean length3.4230769
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
10
 
19.2%

Length

2023-12-12T06:35:18.529943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:18.612216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
10
 
19.2%

개인법인구분
Categorical

IMBALANCE 

Distinct6
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
176
652
 
2
266
 
1
448
 
1

Length

Max length4
Median length4
Mean length3.8076923
Min length3

Unique

Unique3 ?
Unique (%)5.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
176 5
 
9.6%
652 2
 
3.8%
266 1
 
1.9%
448 1
 
1.9%
115 1
 
1.9%

Length

2023-12-12T06:35:18.691840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:18.785472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
176 5
 
9.6%
652 2
 
3.8%
266 1
 
1.9%
448 1
 
1.9%
115 1
 
1.9%
Distinct3
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
202106
202109
 
4

Length

Max length6
Median length4
Mean length4.3846154
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
202106 6
 
11.5%
202109 4
 
7.7%

Length

2023-12-12T06:35:18.904071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:19.001317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
202106 6
 
11.5%
202109 4
 
7.7%
Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
202106
10 

Length

Max length6
Median length4
Mean length4.3846154
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
202106 10
 
19.2%

Length

2023-12-12T06:35:19.098986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:19.180423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
202106 10
 
19.2%

종업원수
Text

MISSING 

Distinct5
Distinct (%)50.0%
Missing42
Missing (%)80.8%
Memory size548.0 B
2023-12-12T06:35:19.281268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length7.4
Min length3

Characters and Unicode

Total characters74
Distinct characters34
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

Unique3 ?
Unique (%)30.0%

Sample

1st row스카이레이크롱텀스트래티직인베
2nd row두산중공업(주)
3rd row예금보험공사
4th row예금보험공사
5th row예금보험공사
ValueCountFrequency (%)
예금보험공사 5
50.0%
주)세아제강지주 2
 
20.0%
스카이레이크롱텀스트래티직인베 1
 
10.0%
두산중공업(주 1
 
10.0%
홍종호 1
 
10.0%
2023-12-12T06:35:19.500197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
8.1%
5
 
6.8%
5
 
6.8%
5
 
6.8%
5
 
6.8%
5
 
6.8%
5
 
6.8%
( 3
 
4.1%
) 3
 
4.1%
2
 
2.7%
Other values (24) 30
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68
91.9%
Open Punctuation 3
 
4.1%
Close Punctuation 3
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6
 
8.8%
5
 
7.4%
5
 
7.4%
5
 
7.4%
5
 
7.4%
5
 
7.4%
5
 
7.4%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (22) 26
38.2%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68
91.9%
Common 6
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6
 
8.8%
5
 
7.4%
5
 
7.4%
5
 
7.4%
5
 
7.4%
5
 
7.4%
5
 
7.4%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (22) 26
38.2%
Common
ValueCountFrequency (%)
( 3
50.0%
) 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68
91.9%
ASCII 6
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6
 
8.8%
5
 
7.4%
5
 
7.4%
5
 
7.4%
5
 
7.4%
5
 
7.4%
5
 
7.4%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (22) 26
38.2%
ASCII
ValueCountFrequency (%)
( 3
50.0%
) 3
50.0%

종업원수기준일
Categorical

IMBALANCE 

Distinct6
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
15.25
46.6
 
2
41.06
 
1
30.33
 
1

Length

Max length5
Median length4
Mean length4.1538462
Min length4

Unique

Unique3 ?
Unique (%)5.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
15.25 5
 
9.6%
46.6 2
 
3.8%
41.06 1
 
1.9%
30.33 1
 
1.9%
43.56 1
 
1.9%

Length

2023-12-12T06:35:19.597867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:19.676599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
15.25 5
 
9.6%
46.6 2
 
3.8%
41.06 1
 
1.9%
30.33 1
 
1.9%
43.56 1
 
1.9%

주주기준일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
국민연금공단
이순형
 
2
진대제
 
1
홍종훈
 
1

Length

Max length6
Median length4
Mean length4.1538462
Min length3

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
국민연금공단 6
 
11.5%
이순형 2
 
3.8%
진대제 1
 
1.9%
홍종훈 1
 
1.9%

Length

2023-12-12T06:35:19.768765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:19.852105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
국민연금공단 6
 
11.5%
이순형 2
 
3.8%
진대제 1
 
1.9%
홍종훈 1
 
1.9%

주주명1
Categorical

IMBALANCE 

Distinct6
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
9.8
7.82
 
2
0.0
 
1
5.48
 
1

Length

Max length5
Median length4
Mean length3.9038462
Min length3

Unique

Unique3 ?
Unique (%)5.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
9.8 5
 
9.6%
7.82 2
 
3.8%
0.0 1
 
1.9%
5.48 1
 
1.9%
11.77 1
 
1.9%

Length

2023-12-12T06:35:19.958251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:20.049098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
9.8 5
 
9.6%
7.82 2
 
3.8%
0.0 1
 
1.9%
5.48 1
 
1.9%
11.77 1
 
1.9%

주식비율1
Categorical

IMBALANCE 

Distinct5
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
43 
우리사주조합
국민연금공단
 
2
(재)두산연강재단
 
1
홍종학
 
1

Length

Max length9
Median length4
Mean length4.3461538
Min length3

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 43
82.7%
우리사주조합 5
 
9.6%
국민연금공단 2
 
3.8%
(재)두산연강재단 1
 
1.9%
홍종학 1
 
1.9%

Length

2023-12-12T06:35:20.138593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:20.466177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
82.7%
우리사주조합 5
 
9.6%
국민연금공단 2
 
3.8%
재)두산연강재단 1
 
1.9%
홍종학 1
 
1.9%

주주명2
Categorical

IMBALANCE 

Distinct5
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
43 
8.75
7.34
 
2
3.56
 
1
7.3
 
1

Length

Max length4
Median length4
Mean length3.9807692
Min length3

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 43
82.7%
8.75 5
 
9.6%
7.34 2
 
3.8%
3.56 1
 
1.9%
7.3 1
 
1.9%

Length

2023-12-12T06:35:20.555573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:20.634867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
82.7%
8.75 5
 
9.6%
7.34 2
 
3.8%
3.56 1
 
1.9%
7.3 1
 
1.9%

주식비율2
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
<NA>
42 
20201231
10 

Length

Max length8
Median length4
Mean length4.7692308
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
80.8%
20201231 10
 
19.2%

Length

2023-12-12T06:35:20.723789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:35:20.808316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
80.8%
20201231 10
 
19.2%

주주명3
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)60.0%
Missing42
Missing (%)80.8%
Infinite0
Infinite (%)0.0%
Mean6.7487297 × 108
Minimum0
Maximum3.4514449 × 109
Zeros3
Zeros (%)5.8%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T06:35:20.877105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112586414
median1.2715052 × 108
Q31.0967508 × 109
95-th percentile2.5257589 × 109
Maximum3.4514449 × 109
Range3.4514449 × 109
Interquartile range (IQR)1.0841643 × 109

Descriptive statistics

Standard deviation1.1216502 × 109
Coefficient of variation (CV)1.6620167
Kurtosis4.0683726
Mean6.7487297 × 108
Median Absolute Deviation (MAD)1.2715052 × 108
Skewness2.022752
Sum6.7487297 × 109
Variance1.2580991 × 1018
MonotonicityNot monotonic
2023-12-12T06:35:20.967159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 3
 
5.8%
127150516 2
 
3.8%
1394364933 2
 
3.8%
203908240 1
 
1.9%
3451444903 1
 
1.9%
50345658 1
 
1.9%
(Missing) 42
80.8%
ValueCountFrequency (%)
0 3
5.8%
50345658 1
 
1.9%
127150516 2
3.8%
203908240 1
 
1.9%
1394364933 2
3.8%
3451444903 1
 
1.9%
ValueCountFrequency (%)
3451444903 1
 
1.9%
1394364933 2
3.8%
203908240 1
 
1.9%
127150516 2
3.8%
50345658 1
 
1.9%
0 3
5.8%

주식비율3
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)60.0%
Missing42
Missing (%)80.8%
Infinite0
Infinite (%)0.0%
Mean-35948005
Minimum-4.7306219 × 108
Maximum1.7113073 × 108
Zeros3
Zeros (%)5.8%
Negative5
Negative (%)9.6%
Memory size600.0 B
2023-12-12T06:35:21.047363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-4.7306219 × 108
5-th percentile-2.712286 × 108
Q1-20101296
median-3387929.5
Q30
95-th percentile96412105
Maximum1.7113073 × 108
Range6.4419292 × 108
Interquartile range (IQR)20101296

Descriptive statistics

Standard deviation1.6379982 × 108
Coefficient of variation (CV)-4.556576
Kurtosis7.289532
Mean-35948005
Median Absolute Deviation (MAD)5932599
Skewness-2.3505599
Sum-3.5948005 × 108
Variance2.683038 × 1016
MonotonicityNot monotonic
2023-12-12T06:35:21.126568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 3
 
5.8%
-6775859 2
 
3.8%
-24543109 2
 
3.8%
171130732 1
 
1.9%
-473062187 1
 
1.9%
5089339 1
 
1.9%
(Missing) 42
80.8%
ValueCountFrequency (%)
-473062187 1
 
1.9%
-24543109 2
3.8%
-6775859 2
3.8%
0 3
5.8%
5089339 1
 
1.9%
171130732 1
 
1.9%
ValueCountFrequency (%)
171130732 1
 
1.9%
5089339 1
 
1.9%
0 3
5.8%
-6775859 2
3.8%
-24543109 2
3.8%
-473062187 1
 
1.9%

결산일
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

매출액
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

영업이익
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

Unnamed: 43
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

Sample

사업자등록번호언론사명뉴스제목뉴스요약뉴스식별번호뉴스작성시간뉴스작성자뉴스ESG분류뉴스ESG관련도뉴스ESG스코어법인번호대표자주요사업기업규모기업규모형태기업업종(대표)기업업종(상세)기업업태(대표)기업업태(상세)산업코드차수산업대분류코드산업대분류명산업코드산업명설립일상장코드상장일공기업구분개인법인구분본점지점구분외국투자법인종업원수종업원수기준일주주기준일자주주명1주식비율1주주명2주식비율2주주명3주식비율3결산일매출액영업이익Unnamed: 43
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12018******이데일리두산밥캣, 코로나에 美공장 5곳 중 4곳 일시 가동중단19일까지 2주가량 셧다운…1곳만 정상 가동 두산밥캣이 ‘코로나19’(신종 코로나바이러스 감염증) 확산한 데 따라 미국 공장 5곳 가운데 4곳 가동을 중단키로 했다.<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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3두산밥캣(241560)은 1일(현지시간) 미국 노스캐롤라이나주에 있는 공장 1곳 가동을 4일부터, 미네소타·노스다코타주에 있는 공장 3곳 가동을 6일부터 각각 일시 중단한다고 밝혔다.<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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5미국 공장 5곳 가운데 가장 규모가 작은 노스다코타주 와페튼 공장 1곳은 정상 가동한다.8.97E+172.02E+13경계*UESG아님0.9822150000000000진대*HBL 외중견기업거래소상장발광 다이오드 제조업건강 기능 식품 제조업/기타 식품 첨가물 제조업/동박 및 전지박 제조/발광 다이오드 제조업/사료 도매업/식물성 유지 제조업/의약용 화합물 및 항생물질 제조업/화장품 원료제조업건강 기능 식품 제조업/기타 식품 첨가물 제조업/동박 및 전지박 제조/발광 다이오드 제조업/사료 도매업/식물성 유지 제조업/의약용 화합물 및 항생물질 제조업/화장품 원료10C제조업26121발광 다이오드 제조업20191001A33637020191018일반기업법인본점266202106202106스카이레이크롱텀스트래티직인베41.06진대제0.0<NA><NA>20201231203908240171130732<NA><NA><NA><NA>
66098******아시아경제"두산중공업, 올 1분기 누적수주액 1조5000억원 달성"최근 두산중공업은 대규모 수주 소식을 전하고 있다.<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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8정동익 현대증권 연구원은 "이번 수주는 국내 최초의 1000MW급 민자발전소 프로젝트에 핵심기기를 공급하는 건으로 향후 유사한 민자석탄 발전소용 주기기 수주입찰에서 유리한 고지를 선점했다"고 평가했다.<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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사업자등록번호언론사명뉴스제목뉴스요약뉴스식별번호뉴스작성시간뉴스작성자뉴스ESG분류뉴스ESG관련도뉴스ESG스코어법인번호대표자주요사업기업규모기업규모형태기업업종(대표)기업업종(상세)기업업태(대표)기업업태(상세)산업코드차수산업대분류코드산업대분류명산업코드산업명설립일상장코드상장일공기업구분개인법인구분본점지점구분외국투자법인종업원수종업원수기준일주주기준일자주주명1주식비율1주주명2주식비율2주주명3주식비율3결산일매출액영업이익Unnamed: 43
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43변종만 연구원은 “세아베스틸은 원가하락과 판매량 증가로 2분기 매출과 영업이익이 지난해 같은 기간보다 각각 8.4%, 4.4% 증가한 5959억원과 535억원으로 예상된다”며 “2분기 영업이익은 시장 컨센서스를 23.3% 웃돌 것”이라고 밝혔다.<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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45그는 다만 “올 하반기에도 철강업황 부진이 지속될 것으로 예상되고, 2016년부터 국내 특수강 시장의 경쟁심화로 인해 수익성이 악화될 수 있다는 우려는 여전하다”며 중립 의견을 유지했다.3.22E+172.02E+13<NA>UESG아님1.01100000000000이휘*강관, 강판, 강재, 기계, 전기기기, 공구, 산소 및 화학약품 등의 제조매매중견기업거래소상장강관강관제조업강관10C제조업24132강관 제조업20180903A30620020181005일반기업법인본점652202109202106(주)세아제강지주46.6이순형7.82국민연금공단7.34202012311394364933-24543109<NA><NA><NA><NA>
461138******뉴시스담합 조사 방해한 세아베스틸…공정위 檢 고발 '첫 사례'담합 조사 과정에서 정당한 사유 없이 공정위의 출석 요구에 응하지 않은 현대제철의 전·현직 임직원 3명에게는 과태료를 부과했다.<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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48공정위는 17일 "철스크랩(고철) 구매 담합 사건을 현장 조사하는 과정에서 세아베스틸 소속 직원의 자료 폐기·은닉, 전산 자료 삭제 등 조사 방해 행위를 적발했다"면서 "세아베스틸 법인과 소속 직원 3명을 검찰에 고발하기로 했다"고 밝혔다.<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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50결국 공정위 조사 직원은 해당 PC 내 자료의 제목·생성 시간 등을 확인할 수 없었다.1.01E+182.02E+13김진*S사회0.9921100000000000이휘*강관, 강판, 강재, 기계, 전기기기, 공구, 산소 및 화학약품 등의 제조매매중견기업거래소상장강관강관제조업강관10C제조업24132강관 제조업20180903A30620020181005일반기업법인본점652202109202106(주)세아제강지주46.6이순형7.82국민연금공단7.34202012311394364933-24543109<NA><NA><NA><NA>
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Most frequently occurring

사업자등록번호언론사명뉴스제목뉴스요약뉴스식별번호뉴스작성시간뉴스작성자뉴스ESG분류뉴스ESG관련도뉴스ESG스코어법인번호대표자주요사업기업규모기업규모형태기업업종(대표)기업업종(상세)기업업태(대표)기업업태(상세)산업코드차수산업대분류코드산업대분류명산업코드산업명설립일상장코드상장일공기업구분개인법인구분본점지점구분외국투자법인종업원수종업원수기준일주주기준일자주주명1주식비율1주주명2주식비율2주주명3주식비율3# duplicates
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