Overview

Dataset statistics

Number of variables3
Number of observations108
Missing cells84
Missing cells (%)25.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory25.2 B

Variable types

Text3

Dataset

Description한국남부발전(주)_해외사업 영문계약 용어 정보에 대한 데이터로 영문계약 용어, 용어 정의, 비고 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15110045/fileData.do

Alerts

비고 has 84 (77.8%) missing valuesMissing
영문계약 용어 has unique valuesUnique
has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:25:50.761118
Analysis finished2023-12-12 16:25:51.506739
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

영문계약 용어
Text

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-13T01:25:51.718345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length31
Mean length15.583333
Min length2

Characters and Unicode

Total characters1683
Distinct characters53
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

Unique108 ?
Unique (%)100.0%

Sample

1st rowChinese Wall
2nd rowab initio (라틴어)
3rd rowABA / American Bar Association
4th rowabsolute conveyance
5th rowacceleration clause
ValueCountFrequency (%)
25
 
10.1%
of 7
 
2.8%
to 4
 
1.6%
contract 3
 
1.2%
act 3
 
1.2%
draft 3
 
1.2%
deposit 2
 
0.8%
first 2
 
0.8%
easement 2
 
0.8%
fidelity 2
 
0.8%
Other values (176) 194
78.5%
2023-12-13T01:25:52.160629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
196
11.6%
e 187
 
11.1%
t 135
 
8.0%
a 125
 
7.4%
i 110
 
6.5%
n 108
 
6.4%
o 104
 
6.2%
r 88
 
5.2%
c 80
 
4.8%
d 66
 
3.9%
Other values (43) 484
28.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1363
81.0%
Space Separator 196
 
11.6%
Uppercase Letter 67
 
4.0%
Other Punctuation 34
 
2.0%
Open Punctuation 8
 
0.5%
Close Punctuation 8
 
0.5%
Other Letter 6
 
0.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 187
13.7%
t 135
9.9%
a 125
9.2%
i 110
 
8.1%
n 108
 
7.9%
o 104
 
7.6%
r 88
 
6.5%
c 80
 
5.9%
d 66
 
4.8%
l 61
 
4.5%
Other values (16) 299
21.9%
Uppercase Letter
ValueCountFrequency (%)
A 10
14.9%
B 7
10.4%
O 7
10.4%
R 6
9.0%
F 5
7.5%
P 5
7.5%
Q 4
 
6.0%
I 4
 
6.0%
L 4
 
6.0%
C 3
 
4.5%
Other values (7) 12
17.9%
Other Punctuation
ValueCountFrequency (%)
/ 27
79.4%
. 6
 
17.6%
' 1
 
2.9%
Other Letter
ValueCountFrequency (%)
2
33.3%
2
33.3%
2
33.3%
Space Separator
ValueCountFrequency (%)
196
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1430
85.0%
Common 247
 
14.7%
Hangul 6
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 187
13.1%
t 135
 
9.4%
a 125
 
8.7%
i 110
 
7.7%
n 108
 
7.6%
o 104
 
7.3%
r 88
 
6.2%
c 80
 
5.6%
d 66
 
4.6%
l 61
 
4.3%
Other values (33) 366
25.6%
Common
ValueCountFrequency (%)
196
79.4%
/ 27
 
10.9%
( 8
 
3.2%
) 8
 
3.2%
. 6
 
2.4%
' 1
 
0.4%
- 1
 
0.4%
Hangul
ValueCountFrequency (%)
2
33.3%
2
33.3%
2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1677
99.6%
Hangul 6
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
196
11.7%
e 187
 
11.2%
t 135
 
8.1%
a 125
 
7.5%
i 110
 
6.6%
n 108
 
6.4%
o 104
 
6.2%
r 88
 
5.2%
c 80
 
4.8%
d 66
 
3.9%
Other values (40) 478
28.5%
Hangul
ValueCountFrequency (%)
2
33.3%
2
33.3%
2
33.3%


Text

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-13T01:25:52.452929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length7.9722222
Min length2

Characters and Unicode

Total characters861
Distinct characters191
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)100.0%

Sample

1st row만리장성 / 차단벽
2nd row당초부터 / 처음부터
3rd row미국 법조협회
4th row무조건인도
5th row기한 이익 상실조항
ValueCountFrequency (%)
26
 
13.1%
세금 2
 
1.0%
계약 2
 
1.0%
어음 2
 
1.0%
양도하다 2
 
1.0%
등이 2
 
1.0%
재발행된 1
 
0.5%
당초부터 1
 
0.5%
처음부터 1
 
0.5%
가족관계(법 1
 
0.5%
Other values (158) 158
79.8%
2023-12-13T01:25:52.926902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
184
 
21.4%
/ 27
 
3.1%
18
 
2.1%
17
 
2.0%
15
 
1.7%
13
 
1.5%
13
 
1.5%
12
 
1.4%
11
 
1.3%
) 11
 
1.3%
Other values (181) 540
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 624
72.5%
Space Separator 184
 
21.4%
Other Punctuation 28
 
3.3%
Close Punctuation 11
 
1.3%
Open Punctuation 11
 
1.3%
Math Symbol 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18
 
2.9%
17
 
2.7%
15
 
2.4%
13
 
2.1%
13
 
2.1%
12
 
1.9%
11
 
1.8%
10
 
1.6%
10
 
1.6%
10
 
1.6%
Other values (175) 495
79.3%
Other Punctuation
ValueCountFrequency (%)
/ 27
96.4%
, 1
 
3.6%
Space Separator
ValueCountFrequency (%)
184
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 622
72.2%
Common 237
 
27.5%
Han 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18
 
2.9%
17
 
2.7%
15
 
2.4%
13
 
2.1%
13
 
2.1%
12
 
1.9%
11
 
1.8%
10
 
1.6%
10
 
1.6%
10
 
1.6%
Other values (173) 493
79.3%
Common
ValueCountFrequency (%)
184
77.6%
/ 27
 
11.4%
) 11
 
4.6%
( 11
 
4.6%
~ 3
 
1.3%
, 1
 
0.4%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 622
72.2%
ASCII 237
 
27.5%
CJK 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
184
77.6%
/ 27
 
11.4%
) 11
 
4.6%
( 11
 
4.6%
~ 3
 
1.3%
, 1
 
0.4%
Hangul
ValueCountFrequency (%)
18
 
2.9%
17
 
2.7%
15
 
2.4%
13
 
2.1%
13
 
2.1%
12
 
1.9%
11
 
1.8%
10
 
1.6%
10
 
1.6%
10
 
1.6%
Other values (173) 493
79.3%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

비고
Text

MISSING 

Distinct24
Distinct (%)100.0%
Missing84
Missing (%)77.8%
Memory size996.0 B
2023-12-13T01:25:53.277965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length182
Median length49.5
Mean length58.75
Min length12

Characters and Unicode

Total characters1410
Distinct characters263
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row이해상충이 일어나지 않도록 한 금융/법률회사 내에서 정보 교류를 차단하는 장치
2nd row날인증서(deed)를 무조건으로 인도하고 그 효력이 현실적인 인도와 더불어 발생 하는 것
3rd row약속어음에서 어음이 원금을 분할하여 지급하는 조건인 경우, 발행인이 특정 회차의 지급금을 지급하지 못하여 어음소지인이 잔여 분할상환원금 모두의 지급을 즉시 신청할 때, 기한 이익 상실에 대해 규정한 조항
4th row산술적인 비율이나 합리적인 범위내에서의 조정을 의미함
5th rowfrom처럼 해당일이 포함이 안되 만 만약에 after 뒤에 특정한 날짜가 아니라 어떤 사실의 발생사실을 시작시점으로 규정하고 있을 경우에는 그 해당일을 포함한다 (ex) ~ at any time after the effective date of thic Agreement에서, the effective date를 포함한다.
ValueCountFrequency (%)
있는 4
 
1.3%
또는 3
 
1.0%
3
 
1.0%
포함한다 2
 
0.6%
december 2
 
0.6%
문서 2
 
0.6%
2
 
0.6%
of 2
 
0.6%
의미함 2
 
0.6%
포함이 2
 
0.6%
Other values (273) 287
92.3%
2023-12-13T01:25:53.829184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
289
 
20.5%
e 33
 
2.3%
31
 
2.2%
28
 
2.0%
26
 
1.8%
23
 
1.6%
23
 
1.6%
21
 
1.5%
20
 
1.4%
19
 
1.3%
Other values (253) 897
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 933
66.2%
Space Separator 289
 
20.5%
Lowercase Letter 149
 
10.6%
Uppercase Letter 12
 
0.9%
Other Punctuation 11
 
0.8%
Decimal Number 5
 
0.4%
Close Punctuation 4
 
0.3%
Open Punctuation 4
 
0.3%
Math Symbol 2
 
0.1%
Final Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
31
 
3.3%
28
 
3.0%
26
 
2.8%
23
 
2.5%
23
 
2.5%
21
 
2.3%
20
 
2.1%
19
 
2.0%
18
 
1.9%
16
 
1.7%
Other values (212) 708
75.9%
Lowercase Letter
ValueCountFrequency (%)
e 33
22.1%
t 16
10.7%
r 14
9.4%
f 11
 
7.4%
a 10
 
6.7%
n 8
 
5.4%
i 8
 
5.4%
c 8
 
5.4%
o 8
 
5.4%
m 8
 
5.4%
Other values (11) 25
16.8%
Uppercase Letter
ValueCountFrequency (%)
D 3
25.0%
F 2
16.7%
L 1
 
8.3%
I 1
 
8.3%
B 1
 
8.3%
O 1
 
8.3%
R 1
 
8.3%
M 1
 
8.3%
A 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 6
54.5%
. 4
36.4%
/ 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 3
60.0%
2 2
40.0%
Math Symbol
ValueCountFrequency (%)
= 1
50.0%
~ 1
50.0%
Space Separator
ValueCountFrequency (%)
289
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 933
66.2%
Common 316
 
22.4%
Latin 161
 
11.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
31
 
3.3%
28
 
3.0%
26
 
2.8%
23
 
2.5%
23
 
2.5%
21
 
2.3%
20
 
2.1%
19
 
2.0%
18
 
1.9%
16
 
1.7%
Other values (212) 708
75.9%
Latin
ValueCountFrequency (%)
e 33
20.5%
t 16
9.9%
r 14
 
8.7%
f 11
 
6.8%
a 10
 
6.2%
n 8
 
5.0%
i 8
 
5.0%
c 8
 
5.0%
o 8
 
5.0%
m 8
 
5.0%
Other values (20) 37
23.0%
Common
ValueCountFrequency (%)
289
91.5%
, 6
 
1.9%
. 4
 
1.3%
) 4
 
1.3%
( 4
 
1.3%
1 3
 
0.9%
2 2
 
0.6%
1
 
0.3%
= 1
 
0.3%
~ 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 933
66.2%
ASCII 476
33.8%
Punctuation 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
289
60.7%
e 33
 
6.9%
t 16
 
3.4%
r 14
 
2.9%
f 11
 
2.3%
a 10
 
2.1%
n 8
 
1.7%
i 8
 
1.7%
c 8
 
1.7%
o 8
 
1.7%
Other values (30) 71
 
14.9%
Hangul
ValueCountFrequency (%)
31
 
3.3%
28
 
3.0%
26
 
2.8%
23
 
2.5%
23
 
2.5%
21
 
2.3%
20
 
2.1%
19
 
2.0%
18
 
1.9%
16
 
1.7%
Other values (212) 708
75.9%
Punctuation
ValueCountFrequency (%)
1
100.0%

Missing values

2023-12-13T01:25:51.390060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:25:51.472070image/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

영문계약 용어비고
0Chinese Wall만리장성 / 차단벽이해상충이 일어나지 않도록 한 금융/법률회사 내에서 정보 교류를 차단하는 장치
1ab initio (라틴어)당초부터 / 처음부터<NA>
2ABA / American Bar Association미국 법조협회<NA>
3absolute conveyance무조건인도날인증서(deed)를 무조건으로 인도하고 그 효력이 현실적인 인도와 더불어 발생 하는 것
4acceleration clause기한 이익 상실조항약속어음에서 어음이 원금을 분할하여 지급하는 조건인 경우, 발행인이 특정 회차의 지급금을 지급하지 못하여 어음소지인이 잔여 분할상환원금 모두의 지급을 즉시 신청할 때, 기한 이익 상실에 대해 규정한 조항
5accordingly부합산술적인 비율이나 합리적인 범위내에서의 조정을 의미함
6accommodate융통어음을 발행하다<NA>
7account payable미지급금 / 외상매입금<NA>
8account receivable수취계정 / 외상매출금<NA>
9accrue(이자 등이) 생기다 / (소권이) 발생하다<NA>
영문계약 용어비고
98LIBOR(London Inter-Bank Offered Rate)리보금리런던 국제금융시장에서 은행들간에 자금을 빌려줄 때 적용되는 금리’로 국제금융거래에서 기준금리 역할을 한다. 즉, 자금을 차입하는 국가나 기업의 신용상태에 따라 LIBOR 금리에 차등금리를 가산하여 실제 적용금리가 정해진다
99KOLIBOR코리보영국의 리보금리를 본 뜬 것으로써 한국 시중은행들 간에 적용되는 단기 기준금리
100RFQ입찰자격요청서사업수행실적 및 신인도 등을 종합 평가해 일정기준 이상의 입찰참가자를 선정하는 제도
101PQ입찰참가자격사전심사국제경쟁입찰에서 관계 공사 또는 플랜트건설에 경험이 있는 자가 우선권을 가지게 되는 사전 경험
102PQQ사전자격심사입찰에 참가가능한 업체의 자격을 사전에 심사하여 업체의 임찰참가를 제한하는 방식
103RFP제안요청서발주처에서 제안서 작성을 보다 프로젝트 특성에 맞게 작성하도록 유도하기 위하여 제안서를 작성하는데 필요한 제반정보가 담겨있는 문서
104LOI의향서국제거래에 관한 협상단계에서 당사자의 의도를 확인하기 위하여 문서로 작성하는 당사자간 예비적 합의의 일종
105MOA합의각서양 측에서 협의를 통해 진행 또는 합의된 사안을 기록해놓은 문서
106CA양허계약서사회기반시설에 대해 정부기관이 양여자로서 운영사업자와 체결하는 양허계약
107MDB다자간개발은행경제개발자금을 지원하는 은행으로서 가입자격에 제한없이 참여하는 은행