Overview

Dataset statistics

Number of variables5
Number of observations35
Missing cells30
Missing cells (%)17.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory44.8 B

Variable types

DateTime1
Categorical1
Text2
Numeric1

Dataset

Description한국서부발전의 재난대응 훈련수행 현황 정보입니다.제공항목은 훈련일시,훈련유형,훈련명,훈련시간,불시메시지 데이터를 제공합니다.
Author한국서부발전(주)
URLhttps://www.data.go.kr/data/15123090/fileData.do

Alerts

불시메시지 has 30 (85.7%) missing valuesMissing
훈련명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:24:39.667978
Analysis finished2023-12-12 11:24:40.557773
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

훈련일시
Date

Distinct25
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum2017-07-12 00:00:00
Maximum2019-10-29 00:00:00
2023-12-12T20:24:40.654750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:24:40.911875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

훈련유형
Categorical

Distinct3
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
초등대응훈련
26 
종합실행훈련
5 
상황관리훈련
4 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row초등대응훈련
2nd row상황관리훈련
3rd row초등대응훈련
4th row초등대응훈련
5th row초등대응훈련

Common Values

ValueCountFrequency (%)
초등대응훈련 26
74.3%
종합실행훈련 5
 
14.3%
상황관리훈련 4
 
11.4%

Length

2023-12-12T20:24:41.175575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:24:41.425882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초등대응훈련 26
74.3%
종합실행훈련 5
 
14.3%
상황관리훈련 4
 
11.4%

훈련명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-12T20:24:41.912273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length27
Mean length21.028571
Min length11

Characters and Unicode

Total characters736
Distinct characters152
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row재난대응 훈련(2017.07.12)
2nd row2017.07.19 훈련
3rd row암모니아누출 초동대응훈련
4th row태안발전 재난 안전 테스트
5th row상반기 기반시설팀 재난대응훈련(지진)
ValueCountFrequency (%)
2복합 14
 
8.0%
누출 11
 
6.3%
훈련 8
 
4.6%
초동대응훈련 7
 
4.0%
암모니아 6
 
3.4%
발생 6
 
3.4%
초동대응 5
 
2.9%
인한 5
 
2.9%
기력 4
 
2.3%
ng 4
 
2.3%
Other values (83) 105
60.0%
2023-12-12T20:24:42.650687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
144
 
19.6%
훈 23
 
3.1%
련 23
 
3.1%
2 21
 
2.9%
동 18
 
2.4%
대 17
 
2.3%
응 17
 
2.3%
출 15
 
2.0%
기 15
 
2.0%
초 14
 
1.9%
Other values (142) 429
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 479
65.1%
Space Separator 144
 
19.6%
Decimal Number 42
 
5.7%
Lowercase Letter 32
 
4.3%
Uppercase Letter 24
 
3.3%
Other Punctuation 8
 
1.1%
Open Punctuation 3
 
0.4%
Close Punctuation 3
 
0.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
훈 23
 
4.8%
련 23
 
4.8%
동 18
 
3.8%
대 17
 
3.5%
응 17
 
3.5%
출 15
 
3.1%
기 15
 
3.1%
초 14
 
2.9%
합 14
 
2.9%
복 14
 
2.9%
Other values (101) 309
64.5%
Lowercase Letter
ValueCountFrequency (%)
t 4
12.5%
o 4
12.5%
a 4
12.5%
e 3
9.4%
i 3
9.4%
n 2
 
6.2%
l 2
 
6.2%
k 2
 
6.2%
d 1
 
3.1%
u 1
 
3.1%
Other values (6) 6
18.8%
Uppercase Letter
ValueCountFrequency (%)
G 7
29.2%
N 4
16.7%
S 3
12.5%
T 2
 
8.3%
F 2
 
8.3%
U 1
 
4.2%
P 1
 
4.2%
L 1
 
4.2%
V 1
 
4.2%
C 1
 
4.2%
Decimal Number
ValueCountFrequency (%)
2 21
50.0%
1 8
 
19.0%
0 5
 
11.9%
7 4
 
9.5%
9 2
 
4.8%
4 1
 
2.4%
3 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
, 3
37.5%
# 1
 
12.5%
Space Separator
ValueCountFrequency (%)
144
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 479
65.1%
Common 201
27.3%
Latin 56
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
훈 23
 
4.8%
련 23
 
4.8%
동 18
 
3.8%
대 17
 
3.5%
응 17
 
3.5%
출 15
 
3.1%
기 15
 
3.1%
초 14
 
2.9%
합 14
 
2.9%
복 14
 
2.9%
Other values (101) 309
64.5%
Latin
ValueCountFrequency (%)
G 7
 
12.5%
N 4
 
7.1%
t 4
 
7.1%
o 4
 
7.1%
a 4
 
7.1%
e 3
 
5.4%
i 3
 
5.4%
S 3
 
5.4%
n 2
 
3.6%
T 2
 
3.6%
Other values (17) 20
35.7%
Common
ValueCountFrequency (%)
144
71.6%
2 21
 
10.4%
1 8
 
4.0%
0 5
 
2.5%
7 4
 
2.0%
. 4
 
2.0%
, 3
 
1.5%
( 3
 
1.5%
) 3
 
1.5%
9 2
 
1.0%
Other values (4) 4
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 479
65.1%
ASCII 257
34.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
144
56.0%
2 21
 
8.2%
1 8
 
3.1%
G 7
 
2.7%
0 5
 
1.9%
N 4
 
1.6%
t 4
 
1.6%
o 4
 
1.6%
a 4
 
1.6%
7 4
 
1.6%
Other values (31) 52
 
20.2%
Hangul
ValueCountFrequency (%)
훈 23
 
4.8%
련 23
 
4.8%
동 18
 
3.8%
대 17
 
3.5%
응 17
 
3.5%
출 15
 
3.1%
기 15
 
3.1%
초 14
 
2.9%
합 14
 
2.9%
복 14
 
2.9%
Other values (101) 309
64.5%

훈련시간
Real number (ℝ)

Distinct6
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.2
Minimum10
Maximum16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T20:24:42.875039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10
Q112
median14
Q314
95-th percentile15.3
Maximum16
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.9066447
Coefficient of variation (CV)0.14444278
Kurtosis-0.72727701
Mean13.2
Median Absolute Deviation (MAD)1
Skewness-0.76257366
Sum462
Variance3.6352941
MonotonicityNot monotonic
2023-12-12T20:24:43.077704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
14 16
45.7%
10 7
20.0%
15 5
 
14.3%
13 3
 
8.6%
11 2
 
5.7%
16 2
 
5.7%
ValueCountFrequency (%)
10 7
20.0%
11 2
 
5.7%
13 3
 
8.6%
14 16
45.7%
15 5
 
14.3%
16 2
 
5.7%
ValueCountFrequency (%)
16 2
 
5.7%
15 5
 
14.3%
14 16
45.7%
13 3
 
8.6%
11 2
 
5.7%
10 7
20.0%

불시메시지
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing30
Missing (%)85.7%
Memory size412.0 B
2023-12-12T20:24:43.411238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length45
Mean length45
Min length42

Characters and Unicode

Total characters225
Distinct characters88
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row[훈련상황] 기력 3,4호기 기동용 변압기 절연유 누출.현장점검 후 임무수행 바람
2nd row[훈련상황] 기력 NH3 TK 누설 발생 -> 현장 점검 후 임무 수행 바람
3rd row(훈련상황 메시지 입니다) 기력 주제어 전자카드 화재발생.. 초동대응 바람..
4th row(훈련상황 메시지 입니다) 27일 14시 현재 행정동 화재 발생. 신속하게 초동대응바람
5th row(훈련상황) 1호기 NG Station 가스누출감지 경보알람으로 초동대응 바랍니다.
ValueCountFrequency (%)
훈련상황 5
 
9.8%
기력 3
 
5.9%
바람 3
 
5.9%
후 2
 
3.9%
초동대응 2
 
3.9%
입니다 2
 
3.9%
발생 2
 
3.9%
메시지 2
 
3.9%
임무수행 1
 
2.0%
누출.현장점검 1
 
2.0%
Other values (28) 28
54.9%
2023-12-12T20:24:43.997132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47
 
20.9%
기 7
 
3.1%
. 7
 
3.1%
동 5
 
2.2%
련 5
 
2.2%
상 5
 
2.2%
황 5
 
2.2%
람 5
 
2.2%
바 5
 
2.2%
훈 5
 
2.2%
Other values (78) 129
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
60.9%
Space Separator 47
 
20.9%
Other Punctuation 8
 
3.6%
Decimal Number 8
 
3.6%
Uppercase Letter 7
 
3.1%
Lowercase Letter 6
 
2.7%
Close Punctuation 5
 
2.2%
Open Punctuation 5
 
2.2%
Math Symbol 1
 
0.4%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 7
 
5.1%
동 5
 
3.6%
련 5
 
3.6%
상 5
 
3.6%
황 5
 
3.6%
람 5
 
3.6%
바 5
 
3.6%
훈 5
 
3.6%
현 3
 
2.2%
생 3
 
2.2%
Other values (53) 89
65.0%
Uppercase Letter
ValueCountFrequency (%)
N 2
28.6%
G 1
14.3%
S 1
14.3%
H 1
14.3%
T 1
14.3%
K 1
14.3%
Decimal Number
ValueCountFrequency (%)
1 2
25.0%
3 2
25.0%
4 2
25.0%
2 1
12.5%
7 1
12.5%
Lowercase Letter
ValueCountFrequency (%)
t 2
33.3%
o 1
16.7%
a 1
16.7%
i 1
16.7%
n 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 7
87.5%
, 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 3
60.0%
] 2
40.0%
Open Punctuation
ValueCountFrequency (%)
( 3
60.0%
[ 2
40.0%
Space Separator
ValueCountFrequency (%)
47
100.0%
Math Symbol
ValueCountFrequency (%)
> 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137
60.9%
Common 75
33.3%
Latin 13
 
5.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 7
 
5.1%
동 5
 
3.6%
련 5
 
3.6%
상 5
 
3.6%
황 5
 
3.6%
람 5
 
3.6%
바 5
 
3.6%
훈 5
 
3.6%
현 3
 
2.2%
생 3
 
2.2%
Other values (53) 89
65.0%
Common
ValueCountFrequency (%)
47
62.7%
. 7
 
9.3%
) 3
 
4.0%
( 3
 
4.0%
1 2
 
2.7%
[ 2
 
2.7%
] 2
 
2.7%
3 2
 
2.7%
4 2
 
2.7%
> 1
 
1.3%
Other values (4) 4
 
5.3%
Latin
ValueCountFrequency (%)
N 2
15.4%
t 2
15.4%
o 1
7.7%
G 1
7.7%
S 1
7.7%
H 1
7.7%
a 1
7.7%
i 1
7.7%
n 1
7.7%
T 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137
60.9%
ASCII 88
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47
53.4%
. 7
 
8.0%
) 3
 
3.4%
( 3
 
3.4%
1 2
 
2.3%
N 2
 
2.3%
t 2
 
2.3%
[ 2
 
2.3%
] 2
 
2.3%
3 2
 
2.3%
Other values (15) 16
 
18.2%
Hangul
ValueCountFrequency (%)
기 7
 
5.1%
동 5
 
3.6%
련 5
 
3.6%
상 5
 
3.6%
황 5
 
3.6%
람 5
 
3.6%
바 5
 
3.6%
훈 5
 
3.6%
현 3
 
2.2%
생 3
 
2.2%
Other values (53) 89
65.0%

Interactions

2023-12-12T20:24:40.035164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:24:44.181464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
훈련일시훈련유형훈련명훈련시간불시메시지
훈련일시1.0000.8151.0000.8191.000
훈련유형0.8151.0001.0000.462NaN
훈련명1.0001.0001.0001.0001.000
훈련시간0.8190.4621.0001.000NaN
불시메시지1.000NaN1.000NaN1.000
2023-12-12T20:24:44.375837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
훈련시간훈련유형
훈련시간1.0000.194
훈련유형0.1941.000

Missing values

2023-12-12T20:24:40.308890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:24:40.491980image/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

훈련일시훈련유형훈련명훈련시간불시메시지
02017-07-12초등대응훈련재난대응 훈련(2017.07.12)11<NA>
12017-07-19상황관리훈련2017.07.19 훈련11<NA>
22018-04-16초등대응훈련암모니아누출 초동대응훈련15<NA>
32018-04-18초등대응훈련태안발전 재난 안전 테스트15<NA>
42018-05-04초등대응훈련상반기 기반시설팀 재난대응훈련(지진)13<NA>
52018-05-24상황관리훈련지진 발생 후 2복합 주제어동 점검훈련13<NA>
62018-05-30초등대응훈련#1 NG Stop Valve에서 NG Leak14<NA>
72018-05-30초등대응훈련기력 3,4호기 기동용 변압기 절연유 누출 방제훈련14[훈련상황] 기력 3,4호기 기동용 변압기 절연유 누출.현장점검 후 임무수행 바람
82018-06-08초등대응훈련기력 암모니아 누출 초동대응 훈련14[훈련상황] 기력 NH3 TK 누설 발생 -> 현장 점검 후 임무 수행 바람
92018-06-19초등대응훈련염산 유출 대응 훈련14<NA>
훈련일시훈련유형훈련명훈련시간불시메시지
252018-09-28초등대응훈련지하전력구 화재 초동대응훈련14<NA>
262019-03-07초등대응훈련NG Station 가스누출 사고14(훈련상황) 1호기 NG Station 가스누출감지 경보알람으로 초동대응 바랍니다.
272019-05-28초등대응훈련2복합 지하전력구 화재로 인한 초동대응 훈련10<NA>
282019-06-18상황관리훈련지진 발생 후 2복합 주제어동 점검16<NA>
292019-06-19종합실행훈련2복합 수소가스저장소 가스 누출13<NA>
302019-06-20초등대응훈련2019년 유해화학물질(염산) 누출 방재훈련 계획16<NA>
312019-06-20초등대응훈련기력 1,2호기 공용 Pc-Tr 절연유 누출 방제훈련15<NA>
322019-06-20초등대응훈련2복합 탈질설비 암모니아 가스 누출10<NA>
332019-10-01초등대응훈련2복합 GT 2호기 발전기 수소폭발로 인한 초동대응 훈련10<NA>
342019-10-29초등대응훈련지진 발생으로 인한 탈황사면 붕괴14<NA>