Overview

Dataset statistics

Number of variables7
Number of observations8308
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory462.6 KiB
Average record size in memory57.0 B

Variable types

Numeric1
Text2
Categorical4

Dataset

Description4차 산업혁명기술을 적용한 자동예측진단 기술개발 현황 번호,기기명,기능위치,진단기법,열화상,발전소,완료연도 관련자료입니다.
Author한국수력원자력(주)
URLhttps://www.data.go.kr/data/15060806/fileData.do

Alerts

진단기법 has constant value ""Constant
발전소 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
완료연도 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
열화상 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
번호 is highly overall correlated with 열화상 and 2 other fieldsHigh correlation
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:09:45.981122
Analysis finished2023-12-11 23:09:46.865894
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct8308
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4154.5
Minimum1
Maximum8308
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size73.1 KiB
2023-12-12T08:09:46.964858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile416.35
Q12077.75
median4154.5
Q36231.25
95-th percentile7892.65
Maximum8308
Range8307
Interquartile range (IQR)4153.5

Descriptive statistics

Standard deviation2398.4574
Coefficient of variation (CV)0.57731553
Kurtosis-1.2
Mean4154.5
Median Absolute Deviation (MAD)2077
Skewness0
Sum34515586
Variance5752597.7
MonotonicityStrictly increasing
2023-12-12T08:09:47.116125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5520 1
 
< 0.1%
5550 1
 
< 0.1%
5549 1
 
< 0.1%
5548 1
 
< 0.1%
5547 1
 
< 0.1%
5546 1
 
< 0.1%
5545 1
 
< 0.1%
5544 1
 
< 0.1%
5543 1
 
< 0.1%
Other values (8298) 8298
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
8308 1
< 0.1%
8307 1
< 0.1%
8306 1
< 0.1%
8305 1
< 0.1%
8304 1
< 0.1%
8303 1
< 0.1%
8302 1
< 0.1%
8301 1
< 0.1%
8300 1
< 0.1%
8299 1
< 0.1%

기기명
Text

Distinct1428
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size65.0 KiB
2023-12-12T08:09:47.435835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length35
Mean length24.173688
Min length4

Characters and Unicode

Total characters200835
Distinct characters71
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique324 ?
Unique (%)3.9%

Sample

1st rowLRS Auxiliary Feed Pump
2nd rowLRS Auxiliary Feed Pump MTR
3rd rowLRS Recirculation Pump
4th rowLRS Recirculation Pump MTR
5th rowLRS Distillate Pump
ValueCountFrequency (%)
mtr 3937
 
9.8%
pp 2470
 
6.2%
pump 1977
 
4.9%
fan 1940
 
4.9%
oil 880
 
2.2%
rm 818
 
2.0%
a 673
 
1.7%
b 653
 
1.6%
ahu 639
 
1.6%
exh 593
 
1.5%
Other values (705) 25403
63.5%
2023-12-12T08:09:48.221199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31991
15.9%
R 14431
 
7.2%
P 13316
 
6.6%
A 11275
 
5.6%
E 10913
 
5.4%
T 10405
 
5.2%
M 9668
 
4.8%
L 8044
 
4.0%
C 7630
 
3.8%
N 6865
 
3.4%
Other values (61) 76297
38.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 141659
70.5%
Space Separator 31991
 
15.9%
Lowercase Letter 21953
 
10.9%
Other Punctuation 2263
 
1.1%
Decimal Number 1967
 
1.0%
Open Punctuation 394
 
0.2%
Close Punctuation 390
 
0.2%
Dash Punctuation 218
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 14431
 
10.2%
P 13316
 
9.4%
A 11275
 
8.0%
E 10913
 
7.7%
T 10405
 
7.3%
M 9668
 
6.8%
L 8044
 
5.7%
C 7630
 
5.4%
N 6865
 
4.8%
S 6345
 
4.5%
Other values (16) 42767
30.2%
Lowercase Letter
ValueCountFrequency (%)
e 2401
10.9%
o 1908
 
8.7%
i 1692
 
7.7%
u 1679
 
7.6%
a 1619
 
7.4%
n 1532
 
7.0%
l 1527
 
7.0%
p 1518
 
6.9%
t 1498
 
6.8%
r 1496
 
6.8%
Other values (15) 5083
23.2%
Decimal Number
ValueCountFrequency (%)
0 733
37.3%
1 617
31.4%
2 310
15.8%
3 156
 
7.9%
4 50
 
2.5%
5 31
 
1.6%
6 18
 
0.9%
9 18
 
0.9%
7 18
 
0.9%
8 16
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 1601
70.7%
/ 503
 
22.2%
' 66
 
2.9%
& 65
 
2.9%
# 20
 
0.9%
% 8
 
0.4%
Space Separator
ValueCountFrequency (%)
31991
100.0%
Open Punctuation
ValueCountFrequency (%)
( 394
100.0%
Close Punctuation
ValueCountFrequency (%)
) 390
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 218
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 163612
81.5%
Common 37223
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 14431
 
8.8%
P 13316
 
8.1%
A 11275
 
6.9%
E 10913
 
6.7%
T 10405
 
6.4%
M 9668
 
5.9%
L 8044
 
4.9%
C 7630
 
4.7%
N 6865
 
4.2%
S 6345
 
3.9%
Other values (41) 64720
39.6%
Common
ValueCountFrequency (%)
31991
85.9%
. 1601
 
4.3%
0 733
 
2.0%
1 617
 
1.7%
/ 503
 
1.4%
( 394
 
1.1%
) 390
 
1.0%
2 310
 
0.8%
- 218
 
0.6%
3 156
 
0.4%
Other values (10) 310
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 200835
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31991
15.9%
R 14431
 
7.2%
P 13316
 
6.6%
A 11275
 
5.6%
E 10913
 
5.4%
T 10405
 
5.2%
M 9668
 
4.8%
L 8044
 
4.0%
C 7630
 
3.8%
N 6865
 
3.4%
Other values (61) 76297
38.0%

기능위치
Text

Distinct4938
Distinct (%)59.4%
Missing0
Missing (%)0.0%
Memory size65.0 KiB
2023-12-12T08:09:48.498191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length15.219427
Min length11

Characters and Unicode

Total characters126443
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1574 ?
Unique (%)18.9%

Sample

1st row2111-WD-XPP0K01
2nd row2111-WD-XPP0K01
3rd row2111-WD-XPPWEP1
4th row2111-WD-XPPWEP1
5th row2111-WD-XPPWEP2A
ValueCountFrequency (%)
2135-451-m-pp06 4
 
< 0.1%
2712-633-m-pp02b 4
 
< 0.1%
2135-451-m-pp05 4
 
< 0.1%
2435-633-m-pp02b 2
 
< 0.1%
2436-451-m-pp03 2
 
< 0.1%
2435-634-m-pp05 2
 
< 0.1%
2435-614-m-ah11 2
 
< 0.1%
2435-614-m-ah12 2
 
< 0.1%
2435-632-m-pp03 2
 
< 0.1%
2435-632-m-pp04 2
 
< 0.1%
Other values (4928) 8282
99.7%
2023-12-12T08:09:48.979578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 23595
18.7%
2 16859
13.3%
1 13539
10.7%
0 9869
7.8%
3 9800
7.8%
P 7690
 
6.1%
M 6315
 
5.0%
4 6181
 
4.9%
6 5822
 
4.6%
5 5617
 
4.4%
Other values (28) 21156
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73067
57.8%
Uppercase Letter 29733
23.5%
Dash Punctuation 23595
 
18.7%
Lowercase Letter 48
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 7690
25.9%
M 6315
21.2%
A 3912
13.2%
H 2712
 
9.1%
C 1466
 
4.9%
B 1237
 
4.2%
V 1101
 
3.7%
G 658
 
2.2%
O 622
 
2.1%
F 531
 
1.8%
Other values (16) 3489
11.7%
Decimal Number
ValueCountFrequency (%)
2 16859
23.1%
1 13539
18.5%
0 9869
13.5%
3 9800
13.4%
4 6181
 
8.5%
6 5822
 
8.0%
5 5617
 
7.7%
7 2437
 
3.3%
8 1684
 
2.3%
9 1259
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 23595
100.0%
Lowercase Letter
ValueCountFrequency (%)
p 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96662
76.4%
Latin 29781
 
23.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 7690
25.8%
M 6315
21.2%
A 3912
13.1%
H 2712
 
9.1%
C 1466
 
4.9%
B 1237
 
4.2%
V 1101
 
3.7%
G 658
 
2.2%
O 622
 
2.1%
F 531
 
1.8%
Other values (17) 3537
11.9%
Common
ValueCountFrequency (%)
- 23595
24.4%
2 16859
17.4%
1 13539
14.0%
0 9869
10.2%
3 9800
10.1%
4 6181
 
6.4%
6 5822
 
6.0%
5 5617
 
5.8%
7 2437
 
2.5%
8 1684
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 126443
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 23595
18.7%
2 16859
13.3%
1 13539
10.7%
0 9869
7.8%
3 9800
7.8%
P 7690
 
6.1%
M 6315
 
5.0%
4 6181
 
4.9%
6 5822
 
4.6%
5 5617
 
4.4%
Other values (28) 21156
16.7%

진단기법
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.0 KiB
진동
8308 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row진동
2nd row진동
3rd row진동
4th row진동
5th row진동

Common Values

ValueCountFrequency (%)
진동 8308
100.0%

Length

2023-12-12T08:09:49.158080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:09:49.263498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진동 8308
100.0%

열화상
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.0 KiB
<NA>
7256 
열화상
1052 

Length

Max length4
Median length4
Mean length3.8733751
Min length3

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> 7256
87.3%
열화상 1052
 
12.7%

Length

2023-12-12T08:09:49.391972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:09:49.551856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7256
87.3%
열화상 1052
 
12.7%

발전소
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size65.0 KiB
신한울1발
872 
한빛3발
853 
새울1발
765 
한울3발
744 
한빛2발
724 
Other values (9)
4350 

Length

Max length5
Median length4
Mean length4.1049591
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고리1발
2nd row고리1발
3rd row고리1발
4th row고리1발
5th row고리1발

Common Values

ValueCountFrequency (%)
신한울1발 872
10.5%
한빛3발 853
10.3%
새울1발 765
9.2%
한울3발 744
9.0%
한빛2발 724
8.7%
한울2발 696
8.4%
고리3발 668
8.0%
월성3발 627
7.5%
한울1발 614
7.4%
고리2발 536
6.5%
Other values (4) 1209
14.6%

Length

2023-12-12T08:09:49.715045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신한울1발 872
10.5%
한빛3발 853
10.3%
새울1발 765
9.2%
한울3발 744
9.0%
한빛2발 724
8.7%
한울2발 696
8.4%
고리3발 668
8.0%
월성3발 627
7.5%
한울1발 614
7.4%
고리2발 536
6.5%
Other values (4) 1209
14.6%

완료연도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.0 KiB
2020
5293 
2019
2898 
완료
 
117

Length

Max length4
Median length4
Mean length3.9718344
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 5293
63.7%
2019 2898
34.9%
완료 117
 
1.4%

Length

2023-12-12T08:09:49.877095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:09:50.024856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 5293
63.7%
2019 2898
34.9%
완료 117
 
1.4%

Interactions

2023-12-12T08:09:46.492084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:09:50.110993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호발전소완료연도
번호1.0000.9700.667
발전소0.9701.0000.801
완료연도0.6670.8011.000
2023-12-12T08:09:50.191916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발전소완료연도열화상
발전소1.0000.6501.000
완료연도0.6501.0001.000
열화상1.0001.0001.000
2023-12-12T08:09:50.280010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호열화상발전소완료연도
번호1.0001.0000.8710.518
열화상1.0001.0001.0001.000
발전소0.8711.0001.0000.650
완료연도0.5181.0000.6501.000

Missing values

2023-12-12T08:09:46.659384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:09:46.793202image/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

번호기기명기능위치진단기법열화상발전소완료연도
01LRS Auxiliary Feed Pump2111-WD-XPP0K01진동<NA>고리1발2020
12LRS Auxiliary Feed Pump MTR2111-WD-XPP0K01진동<NA>고리1발2020
23LRS Recirculation Pump2111-WD-XPPWEP1진동<NA>고리1발2020
34LRS Recirculation Pump MTR2111-WD-XPPWEP1진동<NA>고리1발2020
45LRS Distillate Pump2111-WD-XPPWEP2A진동<NA>고리1발2020
56LRS Distillate Pump MTR2111-WD-XPPWEP2A진동<NA>고리1발2020
67AUXILIARY FEEDWATER TURBINE DRIVE PP2112-AF-101PMP03C진동<NA>고리1발2020
78AUXILIARY FEEDWATER TURBINE DRIVE PP TBN2112-AF-101PMP03CTBN진동<NA>고리1발2020
89AFP A MTR DRIVEN AUX FEED WATER PP2112-AF-102PMP01A진동<NA>고리1발2020
910AFP A MTR DRIVEN AUX FEED WATER PP MTR2112-AF-102PMP01A진동<NA>고리1발2020
번호기기명기능위치진단기법열화상발전소완료연도
82988299Essential Chilled Water Pump MTR2712-633-M-PP02B진동<NA>신한울1발2020
82998300Essential Chilled Water Pump2712-633-M-PP02B진동<NA>신한울1발2020
83008301CL SEAWTR SPLY PP A(U1)2712-645-M-PP01진동<NA>신한울1발2020
83018302CL SEAWTR SPLY PP A MTR2712-645-M-PP01진동<NA>신한울1발2020
83028303CL SEAWTR SPLY PP B(U1)2712-645-M-PP02진동<NA>신한울1발2020
83038304CL SEAWTR SPLY PP B MTR2712-645-M-PP02진동<NA>신한울1발2020
83048305MOTOR DRIVEN SEISMIC CAT.1 FIRE PUMP2712-691-M-PP05진동<NA>신한울1발2020
83058306MTR DRIVEN SEISMIC CAT 1 FIRE PP MTR2712-691-M-PP05진동<NA>신한울1발2020
83068307MOTOR DRIVEN SEISMIC CAT.1 FIRE PUMP2712-691-M-PP06진동<NA>신한울1발2020
83078308MTR DRIVEN SEISMIC CAT 1 FIRE PP MTR2712-691-M-PP06진동<NA>신한울1발2020