Overview

Dataset statistics

Number of variables7
Number of observations703
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.3 KiB
Average record size in memory57.2 B

Variable types

Numeric1
Text3
Categorical3

Dataset

Description한국서부발전 신재생(풍력) 발전설비 예방점검기준 데이터 입니다. 제공데이터는 점검번호,설비종류,설비명,점검종류코드,점검주기,점검종류,점검항목 입니다.
URLhttps://www.data.go.kr/data/15067723/fileData.do

Alerts

점검종류 is highly overall correlated with 점검종류코드High correlation
점검종류코드 is highly overall correlated with 점검종류High correlation

Reproduction

Analysis started2023-12-12 14:24:14.641974
Analysis finished2023-12-12 14:24:15.468332
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

점검번호
Real number (ℝ)

Distinct223
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean421041.94
Minimum420155
Maximum421896
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.3 KiB
2023-12-12T23:24:15.554796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum420155
5-th percentile420221
Q1420367
median421235
Q3421543
95-th percentile421795.9
Maximum421896
Range1741
Interquartile range (IQR)1176

Descriptive statistics

Standard deviation561.87981
Coefficient of variation (CV)0.0013344984
Kurtosis-1.5125027
Mean421041.94
Median Absolute Deviation (MAD)451
Skewness-0.21734867
Sum2.9599248 × 108
Variance315708.92
MonotonicityIncreasing
2023-12-12T23:24:15.713243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
420195 11
 
1.6%
421544 10
 
1.4%
421539 10
 
1.4%
421543 10
 
1.4%
421542 10
 
1.4%
421541 10
 
1.4%
421545 10
 
1.4%
421540 10
 
1.4%
420369 8
 
1.1%
420357 8
 
1.1%
Other values (213) 606
86.2%
ValueCountFrequency (%)
420155 2
 
0.3%
420156 2
 
0.3%
420157 2
 
0.3%
420179 2
 
0.3%
420187 1
 
0.1%
420195 11
1.6%
420203 1
 
0.1%
420211 1
 
0.1%
420219 5
0.7%
420220 5
0.7%
ValueCountFrequency (%)
421896 2
0.3%
421895 2
0.3%
421894 2
0.3%
421893 2
0.3%
421892 2
0.3%
421891 2
0.3%
421883 2
0.3%
421875 1
 
0.1%
421867 3
0.4%
421859 1
 
0.1%

설비종류
Text

Distinct64
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
2023-12-12T23:24:15.964312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2812
Distinct characters27
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

Unique10 ?
Unique (%)1.4%

Sample

1st rowWBAT
2nd rowWBAT
3rd rowWBAT
4th rowWBAT
5th rowWBAT
ValueCountFrequency (%)
wmoa 135
19.2%
wpp1 70
 
10.0%
wvv1 70
 
10.0%
wgr1 55
 
7.8%
wocb 30
 
4.3%
wtn3 24
 
3.4%
wivt 21
 
3.0%
weta 15
 
2.1%
wet4 14
 
2.0%
wpi1 14
 
2.0%
Other values (54) 255
36.3%
2023-12-12T23:24:16.303891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
W 736
26.2%
P 231
 
8.2%
1 219
 
7.8%
V 211
 
7.5%
A 193
 
6.9%
O 189
 
6.7%
M 179
 
6.4%
T 134
 
4.8%
E 96
 
3.4%
C 84
 
3.0%
Other values (17) 540
19.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2516
89.5%
Decimal Number 296
 
10.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
W 736
29.3%
P 231
 
9.2%
V 211
 
8.4%
A 193
 
7.7%
O 189
 
7.5%
M 179
 
7.1%
T 134
 
5.3%
E 96
 
3.8%
C 84
 
3.3%
G 83
 
3.3%
Other values (12) 380
15.1%
Decimal Number
ValueCountFrequency (%)
1 219
74.0%
3 24
 
8.1%
2 22
 
7.4%
4 21
 
7.1%
7 10
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 2516
89.5%
Common 296
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
W 736
29.3%
P 231
 
9.2%
V 211
 
8.4%
A 193
 
7.7%
O 189
 
7.5%
M 179
 
7.1%
T 134
 
5.3%
E 96
 
3.8%
C 84
 
3.3%
G 83
 
3.3%
Other values (12) 380
15.1%
Common
ValueCountFrequency (%)
1 219
74.0%
3 24
 
8.1%
2 22
 
7.4%
4 21
 
7.1%
7 10
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2812
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
W 736
26.2%
P 231
 
8.2%
1 219
 
7.8%
V 211
 
7.5%
A 193
 
6.9%
O 189
 
6.7%
M 179
 
6.4%
T 134
 
4.8%
E 96
 
3.4%
C 84
 
3.0%
Other values (17) 540
19.2%

설비명
Text

Distinct202
Distinct (%)28.7%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
2023-12-12T23:24:16.584103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length23.476529
Min length6

Characters and Unicode

Total characters16504
Distinct characters58
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)8.3%

Sample

1st row#1 Blade-A Battery Box
2nd row#1 Blade-A Battery Box
3rd row#1 Blade-B Battery Box
4th row#1 Blade-B Battery Box
5th row#1 Blade-C Battery Box
ValueCountFrequency (%)
1 703
19.7%
yaw 201
 
5.6%
gear 193
 
5.4%
brake 181
 
5.1%
mtr 146
 
4.1%
pp 141
 
4.0%
sys 138
 
3.9%
hyd 121
 
3.4%
assy 108
 
3.0%
oil 99
 
2.8%
Other values (117) 1530
43.0%
2023-12-12T23:24:16.999709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2858
17.3%
e 1203
 
7.3%
a 1047
 
6.3%
r 873
 
5.3%
1 720
 
4.4%
# 703
 
4.3%
Y 568
 
3.4%
o 561
 
3.4%
S 556
 
3.4%
P 523
 
3.2%
Other values (48) 6892
41.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7157
43.4%
Uppercase Letter 4837
29.3%
Space Separator 2858
 
17.3%
Decimal Number 769
 
4.7%
Other Punctuation 725
 
4.4%
Dash Punctuation 158
 
1.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 568
11.7%
S 556
11.5%
P 523
10.8%
G 392
 
8.1%
B 370
 
7.6%
M 312
 
6.5%
R 299
 
6.2%
C 278
 
5.7%
T 217
 
4.5%
L 178
 
3.7%
Other values (14) 1144
23.7%
Lowercase Letter
ValueCountFrequency (%)
e 1203
16.8%
a 1047
14.6%
r 873
12.2%
o 561
7.8%
l 518
7.2%
i 487
6.8%
n 414
 
5.8%
t 395
 
5.5%
d 304
 
4.2%
w 216
 
3.0%
Other values (13) 1139
15.9%
Decimal Number
ValueCountFrequency (%)
1 720
93.6%
2 17
 
2.2%
4 14
 
1.8%
3 14
 
1.8%
6 2
 
0.3%
5 2
 
0.3%
Other Punctuation
ValueCountFrequency (%)
# 703
97.0%
& 17
 
2.3%
/ 5
 
0.7%
Space Separator
ValueCountFrequency (%)
2858
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11994
72.7%
Common 4510
 
27.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1203
 
10.0%
a 1047
 
8.7%
r 873
 
7.3%
Y 568
 
4.7%
o 561
 
4.7%
S 556
 
4.6%
P 523
 
4.4%
l 518
 
4.3%
i 487
 
4.1%
n 414
 
3.5%
Other values (37) 5244
43.7%
Common
ValueCountFrequency (%)
2858
63.4%
1 720
 
16.0%
# 703
 
15.6%
- 158
 
3.5%
2 17
 
0.4%
& 17
 
0.4%
4 14
 
0.3%
3 14
 
0.3%
/ 5
 
0.1%
6 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16504
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2858
17.3%
e 1203
 
7.3%
a 1047
 
6.3%
r 873
 
5.3%
1 720
 
4.4%
# 703
 
4.3%
Y 568
 
3.4%
o 561
 
3.4%
S 556
 
3.4%
P 523
 
3.2%
Other values (48) 6892
41.8%

점검종류코드
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
PM0156
312 
PM0052
105 
PM0168
38 
PM0233
36 
PM0275
 
30
Other values (17)
182 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st rowPM0156
2nd rowPM0156
3rd rowPM0156
4th rowPM0156
5th rowPM0156

Common Values

ValueCountFrequency (%)
PM0156 312
44.4%
PM0052 105
 
14.9%
PM0168 38
 
5.4%
PM0233 36
 
5.1%
PM0275 30
 
4.3%
PM0202 30
 
4.3%
PM0160 27
 
3.8%
PM0172 17
 
2.4%
PM0200 16
 
2.3%
PM0272 16
 
2.3%
Other values (12) 76
 
10.8%

Length

2023-12-12T23:24:17.448200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pm0156 312
44.4%
pm0052 105
 
14.9%
pm0168 38
 
5.4%
pm0233 36
 
5.1%
pm0275 30
 
4.3%
pm0202 30
 
4.3%
pm0160 27
 
3.8%
pm0172 17
 
2.4%
pm0200 16
 
2.3%
pm0272 16
 
2.3%
Other values (12) 76
 
10.8%

점검주기
Categorical

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
월간
295 
반기
234 
분기
107 
주간
66 
년간
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row월간
2nd row반기
3rd row월간
4th row반기
5th row월간

Common Values

ValueCountFrequency (%)
월간 295
42.0%
반기 234
33.3%
분기 107
 
15.2%
주간 66
 
9.4%
년간 1
 
0.1%

Length

2023-12-12T23:24:17.600586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:24:17.732236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
월간 295
42.0%
반기 234
33.3%
분기 107
 
15.2%
주간 66
 
9.4%
년간 1
 
0.1%

점검종류
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
육안 점검
312 
누설점검
105 
이음점검
38 
진동 분석
36 
윤활제 점검
 
30
Other values (17)
182 

Length

Max length9
Median length7
Mean length4.8392603
Min length2

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st row육안 점검
2nd row육안 점검
3rd row육안 점검
4th row육안 점검
5th row육안 점검

Common Values

ValueCountFrequency (%)
육안 점검 312
44.4%
누설점검 105
 
14.9%
이음점검 38
 
5.4%
진동 분석 36
 
5.1%
윤활제 점검 30
 
4.3%
점검 30
 
4.3%
윤활유 유위 점검 27
 
3.8%
일상점검 17
 
2.4%
절연저항 측정 16
 
2.3%
전류측정 16
 
2.3%
Other values (12) 76
 
10.8%

Length

2023-12-12T23:24:17.883536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
점검 414
34.6%
육안 312
26.1%
누설점검 105
 
8.8%
분석 51
 
4.3%
이음점검 38
 
3.2%
진동 36
 
3.0%
윤활제 30
 
2.5%
윤활유 27
 
2.3%
유위 27
 
2.3%
일상점검 17
 
1.4%
Other values (16) 139
 
11.6%

점검항목
Text

Distinct118
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
2023-12-12T23:24:18.159273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length25
Mean length11.881935
Min length4

Characters and Unicode

Total characters8353
Distinct characters216
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

Unique45 ?
Unique (%)6.4%

Sample

1st row축전지 감시(Battery Monitoring)
2nd row셀 검사(Cell Inspection)
3rd row축전지 감시(Battery Monitoring)
4th row셀 검사(Cell Inspection)
5th row축전지 감시(Battery Monitoring)
ValueCountFrequency (%)
점검 311
 
13.8%
및 161
 
7.1%
누설점검 93
 
4.1%
상태 57
 
2.5%
연결부 50
 
2.2%
이완상태 47
 
2.1%
이음 39
 
1.7%
이취 39
 
1.7%
보충 35
 
1.6%
그랜드 35
 
1.6%
Other values (177) 1386
61.5%
2023-12-12T23:24:18.651567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1550
 
18.6%
검 579
 
6.9%
점 554
 
6.6%
상 286
 
3.4%
태 242
 
2.9%
이 186
 
2.2%
부 174
 
2.1%
및 161
 
1.9%
동 141
 
1.7%
설 128
 
1.5%
Other values (206) 4352
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5912
70.8%
Space Separator 1550
 
18.6%
Uppercase Letter 319
 
3.8%
Lowercase Letter 194
 
2.3%
Other Punctuation 143
 
1.7%
Open Punctuation 112
 
1.3%
Close Punctuation 112
 
1.3%
Dash Punctuation 7
 
0.1%
Decimal Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
검 579
 
9.8%
점 554
 
9.4%
상 286
 
4.8%
태 242
 
4.1%
이 186
 
3.1%
부 174
 
2.9%
및 161
 
2.7%
동 141
 
2.4%
설 128
 
2.2%
누 126
 
2.1%
Other values (159) 3335
56.4%
Uppercase Letter
ValueCountFrequency (%)
B 64
20.1%
C 49
15.4%
U 30
9.4%
I 30
9.4%
N 23
 
7.2%
O 22
 
6.9%
V 14
 
4.4%
H 13
 
4.1%
A 13
 
4.1%
G 11
 
3.4%
Other values (9) 50
15.7%
Lowercase Letter
ValueCountFrequency (%)
i 26
13.4%
e 24
12.4%
n 22
11.3%
a 20
10.3%
r 19
9.8%
l 18
9.3%
t 12
6.2%
p 11
5.7%
o 9
 
4.6%
g 8
 
4.1%
Other values (7) 25
12.9%
Other Punctuation
ValueCountFrequency (%)
, 79
55.2%
. 60
42.0%
# 4
 
2.8%
Open Punctuation
ValueCountFrequency (%)
( 110
98.2%
[ 2
 
1.8%
Close Punctuation
ValueCountFrequency (%)
) 110
98.2%
] 2
 
1.8%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%
Space Separator
ValueCountFrequency (%)
1550
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5912
70.8%
Common 1928
 
23.1%
Latin 513
 
6.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
검 579
 
9.8%
점 554
 
9.4%
상 286
 
4.8%
태 242
 
4.1%
이 186
 
3.1%
부 174
 
2.9%
및 161
 
2.7%
동 141
 
2.4%
설 128
 
2.2%
누 126
 
2.1%
Other values (159) 3335
56.4%
Latin
ValueCountFrequency (%)
B 64
 
12.5%
C 49
 
9.6%
U 30
 
5.8%
I 30
 
5.8%
i 26
 
5.1%
e 24
 
4.7%
N 23
 
4.5%
n 22
 
4.3%
O 22
 
4.3%
a 20
 
3.9%
Other values (26) 203
39.6%
Common
ValueCountFrequency (%)
1550
80.4%
( 110
 
5.7%
) 110
 
5.7%
, 79
 
4.1%
. 60
 
3.1%
- 7
 
0.4%
# 4
 
0.2%
1 2
 
0.1%
[ 2
 
0.1%
] 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5912
70.8%
ASCII 2441
29.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1550
63.5%
( 110
 
4.5%
) 110
 
4.5%
, 79
 
3.2%
B 64
 
2.6%
. 60
 
2.5%
C 49
 
2.0%
U 30
 
1.2%
I 30
 
1.2%
i 26
 
1.1%
Other values (37) 333
 
13.6%
Hangul
ValueCountFrequency (%)
검 579
 
9.8%
점 554
 
9.4%
상 286
 
4.8%
태 242
 
4.1%
이 186
 
3.1%
부 174
 
2.9%
및 161
 
2.7%
동 141
 
2.4%
설 128
 
2.2%
누 126
 
2.1%
Other values (159) 3335
56.4%

Interactions

2023-12-12T23:24:15.197648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:24:18.766542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
점검번호설비종류점검종류코드점검주기점검종류
점검번호1.0001.0000.7910.7210.791
설비종류1.0001.0000.9140.9300.914
점검종류코드0.7910.9141.0000.6971.000
점검주기0.7210.9300.6971.0000.697
점검종류0.7910.9141.0000.6971.000
2023-12-12T23:24:18.893580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
점검종류점검종류코드점검주기
점검종류1.0001.0000.430
점검종류코드1.0001.0000.430
점검주기0.4300.4301.000
2023-12-12T23:24:19.007327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
점검번호점검종류코드점검주기점검종류
점검번호1.0000.4370.3800.437
점검종류코드0.4371.0000.4301.000
점검주기0.3800.4301.0000.430
점검종류0.4371.0000.4301.000

Missing values

2023-12-12T23:24:15.314640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:24:15.423837image/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

점검번호설비종류설비명점검종류코드점검주기점검종류점검항목
0420155WBAT#1 Blade-A Battery BoxPM0156월간육안 점검축전지 감시(Battery Monitoring)
1420155WBAT#1 Blade-A Battery BoxPM0156반기육안 점검셀 검사(Cell Inspection)
2420156WBAT#1 Blade-B Battery BoxPM0156월간육안 점검축전지 감시(Battery Monitoring)
3420156WBAT#1 Blade-B Battery BoxPM0156반기육안 점검셀 검사(Cell Inspection)
4420157WBAT#1 Blade-C Battery BoxPM0156월간육안 점검축전지 감시(Battery Monitoring)
5420157WBAT#1 Blade-C Battery BoxPM0156반기육안 점검셀 검사(Cell Inspection)
6420179WCBA#1 GEN Main BRKPM0156년간육안 점검ACB 설정값 검사
7420179WCBA#1 GEN Main BRKPM0202반기점검ACB 구동시간 검사
8420187WCBD#1 Converter SYS MCCBPM0156반기육안 점검동작상태 육안점검
9420195WCBM#1 Gear Oil MTR Drive UnitPM0273분기전압측정MCC 전압 (R-S)
점검번호설비종류설비명점검종류코드점검주기점검종류점검항목
693421892WWTY#1 Yaw Brake Caliper & Pad-2PM0156월간육안 점검Caliper 외관 상태점검
694421892WWTY#1 Yaw Brake Caliper & Pad-2PM0202반기점검볼트 토크 점검
695421893WWTY#1 Yaw Brake Caliper & Pad-3PM0156월간육안 점검Caliper 외관 상태점검
696421893WWTY#1 Yaw Brake Caliper & Pad-3PM0202반기점검볼트 토크 점검
697421894WWTY#1 Yaw Brake Caliper & Pad-4PM0156월간육안 점검Caliper 외관 상태점검
698421894WWTY#1 Yaw Brake Caliper & Pad-4PM0202반기점검볼트 토크 점검
699421895WWTY#1 Yaw Brake Caliper & Pad-5PM0156월간육안 점검Caliper 외관 상태점검
700421895WWTY#1 Yaw Brake Caliper & Pad-5PM0202반기점검볼트 토크 점검
701421896WWTY#1 Yaw Brake Caliper & Pad-6PM0156월간육안 점검Caliper 외관 상태점검
702421896WWTY#1 Yaw Brake Caliper & Pad-6PM0202반기점검볼트 토크 점검