Overview

Dataset statistics

Number of variables8
Number of observations511
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.2%
Total size in memory33.1 KiB
Average record size in memory66.3 B

Variable types

Categorical1
Text5
Numeric2

Dataset

Description한국남동발전 환경화학 시스템 내 변압기 운영 정보 데이터입니다. 사업소에 따른 변압기 기기명, 제작사, 제작연도, 용량 등의 데이터를 포함하고 있습니다.
Author한국남동발전㈜
URLhttps://www.data.go.kr/data/15093181/fileData.do

Alerts

Dataset has 1 (0.2%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 21:00:50.682926
Analysis finished2023-12-12 21:00:51.736384
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업소명
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
삼천포발전본부
202 
영흥발전본부
165 
영동에코발전본부
67 
여수발전본부
40 
분당발전본부
24 

Length

Max length8
Median length7
Mean length6.6829746
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
삼천포발전본부 202
39.5%
영흥발전본부 165
32.3%
영동에코발전본부 67
 
13.1%
여수발전본부 40
 
7.8%
분당발전본부 24
 
4.7%
무주양수발전처 13
 
2.5%

Length

2023-12-13T06:00:51.821887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:00:51.958131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
삼천포발전본부 202
39.5%
영흥발전본부 165
32.3%
영동에코발전본부 67
 
13.1%
여수발전본부 40
 
7.8%
분당발전본부 24
 
4.7%
무주양수발전처 13
 
2.5%

기기명
Text

Distinct502
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T06:00:52.255140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length25
Mean length14.307241
Min length6

Characters and Unicode

Total characters7311
Distinct characters144
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

Unique493 ?
Unique (%)96.5%

Sample

1st row#1,2 EP Si-Tr 예비기
2nd row#1 EPSi-TR-A1-1
3rd row#1 EPSi-TR-A1-2
4th row#1 EPSI-TR-A1-3
5th row#1 EPSi-TR-A2-1
ValueCountFrequency (%)
1 96
 
7.7%
2 91
 
7.3%
si-tr 67
 
5.4%
3 42
 
3.4%
4 37
 
3.0%
1,2 28
 
2.3%
ep 25
 
2.0%
sa용 24
 
1.9%
condenser 24
 
1.9%
g/t 20
 
1.6%
Other values (426) 789
63.5%
2023-12-13T06:00:52.782235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
733
 
10.0%
- 519
 
7.1%
# 422
 
5.8%
1 364
 
5.0%
T 360
 
4.9%
2 340
 
4.7%
S 302
 
4.1%
0 215
 
2.9%
E 209
 
2.9%
r 209
 
2.9%
Other values (134) 3638
49.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1950
26.7%
Decimal Number 1617
22.1%
Other Letter 1101
15.1%
Space Separator 733
 
10.0%
Lowercase Letter 604
 
8.3%
Other Punctuation 524
 
7.2%
Dash Punctuation 519
 
7.1%
Open Punctuation 130
 
1.8%
Close Punctuation 130
 
1.8%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 180
 
16.3%
변 102
 
9.3%
압 99
 
9.0%
용 85
 
7.7%
해 36
 
3.3%
상 33
 
3.0%
리 30
 
2.7%
비 29
 
2.6%
호 29
 
2.6%
조 28
 
2.5%
Other values (72) 450
40.9%
Uppercase Letter
ValueCountFrequency (%)
T 360
18.5%
S 302
15.5%
E 209
10.7%
A 198
10.2%
P 186
9.5%
R 160
8.2%
B 146
7.5%
M 89
 
4.6%
C 82
 
4.2%
N 39
 
2.0%
Other values (14) 179
9.2%
Lowercase Letter
ValueCountFrequency (%)
r 209
34.6%
i 193
32.0%
e 47
 
7.8%
n 30
 
5.0%
p 20
 
3.3%
t 18
 
3.0%
o 17
 
2.8%
s 14
 
2.3%
c 12
 
2.0%
d 12
 
2.0%
Other values (9) 32
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 364
22.5%
2 340
21.0%
0 215
13.3%
4 194
12.0%
3 182
11.3%
6 85
 
5.3%
5 85
 
5.3%
7 58
 
3.6%
9 53
 
3.3%
8 41
 
2.5%
Other Punctuation
ValueCountFrequency (%)
# 422
80.5%
/ 46
 
8.8%
, 42
 
8.0%
. 14
 
2.7%
Space Separator
ValueCountFrequency (%)
733
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 519
100.0%
Open Punctuation
ValueCountFrequency (%)
( 130
100.0%
Close Punctuation
ValueCountFrequency (%)
) 130
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3656
50.0%
Latin 2554
34.9%
Hangul 1101
 
15.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 180
 
16.3%
변 102
 
9.3%
압 99
 
9.0%
용 85
 
7.7%
해 36
 
3.3%
상 33
 
3.0%
리 30
 
2.7%
비 29
 
2.6%
호 29
 
2.6%
조 28
 
2.5%
Other values (72) 450
40.9%
Latin
ValueCountFrequency (%)
T 360
14.1%
S 302
11.8%
E 209
8.2%
r 209
8.2%
A 198
 
7.8%
i 193
 
7.6%
P 186
 
7.3%
R 160
 
6.3%
B 146
 
5.7%
M 89
 
3.5%
Other values (33) 502
19.7%
Common
ValueCountFrequency (%)
733
20.0%
- 519
14.2%
# 422
11.5%
1 364
10.0%
2 340
9.3%
0 215
 
5.9%
4 194
 
5.3%
3 182
 
5.0%
( 130
 
3.6%
) 130
 
3.6%
Other values (9) 427
11.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6210
84.9%
Hangul 1101
 
15.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
733
 
11.8%
- 519
 
8.4%
# 422
 
6.8%
1 364
 
5.9%
T 360
 
5.8%
2 340
 
5.5%
S 302
 
4.9%
0 215
 
3.5%
E 209
 
3.4%
r 209
 
3.4%
Other values (52) 2537
40.9%
Hangul
ValueCountFrequency (%)
기 180
 
16.3%
변 102
 
9.3%
압 99
 
9.0%
용 85
 
7.7%
해 36
 
3.3%
상 33
 
3.0%
리 30
 
2.7%
비 29
 
2.6%
호 29
 
2.6%
조 28
 
2.5%
Other values (72) 450
40.9%

제작사
Text

Distinct54
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T06:00:52.980549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length4.5479452
Min length2

Characters and Unicode

Total characters2324
Distinct characters93
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)4.5%

Sample

1st rowNWL퍼시픽
2nd row한국중공업
3rd row한국중공업
4th row한국중공업
5th row한국중공업
ValueCountFrequency (%)
국제전기 89
16.4%
halla 64
11.8%
현대 59
10.8%
현대중공업 36
 
6.6%
효성 30
 
5.5%
코트렐 28
 
5.1%
태화에레마 25
 
4.6%
abb 24
 
4.4%
한국중공업 24
 
4.4%
electric 21
 
3.9%
Other values (48) 144
26.5%
2023-12-13T06:00:53.390419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 160
 
6.9%
L 146
 
6.3%
전 129
 
5.6%
국 127
 
5.5%
기 124
 
5.3%
대 111
 
4.8%
현 95
 
4.1%
제 90
 
3.9%
H 88
 
3.8%
업 71
 
3.1%
Other values (83) 1183
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1444
62.1%
Uppercase Letter 758
32.6%
Lowercase Letter 68
 
2.9%
Space Separator 33
 
1.4%
Close Punctuation 10
 
0.4%
Open Punctuation 8
 
0.3%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 129
 
8.9%
국 127
 
8.8%
기 124
 
8.6%
대 111
 
7.7%
현 95
 
6.6%
제 90
 
6.2%
업 71
 
4.9%
중 71
 
4.9%
공 70
 
4.8%
화 48
 
3.3%
Other values (48) 508
35.2%
Uppercase Letter
ValueCountFrequency (%)
A 160
21.1%
L 146
19.3%
H 88
11.6%
E 68
9.0%
B 48
 
6.3%
I 47
 
6.2%
C 44
 
5.8%
S 37
 
4.9%
R 34
 
4.5%
T 23
 
3.0%
Other values (10) 63
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
c 12
17.6%
e 10
14.7%
r 8
11.8%
t 8
11.8%
n 6
8.8%
i 6
8.8%
l 6
8.8%
u 4
 
5.9%
o 4
 
5.9%
a 2
 
2.9%
Space Separator
ValueCountFrequency (%)
33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1444
62.1%
Latin 826
35.5%
Common 54
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 129
 
8.9%
국 127
 
8.8%
기 124
 
8.6%
대 111
 
7.7%
현 95
 
6.6%
제 90
 
6.2%
업 71
 
4.9%
중 71
 
4.9%
공 70
 
4.8%
화 48
 
3.3%
Other values (48) 508
35.2%
Latin
ValueCountFrequency (%)
A 160
19.4%
L 146
17.7%
H 88
10.7%
E 68
8.2%
B 48
 
5.8%
I 47
 
5.7%
C 44
 
5.3%
S 37
 
4.5%
R 34
 
4.1%
T 23
 
2.8%
Other values (21) 131
15.9%
Common
ValueCountFrequency (%)
33
61.1%
) 10
 
18.5%
( 8
 
14.8%
. 3
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1444
62.1%
ASCII 880
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 160
18.2%
L 146
16.6%
H 88
10.0%
E 68
 
7.7%
B 48
 
5.5%
I 47
 
5.3%
C 44
 
5.0%
S 37
 
4.2%
R 34
 
3.9%
33
 
3.8%
Other values (25) 175
19.9%
Hangul
ValueCountFrequency (%)
전 129
 
8.9%
국 127
 
8.8%
기 124
 
8.6%
대 111
 
7.7%
현 95
 
6.6%
제 90
 
6.2%
업 71
 
4.9%
중 71
 
4.9%
공 70
 
4.8%
화 48
 
3.3%
Other values (48) 508
35.2%

제작연도
Real number (ℝ)

Distinct29
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1998.7886
Minimum1969
Maximum2011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-13T06:00:53.569357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1969
5-th percentile1981.5
Q11994
median2002
Q32006
95-th percentile2008
Maximum2011
Range42
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.8194296
Coefficient of variation (CV)0.0039120842
Kurtosis1.0731949
Mean1998.7886
Median Absolute Deviation (MAD)5
Skewness-0.98752128
Sum1021381
Variance61.143479
MonotonicityNot monotonic
2023-12-13T06:00:53.738389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
2003 66
12.9%
1995 61
11.9%
2006 58
11.4%
2002 43
8.4%
2007 42
8.2%
1991 37
 
7.2%
1994 34
 
6.7%
1999 28
 
5.5%
1992 27
 
5.3%
2005 14
 
2.7%
Other values (19) 101
19.8%
ValueCountFrequency (%)
1969 3
 
0.6%
1970 1
 
0.2%
1978 10
2.0%
1979 2
 
0.4%
1981 10
2.0%
1982 1
 
0.2%
1983 1
 
0.2%
1984 3
 
0.6%
1985 4
 
0.8%
1989 4
 
0.8%
ValueCountFrequency (%)
2011 1
 
0.2%
2010 13
 
2.5%
2009 11
 
2.2%
2008 5
 
1.0%
2007 42
8.2%
2006 58
11.4%
2005 14
 
2.7%
2004 11
 
2.2%
2003 66
12.9%
2002 43
8.4%

용량
Text

Distinct108
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T06:00:54.101585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length4.6966732
Min length1

Characters and Unicode

Total characters2400
Distinct characters17
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)6.3%

Sample

1st row저압151.6
2nd row저압151.6
3rd row저압151.6
4th row저압151.6
5th row저압151.6
ValueCountFrequency (%)
130 40
 
7.8%
161.5 40
 
7.8%
저압140 40
 
7.8%
저압151.6 25
 
4.9%
0.25㎌ 24
 
4.7%
고압2000 14
 
2.7%
40000 12
 
2.3%
293 12
 
2.3%
1500 10
 
2.0%
저압20 10
 
2.0%
Other values (98) 284
55.6%
2023-12-13T06:00:54.566810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 592
24.7%
1 375
15.6%
5 211
 
8.8%
압 202
 
8.4%
저 141
 
5.9%
2 138
 
5.8%
6 133
 
5.5%
. 133
 
5.5%
3 131
 
5.5%
4 115
 
4.8%
Other values (7) 229
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1830
76.2%
Other Letter 404
 
16.8%
Other Punctuation 139
 
5.8%
Other Symbol 24
 
1.0%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 592
32.3%
1 375
20.5%
5 211
 
11.5%
2 138
 
7.5%
6 133
 
7.3%
3 131
 
7.2%
4 115
 
6.3%
8 53
 
2.9%
9 52
 
2.8%
7 30
 
1.6%
Other Letter
ValueCountFrequency (%)
압 202
50.0%
저 141
34.9%
고 61
 
15.1%
Other Punctuation
ValueCountFrequency (%)
. 133
95.7%
/ 6
 
4.3%
Other Symbol
ValueCountFrequency (%)
㎌ 24
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1993
83.0%
Hangul 404
 
16.8%
Latin 3
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 592
29.7%
1 375
18.8%
5 211
 
10.6%
2 138
 
6.9%
6 133
 
6.7%
. 133
 
6.7%
3 131
 
6.6%
4 115
 
5.8%
8 53
 
2.7%
9 52
 
2.6%
Other values (3) 60
 
3.0%
Hangul
ValueCountFrequency (%)
압 202
50.0%
저 141
34.9%
고 61
 
15.1%
Latin
ValueCountFrequency (%)
X 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1972
82.2%
Hangul 404
 
16.8%
CJK Compat 24
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 592
30.0%
1 375
19.0%
5 211
 
10.7%
2 138
 
7.0%
6 133
 
6.7%
. 133
 
6.7%
3 131
 
6.6%
4 115
 
5.8%
8 53
 
2.7%
9 52
 
2.6%
Other values (3) 39
 
2.0%
Hangul
ValueCountFrequency (%)
압 202
50.0%
저 141
34.9%
고 61
 
15.1%
CJK Compat
ValueCountFrequency (%)
㎌ 24
100.0%

총중량
Real number (ℝ)

Distinct111
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.787593
Minimum0
Maximum412
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-13T06:00:54.710213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.16
Q11.88
median2.26
Q36.4
95-th percentile216
Maximum412
Range412
Interquartile range (IQR)4.52

Descriptive statistics

Standard deviation70.78749
Coefficient of variation (CV)2.6425476
Kurtosis14.287762
Mean26.787593
Median Absolute Deviation (MAD)1.06
Skewness3.7121105
Sum13688.46
Variance5010.8687
MonotonicityNot monotonic
2023-12-13T06:00:54.868060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.18 40
 
7.8%
1.8 40
 
7.8%
2.12 32
 
6.3%
0.02 24
 
4.7%
1.88 24
 
4.7%
1.2 23
 
4.5%
2.35 16
 
3.1%
2.7 16
 
3.1%
5.5 16
 
3.1%
2.6 12
 
2.3%
Other values (101) 268
52.4%
ValueCountFrequency (%)
0.0 1
 
0.2%
0.02 24
4.7%
0.16 3
 
0.6%
0.2 1
 
0.2%
0.3 1
 
0.2%
0.35 1
 
0.2%
0.36 1
 
0.2%
0.44 2
 
0.4%
0.54 1
 
0.2%
0.57 1
 
0.2%
ValueCountFrequency (%)
412.0 2
 
0.4%
402.0 2
 
0.4%
385.0 1
 
0.2%
380.0 4
0.8%
372.3 2
 
0.4%
233.2 7
1.4%
230.0 1
 
0.2%
220.0 7
1.4%
212.0 1
 
0.2%
195.0 1
 
0.2%

절연유량
Text

Distinct109
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T06:00:55.109704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length3.4520548
Min length1

Characters and Unicode

Total characters1764
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)8.4%

Sample

1st row0.81
2nd row0.81
3rd row0.81
4th row0.81
5th row0.81
ValueCountFrequency (%)
0.77 64
 
12.5%
0.65 40
 
7.8%
0.86 37
 
7.2%
1.7 28
 
5.5%
0.81 25
 
4.9%
0 15
 
2.9%
0.01 12
 
2.3%
1.18 12
 
2.3%
1.27 12
 
2.3%
31 11
 
2.2%
Other values (99) 255
49.9%
2023-12-13T06:00:55.576755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 426
24.1%
0 337
19.1%
1 210
11.9%
7 203
11.5%
8 136
 
7.7%
5 124
 
7.0%
6 112
 
6.3%
2 71
 
4.0%
4 56
 
3.2%
3 47
 
2.7%
Other values (3) 42
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1336
75.7%
Other Punctuation 426
 
24.1%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 337
25.2%
1 210
15.7%
7 203
15.2%
8 136
10.2%
5 124
 
9.3%
6 112
 
8.4%
2 71
 
5.3%
4 56
 
4.2%
3 47
 
3.5%
9 40
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
g 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 426
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1762
99.9%
Latin 2
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 426
24.2%
0 337
19.1%
1 210
11.9%
7 203
11.5%
8 136
 
7.7%
5 124
 
7.0%
6 112
 
6.4%
2 71
 
4.0%
4 56
 
3.2%
3 47
 
2.7%
Latin
ValueCountFrequency (%)
k 1
50.0%
g 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 426
24.1%
0 337
19.1%
1 210
11.9%
7 203
11.5%
8 136
 
7.7%
5 124
 
7.0%
6 112
 
6.3%
2 71
 
4.0%
4 56
 
3.2%
3 47
 
2.7%
Other values (3) 42
 
2.4%

농도(PCB)
Text

Distinct99
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T06:00:55.878117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.8375734
Min length1

Characters and Unicode

Total characters1450
Distinct characters19
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

Unique76 ?
Unique (%)14.9%

Sample

1st rowND
2nd row3.93
3rd row3.78
4th row4.15
5th row2.75
ValueCountFrequency (%)
nd 200
39.1%
불검출 165
32.3%
미실시 18
 
3.5%
0.18 6
 
1.2%
0.24 5
 
1.0%
0.38 4
 
0.8%
0.14 4
 
0.8%
0.1 3
 
0.6%
0.11 2
 
0.4%
0.17 2
 
0.4%
Other values (89) 102
20.0%
2023-12-13T06:00:56.401059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 200
13.8%
D 200
13.8%
불 165
11.4%
검 165
11.4%
출 165
11.4%
. 126
8.7%
0 80
 
5.5%
1 57
 
3.9%
4 46
 
3.2%
2 35
 
2.4%
Other values (9) 211
14.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 549
37.9%
Uppercase Letter 400
27.6%
Decimal Number 375
25.9%
Other Punctuation 126
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 80
21.3%
1 57
15.2%
4 46
12.3%
2 35
9.3%
3 33
8.8%
5 28
 
7.5%
6 26
 
6.9%
7 25
 
6.7%
8 23
 
6.1%
9 22
 
5.9%
Other Letter
ValueCountFrequency (%)
불 165
30.1%
검 165
30.1%
출 165
30.1%
실 18
 
3.3%
시 18
 
3.3%
미 18
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
N 200
50.0%
D 200
50.0%
Other Punctuation
ValueCountFrequency (%)
. 126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 549
37.9%
Common 501
34.6%
Latin 400
27.6%

Most frequent character per script

Common
ValueCountFrequency (%)
. 126
25.1%
0 80
16.0%
1 57
11.4%
4 46
 
9.2%
2 35
 
7.0%
3 33
 
6.6%
5 28
 
5.6%
6 26
 
5.2%
7 25
 
5.0%
8 23
 
4.6%
Hangul
ValueCountFrequency (%)
불 165
30.1%
검 165
30.1%
출 165
30.1%
실 18
 
3.3%
시 18
 
3.3%
미 18
 
3.3%
Latin
ValueCountFrequency (%)
N 200
50.0%
D 200
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 901
62.1%
Hangul 549
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 200
22.2%
D 200
22.2%
. 126
14.0%
0 80
 
8.9%
1 57
 
6.3%
4 46
 
5.1%
2 35
 
3.9%
3 33
 
3.7%
5 28
 
3.1%
6 26
 
2.9%
Other values (3) 70
 
7.8%
Hangul
ValueCountFrequency (%)
불 165
30.1%
검 165
30.1%
출 165
30.1%
실 18
 
3.3%
시 18
 
3.3%
미 18
 
3.3%

Interactions

2023-12-13T06:00:51.310151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:00:51.143729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:00:51.388709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:00:51.233721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:00:56.527475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업소명제작사제작연도총중량농도(PCB)
사업소명1.0000.9680.6400.4680.837
제작사0.9681.0000.9120.6020.658
제작연도0.6400.9121.0000.2130.866
총중량0.4680.6020.2131.0000.519
농도(PCB)0.8370.6580.8660.5191.000
2023-12-13T06:00:56.639703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제작연도총중량사업소명
제작연도1.000-0.0450.381
총중량-0.0451.0000.301
사업소명0.3810.3011.000

Missing values

2023-12-13T06:00:51.510940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:00:51.675467image/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

사업소명기기명제작사제작연도용량총중량절연유량농도(PCB)
0삼천포발전본부#1,2 EP Si-Tr 예비기NWL퍼시픽2002저압151.62.120.81ND
1삼천포발전본부#1 EPSi-TR-A1-1한국중공업1999저압151.62.120.813.93
2삼천포발전본부#1 EPSi-TR-A1-2한국중공업1999저압151.62.120.813.78
3삼천포발전본부#1 EPSI-TR-A1-3한국중공업1999저압151.62.120.814.15
4삼천포발전본부#1 EPSi-TR-A2-1한국중공업1999저압151.62.120.812.75
5삼천포발전본부#1 EPSi-TR-A2-2한국중공업1999저압151.62.120.814.64
6삼천포발전본부#1 EPSi-TR-A2-3한국중공업1999저압151.62.120.814.71
7삼천포발전본부#1 EPSi-TR-B1-1한국중공업1999저압151.62.120.812.69
8삼천포발전본부#1 EPSi-TR-B1-2한국중공업1999저압151.62.120.813.84
9삼천포발전본부#1 EPSi-TR-B1-3한국중공업1999저압151.62.120.813.93
사업소명기기명제작사제작연도용량총중량절연유량농도(PCB)
501무주양수발전처#2 주변압기 OLTC현대중공업1994380000380.00.72ND
502무주양수발전처#1 소내변압기현대중공업1994375011.53.3ND
503무주양수발전처#2 소내변압기현대중공업1993375011.53.30.23
504무주양수발전처SFC 변압기TAIWAN TATUNG.CO19933500033.627.67ND
505무주양수발전처상부댐 계기용 변압변류기영화산업전기20073X0.0250.160.09ND
506무주양수발전처하부댐 계기용 변압변류기영화산업전기20073X0.0250.160.09ND
507무주양수발전처홍보관 계기용 변압변류기영화산업전기20073X0.0250.160.09ND
508무주양수발전처OF Cable대한전선19934478000.01.63ND
509무주양수발전처D/T 배수변압기한양전기공업199420003.00.73ND
510무주양수발전처비상용변압기현대중공업198120005.51.553.41

Duplicate rows

Most frequently occurring

사업소명기기명제작사제작연도용량총중량절연유량농도(PCB)# duplicates
0영흥발전본부#2 Si-Tr 07AHALLA20021301.880.77불검출2