Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.7 KiB
Average record size in memory68.3 B

Variable types

Categorical3
Text4
Numeric1

Alerts

운영일자 has constant value ""Constant
발전소구분명 is highly overall correlated with 발전소구분코드High correlation
발전소구분코드 is highly overall correlated with 발전소구분명High correlation
발전소코드 has unique valuesUnique
발전소명 has unique valuesUnique
달성률 has 25 (25.0%) zerosZeros

Reproduction

Analysis started2023-12-10 12:01:04.541941
Analysis finished2023-12-10 12:01:05.441133
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

운영일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
202101
100 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202101
2nd row202101
3rd row202101
4th row202101
5th row202101

Common Values

ValueCountFrequency (%)
202101 100
100.0%

Length

2023-12-10T21:01:05.522460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:01:05.708711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202101 100
100.0%

발전소코드
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:01:06.060472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters400
Distinct characters13
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

Unique100 ?
Unique (%)100.0%

Sample

1st row5572
2nd row9713
3rd row1221
4th row5536
5th row1997
ValueCountFrequency (%)
5572 1
 
1.0%
1212 1
 
1.0%
1100 1
 
1.0%
1090 1
 
1.0%
1070 1
 
1.0%
1334 1
 
1.0%
1227 1
 
1.0%
1226 1
 
1.0%
1224 1
 
1.0%
1223 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T21:01:06.616905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 117
29.2%
2 48
12.0%
3 43
 
10.8%
4 35
 
8.8%
5 31
 
7.8%
9 29
 
7.2%
0 28
 
7.0%
7 25
 
6.2%
8 21
 
5.2%
6 16
 
4.0%
Other values (3) 7
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 393
98.2%
Uppercase Letter 7
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 117
29.8%
2 48
12.2%
3 43
 
10.9%
4 35
 
8.9%
5 31
 
7.9%
9 29
 
7.4%
0 28
 
7.1%
7 25
 
6.4%
8 21
 
5.3%
6 16
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 4
57.1%
A 2
28.6%
K 1
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 393
98.2%
Latin 7
 
1.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 117
29.8%
2 48
12.2%
3 43
 
10.9%
4 35
 
8.9%
5 31
 
7.9%
9 29
 
7.4%
0 28
 
7.1%
7 25
 
6.4%
8 21
 
5.3%
6 16
 
4.1%
Latin
ValueCountFrequency (%)
B 4
57.1%
A 2
28.6%
K 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 117
29.2%
2 48
12.0%
3 43
 
10.8%
4 35
 
8.8%
5 31
 
7.8%
9 29
 
7.2%
0 28
 
7.0%
7 25
 
6.2%
8 21
 
5.2%
6 16
 
4.0%
Other values (3) 7
 
1.8%

발전소명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:01:06.953267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length7.33
Min length4

Characters and Unicode

Total characters733
Distinct characters129
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

Unique100 ?
Unique (%)100.0%

Sample

1st row대청댐소수력#2
2nd row석성태양광
3rd row대청댐소수력#1
4th row일산정수장소수력
5th row덕소(정)태양광
ValueCountFrequency (%)
철거 4
 
3.5%
제2태양광 2
 
1.8%
태양광 2
 
1.8%
시흥(정)태양광#2 1
 
0.9%
대청수력 1
 
0.9%
소양강수력 1
 
0.9%
공주보소수력 1
 
0.9%
이포보소수력 1
 
0.9%
상주보소수력 1
 
0.9%
구미보소수력 1
 
0.9%
Other values (98) 98
86.7%
2023-12-10T21:01:07.492560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 82
 
11.2%
력 68
 
9.3%
소 59
 
8.0%
양 38
 
5.2%
광 34
 
4.6%
태 32
 
4.4%
보 22
 
3.0%
정 20
 
2.7%
( 18
 
2.5%
) 18
 
2.5%
Other values (119) 342
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 626
85.4%
Decimal Number 32
 
4.4%
Open Punctuation 18
 
2.5%
Close Punctuation 18
 
2.5%
Other Punctuation 15
 
2.0%
Space Separator 13
 
1.8%
Lowercase Letter 5
 
0.7%
Modifier Symbol 4
 
0.5%
Uppercase Letter 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 82
 
13.1%
력 68
 
10.9%
소 59
 
9.4%
양 38
 
6.1%
광 34
 
5.4%
태 32
 
5.1%
보 22
 
3.5%
정 20
 
3.2%
주 12
 
1.9%
제 11
 
1.8%
Other values (98) 248
39.6%
Decimal Number
ValueCountFrequency (%)
1 13
40.6%
2 11
34.4%
9 3
 
9.4%
3 2
 
6.2%
5 1
 
3.1%
4 1
 
3.1%
7 1
 
3.1%
Lowercase Letter
ValueCountFrequency (%)
a 1
20.0%
w 1
20.0%
t 1
20.0%
e 1
20.0%
r 1
20.0%
Other Punctuation
ValueCountFrequency (%)
# 7
46.7%
. 4
26.7%
, 4
26.7%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 626
85.4%
Common 101
 
13.8%
Latin 6
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 82
 
13.1%
력 68
 
10.9%
소 59
 
9.4%
양 38
 
6.1%
광 34
 
5.4%
태 32
 
5.1%
보 22
 
3.5%
정 20
 
3.2%
주 12
 
1.9%
제 11
 
1.8%
Other values (98) 248
39.6%
Common
ValueCountFrequency (%)
( 18
17.8%
) 18
17.8%
1 13
12.9%
13
12.9%
2 11
10.9%
# 7
 
6.9%
. 4
 
4.0%
` 4
 
4.0%
, 4
 
4.0%
9 3
 
3.0%
Other values (5) 6
 
5.9%
Latin
ValueCountFrequency (%)
a 1
16.7%
K 1
16.7%
w 1
16.7%
t 1
16.7%
e 1
16.7%
r 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 626
85.4%
ASCII 107
 
14.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 82
 
13.1%
력 68
 
10.9%
소 59
 
9.4%
양 38
 
6.1%
광 34
 
5.4%
태 32
 
5.1%
보 22
 
3.5%
정 20
 
3.2%
주 12
 
1.9%
제 11
 
1.8%
Other values (98) 248
39.6%
ASCII
ValueCountFrequency (%)
( 18
16.8%
) 18
16.8%
1 13
12.1%
13
12.1%
2 11
10.3%
# 7
 
6.5%
. 4
 
3.7%
` 4
 
3.7%
, 4
 
3.7%
9 3
 
2.8%
Other values (11) 12
11.2%

계획값
Text

Distinct73
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:01:07.750586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5
Min length1

Characters and Unicode

Total characters250
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)63.0%

Sample

1st row206
2nd row16
3rd row70
4th row43
5th row29
ValueCountFrequency (%)
0 17
 
17.0%
10 3
 
3.0%
55 3
 
3.0%
26 2
 
2.0%
62 2
 
2.0%
43 2
 
2.0%
53 2
 
2.0%
25 2
 
2.0%
11 2
 
2.0%
6 2
 
2.0%
Other values (63) 63
63.0%
2023-12-10T21:01:08.176537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 34
13.6%
1 32
12.8%
0 30
12.0%
3 27
10.8%
6 26
10.4%
5 23
9.2%
4 18
7.2%
8 18
7.2%
, 16
6.4%
7 14
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 234
93.6%
Other Punctuation 16
 
6.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 34
14.5%
1 32
13.7%
0 30
12.8%
3 27
11.5%
6 26
11.1%
5 23
9.8%
4 18
7.7%
8 18
7.7%
7 14
6.0%
9 12
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 250
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 34
13.6%
1 32
12.8%
0 30
12.0%
3 27
10.8%
6 26
10.4%
5 23
9.2%
4 18
7.2%
8 18
7.2%
, 16
6.4%
7 14
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 34
13.6%
1 32
12.8%
0 30
12.0%
3 27
10.8%
6 26
10.4%
5 23
9.2%
4 18
7.2%
8 18
7.2%
, 16
6.4%
7 14
5.6%

실적값
Text

Distinct76
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:01:08.425595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.47
Min length1

Characters and Unicode

Total characters247
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)69.0%

Sample

1st row0
2nd row11
3rd row159
4th row44
5th row30
ValueCountFrequency (%)
0 19
 
19.0%
12 2
 
2.0%
8 2
 
2.0%
10 2
 
2.0%
1 2
 
2.0%
6 2
 
2.0%
11 2
 
2.0%
664 1
 
1.0%
1,051 1
 
1.0%
7,180 1
 
1.0%
Other values (66) 66
66.0%
2023-12-10T21:01:08.865547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 38
15.4%
0 35
14.2%
2 33
13.4%
6 25
10.1%
4 23
9.3%
5 19
7.7%
8 18
7.3%
9 16
6.5%
3 15
 
6.1%
, 15
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 232
93.9%
Other Punctuation 15
 
6.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 38
16.4%
0 35
15.1%
2 33
14.2%
6 25
10.8%
4 23
9.9%
5 19
8.2%
8 18
7.8%
9 16
6.9%
3 15
 
6.5%
7 10
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 247
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 38
15.4%
0 35
14.2%
2 33
13.4%
6 25
10.1%
4 23
9.3%
5 19
7.7%
8 18
7.3%
9 16
6.5%
3 15
 
6.1%
, 15
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 247
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 38
15.4%
0 35
14.2%
2 33
13.4%
6 25
10.1%
4 23
9.3%
5 19
7.7%
8 18
7.3%
9 16
6.5%
3 15
 
6.1%
, 15
 
6.1%

달성률
Real number (ℝ)

ZEROS 

Distinct72
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.702
Minimum0
Maximum6220
Zeros25
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:01:09.058776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.125
median87.85
Q3102.575
95-th percentile212.185
Maximum6220
Range6220
Interquartile range (IQR)95.45

Descriptive statistics

Standard deviation637.31408
Coefficient of variation (CV)4.067045
Kurtosis85.194302
Mean156.702
Median Absolute Deviation (MAD)33.45
Skewness9.0158827
Sum15670.2
Variance406169.24
MonotonicityNot monotonic
2023-12-10T21:01:09.244555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 25
25.0%
100.0 4
 
4.0%
92.0 2
 
2.0%
88.6 1
 
1.0%
89.3 1
 
1.0%
100.6 1
 
1.0%
144.9 1
 
1.0%
39.2 1
 
1.0%
99.5 1
 
1.0%
117.1 1
 
1.0%
Other values (62) 62
62.0%
ValueCountFrequency (%)
0.0 25
25.0%
9.5 1
 
1.0%
10.0 1
 
1.0%
12.9 1
 
1.0%
16.7 1
 
1.0%
18.2 1
 
1.0%
39.2 1
 
1.0%
41.0 1
 
1.0%
53.3 1
 
1.0%
66.2 1
 
1.0%
ValueCountFrequency (%)
6220.0 1
1.0%
1691.5 1
1.0%
477.4 1
1.0%
233.3 1
1.0%
227.1 1
1.0%
211.4 1
1.0%
200.7 1
1.0%
190.7 1
1.0%
185.4 1
1.0%
173.1 1
1.0%

발전소구분코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2
42 
4
32 
7
16 
1
9 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row2
2nd row4
3rd row2
4th row2
5th row4

Common Values

ValueCountFrequency (%)
2 42
42.0%
4 32
32.0%
7 16
 
16.0%
1 9
 
9.0%
3 1
 
1.0%

Length

2023-12-10T21:01:09.418584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:01:09.561779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 42
42.0%
4 32
32.0%
7 16
 
16.0%
1 9
 
9.0%
3 1
 
1.0%

발전소구분명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
소수력
42 
태양광
32 
4대강
16 
대수력
9 
조력
 
1

Length

Max length3
Median length3
Mean length2.99
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row소수력
2nd row태양광
3rd row소수력
4th row소수력
5th row태양광

Common Values

ValueCountFrequency (%)
소수력 42
42.0%
태양광 32
32.0%
4대강 16
 
16.0%
대수력 9
 
9.0%
조력 1
 
1.0%

Length

2023-12-10T21:01:09.699668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:01:09.898109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소수력 42
42.0%
태양광 32
32.0%
4대강 16
 
16.0%
대수력 9
 
9.0%
조력 1
 
1.0%

Interactions

2023-12-10T21:01:05.103537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:01:10.010096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발전소코드발전소명계획값실적값달성률발전소구분코드발전소구분명
발전소코드1.0001.0001.0001.0001.0001.0001.000
발전소명1.0001.0001.0001.0001.0001.0001.000
계획값1.0001.0001.0000.9891.0000.9310.931
실적값1.0001.0000.9891.0001.0000.9360.936
달성률1.0001.0001.0001.0001.0000.0000.000
발전소구분코드1.0001.0000.9310.9360.0001.0001.000
발전소구분명1.0001.0000.9310.9360.0001.0001.000
2023-12-10T21:01:10.164416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발전소구분명발전소구분코드
발전소구분명1.0001.000
발전소구분코드1.0001.000
2023-12-10T21:01:10.267179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
달성률발전소구분코드발전소구분명
달성률1.0000.0000.000
발전소구분코드0.0001.0001.000
발전소구분명0.0001.0001.000

Missing values

2023-12-10T21:01:05.227286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:01:05.365217image/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

운영일자발전소코드발전소명계획값실적값달성률발전소구분코드발전소구분명
02021015572대청댐소수력#220600.02소수력
12021019713석성태양광161168.84태양광
22021011221대청댐소수력#170159227.12소수력
32021015536일산정수장소수력4344102.32소수력
42021011997덕소(정)태양광2930103.44태양광
52021018712합천댐수상태양광10110.04태양광
62021011333세종보소수력000.074대강
72021011211달방소수력22418.22소수력
82021011341용담소수력제1호기 (철거, `19.4)000.02소수력
92021014973용담고산소수력000.02소수력
운영일자발전소코드발전소명계획값실적값달성률발전소구분코드발전소구분명
902021011851부항댐소수력238388163.02소수력
912021011916영주댐소수력06400.02소수력
922021014509보현산댐소수력4382190.72소수력
932021014628섬진강댐소수력477951691.52소수력
942021018933군위소수력5584152.72소수력
95202101A462용담3소수력9981,570157.32소수력
96202101BBBB충주조정지소수력41700.02소수력
972021018811시화호조력36,35239,502108.73조력
982021019992광명(가) 태양광000.04태양광
992021019715대불태양광181266.74태양광