Overview

Dataset statistics

Number of variables3
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory782.0 B
Average record size in memory30.1 B

Variable types

Categorical1
Text1
Numeric1

Dataset

Description한국남동발전 발전소의 각 호기별 열 효율 정보입니다. 발전기별 열효율에 대한 데이터로 발전소, 호기, 열효율 등의 항목을 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15039183/fileData.do

Alerts

열효율 is highly overall correlated with 발전소High correlation
발전소 is highly overall correlated with 열효율High correlation
열효율 has 2 (7.7%) zerosZeros

Reproduction

Analysis started2023-12-11 23:45:24.744349
Analysis finished2023-12-11 23:45:25.036584
Duration0.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

발전소
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
분당 발전본부
10 
삼천포 발전본부
6 
영흥 발전본부
6 
영동에코 발전본부
2 
여수 발전본부
2 

Length

Max length9
Median length7
Mean length7.3846154
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row삼천포 발전본부
2nd row삼천포 발전본부
3rd row삼천포 발전본부
4th row삼천포 발전본부
5th row삼천포 발전본부

Common Values

ValueCountFrequency (%)
분당 발전본부 10
38.5%
삼천포 발전본부 6
23.1%
영흥 발전본부 6
23.1%
영동에코 발전본부 2
 
7.7%
여수 발전본부 2
 
7.7%

Length

2023-12-12T08:45:25.133301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:45:25.284717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
발전본부 26
50.0%
분당 10
 
19.2%
삼천포 6
 
11.5%
영흥 6
 
11.5%
영동에코 2
 
3.8%
여수 2
 
3.8%

호기
Text

Distinct16
Distinct (%)61.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T08:45:25.446042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters78
Distinct characters13
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)38.5%

Sample

1st row1호기
2nd row2호기
3rd row3호기
4th row4호기
5th row5호기
ValueCountFrequency (%)
1호기 4
15.4%
2호기 4
15.4%
3호기 2
 
7.7%
4호기 2
 
7.7%
5호기 2
 
7.7%
6호기 2
 
7.7%
gt1 1
 
3.8%
gt2 1
 
3.8%
gt3 1
 
3.8%
gt4 1
 
3.8%
Other values (6) 6
23.1%
2023-12-12T08:45:25.782375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
호 16
20.5%
기 16
20.5%
T 10
12.8%
G 8
10.3%
1 6
 
7.7%
2 6
 
7.7%
3 3
 
3.8%
4 3
 
3.8%
5 3
 
3.8%
6 3
 
3.8%
Other values (3) 4
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32
41.0%
Decimal Number 26
33.3%
Uppercase Letter 20
25.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6
23.1%
2 6
23.1%
3 3
11.5%
4 3
11.5%
5 3
11.5%
6 3
11.5%
7 1
 
3.8%
8 1
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
T 10
50.0%
G 8
40.0%
S 2
 
10.0%
Other Letter
ValueCountFrequency (%)
호 16
50.0%
기 16
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32
41.0%
Common 26
33.3%
Latin 20
25.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6
23.1%
2 6
23.1%
3 3
11.5%
4 3
11.5%
5 3
11.5%
6 3
11.5%
7 1
 
3.8%
8 1
 
3.8%
Latin
ValueCountFrequency (%)
T 10
50.0%
G 8
40.0%
S 2
 
10.0%
Hangul
ValueCountFrequency (%)
호 16
50.0%
기 16
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46
59.0%
Hangul 32
41.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
호 16
50.0%
기 16
50.0%
ASCII
ValueCountFrequency (%)
T 10
21.7%
G 8
17.4%
1 6
13.0%
2 6
13.0%
3 3
 
6.5%
4 3
 
6.5%
5 3
 
6.5%
6 3
 
6.5%
S 2
 
4.3%
7 1
 
2.2%

열효율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.282308
Minimum0
Maximum39.9
Zeros2
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T08:45:25.900467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.0775
Q129.61
median36.635
Q338.335
95-th percentile39.6225
Maximum39.9
Range39.9
Interquartile range (IQR)8.725

Descriptive statistics

Standard deviation10.336851
Coefficient of variation (CV)0.32020173
Kurtosis6.3768787
Mean32.282308
Median Absolute Deviation (MAD)2.66
Skewness-2.5216861
Sum839.34
Variance106.85048
MonotonicityNot monotonic
2023-12-12T08:45:26.034427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.0 2
 
7.7%
37.19 1
 
3.8%
36.71 1
 
3.8%
29.59 1
 
3.8%
29.99 1
 
3.8%
29.79 1
 
3.8%
29.23 1
 
3.8%
29.6 1
 
3.8%
29.64 1
 
3.8%
29.02 1
 
3.8%
Other values (15) 15
57.7%
ValueCountFrequency (%)
0.0 2
7.7%
28.31 1
3.8%
29.02 1
3.8%
29.23 1
3.8%
29.59 1
3.8%
29.6 1
3.8%
29.64 1
3.8%
29.79 1
3.8%
29.99 1
3.8%
34.33 1
3.8%
ValueCountFrequency (%)
39.9 1
3.8%
39.72 1
3.8%
39.33 1
3.8%
39.26 1
3.8%
38.8 1
3.8%
38.68 1
3.8%
38.34 1
3.8%
38.32 1
3.8%
37.8 1
3.8%
37.19 1
3.8%

Interactions

2023-12-12T08:45:24.827222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:45:26.134634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발전소호기열효율
발전소1.0000.0000.814
호기0.0001.0000.856
열효율0.8140.8561.000
2023-12-12T08:45:26.226325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
열효율발전소
열효율1.0000.759
발전소0.7591.000

Missing values

2023-12-12T08:45:24.931736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:45:24.999574image/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

발전소호기열효율
0삼천포 발전본부1호기37.19
1삼천포 발전본부2호기36.71
2삼천포 발전본부3호기37.14
3삼천포 발전본부4호기37.8
4삼천포 발전본부5호기38.32
5삼천포 발전본부6호기38.8
6영흥 발전본부1호기38.34
7영흥 발전본부2호기38.68
8영흥 발전본부3호기39.9
9영흥 발전본부4호기39.72
발전소호기열효율
16분당 발전본부GT128.31
17분당 발전본부GT229.02
18분당 발전본부GT329.64
19분당 발전본부GT429.6
20분당 발전본부GT529.23
21분당 발전본부ST10.0
22분당 발전본부GT629.79
23분당 발전본부GT729.99
24분당 발전본부GT829.59
25분당 발전본부ST20.0