Overview

Dataset statistics

Number of variables6
Number of observations736
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.5 KiB
Average record size in memory52.2 B

Variable types

Categorical5
DateTime1

Dataset

Description한국남동발전의 냉각해수관리 실적 현황입니다. 사업소명, 검수일, 호기, 시간당채수량(톤), 취수펌프효율 등의 정보를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15066064/fileData.do

Alerts

사업소명 has constant value ""Constant
취수펌프효율 has constant value ""Constant
호기 is highly overall correlated with 시간당채수량(톤) and 1 other fieldsHigh correlation
사용량(톤) is highly overall correlated with 호기 and 1 other fieldsHigh correlation
시간당채수량(톤) is highly overall correlated with 호기 and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 03:22:23.083737
Analysis finished2023-12-12 03:22:23.416247
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업소명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
영흥발전본부
736 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영흥발전본부 736
100.0%

Length

2023-12-12T12:22:23.494671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:22:23.608283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영흥발전본부 736
100.0%

검수일
Date

Distinct184
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Minimum2022-01-01 00:00:00
Maximum2022-12-31 00:00:00
2023-12-12T12:22:23.732989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:22:23.898978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

호기
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
1
184 
2
184 
3
184 
4
184 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row1

Common Values

ValueCountFrequency (%)
1 184
25.0%
2 184
25.0%
3 184
25.0%
4 184
25.0%

Length

2023-12-12T12:22:24.037454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:22:24.184417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 184
25.0%
2 184
25.0%
3 184
25.0%
4 184
25.0%

시간당채수량(톤)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
66000
368 
73000
368 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row66000
2nd row66000
3rd row73000
4th row73000
5th row66000

Common Values

ValueCountFrequency (%)
66000 368
50.0%
73000 368
50.0%

Length

2023-12-12T12:22:24.304611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:22:24.415323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
66000 368
50.0%
73000 368
50.0%

취수펌프효율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
0.8
736 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.8
2nd row0.8
3rd row0.8
4th row0.8
5th row0.8

Common Values

ValueCountFrequency (%)
0.8 736
100.0%

Length

2023-12-12T12:22:24.560105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:22:24.693524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.8 736
100.0%

사용량(톤)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2534400
368 
2803200
368 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2534400
2nd row2534400
3rd row2803200
4th row2803200
5th row2534400

Common Values

ValueCountFrequency (%)
2534400 368
50.0%
2803200 368
50.0%

Length

2023-12-12T12:22:24.829979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:22:24.954914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2534400 368
50.0%
2803200 368
50.0%

Correlations

2023-12-12T12:22:25.033451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호기시간당채수량(톤)사용량(톤)
호기1.0001.0001.000
시간당채수량(톤)1.0001.0001.000
사용량(톤)1.0001.0001.000
2023-12-12T12:22:25.136451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호기사용량(톤)시간당채수량(톤)
호기1.0000.9990.999
사용량(톤)0.9991.0000.997
시간당채수량(톤)0.9990.9971.000
2023-12-12T12:22:25.252439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호기시간당채수량(톤)사용량(톤)
호기1.0000.9990.999
시간당채수량(톤)0.9991.0000.997
사용량(톤)0.9990.9971.000

Missing values

2023-12-12T12:22:23.253741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:22:23.364681image/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

사업소명검수일호기시간당채수량(톤)취수펌프효율사용량(톤)
0영흥발전본부2022-01-011660000.82534400
1영흥발전본부2022-01-012660000.82534400
2영흥발전본부2022-01-013730000.82803200
3영흥발전본부2022-01-014730000.82803200
4영흥발전본부2022-01-041660000.82534400
5영흥발전본부2022-01-042660000.82534400
6영흥발전본부2022-01-043730000.82803200
7영흥발전본부2022-01-044730000.82803200
8영흥발전본부2022-01-061660000.82534400
9영흥발전본부2022-01-062660000.82534400
사업소명검수일호기시간당채수량(톤)취수펌프효율사용량(톤)
726영흥발전본부2022-12-273730000.82803200
727영흥발전본부2022-12-274730000.82803200
728영흥발전본부2022-12-301660000.82534400
729영흥발전본부2022-12-302660000.82534400
730영흥발전본부2022-12-303730000.82803200
731영흥발전본부2022-12-304730000.82803200
732영흥발전본부2022-12-311660000.82534400
733영흥발전본부2022-12-312660000.82534400
734영흥발전본부2022-12-313730000.82803200
735영흥발전본부2022-12-314730000.82803200