Overview

Dataset statistics

Number of variables8
Number of observations31
Missing cells11
Missing cells (%)4.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory72.3 B

Variable types

Categorical6
Numeric2

Dataset

Description전력계통의 비상전원공급 장치인 무정전전원장치(UPS)는 상용전원공급용과 축전지가 조합된 설비로써 주요부하에 문제가 발생되었을때 축전지로 전원을 공급하여 주며 축전지가 모두 방전되었을때 상용전원으로 절체되어 상시 전력을 공급할 수 있게 해주는 설비이다.
Author한국가스공사
URLhttps://www.data.go.kr/data/15087489/fileData.do

Alerts

축전지 수량(Cell) is highly overall correlated with 축전지 용량(Ah) and 3 other fieldsHigh correlation
UPS설비 is highly overall correlated with 축전지 용량(Ah) and 2 other fieldsHigh correlation
축전지 사용방식 is highly overall correlated with 설치위치 and 2 other fieldsHigh correlation
UPS설치년도 is highly overall correlated with 설치위치 and 1 other fieldsHigh correlation
축전지 용량(Ah) is highly overall correlated with UPS설비 and 3 other fieldsHigh correlation
설치위치 is highly overall correlated with UPS설치년도 and 2 other fieldsHigh correlation
UPS용량 is highly overall correlated with 축전지 용량(Ah) and 2 other fieldsHigh correlation
축전지 설치년도 is highly overall correlated with UPS설치년도 and 3 other fieldsHigh correlation
축전지 용량(Ah) has 11 (35.5%) missing valuesMissing

Reproduction

Analysis started2023-12-12 05:29:25.454025
Analysis finished2023-12-12 05:29:26.563223
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설치위치
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)35.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
A
3 
B
3 
C
3 
D
3 
E
3 
Other values (6)
16 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA
2nd rowA
3rd rowA
4th rowB
5th rowB

Common Values

ValueCountFrequency (%)
A 3
9.7%
B 3
9.7%
C 3
9.7%
D 3
9.7%
E 3
9.7%
F 3
9.7%
G 3
9.7%
H 3
9.7%
I 3
9.7%
J 2
6.5%

Length

2023-12-12T14:29:26.650908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
a 3
9.7%
b 3
9.7%
c 3
9.7%
d 3
9.7%
e 3
9.7%
f 3
9.7%
g 3
9.7%
h 3
9.7%
i 3
9.7%
j 2
6.5%

UPS설비
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
UPS
11 
AVR
11 
B/CH
9 

Length

Max length4
Median length3
Mean length3.2903226
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUPS
2nd rowAVR
3rd rowB/CH
4th rowUPS
5th rowAVR

Common Values

ValueCountFrequency (%)
UPS 11
35.5%
AVR 11
35.5%
B/CH 9
29.0%

Length

2023-12-12T14:29:26.799964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:29:26.924868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ups 11
35.5%
avr 11
35.5%
b/ch 9
29.0%

UPS용량
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
75kVA
10 
50kVA
8 
50A
4 
75A
3 
100kVA
2 
Other values (3)
4 

Length

Max length6
Median length5
Mean length4.516129
Min length3

Unique

Unique2 ?
Unique (%)6.5%

Sample

1st row75kVA
2nd row75kVA
3rd row100A
4th row75kVA
5th row75kVA

Common Values

ValueCountFrequency (%)
75kVA 10
32.3%
50kVA 8
25.8%
50A 4
 
12.9%
75A 3
 
9.7%
100kVA 2
 
6.5%
20kVA 2
 
6.5%
100A 1
 
3.2%
30A 1
 
3.2%

Length

2023-12-12T14:29:27.080611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:29:27.276697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
75kva 10
32.3%
50kva 8
25.8%
50a 4
 
12.9%
75a 3
 
9.7%
100kva 2
 
6.5%
20kva 2
 
6.5%
100a 1
 
3.2%
30a 1
 
3.2%

UPS설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.4839
Minimum2004
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T14:29:27.441203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2004
5-th percentile2005.5
Q12008
median2020
Q32021
95-th percentile2022
Maximum2022
Range18
Interquartile range (IQR)13

Descriptive statistics

Standard deviation6.6976163
Coefficient of variation (CV)0.0033230811
Kurtosis-1.563706
Mean2015.4839
Median Absolute Deviation (MAD)2
Skewness-0.56405863
Sum62480
Variance44.858065
MonotonicityNot monotonic
2023-12-12T14:29:27.592534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2020 6
19.4%
2021 6
19.4%
2007 6
19.4%
2022 4
12.9%
2019 3
9.7%
2009 3
9.7%
2004 2
 
6.5%
2012 1
 
3.2%
ValueCountFrequency (%)
2004 2
 
6.5%
2007 6
19.4%
2009 3
9.7%
2012 1
 
3.2%
2019 3
9.7%
2020 6
19.4%
2021 6
19.4%
2022 4
12.9%
ValueCountFrequency (%)
2022 4
12.9%
2021 6
19.4%
2020 6
19.4%
2019 3
9.7%
2012 1
 
3.2%
2009 3
9.7%
2007 6
19.4%
2004 2
 
6.5%

축전지 사용방식
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
이중화
12 
<NA>
11 
공통
8 

Length

Max length4
Median length3
Mean length3.0967742
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row이중화
2nd row<NA>
3rd row이중화
4th row이중화
5th row<NA>

Common Values

ValueCountFrequency (%)
이중화 12
38.7%
<NA> 11
35.5%
공통 8
25.8%

Length

2023-12-12T14:29:27.781830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:29:27.929747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이중화 12
38.7%
na 11
35.5%
공통 8
25.8%

축전지 수량(Cell)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
11 
360
7 
120
5 
180
4 
60
4 

Length

Max length4
Median length3
Mean length3.2258065
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row360
2nd row<NA>
3rd row120
4th row360
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 11
35.5%
360 7
22.6%
120 5
16.1%
180 4
 
12.9%
60 4
 
12.9%

Length

2023-12-12T14:29:28.127214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:29:28.263077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 11
35.5%
360 7
22.6%
120 5
16.1%
180 4
 
12.9%
60 4
 
12.9%

축전지 용량(Ah)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)35.0%
Missing11
Missing (%)35.5%
Infinite0
Infinite (%)0.0%
Mean306
Minimum100
Maximum600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T14:29:28.386674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile157
Q1200
median200
Q3420
95-th percentile600
Maximum600
Range500
Interquartile range (IQR)220

Descriptive statistics

Standard deviation157.62714
Coefficient of variation (CV)0.51512138
Kurtosis-0.45115974
Mean306
Median Absolute Deviation (MAD)70
Skewness0.88005143
Sum6120
Variance24846.316
MonotonicityNot monotonic
2023-12-12T14:29:28.528176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
200 9
29.0%
420 3
 
9.7%
600 3
 
9.7%
300 2
 
6.5%
160 1
 
3.2%
400 1
 
3.2%
100 1
 
3.2%
(Missing) 11
35.5%
ValueCountFrequency (%)
100 1
 
3.2%
160 1
 
3.2%
200 9
29.0%
300 2
 
6.5%
400 1
 
3.2%
420 3
 
9.7%
600 3
 
9.7%
ValueCountFrequency (%)
600 3
 
9.7%
420 3
 
9.7%
400 1
 
3.2%
300 2
 
6.5%
200 9
29.0%
160 1
 
3.2%
100 1
 
3.2%

축전지 설치년도
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
11 
2015
8 
2016
5 
2007
4 
2014
2 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row2015
2nd row<NA>
3rd row2015
4th row2015
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 11
35.5%
2015 8
25.8%
2016 5
16.1%
2007 4
 
12.9%
2014 2
 
6.5%
2022 1
 
3.2%

Length

2023-12-12T14:29:28.672937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:29:28.790894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 11
35.5%
2015 8
25.8%
2016 5
16.1%
2007 4
 
12.9%
2014 2
 
6.5%
2022 1
 
3.2%

Interactions

2023-12-12T14:29:26.115266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:29:25.912155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:29:26.213331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:29:26.007329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:29:28.899270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치UPS설비UPS용량UPS설치년도축전지 사용방식축전지 수량(Cell)축전지 용량(Ah)축전지 설치년도
설치위치1.0000.0000.7991.0001.0000.0000.7330.928
UPS설비0.0001.0000.7070.0000.0001.0000.9790.000
UPS용량0.7990.7071.0000.1620.2950.9010.8970.687
UPS설치년도1.0000.0000.1621.0000.4280.0000.0000.896
축전지 사용방식1.0000.0000.2950.4281.0001.0000.5320.651
축전지 수량(Cell)0.0001.0000.9010.0001.0001.0000.7440.515
축전지 용량(Ah)0.7330.9790.8970.0000.5320.7441.0000.753
축전지 설치년도0.9280.0000.6870.8960.6510.5150.7531.000
2023-12-12T14:29:29.062384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
축전지 수량(Cell)UPS설비축전지 설치년도UPS용량설치위치축전지 사용방식
축전지 수량(Cell)1.0000.9430.4170.5070.0000.943
UPS설비0.9431.0000.0000.5350.0000.000
축전지 설치년도0.4170.0001.0000.4400.6340.710
UPS용량0.5070.5350.4401.0000.4980.119
설치위치0.0000.0000.6340.4981.0000.707
축전지 사용방식0.9430.0000.7100.1190.7071.000
2023-12-12T14:29:29.192856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
UPS설치년도축전지 용량(Ah)설치위치UPS설비UPS용량축전지 사용방식축전지 수량(Cell)축전지 설치년도
UPS설치년도1.000-0.1900.7480.0000.0000.4370.0000.510
축전지 용량(Ah)-0.1901.0000.3570.7650.7050.3220.5340.597
설치위치0.7480.3571.0000.0000.4980.7070.0000.634
UPS설비0.0000.7650.0001.0000.5350.0000.9430.000
UPS용량0.0000.7050.4980.5351.0000.1190.5070.440
축전지 사용방식0.4370.3220.7070.0000.1191.0000.9430.710
축전지 수량(Cell)0.0000.5340.0000.9430.5070.9431.0000.417
축전지 설치년도0.5100.5970.6340.0000.4400.7100.4171.000

Missing values

2023-12-12T14:29:26.336396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:29:26.498049image/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

설치위치UPS설비UPS용량UPS설치년도축전지 사용방식축전지 수량(Cell)축전지 용량(Ah)축전지 설치년도
0AUPS75kVA2019이중화3603002015
1AAVR75kVA2019<NA><NA><NA><NA>
2AB/CH100A2019이중화1202002015
3BUPS75kVA2020이중화3603002015
4BAVR75kVA2020<NA><NA><NA><NA>
5BB/CH50A2020이중화1202002015
6CUPS50kVA2020공통1804202014
7CAVR50kVA2020<NA><NA><NA><NA>
8CB/CH50A2020공통602002015
9DUPS50kVA2021이중화3602002015
설치위치UPS설비UPS용량UPS설치년도축전지 사용방식축전지 수량(Cell)축전지 용량(Ah)축전지 설치년도
21HUPS50kVA2007공통1804202007
22HAVR50kVA2007<NA><NA><NA><NA>
23HB/CH75A2007공통602002007
24IUPS75kVA2009이중화3606002016
25IAVR75kVA2009<NA><NA><NA><NA>
26IB/CH75A2009이중화1201602016
27JUPS100kVA2022이중화3604002022
28JAVR100kVA2022<NA><NA><NA><NA>
29KUPS20kVA2022이중화3601002016
30KAVR20kVA2022<NA><NA><NA><NA>