Overview

Dataset statistics

Number of variables5
Number of observations1306
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory53.7 KiB
Average record size in memory42.1 B

Variable types

Categorical3
Text1
Numeric1

Dataset

Description한국전기안전공사에서 정기점검을 진행한 설비의 점검주기(1년 ~ 3년)별, 부적합 유형별(절연저항, 인입구배선, 누전차단기, 개폐기차단기, 옥내외배선, 접지상태) 현황을 연도별(2020년 ~ 2022년)로 제공하는 데이터입니다.
URLhttps://www.data.go.kr/data/15071157/fileData.do

Alerts

부적합 호수 has 384 (29.4%) zerosZeros

Reproduction

Analysis started2023-12-11 23:04:48.142707
Analysis finished2023-12-11 23:04:48.632353
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
2022
438 
2021
438 
2020
430 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 438
33.5%
2021 438
33.5%
2020 430
32.9%

Length

2023-12-12T08:04:48.687851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:04:48.779948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 438
33.5%
2021 438
33.5%
2020 430
32.9%

점검주기
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
3년
676 
1년
576 
2년
 
54

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
3년 676
51.8%
1년 576
44.1%
2년 54
 
4.1%

Length

2023-12-12T08:04:48.875536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:04:48.960914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3년 676
51.8%
1년 576
44.1%
2년 54
 
4.1%
Distinct77
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
2023-12-12T08:04:49.153741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length4.5068913
Min length2

Characters and Unicode

Total characters5886
Distinct characters142
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유흥단란주점
2nd row유흥단란주점
3rd row유흥단란주점
4th row유흥단란주점
5th row유흥단란주점
ValueCountFrequency (%)
분전함 48
 
3.4%
등주 48
 
3.4%
가로등 36
 
2.5%
신호등 36
 
2.5%
자동차전용도로 24
 
1.7%
기타산업용 18
 
1.3%
정류장 18
 
1.3%
체육시설 18
 
1.3%
기숙사 18
 
1.3%
노래연습장 18
 
1.3%
Other values (69) 1144
80.2%
2023-12-12T08:04:49.466186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
198
 
3.4%
198
 
3.4%
192
 
3.3%
180
 
3.1%
162
 
2.8%
144
 
2.4%
120
 
2.0%
120
 
2.0%
108
 
1.8%
108
 
1.8%
Other values (132) 4356
74.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5652
96.0%
Space Separator 120
 
2.0%
Uppercase Letter 72
 
1.2%
Other Punctuation 42
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
198
 
3.5%
198
 
3.5%
192
 
3.4%
180
 
3.2%
162
 
2.9%
144
 
2.5%
120
 
2.1%
108
 
1.9%
108
 
1.9%
108
 
1.9%
Other values (126) 4134
73.1%
Uppercase Letter
ValueCountFrequency (%)
C 36
50.0%
V 18
25.0%
T 18
25.0%
Other Punctuation
ValueCountFrequency (%)
· 30
71.4%
? 12
 
28.6%
Space Separator
ValueCountFrequency (%)
120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5652
96.0%
Common 162
 
2.8%
Latin 72
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
198
 
3.5%
198
 
3.5%
192
 
3.4%
180
 
3.2%
162
 
2.9%
144
 
2.5%
120
 
2.1%
108
 
1.9%
108
 
1.9%
108
 
1.9%
Other values (126) 4134
73.1%
Common
ValueCountFrequency (%)
120
74.1%
· 30
 
18.5%
? 12
 
7.4%
Latin
ValueCountFrequency (%)
C 36
50.0%
V 18
25.0%
T 18
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5652
96.0%
ASCII 204
 
3.5%
None 30
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
198
 
3.5%
198
 
3.5%
192
 
3.4%
180
 
3.2%
162
 
2.9%
144
 
2.5%
120
 
2.1%
108
 
1.9%
108
 
1.9%
108
 
1.9%
Other values (126) 4134
73.1%
ASCII
ValueCountFrequency (%)
120
58.8%
C 36
 
17.6%
V 18
 
8.8%
T 18
 
8.8%
? 12
 
5.9%
None
ValueCountFrequency (%)
· 30
100.0%

부적합 유형
Categorical

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
절연저항
218 
누전차단기
218 
옥내외배선
218 
접지상태
218 
인입구배선
217 

Length

Max length6
Median length5.5
Mean length4.8323124
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row절연저항
2nd row인입구배선
3rd row누전차단기
4th row개폐기차단기
5th row옥내외배선

Common Values

ValueCountFrequency (%)
절연저항 218
16.7%
누전차단기 218
16.7%
옥내외배선 218
16.7%
접지상태 218
16.7%
인입구배선 217
16.6%
개폐기차단기 217
16.6%

Length

2023-12-12T08:04:49.584622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:04:49.677827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
절연저항 218
16.7%
누전차단기 218
16.7%
옥내외배선 218
16.7%
접지상태 218
16.7%
인입구배선 217
16.6%
개폐기차단기 217
16.6%

부적합 호수
Real number (ℝ)

ZEROS 

Distinct347
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean357.82159
Minimum0
Maximum45026
Zeros384
Zeros (%)29.4%
Negative0
Negative (%)0.0%
Memory size11.6 KiB
2023-12-12T08:04:49.782476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q380
95-th percentile1488.75
Maximum45026
Range45026
Interquartile range (IQR)80

Descriptive statistics

Standard deviation2073.96
Coefficient of variation (CV)5.7960728
Kurtosis291.35235
Mean357.82159
Median Absolute Deviation (MAD)6
Skewness15.513081
Sum467315
Variance4301310.1
MonotonicityNot monotonic
2023-12-12T08:04:49.893980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 384
29.4%
1 102
 
7.8%
2 59
 
4.5%
3 40
 
3.1%
4 31
 
2.4%
5 30
 
2.3%
7 20
 
1.5%
9 20
 
1.5%
6 18
 
1.4%
8 17
 
1.3%
Other values (337) 585
44.8%
ValueCountFrequency (%)
0 384
29.4%
1 102
 
7.8%
2 59
 
4.5%
3 40
 
3.1%
4 31
 
2.4%
5 30
 
2.3%
6 18
 
1.4%
7 20
 
1.5%
8 17
 
1.3%
9 20
 
1.5%
ValueCountFrequency (%)
45026 1
0.1%
39795 1
0.1%
28083 1
0.1%
14542 1
0.1%
12258 1
0.1%
7970 1
0.1%
7835 1
0.1%
7376 1
0.1%
7230 1
0.1%
6754 1
0.1%

Interactions

2023-12-12T08:04:48.396498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:04:49.966242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도점검주기업종명부적합 유형부적합 호수
연도1.0000.0000.0000.0000.000
점검주기0.0001.0000.9990.0000.000
업종명0.0000.9991.0000.0000.338
부적합 유형0.0000.0000.0001.0000.134
부적합 호수0.0000.0000.3380.1341.000
2023-12-12T08:04:50.269146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부적합 유형점검주기연도
부적합 유형1.0000.0000.000
점검주기0.0001.0000.000
연도0.0000.0001.000
2023-12-12T08:04:50.354148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부적합 호수연도점검주기부적합 유형
부적합 호수1.0000.0000.0000.080
연도0.0001.0000.0000.000
점검주기0.0000.0001.0000.000
부적합 유형0.0800.0000.0001.000

Missing values

2023-12-12T08:04:48.497196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:04:48.598262image/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

연도점검주기업종명부적합 유형부적합 호수
020221년유흥단란주점절연저항13
120221년유흥단란주점인입구배선0
220221년유흥단란주점누전차단기58
320221년유흥단란주점개폐기차단기1
420221년유흥단란주점옥내외배선4
520221년유흥단란주점접지상태10
620221년노래연습장절연저항25
720221년노래연습장인입구배선0
820221년노래연습장누전차단기58
920221년노래연습장개폐기차단기5
연도점검주기업종명부적합 유형부적합 호수
129620203년태양광설비누전차단기2
129720203년태양광설비개폐기차단기0
129820203년태양광설비옥내외배선0
129920203년태양광설비접지상태1
130020203년전기차충전시설절연저항4
130120203년전기차충전시설인입구배선0
130220203년전기차충전시설누전차단기14
130320203년전기차충전시설개폐기차단기0
130420203년전기차충전시설옥내외배선0
130520203년전기차충전시설접지상태8