Overview

Dataset statistics

Number of variables4
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)2.5%
Total size in memory1.5 KiB
Average record size in memory37.3 B

Variable types

Categorical2
Text1
Numeric1

Dataset

Description한국전기안전공사에서 2022년도에 보유하고 있는 계측장비를 제공하는 데이터입니다. 계측기의 용도 구분별(공용, 개인, 특수)로 종류 및 수량을 확인하실 수 있습니다.
URLhttps://www.data.go.kr/data/15044370/fileData.do

Alerts

연도 has constant value ""Constant
Dataset has 1 (2.5%) duplicate rowsDuplicates
수량 is highly overall correlated with 용도구분High correlation
용도구분 is highly overall correlated with 수량High correlation

Reproduction

Analysis started2023-12-12 22:22:38.513092
Analysis finished2023-12-12 22:22:38.928660
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2022
40 

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 40
100.0%

Length

2023-12-13T07:22:38.998646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:22:39.099107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 40
100.0%

용도구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
공용
33 
개인
5 
특수
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공용 33
82.5%
개인 5
 
12.5%
특수 2
 
5.0%

Length

2023-12-13T07:22:39.203081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:22:39.331477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공용 33
82.5%
개인 5
 
12.5%
특수 2
 
5.0%

계측기 종류
Text

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-13T07:22:39.556884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length9.05
Min length5

Characters and Unicode

Total characters362
Distinct characters112
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)95.0%

Sample

1st rowAC절연진단장비
2nd rowGIS부분방전진단장치
3rd rowSF6가스분석기
4th rowSF6가스누기측정기
5th rowSPD 시험기
ValueCountFrequency (%)
sf6가스누기측정기 2
 
4.9%
고시용전원품질분석기 1
 
2.4%
축전지진단측정기 1
 
2.4%
태양광설비진단장비 1
 
2.4%
정밀(거치형)절연유가스분석기 1
 
2.4%
차단기동작분석기 1
 
2.4%
비파괴절연진단장치(25kv 1
 
2.4%
비파괴절연진단장치 1
 
2.4%
초고압절연유내압시험기 1
 
2.4%
절연유내압시험기 1
 
2.4%
Other values (30) 30
73.2%
2023-12-13T07:22:39.958846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 32
 
8.8%
정 12
 
3.3%
단 11
 
3.0%
측 11
 
3.0%
비 11
 
3.0%
진 10
 
2.8%
장 10
 
2.8%
전 9
 
2.5%
절 8
 
2.2%
연 8
 
2.2%
Other values (102) 240
66.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 313
86.5%
Uppercase Letter 22
 
6.1%
Decimal Number 11
 
3.0%
Close Punctuation 6
 
1.7%
Open Punctuation 6
 
1.7%
Other Punctuation 2
 
0.6%
Lowercase Letter 1
 
0.3%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 32
 
10.2%
정 12
 
3.8%
단 11
 
3.5%
측 11
 
3.5%
비 11
 
3.5%
진 10
 
3.2%
장 10
 
3.2%
전 9
 
2.9%
절 8
 
2.6%
연 8
 
2.6%
Other values (80) 191
61.0%
Uppercase Letter
ValueCountFrequency (%)
S 5
22.7%
V 3
13.6%
F 3
13.6%
G 2
 
9.1%
I 2
 
9.1%
C 2
 
9.1%
R 1
 
4.5%
P 1
 
4.5%
D 1
 
4.5%
B 1
 
4.5%
Decimal Number
ValueCountFrequency (%)
6 4
36.4%
0 3
27.3%
5 1
 
9.1%
1 1
 
9.1%
2 1
 
9.1%
3 1
 
9.1%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 313
86.5%
Common 26
 
7.2%
Latin 23
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 32
 
10.2%
정 12
 
3.8%
단 11
 
3.5%
측 11
 
3.5%
비 11
 
3.5%
진 10
 
3.2%
장 10
 
3.2%
전 9
 
2.9%
절 8
 
2.6%
연 8
 
2.6%
Other values (80) 191
61.0%
Latin
ValueCountFrequency (%)
S 5
21.7%
V 3
13.0%
F 3
13.0%
G 2
 
8.7%
I 2
 
8.7%
C 2
 
8.7%
k 1
 
4.3%
R 1
 
4.3%
P 1
 
4.3%
D 1
 
4.3%
Other values (2) 2
 
8.7%
Common
ValueCountFrequency (%)
) 6
23.1%
( 6
23.1%
6 4
15.4%
0 3
11.5%
. 2
 
7.7%
5 1
 
3.8%
1 1
 
3.8%
2 1
 
3.8%
1
 
3.8%
3 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 313
86.5%
ASCII 49
 
13.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 32
 
10.2%
정 12
 
3.8%
단 11
 
3.5%
측 11
 
3.5%
비 11
 
3.5%
진 10
 
3.2%
장 10
 
3.2%
전 9
 
2.9%
절 8
 
2.6%
연 8
 
2.6%
Other values (80) 191
61.0%
ASCII
ValueCountFrequency (%)
) 6
12.2%
( 6
12.2%
S 5
 
10.2%
6 4
 
8.2%
V 3
 
6.1%
F 3
 
6.1%
0 3
 
6.1%
G 2
 
4.1%
I 2
 
4.1%
C 2
 
4.1%
Other values (12) 13
26.5%

수량
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean371.05
Minimum5
Maximum3171
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-13T07:22:40.106215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5.95
Q115
median60.5
Q3167.5
95-th percentile2839.15
Maximum3171
Range3166
Interquartile range (IQR)152.5

Descriptive statistics

Standard deviation830.97687
Coefficient of variation (CV)2.239528
Kurtosis6.1522639
Mean371.05
Median Absolute Deviation (MAD)51
Skewness2.7124156
Sum14842
Variance690522.56
MonotonicityNot monotonic
2023-12-13T07:22:40.254990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
10 2
 
5.0%
5 2
 
5.0%
6 2
 
5.0%
60 2
 
5.0%
7 1
 
2.5%
61 1
 
2.5%
22 1
 
2.5%
404 1
 
2.5%
9 1
 
2.5%
266 1
 
2.5%
Other values (26) 26
65.0%
ValueCountFrequency (%)
5 2
5.0%
6 2
5.0%
7 1
2.5%
9 1
2.5%
10 2
5.0%
11 1
2.5%
12 1
2.5%
16 1
2.5%
19 1
2.5%
21 1
2.5%
ValueCountFrequency (%)
3171 1
2.5%
2918 1
2.5%
2835 1
2.5%
2103 1
2.5%
867 1
2.5%
469 1
2.5%
404 1
2.5%
266 1
2.5%
202 1
2.5%
172 1
2.5%

Interactions

2023-12-13T07:22:38.647906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:22:40.364205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도구분계측기 종류수량
용도구분1.0001.0000.918
계측기 종류1.0001.0001.000
수량0.9181.0001.000
2023-12-13T07:22:40.461002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수량용도구분
수량1.0000.628
용도구분0.6281.000

Missing values

2023-12-13T07:22:38.787324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:22:38.890301image/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

연도용도구분계측기 종류수량
02022공용AC절연진단장비7
12022공용GIS부분방전진단장치11
22022공용SF6가스분석기21
32022공용SF6가스누기측정기10
42022공용SPD 시험기19
52022공용V.C.B시험기28
62022공용SF6가스누기측정기10
72022공용계전기시험기(6상)103
82022공용계전기시험기(3상)202
92022공용전원품질분석기128
연도용도구분계측기 종류수량
302022공용태양광설비진단장비61
312022공용피뢰기누설전류측정기68
322022공용절연유산가측정기469
332022개인디지털다기능계측기3171
342022개인크램프메타2835
352022개인누설전류계(IGR포함)2918
362022개인절연저항계(1000V)867
372022개인휴대용적외선열화상장비2103
382022특수복합가스측정기5
392022특수매설측정기60

Duplicate rows

Most frequently occurring

연도용도구분계측기 종류수량# duplicates
02022공용SF6가스누기측정기102