Overview

Dataset statistics

Number of variables4
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory867.0 B
Average record size in memory41.3 B

Variable types

Text1
Numeric3

Dataset

Description고객 제공 전력공급 현황 정보
Author한국전력공사
URLhttps://www.data.go.kr/data/15024605/fileData.do

Alerts

신설 is highly overall correlated with 증설 and 1 other fieldsHigh correlation
증설 is highly overall correlated with 신설 and 1 other fieldsHigh correlation
해지 is highly overall correlated with 신설 and 1 other fieldsHigh correlation
추출정보 has unique valuesUnique
신설 has unique valuesUnique
증설 has unique valuesUnique
해지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:52:55.606079
Analysis finished2023-12-12 11:52:57.026923
Duration1.42 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

추출정보
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T20:52:57.200449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length17
Mean length11.904762
Min length2

Characters and Unicode

Total characters250
Distinct characters89
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row건설업
2nd row공공행정/ 국방 및 사회보장 행정
3rd row광업
4th row교육 서비스업
5th row국제 및 외국기관
ValueCountFrequency (%)
및 16
 
21.6%
서비스업 6
 
8.1%
건설업 1
 
1.4%
방송통신 1
 
1.4%
전기 1
 
1.4%
가스 1
 
1.4%
증기 1
 
1.4%
수도사업 1
 
1.4%
전문 1
 
1.4%
과학 1
 
1.4%
Other values (44) 44
59.5%
2023-12-12T20:52:57.623303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
21.6%
업 24
 
9.6%
및 16
 
6.4%
/ 10
 
4.0%
스 9
 
3.6%
서 7
 
2.8%
비 7
 
2.8%
기 6
 
2.4%
사 5
 
2.0%
수 4
 
1.6%
Other values (79) 108
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 185
74.0%
Space Separator 54
 
21.6%
Other Punctuation 11
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 24
 
13.0%
및 16
 
8.6%
스 9
 
4.9%
서 7
 
3.8%
비 7
 
3.8%
기 6
 
3.2%
사 5
 
2.7%
수 4
 
2.2%
보 4
 
2.2%
국 3
 
1.6%
Other values (76) 100
54.1%
Other Punctuation
ValueCountFrequency (%)
/ 10
90.9%
· 1
 
9.1%
Space Separator
ValueCountFrequency (%)
54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 185
74.0%
Common 65
 
26.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 24
 
13.0%
및 16
 
8.6%
스 9
 
4.9%
서 7
 
3.8%
비 7
 
3.8%
기 6
 
3.2%
사 5
 
2.7%
수 4
 
2.2%
보 4
 
2.2%
국 3
 
1.6%
Other values (76) 100
54.1%
Common
ValueCountFrequency (%)
54
83.1%
/ 10
 
15.4%
· 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 185
74.0%
ASCII 64
 
25.6%
None 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54
84.4%
/ 10
 
15.6%
Hangul
ValueCountFrequency (%)
업 24
 
13.0%
및 16
 
8.6%
스 9
 
4.9%
서 7
 
3.8%
비 7
 
3.8%
기 6
 
3.2%
사 5
 
2.7%
수 4
 
2.2%
보 4
 
2.2%
국 3
 
1.6%
Other values (76) 100
54.1%
None
ValueCountFrequency (%)
· 1
100.0%

신설
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61623.286
Minimum185
Maximum297619
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T20:52:57.789987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum185
5-th percentile3188
Q18568
median15500
Q335509
95-th percentile286619
Maximum297619
Range297434
Interquartile range (IQR)26941

Descriptive statistics

Standard deviation98258.056
Coefficient of variation (CV)1.5944956
Kurtosis2.1315701
Mean61623.286
Median Absolute Deviation (MAD)12005
Skewness1.8841732
Sum1294089
Variance9.6546456 × 109
MonotonicityNot monotonic
2023-12-12T20:52:57.938475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
127457 1
 
4.8%
15982 1
 
4.8%
15500 1
 
4.8%
3495 1
 
4.8%
13311 1
 
4.8%
297619 1
 
4.8%
286619 1
 
4.8%
8793 1
 
4.8%
24388 1
 
4.8%
35509 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
185 1
4.8%
3188 1
4.8%
3495 1
4.8%
3985 1
4.8%
6042 1
4.8%
8568 1
4.8%
8793 1
4.8%
12862 1
4.8%
13311 1
4.8%
15073 1
4.8%
ValueCountFrequency (%)
297619 1
4.8%
286619 1
4.8%
273052 1
4.8%
127457 1
4.8%
78004 1
4.8%
35509 1
4.8%
32425 1
4.8%
32032 1
4.8%
24388 1
4.8%
15982 1
4.8%

증설
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35322.19
Minimum13
Maximum478887
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T20:52:58.090306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile928
Q12643
median7024
Q325855
95-th percentile56546
Maximum478887
Range478874
Interquartile range (IQR)23212

Descriptive statistics

Standard deviation102687.12
Coefficient of variation (CV)2.907156
Kurtosis20.014734
Mean35322.19
Median Absolute Deviation (MAD)5462
Skewness4.4330241
Sum741766
Variance1.0544644 × 1010
MonotonicityNot monotonic
2023-12-12T20:52:58.291125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
7024 1
 
4.8%
36701 1
 
4.8%
7760 1
 
4.8%
2030 1
 
4.8%
4955 1
 
4.8%
29403 1
 
4.8%
478887 1
 
4.8%
928 1
 
4.8%
2794 1
 
4.8%
6456 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
13 1
4.8%
928 1
4.8%
1392 1
4.8%
2030 1
4.8%
2138 1
4.8%
2643 1
4.8%
2794 1
4.8%
4955 1
4.8%
5192 1
4.8%
6456 1
4.8%
ValueCountFrequency (%)
478887 1
4.8%
56546 1
4.8%
36701 1
4.8%
29403 1
4.8%
26396 1
4.8%
25855 1
4.8%
22582 1
4.8%
12486 1
4.8%
9585 1
4.8%
7760 1
4.8%

해지
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26451.81
Minimum16
Maximum161023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T20:52:58.457298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile497
Q12701
median7284
Q316434
95-th percentile146185
Maximum161023
Range161007
Interquartile range (IQR)13733

Descriptive statistics

Standard deviation46574.221
Coefficient of variation (CV)1.7607196
Kurtosis4.368058
Mean26451.81
Median Absolute Deviation (MAD)4996
Skewness2.2993075
Sum555488
Variance2.169158 × 109
MonotonicityNot monotonic
2023-12-12T20:52:58.617851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
84605 1
 
4.8%
2288 1
 
4.8%
7284 1
 
4.8%
2440 1
 
4.8%
6746 1
 
4.8%
161023 1
 
4.8%
146185 1
 
4.8%
2701 1
 
4.8%
3143 1
 
4.8%
4753 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
16 1
4.8%
497 1
4.8%
2193 1
4.8%
2288 1
4.8%
2440 1
4.8%
2701 1
4.8%
3143 1
4.8%
4753 1
4.8%
5318 1
4.8%
6746 1
4.8%
ValueCountFrequency (%)
161023 1
4.8%
146185 1
4.8%
84605 1
4.8%
48195 1
4.8%
18395 1
4.8%
16434 1
4.8%
16154 1
4.8%
9328 1
4.8%
9101 1
4.8%
8689 1
4.8%

Interactions

2023-12-12T20:52:56.486233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:52:55.796760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:52:56.143577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:52:56.614086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:52:55.911524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:52:56.254044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:52:56.731485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:52:56.024337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:52:56.363637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:52:58.748731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
추출정보신설증설해지
추출정보1.0001.0001.0001.000
신설1.0001.0000.4480.976
증설1.0000.4481.0000.801
해지1.0000.9760.8011.000
2023-12-12T20:52:58.911670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신설증설해지
신설1.0000.7640.796
증설0.7641.0000.623
해지0.7960.6231.000

Missing values

2023-12-12T20:52:56.883039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:52:56.977631image/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

추출정보신설증설해지
0건설업127457702484605
1공공행정/ 국방 및 사회보장 행정15982367012288
2광업398526439101
3교육 서비스업6042124865318
4국제 및 외국기관1851316
5금융 및 보험업31881392497
6농업/ 임업 및 어업780042585518395
7도매 및 소매업320322639616434
8보건업 및 사회복지 서비스업856895852193
9부동산업 및 임대업2730525654648195
추출정보신설증설해지
11숙박 및 음식점업324252258216154
12예술/ 스포츠 및 여가관련 서비스업1507351929328
13운수업3550964564753
14전기/ 가스/ 증기 및 수도사업2438827943143
15전문/ 과학 및 기술 서비스업87939282701
16제조업286619478887146185
17주택용29761929403161023
18출판/ 영상/ 방송통신 및 정보서비스업1331149556746
19하수 · 폐기물 처리/ 원료재생 및 환경복원업349520302440
20협회 및 단체/ 수리 및 기타 개인 서비스업1550077607284