Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells3525
Missing cells (%)7.0%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory478.5 KiB
Average record size in memory49.0 B

Variable types

DateTime1
Categorical2
Text1
Numeric1

Dataset

Description2016~2017년 월별 전력판매 총괄현황
Author한국전력공사
URLhttps://www.data.go.kr/data/15069679/fileData.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
조회기간 has 1175 (11.8%) missing valuesMissing
시군구 has 1175 (11.8%) missing valuesMissing
판매량 has 1175 (11.8%) missing valuesMissing

Reproduction

Analysis started2023-12-12 08:11:26.882045
Analysis finished2023-12-12 08:11:27.661163
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

조회기간
Date

MISSING 

Distinct6
Distinct (%)0.1%
Missing1175
Missing (%)11.8%
Memory size156.2 KiB
Minimum2020-01-17 00:00:00
Maximum2020-12-16 00:00:00
2023-12-12T17:11:27.701983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:11:27.806275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)

시도
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
1182 
<NA>
1175 
서울특별시
958 
경상북도
878 
전라남도
856 
Other values (13)
4951 

Length

Max length7
Median length4
Mean length4.1319
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row경상남도
3rd row강원도
4th row인천광역시
5th row인천광역시

Common Values

ValueCountFrequency (%)
경기도 1182
11.8%
<NA> 1175
11.8%
서울특별시 958
9.6%
경상북도 878
8.8%
전라남도 856
8.6%
경상남도 698
 
7.0%
강원도 693
 
6.9%
부산광역시 613
 
6.1%
충청남도 591
 
5.9%
전라북도 536
 
5.4%
Other values (8) 1820
18.2%

Length

2023-12-12T17:11:27.956574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 1182
11.8%
na 1175
11.8%
서울특별시 958
9.6%
경상북도 878
8.8%
전라남도 856
8.6%
경상남도 698
 
7.0%
강원도 693
 
6.9%
부산광역시 613
 
6.1%
충청남도 591
 
5.9%
전라북도 536
 
5.4%
Other values (8) 1820
18.2%

시군구
Text

MISSING 

Distinct207
Distinct (%)2.3%
Missing1175
Missing (%)11.8%
Memory size156.2 KiB
2023-12-12T17:11:28.298239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9253258
Min length2

Characters and Unicode

Total characters25816
Distinct characters131
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row창녕군
2nd row횡성군
3rd row남구
4th row계양구
5th row영동군
ValueCountFrequency (%)
중구 233
 
2.6%
동구 226
 
2.6%
서구 198
 
2.2%
남구 193
 
2.2%
북구 153
 
1.7%
고성군 78
 
0.9%
강서구 77
 
0.9%
홍성군 42
 
0.5%
은평구 42
 
0.5%
음성군 42
 
0.5%
Other values (197) 7541
85.5%
2023-12-12T17:11:28.782482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 3293
 
12.8%
시 3029
 
11.7%
구 2851
 
11.0%
천 850
 
3.3%
주 763
 
3.0%
양 702
 
2.7%
성 695
 
2.7%
동 639
 
2.5%
산 608
 
2.4%
서 512
 
2.0%
Other values (121) 11874
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25816
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 3293
 
12.8%
시 3029
 
11.7%
구 2851
 
11.0%
천 850
 
3.3%
주 763
 
3.0%
양 702
 
2.7%
성 695
 
2.7%
동 639
 
2.5%
산 608
 
2.4%
서 512
 
2.0%
Other values (121) 11874
46.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25816
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 3293
 
12.8%
시 3029
 
11.7%
구 2851
 
11.0%
천 850
 
3.3%
주 763
 
3.0%
양 702
 
2.7%
성 695
 
2.7%
동 639
 
2.5%
산 608
 
2.4%
서 512
 
2.0%
Other values (121) 11874
46.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25816
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 3293
 
12.8%
시 3029
 
11.7%
구 2851
 
11.0%
천 850
 
3.3%
주 763
 
3.0%
양 702
 
2.7%
성 695
 
2.7%
동 639
 
2.5%
산 608
 
2.4%
서 512
 
2.0%
Other values (121) 11874
46.0%

계약종별(대)
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반용
1276 
교육용
1272 
주택용
1260 
심 야
1259 
산업용
1259 
Other values (3)
3674 

Length

Max length4
Median length3
Mean length3.2434
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row교육용
3rd row가로등
4th row심 야
5th row심 야

Common Values

ValueCountFrequency (%)
일반용 1276
12.8%
교육용 1272
12.7%
주택용 1260
12.6%
심 야 1259
12.6%
산업용 1259
12.6%
가로등 1254
12.5%
농사용 1245
12.4%
<NA> 1175
11.8%

Length

2023-12-12T17:11:28.932251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:11:29.082331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반용 1276
11.3%
교육용 1272
11.3%
주택용 1260
11.2%
심 1259
11.2%
야 1259
11.2%
산업용 1259
11.2%
가로등 1254
11.1%
농사용 1245
11.1%
na 1175
10.4%

판매량
Real number (ℝ)

MISSING 

Distinct8823
Distinct (%)> 99.9%
Missing1175
Missing (%)11.8%
Infinite0
Infinite (%)0.0%
Mean26404834
Minimum25
Maximum1.2324661 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:11:29.222605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile310624.6
Q11473176
median5294104
Q319160882
95-th percentile94326951
Maximum1.2324661 × 109
Range1.2324661 × 109
Interquartile range (IQR)17687706

Descriptive statistics

Standard deviation86185857
Coefficient of variation (CV)3.2640182
Kurtosis89.935668
Mean26404834
Median Absolute Deviation (MAD)4557087
Skewness8.5898859
Sum2.3302266 × 1011
Variance7.4280019 × 1015
MonotonicityNot monotonic
2023-12-12T17:11:29.391964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5115179 2
 
< 0.1%
153965 2
 
< 0.1%
40948726 1
 
< 0.1%
130572 1
 
< 0.1%
2784 1
 
< 0.1%
11007866 1
 
< 0.1%
2973442 1
 
< 0.1%
852573 1
 
< 0.1%
21507013 1
 
< 0.1%
7093388 1
 
< 0.1%
Other values (8813) 8813
88.1%
(Missing) 1175
 
11.8%
ValueCountFrequency (%)
25 1
< 0.1%
48 1
< 0.1%
52 1
< 0.1%
65 1
< 0.1%
101 1
< 0.1%
755 1
< 0.1%
800 1
< 0.1%
816 1
< 0.1%
897 1
< 0.1%
1059 1
< 0.1%
ValueCountFrequency (%)
1232466115 1
< 0.1%
1219319661 1
< 0.1%
1214072436 1
< 0.1%
1213934509 1
< 0.1%
1197447718 1
< 0.1%
1189951019 1
< 0.1%
1179690105 1
< 0.1%
1177424285 1
< 0.1%
1169863812 1
< 0.1%
1142897250 1
< 0.1%

Interactions

2023-12-12T17:11:27.246949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:11:29.489852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조회기간시도계약종별(대)판매량
조회기간1.0000.0000.0000.000
시도0.0001.0000.0000.216
계약종별(대)0.0000.0001.0000.299
판매량0.0000.2160.2991.000
2023-12-12T17:11:29.581260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계약종별(대)시도
계약종별(대)1.0000.000
시도0.0001.000
2023-12-12T17:11:29.980590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
판매량시도계약종별(대)
판매량1.0000.0850.156
시도0.0851.0000.000
계약종별(대)0.1560.0001.000

Missing values

2023-12-12T17:11:27.366044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:11:27.476167image/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.
2023-12-12T17:11:27.593385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

조회기간시도시군구계약종별(대)판매량
7268<NA><NA><NA><NA><NA>
71162020-01-17경상남도창녕군교육용614969
81852020-02-17강원도횡성군가로등727184
57632020-01-17인천광역시남구심 야3565924
94552020-03-17인천광역시계양구심 야1806313
8812020-10-16충청북도영동군주택용4746753
33322020-11-16경상남도거제시심 야4823753
91702020-03-17서울특별시성동구산업용55868103
97232020-03-17경기도동두천시심 야2810647
32982020-11-16경상북도청도군가로등817416
조회기간시도시군구계약종별(대)판매량
25302020-11-16강원도속초시농사용391545
31342020-11-16전라남도화순군교육용758357
9326<NA><NA><NA><NA><NA>
89752020-02-17경상남도창원시산업용556001065
101042020-03-17충청북도진천군일반용17011883
6265<NA><NA><NA><NA><NA>
41522020-12-16경기도김포시일반용62536695
23652020-11-16경기도안성시주택용19447868
46462020-12-16충청남도서천군농사용33032317
74772020-02-17부산광역시서구주택용13592755

Duplicate rows

Most frequently occurring

조회기간시도시군구계약종별(대)판매량# duplicates
0<NA><NA><NA><NA><NA>1175