Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells4
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
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/15069678/fileData.do

Reproduction

Analysis started2023-12-12 19:54:58.216072
Analysis finished2023-12-12 19:54:58.921903
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

조회기간
Date

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2016-10-01 00:00:00
Maximum2017-03-01 00:00:00
2023-12-13T04:54:58.978855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:54:59.137207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)

시도
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
1487 
서울특별시
1064 
경상북도
963 
전라남도
898 
경상남도
818 
Other values (12)
4770 

Length

Max length7
Median length5
Mean length4.1316
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시
2nd row경상북도
3rd row충청북도
4th row전라북도
5th row전라남도

Common Values

ValueCountFrequency (%)
경기도 1487
14.9%
서울특별시 1064
10.6%
경상북도 963
9.6%
전라남도 898
9.0%
경상남도 818
8.2%
강원도 746
7.5%
충청남도 701
7.0%
부산광역시 671
6.7%
전라북도 615
 
6.2%
충청북도 479
 
4.8%
Other values (7) 1558
15.6%

Length

2023-12-13T04:54:59.327544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 1487
14.9%
서울특별시 1064
10.6%
경상북도 963
9.6%
전라남도 898
9.0%
경상남도 818
8.2%
강원도 746
7.5%
충청남도 701
7.0%
부산광역시 671
6.7%
전라북도 615
 
6.2%
충청북도 479
 
4.8%
Other values (7) 1558
15.6%

시군구
Text

Distinct207
Distinct (%)2.1%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T04:54:59.682668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9383754
Min length2

Characters and Unicode

Total characters29372
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row사상구
2nd row문경시
3rd row음성군
4th row장수군
5th row나주시
ValueCountFrequency (%)
동구 241
 
2.4%
중구 238
 
2.4%
남구 201
 
2.0%
서구 200
 
2.0%
북구 165
 
1.7%
강서구 99
 
1.0%
고성군 73
 
0.7%
남동구 62
 
0.6%
음성군 61
 
0.6%
김제시 60
 
0.6%
Other values (197) 8596
86.0%
2023-12-13T04:55:00.231879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 3723
 
12.7%
군 3514
 
12.0%
구 3170
 
10.8%
천 1030
 
3.5%
주 900
 
3.1%
성 830
 
2.8%
양 794
 
2.7%
산 754
 
2.6%
동 739
 
2.5%
서 573
 
2.0%
Other values (121) 13345
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29372
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3723
 
12.7%
군 3514
 
12.0%
구 3170
 
10.8%
천 1030
 
3.5%
주 900
 
3.1%
성 830
 
2.8%
양 794
 
2.7%
산 754
 
2.6%
동 739
 
2.5%
서 573
 
2.0%
Other values (121) 13345
45.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29372
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3723
 
12.7%
군 3514
 
12.0%
구 3170
 
10.8%
천 1030
 
3.5%
주 900
 
3.1%
성 830
 
2.8%
양 794
 
2.7%
산 754
 
2.6%
동 739
 
2.5%
서 573
 
2.0%
Other values (121) 13345
45.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29372
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 3723
 
12.7%
군 3514
 
12.0%
구 3170
 
10.8%
천 1030
 
3.5%
주 900
 
3.1%
성 830
 
2.8%
양 794
 
2.7%
산 754
 
2.6%
동 739
 
2.5%
서 573
 
2.0%
Other values (121) 13345
45.4%

용도업종(소)
Categorical

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수도
 
345
가정용
 
339
화학제품
 
338
사업자용
 
331
목재.나무
 
329
Other values (33)
8318 

Length

Max length5
Median length4
Mean length4.0416
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수도
2nd row유리
3rd row수도
4th row섬유
5th row출판.인쇄

Common Values

ValueCountFrequency (%)
수도 345
 
3.5%
가정용 339
 
3.4%
화학제품 338
 
3.4%
사업자용 331
 
3.3%
목재.나무 329
 
3.3%
기타공공용 323
 
3.2%
고무.플라 318
 
3.2%
관공용 314
 
3.1%
농업.임업 312
 
3.1%
조립금속 312
 
3.1%
Other values (28) 6739
67.4%

Length

2023-12-13T04:55:00.684994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수도 345
 
3.5%
가정용 339
 
3.4%
화학제품 338
 
3.4%
사업자용 331
 
3.3%
목재.나무 329
 
3.3%
기타공공용 323
 
3.2%
고무.플라 318
 
3.2%
관공용 314
 
3.1%
조립금속 312
 
3.1%
농업.임업 312
 
3.1%
Other values (28) 6739
67.4%

판매량
Real number (ℝ)

Distinct9825
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6310337.6
Minimum0
Maximum9.7234784 × 108
Zeros12
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:55:00.824218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1679.85
Q133019.25
median314862.5
Q32411895.2
95-th percentile28057545
Maximum9.7234784 × 108
Range9.7234784 × 108
Interquartile range (IQR)2378876

Descriptive statistics

Standard deviation32534080
Coefficient of variation (CV)5.1556798
Kurtosis347.60991
Mean6310337.6
Median Absolute Deviation (MAD)311372
Skewness16.397957
Sum6.3103376 × 1010
Variance1.0584664 × 1015
MonotonicityNot monotonic
2023-12-13T04:55:01.017806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12
 
0.1%
7 4
 
< 0.1%
906 3
 
< 0.1%
8 3
 
< 0.1%
774 3
 
< 0.1%
831 3
 
< 0.1%
2355 3
 
< 0.1%
1902 2
 
< 0.1%
14 2
 
< 0.1%
127 2
 
< 0.1%
Other values (9815) 9963
99.6%
ValueCountFrequency (%)
0 12
0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
6 2
 
< 0.1%
7 4
 
< 0.1%
8 3
 
< 0.1%
11 1
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
972347835 1
< 0.1%
871004058 1
< 0.1%
789551142 1
< 0.1%
782395641 1
< 0.1%
763674625 1
< 0.1%
669829978 1
< 0.1%
648484164 1
< 0.1%
637062392 1
< 0.1%
621218934 1
< 0.1%
617848182 1
< 0.1%

Interactions

2023-12-13T04:54:58.630700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:55:01.131543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조회기간시도용도업종(소)판매량
조회기간1.0000.0000.0000.018
시도0.0001.0000.1080.081
용도업종(소)0.0000.1081.0000.216
판매량0.0180.0810.2161.000
2023-12-13T04:55:01.270931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도업종(소)시도
용도업종(소)1.0000.030
시도0.0301.000
2023-12-13T04:55:01.373025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
판매량시도용도업종(소)
판매량1.0000.0310.076
시도0.0311.0000.030
용도업종(소)0.0760.0301.000

Missing values

2023-12-13T04:54:58.767651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:54:58.875868image/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

조회기간시도시군구용도업종(소)판매량
154712016-12부산광역시사상구수도1258440
60882016-10경상북도문경시유리1505
113042016-11충청북도음성군수도430675
195222016-12전라북도장수군섬유15532
414432017-03전라남도나주시출판.인쇄16805
248932017-01경기도파주시전기기기2281120
48952016-10전라북도남원시재생재료286216
426922017-03경상남도거창군금속비금속1046363
198562016-12전라남도목포시가죽.신발3146
57502016-10전라남도진도군음료품제조12443
조회기간시도시군구용도업종(소)판매량
80882016-11부산광역시기장군농업.임업1358038
343012017-02전라남도목포시시멘트169961
314112017-02경기도군포시농업.임업207955
348692017-02경상북도군위군기타기계190856
110232016-11강원도태백시영상.음향3477
100852016-11경기도안성시영상.음향25562692
298902017-02부산광역시북구조립금속51149
412402017-03전라북도정읍시1차금속16499098
53162016-10전라남도광양시시멘트18144859
408122017-03충청남도태안군조립금속63211