Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells204
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory761.7 KiB
Average record size in memory78.0 B

Variable types

Numeric6
Categorical1
Text1

Dataset

Description산업분류별 전력사용량 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=KSB2T8Q0EHTFND5VLSSV27081780&infSeq=1

Alerts

사용년도 is highly overall correlated with 평균판매단가(원/kWh)High correlation
고객가구수(호) is highly overall correlated with 전력사용량(kWh) and 1 other fieldsHigh correlation
전력사용량(kWh) is highly overall correlated with 고객가구수(호) and 1 other fieldsHigh correlation
전기요금합계(원) is highly overall correlated with 고객가구수(호) and 1 other fieldsHigh correlation
평균판매단가(원/kWh) is highly overall correlated with 사용년도High correlation
평균판매단가(원/kWh) is highly skewed (γ1 = 29.12723905)Skewed

Reproduction

Analysis started2024-04-11 03:01:18.156368
Analysis finished2024-04-11 03:01:24.212348
Duration6.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용년도
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.9898
Minimum2007
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-11T12:01:24.259819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2008
Q12013
median2019
Q32021
95-th percentile2023
Maximum2024
Range17
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.9376446
Coefficient of variation (CV)0.0024480265
Kurtosis-1.0417311
Mean2016.9898
Median Absolute Deviation (MAD)3
Skewness-0.50969692
Sum20169898
Variance24.380334
MonotonicityNot monotonic
2024-04-11T12:01:24.358088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
2022 1084
 
10.8%
2023 1072
 
10.7%
2020 1025
 
10.2%
2021 937
 
9.4%
2019 869
 
8.7%
2018 456
 
4.6%
2011 443
 
4.4%
2014 436
 
4.4%
2017 434
 
4.3%
2010 426
 
4.3%
Other values (8) 2818
28.2%
ValueCountFrequency (%)
2007 295
2.9%
2008 359
3.6%
2009 426
4.3%
2010 426
4.3%
2011 443
4.4%
2012 418
4.2%
2013 422
4.2%
2014 436
4.4%
2015 422
4.2%
2016 393
3.9%
ValueCountFrequency (%)
2024 83
 
0.8%
2023 1072
10.7%
2022 1084
10.8%
2021 937
9.4%
2020 1025
10.2%
2019 869
8.7%
2018 456
4.6%
2017 434
4.3%
2016 393
 
3.9%
2015 422
 
4.2%

사용월
Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3656
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-11T12:01:24.468316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4786415
Coefficient of variation (CV)0.54647504
Kurtosis-1.2201304
Mean6.3656
Median Absolute Deviation (MAD)3
Skewness0.050979752
Sum63656
Variance12.100947
MonotonicityNot monotonic
2024-04-11T12:01:24.558704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 929
9.3%
5 925
9.2%
7 885
8.8%
2 874
8.7%
3 860
8.6%
10 826
8.3%
12 816
8.2%
6 810
8.1%
11 808
8.1%
4 775
7.8%
Other values (2) 1492
14.9%
ValueCountFrequency (%)
1 929
9.3%
2 874
8.7%
3 860
8.6%
4 775
7.8%
5 925
9.2%
6 810
8.1%
7 885
8.8%
8 749
7.5%
9 743
7.4%
10 826
8.3%
ValueCountFrequency (%)
12 816
8.2%
11 808
8.1%
10 826
8.3%
9 743
7.4%
8 749
7.5%
7 885
8.8%
6 810
8.1%
5 925
9.2%
4 775
7.8%
3 860
8.6%

시군명
Categorical

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원시
 
363
의정부시
 
351
평택시
 
348
파주시
 
346
광주시
 
345
Other values (26)
8247 

Length

Max length4
Median length3
Mean length3.1006
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row군포시
2nd row이천시
3rd row광주시
4th row이천시
5th row가평군

Common Values

ValueCountFrequency (%)
수원시 363
 
3.6%
의정부시 351
 
3.5%
평택시 348
 
3.5%
파주시 346
 
3.5%
광주시 345
 
3.5%
성남시 343
 
3.4%
이천시 337
 
3.4%
의왕시 331
 
3.3%
광명시 331
 
3.3%
하남시 328
 
3.3%
Other values (21) 6577
65.8%

Length

2024-04-11T12:01:24.652660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 363
 
3.6%
의정부시 351
 
3.5%
평택시 348
 
3.5%
파주시 346
 
3.5%
광주시 345
 
3.5%
성남시 343
 
3.4%
이천시 337
 
3.4%
의왕시 331
 
3.3%
광명시 331
 
3.3%
하남시 328
 
3.3%
Other values (21) 6577
65.8%

산업종류명
Text

Distinct54
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-11T12:01:24.798241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length9.2086
Min length2

Characters and Unicode

Total characters92086
Distinct characters104
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row도매 및 소매업
2nd row사업시설관리,사업지원서비스업
3rd row건설업
4th row도매 및 소매업
5th row광업
ValueCountFrequency (%)
및 4146
18.6%
소매업 905
 
4.0%
도매 905
 
4.0%
운수업 894
 
4.0%
농업 877
 
3.9%
임업 877
 
3.9%
어업 877
 
3.9%
제조업 871
 
3.9%
가스 829
 
3.7%
전기 829
 
3.7%
Other values (72) 10336
46.3%
2024-04-11T12:01:25.266024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14531
 
15.8%
업 11229
 
12.2%
및 4518
 
4.9%
, 4196
 
4.6%
기 3015
 
3.3%
스 2817
 
3.1%
수 2731
 
3.0%
비 1871
 
2.0%
매 1824
 
2.0%
사 1820
 
2.0%
Other values (94) 43534
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73359
79.7%
Space Separator 14531
 
15.8%
Other Punctuation 4196
 
4.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 11229
 
15.3%
및 4518
 
6.2%
기 3015
 
4.1%
스 2817
 
3.8%
수 2731
 
3.7%
비 1871
 
2.6%
매 1824
 
2.5%
사 1820
 
2.5%
도 1750
 
2.4%
원 1737
 
2.4%
Other values (92) 40047
54.6%
Space Separator
ValueCountFrequency (%)
14531
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73359
79.7%
Common 18727
 
20.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 11229
 
15.3%
및 4518
 
6.2%
기 3015
 
4.1%
스 2817
 
3.8%
수 2731
 
3.7%
비 1871
 
2.6%
매 1824
 
2.5%
사 1820
 
2.5%
도 1750
 
2.4%
원 1737
 
2.4%
Other values (92) 40047
54.6%
Common
ValueCountFrequency (%)
14531
77.6%
, 4196
 
22.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73359
79.7%
ASCII 18727
 
20.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14531
77.6%
, 4196
 
22.4%
Hangul
ValueCountFrequency (%)
업 11229
 
15.3%
및 4518
 
6.2%
기 3015
 
4.1%
스 2817
 
3.8%
수 2731
 
3.7%
비 1871
 
2.6%
매 1824
 
2.5%
사 1820
 
2.5%
도 1750
 
2.4%
원 1737
 
2.4%
Other values (92) 40047
54.6%

고객가구수(호)
Real number (ℝ)

HIGH CORRELATION 

Distinct3794
Distinct (%)38.1%
Missing51
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean2770.7732
Minimum1
Maximum109408
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-11T12:01:25.386227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q1137
median504
Q31981
95-th percentile12125.4
Maximum109408
Range109407
Interquartile range (IQR)1844

Descriptive statistics

Standard deviation7475.8599
Coefficient of variation (CV)2.6981132
Kurtosis60.232497
Mean2770.7732
Median Absolute Deviation (MAD)466
Skewness6.673546
Sum27566423
Variance55888482
MonotonicityNot monotonic
2024-04-11T12:01:25.517619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 133
 
1.3%
4 104
 
1.0%
5 90
 
0.9%
3 71
 
0.7%
2 59
 
0.6%
8 48
 
0.5%
9 45
 
0.4%
6 44
 
0.4%
34 36
 
0.4%
26 34
 
0.3%
Other values (3784) 9285
92.8%
(Missing) 51
 
0.5%
ValueCountFrequency (%)
1 133
1.3%
2 59
0.6%
3 71
0.7%
4 104
1.0%
5 90
0.9%
6 44
 
0.4%
7 29
 
0.3%
8 48
 
0.5%
9 45
 
0.4%
10 25
 
0.2%
ValueCountFrequency (%)
109408 1
< 0.1%
108389 1
< 0.1%
104338 1
< 0.1%
102323 1
< 0.1%
100781 1
< 0.1%
100580 1
< 0.1%
99502 1
< 0.1%
99448 1
< 0.1%
99182 1
< 0.1%
94652 1
< 0.1%

전력사용량(kWh)
Real number (ℝ)

HIGH CORRELATION 

Distinct9935
Distinct (%)99.9%
Missing51
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean25338251
Minimum-18524874
Maximum1.7491451 × 109
Zeros3
Zeros (%)< 0.1%
Negative3
Negative (%)< 0.1%
Memory size166.0 KiB
2024-04-11T12:01:25.640745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-18524874
5-th percentile49587.4
Q1812307
median2824379
Q39228595
95-th percentile86641531
Maximum1.7491451 × 109
Range1.76767 × 109
Interquartile range (IQR)8416288

Descriptive statistics

Standard deviation1.1235749 × 108
Coefficient of variation (CV)4.4343033
Kurtosis97.305365
Mean25338251
Median Absolute Deviation (MAD)2455811
Skewness8.9683188
Sum2.5209025 × 1011
Variance1.2624205 × 1016
MonotonicityNot monotonic
2024-04-11T12:01:25.793242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
< 0.1%
31821 2
 
< 0.1%
8292 2
 
< 0.1%
2067787 2
 
< 0.1%
2723 2
 
< 0.1%
433 2
 
< 0.1%
35473 2
 
< 0.1%
367905 2
 
< 0.1%
67 2
 
< 0.1%
111 2
 
< 0.1%
Other values (9925) 9928
99.3%
(Missing) 51
 
0.5%
ValueCountFrequency (%)
-18524874 1
 
< 0.1%
-8863700 1
 
< 0.1%
-1748716 1
 
< 0.1%
0 3
< 0.1%
13 1
 
< 0.1%
21 1
 
< 0.1%
22 1
 
< 0.1%
26 1
 
< 0.1%
28 1
 
< 0.1%
59 1
 
< 0.1%
ValueCountFrequency (%)
1749145126 1
< 0.1%
1708667872 1
< 0.1%
1704995051 1
< 0.1%
1597355183 1
< 0.1%
1591957129 1
< 0.1%
1579493647 1
< 0.1%
1559609821 1
< 0.1%
1552422747 1
< 0.1%
1547158334 1
< 0.1%
1544957706 1
< 0.1%

전기요금합계(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct9947
Distinct (%)> 99.9%
Missing51
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean2.8873066 × 109
Minimum-9.2036542 × 108
Maximum2.8647289 × 1011
Zeros3
Zeros (%)< 0.1%
Negative1
Negative (%)< 0.1%
Memory size166.0 KiB
2024-04-11T12:01:25.957242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9.2036542 × 108
5-th percentile5800669.8
Q195488371
median3.2464706 × 108
Q39.8394277 × 108
95-th percentile1.0308497 × 1010
Maximum2.8647289 × 1011
Range2.8739326 × 1011
Interquartile range (IQR)8.884544 × 108

Descriptive statistics

Standard deviation1.3310422 × 1010
Coefficient of variation (CV)4.6099788
Kurtosis135.25738
Mean2.8873066 × 109
Median Absolute Deviation (MAD)2.8357813 × 108
Skewness10.268928
Sum2.8725813 × 1013
Variance1.7716734 × 1020
MonotonicityNot monotonic
2024-04-11T12:01:26.089466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
< 0.1%
1010044146 1
 
< 0.1%
21471606416 1
 
< 0.1%
161064751 1
 
< 0.1%
8814783 1
 
< 0.1%
10785484187 1
 
< 0.1%
859939374 1
 
< 0.1%
169935705 1
 
< 0.1%
419999400 1
 
< 0.1%
97550464442 1
 
< 0.1%
Other values (9937) 9937
99.4%
(Missing) 51
 
0.5%
ValueCountFrequency (%)
-920365415 1
 
< 0.1%
0 3
< 0.1%
4010 1
 
< 0.1%
5823 1
 
< 0.1%
7250 1
 
< 0.1%
8852 1
 
< 0.1%
10446 1
 
< 0.1%
14413 1
 
< 0.1%
25151 1
 
< 0.1%
28771 1
 
< 0.1%
ValueCountFrequency (%)
286472891746 1
< 0.1%
244558487801 1
< 0.1%
230629826081 1
< 0.1%
228432963196 1
< 0.1%
222005435119 1
< 0.1%
221833957419 1
< 0.1%
211924797357 1
< 0.1%
208579970238 1
< 0.1%
204334085954 1
< 0.1%
202592835473 1
< 0.1%

평균판매단가(원/kWh)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1674
Distinct (%)16.8%
Missing51
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean121.82492
Minimum-193.9
Maximum4198.8
Zeros3
Zeros (%)< 0.1%
Negative2
Negative (%)< 0.1%
Memory size166.0 KiB
2024-04-11T12:01:26.215728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-193.9
5-th percentile49.8
Q198.5
median121.8
Q3140.1
95-th percentile178.5
Maximum4198.8
Range4392.7
Interquartile range (IQR)41.6

Descriptive statistics

Standard deviation73.744029
Coefficient of variation (CV)0.60532796
Kurtosis1349.1092
Mean121.82492
Median Absolute Deviation (MAD)20.6
Skewness29.127239
Sum1212036.1
Variance5438.1818
MonotonicityNot monotonic
2024-04-11T12:01:26.339972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
132.0 24
 
0.2%
129.9 23
 
0.2%
132.6 23
 
0.2%
112.7 22
 
0.2%
132.4 22
 
0.2%
124.4 21
 
0.2%
128.3 21
 
0.2%
129.4 21
 
0.2%
120.6 20
 
0.2%
131.4 20
 
0.2%
Other values (1664) 9732
97.3%
(Missing) 51
 
0.5%
ValueCountFrequency (%)
-193.9 1
 
< 0.1%
-2.0 1
 
< 0.1%
0.0 3
< 0.1%
18.8 1
 
< 0.1%
19.9 1
 
< 0.1%
33.3 1
 
< 0.1%
34.2 1
 
< 0.1%
34.4 1
 
< 0.1%
35.3 1
 
< 0.1%
35.9 1
 
< 0.1%
ValueCountFrequency (%)
4198.8 1
< 0.1%
3209.5 1
< 0.1%
2118.5 1
< 0.1%
1720.9 1
< 0.1%
1647.8 1
< 0.1%
1111.3 1
< 0.1%
968.1 1
< 0.1%
836.5 1
< 0.1%
811.0 1
< 0.1%
659.9 1
< 0.1%

Interactions

2024-04-11T12:01:23.392766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:20.730431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:21.344088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:21.858602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:22.351687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:22.871315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:23.469569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:20.875757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:21.435100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:21.940096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:22.438626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:22.955116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:23.551242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:20.967168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:21.523665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:22.014449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:22.521946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:23.037810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:23.642679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:21.046033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:21.607080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:22.090446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:22.610159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:23.136904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:23.735870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:21.166312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:21.705517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:22.175028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:22.701133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:23.231153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:23.820158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:21.259120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:21.787060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:22.273846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:22.793638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:01:23.315930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-11T12:01:26.434419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용년도사용월시군명산업종류명고객가구수(호)전력사용량(kWh)전기요금합계(원)평균판매단가(원/kWh)
사용년도1.0000.1540.0000.6880.1200.0920.0620.010
사용월0.1541.0000.0000.1590.0400.0400.0000.021
시군명0.0000.0001.0000.0380.3080.3740.2980.103
산업종류명0.6880.1590.0381.0000.6640.5030.4110.349
고객가구수(호)0.1200.0400.3080.6641.0000.7400.6620.000
전력사용량(kWh)0.0920.0400.3740.5030.7401.0000.9350.000
전기요금합계(원)0.0620.0000.2980.4110.6620.9351.0000.000
평균판매단가(원/kWh)0.0100.0210.1030.3490.0000.0000.0001.000
2024-04-11T12:01:26.549955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용년도사용월고객가구수(호)전력사용량(kWh)전기요금합계(원)평균판매단가(원/kWh)시군명
사용년도1.000-0.0600.0460.0530.1480.5890.000
사용월-0.0601.0000.025-0.0070.0030.0810.000
고객가구수(호)0.0460.0251.0000.7590.718-0.1780.119
전력사용량(kWh)0.053-0.0070.7591.0000.981-0.1550.140
전기요금합계(원)0.1480.0030.7180.9811.0000.0040.109
평균판매단가(원/kWh)0.5890.081-0.178-0.1550.0041.0000.043
시군명0.0000.0000.1190.1400.1090.0431.000

Missing values

2024-04-11T12:01:23.919370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-11T12:01:24.053934image/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.
2024-04-11T12:01:24.154021image/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

사용년도사용월시군명산업종류명고객가구수(호)전력사용량(kWh)전기요금합계(원)평균판매단가(원/kWh)
6587520091군포시도매 및 소매업365713765784124882893690.7
3339120196이천시사업시설관리,사업지원서비스업18739140060419303154.4
333920238광주시건설업9171564320329678368210.7
1830202311이천시도매 및 소매업291669595661185505799170.3
1363520224가평군광업727796446599582167.6
43720241연천군광업12633928150773055237.8
3000420201연천군사업시설관리,사업지원서비스업35339744712728138.7
6535320093과천시전기, 가스, 중기 및 수도사업35256257114835682457.9
3344220196평택시운수업1173302241513956080093130.9
6833120083용인시도매 및 소매업551190054918252816696.0
사용년도사용월시군명산업종류명고객가구수(호)전력사용량(kWh)전기요금합계(원)평균판매단가(원/kWh)
747202312광주시숙박및음식점업21835377544946407725176.0
6401520099양평군전기, 가스, 중기 및 수도사업5309093788235487190.6
1081420229연천군하수폐기처리원료재생환경복원2292686062317970733118.4
16382202111김포시예술,스포츠및여가관련서비스업271929020133505948143.7
3789220187화성시도매 및 소매업4216180449462525002589139.9
6417520098김포시하수폐기처리원료재생환경복원891615826207282782128.3
5901420115동두천시제조업31214474698114229724878.9
5837320118오산시광업420300198037597.6
2633320207양주시전기, 가스, 증기 및 수도사업5293984554513191072128.8
10337202210하남시합계2046710095014212783483138126.6