Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory507.8 KiB
Average record size in memory52.0 B

Variable types

Numeric4
Categorical1

Dataset

Description한국지역난방공사의 수열열량 정보를 일자별, 시간대별, 지사별 예측한 시나리오 데이터입니다. 제공기간은 23년 6월부터 9월까지 입니다.
Author한국지역난방공사
URLhttps://www.data.go.kr/data/15124139/fileData.do

Alerts

시나리오아이디 is highly overall correlated with 계획일자High correlation
계획일자 is highly overall correlated with 시나리오아이디High correlation
수열량 has 5192 (51.9%) zerosZeros

Reproduction

Analysis started2023-12-12 13:22:27.648794
Analysis finished2023-12-12 13:22:30.116113
Duration2.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시나리오아이디
Real number (ℝ)

HIGH CORRELATION 

Distinct128
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58859.575
Minimum57224
Maximum59893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:22:30.190478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum57224
5-th percentile57224
Q158566
median59000
Q359440
95-th percentile59881
Maximum59893
Range2669
Interquartile range (IQR)874

Descriptive statistics

Standard deviation807.3391
Coefficient of variation (CV)0.01371636
Kurtosis-0.074010967
Mean58859.575
Median Absolute Deviation (MAD)434
Skewness-0.89783361
Sum5.8859575 × 108
Variance651796.42
MonotonicityNot monotonic
2023-12-12T22:22:30.332654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57224 1497
 
15.0%
58822 545
 
5.5%
59760 478
 
4.8%
59302 427
 
4.3%
58566 405
 
4.0%
59892 150
 
1.5%
59200 84
 
0.8%
59301 74
 
0.7%
59381 74
 
0.7%
58800 72
 
0.7%
Other values (118) 6194
61.9%
ValueCountFrequency (%)
57224 1497
15.0%
58340 15
 
0.1%
58360 31
 
0.3%
58380 48
 
0.5%
58381 61
 
0.6%
58382 61
 
0.6%
58400 49
 
0.5%
58420 64
 
0.6%
58440 51
 
0.5%
58460 15
 
0.1%
ValueCountFrequency (%)
59893 18
 
0.2%
59892 150
1.5%
59891 11
 
0.1%
59890 30
 
0.3%
59889 15
 
0.1%
59888 37
 
0.4%
59887 54
 
0.5%
59886 62
0.6%
59885 17
 
0.2%
59884 19
 
0.2%

열원시설명
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
고양
2562 
분당
2509 
세종
2494 
중앙
2435 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중앙
2nd row분당
3rd row세종
4th row중앙
5th row고양

Common Values

ValueCountFrequency (%)
고양 2562
25.6%
분당 2509
25.1%
세종 2494
24.9%
중앙 2435
24.3%

Length

2023-12-12T22:22:30.454024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:22:30.568292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고양 2562
25.6%
분당 2509
25.1%
세종 2494
24.9%
중앙 2435
24.3%

계획일자
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20230746
Minimum20230604
Maximum20230910
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:22:30.713055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20230604
5-th percentile20230609
Q120230701
median20230727
Q320230819
95-th percentile20230905
Maximum20230910
Range306
Interquartile range (IQR)118

Descriptive statistics

Standard deviation93.20925
Coefficient of variation (CV)4.6073066 × 10-6
Kurtosis-1.1197388
Mean20230746
Median Absolute Deviation (MAD)92
Skewness-0.023552459
Sum2.0230746 × 1011
Variance8687.9642
MonotonicityNot monotonic
2023-12-12T22:22:30.865122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230826 183
 
1.8%
20230825 169
 
1.7%
20230827 154
 
1.5%
20230809 149
 
1.5%
20230822 142
 
1.4%
20230810 135
 
1.4%
20230823 131
 
1.3%
20230626 130
 
1.3%
20230811 128
 
1.3%
20230606 124
 
1.2%
Other values (89) 8555
85.5%
ValueCountFrequency (%)
20230604 17
 
0.2%
20230605 109
1.1%
20230606 124
1.2%
20230607 105
1.1%
20230608 92
0.9%
20230609 82
0.8%
20230610 99
1.0%
20230611 86
0.9%
20230612 96
1.0%
20230613 73
0.7%
ValueCountFrequency (%)
20230910 78
0.8%
20230909 90
0.9%
20230908 91
0.9%
20230907 105
1.1%
20230906 85
0.9%
20230905 119
1.2%
20230904 107
1.1%
20230903 114
1.1%
20230902 87
0.9%
20230901 93
0.9%

시간
Real number (ℝ)

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.4538
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:22:30.995471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median12
Q318
95-th percentile23
Maximum24
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.9143797
Coefficient of variation (CV)0.5552024
Kurtosis-1.1981655
Mean12.4538
Median Absolute Deviation (MAD)6
Skewness0.016332489
Sum124538
Variance47.808646
MonotonicityNot monotonic
2023-12-12T22:22:31.166415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
9 457
 
4.6%
12 441
 
4.4%
4 427
 
4.3%
5 426
 
4.3%
24 424
 
4.2%
22 422
 
4.2%
3 420
 
4.2%
13 420
 
4.2%
8 418
 
4.2%
14 417
 
4.2%
Other values (14) 5728
57.3%
ValueCountFrequency (%)
1 416
4.2%
2 409
4.1%
3 420
4.2%
4 427
4.3%
5 426
4.3%
6 410
4.1%
7 410
4.1%
8 418
4.2%
9 457
4.6%
10 410
4.1%
ValueCountFrequency (%)
24 424
4.2%
23 407
4.1%
22 422
4.2%
21 409
4.1%
20 398
4.0%
19 416
4.2%
18 416
4.2%
17 400
4.0%
16 414
4.1%
15 400
4.0%

수열량
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.0401
Minimum-1
Maximum320
Zeros5192
Zeros (%)51.9%
Negative139
Negative (%)1.4%
Memory size166.0 KiB
2023-12-12T22:22:31.316113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q325
95-th percentile55
Maximum320
Range321
Interquartile range (IQR)25

Descriptive statistics

Standard deviation30.505395
Coefficient of variation (CV)1.9018208
Kurtosis22.97167
Mean16.0401
Median Absolute Deviation (MAD)0
Skewness3.8895544
Sum160401
Variance930.57915
MonotonicityNot monotonic
2023-12-12T22:22:31.470685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 5192
51.9%
25 1566
 
15.7%
55 1376
 
13.8%
4 1328
 
13.3%
-1 139
 
1.4%
180 66
 
0.7%
30 66
 
0.7%
20 39
 
0.4%
50 37
 
0.4%
100 37
 
0.4%
Other values (10) 154
 
1.5%
ValueCountFrequency (%)
-1 139
 
1.4%
0 5192
51.9%
4 1328
 
13.3%
9 32
 
0.3%
10 8
 
0.1%
14 5
 
0.1%
20 39
 
0.4%
25 1566
 
15.7%
30 66
 
0.7%
40 4
 
< 0.1%
ValueCountFrequency (%)
320 11
 
0.1%
250 1
 
< 0.1%
220 35
 
0.4%
180 66
 
0.7%
150 17
 
0.2%
140 26
 
0.3%
130 15
 
0.1%
100 37
 
0.4%
55 1376
13.8%
50 37
 
0.4%

Interactions

2023-12-12T22:22:29.543218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:28.224953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:28.679726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:29.123553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:29.653598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:28.331775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:28.793971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:29.231559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:29.751251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:28.472798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:28.910573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:29.346434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:29.846473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:28.578403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:29.023085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:29.440602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:22:31.576397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시나리오아이디열원시설명계획일자시간수열량
시나리오아이디1.0000.0000.9220.0000.249
열원시설명0.0001.0000.0000.0000.762
계획일자0.9220.0001.0000.0000.160
시간0.0000.0000.0001.0000.116
수열량0.2490.7620.1600.1161.000
2023-12-12T22:22:31.700455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시나리오아이디계획일자시간수열량열원시설명
시나리오아이디1.0000.7220.0010.2590.000
계획일자0.7221.000-0.0070.0730.000
시간0.001-0.0071.000-0.0030.000
수열량0.2590.073-0.0031.0000.429
열원시설명0.0000.0000.0000.4291.000

Missing values

2023-12-12T22:22:29.976358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:22:30.071272image/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

시나리오아이디열원시설명계획일자시간수열량
6391558381중앙202306062225
293559880분당20230906180
3668759100세종202307191055
920159720중앙202308271625
5246258640고양2023062530
3065958822고양20230730140
3600559140세종202307202055
4906258720세종202306301955
414859860세종20230904555
2239159340세종202308102130
시나리오아이디열원시설명계획일자시간수열량
65459892중앙20230909190
762659780고양2023082974
6088458382세종202306115-1
4245358940세종20230710455
466859880분당20230903130
1523059302분당20230821110
2900659220세종202308011155
5271258566세종20230625170
2620259280중앙20230805725
1326959601세종202308234130