Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory498.0 KiB
Average record size in memory51.0 B

Variable types

Numeric3
Categorical2

Dataset

Description한국지역난방공사 내 동탄 및 용인 열원 간 일지별, 시간대별 실적 수열량에 대한 데이터로 2년간 수열실적을 제공합니다.
Author한국지역난방공사
URLhttps://www.data.go.kr/data/15124148/fileData.do

Alerts

공급사업장 has constant value ""Constant
수열사업장 has constant value ""Constant
실적일자 is highly overall correlated with 수열량High correlation
수열량 is highly overall correlated with 실적일자High correlation
수열량 has 6387 (63.9%) zerosZeros

Reproduction

Analysis started2023-12-12 19:36:53.451961
Analysis finished2023-12-12 19:36:55.575001
Duration2.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

실적일자
Real number (ℝ)

HIGH CORRELATION 

Distinct730
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20222623
Minimum20210910
Maximum20230910
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:36:55.669257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210910
5-th percentile20211015
Q120220313
median20220913
Q320230314
95-th percentile20230807
Maximum20230910
Range20000
Interquartile range (IQR)10001

Descriptive statistics

Standard deviation6659.6179
Coefficient of variation (CV)0.00032931523
Kurtosis-0.90706102
Mean20222623
Median Absolute Deviation (MAD)9192
Skewness-0.24350883
Sum2.0222623 × 1011
Variance44350510
MonotonicityNot monotonic
2023-12-13T04:36:55.841833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211014 20
 
0.2%
20230224 20
 
0.2%
20221210 19
 
0.2%
20230731 19
 
0.2%
20230214 19
 
0.2%
20230404 19
 
0.2%
20211031 19
 
0.2%
20210918 19
 
0.2%
20220918 19
 
0.2%
20230331 19
 
0.2%
Other values (720) 9808
98.1%
ValueCountFrequency (%)
20210910 14
0.1%
20210911 11
0.1%
20210912 11
0.1%
20210913 17
0.2%
20210914 14
0.1%
20210915 11
0.1%
20210916 13
0.1%
20210917 10
0.1%
20210918 19
0.2%
20210919 18
0.2%
ValueCountFrequency (%)
20230910 14
0.1%
20230909 17
0.2%
20230908 14
0.1%
20230907 16
0.2%
20230906 15
0.1%
20230905 12
0.1%
20230904 9
0.1%
20230903 18
0.2%
20230902 14
0.1%
20230901 14
0.1%

시간
Real number (ℝ)

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5801
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:36:55.985696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q17
median13
Q319
95-th percentile23
Maximum24
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.8976186
Coefficient of variation (CV)0.548296
Kurtosis-1.2039086
Mean12.5801
Median Absolute Deviation (MAD)6
Skewness-0.0027418884
Sum125801
Variance47.577142
MonotonicityNot monotonic
2023-12-13T04:36:56.126438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
11 440
 
4.4%
8 435
 
4.3%
23 429
 
4.3%
18 428
 
4.3%
17 426
 
4.3%
16 425
 
4.2%
12 425
 
4.2%
19 425
 
4.2%
24 424
 
4.2%
3 423
 
4.2%
Other values (14) 5720
57.2%
ValueCountFrequency (%)
1 375
3.8%
2 399
4.0%
3 423
4.2%
4 417
4.2%
5 421
4.2%
6 412
4.1%
7 420
4.2%
8 435
4.3%
9 416
4.2%
10 402
4.0%
ValueCountFrequency (%)
24 424
4.2%
23 429
4.3%
22 421
4.2%
21 410
4.1%
20 416
4.2%
19 425
4.2%
18 428
4.3%
17 426
4.3%
16 425
4.2%
15 392
3.9%

공급사업장
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
동탄
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동탄
2nd row동탄
3rd row동탄
4th row동탄
5th row동탄

Common Values

ValueCountFrequency (%)
동탄 10000
100.0%

Length

2023-12-13T04:36:56.278216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:36:56.385409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동탄 10000
100.0%

수열사업장
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
용인
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용인
2nd row용인
3rd row용인
4th row용인
5th row용인

Common Values

ValueCountFrequency (%)
용인 10000
100.0%

Length

2023-12-13T04:36:56.490478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:36:56.591553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용인 10000
100.0%

수열량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct112
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.9948
Minimum0
Maximum119
Zeros6387
Zeros (%)63.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:36:56.700472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q332
95-th percentile91
Maximum119
Range119
Interquartile range (IQR)32

Descriptive statistics

Standard deviation30.437185
Coefficient of variation (CV)1.6023956
Kurtosis0.80421712
Mean18.9948
Median Absolute Deviation (MAD)0
Skewness1.4564752
Sum189948
Variance926.42222
MonotonicityNot monotonic
2023-12-13T04:36:56.869974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6387
63.9%
32 86
 
0.9%
33 79
 
0.8%
20 64
 
0.6%
34 60
 
0.6%
88 60
 
0.6%
16 59
 
0.6%
38 59
 
0.6%
19 58
 
0.6%
22 58
 
0.6%
Other values (102) 3030
30.3%
ValueCountFrequency (%)
0 6387
63.9%
4 1
 
< 0.1%
6 2
 
< 0.1%
7 4
 
< 0.1%
8 5
 
0.1%
9 12
 
0.1%
10 17
 
0.2%
11 17
 
0.2%
12 19
 
0.2%
13 34
 
0.3%
ValueCountFrequency (%)
119 1
 
< 0.1%
116 2
 
< 0.1%
114 2
 
< 0.1%
113 1
 
< 0.1%
112 3
 
< 0.1%
110 6
0.1%
109 3
 
< 0.1%
108 1
 
< 0.1%
107 1
 
< 0.1%
106 9
0.1%

Interactions

2023-12-13T04:36:54.620158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:36:53.840075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:36:54.249366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:36:54.783121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:36:53.995425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:36:54.383383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:36:54.919398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:36:54.125203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:36:54.510031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:36:56.984406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실적일자시간수열량
실적일자1.0000.0000.655
시간0.0001.0000.126
수열량0.6550.1261.000
2023-12-13T04:36:57.092773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실적일자시간수열량
실적일자1.000-0.0110.505
시간-0.0111.000-0.001
수열량0.505-0.0011.000

Missing values

2023-12-13T04:36:55.088467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:36:55.522450image/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

실적일자시간공급사업장수열사업장수열량
149302021122624동탄용인0
3105202305047동탄용인29
124652022040823동탄용인0
4324202303141동탄용인60
5976202301049동탄용인95
73722022110720동탄용인71
141752022012724동탄용인0
59202023010618동탄용인97
75362022103114동탄용인34
118902022050223동탄용인0
실적일자시간공급사업장수열사업장수열량
159612021111211동탄용인0
124342022040920동탄용인0
990202307314동탄용인0
7945202210147동탄용인45
8488202209217동탄용인0
772023090718동탄용인0
21522023061211동탄용인14
109342022061123동탄용인0
119172022050112동탄용인0
58192023011111동탄용인88