Overview

Dataset statistics

Number of variables3
Number of observations174
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory27.8 B

Variable types

Numeric3

Dataset

Description도시가스 산업용 월별 기온효과 자료입니다. 도시가스 산업용 수요에 기온이 미치는 정도를 나타내는 지표입니다. (2007.01~2021.06)
Author한국가스공사
URLhttps://www.data.go.kr/data/15065993/fileData.do

Alerts

기온효과 has 18 (10.3%) zerosZeros

Reproduction

Analysis started2023-12-30 04:57:34.748122
Analysis finished2023-12-30 04:57:41.212050
Duration6.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연
Real number (ℝ)

Distinct15
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.7586
Minimum2007
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-30T04:57:41.352869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2007
Q12010
median2014
Q32017
95-th percentile2020
Maximum2021
Range14
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.2028493
Coefficient of variation (CV)0.0020870671
Kurtosis-1.1942031
Mean2013.7586
Median Absolute Deviation (MAD)4
Skewness0.012391021
Sum350394
Variance17.663943
MonotonicityIncreasing
2023-12-30T04:57:41.687803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2007 12
 
6.9%
2008 12
 
6.9%
2009 12
 
6.9%
2010 12
 
6.9%
2011 12
 
6.9%
2012 12
 
6.9%
2013 12
 
6.9%
2014 12
 
6.9%
2015 12
 
6.9%
2016 12
 
6.9%
Other values (5) 54
31.0%
ValueCountFrequency (%)
2007 12
6.9%
2008 12
6.9%
2009 12
6.9%
2010 12
6.9%
2011 12
6.9%
2012 12
6.9%
2013 12
6.9%
2014 12
6.9%
2015 12
6.9%
2016 12
6.9%
ValueCountFrequency (%)
2021 6
3.4%
2020 12
6.9%
2019 12
6.9%
2018 12
6.9%
2017 12
6.9%
2016 12
6.9%
2015 12
6.9%
2014 12
6.9%
2013 12
6.9%
2012 12
6.9%

월
Real number (ℝ)

Distinct12
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3965517
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-30T04:57:41.967353image/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 deviation3.4604603
Coefficient of variation (CV)0.54098841
Kurtosis-1.2138565
Mean6.3965517
Median Absolute Deviation (MAD)3
Skewness0.045666883
Sum1113
Variance11.974786
MonotonicityNot monotonic
2023-12-30T04:57:42.188166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 15
8.6%
2 15
8.6%
3 15
8.6%
4 15
8.6%
5 15
8.6%
6 15
8.6%
7 14
8.0%
8 14
8.0%
9 14
8.0%
10 14
8.0%
Other values (2) 28
16.1%
ValueCountFrequency (%)
1 15
8.6%
2 15
8.6%
3 15
8.6%
4 15
8.6%
5 15
8.6%
6 15
8.6%
7 14
8.0%
8 14
8.0%
9 14
8.0%
10 14
8.0%
ValueCountFrequency (%)
12 14
8.0%
11 14
8.0%
10 14
8.0%
9 14
8.0%
8 14
8.0%
7 14
8.0%
6 15
8.6%
5 15
8.6%
4 15
8.6%
3 15
8.6%

기온효과
Real number (ℝ)

ZEROS 

Distinct44
Distinct (%)25.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.13597701
Minimum-0.02
Maximum0.51
Zeros18
Zeros (%)10.3%
Negative13
Negative (%)7.5%
Memory size1.7 KiB
2023-12-30T04:57:42.521503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.02
5-th percentile-0.01
Q10.01
median0.08
Q30.2375
95-th percentile0.3835
Maximum0.51
Range0.53
Interquartile range (IQR)0.2275

Descriptive statistics

Standard deviation0.14020183
Coefficient of variation (CV)1.0310701
Kurtosis-0.8129415
Mean0.13597701
Median Absolute Deviation (MAD)0.08
Skewness0.71461368
Sum23.66
Variance0.019656554
MonotonicityNot monotonic
2023-12-30T04:57:42.943437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0.0 18
 
10.3%
0.01 16
 
9.2%
0.02 13
 
7.5%
-0.01 10
 
5.7%
0.06 8
 
4.6%
0.2 7
 
4.0%
0.18 6
 
3.4%
0.3 6
 
3.4%
0.35 5
 
2.9%
0.17 5
 
2.9%
Other values (34) 80
46.0%
ValueCountFrequency (%)
-0.02 3
 
1.7%
-0.01 10
5.7%
0.0 18
10.3%
0.01 16
9.2%
0.02 13
7.5%
0.03 5
 
2.9%
0.04 5
 
2.9%
0.05 3
 
1.7%
0.06 8
4.6%
0.07 4
 
2.3%
ValueCountFrequency (%)
0.51 1
 
0.6%
0.44 1
 
0.6%
0.43 2
1.1%
0.42 1
 
0.6%
0.41 2
1.1%
0.4 1
 
0.6%
0.39 1
 
0.6%
0.38 4
2.3%
0.37 1
 
0.6%
0.36 3
1.7%

Interactions

2023-12-30T04:57:39.954997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:38.459082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:39.282680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:40.191884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:38.729810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:39.515074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:40.484243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:38.990597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:39.735090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-30T04:57:43.215952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월기온효과
연1.0000.0000.000
월0.0001.0000.914
기온효과0.0000.9141.000
2023-12-30T04:57:43.452471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월기온효과
연1.000-0.0500.116
월-0.0501.000-0.284
기온효과0.116-0.2841.000

Missing values

2023-12-30T04:57:40.885944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-30T04:57:41.121474image/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

연월기온효과
0200710.3
1200720.23
2200730.19
3200740.1
4200750.02
520076-0.01
620077-0.01
720078-0.02
8200790.0
92007100.06
연월기온효과
164202090.02
1652020100.08
1662020110.18
1672020120.35
168202110.41
169202120.28
170202130.16
171202140.09
172202150.06
173202160.02