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 민수용 수요 전망시 사용되는 월별 유효일수 자료입니다. 공휴일 등의 특수일을 고려하여 산정된 유효일수입니다.(2007.01~2021.06)
Author한국가스공사
URLhttps://www.data.go.kr/data/15066050/fileData.do

Reproduction

Analysis started2023-12-30 04:48:31.147934
Analysis finished2023-12-30 04:48:35.450302
Duration4.3 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
2023-12-30T04:48:35.709851image/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
2023-12-30T04:48:36.461573image/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
2023-12-30T04:48:37.384027image/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
2023-12-30T04:48:38.096885image/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%

유효일수
Real number (ℝ)

Distinct71
Distinct (%)40.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.994425
Minimum27.61
Maximum30.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-30T04:48:38.902810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27.61
5-th percentile27.81
Q129.6725
median30.45
Q330.72
95-th percentile30.79
Maximum30.81
Range3.2
Interquartile range (IQR)1.0475

Descriptive statistics

Standard deviation0.91048387
Coefficient of variation (CV)0.030355103
Kurtosis0.68539753
Mean29.994425
Median Absolute Deviation (MAD)0.335
Skewness-1.2844862
Sum5219.03
Variance0.82898088
MonotonicityNot monotonic
2023-12-30T04:48:39.444775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29.82 15
 
8.6%
30.76 10
 
5.7%
30.46 7
 
4.0%
30.72 6
 
3.4%
30.75 6
 
3.4%
30.74 5
 
2.9%
29.79 5
 
2.9%
30.77 5
 
2.9%
30.79 4
 
2.3%
29.74 4
 
2.3%
Other values (61) 107
61.5%
ValueCountFrequency (%)
27.61 3
1.7%
27.66 2
1.1%
27.68 3
1.7%
27.81 2
1.1%
27.88 1
 
0.6%
28.2 1
 
0.6%
28.23 2
1.1%
28.28 2
1.1%
28.3 1
 
0.6%
28.32 2
1.1%
ValueCountFrequency (%)
30.81 3
 
1.7%
30.8 4
 
2.3%
30.79 4
 
2.3%
30.78 2
 
1.1%
30.77 5
2.9%
30.76 10
5.7%
30.75 6
3.4%
30.74 5
2.9%
30.73 3
 
1.7%
30.72 6
3.4%

Interactions

2023-12-30T04:48:33.601505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:48:31.477468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:48:32.532988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:48:33.979973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:48:31.842912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:48:32.921479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:48:34.336225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:48:32.159742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:48:33.245071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-30T04:48:39.868368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월유효일수
연1.0000.0000.000
월0.0001.0000.812
유효일수0.0000.8121.000
2023-12-30T04:48:40.393731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월유효일수
연1.000-0.050-0.026
월-0.0501.0000.099
유효일수-0.0260.0991.000

Missing values

2023-12-30T04:48:34.942549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-30T04:48:35.309725image/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

연월유효일수
02007130.76
12007227.68
22007330.72
32007429.76
42007530.53
52007629.59
62007730.59
72007830.48
82007928.2
920071030.81
연월유효일수
1642020929.35
16520201029.74
16620201129.77
16720201230.74
1682021130.67
1692021227.66
1702021330.76
1712021429.82
1722021530.45
1732021629.64