Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory332.0 KiB
Average record size in memory34.0 B

Variable types

Numeric2
DateTime1

Dataset

Description도시가스 산업용 수요의 일별 유효일수 데이터입니다. 공휴일 등 특정일을 반영한 유효일수를 나타내며, 도시가스 수요예측 등에 활용할 수 있습니다.
Author한국가스공사
URLhttps://www.data.go.kr/data/15088309/fileData.do

Alerts

순번 has unique valuesUnique
연월일 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:14:13.244882
Analysis finished2023-12-12 00:14:14.184944
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8420.0175
Minimum2
Maximum16800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:14:14.283013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile846.85
Q14236.75
median8410.5
Q312630.25
95-th percentile15942.05
Maximum16800
Range16798
Interquartile range (IQR)8393.5

Descriptive statistics

Standard deviation4850.7962
Coefficient of variation (CV)0.57610286
Kurtosis-1.2037602
Mean8420.0175
Median Absolute Deviation (MAD)4195
Skewness-0.0058572563
Sum84200175
Variance23530223
MonotonicityNot monotonic
2023-12-12T09:14:14.429469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9428 1
 
< 0.1%
15959 1
 
< 0.1%
14897 1
 
< 0.1%
12275 1
 
< 0.1%
2392 1
 
< 0.1%
10617 1
 
< 0.1%
13601 1
 
< 0.1%
7377 1
 
< 0.1%
1265 1
 
< 0.1%
15507 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
ValueCountFrequency (%)
16800 1
< 0.1%
16799 1
< 0.1%
16798 1
< 0.1%
16796 1
< 0.1%
16795 1
< 0.1%
16793 1
< 0.1%
16790 1
< 0.1%
16789 1
< 0.1%
16784 1
< 0.1%
16783 1
< 0.1%

연월일
Date

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1985-01-02 00:00:00
Maximum2030-12-30 00:00:00
2023-12-12T09:14:14.572401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:14:14.738077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

유효일수
Real number (ℝ)

Distinct117
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9196395
Minimum0.32815
Maximum1.02522
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T09:14:14.897942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.32815
5-th percentile0.71829
Q10.83792
median1.00528
Q31.00528
95-th percentile1.00528
Maximum1.02522
Range0.69707
Interquartile range (IQR)0.16736

Descriptive statistics

Standard deviation0.11644074
Coefficient of variation (CV)0.12661563
Kurtosis1.1440107
Mean0.9196395
Median Absolute Deviation (MAD)0
Skewness-1.3012033
Sum9196.395
Variance0.013558445
MonotonicityNot monotonic
2023-12-12T09:14:15.068737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.00528 5283
52.8%
0.71829 1354
 
13.5%
0.83792 1316
 
13.2%
0.94399 1259
 
12.6%
0.90555 97
 
1.0%
0.89066 62
 
0.6%
0.78459 43
 
0.4%
0.92398 21
 
0.2%
0.84346 17
 
0.2%
0.96253 17
 
0.2%
Other values (107) 531
 
5.3%
ValueCountFrequency (%)
0.32815 3
< 0.1%
0.34204 5
0.1%
0.39467 2
 
< 0.1%
0.41635 5
0.1%
0.41877 1
 
< 0.1%
0.42698 6
0.1%
0.43023 2
 
< 0.1%
0.43324 2
 
< 0.1%
0.43433 1
 
< 0.1%
0.45427 1
 
< 0.1%
ValueCountFrequency (%)
1.02522 3
 
< 0.1%
1.00528 5283
52.8%
0.9922 2
 
< 0.1%
0.98247 6
 
0.1%
0.97225 5
 
0.1%
0.96771 3
 
< 0.1%
0.96253 17
 
0.2%
0.95195 3
 
< 0.1%
0.94997 12
 
0.1%
0.94776 13
 
0.1%

Interactions

2023-12-12T09:14:13.726646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:14:13.465800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:14:13.873894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:14:13.584052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:14:15.199363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번유효일수
순번1.0000.046
유효일수0.0461.000
2023-12-12T09:14:15.295378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번유효일수
순번1.0000.017
유효일수0.0171.000

Missing values

2023-12-12T09:14:14.041104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:14:14.139858image/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

순번연월일유효일수
942794282010-10-240.71829
210121021990-10-030.43433
155615571989-04-061.00528
163516361989-06-240.83792
10352103532013-05-060.94399
12621126222019-07-231.00528
725772582004-11-140.71829
10776107772014-07-041.00528
458845891997-07-251.00528
13132131332020-12-151.00528
순번연월일유효일수
15262152632026-10-151.00528
12459124602019-02-110.94399
15764157652028-02-291.00528
158415851989-05-041.00528
16180161812029-04-201.00528
11171111722015-08-030.94399
893789382009-06-210.71829
144014411988-12-110.71829
758575862005-10-080.83792
10542105432013-11-121.00528