Overview

Dataset statistics

Number of variables4
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory37.8 B

Variable types

DateTime1
Numeric3

Dataset

Description한국가스공사 인천기지본부의 연간 상수도 사용량으로, 용도별(설비용, 사무용) 상수도 사용량(㎥)에 대한 정보를 나타냄
Author한국가스공사
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15087687&srcSe=7661IVAWM27C61E190

Alerts

설비용사용량 is highly overall correlated with 합계High correlation
합계 is highly overall correlated with 설비용사용량High correlation
사용 월 has unique valuesUnique
설비용사용량 has unique valuesUnique

Reproduction

Analysis started2024-04-06 09:45:39.799846
Analysis finished2024-04-06 09:45:41.682281
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용 월
Date

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
Minimum2020-01-01 00:00:00
Maximum2023-12-01 00:00:00
2024-04-06T18:45:42.147077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:45:42.667672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)

설비용사용량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14545.896
Minimum4300
Maximum50749
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-04-06T18:45:43.085649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4300
5-th percentile6587.35
Q17570.75
median11394.5
Q316327.25
95-th percentile45688.35
Maximum50749
Range46449
Interquartile range (IQR)8756.5

Descriptive statistics

Standard deviation11120.184
Coefficient of variation (CV)0.76448945
Kurtosis4.4279975
Mean14545.896
Median Absolute Deviation (MAD)3963
Skewness2.2201599
Sum698203
Variance1.2365849 × 108
MonotonicityNot monotonic
2024-04-06T18:45:43.346208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
8729 1
 
2.1%
12591 1
 
2.1%
12302 1
 
2.1%
42829 1
 
2.1%
50749 1
 
2.1%
13526 1
 
2.1%
8708 1
 
2.1%
10211 1
 
2.1%
17287 1
 
2.1%
8323 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
4300 1
2.1%
5927 1
2.1%
6580 1
2.1%
6601 1
2.1%
6696 1
2.1%
6744 1
2.1%
6810 1
2.1%
6883 1
2.1%
7100 1
2.1%
7155 1
2.1%
ValueCountFrequency (%)
50749 1
2.1%
47718 1
2.1%
47228 1
2.1%
42829 1
2.1%
29044 1
2.1%
23924 1
2.1%
20933 1
2.1%
18032 1
2.1%
17489 1
2.1%
17287 1
2.1%

사무용사용량
Real number (ℝ)

Distinct47
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3254.7708
Minimum1813
Maximum6598
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-04-06T18:45:43.560530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1813
5-th percentile1861.55
Q12484.5
median2953
Q33562
95-th percentile5825.55
Maximum6598
Range4785
Interquartile range (IQR)1077.5

Descriptive statistics

Standard deviation1176.6136
Coefficient of variation (CV)0.36150429
Kurtosis1.1209405
Mean3254.7708
Median Absolute Deviation (MAD)558.5
Skewness1.2659573
Sum156229
Variance1384419.6
MonotonicityNot monotonic
2024-04-06T18:45:43.789714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
1813 2
 
4.2%
2567 1
 
2.1%
6598 1
 
2.1%
1922 1
 
2.1%
2248 1
 
2.1%
4539 1
 
2.1%
4284 1
 
2.1%
4482 1
 
2.1%
4146 1
 
2.1%
3513 1
 
2.1%
Other values (37) 37
77.1%
ValueCountFrequency (%)
1813 2
4.2%
1829 1
2.1%
1922 1
2.1%
2020 1
2.1%
2140 1
2.1%
2183 1
2.1%
2238 1
2.1%
2248 1
2.1%
2351 1
2.1%
2381 1
2.1%
ValueCountFrequency (%)
6598 1
2.1%
6073 1
2.1%
5835 1
2.1%
5808 1
2.1%
5658 1
2.1%
4539 1
2.1%
4482 1
2.1%
4337 1
2.1%
4284 1
2.1%
4146 1
2.1%

합계
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17800.667
Minimum7321
Maximum52997
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-04-06T18:45:44.036052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7321
5-th percentile8955.05
Q110221
median14596.5
Q319848
95-th percentile47549.9
Maximum52997
Range45676
Interquartile range (IQR)9627

Descriptive statistics

Standard deviation11043.967
Coefficient of variation (CV)0.62042435
Kurtosis3.6062917
Mean17800.667
Median Absolute Deviation (MAD)4899
Skewness1.9991801
Sum854432
Variance1.2196921 × 108
MonotonicityNot monotonic
2024-04-06T18:45:44.346019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
9682 2
 
4.2%
11296 1
 
2.1%
19480 1
 
2.1%
44751 1
 
2.1%
52997 1
 
2.1%
18065 1
 
2.1%
12992 1
 
2.1%
14693 1
 
2.1%
21433 1
 
2.1%
11836 1
 
2.1%
Other values (37) 37
77.1%
ValueCountFrequency (%)
7321 1
2.1%
7740 1
2.1%
8716 1
2.1%
9399 1
2.1%
9438 1
2.1%
9451 1
2.1%
9478 1
2.1%
9500 1
2.1%
9623 1
2.1%
9682 2
4.2%
ValueCountFrequency (%)
52997 1
2.1%
49531 1
2.1%
49057 1
2.1%
44751 1
2.1%
33381 1
2.1%
27184 1
2.1%
27006 1
2.1%
23867 1
2.1%
21433 1
2.1%
20993 1
2.1%

Interactions

2024-04-06T18:45:40.763026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:45:39.983849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:45:40.394652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:45:40.883738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:45:40.119109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:45:40.511457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:45:41.013265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:45:40.260858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:45:40.634286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T18:45:44.497799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용 월설비용사용량사무용사용량합계
사용 월1.0001.0001.0001.000
설비용사용량1.0001.0000.6780.992
사무용사용량1.0000.6781.0000.715
합계1.0000.9920.7151.000
2024-04-06T18:45:44.663904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설비용사용량사무용사용량합계
설비용사용량1.0000.2380.983
사무용사용량0.2381.0000.335
합계0.9830.3351.000

Missing values

2024-04-06T18:45:41.201868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T18:45:41.507337image/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

사용 월설비용사용량사무용사용량합계
02020-01-01 00:008729256711296
12020-02-01 00:00710023519451
22020-03-01 00:00592718137740
32020-04-01 00:00715524689623
42020-05-01 00:00752523819906
52020-06-01 00:00674426559399
62020-07-01 00:00430030217321
72020-08-01 00:00658028989478
82020-09-01 00:00660130819682
92020-10-01 00:00688325559438
사용 월설비용사용량사무용사용량합계
382023-03-01 00:0011400580817208
392023-04-01 00:008361565814019
402023-05-01 00:008786214010926
412023-06-01 00:0010327295013277
422023-07-01 00:00681026909500
432023-08-01 00:007701347011171
442023-09-01 00:007586274010326
452023-10-01 00:00669620208716
462023-11-01 00:0011389302014409
472023-12-01 00:0016108383019938