Overview

Dataset statistics

Number of variables4
Number of observations76
Missing cells16
Missing cells (%)5.3%
Duplicate rows1
Duplicate rows (%)1.3%
Total size in memory2.7 KiB
Average record size in memory36.7 B

Variable types

DateTime1
Numeric3

Dataset

Description인천광역시 동구청사 에너지사용량의 월별 데이터로, 연월, 전기사용량, 수도사용량, 가스사용량에 대한 항목을 제공합니다.
Author인천광역시 동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15113820&srcSe=7661IVAWM27C61E190

Alerts

Dataset has 1 (1.3%) duplicate rowsDuplicates
연월 has 4 (5.3%) missing valuesMissing
전기사용량 has 4 (5.3%) missing valuesMissing
수도사용량 has 4 (5.3%) missing valuesMissing
가스사용량 has 4 (5.3%) missing valuesMissing

Reproduction

Analysis started2024-05-17 21:16:48.951129
Analysis finished2024-05-17 21:16:52.643831
Duration3.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월
Date

MISSING 

Distinct72
Distinct (%)100.0%
Missing4
Missing (%)5.3%
Memory size740.0 B
Minimum2018-01-01 00:00:00
Maximum2023-12-01 00:00:00
2024-05-18T06:16:52.859802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:16:53.328315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전기사용량
Real number (ℝ)

MISSING 

Distinct72
Distinct (%)100.0%
Missing4
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean124618.97
Minimum86209
Maximum178405
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2024-05-18T06:16:53.775924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86209
5-th percentile93180.2
Q1104910
median124442
Q3141675.25
95-th percentile164932.15
Maximum178405
Range92196
Interquartile range (IQR)36765.25

Descriptive statistics

Standard deviation22814.369
Coefficient of variation (CV)0.183073
Kurtosis-0.72248694
Mean124618.97
Median Absolute Deviation (MAD)19394.5
Skewness0.34967554
Sum8972566
Variance5.2049545 × 108
MonotonicityNot monotonic
2024-05-18T06:16:54.196575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
114630 1
 
1.3%
135014 1
 
1.3%
104973 1
 
1.3%
94906 1
 
1.3%
117182 1
 
1.3%
137715 1
 
1.3%
167246 1
 
1.3%
156878 1
 
1.3%
125001 1
 
1.3%
104638 1
 
1.3%
Other values (62) 62
81.6%
(Missing) 4
 
5.3%
ValueCountFrequency (%)
86209 1
1.3%
87737 1
1.3%
90531 1
1.3%
93079 1
1.3%
93263 1
1.3%
93309 1
1.3%
94906 1
1.3%
95703 1
1.3%
97077 1
1.3%
97429 1
1.3%
ValueCountFrequency (%)
178405 1
1.3%
171672 1
1.3%
169088 1
1.3%
167246 1
1.3%
163039 1
1.3%
157839 1
1.3%
156878 1
1.3%
156326 1
1.3%
153473 1
1.3%
151191 1
1.3%

수도사용량
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)86.1%
Missing4
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean715.09722
Minimum547
Maximum918
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2024-05-18T06:16:54.596624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum547
5-th percentile570.65
Q1662.75
median722
Q3762.25
95-th percentile832.75
Maximum918
Range371
Interquartile range (IQR)99.5

Descriptive statistics

Standard deviation82.401484
Coefficient of variation (CV)0.11523116
Kurtosis-0.21165522
Mean715.09722
Median Absolute Deviation (MAD)56
Skewness-0.056921961
Sum51487
Variance6790.0045
MonotonicityNot monotonic
2024-05-18T06:16:55.030967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
715 3
 
3.9%
666 2
 
2.6%
738 2
 
2.6%
722 2
 
2.6%
729 2
 
2.6%
750 2
 
2.6%
742 2
 
2.6%
786 2
 
2.6%
726 2
 
2.6%
572 1
 
1.3%
Other values (52) 52
68.4%
(Missing) 4
 
5.3%
ValueCountFrequency (%)
547 1
1.3%
559 1
1.3%
566 1
1.3%
569 1
1.3%
572 1
1.3%
578 1
1.3%
584 1
1.3%
587 1
1.3%
588 1
1.3%
610 1
1.3%
ValueCountFrequency (%)
918 1
1.3%
901 1
1.3%
854 1
1.3%
841 1
1.3%
826 1
1.3%
823 1
1.3%
816 1
1.3%
814 1
1.3%
808 1
1.3%
807 1
1.3%

가스사용량
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)95.8%
Missing4
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean992.11111
Minimum5
Maximum4799
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2024-05-18T06:16:55.293200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile10.65
Q183
median355
Q31291.75
95-th percentile3460.25
Maximum4799
Range4794
Interquartile range (IQR)1208.75

Descriptive statistics

Standard deviation1281.5833
Coefficient of variation (CV)1.291774
Kurtosis0.45239462
Mean992.11111
Median Absolute Deviation (MAD)335
Skewness1.3126741
Sum71432
Variance1642455.8
MonotonicityNot monotonic
2024-05-18T06:16:55.650782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 2
 
2.6%
355 2
 
2.6%
20 2
 
2.6%
795 1
 
1.3%
90 1
 
1.3%
412 1
 
1.3%
1224 1
 
1.3%
2953 1
 
1.3%
3737 1
 
1.3%
3317 1
 
1.3%
Other values (59) 59
77.6%
(Missing) 4
 
5.3%
ValueCountFrequency (%)
5 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
12 1
1.3%
14 1
1.3%
15 2
2.6%
20 2
2.6%
24 1
1.3%
28 1
1.3%
ValueCountFrequency (%)
4799 1
1.3%
4201 1
1.3%
3737 1
1.3%
3540 1
1.3%
3395 1
1.3%
3317 1
1.3%
3266 1
1.3%
3098 1
1.3%
3062 1
1.3%
2976 1
1.3%

Interactions

2024-05-18T06:16:50.673223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:16:49.138834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:16:49.910293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:16:51.219736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:16:49.367580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:16:50.161362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:16:51.464178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:16:49.665584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:16:50.426746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T06:16:55.816014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월전기사용량수도사용량가스사용량
연월1.0001.0001.0001.000
전기사용량1.0001.0000.4360.690
수도사용량1.0000.4361.0000.000
가스사용량1.0000.6900.0001.000
2024-05-18T06:16:55.973461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전기사용량수도사용량가스사용량
전기사용량1.0000.2060.355
수도사용량0.2061.000-0.072
가스사용량0.355-0.0721.000

Missing values

2024-05-18T06:16:51.780285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T06:16:52.130316image/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.
2024-05-18T06:16:52.382384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연월전기사용량수도사용량가스사용량
02018-01-011534737263098
12018-02-011716727154799
22018-03-011217876323266
32018-04-01102556547553
42018-05-018620974693
52018-06-019307963371
62018-07-011094625669
72018-08-0114964071215
82018-09-011356377945
92018-10-0110024471312
연월전기사용량수도사용량가스사용량
662023-07-01126375745355
672023-08-011498696461375
682023-09-01143836739766
692023-10-01115224808278
702023-11-01108960569243
712023-12-01143837799407
72<NA><NA><NA><NA>
73<NA><NA><NA><NA>
74<NA><NA><NA><NA>
75<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

연월전기사용량수도사용량가스사용량# duplicates
0<NA><NA><NA><NA>4