Overview

Dataset statistics

Number of variables3
Number of observations55
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory28.4 B

Variable types

Categorical1
Numeric2

Dataset

Description한국가스기술공사의 고압에너지(전기) 사용량에 대한 데이터를 연도별 사용정보를 제고합니다. 사용량 단위는 kwh 입니다.
URLhttps://www.data.go.kr/data/15103186/fileData.do

Alerts

사용전력량 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:50:21.148499
Analysis finished2023-12-12 03:50:21.839896
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

Distinct5
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size572.0 B
2019년
12 
2020년
12 
2021년
12 
2022년
12 
2023년
7 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019년
2nd row2019년
3rd row2019년
4th row2019년
5th row2019년

Common Values

ValueCountFrequency (%)
2019년 12
21.8%
2020년 12
21.8%
2021년 12
21.8%
2022년 12
21.8%
2023년 7
12.7%

Length

2023-12-12T12:50:21.956932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:50:22.120619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019년 12
21.8%
2020년 12
21.8%
2021년 12
21.8%
2022년 12
21.8%
2023년 7
12.7%

해당월
Real number (ℝ)

Distinct12
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1818182
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T12:50:22.248160image/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 deviation3.4377583
Coefficient of variation (CV)0.55610795
Kurtosis-1.1504871
Mean6.1818182
Median Absolute Deviation (MAD)3
Skewness0.13791461
Sum340
Variance11.818182
MonotonicityNot monotonic
2023-12-12T12:50:22.371136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 5
9.1%
2 5
9.1%
3 5
9.1%
4 5
9.1%
5 5
9.1%
6 5
9.1%
7 5
9.1%
8 4
7.3%
9 4
7.3%
10 4
7.3%
Other values (2) 8
14.5%
ValueCountFrequency (%)
1 5
9.1%
2 5
9.1%
3 5
9.1%
4 5
9.1%
5 5
9.1%
6 5
9.1%
7 5
9.1%
8 4
7.3%
9 4
7.3%
10 4
7.3%
ValueCountFrequency (%)
12 4
7.3%
11 4
7.3%
10 4
7.3%
9 4
7.3%
8 4
7.3%
7 5
9.1%
6 5
9.1%
5 5
9.1%
4 5
9.1%
3 5
9.1%

사용전력량
Real number (ℝ)

UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64959.036
Minimum50329
Maximum83645
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T12:50:22.546297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50329
5-th percentile53006
Q158358.5
median64939
Q371551
95-th percentile77933.3
Maximum83645
Range33316
Interquartile range (IQR)13192.5

Descriptive statistics

Standard deviation8352.1922
Coefficient of variation (CV)0.12857629
Kurtosis-0.68596347
Mean64959.036
Median Absolute Deviation (MAD)6878
Skewness0.25103751
Sum3572747
Variance69759115
MonotonicityNot monotonic
2023-12-12T12:50:22.741108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57565 1
 
1.8%
58037 1
 
1.8%
71165 1
 
1.8%
72225 1
 
1.8%
71837 1
 
1.8%
64939 1
 
1.8%
71285 1
 
1.8%
74803 1
 
1.8%
72772 1
 
1.8%
65146 1
 
1.8%
Other values (45) 45
81.8%
ValueCountFrequency (%)
50329 1
1.8%
51470 1
1.8%
52656 1
1.8%
53156 1
1.8%
53500 1
1.8%
53784 1
1.8%
54692 1
1.8%
55473 1
1.8%
55843 1
1.8%
56769 1
1.8%
ValueCountFrequency (%)
83645 1
1.8%
83582 1
1.8%
79334 1
1.8%
77333 1
1.8%
76977 1
1.8%
74995 1
1.8%
74803 1
1.8%
74460 1
1.8%
72772 1
1.8%
72652 1
1.8%

Interactions

2023-12-12T12:50:21.481242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:50:21.251316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:50:21.577052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:50:21.355071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:50:22.892845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도해당월사용전력량
년도1.0000.0000.672
해당월0.0001.0000.000
사용전력량0.6720.0001.000
2023-12-12T12:50:23.021570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
해당월사용전력량년도
해당월1.0000.1280.000
사용전력량0.1281.0000.328
년도0.0000.3281.000

Missing values

2023-12-12T12:50:21.711302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:50:21.804942image/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

년도해당월사용전력량
02019년157565
12019년258037
22019년353156
32019년455843
42019년550329
52019년651470
62019년753784
72019년859837
82019년956769
92019년1055473
년도해당월사용전력량
452022년1068559
462022년1172652
472022년1277333
482023년183645
492023년276977
502023년364109
512023년468765
522023년563749
532023년667180
542023년771817