Overview

Dataset statistics

Number of variables6
Number of observations1464
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory74.5 KiB
Average record size in memory52.1 B

Variable types

DateTime1
Numeric4
Categorical1

Dataset

Description서울에너지공사의 지사별 시간대별 열공급량 데이터로 실적일자, 시간, 단위, 열공급량(Gcal) 정보를 포함합니다.
Author서울에너지공사
URLhttps://www.data.go.kr/data/15111861/fileData.do

Alerts

단위(열공급) has constant value ""Constant
목동 is highly overall correlated with 마곡 and 1 other fieldsHigh correlation
마곡 is highly overall correlated with 목동 and 1 other fieldsHigh correlation
노원 is highly overall correlated with 목동 and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 07:34:59.045741
Analysis finished2023-12-12 07:35:01.226152
Duration2.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

실적일자
Date

Distinct61
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
Minimum2021-10-01 00:00:00
Maximum2021-11-30 00:00:00
2023-12-12T16:35:01.297907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:01.449144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시간
Real number (ℝ)

Distinct24
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-12T16:35:01.599133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16.75
median12.5
Q318.25
95-th percentile23
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation6.9245519
Coefficient of variation (CV)0.55396415
Kurtosis-1.2041871
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum18300
Variance47.949419
MonotonicityNot monotonic
2023-12-12T16:35:02.032368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 61
 
4.2%
14 61
 
4.2%
24 61
 
4.2%
23 61
 
4.2%
22 61
 
4.2%
21 61
 
4.2%
20 61
 
4.2%
19 61
 
4.2%
18 61
 
4.2%
17 61
 
4.2%
Other values (14) 854
58.3%
ValueCountFrequency (%)
1 61
4.2%
2 61
4.2%
3 61
4.2%
4 61
4.2%
5 61
4.2%
6 61
4.2%
7 61
4.2%
8 61
4.2%
9 61
4.2%
10 61
4.2%
ValueCountFrequency (%)
24 61
4.2%
23 61
4.2%
22 61
4.2%
21 61
4.2%
20 61
4.2%
19 61
4.2%
18 61
4.2%
17 61
4.2%
16 61
4.2%
15 61
4.2%

단위(열공급)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
Gcal
1464 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Gcal 1464
100.0%

Length

2023-12-12T16:35:02.164777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:35:02.254626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
gcal 1464
100.0%

목동
Real number (ℝ)

HIGH CORRELATION 

Distinct1388
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.230007
Minimum2.34
Maximum314.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-12T16:35:02.371738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.34
5-th percentile20.6475
Q138.3625
median63.035
Q391.8
95-th percentile156.8035
Maximum314.17
Range311.83
Interquartile range (IQR)53.4375

Descriptive statistics

Standard deviation42.140086
Coefficient of variation (CV)0.59160581
Kurtosis1.6790993
Mean71.230007
Median Absolute Deviation (MAD)26.315
Skewness1.1513501
Sum104280.73
Variance1775.7868
MonotonicityNot monotonic
2023-12-12T16:35:02.538063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
62.96 3
 
0.2%
43.47 3
 
0.2%
57.14 2
 
0.1%
47.29 2
 
0.1%
32.56 2
 
0.1%
54.94 2
 
0.1%
69.17 2
 
0.1%
83.94 2
 
0.1%
76.18 2
 
0.1%
59.86 2
 
0.1%
Other values (1378) 1442
98.5%
ValueCountFrequency (%)
2.34 1
0.1%
3.18 1
0.1%
9.5 1
0.1%
9.81 1
0.1%
10.82 1
0.1%
11.11 1
0.1%
11.18 1
0.1%
11.93 1
0.1%
12.03 1
0.1%
12.45 1
0.1%
ValueCountFrequency (%)
314.17 1
0.1%
267.34 1
0.1%
252.93 1
0.1%
245.76 1
0.1%
220.1 1
0.1%
215.05 1
0.1%
211.22 1
0.1%
209.09 1
0.1%
204.41 1
0.1%
204.11 1
0.1%

마곡
Real number (ℝ)

HIGH CORRELATION 

Distinct1347
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.339337
Minimum19.96
Maximum156.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-12T16:35:02.691424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19.96
5-th percentile29.5645
Q145.76
median59.45
Q381.78
95-th percentile121.668
Maximum156.71
Range136.75
Interquartile range (IQR)36.02

Descriptive statistics

Standard deviation27.718828
Coefficient of variation (CV)0.41783396
Kurtosis0.16059123
Mean66.339337
Median Absolute Deviation (MAD)15.815
Skewness0.86731276
Sum97120.79
Variance768.33343
MonotonicityNot monotonic
2023-12-12T16:35:02.857102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57.62 4
 
0.3%
61.64 3
 
0.2%
45.66 3
 
0.2%
62.87 3
 
0.2%
42.52 3
 
0.2%
61.25 3
 
0.2%
40.89 3
 
0.2%
45.3 3
 
0.2%
76.48 2
 
0.1%
75.76 2
 
0.1%
Other values (1337) 1435
98.0%
ValueCountFrequency (%)
19.96 1
0.1%
20.18 1
0.1%
21.16 1
0.1%
21.74 1
0.1%
23.26 1
0.1%
23.54 1
0.1%
23.68 1
0.1%
23.81 1
0.1%
23.85 1
0.1%
24.12 1
0.1%
ValueCountFrequency (%)
156.71 1
0.1%
152.95 1
0.1%
152.66 1
0.1%
152.24 1
0.1%
150.91 1
0.1%
150.39 1
0.1%
149.88 1
0.1%
149.45 1
0.1%
147.66 1
0.1%
147.12 1
0.1%

노원
Real number (ℝ)

HIGH CORRELATION 

Distinct1373
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.165581
Minimum5.43
Maximum214.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-12T16:35:03.048959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.43
5-th percentile18.7035
Q137.3275
median67.35
Q397.7325
95-th percentile153.132
Maximum214.23
Range208.8
Interquartile range (IQR)60.405

Descriptive statistics

Standard deviation41.495662
Coefficient of variation (CV)0.57500628
Kurtosis0.032296245
Mean72.165581
Median Absolute Deviation (MAD)30.09
Skewness0.70824869
Sum105650.41
Variance1721.89
MonotonicityNot monotonic
2023-12-12T16:35:03.208040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55.0 3
 
0.2%
22.32 3
 
0.2%
60.25 2
 
0.1%
59.46 2
 
0.1%
88.32 2
 
0.1%
40.2 2
 
0.1%
59.35 2
 
0.1%
91.84 2
 
0.1%
76.95 2
 
0.1%
84.74 2
 
0.1%
Other values (1363) 1442
98.5%
ValueCountFrequency (%)
5.43 1
0.1%
7.5 1
0.1%
7.83 1
0.1%
7.92 1
0.1%
8.21 1
0.1%
8.35 1
0.1%
8.9 1
0.1%
8.97 1
0.1%
9.08 1
0.1%
9.6 1
0.1%
ValueCountFrequency (%)
214.23 1
0.1%
212.17 1
0.1%
207.71 1
0.1%
207.2 1
0.1%
195.41 1
0.1%
193.48 1
0.1%
193.44 1
0.1%
193.4 1
0.1%
191.96 1
0.1%
191.77 1
0.1%

Interactions

2023-12-12T16:35:00.633992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:59.326056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:59.740310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:00.188416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:00.731217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:59.421921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:59.843729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:00.280899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:00.850470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:59.524948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:59.963073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:00.385477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:00.941484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:59.628040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:00.104806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:00.514813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:35:03.328464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실적일자시간목동마곡노원
실적일자1.0000.0000.7290.8130.800
시간0.0001.0000.3850.4650.528
목동0.7290.3851.0000.8090.861
마곡0.8130.4650.8091.0000.891
노원0.8000.5280.8610.8911.000
2023-12-12T16:35:03.446922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간목동마곡노원
시간1.0000.1230.1530.152
목동0.1231.0000.8090.883
마곡0.1530.8091.0000.887
노원0.1520.8830.8871.000

Missing values

2023-12-12T16:35:01.044756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:35:01.183713image/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

실적일자시간단위(열공급)목동마곡노원
02021-10-011Gcal14.6628.1924.38
12021-10-012Gcal13.4424.8720.68
22021-10-013Gcal14.4623.6818.38
32021-10-014Gcal16.3324.6916.38
42021-10-015Gcal17.8620.1816.79
52021-10-016Gcal21.7126.8923.52
62021-10-017Gcal24.9633.4331.87
72021-10-018Gcal34.3241.8437.91
82021-10-019Gcal32.2648.7230.76
92021-10-0110Gcal27.3855.929.01
실적일자시간단위(열공급)목동마곡노원
14542021-11-3015Gcal85.89105.54102.64
14552021-11-3016Gcal130.8109.86103.89
14562021-11-3017Gcal112.9117.36126.34
14572021-11-3018Gcal100.11127.26147.32
14582021-11-3019Gcal119.7135.87174.74
14592021-11-3020Gcal200.4140.84193.44
14602021-11-3021Gcal140.53147.12207.2
14612021-11-3022Gcal267.34152.24214.23
14622021-11-3023Gcal156.14146.56212.17
14632021-11-3024Gcal191.55141.66193.48