Overview

Dataset statistics

Number of variables5
Number of observations72
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory45.8 B

Variable types

DateTime1
Numeric2
Categorical2

Dataset

Description탄소거래제관련 지역난방공사 화석연료 사용시설에서 발생되는 온실가스 배출량 정보를 제공합니다. 현재 API를 이용하여 실시간 데이터를 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15082994/fileData.do

Alerts

기타배출량(tCO2e) has constant value ""Constant
공정배출량(tCO2e) has constant value ""Constant
기준일 has unique valuesUnique
고정배출량(tCO2e) has unique valuesUnique
간접배출량(tCO2e) has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:20:41.919553
Analysis finished2023-12-12 04:20:43.049555
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일
Date

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
Minimum2011-01-01 00:00:00
Maximum2016-12-01 00:00:00
2023-12-12T13:20:43.153071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:43.345795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

고정배출량(tCO2e)
Real number (ℝ)

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean362092.14
Minimum131614.44
Maximum711089.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-12T13:20:43.545697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum131614.44
5-th percentile152250.5
Q1196402.85
median322870.14
Q3523821.2
95-th percentile661409.13
Maximum711089.45
Range579475.01
Interquartile range (IQR)327418.35

Descriptive statistics

Standard deviation180721.25
Coefficient of variation (CV)0.49910293
Kurtosis-1.2420277
Mean362092.14
Median Absolute Deviation (MAD)143644.76
Skewness0.4301031
Sum26070634
Variance3.2660169 × 1010
MonotonicityNot monotonic
2023-12-12T13:20:43.712863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
547864.44 1
 
1.4%
499830.11 1
 
1.4%
198522.22 1
 
1.4%
226366.32 1
 
1.4%
175157.67 1
 
1.4%
309610.58 1
 
1.4%
496360.69 1
 
1.4%
711089.45 1
 
1.4%
708938.14 1
 
1.4%
583849.82 1
 
1.4%
Other values (62) 62
86.1%
ValueCountFrequency (%)
131614.44 1
1.4%
134437.5 1
1.4%
139249.42 1
1.4%
151425.01 1
1.4%
152925.9 1
1.4%
153834.34 1
1.4%
154396.66 1
1.4%
160213.97 1
1.4%
165265.84 1
1.4%
171359.31 1
1.4%
ValueCountFrequency (%)
711089.45 1
1.4%
708938.14 1
1.4%
686155.34 1
1.4%
662997.54 1
1.4%
660109.52 1
1.4%
656991.05 1
1.4%
643297.48 1
1.4%
616549.24 1
1.4%
613868.22 1
1.4%
613774.13 1
1.4%

간접배출량(tCO2e)
Real number (ℝ)

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8778.0735
Minimum135.578
Maximum13102.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-12T13:20:43.927376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum135.578
5-th percentile6416.5855
Q17411.0475
median8692.517
Q310130.37
95-th percentile11831.387
Maximum13102.19
Range12966.612
Interquartile range (IQR)2719.3225

Descriptive statistics

Standard deviation1934.4373
Coefficient of variation (CV)0.22037151
Kurtosis4.442093
Mean8778.0735
Median Absolute Deviation (MAD)1349.3785
Skewness-0.94515716
Sum632021.29
Variance3742047.6
MonotonicityNot monotonic
2023-12-12T13:20:44.154919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10093.15 1
 
1.4%
8153.47 1
 
1.4%
9358.39 1
 
1.4%
9203.21 1
 
1.4%
7298.69 1
 
1.4%
6529.18 1
 
1.4%
8692.55 1
 
1.4%
10390.99 1
 
1.4%
11021.73 1
 
1.4%
9276.88 1
 
1.4%
Other values (62) 62
86.1%
ValueCountFrequency (%)
135.578 1
1.4%
5838.58 1
1.4%
6123.79 1
1.4%
6278.97 1
1.4%
6529.18 1
1.4%
6547.67 1
1.4%
6679.193 1
1.4%
6715.55 1
1.4%
6722.35 1
1.4%
6984.7 1
1.4%
ValueCountFrequency (%)
13102.19 1
1.4%
12292.313 1
1.4%
12055.15 1
1.4%
11955.1 1
1.4%
11730.168 1
1.4%
11407.23 1
1.4%
11356.09 1
1.4%
11021.73 1
1.4%
10743.06 1
1.4%
10706.424 1
1.4%

기타배출량(tCO2e)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
0
72 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 72
100.0%

Length

2023-12-12T13:20:44.381761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:20:44.513846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 72
100.0%

공정배출량(tCO2e)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
0
72 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 72
100.0%

Length

2023-12-12T13:20:44.635911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:20:44.781383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 72
100.0%

Interactions

2023-12-12T13:20:42.222098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:42.012715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:42.344532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:42.112694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:20:44.865321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일고정배출량(tCO2e)간접배출량(tCO2e)
기준일1.0001.0001.000
고정배출량(tCO2e)1.0001.0000.516
간접배출량(tCO2e)1.0000.5161.000
2023-12-12T13:20:44.988544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고정배출량(tCO2e)간접배출량(tCO2e)
고정배출량(tCO2e)1.0000.364
간접배출량(tCO2e)0.3641.000

Missing values

2023-12-12T13:20:42.851661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:20:42.989640image/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

기준일고정배출량(tCO2e)간접배출량(tCO2e)기타배출량(tCO2e)공정배출량(tCO2e)
02016-12-01547864.4410093.1500
12016-11-01408620.258331.4100
22016-10-01213502.178209.4700
32016-09-01165265.849053.4100
42016-08-01189156.9111955.100
52016-07-01176695.4611407.2300
62016-06-01134437.59929.1900
72016-05-01152925.98111.4600
82016-04-01329653.476123.7900
92016-03-01448662.098305.7600
기준일고정배출량(tCO2e)간접배출량(tCO2e)기타배출량(tCO2e)공정배출량(tCO2e)
622011-10-01333068.196722.3500
632011-09-01131614.447374.6500
642011-08-01188951.178467.6300
652011-07-01199365.718885.0500
662011-06-01215177.147551.7400
672011-05-01217975.537572.200
682011-04-01337115.218099.6400
692011-03-01511424.839585.8800
702011-02-01534161.519095.2900
712011-01-01686155.3412055.1500