Overview

Dataset statistics

Number of variables14
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory126.0 B

Variable types

Numeric5
Categorical9

Dataset

Description한국지역난방공사 기후환경시스템의 TIER3 BIO 발열량(온실가스) 자료입니다. 기준연월별 바이오사용량, 메탄포함량, 바이오메탄량, 메탄용량 등의 정보를 제공합니다.
Author한국지역난방공사
URLhttps://www.data.go.kr/data/15124180/fileData.do

Alerts

사업장순번 has constant value ""Constant
메탄용량 has constant value ""Constant
계산식내용3 is highly overall correlated with 배출시설순번 and 3 other fieldsHigh correlation
계산식내용1 is highly overall correlated with 배출시설순번 and 3 other fieldsHigh correlation
계산식내용2 is highly overall correlated with 배출시설순번 and 3 other fieldsHigh correlation
배출시설순번 is highly overall correlated with 계산식내용1 and 3 other fieldsHigh correlation
계산식내용4 is highly overall correlated with 배출시설순번 and 3 other fieldsHigh correlation
기준연월 is highly overall correlated with 메탄포함량 and 3 other fieldsHigh correlation
바이오사용량 is highly overall correlated with 바이오메탄량 and 1 other fieldsHigh correlation
메탄포함량 is highly overall correlated with 기준연월 and 3 other fieldsHigh correlation
바이오메탄량 is highly overall correlated with 기준연월 and 3 other fieldsHigh correlation
순발열량1 is highly overall correlated with 기준연월 and 3 other fieldsHigh correlation
순발열량2 is highly overall correlated with 기준연월 and 5 other fieldsHigh correlation
총발열량 is highly overall correlated with 메탄포함량 and 3 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 22:22:50.260465
Analysis finished2023-12-12 22:22:53.655387
Duration3.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준연월
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201306.67
Minimum201301
Maximum201312
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T07:22:53.706656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201301
5-th percentile201302
Q1201304
median201307
Q3201309
95-th percentile201311.4
Maximum201312
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.2467933
Coefficient of variation (CV)1.6128593 × 10-5
Kurtosis-1.1602659
Mean201306.67
Median Absolute Deviation (MAD)3
Skewness-0.0023758473
Sum6643120
Variance10.541667
MonotonicityNot monotonic
2023-12-13T07:22:53.805456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
201302 3
9.1%
201303 3
9.1%
201304 3
9.1%
201305 3
9.1%
201306 3
9.1%
201307 3
9.1%
201308 3
9.1%
201309 3
9.1%
201310 3
9.1%
201311 3
9.1%
Other values (2) 3
9.1%
ValueCountFrequency (%)
201301 1
 
3.0%
201302 3
9.1%
201303 3
9.1%
201304 3
9.1%
201305 3
9.1%
201306 3
9.1%
201307 3
9.1%
201308 3
9.1%
201309 3
9.1%
201310 3
9.1%
ValueCountFrequency (%)
201312 2
6.1%
201311 3
9.1%
201310 3
9.1%
201309 3
9.1%
201308 3
9.1%
201307 3
9.1%
201306 3
9.1%
201305 3
9.1%
201304 3
9.1%
201303 3
9.1%

사업장순번
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
14
33 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row14
2nd row14
3rd row14
4th row14
5th row14

Common Values

ValueCountFrequency (%)
14 33
100.0%

Length

2023-12-13T07:22:53.921834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:22:54.002501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
14 33
100.0%

배출시설순번
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
35
11 
36
11 
9
11 

Length

Max length2
Median length2
Mean length1.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row35
2nd row35
3rd row35
4th row35
5th row35

Common Values

ValueCountFrequency (%)
35 11
33.3%
36 11
33.3%
9 11
33.3%

Length

2023-12-13T07:22:54.084794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:22:54.199595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
35 11
33.3%
36 11
33.3%
9 11
33.3%

바이오사용량
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean361208.27
Minimum111410
Maximum428461
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T07:22:54.300355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum111410
5-th percentile159251.6
Q1345770
median401191
Q3420102
95-th percentile425552.6
Maximum428461
Range317051
Interquartile range (IQR)74332

Descriptive statistics

Standard deviation92728.436
Coefficient of variation (CV)0.25671737
Kurtosis1.9913085
Mean361208.27
Median Absolute Deviation (MAD)21622
Skewness-1.7646409
Sum11919873
Variance8.5985629 × 109
MonotonicityNot monotonic
2023-12-13T07:22:54.395002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
111410 2
 
6.1%
191146 2
 
6.1%
309296 2
 
6.1%
384212 2
 
6.1%
345770 2
 
6.1%
423077 2
 
6.1%
407714 2
 
6.1%
422813 2
 
6.1%
393360 2
 
6.1%
401191 2
 
6.1%
Other values (12) 13
39.4%
ValueCountFrequency (%)
111410 2
6.1%
191146 2
6.1%
197840 1
3.0%
309296 2
6.1%
345770 2
6.1%
379599 2
6.1%
384212 2
6.1%
393360 2
6.1%
396997 1
3.0%
401191 2
6.1%
ValueCountFrequency (%)
428461 1
3.0%
426260 1
3.0%
425081 1
3.0%
424997 1
3.0%
423077 2
6.1%
422813 2
6.1%
420102 1
3.0%
418624 1
3.0%
418097 1
3.0%
415074 1
3.0%

메탄포함량
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.818182
Minimum59
Maximum64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T07:22:54.488114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum59
5-th percentile59
Q161
median62
Q363
95-th percentile64
Maximum64
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4242223
Coefficient of variation (CV)0.02303889
Kurtosis-0.46028218
Mean61.818182
Median Absolute Deviation (MAD)1
Skewness-0.48820356
Sum2040
Variance2.0284091
MonotonicityNot monotonic
2023-12-13T07:22:54.579518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
62 9
27.3%
63 9
27.3%
61 6
18.2%
59 3
 
9.1%
60 3
 
9.1%
64 3
 
9.1%
ValueCountFrequency (%)
59 3
 
9.1%
60 3
 
9.1%
61 6
18.2%
62 9
27.3%
63 9
27.3%
64 3
 
9.1%
ValueCountFrequency (%)
64 3
 
9.1%
63 9
27.3%
62 9
27.3%
61 6
18.2%
60 3
 
9.1%
59 3
 
9.1%

바이오메탄량
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean223972.64
Minimum65698
Maximum270862
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T07:22:54.697382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65698
5-th percentile96278.8
Q1216798
median250303
Q3259177
95-th percentile266986.6
Maximum270862
Range205164
Interquartile range (IQR)42379

Descriptive statistics

Standard deviation58640.911
Coefficient of variation (CV)0.26182176
Kurtosis2.0646771
Mean223972.64
Median Absolute Deviation (MAD)10874
Skewness-1.7818098
Sum7391097
Variance3.4387564 × 109
MonotonicityNot monotonic
2023-12-13T07:22:54.820919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
65698 2
 
6.1%
116905 2
 
6.1%
197083 2
 
6.1%
239902 2
 
6.1%
216798 2
 
6.1%
259177 2
 
6.1%
253476 2
 
6.1%
266119 2
 
6.1%
247069 2
 
6.1%
250303 2
 
6.1%
Other values (12) 13
39.4%
ValueCountFrequency (%)
65698 2
6.1%
116666 1
3.0%
116905 2
6.1%
197083 2
6.1%
216798 2
6.1%
225861 2
6.1%
239902 2
6.1%
247069 2
6.1%
247885 1
3.0%
250303 2
6.1%
ValueCountFrequency (%)
270862 1
3.0%
268288 1
3.0%
266119 2
6.1%
262938 1
3.0%
261177 1
3.0%
259928 1
3.0%
259177 2
6.1%
258965 1
3.0%
256546 1
3.0%
256126 1
3.0%

메탄용량
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
8640
33 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row8640
2nd row8640
3rd row8640
4th row8640
5th row8640

Common Values

ValueCountFrequency (%)
8640 33
100.0%

Length

2023-12-13T07:22:54.931172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:22:55.033931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8640 33
100.0%

순발열량1
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5341.4545
Minimum5095
Maximum5505
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-13T07:22:55.113930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5095
5-th percentile5095
Q15284
median5390
Q35427
95-th percentile5505
Maximum5505
Range410
Interquartile range (IQR)143

Descriptive statistics

Standard deviation123.14653
Coefficient of variation (CV)0.023054868
Kurtosis-0.24258739
Mean5341.4545
Median Absolute Deviation (MAD)48
Skewness-0.89256441
Sum176268
Variance15165.068
MonotonicityNot monotonic
2023-12-13T07:22:55.226305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
5095 3
9.1%
5141 3
9.1%
5284 3
9.1%
5505 3
9.1%
5395 3
9.1%
5417 3
9.1%
5293 3
9.1%
5371 3
9.1%
5438 3
9.1%
5427 3
9.1%
ValueCountFrequency (%)
5095 3
9.1%
5141 3
9.1%
5284 3
9.1%
5293 3
9.1%
5371 3
9.1%
5390 3
9.1%
5395 3
9.1%
5417 3
9.1%
5427 3
9.1%
5438 3
9.1%
ValueCountFrequency (%)
5505 3
9.1%
5438 3
9.1%
5427 3
9.1%
5417 3
9.1%
5395 3
9.1%
5390 3
9.1%
5371 3
9.1%
5293 3
9.1%
5284 3
9.1%
5141 3
9.1%

순발열량2
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
23
18 
22
12 
21
3 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row21
2nd row22
3rd row22
4th row23
5th row23

Common Values

ValueCountFrequency (%)
23 18
54.5%
22 12
36.4%
21 3
 
9.1%

Length

2023-12-13T07:22:55.337594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:22:55.466988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
23 18
54.5%
22 12
36.4%
21 3
 
9.1%

총발열량
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
25
21 
24
11 
23
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)3.0%

Sample

1st row24
2nd row24
3rd row24
4th row25
5th row25

Common Values

ValueCountFrequency (%)
25 21
63.6%
24 11
33.3%
23 1
 
3.0%

Length

2023-12-13T07:22:55.584324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:22:55.696966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
25 21
63.6%
24 11
33.3%
23 1
 
3.0%

계산식내용1
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
BIO_USE*CH4_CON/100
22 
BIO_USE*(CH4_CON/100)
11 

Length

Max length21
Median length19
Mean length19.666667
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBIO_USE*CH4_CON/100
2nd rowBIO_USE*CH4_CON/100
3rd rowBIO_USE*CH4_CON/100
4th rowBIO_USE*CH4_CON/100
5th rowBIO_USE*CH4_CON/100

Common Values

ValueCountFrequency (%)
BIO_USE*CH4_CON/100 22
66.7%
BIO_USE*(CH4_CON/100) 11
33.3%

Length

2023-12-13T07:22:55.806165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:22:55.929221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bio_use*ch4_con/100 22
66.7%
bio_use*(ch4_con/100 11
33.3%

계산식내용2
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
CH4_CON*CH4/100
22 
CH4*(CH4_CON/100)
11 

Length

Max length18
Median length15
Mean length16
Min length15

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCH4_CON*CH4/100
2nd rowCH4_CON*CH4/100
3rd rowCH4_CON*CH4/100
4th rowCH4_CON*CH4/100
5th rowCH4_CON*CH4/100

Common Values

ValueCountFrequency (%)
CH4_CON*CH4/100 22
66.7%
CH4*(CH4_CON/100) 11
33.3%

Length

2023-12-13T07:22:56.044981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:22:56.160325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ch4_con*ch4/100 22
66.7%
ch4*(ch4_con/100 11
33.3%

계산식내용3
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
LOW_CAL1*4.1868/1000
22 
LOW_CAL1*4.1868*0.001
11 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLOW_CAL1*4.1868/1000
2nd rowLOW_CAL1*4.1868/1000
3rd rowLOW_CAL1*4.1868/1000
4th rowLOW_CAL1*4.1868/1000
5th rowLOW_CAL1*4.1868/1000

Common Values

ValueCountFrequency (%)
LOW_CAL1*4.1868/1000 22
66.7%
LOW_CAL1*4.1868*0.001 11
33.3%

Length

2023-12-13T07:22:56.258601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:22:56.375358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
low_cal1*4.1868/1000 22
66.7%
low_cal1*4.1868*0.001 11
33.3%

계산식내용4
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
(9523*CH4_CON*0.01)*4.1868*0.001
22 
(9500*CH4_CON*0.01)*4.1868*0.001
11 

Length

Max length33
Median length32
Mean length32.333333
Min length32

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row(9523*CH4_CON*0.01)*4.1868*0.001
2nd row(9523*CH4_CON*0.01)*4.1868*0.001
3rd row(9523*CH4_CON*0.01)*4.1868*0.001
4th row(9523*CH4_CON*0.01)*4.1868*0.001
5th row(9523*CH4_CON*0.01)*4.1868*0.001

Common Values

ValueCountFrequency (%)
(9523*CH4_CON*0.01)*4.1868*0.001 22
66.7%
(9500*CH4_CON*0.01)*4.1868*0.001 11
33.3%

Length

2023-12-13T07:22:56.502997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:22:56.614480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9523*ch4_con*0.01)*4.1868*0.001 22
66.7%
9500*ch4_con*0.01)*4.1868*0.001 11
33.3%

Interactions

2023-12-13T07:22:52.988700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:50.945174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:51.690751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:52.151231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:52.579287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:53.071201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:51.039846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:51.787462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:52.251906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:52.652916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:53.169086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:51.443266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:51.876272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:52.350256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:52.745459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:53.246792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:51.531223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:51.962283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:52.435947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:52.829205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:53.315341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:51.610511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:52.050011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:52.506303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:22:52.905707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:22:56.697223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준연월배출시설순번바이오사용량메탄포함량바이오메탄량순발열량1순발열량2총발열량계산식내용1계산식내용2계산식내용3계산식내용4
기준연월1.0000.0000.0000.7830.5330.8230.8280.9340.0000.0000.0000.000
배출시설순번0.0001.0000.1480.0000.1420.0000.0000.0001.0001.0001.0001.000
바이오사용량0.0000.1481.0000.6320.9870.5690.4230.3300.0000.0000.0000.000
메탄포함량0.7830.0000.6321.0000.6850.9480.9950.9600.0000.0000.0000.000
바이오메탄량0.5330.1420.9870.6851.0000.6590.5190.4230.0000.0000.0000.000
순발열량10.8230.0000.5690.9480.6591.0001.0001.0000.0000.0000.0000.000
순발열량20.8280.0000.4230.9950.5191.0001.0000.9260.0000.0000.0000.000
총발열량0.9340.0000.3300.9600.4231.0000.9261.0000.0460.0460.0460.046
계산식내용10.0001.0000.0000.0000.0000.0000.0000.0461.0000.9940.9940.994
계산식내용20.0001.0000.0000.0000.0000.0000.0000.0460.9941.0000.9940.994
계산식내용30.0001.0000.0000.0000.0000.0000.0000.0460.9940.9941.0000.994
계산식내용40.0001.0000.0000.0000.0000.0000.0000.0460.9940.9940.9941.000
2023-12-13T07:22:56.829616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계산식내용3계산식내용1계산식내용2총발열량배출시설순번순발열량2계산식내용4
계산식내용31.0000.9300.9300.0610.9840.0000.930
계산식내용10.9301.0000.9300.0610.9840.0000.930
계산식내용20.9300.9301.0000.0610.9840.0000.930
총발열량0.0610.0610.0611.0000.0000.6680.061
배출시설순번0.9840.9840.9840.0001.0000.0000.984
순발열량20.0000.0000.0000.6680.0001.0000.000
계산식내용40.9300.9300.9300.0610.9840.0001.000
2023-12-13T07:22:56.941150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준연월바이오사용량메탄포함량바이오메탄량순발열량1배출시설순번순발열량2총발열량계산식내용1계산식내용2계산식내용3계산식내용4
기준연월1.0000.4990.5240.6070.5310.0000.6720.4270.0000.0000.0000.000
바이오사용량0.4991.0000.2050.9570.2470.0000.5690.4940.0000.0000.0000.000
메탄포함량0.5240.2051.0000.3420.9790.0000.8670.7160.0000.0000.0000.000
바이오메탄량0.6070.9570.3421.0000.3810.0000.6330.5380.0000.0000.0000.000
순발열량10.5310.2470.9790.3811.0000.0000.9310.6920.0000.0000.0000.000
배출시설순번0.0000.0000.0000.0000.0001.0000.0000.0000.9840.9840.9840.984
순발열량20.6720.5690.8670.6330.9310.0001.0000.6680.0000.0000.0000.000
총발열량0.4270.4940.7160.5380.6920.0000.6681.0000.0610.0610.0610.061
계산식내용10.0000.0000.0000.0000.0000.9840.0000.0611.0000.9300.9300.930
계산식내용20.0000.0000.0000.0000.0000.9840.0000.0610.9301.0000.9300.930
계산식내용30.0000.0000.0000.0000.0000.9840.0000.0610.9300.9301.0000.930
계산식내용40.0000.0000.0000.0000.0000.9840.0000.0610.9300.9300.9301.000

Missing values

2023-12-13T07:22:53.429992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:22:53.593777image/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

기준연월사업장순번배출시설순번바이오사용량메탄포함량바이오메탄량메탄용량순발열량1순발열량2총발열량계산식내용1계산식내용2계산식내용3계산식내용4
020130214351114105965698864050952124BIO_USE*CH4_CON/100CH4_CON*CH4/100LOW_CAL1*4.1868/1000(9523*CH4_CON*0.01)*4.1868*0.001
1201303143537959960225861864051412224BIO_USE*CH4_CON/100CH4_CON*CH4/100LOW_CAL1*4.1868/1000(9523*CH4_CON*0.01)*4.1868*0.001
2201304143519114661116905864052842224BIO_USE*CH4_CON/100CH4_CON*CH4/100LOW_CAL1*4.1868/1000(9523*CH4_CON*0.01)*4.1868*0.001
3201305143530929664197083864055052325BIO_USE*CH4_CON/100CH4_CON*CH4/100LOW_CAL1*4.1868/1000(9523*CH4_CON*0.01)*4.1868*0.001
4201306143538421262239902864053952325BIO_USE*CH4_CON/100CH4_CON*CH4/100LOW_CAL1*4.1868/1000(9523*CH4_CON*0.01)*4.1868*0.001
5201307143534577063216798864054172325BIO_USE*CH4_CON/100CH4_CON*CH4/100LOW_CAL1*4.1868/1000(9523*CH4_CON*0.01)*4.1868*0.001
6201308143542307761259177864052932224BIO_USE*CH4_CON/100CH4_CON*CH4/100LOW_CAL1*4.1868/1000(9523*CH4_CON*0.01)*4.1868*0.001
7201309143540771462253476864053712225BIO_USE*CH4_CON/100CH4_CON*CH4/100LOW_CAL1*4.1868/1000(9523*CH4_CON*0.01)*4.1868*0.001
8201310143542281363266119864054382325BIO_USE*CH4_CON/100CH4_CON*CH4/100LOW_CAL1*4.1868/1000(9523*CH4_CON*0.01)*4.1868*0.001
9201311143539336063247069864054272325BIO_USE*CH4_CON/100CH4_CON*CH4/100LOW_CAL1*4.1868/1000(9523*CH4_CON*0.01)*4.1868*0.001
기준연월사업장순번배출시설순번바이오사용량메탄포함량바이오메탄량메탄용량순발열량1순발열량2총발열량계산식내용1계산식내용2계산식내용3계산식내용4
2320130214937959960225861864051412224BIO_USE*(CH4_CON/100)CH4*(CH4_CON/100)LOW_CAL1*4.1868*0.001(9500*CH4_CON*0.01)*4.1868*0.001
2420130314919114661116905864052842224BIO_USE*(CH4_CON/100)CH4*(CH4_CON/100)LOW_CAL1*4.1868*0.001(9500*CH4_CON*0.01)*4.1868*0.001
2520130414930929664197083864055052325BIO_USE*(CH4_CON/100)CH4*(CH4_CON/100)LOW_CAL1*4.1868*0.001(9500*CH4_CON*0.01)*4.1868*0.001
2620130514938421262239902864053952325BIO_USE*(CH4_CON/100)CH4*(CH4_CON/100)LOW_CAL1*4.1868*0.001(9500*CH4_CON*0.01)*4.1868*0.001
2720130614934577063216798864054172325BIO_USE*(CH4_CON/100)CH4*(CH4_CON/100)LOW_CAL1*4.1868*0.001(9500*CH4_CON*0.01)*4.1868*0.001
2820130714942307761259177864052932224BIO_USE*(CH4_CON/100)CH4*(CH4_CON/100)LOW_CAL1*4.1868*0.001(9500*CH4_CON*0.01)*4.1868*0.001
2920130814940771462253476864053712225BIO_USE*(CH4_CON/100)CH4*(CH4_CON/100)LOW_CAL1*4.1868*0.001(9500*CH4_CON*0.01)*4.1868*0.001
3020130914942281363266119864054382325BIO_USE*(CH4_CON/100)CH4*(CH4_CON/100)LOW_CAL1*4.1868*0.001(9500*CH4_CON*0.01)*4.1868*0.001
3120131014939336063247069864054272325BIO_USE*(CH4_CON/100)CH4*(CH4_CON/100)LOW_CAL1*4.1868*0.001(9500*CH4_CON*0.01)*4.1868*0.001
3220131114940119162250303864053902325BIO_USE*(CH4_CON/100)CH4*(CH4_CON/100)LOW_CAL1*4.1868*0.001(9500*CH4_CON*0.01)*4.1868*0.001