Overview

Dataset statistics

Number of variables18
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory163.3 B

Variable types

Categorical3
Numeric14
DateTime1

Dataset

Description광주에서 발생한 폐기물의 부문별(가정생활폐기물/사업장생활계폐기물/사업장배출시설계폐기물/건설폐기물/지정폐기물/의료폐기물) 현황입니다.(2008년~2021년, 단위:톤/일)
Author광주광역시
URLhttps://www.data.go.kr/data/3083986/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
대분류 is highly overall correlated with 중분류High correlation
중분류 is highly overall correlated with 대분류High correlation
2008년 is highly overall correlated with 2009년 and 12 other fieldsHigh correlation
2009년 is highly overall correlated with 2008년 and 12 other fieldsHigh correlation
2010년 is highly overall correlated with 2008년 and 12 other fieldsHigh correlation
2011년 is highly overall correlated with 2008년 and 12 other fieldsHigh correlation
2012년 is highly overall correlated with 2008년 and 12 other fieldsHigh correlation
2013년 is highly overall correlated with 2008년 and 12 other fieldsHigh correlation
2014년 is highly overall correlated with 2008년 and 12 other fieldsHigh correlation
2015년 is highly overall correlated with 2008년 and 12 other fieldsHigh correlation
2016년 is highly overall correlated with 2008년 and 12 other fieldsHigh correlation
2017년 is highly overall correlated with 2008년 and 12 other fieldsHigh correlation
2018년 is highly overall correlated with 2008년 and 12 other fieldsHigh correlation
2019년 is highly overall correlated with 2008년 and 12 other fieldsHigh correlation
2020년 is highly overall correlated with 2008년 and 12 other fieldsHigh correlation
2021년 is highly overall correlated with 2008년 and 12 other fieldsHigh correlation
2008년 has 6 (24.0%) zerosZeros
2009년 has 6 (24.0%) zerosZeros
2010년 has 6 (24.0%) zerosZeros
2011년 has 6 (24.0%) zerosZeros
2012년 has 6 (24.0%) zerosZeros
2013년 has 6 (24.0%) zerosZeros
2014년 has 6 (24.0%) zerosZeros
2015년 has 7 (28.0%) zerosZeros
2016년 has 7 (28.0%) zerosZeros
2017년 has 8 (32.0%) zerosZeros
2018년 has 8 (32.0%) zerosZeros
2019년 has 5 (20.0%) zerosZeros
2020년 has 5 (20.0%) zerosZeros
2021년 has 5 (20.0%) zerosZeros

Reproduction

Analysis started2023-12-12 10:27:50.607728
Analysis finished2023-12-12 10:28:11.004703
Duration20.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대분류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
생활폐기물
사업장배출시설계폐기물
건설폐기물
지정폐기물
의료폐기물

Length

Max length11
Median length5
Mean length6.2
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생활폐기물 7
28.0%
사업장배출시설계폐기물 5
20.0%
건설폐기물 5
20.0%
지정폐기물 4
16.0%
의료폐기물 4
16.0%

Length

2023-12-12T19:28:11.096242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:28:11.226832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활폐기물 7
28.0%
사업장배출시설계폐기물 5
20.0%
건설폐기물 5
20.0%
지정폐기물 4
16.0%
의료폐기물 4
16.0%

중분류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
사업장배출시설계폐기물
건설폐기물
사업장생활계폐기물
지정폐기물
의료폐기물

Length

Max length11
Median length5
Mean length7.08
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가정생활폐기물
2nd row가정생활폐기물
3rd row가정생활폐기물
4th row사업장생활계폐기물
5th row사업장생활계폐기물

Common Values

ValueCountFrequency (%)
사업장배출시설계폐기물 5
20.0%
건설폐기물 5
20.0%
사업장생활계폐기물 4
16.0%
지정폐기물 4
16.0%
의료폐기물 4
16.0%
가정생활폐기물 3
12.0%

Length

2023-12-12T19:28:11.404613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:28:11.560267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사업장배출시설계폐기물 5
20.0%
건설폐기물 5
20.0%
사업장생활계폐기물 4
16.0%
지정폐기물 4
16.0%
의료폐기물 4
16.0%
가정생활폐기물 3
12.0%

소분류
Categorical

Distinct6
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
소각
재활용
매립
기타
해역배출

Length

Max length4
Median length2
Mean length2.48
Min length2

Unique

Unique1 ?
Unique (%)4.0%

Sample

1st row매립
2nd row소각
3rd row재활용
4th row매립
5th row소각

Common Values

ValueCountFrequency (%)
소각 6
24.0%
재활용 6
24.0%
매립 5
20.0%
기타 5
20.0%
해역배출 2
 
8.0%
멸균분쇄 1
 
4.0%

Length

2023-12-12T19:28:11.735922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:28:11.896096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소각 6
24.0%
재활용 6
24.0%
매립 5
20.0%
기타 5
20.0%
해역배출 2
 
8.0%
멸균분쇄 1
 
4.0%

2008년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean206.004
Minimum0
Maximum2870.3
Zeros6
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:12.017698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median21.9
Q395.3
95-th percentile726.68
Maximum2870.3
Range2870.3
Interquartile range (IQR)95.2

Descriptive statistics

Standard deviation583.76553
Coefficient of variation (CV)2.8337582
Kurtosis19.880146
Mean206.004
Median Absolute Deviation (MAD)21.9
Skewness4.3272114
Sum5150.1
Variance340782.2
MonotonicityNot monotonic
2023-12-12T19:28:12.148350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 6
24.0%
272.7 1
 
4.0%
54.5 1
 
4.0%
0.1 1
 
4.0%
7.8 1
 
4.0%
1.6 1
 
4.0%
37.4 1
 
4.0%
21.9 1
 
4.0%
3.3 1
 
4.0%
2870.3 1
 
4.0%
Other values (10) 10
40.0%
ValueCountFrequency (%)
0.0 6
24.0%
0.1 1
 
4.0%
1.6 1
 
4.0%
3.3 1
 
4.0%
7.8 1
 
4.0%
10.1 1
 
4.0%
21.8 1
 
4.0%
21.9 1
 
4.0%
27.6 1
 
4.0%
37.4 1
 
4.0%
ValueCountFrequency (%)
2870.3 1
4.0%
804.7 1
4.0%
414.6 1
4.0%
272.7 1
4.0%
246.1 1
4.0%
162.7 1
4.0%
95.3 1
4.0%
57.4 1
4.0%
54.5 1
4.0%
40.2 1
4.0%

2009년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184.52
Minimum0
Maximum2373.9
Zeros6
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:12.305135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median20.5
Q3107.2
95-th percentile714.64
Maximum2373.9
Range2373.9
Interquartile range (IQR)107.1

Descriptive statistics

Standard deviation489.00624
Coefficient of variation (CV)2.6501531
Kurtosis18.242693
Mean184.52
Median Absolute Deviation (MAD)20.5
Skewness4.1232614
Sum4613
Variance239127.11
MonotonicityNot monotonic
2023-12-12T19:28:12.440889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 6
24.0%
255.0 1
 
4.0%
10.9 1
 
4.0%
0.1 1
 
4.0%
9.5 1
 
4.0%
2.3 1
 
4.0%
54.4 1
 
4.0%
20.5 1
 
4.0%
7.4 1
 
4.0%
2373.9 1
 
4.0%
Other values (10) 10
40.0%
ValueCountFrequency (%)
0.0 6
24.0%
0.1 1
 
4.0%
2.3 1
 
4.0%
7.4 1
 
4.0%
9.5 1
 
4.0%
10.9 1
 
4.0%
17.0 1
 
4.0%
20.5 1
 
4.0%
20.8 1
 
4.0%
35.0 1
 
4.0%
ValueCountFrequency (%)
2373.9 1
4.0%
800.8 1
4.0%
370.0 1
4.0%
255.0 1
4.0%
247.2 1
4.0%
161.3 1
4.0%
107.2 1
4.0%
71.2 1
4.0%
54.4 1
4.0%
48.5 1
4.0%

2010년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean178.484
Minimum0
Maximum2206.7
Zeros6
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:12.580460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2
median17.9
Q3109.2
95-th percentile701.46
Maximum2206.7
Range2206.7
Interquartile range (IQR)109

Descriptive statistics

Standard deviation457.84126
Coefficient of variation (CV)2.565167
Kurtosis17.37034
Mean178.484
Median Absolute Deviation (MAD)17.9
Skewness4.0033078
Sum4462.1
Variance209618.62
MonotonicityNot monotonic
2023-12-12T19:28:12.721590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 6
24.0%
235.2 1
 
4.0%
1.2 1
 
4.0%
0.2 1
 
4.0%
10.2 1
 
4.0%
0.7 1
 
4.0%
40.3 1
 
4.0%
24.0 1
 
4.0%
5.8 1
 
4.0%
2206.7 1
 
4.0%
Other values (10) 10
40.0%
ValueCountFrequency (%)
0.0 6
24.0%
0.2 1
 
4.0%
0.7 1
 
4.0%
1.2 1
 
4.0%
5.8 1
 
4.0%
7.2 1
 
4.0%
10.2 1
 
4.0%
17.9 1
 
4.0%
24.0 1
 
4.0%
31.4 1
 
4.0%
ValueCountFrequency (%)
2206.7 1
4.0%
771.3 1
4.0%
422.1 1
4.0%
235.2 1
4.0%
231.9 1
4.0%
230.5 1
4.0%
109.2 1
4.0%
63.2 1
4.0%
53.1 1
4.0%
40.3 1
4.0%

2011년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean221.72
Minimum0
Maximum3304.6
Zeros6
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:12.850679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2
median18.8
Q3128.7
95-th percentile683.52
Maximum3304.6
Range3304.6
Interquartile range (IQR)128.5

Descriptive statistics

Standard deviation664.8165
Coefficient of variation (CV)2.9984508
Kurtosis21.365378
Mean221.72
Median Absolute Deviation (MAD)18.8
Skewness4.5145288
Sum5543
Variance441980.98
MonotonicityNot monotonic
2023-12-12T19:28:12.991013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 6
24.0%
206.2 1
 
4.0%
1.2 1
 
4.0%
0.2 1
 
4.0%
11.7 1
 
4.0%
2.9 1
 
4.0%
63.6 1
 
4.0%
24.4 1
 
4.0%
3.8 1
 
4.0%
3304.6 1
 
4.0%
Other values (10) 10
40.0%
ValueCountFrequency (%)
0.0 6
24.0%
0.2 1
 
4.0%
1.2 1
 
4.0%
2.9 1
 
4.0%
3.8 1
 
4.0%
4.3 1
 
4.0%
11.7 1
 
4.0%
18.8 1
 
4.0%
24.4 1
 
4.0%
32.1 1
 
4.0%
ValueCountFrequency (%)
3304.6 1
4.0%
745.1 1
4.0%
437.2 1
4.0%
236.8 1
4.0%
206.2 1
4.0%
203.0 1
4.0%
128.7 1
4.0%
70.6 1
4.0%
63.6 1
4.0%
47.8 1
4.0%

2012년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean226.024
Minimum0
Maximum3464.6
Zeros6
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:13.142836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2
median12.9
Q3100.3
95-th percentile679.22
Maximum3464.6
Range3464.6
Interquartile range (IQR)100.1

Descriptive statistics

Standard deviation696.86523
Coefficient of variation (CV)3.0831471
Kurtosis21.576605
Mean226.024
Median Absolute Deviation (MAD)12.9
Skewness4.5408101
Sum5650.6
Variance485621.15
MonotonicityNot monotonic
2023-12-12T19:28:13.308598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 6
24.0%
29.6 2
 
8.0%
208.9 1
 
4.0%
3.5 1
 
4.0%
0.2 1
 
4.0%
12.9 1
 
4.0%
0.7 1
 
4.0%
51.6 1
 
4.0%
7.8 1
 
4.0%
3464.6 1
 
4.0%
Other values (9) 9
36.0%
ValueCountFrequency (%)
0.0 6
24.0%
0.2 1
 
4.0%
0.7 1
 
4.0%
3.5 1
 
4.0%
5.3 1
 
4.0%
5.4 1
 
4.0%
7.8 1
 
4.0%
12.9 1
 
4.0%
29.6 2
 
8.0%
29.8 1
 
4.0%
ValueCountFrequency (%)
3464.6 1
4.0%
726.5 1
4.0%
490.1 1
4.0%
233.7 1
4.0%
212.9 1
4.0%
208.9 1
4.0%
100.3 1
4.0%
51.6 1
4.0%
37.2 1
4.0%
29.8 1
4.0%

2013년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean228.964
Minimum0
Maximum3491.7
Zeros6
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:13.442925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2
median22.6
Q373.6
95-th percentile702.3
Maximum3491.7
Range3491.7
Interquartile range (IQR)73.4

Descriptive statistics

Standard deviation702.84808
Coefficient of variation (CV)3.0696881
Kurtosis21.467593
Mean228.964
Median Absolute Deviation (MAD)22.6
Skewness4.5278503
Sum5724.1
Variance493995.42
MonotonicityNot monotonic
2023-12-12T19:28:13.567428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 6
24.0%
201.1 1
 
4.0%
16.6 1
 
4.0%
0.2 1
 
4.0%
13.9 1
 
4.0%
1.6 1
 
4.0%
58.4 1
 
4.0%
23.5 1
 
4.0%
12.6 1
 
4.0%
3491.7 1
 
4.0%
Other values (10) 10
40.0%
ValueCountFrequency (%)
0.0 6
24.0%
0.2 1
 
4.0%
1.6 1
 
4.0%
6.0 1
 
4.0%
12.6 1
 
4.0%
13.9 1
 
4.0%
16.6 1
 
4.0%
22.6 1
 
4.0%
23.5 1
 
4.0%
28.8 1
 
4.0%
ValueCountFrequency (%)
3491.7 1
4.0%
752.0 1
4.0%
503.5 1
4.0%
242.5 1
4.0%
205.9 1
4.0%
201.1 1
4.0%
73.6 1
4.0%
58.4 1
4.0%
40.6 1
4.0%
29.0 1
4.0%

2014년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean218.584
Minimum0
Maximum3290
Zeros6
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:13.694877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median15.8
Q3108.1
95-th percentile685.06
Maximum3290
Range3290
Interquartile range (IQR)108

Descriptive statistics

Standard deviation663.22032
Coefficient of variation (CV)3.0341668
Kurtosis21.23455
Mean218.584
Median Absolute Deviation (MAD)15.8
Skewness4.4974854
Sum5464.6
Variance439861.2
MonotonicityNot monotonic
2023-12-12T19:28:13.793284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 6
24.0%
173.0 1
 
4.0%
1.9 1
 
4.0%
0.1 1
 
4.0%
15.8 1
 
4.0%
1.3 1
 
4.0%
58.3 1
 
4.0%
22.4 1
 
4.0%
11.8 1
 
4.0%
3290.0 1
 
4.0%
Other values (10) 10
40.0%
ValueCountFrequency (%)
0.0 6
24.0%
0.1 1
 
4.0%
1.3 1
 
4.0%
1.9 1
 
4.0%
3.4 1
 
4.0%
8.0 1
 
4.0%
11.8 1
 
4.0%
15.8 1
 
4.0%
22.4 1
 
4.0%
29.7 1
 
4.0%
ValueCountFrequency (%)
3290.0 1
4.0%
733.5 1
4.0%
491.3 1
4.0%
240.9 1
4.0%
199.5 1
4.0%
173.0 1
4.0%
108.1 1
4.0%
58.3 1
4.0%
44.4 1
4.0%
31.2 1
4.0%

2015년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean210.5028
Minimum0
Maximum3214.1
Zeros7
Zeros (%)28.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:13.895643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median17.27
Q382.5
95-th percentile657.42
Maximum3214.1
Range3214.1
Interquartile range (IQR)82.5

Descriptive statistics

Standard deviation647.51901
Coefficient of variation (CV)3.0760589
Kurtosis21.393673
Mean210.5028
Median Absolute Deviation (MAD)17.27
Skewness4.5192528
Sum5262.57
Variance419280.86
MonotonicityNot monotonic
2023-12-12T19:28:13.999265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 7
28.0%
183.7 1
 
4.0%
12.2 1
 
4.0%
0.2 1
 
4.0%
17.27 1
 
4.0%
1.6 1
 
4.0%
53.9 1
 
4.0%
21.3 1
 
4.0%
15.2 1
 
4.0%
3214.1 1
 
4.0%
Other values (9) 9
36.0%
ValueCountFrequency (%)
0.0 7
28.0%
0.2 1
 
4.0%
0.9 1
 
4.0%
1.6 1
 
4.0%
12.2 1
 
4.0%
15.2 1
 
4.0%
17.27 1
 
4.0%
21.3 1
 
4.0%
31.8 1
 
4.0%
32.1 1
 
4.0%
ValueCountFrequency (%)
3214.1 1
4.0%
704.8 1
4.0%
467.9 1
4.0%
238.0 1
4.0%
183.7 1
4.0%
137.3 1
4.0%
82.5 1
4.0%
53.9 1
4.0%
47.8 1
4.0%
32.1 1
4.0%

2016년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean248.768
Minimum0
Maximum3915.3
Zeros7
Zeros (%)28.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:14.101897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median18.5
Q387.9
95-th percentile695.36
Maximum3915.3
Range3915.3
Interquartile range (IQR)87.9

Descriptive statistics

Standard deviation786.48397
Coefficient of variation (CV)3.1615158
Kurtosis21.884873
Mean248.768
Median Absolute Deviation (MAD)18.5
Skewness4.5813203
Sum6219.2
Variance618557.04
MonotonicityNot monotonic
2023-12-12T19:28:14.236140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 7
28.0%
5.5 2
 
8.0%
247.0 1
 
4.0%
0.2 1
 
4.0%
18.5 1
 
4.0%
58.2 1
 
4.0%
23.4 1
 
4.0%
15.9 1
 
4.0%
3915.3 1
 
4.0%
7.5 1
 
4.0%
Other values (8) 8
32.0%
ValueCountFrequency (%)
0.0 7
28.0%
0.2 1
 
4.0%
5.5 2
 
8.0%
7.5 1
 
4.0%
15.9 1
 
4.0%
18.5 1
 
4.0%
23.4 1
 
4.0%
33.6 1
 
4.0%
39.1 1
 
4.0%
53.6 1
 
4.0%
ValueCountFrequency (%)
3915.3 1
4.0%
706.7 1
4.0%
650.0 1
4.0%
247.0 1
4.0%
189.6 1
4.0%
161.7 1
4.0%
87.9 1
4.0%
58.2 1
4.0%
53.6 1
4.0%
39.1 1
4.0%

2017년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean269.84
Minimum0
Maximum4236.8
Zeros8
Zeros (%)32.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:14.350029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median17.9
Q367.7
95-th percentile914.74
Maximum4236.8
Range4236.8
Interquartile range (IQR)67.7

Descriptive statistics

Standard deviation859.57478
Coefficient of variation (CV)3.185498
Kurtosis20.900295
Mean269.84
Median Absolute Deviation (MAD)17.9
Skewness4.4594483
Sum6746
Variance738868.8
MonotonicityNot monotonic
2023-12-12T19:28:14.452300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 8
32.0%
117.9 1
 
4.0%
17.9 1
 
4.0%
0.2 1
 
4.0%
20.7 1
 
4.0%
6.1 1
 
4.0%
67.7 1
 
4.0%
30.2 1
 
4.0%
14.6 1
 
4.0%
4236.8 1
 
4.0%
Other values (8) 8
32.0%
ValueCountFrequency (%)
0.0 8
32.0%
0.2 1
 
4.0%
0.3 1
 
4.0%
6.1 1
 
4.0%
14.6 1
 
4.0%
17.9 1
 
4.0%
20.7 1
 
4.0%
26.3 1
 
4.0%
30.2 1
 
4.0%
39.8 1
 
4.0%
ValueCountFrequency (%)
4236.8 1
4.0%
953.5 1
4.0%
759.7 1
4.0%
271.7 1
4.0%
131.6 1
4.0%
117.9 1
4.0%
67.7 1
4.0%
51.0 1
4.0%
39.8 1
4.0%
30.2 1
4.0%

2018년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean269.836
Minimum0
Maximum4375.9
Zeros8
Zeros (%)32.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:14.545472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median14.5
Q372
95-th percentile701.34
Maximum4375.9
Range4375.9
Interquartile range (IQR)72

Descriptive statistics

Standard deviation878.25197
Coefficient of variation (CV)3.254762
Kurtosis22.170596
Mean269.836
Median Absolute Deviation (MAD)14.5
Skewness4.6159855
Sum6745.9
Variance771326.52
MonotonicityNot monotonic
2023-12-12T19:28:14.646098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 8
32.0%
486.6 1
 
4.0%
10.3 1
 
4.0%
0.2 1
 
4.0%
22.4 1
 
4.0%
3.6 1
 
4.0%
72.0 1
 
4.0%
24.2 1
 
4.0%
14.5 1
 
4.0%
4375.9 1
 
4.0%
Other values (8) 8
32.0%
ValueCountFrequency (%)
0.0 8
32.0%
0.2 1
 
4.0%
2.2 1
 
4.0%
3.6 1
 
4.0%
10.3 1
 
4.0%
14.5 1
 
4.0%
22.4 1
 
4.0%
24.2 1
 
4.0%
30.0 1
 
4.0%
31.8 1
 
4.0%
ValueCountFrequency (%)
4375.9 1
4.0%
724.2 1
4.0%
609.9 1
4.0%
486.6 1
4.0%
155.5 1
4.0%
114.0 1
4.0%
72.0 1
4.0%
68.6 1
4.0%
31.8 1
4.0%
30.0 1
4.0%

2019년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean330.224
Minimum0
Maximum5849.9
Zeros5
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:14.740604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.7
median22.2
Q3114.4
95-th percentile605.88
Maximum5849.9
Range5849.9
Interquartile range (IQR)113.7

Descriptive statistics

Standard deviation1162.993
Coefficient of variation (CV)3.5218305
Kurtosis23.748598
Mean330.224
Median Absolute Deviation (MAD)22.2
Skewness4.8260536
Sum8255.6
Variance1352552.6
MonotonicityNot monotonic
2023-12-12T19:28:14.845328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 5
20.0%
519.0 1
 
4.0%
0.7 1
 
4.0%
0.1 1
 
4.0%
22.2 1
 
4.0%
2.6 1
 
4.0%
75.9 1
 
4.0%
13.3 1
 
4.0%
24.8 1
 
4.0%
5849.9 1
 
4.0%
Other values (11) 11
44.0%
ValueCountFrequency (%)
0.0 5
20.0%
0.1 1
 
4.0%
0.7 1
 
4.0%
2.6 1
 
4.0%
9.1 1
 
4.0%
10.7 1
 
4.0%
13.3 1
 
4.0%
13.6 1
 
4.0%
22.2 1
 
4.0%
24.0 1
 
4.0%
ValueCountFrequency (%)
5849.9 1
4.0%
627.6 1
4.0%
519.0 1
4.0%
407.4 1
4.0%
291.9 1
4.0%
164.3 1
4.0%
114.4 1
4.0%
75.9 1
4.0%
48.3 1
4.0%
35.8 1
4.0%

2020년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean279.208
Minimum0
Maximum4443.4
Zeros5
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:14.941296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2
median20.3
Q3135
95-th percentile629.14
Maximum4443.4
Range4443.4
Interquartile range (IQR)134.8

Descriptive statistics

Standard deviation886.80504
Coefficient of variation (CV)3.1761448
Kurtosis22.618221
Mean279.208
Median Absolute Deviation (MAD)20.3
Skewness4.6724329
Sum6980.2
Variance786423.18
MonotonicityNot monotonic
2023-12-12T19:28:15.316180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 5
20.0%
0.2 2
 
8.0%
278.7 1
 
4.0%
16.6 1
 
4.0%
2.3 1
 
4.0%
81.3 1
 
4.0%
22.0 1
 
4.0%
12.1 1
 
4.0%
4443.4 1
 
4.0%
20.3 1
 
4.0%
Other values (10) 10
40.0%
ValueCountFrequency (%)
0.0 5
20.0%
0.2 2
 
8.0%
2.3 1
 
4.0%
3.2 1
 
4.0%
6.1 1
 
4.0%
12.1 1
 
4.0%
16.6 1
 
4.0%
20.3 1
 
4.0%
22.0 1
 
4.0%
38.1 1
 
4.0%
ValueCountFrequency (%)
4443.4 1
4.0%
647.5 1
4.0%
555.7 1
4.0%
466.9 1
4.0%
278.7 1
4.0%
151.1 1
4.0%
135.0 1
4.0%
81.3 1
4.0%
57.3 1
4.0%
42.2 1
4.0%

2021년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean308.268
Minimum0
Maximum4895
Zeros5
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T19:28:15.413748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.7
median16.2
Q3137
95-th percentile769.76
Maximum4895
Range4895
Interquartile range (IQR)136.3

Descriptive statistics

Standard deviation978.54489
Coefficient of variation (CV)3.1743317
Kurtosis22.433986
Mean308.268
Median Absolute Deviation (MAD)16.2
Skewness4.6497432
Sum7706.7
Variance957550.11
MonotonicityNot monotonic
2023-12-12T19:28:15.544704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 5
20.0%
465.2 1
 
4.0%
0.7 1
 
4.0%
0.1 1
 
4.0%
16.2 1
 
4.0%
2.7 1
 
4.0%
96.3 1
 
4.0%
21.5 1
 
4.0%
12.7 1
 
4.0%
4895.0 1
 
4.0%
Other values (11) 11
44.0%
ValueCountFrequency (%)
0.0 5
20.0%
0.1 1
 
4.0%
0.7 1
 
4.0%
2.7 1
 
4.0%
4.0 1
 
4.0%
7.7 1
 
4.0%
11.4 1
 
4.0%
12.7 1
 
4.0%
16.2 1
 
4.0%
21.5 1
 
4.0%
ValueCountFrequency (%)
4895.0 1
4.0%
807.3 1
4.0%
619.6 1
4.0%
465.2 1
4.0%
281.0 1
4.0%
162.8 1
4.0%
137.0 1
4.0%
96.3 1
4.0%
60.3 1
4.0%
59.0 1
4.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
Minimum2021-12-31 00:00:00
Maximum2021-12-31 00:00:00
2023-12-12T19:28:15.704172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:15.818842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T19:28:09.298017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:51.500916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:52.828668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:54.035925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:55.245549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:56.722051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:58.021715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:59.450265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:00.799938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:02.097055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:03.880062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.140224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:06.095954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:07.518150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:09.383259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:51.585787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:52.923591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:54.108163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:55.329008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:56.815254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:58.117961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:59.548244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:00.876475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:02.542525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:03.971790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.211475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:06.173589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:07.632404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:09.459626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:51.677095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:53.001503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:54.190499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:55.404372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:56.915545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:58.212781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:59.658435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:00.954759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:02.630087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:04.044199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.275019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:06.245684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:07.723133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:09.539347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:51.758415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:53.069698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:54.257782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:55.479237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:57.003739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:58.289350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:59.756995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:01.030323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:02.711179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:04.119200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.340883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:06.326439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:07.805851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:09.627573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:51.857851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:53.153845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:54.336703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:55.574021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:57.089775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:58.450213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:59.854639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:01.117194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:02.821843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:04.223879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.413240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:06.408148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:07.910210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:09.729284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:51.968009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:53.236922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:54.425706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:55.663562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:57.191909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:58.559687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:59.969164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:01.229435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:02.919961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:04.353956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.481374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:06.538794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:08.014803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:09.835361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:52.064951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:53.325067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:54.513155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:55.749068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:57.306003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:58.645098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:00.086804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:01.347102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:03.054649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:04.442567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.550844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:06.661432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:08.170511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:09.926574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:52.181864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:53.401596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:54.603599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:55.842673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:57.414420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:58.739213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:00.177208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:01.428025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:03.178375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:04.523891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.615027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:06.766089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:08.304724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.027600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:52.276191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:53.481231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:54.739259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:55.947874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:57.497956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:58.834013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:00.267515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:01.510424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:03.281939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:04.613305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.681735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:06.884291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:08.437598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.135148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:52.369531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:53.607078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:54.832411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:56.319417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:57.596982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:58.927700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:00.382174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:01.609359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:03.406426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:04.725224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.762948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:06.996563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:08.559188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.220453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:52.472401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:53.699859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:54.904248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:56.392643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:57.679875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:59.015091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:00.472197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:01.689673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:03.505644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:04.819340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.835362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:07.101386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:08.645293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.305753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:52.560590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:53.785150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:54.987708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:56.467662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:57.759380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:59.127144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:00.547912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:01.765782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:03.602494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:04.900520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.898357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:07.196587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:09.025367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.395505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:52.651863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:53.880940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:55.086582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:56.551776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:57.848066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:59.229972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:00.635317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:01.855615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:03.688956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:04.996150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.969027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:07.288626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:09.121618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.493704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:52.751040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:53.954409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:55.167946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:56.644818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:57.929735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:27:59.317730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:00.713133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:01.950609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:03.776384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:05.070158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:06.031950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:07.397619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:09.202624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:28:15.942150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류중분류소분류2008년2009년2010년2011년2012년2013년2014년2015년2016년2017년2018년2019년2020년2021년
대분류1.0001.0000.0000.0000.0000.0780.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
중분류1.0001.0000.0000.1730.5540.5520.1730.1730.1730.1730.1730.0000.1730.6690.4500.6690.000
소분류0.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.3220.0000.0000.0000.0000.322
2008년0.0000.1730.0001.0000.9890.9861.0001.0001.0001.0001.0001.0001.0000.8231.0000.8231.000
2009년0.0000.5540.0000.9891.0000.9980.9890.9890.9890.9890.9890.8230.9890.8531.0000.8530.823
2010년0.0780.5520.0000.9860.9981.0000.9860.9860.9860.9860.9860.8110.9860.8191.0000.8190.811
2011년0.0000.1730.0001.0000.9890.9861.0001.0001.0001.0001.0001.0001.0000.8231.0000.8231.000
2012년0.0000.1730.0001.0000.9890.9861.0001.0001.0001.0001.0001.0001.0000.8231.0000.8231.000
2013년0.0000.1730.0001.0000.9890.9861.0001.0001.0001.0001.0001.0001.0000.8231.0000.8231.000
2014년0.0000.1730.0001.0000.9890.9861.0001.0001.0001.0001.0001.0001.0000.8231.0000.8231.000
2015년0.0000.1730.0001.0000.9890.9861.0001.0001.0001.0001.0001.0001.0000.8231.0000.8231.000
2016년0.0000.0000.3221.0000.8230.8111.0001.0001.0001.0001.0001.0001.0000.9930.9840.9931.000
2017년0.0000.1730.0001.0000.9890.9861.0001.0001.0001.0001.0001.0001.0000.8231.0000.8231.000
2018년0.0000.6690.0000.8230.8530.8190.8230.8230.8230.8230.8230.9930.8231.0000.9701.0000.993
2019년0.0000.4500.0001.0001.0001.0001.0001.0001.0001.0001.0000.9841.0000.9701.0000.9700.984
2020년0.0000.6690.0000.8230.8530.8190.8230.8230.8230.8230.8230.9930.8231.0000.9701.0000.993
2021년0.0000.0000.3221.0000.8230.8111.0001.0001.0001.0001.0001.0001.0000.9930.9840.9931.000
2023-12-12T19:28:16.126121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소분류대분류중분류
소분류1.0000.0000.000
대분류0.0001.0000.975
중분류0.0000.9751.000
2023-12-12T19:28:16.257014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2008년2009년2010년2011년2012년2013년2014년2015년2016년2017년2018년2019년2020년2021년대분류중분류소분류
2008년1.0000.9510.9420.9310.9550.9770.9510.9340.9350.8140.8160.7370.7700.7730.0000.0450.000
2009년0.9511.0000.9940.9900.9530.9540.9550.8960.8990.7770.7790.6840.7200.7270.0000.3600.000
2010년0.9420.9941.0000.9960.9650.9560.9670.9130.9150.7950.7970.7020.7380.7480.0000.3580.000
2011년0.9310.9900.9961.0000.9650.9530.9670.9120.9130.8120.8110.7060.7410.7500.0000.0450.000
2012년0.9550.9530.9650.9651.0000.9910.9990.9820.9790.8510.8520.7670.8060.8170.0000.0450.000
2013년0.9770.9540.9560.9530.9911.0000.9910.9790.9770.8510.8490.7620.8010.8070.0000.0450.000
2014년0.9510.9550.9670.9670.9990.9911.0000.9820.9810.8530.8540.7620.7980.8100.0000.0450.000
2015년0.9340.8960.9130.9120.9820.9790.9821.0000.9970.8670.8710.7920.8300.8410.0000.0450.000
2016년0.9350.8990.9150.9130.9790.9770.9810.9971.0000.8800.8860.7950.8280.8390.0000.0000.091
2017년0.8140.7770.7950.8120.8510.8510.8530.8670.8801.0000.9950.7930.7870.7690.0000.0450.000
2018년0.8160.7790.7970.8110.8520.8490.8540.8710.8860.9951.0000.7980.7910.7740.0000.3190.000
2019년0.7370.6840.7020.7060.7670.7620.7620.7920.7950.7930.7981.0000.9800.9720.0000.1700.000
2020년0.7700.7200.7380.7410.8060.8010.7980.8300.8280.7870.7910.9801.0000.9950.0000.3190.000
2021년0.7730.7270.7480.7500.8170.8070.8100.8410.8390.7690.7740.9720.9951.0000.0000.0000.091
대분류0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.9750.000
중분류0.0450.3600.3580.0450.0450.0450.0450.0450.0000.0450.3190.1700.3190.0000.9751.0000.000
소분류0.0000.0000.0000.0000.0000.0000.0000.0000.0910.0000.0000.0000.0000.0910.0000.0001.000

Missing values

2023-12-12T19:28:10.649018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:28:10.910821image/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

대분류중분류소분류2008년2009년2010년2011년2012년2013년2014년2015년2016년2017년2018년2019년2020년2021년데이터기준일자
0생활폐기물가정생활폐기물매립272.7255.0235.2206.2208.9201.1173.0183.7247.0117.9486.6519.0466.9465.22021-12-31
1생활폐기물가정생활폐기물소각246.1247.2231.9203.0233.7242.5240.9238.0189.60.00.013.638.160.32021-12-31
2생활폐기물가정생활폐기물재활용804.7800.8771.3745.1726.5752.0733.5704.8650.0953.5609.9627.6647.5807.32021-12-31
3생활폐기물사업장생활계폐기물매립21.835.031.432.129.628.831.231.839.139.831.89.13.24.02021-12-31
4생활폐기물사업장생활계폐기물소각40.220.817.918.829.829.029.732.133.626.330.024.042.246.22021-12-31
5생활폐기물사업장생활계폐기물재활용95.371.2109.2128.7100.373.6108.182.587.9131.6114.0164.3151.1162.82021-12-31
6생활폐기물사업장생활계폐기물기타0.00.00.00.00.00.00.00.00.00.00.010.76.17.72021-12-31
7사업장배출시설계폐기물사업장배출시설계폐기물매립162.7161.3230.5236.8212.9205.9199.5137.3161.7271.7155.5114.4135.0137.02021-12-31
8사업장배출시설계폐기물사업장배출시설계폐기물소각57.448.553.147.837.240.644.447.853.651.068.648.357.359.02021-12-31
9사업장배출시설계폐기물사업장배출시설계폐기물재활용414.6370.0422.1437.2490.1503.5491.3467.9706.7759.7724.2407.4555.7619.62021-12-31
대분류중분류소분류2008년2009년2010년2011년2012년2013년2014년2015년2016년2017년2018년2019년2020년2021년데이터기준일자
15건설폐기물건설폐기물해역배출0.00.00.00.00.00.00.00.00.00.00.00.00.00.02021-12-31
16건설폐기물건설폐기물기타0.00.00.00.00.00.00.00.00.00.00.00.00.00.02021-12-31
17지정폐기물지정폐기물매립3.37.45.83.87.812.611.815.215.914.614.524.812.112.72021-12-31
18지정폐기물지정폐기물소각21.920.524.024.429.623.522.421.323.430.224.213.322.021.52021-12-31
19지정폐기물지정폐기물재활용37.454.440.363.651.658.458.353.958.267.772.075.981.396.32021-12-31
20지정폐기물지정폐기물기타1.62.30.72.90.71.61.31.65.56.13.62.62.32.72021-12-31
21의료폐기물의료폐기물소각7.89.510.211.712.913.915.817.2718.520.722.422.216.616.22021-12-31
22의료폐기물의료폐기물멸균분쇄0.00.00.00.00.00.00.00.00.00.00.00.00.00.02021-12-31
23의료폐기물의료폐기물재활용0.00.00.00.00.00.00.00.00.00.00.00.00.00.02021-12-31
24의료폐기물의료폐기물기타0.10.10.20.20.20.20.10.20.20.20.20.10.20.12021-12-31