Overview

Dataset statistics

Number of variables5
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory49.5 B

Variable types

Numeric4
Categorical1

Dataset

Description수도권매립지관리공사로 반입되는 인천시 연도별 폐기물 반입량입니다. 개방항목 : 연도, 지자체명, 생활폐기물 반입량(kg), 사업장폐기물(kg), 건설폐기물 반입량(kg) 항목을 제공합니다. * 생활소각재 분류(2010년까지 : 생활폐기물, 2011년 이후 : 사업장 배출시설계)
Author수도권매립지관리공사
URLhttps://www.data.go.kr/data/15066519/fileData.do

Alerts

지자체명 has constant value ""Constant
연도 is highly overall correlated with 생활폐기물 반입량(kg) and 2 other fieldsHigh correlation
생활폐기물 반입량(kg) is highly overall correlated with 연도 and 2 other fieldsHigh correlation
사업장폐기물 반입량(kg) is highly overall correlated with 연도 and 2 other fieldsHigh correlation
건설폐기물 반입량(kg) is highly overall correlated with 연도 and 2 other fieldsHigh correlation
연도 has unique valuesUnique
생활폐기물 반입량(kg) has unique valuesUnique
사업장폐기물 반입량(kg) has unique valuesUnique
건설폐기물 반입량(kg) has unique valuesUnique
건설폐기물 반입량(kg) has 1 (4.2%) zerosZeros

Reproduction

Analysis started2023-12-12 12:04:36.196738
Analysis finished2023-12-12 12:04:38.254338
Duration2.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2010.5
Minimum1999
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T21:04:38.331522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1999
5-th percentile2000.15
Q12004.75
median2010.5
Q32016.25
95-th percentile2020.85
Maximum2022
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.0035170693
Kurtosis-1.2
Mean2010.5
Median Absolute Deviation (MAD)6
Skewness0
Sum48252
Variance50
MonotonicityStrictly increasing
2023-12-12T21:04:38.480822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1999 1
 
4.2%
2012 1
 
4.2%
2022 1
 
4.2%
2021 1
 
4.2%
2020 1
 
4.2%
2019 1
 
4.2%
2018 1
 
4.2%
2017 1
 
4.2%
2016 1
 
4.2%
2015 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1999 1
4.2%
2000 1
4.2%
2001 1
4.2%
2002 1
4.2%
2003 1
4.2%
2004 1
4.2%
2005 1
4.2%
2006 1
4.2%
2007 1
4.2%
2008 1
4.2%
ValueCountFrequency (%)
2022 1
4.2%
2021 1
4.2%
2020 1
4.2%
2019 1
4.2%
2018 1
4.2%
2017 1
4.2%
2016 1
4.2%
2015 1
4.2%
2014 1
4.2%
2013 1
4.2%

지자체명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
인천광역시
24 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 24
100.0%

Length

2023-12-12T21:04:38.663340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:04:38.774719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 24
100.0%

생활폐기물 반입량(kg)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5698768 × 108
Minimum35523180
Maximum4.6359078 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T21:04:38.881855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35523180
5-th percentile48653342
Q174391058
median1.0304226 × 108
Q31.8709911 × 108
95-th percentile4.541521 × 108
Maximum4.6359078 × 108
Range4.280676 × 108
Interquartile range (IQR)1.1270805 × 108

Descriptive statistics

Standard deviation1.3241588 × 108
Coefficient of variation (CV)0.84347947
Kurtosis0.91513846
Mean1.5698768 × 108
Median Absolute Deviation (MAD)39017220
Skewness1.4626149
Sum3.7677043 × 109
Variance1.7533966 × 1016
MonotonicityNot monotonic
2023-12-12T21:04:39.008218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
461231170 1
 
4.2%
35523180 1
 
4.2%
75794920 1
 
4.2%
89432830 1
 
4.2%
112201020 1
 
4.2%
126603760 1
 
4.2%
106888000 1
 
4.2%
86009070 1
 
4.2%
70179470 1
 
4.2%
57870600 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
35523180 1
4.2%
47896040 1
4.2%
52944720 1
4.2%
54769780 1
4.2%
57870600 1
4.2%
70179470 1
4.2%
75794920 1
4.2%
86009070 1
4.2%
89432830 1
4.2%
95928652 1
4.2%
ValueCountFrequency (%)
463590780 1
4.2%
461231170 1
4.2%
414037340 1
4.2%
324496020 1
4.2%
277186510 1
4.2%
231221420 1
4.2%
172391670 1
4.2%
126603760 1
4.2%
112201020 1
4.2%
106888000 1
4.2%

사업장폐기물 반입량(kg)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5717214 × 108
Minimum1.5327639 × 108
Maximum5.2359535 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T21:04:39.157275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5327639 × 108
5-th percentile1.7101782 × 108
Q12.4728043 × 108
median4.0590126 × 108
Q34.6050762 × 108
95-th percentile4.9494183 × 108
Maximum5.2359535 × 108
Range3.7031896 × 108
Interquartile range (IQR)2.1322719 × 108

Descriptive statistics

Standard deviation1.2682647 × 108
Coefficient of variation (CV)0.35508501
Kurtosis-1.5098154
Mean3.5717214 × 108
Median Absolute Deviation (MAD)88336035
Skewness-0.36915893
Sum8.5721313 × 109
Variance1.6084954 × 1016
MonotonicityNot monotonic
2023-12-12T21:04:39.344872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
242389720 1
 
4.2%
389348560 1
 
4.2%
265938790 1
 
4.2%
452672440 1
 
4.2%
493230810 1
 
4.2%
485760870 1
 
4.2%
450628170 1
 
4.2%
435576460 1
 
4.2%
523595350 1
 
4.2%
484013170 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
153276390 1
4.2%
170663980 1
4.2%
173022900 1
4.2%
184978260 1
4.2%
187440180 1
4.2%
242389720 1
4.2%
248910669 1
4.2%
265938790 1
4.2%
276243270 1
4.2%
294598670 1
4.2%
ValueCountFrequency (%)
523595350 1
4.2%
495243770 1
4.2%
493230810 1
4.2%
485760870 1
4.2%
484638923 1
4.2%
484013170 1
4.2%
452672440 1
4.2%
450628170 1
4.2%
450432880 1
4.2%
435576460 1
4.2%

건설폐기물 반입량(kg)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7448844 × 108
Minimum0
Maximum7.4567113 × 108
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T21:04:39.502575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile45364294
Q11.3645341 × 108
median1.7060298 × 108
Q34.1548907 × 108
95-th percentile6.4906611 × 108
Maximum7.4567113 × 108
Range7.4567113 × 108
Interquartile range (IQR)2.7903566 × 108

Descriptive statistics

Standard deviation2.1543662 × 108
Coefficient of variation (CV)0.78486592
Kurtosis-0.48136444
Mean2.7448844 × 108
Median Absolute Deviation (MAD)92032720
Skewness0.87643543
Sum6.5877225 × 109
Variance4.6412937 × 1016
MonotonicityNot monotonic
2023-12-12T21:04:39.637592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
243213740 1
 
4.2%
137116050 1
 
4.2%
0 1
 
4.2%
52244100 1
 
4.2%
44150210 1
 
4.2%
81026150 1
 
4.2%
133187840 1
 
4.2%
158446370 1
 
4.2%
149583490 1
 
4.2%
172001890 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
0 1
4.2%
44150210 1
4.2%
52244100 1
4.2%
81026150 1
4.2%
133187840 1
4.2%
134465500 1
4.2%
137116050 1
4.2%
145400870 1
4.2%
149583490 1
4.2%
158446370 1
4.2%
ValueCountFrequency (%)
745671130 1
4.2%
656272210 1
4.2%
608231540 1
4.2%
567727170 1
4.2%
550472890 1
4.2%
475528748 1
4.2%
395475850 1
4.2%
361437340 1
4.2%
265091590 1
4.2%
243213740 1
4.2%

Interactions

2023-12-12T21:04:37.631390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.352233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.747061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:37.173478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:37.748304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.447648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.845492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:37.268320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:37.865880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.534563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.928535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:37.384441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:37.961636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.632960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:37.049688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:37.511532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:04:39.728160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도생활폐기물 반입량(kg)사업장폐기물 반입량(kg)건설폐기물 반입량(kg)
연도1.0000.7110.4060.862
생활폐기물 반입량(kg)0.7111.0000.0000.731
사업장폐기물 반입량(kg)0.4060.0001.0000.660
건설폐기물 반입량(kg)0.8620.7310.6601.000
2023-12-12T21:04:39.858723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도생활폐기물 반입량(kg)사업장폐기물 반입량(kg)건설폐기물 반입량(kg)
연도1.000-0.6260.710-0.888
생활폐기물 반입량(kg)-0.6261.000-0.5250.542
사업장폐기물 반입량(kg)0.710-0.5251.000-0.683
건설폐기물 반입량(kg)-0.8880.542-0.6831.000

Missing values

2023-12-12T21:04:38.091560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:04:38.204067image/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

연도지자체명생활폐기물 반입량(kg)사업장폐기물 반입량(kg)건설폐기물 반입량(kg)
01999인천광역시461231170242389720243213740
12000인천광역시463590780276243270361437340
22001인천광역시414037340170663980550472890
32002인천광역시324496020153276390745671130
42003인천광역시277186510173022900656272210
52004인천광역시231221420184978260567727170
62005인천광역시172391670187440180608231540
72006인천광역시103978111248910669395475850
82007인천광역시102106400294598670475528748
92008인천광역시99581110427001010265091590
연도지자체명생활폐기물 반입량(kg)사업장폐기물 반입량(kg)건설폐기물 반입량(kg)
142013인천광역시47896040450432880145400870
152014인천광역시52944720422453950134465500
162015인천광역시57870600484013170172001890
172016인천광역시70179470523595350149583490
182017인천광역시86009070435576460158446370
192018인천광역시106888000450628170133187840
202019인천광역시12660376048576087081026150
212020인천광역시11220102049323081044150210
222021인천광역시8943283045267244052244100
232022인천광역시757949202659387900