Overview

Dataset statistics

Number of variables4
Number of observations8501
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory274.1 KiB
Average record size in memory33.0 B

Variable types

DateTime1
Categorical2
Numeric1

Dataset

Description수도권매립지로 반입되는 서울시, 경기도, 인천시의 폐기물 반입량 정보입니다.개방항목 : 마감년월, 광역지자체명, 폐기물명, 반입량(kg) 항목을 제공합니다.
Author수도권매립지관리공사
URLhttps://www.data.go.kr/data/15064381/fileData.do

Reproduction

Analysis started2024-04-13 11:39:12.628474
Analysis finished2024-04-13 11:39:14.970135
Duration2.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

마감년월
Date

Distinct296
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size66.5 KiB
Minimum1999-08-01 00:00:00
Maximum2024-03-01 00:00:00
2024-04-13T20:39:15.179865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:39:15.625060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

광역지자체명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.5 KiB
경기도
3069 
인천시
2824 
서울시
2608 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 3069
36.1%
인천시 2824
33.2%
서울시 2608
30.7%

Length

2024-04-13T20:39:16.038095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T20:39:16.363224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 3069
36.1%
인천시 2824
33.2%
서울시 2608
30.7%

폐기물명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.5 KiB
생활
888 
건설폐기물
807 
고형화오니
774 
연탄재
719 
하수준설토
576 
Other values (21)
4737 

Length

Max length19
Median length10
Mean length6.2120927
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row하수오니
2nd row하수준설토
3rd row광재등17종
4th row건설폐기물
5th row생활

Common Values

ValueCountFrequency (%)
생활 888
10.4%
건설폐기물 807
 
9.5%
고형화오니 774
 
9.1%
연탄재 719
 
8.5%
하수준설토 576
 
6.8%
중간처리잔재폐기물 567
 
6.7%
광재등17종 538
 
6.3%
정수오니 528
 
6.2%
사업장생활계(자가) 447
 
5.3%
사업장비배출시설계(자가)_협의폐기물 440
 
5.2%
Other values (16) 2217
26.1%

Length

2024-04-13T20:39:16.751371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
생활 888
 
10.2%
건설폐기물 807
 
9.2%
고형화오니 774
 
8.9%
연탄재 719
 
8.2%
하수준설토 576
 
6.6%
중간처리잔재폐기물 567
 
6.5%
광재등17종 538
 
6.2%
정수오니 528
 
6.1%
사업장생활계(자가 447
 
5.1%
사업장비배출시설계(자가)_협의폐기물 440
 
5.0%
Other values (17) 2442
28.0%

반입량(kg)
Real number (ℝ)

Distinct8410
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12417297
Minimum2320
Maximum1.9680948 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.8 KiB
2024-04-13T20:39:17.196070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2320
5-th percentile26870
Q1578900
median3116540
Q312432370
95-th percentile58190440
Maximum1.9680948 × 108
Range1.9680716 × 108
Interquartile range (IQR)11853470

Descriptive statistics

Standard deviation24191303
Coefficient of variation (CV)1.948194
Kurtosis16.476933
Mean12417297
Median Absolute Deviation (MAD)3013610
Skewness3.7112113
Sum1.0555944 × 1011
Variance5.8521913 × 1014
MonotonicityNot monotonic
2024-04-13T20:39:17.682146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19770 4
 
< 0.1%
17460 3
 
< 0.1%
10390 3
 
< 0.1%
10610 3
 
< 0.1%
67310 2
 
< 0.1%
5605220 2
 
< 0.1%
159870 2
 
< 0.1%
20540 2
 
< 0.1%
422180 2
 
< 0.1%
154910 2
 
< 0.1%
Other values (8400) 8476
99.7%
ValueCountFrequency (%)
2320 1
< 0.1%
2930 1
< 0.1%
2960 1
< 0.1%
2980 1
< 0.1%
3000 1
< 0.1%
3160 1
< 0.1%
3180 1
< 0.1%
3210 1
< 0.1%
3320 1
< 0.1%
3330 1
< 0.1%
ValueCountFrequency (%)
196809480 1
< 0.1%
191662660 1
< 0.1%
187013150 1
< 0.1%
186058990 1
< 0.1%
183444630 1
< 0.1%
183294120 1
< 0.1%
182965990 1
< 0.1%
176415340 1
< 0.1%
175787140 1
< 0.1%
174705930 1
< 0.1%

Interactions

2024-04-13T20:39:14.157059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-13T20:39:17.956849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
광역지자체명폐기물명반입량(kg)
광역지자체명1.0000.4960.298
폐기물명0.4961.0000.594
반입량(kg)0.2980.5941.000
2024-04-13T20:39:18.194824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물명광역지자체명
폐기물명1.0000.294
광역지자체명0.2941.000
2024-04-13T20:39:18.431235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
반입량(kg)광역지자체명폐기물명
반입량(kg)1.0000.1870.260
광역지자체명0.1871.0000.294
폐기물명0.2600.2941.000

Missing values

2024-04-13T20:39:14.534666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-13T20:39:14.829899image/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

마감년월광역지자체명폐기물명반입량(kg)
01999-08서울시하수오니127310400
11999-08서울시하수준설토24440330
21999-08서울시광재등17종171610
31999-08서울시건설폐기물105010360
41999-08서울시생활172220840
51999-08서울시사업장생활계(자가)5660040
61999-08서울시가내공업6406330
71999-08서울시연탄재36460
81999-08서울시열경화성폐합성수지993050
91999-08인천시오니류등4종58360
마감년월광역지자체명폐기물명반입량(kg)
84912024-03경기도하수오니39630
84922024-03경기도고형화오니7546550
84932024-03경기도하수준설토300400
84942024-03경기도사업장배출계(기타)417760
84952024-03경기도생활23876670
84962024-03경기도연탄재698300
84972024-03경기도중간처리잔재폐기물1874400
84982024-03경기도사업장비배출시설계(자가)_협의폐기물300280
84992024-03경기도음식물탈리액7041190
85002024-03경기도음폐수5726380