Overview

Dataset statistics

Number of variables3
Number of observations426
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.4 KiB
Average record size in memory27.3 B

Variable types

Numeric1
Categorical2

Dataset

Description폐기물처분부담금시스템 내 등록되어진 데이터로 폐기물처분부담금 신고를 위한 폐기물분류코드를 제공하는 정보입니다.
Author한국환경공단
URLhttps://www.data.go.kr/data/15092758/fileData.do

Alerts

실적년도 has constant value ""Constant
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:47:38.886259
Analysis finished2023-12-12 16:47:39.205979
Duration0.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct426
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean213.5
Minimum1
Maximum426
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-13T01:47:39.296710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.25
Q1107.25
median213.5
Q3319.75
95-th percentile404.75
Maximum426
Range425
Interquartile range (IQR)212.5

Descriptive statistics

Standard deviation123.11986
Coefficient of variation (CV)0.57667382
Kurtosis-1.2
Mean213.5
Median Absolute Deviation (MAD)106.5
Skewness0
Sum90951
Variance15158.5
MonotonicityStrictly increasing
2023-12-13T01:47:39.482178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
294 1
 
0.2%
292 1
 
0.2%
291 1
 
0.2%
290 1
 
0.2%
289 1
 
0.2%
288 1
 
0.2%
287 1
 
0.2%
286 1
 
0.2%
285 1
 
0.2%
Other values (416) 416
97.7%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
426 1
0.2%
425 1
0.2%
424 1
0.2%
423 1
0.2%
422 1
0.2%
421 1
0.2%
420 1
0.2%
419 1
0.2%
418 1
0.2%
417 1
0.2%

폐기물분류코드
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
302002
355 
302001
47 
302003
 
24

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row302002
2nd row302002
3rd row302002
4th row302002
5th row302002

Common Values

ValueCountFrequency (%)
302002 355
83.3%
302001 47
 
11.0%
302003 24
 
5.6%

Length

2023-12-13T01:47:39.619277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:47:39.729736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
302002 355
83.3%
302001 47
 
11.0%
302003 24
 
5.6%

실적년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2022
426 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 426
100.0%

Length

2023-12-13T01:47:39.861116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:47:39.956939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 426
100.0%

Interactions

2023-12-13T01:47:38.963291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:47:40.025471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번폐기물분류코드
순번1.0000.565
폐기물분류코드0.5651.000
2023-12-13T01:47:40.116274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번폐기물분류코드
순번1.0000.408
폐기물분류코드0.4081.000

Missing values

2023-12-13T01:47:39.083966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:47:39.170740image/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

순번폐기물분류코드실적년도
013020022022
123020022022
233020022022
343020022022
453020022022
563020022022
673020022022
783020022022
893020022022
9103020022022
순번폐기물분류코드실적년도
4164173020022022
4174183020022022
4184193020022022
4194203020022022
4204213020022022
4214223020022022
4224233020022022
4234243020022022
4244253020022022
4254263020022022