Dataset statistics
| Number of variables | 3 |
|---|---|
| Number of observations | 42 |
| Missing cells | 0 |
| Missing cells (%) | 0.0% |
| Duplicate rows | 4 |
| Duplicate rows (%) | 9.5% |
| Total size in memory | 1.2 KiB |
| Average record size in memory | 29.1 B |
Variable types
| DateTime | 1 |
|---|---|
| Categorical | 2 |
Dataset
| Description | 폐기물처분부담금시스템 내 폐기물처분부담금 신고한 내역에 대해서 폐기물처분부담금 부과 고지를 위한 정보입니다. |
|---|---|
| Author | 한국환경공단 |
| URL | https://www.data.go.kr/data/15092753/fileData.do |
| Dataset has 4 (9.5%) duplicate rows | Duplicates |
진행상태 is highly imbalanced (72.4%) | Imbalance |
Reproduction
| Analysis started | 2023-12-12 22:33:11.825595 |
|---|---|
| Analysis finished | 2023-12-12 22:33:12.066364 |
| Duration | 0.24 seconds |
| Software version | ydata-profiling vv4.5.1 |
| Download configuration | config.json |
등록일시
Date
| Distinct | 23 |
|---|---|
| Distinct (%) | 54.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 468.0 B |
| Minimum | 2022-01-06 14:38:35 |
|---|---|
| Maximum | 2022-08-08 14:34:36 |
Histogram with fixed size bins (bins=23)
순번
Categorical
| Distinct | 4 |
|---|---|
| Distinct (%) | 9.5% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 468.0 B |
| 1 | |
|---|---|
| 2 | |
| 3 | |
| 4 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 1 |
|---|---|
| 2nd row | 1 |
| 3rd row | 1 |
| 4th row | 1 |
| 5th row | 1 |
Common Values
| Value | Count | Frequency (%) |
| 1 | 25 | |
| 2 | 9 | 21.4% |
| 3 | 4 | 9.5% |
| 4 | 4 | 9.5% |
Length
Histogram of lengths of the category
Common Values (Plot)
| Value | Count | Frequency (%) |
| 1 | 25 | |
| 2 | 9 | 21.4% |
| 3 | 4 | 9.5% |
| 4 | 4 | 9.5% |
진행상태
Categorical
IMBALANCE
| Distinct | 2 |
|---|---|
| Distinct (%) | 4.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 468.0 B |
| 1 | |
|---|---|
| 7 | 2 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 1 |
|---|---|
| 2nd row | 1 |
| 3rd row | 1 |
| 4th row | 1 |
| 5th row | 1 |
Common Values
| Value | Count | Frequency (%) |
| 1 | 40 | |
| 7 | 2 | 4.8% |
Length
Histogram of lengths of the category
Common Values (Plot)
| Value | Count | Frequency (%) |
| 1 | 40 | |
| 7 | 2 | 4.8% |
| 등록일시 | 순번 | 진행상태 | |
|---|---|---|---|
| 등록일시 | 1.000 | 0.000 | 1.000 |
| 순번 | 0.000 | 1.000 | 0.000 |
| 진행상태 | 1.000 | 0.000 | 1.000 |
| 순번 | 진행상태 | |
|---|---|---|
| 순번 | 1.000 | 0.000 |
| 진행상태 | 0.000 | 1.000 |
| 순번 | 진행상태 | |
|---|---|---|
| 순번 | 1.000 | 0.000 |
| 진행상태 | 0.000 | 1.000 |
A simple visualization of nullity by column.
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
| 등록일시 | 순번 | 진행상태 | |
|---|---|---|---|
| 0 | 2022-01-06 14:38:35 | 1 | 1 |
| 1 | 2022-01-06 14:39:02 | 1 | 1 |
| 2 | 2022-01-06 14:39:47 | 1 | 1 |
| 3 | 2022-01-06 15:54:25 | 1 | 1 |
| 4 | 2022-01-06 15:56:27 | 1 | 1 |
| 5 | 2022-01-06 15:57:32 | 1 | 1 |
| 6 | 2022-01-06 15:58:44 | 1 | 1 |
| 7 | 2022-01-06 16:00:09 | 1 | 1 |
| 8 | 2022-01-06 16:00:37 | 1 | 1 |
| 9 | 2022-01-06 16:01:09 | 1 | 1 |
| 등록일시 | 순번 | 진행상태 | |
|---|---|---|---|
| 32 | 2022-04-19 14:18:27 | 2 | 1 |
| 33 | 2022-04-19 14:18:27 | 2 | 1 |
| 34 | 2022-04-19 15:45:00 | 1 | 1 |
| 35 | 2022-04-19 15:57:18 | 1 | 1 |
| 36 | 2022-04-19 15:57:18 | 2 | 1 |
| 37 | 2022-04-19 15:57:18 | 1 | 1 |
| 38 | 2022-04-19 15:57:18 | 2 | 1 |
| 39 | 2022-04-19 16:06:01 | 1 | 1 |
| 40 | 2022-05-09 14:56:29 | 1 | 1 |
| 41 | 2022-08-08 14:34:36 | 1 | 1 |
Most frequently occurring
| 등록일시 | 순번 | 진행상태 | # duplicates | |
|---|---|---|---|---|
| 0 | 2022-04-19 14:18:27 | 1 | 1 | 2 |
| 1 | 2022-04-19 14:18:27 | 2 | 1 | 2 |
| 2 | 2022-04-19 15:57:18 | 1 | 1 | 2 |
| 3 | 2022-04-19 15:57:18 | 2 | 1 | 2 |