Overview

Dataset statistics

Number of variables4
Number of observations1923
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory60.2 KiB
Average record size in memory32.1 B

Variable types

Text1
DateTime2
Boolean1

Dataset

Description메타관리시스템 기반 공공데이터 개방계획 수립 및 이행을 위한 수상구조사 시스템의 수상안전종합관리 첨부파일관리 데이터로 파일 ID, 파일생성일, 사용여부 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15118343/fileData.do

Alerts

첨부파일사용여부(USE_AT) has constant value ""Constant
첨부파일아이디(ATCH_FILE_ID) has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:06:39.626870
Analysis finished2023-12-12 00:06:40.159025
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct1923
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
2023-12-12T09:06:40.330685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters38460
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1923 ?
Unique (%)100.0%

Sample

1st rowFILE_000000000000431
2nd rowFILE_000000000000441
3rd rowFILE_000000000000442
4th rowFILE_000000000000450
5th rowFILE_000000000000451
ValueCountFrequency (%)
file_000000000000431 1
 
0.1%
file_000000000003240 1
 
0.1%
file_000000000004473 1
 
0.1%
file_000000000004472 1
 
0.1%
file_000000000004471 1
 
0.1%
file_000000000004470 1
 
0.1%
file_000000000004462 1
 
0.1%
file_000000000004461 1
 
0.1%
file_000000000004460 1
 
0.1%
file_000000000004456 1
 
0.1%
Other values (1913) 1913
99.5%
2023-12-12T09:06:40.728209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22165
57.6%
F 1923
 
5.0%
I 1923
 
5.0%
L 1923
 
5.0%
E 1923
 
5.0%
_ 1923
 
5.0%
1 1212
 
3.2%
2 932
 
2.4%
4 874
 
2.3%
3 866
 
2.3%
Other values (5) 2796
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28845
75.0%
Uppercase Letter 7692
 
20.0%
Connector Punctuation 1923
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22165
76.8%
1 1212
 
4.2%
2 932
 
3.2%
4 874
 
3.0%
3 866
 
3.0%
5 796
 
2.8%
6 697
 
2.4%
7 484
 
1.7%
9 423
 
1.5%
8 396
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
F 1923
25.0%
I 1923
25.0%
L 1923
25.0%
E 1923
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1923
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30768
80.0%
Latin 7692
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22165
72.0%
_ 1923
 
6.2%
1 1212
 
3.9%
2 932
 
3.0%
4 874
 
2.8%
3 866
 
2.8%
5 796
 
2.6%
6 697
 
2.3%
7 484
 
1.6%
9 423
 
1.4%
Latin
ValueCountFrequency (%)
F 1923
25.0%
I 1923
25.0%
L 1923
25.0%
E 1923
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22165
57.6%
F 1923
 
5.0%
I 1923
 
5.0%
L 1923
 
5.0%
E 1923
 
5.0%
_ 1923
 
5.0%
1 1212
 
3.2%
2 932
 
2.4%
4 874
 
2.3%
3 866
 
2.3%
Other values (5) 2796
 
7.3%
Distinct731
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
Minimum2016-12-15 00:00:00
Maximum2023-08-08 00:00:00
2023-12-12T09:06:40.903373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:06:41.075475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct644
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
Minimum2023-12-12 01:00:00
Maximum2023-12-12 12:59:00
2023-12-12T09:06:41.594714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:06:41.740220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
True
1923 
ValueCountFrequency (%)
True 1923
100.0%
2023-12-12T09:06:41.869445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T09:06:39.985318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:06:40.105843image/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

첨부파일아이디(ATCH_FILE_ID)첨부파일생성일자(CREAT_DATE)첨부파일생성시간(CREAT_TIME)첨부파일사용여부(USE_AT)
0FILE_0000000000004312016-12-1511:09:00Y
1FILE_0000000000004412016-12-1505:09:00Y
2FILE_0000000000004422016-12-1505:51:00Y
3FILE_0000000000004502016-12-1609:54:00Y
4FILE_0000000000004512016-12-1610:48:00Y
5FILE_0000000000004522016-12-1610:50:00Y
6FILE_0000000000004702016-12-2005:37:00Y
7FILE_0000000000004802016-12-2011:05:00Y
8FILE_0000000000004812016-12-2011:05:00Y
9FILE_0000000000004822016-12-2011:06:00Y
첨부파일아이디(ATCH_FILE_ID)첨부파일생성일자(CREAT_DATE)첨부파일생성시간(CREAT_TIME)첨부파일사용여부(USE_AT)
1913FILE_0000000000067212023-07-0511:35:00Y
1914FILE_0000000000067302023-07-1703:16:00Y
1915FILE_0000000000067402023-07-2008:12:00Y
1916FILE_0000000000067502023-07-2603:43:00Y
1917FILE_0000000000067602023-07-2709:35:00Y
1918FILE_0000000000067612023-07-2709:44:00Y
1919FILE_0000000000067702023-07-2902:06:00Y
1920FILE_0000000000067802023-08-0101:35:00Y
1921FILE_0000000000067902023-08-0701:36:00Y
1922FILE_0000000000068002023-08-0807:10:00Y