Overview

Dataset statistics

Number of variables5
Number of observations2355
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory94.4 KiB
Average record size in memory41.1 B

Variable types

Categorical3
Text1
DateTime1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15976/S/1/datasetView.do

Alerts

기관 명 has constant value ""Constant
모델명 has constant value ""Constant

Reproduction

Analysis started2024-05-17 22:43:00.881259
Analysis finished2024-05-17 22:43:01.631710
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관 명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
양천구
2355 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
양천구 2355
100.0%

Length

2024-05-18T07:43:01.894924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:43:02.249240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양천구 2355
100.0%

모델명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
G15v2
2355 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowG15v2
2nd rowG15v2
3rd rowG15v2
4th rowG15v2
5th rowG15v2

Common Values

ValueCountFrequency (%)
G15v2 2355
100.0%

Length

2024-05-18T07:43:02.561093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:43:02.878085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g15v2 2355
100.0%

시리얼
Text

Distinct123
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
2024-05-18T07:43:03.555714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters14130
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.3%

Sample

1st rowyc0594
2nd rowyc0343
3rd rowyc0343
4th rowyc0594
5th rowyc0380
ValueCountFrequency (%)
yc0554 184
 
7.8%
yc0559 155
 
6.6%
yc0545 99
 
4.2%
yc0344 89
 
3.8%
yc0612 77
 
3.3%
yc0574 58
 
2.5%
yc0567 56
 
2.4%
yc0347 54
 
2.3%
yc0384 52
 
2.2%
yc0564 49
 
2.1%
Other values (113) 1482
62.9%
2024-05-18T07:43:05.159048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2768
19.6%
y 2355
16.7%
c 2355
16.7%
5 1991
14.1%
3 1283
9.1%
4 896
 
6.3%
6 575
 
4.1%
7 529
 
3.7%
9 462
 
3.3%
1 352
 
2.5%
Other values (2) 564
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9420
66.7%
Lowercase Letter 4710
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2768
29.4%
5 1991
21.1%
3 1283
13.6%
4 896
 
9.5%
6 575
 
6.1%
7 529
 
5.6%
9 462
 
4.9%
1 352
 
3.7%
8 313
 
3.3%
2 251
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
y 2355
50.0%
c 2355
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9420
66.7%
Latin 4710
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2768
29.4%
5 1991
21.1%
3 1283
13.6%
4 896
 
9.5%
6 575
 
6.1%
7 529
 
5.6%
9 462
 
4.9%
1 352
 
3.7%
8 313
 
3.3%
2 251
 
2.7%
Latin
ValueCountFrequency (%)
y 2355
50.0%
c 2355
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2768
19.6%
y 2355
16.7%
c 2355
16.7%
5 1991
14.1%
3 1283
9.1%
4 896
 
6.3%
6 575
 
4.1%
7 529
 
3.7%
9 462
 
3.3%
1 352
 
2.5%
Other values (2) 564
 
4.0%

주차유무
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
0
1281 
1
1074 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 1281
54.4%
1 1074
45.6%

Length

2024-05-18T07:43:05.799492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:43:06.306596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1281
54.4%
1 1074
45.6%

등록일자
Date

Distinct2345
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size18.5 KiB
Minimum2024-01-22 01:09:06
Maximum2024-01-28 22:37:24
2024-05-18T07:43:06.879312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:43:07.427567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Missing values

2024-05-18T07:43:01.127539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T07:43:01.521018image/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

기관 명모델명시리얼주차유무등록일자
0양천구G15v2yc059412024-01-22 01:09:06
1양천구G15v2yc034302024-01-22 04:05:13
2양천구G15v2yc034312024-01-22 05:27:02
3양천구G15v2yc059402024-01-22 05:49:38
4양천구G15v2yc038012024-01-22 05:57:38
5양천구G15v2yc038402024-01-22 06:01:40
6양천구G15v2yc056812024-01-22 06:12:33
7양천구G15v2yc054512024-01-22 06:35:42
8양천구G15v2yc054502024-01-22 06:36:03
9양천구G15v2yc036412024-01-22 06:43:42
기관 명모델명시리얼주차유무등록일자
2345양천구G15v2yc059002024-01-28 21:55:50
2346양천구G15v2yc061212024-01-28 21:58:55
2347양천구G15v2yc061202024-01-28 21:59:15
2348양천구G15v2yc057402024-01-28 22:07:39
2349양천구G15v2yc056412024-01-28 22:10:49
2350양천구G15v2yc056402024-01-28 22:12:36
2351양천구G15v2yc055812024-01-28 22:13:17
2352양천구G15v2yc055802024-01-28 22:13:37
2353양천구G15v2yc059412024-01-28 22:29:45
2354양천구G15v2yc059702024-01-28 22:37:24