Overview

Dataset statistics

Number of variables5
Number of observations733
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.5 KiB
Average record size in memory41.2 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 22:42:29.556571
Analysis finished2024-05-17 22:42:30.169389
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관 명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
양천구
733 

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 733
100.0%

Length

2024-05-18T07:42:30.364894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:30.678488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양천구 733
100.0%

모델명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
G15v2
733 

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 733
100.0%

Length

2024-05-18T07:42:31.000053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:31.432184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g15v2 733
100.0%

시리얼
Text

Distinct101
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
2024-05-18T07:42:32.306209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters4398
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

Unique10 ?
Unique (%)1.4%

Sample

1st rowyc0589
2nd rowyc0581
3rd rowyc0384
4th rowyc0613
5th rowyc0361
ValueCountFrequency (%)
yc0545 53
 
7.2%
yc0559 36
 
4.9%
yc0554 32
 
4.4%
yc0347 30
 
4.1%
yc0331 27
 
3.7%
yc0344 26
 
3.5%
yc0612 26
 
3.5%
yc0574 22
 
3.0%
yc0567 19
 
2.6%
yc0576 18
 
2.5%
Other values (91) 444
60.6%
2024-05-18T07:42:33.822266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 824
18.7%
y 733
16.7%
c 733
16.7%
5 596
13.6%
3 462
10.5%
4 284
 
6.5%
6 194
 
4.4%
7 152
 
3.5%
1 135
 
3.1%
9 113
 
2.6%
Other values (2) 172
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2932
66.7%
Lowercase Letter 1466
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 824
28.1%
5 596
20.3%
3 462
15.8%
4 284
 
9.7%
6 194
 
6.6%
7 152
 
5.2%
1 135
 
4.6%
9 113
 
3.9%
8 93
 
3.2%
2 79
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
y 733
50.0%
c 733
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2932
66.7%
Latin 1466
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 824
28.1%
5 596
20.3%
3 462
15.8%
4 284
 
9.7%
6 194
 
6.6%
7 152
 
5.2%
1 135
 
4.6%
9 113
 
3.9%
8 93
 
3.2%
2 79
 
2.7%
Latin
ValueCountFrequency (%)
y 733
50.0%
c 733
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4398
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 824
18.7%
y 733
16.7%
c 733
16.7%
5 596
13.6%
3 462
10.5%
4 284
 
6.5%
6 194
 
4.4%
7 152
 
3.5%
1 135
 
3.1%
9 113
 
2.6%
Other values (2) 172
 
3.9%

주차유무
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
0
385 
1
348 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 385
52.5%
1 348
47.5%

Length

2024-05-18T07:42:34.482222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:34.881075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 385
52.5%
1 348
47.5%

등록일자
Date

Distinct729
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Minimum2023-12-25 00:21:37
Maximum2023-12-27 08:57:54
2024-05-18T07:42:35.532410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:42:36.109592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Missing values

2024-05-18T07:42:29.788530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T07:42:30.057514image/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
0양천구G15v2yc058912023-12-25 00:21:37
1양천구G15v2yc058102023-12-25 00:54:49
2양천구G15v2yc038412023-12-25 02:13:25
3양천구G15v2yc061312023-12-25 02:54:05
4양천구G15v2yc036102023-12-25 04:43:12
5양천구G15v2yc036812023-12-25 05:05:30
6양천구G15v2yc036112023-12-25 05:08:10
7양천구G15v2yc034302023-12-25 05:09:27
8양천구G15v2yc036802023-12-25 05:10:52
9양천구G15v2yc056312023-12-25 05:56:40
기관 명모델명시리얼주차유무등록일자
723양천구G15v2yc033902023-12-27 08:13:59
724양천구G15v2yc031912023-12-27 08:29:26
725양천구G15v2yc054512023-12-27 08:36:19
726양천구G15v2yc054502023-12-27 08:36:42
727양천구G15v2yc038002023-12-27 08:46:48
728양천구G15v2yc033612023-12-27 08:49:59
729양천구G15v2yc054512023-12-27 08:56:15
730양천구G15v2yc054502023-12-27 08:56:39
731양천구G15v2yc054512023-12-27 08:57:25
732양천구G15v2yc054502023-12-27 08:57:54