Overview

Dataset statistics

Number of variables5
Number of observations941
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.8 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 22:43:10.307753
Analysis finished2024-05-17 22:43:11.323194
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관 명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
양천구
941 

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 941
100.0%

Length

2024-05-18T07:43:11.652942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:43:11.991513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양천구 941
100.0%

모델명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
G15v2
941 

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 941
100.0%

Length

2024-05-18T07:43:12.281844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:43:12.630529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g15v2 941
100.0%

시리얼
Text

Distinct92
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2024-05-18T07:43:13.263390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters5646
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

Unique6 ?
Unique (%)0.6%

Sample

1st rowyc0602
2nd rowyc0350
3rd rowyc0594
4th rowyc0380
5th rowyc0600
ValueCountFrequency (%)
yc0554 93
 
9.9%
yc0559 70
 
7.4%
yc0341 37
 
3.9%
yc0574 35
 
3.7%
yc0344 34
 
3.6%
yc0599 28
 
3.0%
yc0381 25
 
2.7%
yc0576 21
 
2.2%
yc0302 21
 
2.2%
yc0306 19
 
2.0%
Other values (82) 558
59.3%
2024-05-18T07:43:14.454407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1133
20.1%
y 941
16.7%
c 941
16.7%
5 751
13.3%
3 574
10.2%
4 333
 
5.9%
6 203
 
3.6%
9 199
 
3.5%
7 189
 
3.3%
1 178
 
3.2%
Other values (2) 204
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3764
66.7%
Lowercase Letter 1882
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1133
30.1%
5 751
20.0%
3 574
15.2%
4 333
 
8.8%
6 203
 
5.4%
9 199
 
5.3%
7 189
 
5.0%
1 178
 
4.7%
8 122
 
3.2%
2 82
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
y 941
50.0%
c 941
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3764
66.7%
Latin 1882
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1133
30.1%
5 751
20.0%
3 574
15.2%
4 333
 
8.8%
6 203
 
5.4%
9 199
 
5.3%
7 189
 
5.0%
1 178
 
4.7%
8 122
 
3.2%
2 82
 
2.2%
Latin
ValueCountFrequency (%)
y 941
50.0%
c 941
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5646
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1133
20.1%
y 941
16.7%
c 941
16.7%
5 751
13.3%
3 574
10.2%
4 333
 
5.9%
6 203
 
3.6%
9 199
 
3.5%
7 189
 
3.3%
1 178
 
3.2%
Other values (2) 204
 
3.6%

주차유무
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
0
535 
1
406 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 535
56.9%
1 406
43.1%

Length

2024-05-18T07:43:14.880387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:43:15.235213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 535
56.9%
1 406
43.1%

등록일자
Date

Distinct936
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
Minimum2024-02-05 01:08:18
Maximum2024-02-07 22:43:33
2024-05-18T07:43:15.619651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:43:16.163810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Correlations

2024-05-18T07:43:16.441315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시리얼주차유무
시리얼1.0000.000
주차유무0.0001.000

Missing values

2024-05-18T07:43:10.663289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T07:43:11.134271image/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
0양천구G15v2yc060212024-02-05 01:08:18
1양천구G15v2yc035002024-02-05 05:30:13
2양천구G15v2yc059402024-02-05 05:46:28
3양천구G15v2yc038012024-02-05 05:55:31
4양천구G15v2yc060002024-02-05 06:16:22
5양천구G15v2yc035502024-02-05 06:21:39
6양천구G15v2yc036502024-02-05 06:49:01
7양천구G15v2yc038112024-02-05 06:52:16
8양천구G15v2yc038002024-02-05 06:58:55
9양천구G15v2yc055012024-02-05 06:59:41
기관 명모델명시리얼주차유무등록일자
931양천구G15v2yc034402024-02-07 21:40:44
932양천구G15v2yc038112024-02-07 21:47:33
933양천구G15v2yc038102024-02-07 21:47:53
934양천구G15v2yc061212024-02-07 21:48:29
935양천구G15v2yc061202024-02-07 21:48:50
936양천구G15v2yc030202024-02-07 22:08:26
937양천구G15v2yc060012024-02-07 22:38:54
938양천구G15v2yc060002024-02-07 22:39:24
939양천구G15v2yc033802024-02-07 22:39:57
940양천구G15v2yc031902024-02-07 22:43:33