Overview

Dataset statistics

Number of variables5
Number of observations2848
Missing cells0
Missing cells (%)0.0%
Duplicate rows449
Duplicate rows (%)15.8%
Total size in memory114.2 KiB
Average record size in memory41.0 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
Dataset has 449 (15.8%) duplicate rowsDuplicates

Reproduction

Analysis started2024-05-17 22:42:46.303185
Analysis finished2024-05-17 22:42:47.060147
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관 명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.4 KiB
양천구
2848 

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 2848
100.0%

Length

2024-05-18T07:42:47.239417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:47.553559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양천구 2848
100.0%

모델명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.4 KiB
G15v2
2848 

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 2848
100.0%

Length

2024-05-18T07:42:47.946976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:48.246401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g15v2 2848
100.0%

시리얼
Text

Distinct122
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size22.4 KiB
2024-05-18T07:42:49.037819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters17088
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

Unique2 ?
Unique (%)0.1%

Sample

1st rowyc0380
2nd rowyc0597
3rd rowyc0363
4th rowyc0381
5th rowyc0381
ValueCountFrequency (%)
yc0545 139
 
4.9%
yc0559 129
 
4.5%
yc0554 128
 
4.5%
yc0344 124
 
4.4%
yc0573 94
 
3.3%
yc0347 90
 
3.2%
yc0612 76
 
2.7%
yc0568 69
 
2.4%
yc0331 66
 
2.3%
yc0373 63
 
2.2%
Other values (112) 1870
65.7%
2024-05-18T07:42:50.477385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3296
19.3%
y 2848
16.7%
c 2848
16.7%
5 2168
12.7%
3 1854
10.8%
4 1011
 
5.9%
6 754
 
4.4%
7 671
 
3.9%
9 470
 
2.8%
1 431
 
2.5%
Other values (2) 737
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11392
66.7%
Lowercase Letter 5696
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3296
28.9%
5 2168
19.0%
3 1854
16.3%
4 1011
 
8.9%
6 754
 
6.6%
7 671
 
5.9%
9 470
 
4.1%
1 431
 
3.8%
8 411
 
3.6%
2 326
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
y 2848
50.0%
c 2848
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11392
66.7%
Latin 5696
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3296
28.9%
5 2168
19.0%
3 1854
16.3%
4 1011
 
8.9%
6 754
 
6.6%
7 671
 
5.9%
9 470
 
4.1%
1 431
 
3.8%
8 411
 
3.6%
2 326
 
2.9%
Latin
ValueCountFrequency (%)
y 2848
50.0%
c 2848
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17088
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3296
19.3%
y 2848
16.7%
c 2848
16.7%
5 2168
12.7%
3 1854
10.8%
4 1011
 
5.9%
6 754
 
4.4%
7 671
 
3.9%
9 470
 
2.8%
1 431
 
2.5%
Other values (2) 737
 
4.3%

주차유무
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.4 KiB
0
1485 
1
1363 

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 1485
52.1%
1 1363
47.9%

Length

2024-05-18T07:42:51.020802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:51.404744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1485
52.1%
1 1363
47.9%

등록일자
Date

Distinct2391
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size22.4 KiB
Minimum2024-01-08 05:53:36
Maximum2024-01-14 23:54:21
2024-05-18T07:42:51.761472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:42:52.345645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Missing values

2024-05-18T07:42:46.670198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T07:42:46.950312image/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
0양천구G15v2yc038012024-01-08 05:53:36
1양천구G15v2yc059702024-01-08 05:58:49
2양천구G15v2yc036302024-01-08 06:03:39
3양천구G15v2yc038112024-01-08 06:36:57
4양천구G15v2yc038102024-01-08 06:37:21
5양천구G15v2yc038112024-01-08 06:37:58
6양천구G15v2yc054512024-01-08 06:45:21
7양천구G15v2yc054502024-01-08 06:45:44
8양천구G15v2yc054512024-01-08 06:46:19
9양천구G15v2yc060002024-01-08 06:47:57
기관 명모델명시리얼주차유무등록일자
2838양천구G15v2yc038602024-01-14 20:59:06
2839양천구G15v2yc038612024-01-14 21:02:46
2840양천구G15v2yc058812024-01-14 22:15:45
2841양천구G15v2yc059412024-01-14 22:44:32
2842양천구G15v2yc059402024-01-14 22:44:55
2843양천구G15v2yc059412024-01-14 22:45:33
2844양천구G15v2yc061302024-01-14 22:56:34
2845양천구G15v2yc061112024-01-14 23:32:21
2846양천구G15v2yc056412024-01-14 23:54:00
2847양천구G15v2yc056402024-01-14 23:54:21

Duplicate rows

Most frequently occurring

기관 명모델명시리얼주차유무등록일자# duplicates
0양천구G15v2yc030202024-01-13 08:54:392
1양천구G15v2yc030202024-01-13 17:36:242
2양천구G15v2yc030212024-01-13 08:54:182
3양천구G15v2yc030212024-01-13 14:19:562
4양천구G15v2yc030302024-01-13 09:36:082
5양천구G15v2yc030302024-01-13 16:14:132
6양천구G15v2yc030302024-01-13 16:59:242
7양천구G15v2yc030302024-01-13 22:18:332
8양천구G15v2yc030312024-01-13 09:20:352
9양천구G15v2yc030312024-01-13 16:58:522