Overview

Dataset statistics

Number of variables5
Number of observations2723
Missing cells0
Missing cells (%)0.0%
Duplicate rows383
Duplicate rows (%)14.1%
Total size in memory109.2 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 383 (14.1%) duplicate rowsDuplicates

Reproduction

Analysis started2024-05-17 22:42:38.504541
Analysis finished2024-05-17 22:42:39.717907
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관 명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.4 KiB
양천구
2723 

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 2723
100.0%

Length

2024-05-18T07:42:39.900596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:40.162134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양천구 2723
100.0%

모델명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.4 KiB
G15v2
2723 

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 2723
100.0%

Length

2024-05-18T07:42:40.531833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:40.954262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g15v2 2723
100.0%

시리얼
Text

Distinct118
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size21.4 KiB
2024-05-18T07:42:41.559203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters16338
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

Unique5 ?
Unique (%)0.2%

Sample

1st rowyc0613
2nd rowyc0613
3rd rowyc0602
4th rowyc0602
5th rowyc0545
ValueCountFrequency (%)
yc0559 181
 
6.6%
yc0545 150
 
5.5%
yc0554 134
 
4.9%
yc0347 107
 
3.9%
yc0344 103
 
3.8%
yc0612 85
 
3.1%
yc0567 77
 
2.8%
yc0574 73
 
2.7%
yc0331 72
 
2.6%
yc0386 61
 
2.2%
Other values (108) 1680
61.7%
2024-05-18T07:42:42.644897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3154
19.3%
y 2723
16.7%
c 2723
16.7%
5 2175
13.3%
3 1703
10.4%
4 1031
 
6.3%
6 665
 
4.1%
7 596
 
3.6%
9 490
 
3.0%
1 434
 
2.7%
Other values (2) 644
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10892
66.7%
Lowercase Letter 5446
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3154
29.0%
5 2175
20.0%
3 1703
15.6%
4 1031
 
9.5%
6 665
 
6.1%
7 596
 
5.5%
9 490
 
4.5%
1 434
 
4.0%
8 365
 
3.4%
2 279
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
y 2723
50.0%
c 2723
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10892
66.7%
Latin 5446
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3154
29.0%
5 2175
20.0%
3 1703
15.6%
4 1031
 
9.5%
6 665
 
6.1%
7 596
 
5.5%
9 490
 
4.5%
1 434
 
4.0%
8 365
 
3.4%
2 279
 
2.6%
Latin
ValueCountFrequency (%)
y 2723
50.0%
c 2723
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16338
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3154
19.3%
y 2723
16.7%
c 2723
16.7%
5 2175
13.3%
3 1703
10.4%
4 1031
 
6.3%
6 665
 
4.1%
7 596
 
3.6%
9 490
 
3.0%
1 434
 
2.7%
Other values (2) 644
 
3.9%

주차유무
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.4 KiB
0
1448 
1
1275 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1448
53.2%
1 1275
46.8%

Length

2024-05-18T07:42:43.091033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:42:43.425742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1448
53.2%
1 1275
46.8%

등록일자
Date

Distinct2331
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Memory size21.4 KiB
Minimum2024-01-15 01:48:21
Maximum2024-01-21 22:41:50
2024-05-18T07:42:43.885832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:42:44.293217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Missing values

2024-05-18T07:42:39.143177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T07:42:39.552475image/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
0양천구G15v2yc061312024-01-15 01:48:21
1양천구G15v2yc061312024-01-15 01:48:21
2양천구G15v2yc060212024-01-15 04:47:37
3양천구G15v2yc060212024-01-15 04:47:37
4양천구G15v2yc054512024-01-15 05:24:48
5양천구G15v2yc054512024-01-15 05:24:48
6양천구G15v2yc054502024-01-15 05:25:07
7양천구G15v2yc054502024-01-15 05:25:07
8양천구G15v2yc034802024-01-15 05:35:35
9양천구G15v2yc034802024-01-15 05:35:35
기관 명모델명시리얼주차유무등록일자
2713양천구G15v2yc060102024-01-21 20:57:58
2714양천구G15v2yc061112024-01-21 21:06:18
2715양천구G15v2yc034412024-01-21 21:18:52
2716양천구G15v2yc038612024-01-21 21:21:26
2717양천구G15v2yc060012024-01-21 21:29:03
2718양천구G15v2yc054012024-01-21 21:40:16
2719양천구G15v2yc054002024-01-21 21:40:41
2720양천구G15v2yc034402024-01-21 21:51:29
2721양천구G15v2yc030202024-01-21 22:25:29
2722양천구G15v2yc033802024-01-21 22:41:50

Duplicate rows

Most frequently occurring

기관 명모델명시리얼주차유무등록일자# duplicates
0양천구G15v2yc030202024-01-15 12:24:572
1양천구G15v2yc030202024-01-15 16:23:102
2양천구G15v2yc030202024-01-15 16:56:082
3양천구G15v2yc030202024-01-15 22:33:272
4양천구G15v2yc030212024-01-15 07:03:522
5양천구G15v2yc030212024-01-15 16:56:562
6양천구G15v2yc030302024-01-15 07:30:142
7양천구G15v2yc030302024-01-15 12:09:462
8양천구G15v2yc030312024-01-15 07:29:512
9양천구G15v2yc030312024-01-15 12:09:182