Overview

Dataset statistics

Number of variables7
Number of observations570
Missing cells1140
Missing cells (%)28.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.3 KiB
Average record size in memory63.5 B

Variable types

Text1
Categorical2
Numeric1
DateTime1
Unsupported2

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-20462/S/1/datasetView.do

Alerts

주차여부 is highly imbalanced (98.1%)Imbalance
레이더센서상태 has 570 (100.0%) missing valuesMissing
등록일시 has 570 (100.0%) missing valuesMissing
배터리용량 has unique valuesUnique
레이더센서상태 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등록일시 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시리얼 has 21 (3.7%) zerosZeros

Reproduction

Analysis started2023-12-11 09:01:17.137562
Analysis finished2023-12-11 09:01:17.605686
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관 명
Text

Distinct80
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-11T18:01:17.752378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters9120
Distinct characters16
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 (%)0.4%

Sample

1st row88571dfffe0e7d00
2nd row88571dfffe0e7c2d
3rd row88571dfffe0e7af4
4th row88571dfffe0e7b75
5th row88571dfffe0e7af8
ValueCountFrequency (%)
88571dfffe0e7d68 10
 
1.8%
88571dfffe0e7c7b 10
 
1.8%
88571dfffe0e7c2d 9
 
1.6%
88571dfffe0e7ab7 9
 
1.6%
88571dfffe0e7d55 9
 
1.6%
88571dfffe0e7d0d 9
 
1.6%
88571dfffe0e7a31 9
 
1.6%
88571dfffe0e7ab3 9
 
1.6%
88571dfffe0e7b7c 9
 
1.6%
88571dfffe0e7aed 9
 
1.6%
Other values (70) 478
83.9%
2023-12-11T18:01:18.106739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
f 1806
19.8%
8 1254
13.8%
7 1211
13.3%
e 1176
12.9%
d 723
7.9%
0 665
 
7.3%
5 645
 
7.1%
1 637
 
7.0%
b 246
 
2.7%
a 220
 
2.4%
Other values (6) 537
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4782
52.4%
Lowercase Letter 4338
47.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 1254
26.2%
7 1211
25.3%
0 665
13.9%
5 645
13.5%
1 637
13.3%
2 111
 
2.3%
3 103
 
2.2%
6 78
 
1.6%
4 57
 
1.2%
9 21
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
f 1806
41.6%
e 1176
27.1%
d 723
16.7%
b 246
 
5.7%
a 220
 
5.1%
c 167
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Common 4782
52.4%
Latin 4338
47.6%

Most frequent character per script

Common
ValueCountFrequency (%)
8 1254
26.2%
7 1211
25.3%
0 665
13.9%
5 645
13.5%
1 637
13.3%
2 111
 
2.3%
3 103
 
2.2%
6 78
 
1.6%
4 57
 
1.2%
9 21
 
0.4%
Latin
ValueCountFrequency (%)
f 1806
41.6%
e 1176
27.1%
d 723
16.7%
b 246
 
5.7%
a 220
 
5.1%
c 167
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
f 1806
19.8%
8 1254
13.8%
7 1211
13.3%
e 1176
12.9%
d 723
7.9%
0 665
 
7.3%
5 645
 
7.1%
1 637
 
7.0%
b 246
 
2.7%
a 220
 
2.4%
Other values (6) 537
 
5.9%

모델명
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
3031
420 
3032
129 
3030
 
21

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3031
2nd row3031
3rd row3031
4th row3031
5th row3032

Common Values

ValueCountFrequency (%)
3031 420
73.7%
3032 129
 
22.6%
3030 21
 
3.7%

Length

2023-12-11T18:01:18.264293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:01:18.376343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3031 420
73.7%
3032 129
 
22.6%
3030 21
 
3.7%

시리얼
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.107018
Minimum0
Maximum100
Zeros21
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2023-12-11T18:01:18.476906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile97
Q1100
median100
Q3100
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.878879
Coefficient of variation (CV)0.19643601
Kurtosis22.048534
Mean96.107018
Median Absolute Deviation (MAD)0
Skewness-4.8861179
Sum54781
Variance356.41208
MonotonicityNot monotonic
2023-12-11T18:01:18.604868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
100 507
88.9%
0 21
 
3.7%
99 15
 
2.6%
98 13
 
2.3%
97 9
 
1.6%
96 4
 
0.7%
65 1
 
0.2%
ValueCountFrequency (%)
0 21
 
3.7%
65 1
 
0.2%
96 4
 
0.7%
97 9
 
1.6%
98 13
 
2.3%
99 15
 
2.6%
100 507
88.9%
ValueCountFrequency (%)
100 507
88.9%
99 15
 
2.6%
98 13
 
2.3%
97 9
 
1.6%
96 4
 
0.7%
65 1
 
0.2%
0 21
 
3.7%

주차여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
0
569 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 569
99.8%
1 1
 
0.2%

Length

2023-12-11T18:01:18.751151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:01:18.916594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 569
99.8%
1 1
 
0.2%

배터리용량
Date

UNIQUE 

Distinct570
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
Minimum2023-01-16 00:04:37
Maximum2023-01-22 23:30:58
2023-12-11T18:01:19.076557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:19.525878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

레이더센서상태
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing570
Missing (%)100.0%
Memory size6.4 KiB

등록일시
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing570
Missing (%)100.0%
Memory size6.4 KiB

Interactions

2023-12-11T18:01:17.299292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:01:19.634844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관 명모델명시리얼주차여부
기관 명1.0000.9320.9981.000
모델명0.9321.0000.9430.030
시리얼0.9980.9431.0001.000
주차여부1.0000.0301.0001.000
2023-12-11T18:01:19.739061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차여부모델명
주차여부1.0000.050
모델명0.0501.000

Missing values

2023-12-11T18:01:17.437731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:01:17.558091image/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 명모델명시리얼주차여부배터리용량레이더센서상태등록일시
성동구SKTX-PKS-00288571dfffe0e7d00303110002023-01-16 00:04:37<NA><NA>
SKTX-PKS-00288571dfffe0e7c2d303110002023-01-16 01:28:45<NA><NA>
SKTX-PKS-00288571dfffe0e7af4303110002023-01-16 02:41:31<NA><NA>
SKTX-PKS-00288571dfffe0e7b75303110002023-01-16 03:05:18<NA><NA>
SKTX-PKS-00288571dfffe0e7af8303210002023-01-16 03:33:07<NA><NA>
SKTX-PKS-00288571dfffe0e7b2a303110002023-01-16 03:57:17<NA><NA>
SKTX-PKS-00288571dfffe0e7b52303110002023-01-16 04:25:38<NA><NA>
SKTX-PKS-00288571dfffe0e7d2a303110002023-01-16 04:41:27<NA><NA>
SKTX-PKS-00288571dfffe0e7d55303110002023-01-16 05:00:56<NA><NA>
SKTX-PKS-00288571dfffe0e7ab4303110002023-01-16 05:01:27<NA><NA>
기관 명모델명시리얼주차여부배터리용량레이더센서상태등록일시
성동구SKTX-PKS-00288571dfffe0e7d0f303110002023-01-22 20:07:51<NA><NA>
SKTX-PKS-00288571dfffe0e7b6d303110002023-01-22 20:34:54<NA><NA>
SKTX-PKS-00288571dfffe0e7c03303110002023-01-22 20:36:47<NA><NA>
SKTX-PKS-00288571dfffe0e7d0f303110002023-01-22 21:08:26<NA><NA>
SKTX-PKS-00288571dfffe0e7b8f303110002023-01-22 21:33:22<NA><NA>
SKTX-PKS-00288571dfffe0e7cf0303110002023-01-22 21:41:35<NA><NA>
SKTX-PKS-00288571dfffe0e7b53303210002023-01-22 22:51:33<NA><NA>
SKTX-PKS-00288571dfffe0e7a4e303210002023-01-22 23:01:57<NA><NA>
SKTX-PKS-00288571dfffe0e7c62303110002023-01-22 23:05:44<NA><NA>
SKTX-PKS-00288571dfffe0e7ad4303110002023-01-22 23:30:58<NA><NA>