Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory488.3 KiB
Average record size in memory50.0 B

Variable types

Categorical2
Numeric2
DateTime1

Dataset

Description지구별,주차장명,주차대수,이용시간,날짜
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21084/S/1/datasetView.do

Alerts

지구별 is highly overall correlated with 주차장명High correlation
주차장명 is highly overall correlated with 지구별High correlation
주차대수 is highly overall correlated with 이용시간High correlation
이용시간 is highly overall correlated with 주차대수High correlation

Reproduction

Analysis started2024-05-10 23:46:03.910598
Analysis finished2024-05-10 23:46:06.600452
Duration2.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지구별
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
PLT-008
1966 
PLT-005
1520 
PLT-007
1146 
PLT-004
1132 
PLT-006
861 
Other values (6)
3375 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPLT-005
2nd rowPLT-005
3rd rowPLT-008
4th rowPLT-008
5th rowPLT-006

Common Values

ValueCountFrequency (%)
PLT-008 1966
19.7%
PLT-005 1520
15.2%
PLT-007 1146
11.5%
PLT-004 1132
11.3%
PLT-006 861
8.6%
PLT-009 758
 
7.6%
PLT-003 753
 
7.5%
PLT-010 593
 
5.9%
PLT-011 505
 
5.1%
PLT-001 392
 
3.9%

Length

2024-05-10T23:46:06.926362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
plt-008 1966
19.7%
plt-005 1520
15.2%
plt-007 1146
11.5%
plt-004 1132
11.3%
plt-006 861
8.6%
plt-009 758
 
7.6%
plt-003 753
 
7.5%
plt-010 593
 
5.9%
plt-011 505
 
5.1%
plt-001 392
 
3.9%

주차장명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
여의도3주차장
 
428
여의도2주차장
 
414
이촌1주차장
 
408
뚝섬3주차장
 
406
망원2,3주차장
 
397
Other values (26)
7947 

Length

Max length12
Median length10
Mean length7.0977
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row뚝섬2주차장
2nd row뚝섬4주차장
3rd row여의도3주차장
4th row여의도4주차장
5th row광나루3주차장

Common Values

ValueCountFrequency (%)
여의도3주차장 428
 
4.3%
여의도2주차장 414
 
4.1%
이촌1주차장 408
 
4.1%
뚝섬3주차장 406
 
4.1%
망원2,3주차장 397
 
4.0%
반포2,3주차장 394
 
3.9%
양화1주차장 393
 
3.9%
여의도1주차장 393
 
3.9%
강서1주차장 392
 
3.9%
광나루1,2주차장 385
 
3.9%
Other values (21) 5990
59.9%

Length

2024-05-10T23:46:07.343164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여의도3주차장 428
 
4.3%
여의도2주차장 414
 
4.1%
이촌1주차장 408
 
4.1%
뚝섬3주차장 406
 
4.1%
망원2,3주차장 397
 
4.0%
반포2,3주차장 394
 
3.9%
양화1주차장 393
 
3.9%
여의도1주차장 393
 
3.9%
강서1주차장 392
 
3.9%
광나루1,2주차장 385
 
3.9%
Other values (21) 5990
59.9%

주차대수
Real number (ℝ)

HIGH CORRELATION 

Distinct2797
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean927.2507
Minimum1
Maximum7003
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:46:07.717546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile66
Q1255
median602
Q31267
95-th percentile2927.05
Maximum7003
Range7002
Interquartile range (IQR)1012

Descriptive statistics

Standard deviation961.92872
Coefficient of variation (CV)1.0373988
Kurtosis4.7503595
Mean927.2507
Median Absolute Deviation (MAD)399
Skewness1.964101
Sum9272507
Variance925306.87
MonotonicityNot monotonic
2024-05-10T23:46:08.042815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
211 25
 
0.2%
227 19
 
0.2%
214 19
 
0.2%
196 19
 
0.2%
58 18
 
0.2%
44 18
 
0.2%
218 18
 
0.2%
193 17
 
0.2%
62 17
 
0.2%
85 17
 
0.2%
Other values (2787) 9813
98.1%
ValueCountFrequency (%)
1 6
0.1%
2 3
< 0.1%
3 1
 
< 0.1%
4 3
< 0.1%
5 3
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 3
< 0.1%
10 2
 
< 0.1%
ValueCountFrequency (%)
7003 1
< 0.1%
6930 1
< 0.1%
6410 1
< 0.1%
6369 1
< 0.1%
6306 1
< 0.1%
6230 1
< 0.1%
6212 1
< 0.1%
6208 1
< 0.1%
6166 2
< 0.1%
5996 1
< 0.1%

이용시간
Real number (ℝ)

HIGH CORRELATION 

Distinct9682
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88483.592
Minimum0
Maximum624565
Zeros25
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:46:08.427814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4445.95
Q120507.75
median53028.5
Q3115667.75
95-th percentile325860.3
Maximum624565
Range624565
Interquartile range (IQR)95160

Descriptive statistics

Standard deviation99411.986
Coefficient of variation (CV)1.1235076
Kurtosis3.4949686
Mean88483.592
Median Absolute Deviation (MAD)37675.5
Skewness1.8900963
Sum8.8483592 × 108
Variance9.8827429 × 109
MonotonicityNot monotonic
2024-05-10T23:46:08.916780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25
 
0.2%
9623 3
 
< 0.1%
12933 3
 
< 0.1%
3768 3
 
< 0.1%
6476 3
 
< 0.1%
38171 3
 
< 0.1%
15612 3
 
< 0.1%
49081 3
 
< 0.1%
21384 2
 
< 0.1%
23116 2
 
< 0.1%
Other values (9672) 9950
99.5%
ValueCountFrequency (%)
0 25
0.2%
1 1
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
11 1
 
< 0.1%
13 1
 
< 0.1%
14 2
 
< 0.1%
16 1
 
< 0.1%
ValueCountFrequency (%)
624565 1
< 0.1%
607820 1
< 0.1%
594896 1
< 0.1%
582201 1
< 0.1%
581625 1
< 0.1%
566263 1
< 0.1%
558190 1
< 0.1%
552268 1
< 0.1%
550013 1
< 0.1%
548063 1
< 0.1%

날짜
Date

Distinct1567
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-01-16 00:00:00
Maximum2024-05-09 00:00:00
2024-05-10T23:46:09.399901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:46:09.966239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-05-10T23:46:05.140784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:46:04.550353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:46:05.459925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:46:04.836015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T23:46:10.316085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지구별주차장명주차대수이용시간
지구별1.0001.0000.5000.480
주차장명1.0001.0000.7380.758
주차대수0.5000.7381.0000.791
이용시간0.4800.7580.7911.000
2024-05-10T23:46:10.702306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지구별주차장명
지구별1.0000.999
주차장명0.9991.000
2024-05-10T23:46:11.209447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차대수이용시간지구별주차장명
주차대수1.0000.8660.2390.365
이용시간0.8661.0000.2270.384
지구별0.2390.2271.0000.999
주차장명0.3650.3840.9991.000

Missing values

2024-05-10T23:46:05.985444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T23:46:06.446771image/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

지구별주차장명주차대수이용시간날짜
10197PLT-005뚝섬2주차장842934872023/05/06
17130PLT-005뚝섬4주차장874725942022/08/14
34081PLT-008여의도3주차장737166562020/10/02
3869PLT-008여의도4주차장3223632023/12/23
34568PLT-006광나루3주차장429322312020/09/12
10959PLT-005뚝섬2주차장12651294962023/04/08
1365PLT-003망원2,3주차장641548502024/03/22
37967PLT-009반포1주차장1038719842020/04/19
7316PLT-005뚝섬3주차장311249122023/08/21
20206PLT-008여의도2주차장16212079132022/04/12
지구별주차장명주차대수이용시간날짜
38153PLT-005뚝섬4주차장985939142020/04/12
17025PLT-008여의도3주차장9223196602022/08/19
24265PLT-004이촌2주차장507415272021/10/31
1976PLT-008여의도1주차장17492597302024/02/29
18019PLT-007양화3,4,5주차장875442462022/07/08
7036PLT-010잠원1주차장641457872023/08/31
21823PLT-004이촌3,4주차장7061652022/02/06
16939PLT-005뚝섬3주차장376294992022/08/23
14964PLT-009반포1주차장718261202022/11/11
22481PLT-010잠원1-6주차장17752118162022/01/10