Overview

Dataset statistics

Number of variables5
Number of observations1387
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory57.0 KiB
Average record size in memory42.1 B

Variable types

Categorical2
Numeric2
DateTime1

Dataset

Description지구별,주차장명,주차대수,이용시간,날짜
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21085/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 started2024-05-11 04:54:25.999963
Analysis finished2024-05-11 04:54:27.985408
Duration1.99 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지구별
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size11.0 KiB
PLT-008
265 
PLT-005
212 
PLT-007
160 
PLT-004
159 
PLT-006
122 
Other values (6)
469 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPLT-008
2nd rowPLT-010
3rd rowPLT-007
4th rowPLT-008
5th rowPLT-004

Common Values

ValueCountFrequency (%)
PLT-008 265
19.1%
PLT-005 212
15.3%
PLT-007 160
11.5%
PLT-004 159
11.5%
PLT-006 122
8.8%
PLT-009 106
 
7.6%
PLT-003 106
 
7.6%
PLT-010 79
 
5.7%
PLT-011 73
 
5.3%
PLT-001 53
 
3.8%

Length

2024-05-11T04:54:28.203170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
plt-008 265
19.1%
plt-005 212
15.3%
plt-007 160
11.5%
plt-004 159
11.5%
plt-006 122
8.8%
plt-009 106
 
7.6%
plt-003 106
 
7.6%
plt-010 79
 
5.7%
plt-011 73
 
5.3%
plt-001 53
 
3.8%

주차장명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size11.0 KiB
여의도1주차장
 
53
뚝섬2주차장
 
53
양화1주차장
 
53
이촌2주차장
 
53
반포2,3주차장
 
53
Other values (26)
1122 

Length

Max length12
Median length10
Mean length7.1009373
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여의도1주차장
2nd row잠원1주차장
3rd row양화1주차장
4th row여의도5주차장
5th row이촌2주차장

Common Values

ValueCountFrequency (%)
여의도1주차장 53
 
3.8%
뚝섬2주차장 53
 
3.8%
양화1주차장 53
 
3.8%
이촌2주차장 53
 
3.8%
반포2,3주차장 53
 
3.8%
이촌1주차장 53
 
3.8%
반포1주차장 53
 
3.8%
망원1주차장 53
 
3.8%
여의도3주차장 53
 
3.8%
여의도5주차장 53
 
3.8%
Other values (21) 857
61.8%

Length

2024-05-11T04:54:28.690876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여의도1주차장 53
 
3.8%
뚝섬1주차장 53
 
3.8%
강서1주차장 53
 
3.8%
양화2주차장 53
 
3.8%
광나루1,2주차장 53
 
3.8%
이촌3,4주차장 53
 
3.8%
뚝섬3주차장 53
 
3.8%
뚝섬2주차장 53
 
3.8%
뚝섬4주차장 53
 
3.8%
여의도4주차장 53
 
3.8%
Other values (21) 857
61.8%

주차대수
Real number (ℝ)

HIGH CORRELATION 

Distinct1371
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26670.729
Minimum1
Maximum125342
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.3 KiB
2024-05-11T04:54:29.091697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2321.9
Q17929
median18405
Q335190
95-th percentile83788.3
Maximum125342
Range125341
Interquartile range (IQR)27261

Descriptive statistics

Standard deviation25806.196
Coefficient of variation (CV)0.96758496
Kurtosis1.9893817
Mean26670.729
Median Absolute Deviation (MAD)12039
Skewness1.5460741
Sum36992301
Variance6.6595977 × 108
MonotonicityNot monotonic
2024-05-11T04:54:29.555963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2
 
0.1%
13651 2
 
0.1%
7351 2
 
0.1%
8515 2
 
0.1%
7408 2
 
0.1%
36531 2
 
0.1%
11042 2
 
0.1%
14119 2
 
0.1%
5355 2
 
0.1%
1972 2
 
0.1%
Other values (1361) 1367
98.6%
ValueCountFrequency (%)
1 2
0.1%
285 1
0.1%
392 1
0.1%
509 1
0.1%
609 1
0.1%
652 1
0.1%
743 1
0.1%
754 1
0.1%
849 1
0.1%
871 1
0.1%
ValueCountFrequency (%)
125342 1
0.1%
125124 1
0.1%
123583 1
0.1%
120659 1
0.1%
118590 1
0.1%
118150 1
0.1%
117488 1
0.1%
116501 1
0.1%
116119 1
0.1%
115626 1
0.1%

이용시간
Real number (ℝ)

HIGH CORRELATION 

Distinct1386
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2522596.5
Minimum0
Maximum13022886
Zeros2
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size12.3 KiB
2024-05-11T04:54:30.049615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile176561
Q1739392
median1627170
Q33275763.5
95-th percentile8413626.7
Maximum13022886
Range13022886
Interquartile range (IQR)2536371.5

Descriptive statistics

Standard deviation2545235.2
Coefficient of variation (CV)1.0089744
Kurtosis2.0876091
Mean2522596.5
Median Absolute Deviation (MAD)1047637
Skewness1.6108704
Sum3.4988414 × 109
Variance6.4782223 × 1012
MonotonicityNot monotonic
2024-05-11T04:54:30.557919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2
 
0.1%
3316372 1
 
0.1%
1890853 1
 
0.1%
8493501 1
 
0.1%
159333 1
 
0.1%
2760774 1
 
0.1%
8158791 1
 
0.1%
580497 1
 
0.1%
727435 1
 
0.1%
2665854 1
 
0.1%
Other values (1376) 1376
99.2%
ValueCountFrequency (%)
0 2
0.1%
307 1
0.1%
588 1
0.1%
15597 1
0.1%
29319 1
0.1%
45056 1
0.1%
45724 1
0.1%
59718 1
0.1%
62272 1
0.1%
63230 1
0.1%
ValueCountFrequency (%)
13022886 1
0.1%
12382870 1
0.1%
12236390 1
0.1%
12215235 1
0.1%
11726491 1
0.1%
11474616 1
0.1%
11223561 1
0.1%
11114280 1
0.1%
11040713 1
0.1%
10969822 1
0.1%

날짜
Date

Distinct53
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size11.0 KiB
Minimum2020-01-01 00:00:00
Maximum2024-05-01 00:00:00
2024-05-11T04:54:30.960412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:54:31.441849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-05-11T04:54:26.921527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:54:26.382615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:54:27.194327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:54:26.649127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T04:54:31.688803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지구별주차장명주차대수이용시간날짜
지구별1.0001.0000.5580.5290.000
주차장명1.0001.0000.8220.8090.000
주차대수0.5580.8221.0000.8100.248
이용시간0.5290.8090.8101.0000.000
날짜0.0000.0000.2480.0001.000
2024-05-11T04:54:31.949193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지구별주차장명
지구별1.0000.993
주차장명0.9931.000
2024-05-11T04:54:32.201747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차대수이용시간지구별주차장명
주차대수1.0000.8800.2760.458
이용시간0.8801.0000.2570.441
지구별0.2760.2571.0000.993
주차장명0.4580.4410.9931.000

Missing values

2024-05-11T04:54:27.548866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T04:54:27.864421image/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
0PLT-008여의도1주차장2415233163722024/05
1PLT-010잠원1주차장59185104282024/05
2PLT-007양화1주차장29213153992024/05
3PLT-008여의도5주차장25106313152024/05
4PLT-004이촌2주차장28473037112024/05
5PLT-002난지1,2,3주차장2267914473182024/05
6PLT-004이촌1주차장1460730812024/05
7PLT-009반포1주차장97545526442024/05
8PLT-005뚝섬1주차장26232042622024/05
9PLT-008여의도3주차장1486533214472024/05
지구별주차장명주차대수이용시간날짜
1377PLT-010잠원1-6주차장1462418312402020/01
1378PLT-001강서1주차장1522622722020/01
1379PLT-007양화1주차장18214541442020/01
1380PLT-004이촌3,4주차장74046966472020/01
1381PLT-008여의도4주차장14396155072020/01
1382PLT-003망원1주차장25122657412020/01
1383PLT-008여의도3주차장655025358622020/01
1384PLT-009반포2,3주차장2359012001772020/01
1385PLT-005뚝섬2주차장53558584132020/01
1386PLT-006광나루3주차장40596790462020/01