Overview

Dataset statistics

Number of variables8
Number of observations98
Missing cells10
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory72.3 B

Variable types

Categorical2
Numeric6

Dataset

Description장애인전용주차구역 위반 과태료 집계
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=4IDLNLLF10ZU70V5ACCX32461442&infSeq=1

Alerts

위반건수 is highly overall correlated with 계도건수 and 4 other fieldsHigh correlation
계도건수 is highly overall correlated with 위반건수 and 4 other fieldsHigh correlation
과태료부과건수 is highly overall correlated with 위반건수 and 4 other fieldsHigh correlation
과태료부과금액 is highly overall correlated with 위반건수 and 4 other fieldsHigh correlation
과태료징수건수 is highly overall correlated with 위반건수 and 4 other fieldsHigh correlation
과태료징수금액 is highly overall correlated with 위반건수 and 4 other fieldsHigh correlation
계도건수 has 10 (10.2%) missing valuesMissing
과태료부과금액 has unique valuesUnique

Reproduction

Analysis started2024-05-03 19:19:02.404459
Analysis finished2024-05-03 19:19:16.261267
Duration13.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Categorical

Distinct5
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size916.0 B
2021
27 
2022
27 
2020
27 
2023
16 
2024
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row2021
2nd row2022
3rd row2020
4th row2021
5th row2022

Common Values

ValueCountFrequency (%)
2021 27
27.6%
2022 27
27.6%
2020 27
27.6%
2023 16
16.3%
2024 1
 
1.0%

Length

2024-05-03T19:19:16.436470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:19:16.746610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 27
27.6%
2022 27
27.6%
2020 27
27.6%
2023 16
16.3%
2024 1
 
1.0%

시군명
Categorical

Distinct30
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Memory size916.0 B
오산시
 
5
이천시
 
4
광주시
 
4
고양시
 
4
포천시
 
4
Other values (25)
77 

Length

Max length4
Median length3
Mean length3.0816327
Min length3

Unique

Unique3 ?
Unique (%)3.1%

Sample

1st row의정부시
2nd row의정부시
3rd row수원시
4th row수원시
5th row수원시

Common Values

ValueCountFrequency (%)
오산시 5
 
5.1%
이천시 4
 
4.1%
광주시 4
 
4.1%
고양시 4
 
4.1%
포천시 4
 
4.1%
연천군 4
 
4.1%
파주시 4
 
4.1%
평택시 4
 
4.1%
화성시 4
 
4.1%
안산시 4
 
4.1%
Other values (20) 57
58.2%

Length

2024-05-03T19:19:17.130882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
오산시 5
 
5.1%
평택시 4
 
4.1%
이천시 4
 
4.1%
안양시 4
 
4.1%
가평군 4
 
4.1%
안산시 4
 
4.1%
화성시 4
 
4.1%
동두천시 4
 
4.1%
파주시 4
 
4.1%
연천군 4
 
4.1%
Other values (20) 57
58.2%

위반건수
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4968.1837
Minimum126
Maximum18356
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2024-05-03T19:19:17.530681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126
5-th percentile163.85
Q11053
median3499.5
Q37920.75
95-th percentile12397.35
Maximum18356
Range18230
Interquartile range (IQR)6867.75

Descriptive statistics

Standard deviation4359.4255
Coefficient of variation (CV)0.87746867
Kurtosis-0.091406381
Mean4968.1837
Median Absolute Deviation (MAD)3059
Skewness0.80512263
Sum486882
Variance19004591
MonotonicityNot monotonic
2024-05-03T19:19:17.970886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
430 2
 
2.0%
7565 1
 
1.0%
2037 1
 
1.0%
1059 1
 
1.0%
1051 1
 
1.0%
1240 1
 
1.0%
2434 1
 
1.0%
4742 1
 
1.0%
2846 1
 
1.0%
2364 1
 
1.0%
Other values (87) 87
88.8%
ValueCountFrequency (%)
126 1
1.0%
129 1
1.0%
133 1
1.0%
141 1
1.0%
146 1
1.0%
167 1
1.0%
239 1
1.0%
246 1
1.0%
336 1
1.0%
374 1
1.0%
ValueCountFrequency (%)
18356 1
1.0%
16442 1
1.0%
15268 1
1.0%
12989 1
1.0%
12830 1
1.0%
12321 1
1.0%
12132 1
1.0%
11799 1
1.0%
11772 1
1.0%
10773 1
1.0%

계도건수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct80
Distinct (%)90.9%
Missing10
Missing (%)10.2%
Infinite0
Infinite (%)0.0%
Mean550.51136
Minimum1
Maximum4272
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2024-05-03T19:19:18.393221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.35
Q1104
median233.5
Q3610
95-th percentile1681.65
Maximum4272
Range4271
Interquartile range (IQR)506

Descriptive statistics

Standard deviation844.93813
Coefficient of variation (CV)1.5348241
Kurtosis10.497649
Mean550.51136
Median Absolute Deviation (MAD)214
Skewness3.1281569
Sum48445
Variance713920.44
MonotonicityNot monotonic
2024-05-03T19:19:18.817379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 2
 
2.0%
1 2
 
2.0%
40 2
 
2.0%
557 2
 
2.0%
526 2
 
2.0%
156 2
 
2.0%
104 2
 
2.0%
6 2
 
2.0%
17 1
 
1.0%
115 1
 
1.0%
Other values (70) 70
71.4%
(Missing) 10
 
10.2%
ValueCountFrequency (%)
1 2
2.0%
3 1
1.0%
5 2
2.0%
6 2
2.0%
10 1
1.0%
17 1
1.0%
22 1
1.0%
29 1
1.0%
30 1
1.0%
40 2
2.0%
ValueCountFrequency (%)
4272 1
1.0%
4247 1
1.0%
3727 1
1.0%
3499 1
1.0%
1801 1
1.0%
1460 1
1.0%
1455 1
1.0%
1340 1
1.0%
1302 1
1.0%
1285 1
1.0%

과태료부과건수
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4005.3878
Minimum104
Maximum14375
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2024-05-03T19:19:19.227395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum104
5-th percentile163.85
Q1936
median2697
Q36086.75
95-th percentile11319.85
Maximum14375
Range14271
Interquartile range (IQR)5150.75

Descriptive statistics

Standard deviation3702.0627
Coefficient of variation (CV)0.92427075
Kurtosis0.059481168
Mean4005.3878
Median Absolute Deviation (MAD)2087
Skewness1.0077571
Sum392528
Variance13705269
MonotonicityNot monotonic
2024-05-03T19:19:19.677910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4036 2
 
2.0%
6783 2
 
2.0%
2128 2
 
2.0%
4566 1
 
1.0%
347 1
 
1.0%
615 1
 
1.0%
687 1
 
1.0%
767 1
 
1.0%
1403 1
 
1.0%
2866 1
 
1.0%
Other values (85) 85
86.7%
ValueCountFrequency (%)
104 1
1.0%
129 1
1.0%
133 1
1.0%
141 1
1.0%
146 1
1.0%
167 1
1.0%
238 1
1.0%
246 1
1.0%
254 1
1.0%
330 1
1.0%
ValueCountFrequency (%)
14375 1
1.0%
13966 1
1.0%
12534 1
1.0%
11863 1
1.0%
11608 1
1.0%
11269 1
1.0%
10942 1
1.0%
10339 1
1.0%
10140 1
1.0%
9856 1
1.0%

과태료부과금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct98
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.757081 × 108
Minimum11190000
Maximum1.3471967 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2024-05-03T19:19:20.114747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11190000
5-th percentile16709000
Q190299450
median2.4755017 × 108
Q35.9167694 × 108
95-th percentile1.0357486 × 109
Maximum1.3471967 × 109
Range1.3360067 × 109
Interquartile range (IQR)5.0137749 × 108

Descriptive statistics

Standard deviation3.4245909 × 108
Coefficient of variation (CV)0.91150307
Kurtosis-0.03536355
Mean3.757081 × 108
Median Absolute Deviation (MAD)1.9708531 × 108
Skewness0.9590483
Sum3.6819393 × 1010
Variance1.1727822 × 1017
MonotonicityNot monotonic
2024-05-03T19:19:20.642901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
424491310 1
 
1.0%
192637360 1
 
1.0%
247580340 1
 
1.0%
53920000 1
 
1.0%
67650000 1
 
1.0%
66650000 1
 
1.0%
143870000 1
 
1.0%
229060000 1
 
1.0%
171800000 1
 
1.0%
161890000 1
 
1.0%
Other values (88) 88
89.8%
ValueCountFrequency (%)
11190000 1
1.0%
13000000 1
1.0%
13500000 1
1.0%
13700000 1
1.0%
16080000 1
1.0%
16820000 1
1.0%
23490000 1
1.0%
24800000 1
1.0%
28300000 1
1.0%
29470000 1
1.0%
ValueCountFrequency (%)
1347196720 1
1.0%
1241107910 1
1.0%
1190044830 1
1.0%
1134648470 1
1.0%
1052245460 1
1.0%
1032837360 1
1.0%
1025130450 1
1.0%
937434080 1
1.0%
931927000 1
1.0%
913234400 1
1.0%

과태료징수건수
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3382.551
Minimum68
Maximum13376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2024-05-03T19:19:21.205421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum68
5-th percentile124.65
Q1742.75
median2231
Q35478.75
95-th percentile9620.65
Maximum13376
Range13308
Interquartile range (IQR)4736

Descriptive statistics

Standard deviation3146.6392
Coefficient of variation (CV)0.93025624
Kurtosis0.45771604
Mean3382.551
Median Absolute Deviation (MAD)1751
Skewness1.064957
Sum331490
Variance9901338.3
MonotonicityNot monotonic
2024-05-03T19:19:21.706231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3970 2
 
2.0%
3678 1
 
1.0%
272 1
 
1.0%
496 1
 
1.0%
539 1
 
1.0%
705 1
 
1.0%
957 1
 
1.0%
2591 1
 
1.0%
1739 1
 
1.0%
1864 1
 
1.0%
Other values (87) 87
88.8%
ValueCountFrequency (%)
68 1
1.0%
80 1
1.0%
87 1
1.0%
94 1
1.0%
100 1
1.0%
129 1
1.0%
159 1
1.0%
192 1
1.0%
197 1
1.0%
268 1
1.0%
ValueCountFrequency (%)
13376 1
1.0%
12074 1
1.0%
11237 1
1.0%
9882 1
1.0%
9868 1
1.0%
9577 1
1.0%
8681 1
1.0%
8149 1
1.0%
8072 1
1.0%
7972 1
1.0%

과태료징수금액
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0839956 × 108
Minimum8020000
Maximum1.230708 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2024-05-03T19:19:22.226979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8020000
5-th percentile11143500
Q169010650
median2.200279 × 108
Q34.8779954 × 108
95-th percentile8.4285127 × 108
Maximum1.230708 × 109
Range1.222688 × 109
Interquartile range (IQR)4.1878889 × 108

Descriptive statistics

Standard deviation2.8489627 × 108
Coefficient of variation (CV)0.92378948
Kurtosis0.57420955
Mean3.0839956 × 108
Median Absolute Deviation (MAD)1.772601 × 108
Skewness1.0735222
Sum3.0223157 × 1010
Variance8.1165885 × 1016
MonotonicityNot monotonic
2024-05-03T19:19:22.718219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
424633210 2
 
2.0%
363009410 1
 
1.0%
22151200 1
 
1.0%
43290000 1
 
1.0%
45801980 1
 
1.0%
62460000 1
 
1.0%
114250000 1
 
1.0%
214460000 1
 
1.0%
144640000 1
 
1.0%
149390000 1
 
1.0%
Other values (87) 87
88.8%
ValueCountFrequency (%)
8020000 1
1.0%
8140000 1
1.0%
8520000 1
1.0%
9060000 1
1.0%
10880000 1
1.0%
11190000 1
1.0%
16866000 1
1.0%
19158400 1
1.0%
19790000 1
1.0%
22151200 1
1.0%
ValueCountFrequency (%)
1230708010 1
1.0%
1099823320 1
1.0%
1024073480 1
1.0%
944022240 1
1.0%
902354910 1
1.0%
832350630 1
1.0%
796632860 1
1.0%
736468600 1
1.0%
722120790 1
1.0%
710430600 1
1.0%

Interactions

2024-05-03T19:19:13.565664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:03.323152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:05.243520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:07.094569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:09.357557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:11.719818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:13.869253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:03.600578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:05.517332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:07.395398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:09.690609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:12.049068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:14.113943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:03.917954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:05.789742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:07.646562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:09.997148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:12.320344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:14.423242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:04.270031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:06.229375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:07.984580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:10.318978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:12.576972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:14.737468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:04.635235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:06.535531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:08.312301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:10.792376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:12.908738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:15.083328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:04.906162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:06.742520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:08.806791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:11.345383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:19:13.295139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T19:19:23.143146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명위반건수계도건수과태료부과건수과태료부과금액과태료징수건수과태료징수금액
기준년도1.0000.0000.0000.0000.0000.0000.0000.000
시군명0.0001.0000.8440.8730.8760.8810.8840.878
위반건수0.0000.8441.0000.6390.9530.9490.9590.960
계도건수0.0000.8730.6391.0000.5990.6370.5790.645
과태료부과건수0.0000.8760.9530.5991.0000.9790.9820.966
과태료부과금액0.0000.8810.9490.6370.9791.0000.9720.975
과태료징수건수0.0000.8840.9590.5790.9820.9721.0000.977
과태료징수금액0.0000.8780.9600.6450.9660.9750.9771.000
2024-05-03T19:19:23.463119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명
기준년도1.0000.000
시군명0.0001.000
2024-05-03T19:19:23.731992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위반건수계도건수과태료부과건수과태료부과금액과태료징수건수과태료징수금액기준년도시군명
위반건수1.0000.6970.9680.9610.9630.9590.0000.391
계도건수0.6971.0000.6200.6000.6150.6100.0000.467
과태료부과건수0.9680.6201.0000.9950.9910.9920.0000.434
과태료부과금액0.9610.6000.9951.0000.9830.9910.0000.445
과태료징수건수0.9630.6150.9910.9831.0000.9920.0000.447
과태료징수금액0.9590.6100.9920.9910.9921.0000.0000.440
기준년도0.0000.0000.0000.0000.0000.0001.0000.000
시군명0.3910.4670.4340.4450.4470.4400.0001.000

Missing values

2024-05-03T19:19:15.507520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T19:19:16.061846image/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

기준년도시군명위반건수계도건수과태료부과건수과태료부과금액과태료징수건수과태료징수금액
02021의정부시756515641764244913103678363009410
12022의정부시992331440364419926803209334968300
22020수원시183561455143751347196720133761230708010
32021수원시12830134086157650526507972710430600
42022수원시1644218011186310328373609882902354910
52020가평군33663302947000032028470000
62021가평군374103743183531032427072140
72022가평군49434914045497046838279170
82023가평군44354385233972026832694800
92023군포시17035691134131928000944107028000
기준년도시군명위반건수계도건수과태료부과건수과태료부과금액과태료징수건수과태료징수금액
882022용인시117991460103399319270008072722120790
892020과천시246<NA>2462349000019719790000
902021과천시141<NA>14113000000878520000
912022과천시146<NA>146160800008010880000
922020양평군46414634809000042442245600
932021양평군43064244859000034540762900
942022양평군23912382830000015916866000
952020성남시788410585117352915907268620271380
962021성남시659912867835803231415934497997760
972022성남시731222470885954615405913488343180