Overview

Dataset statistics

Number of variables9
Number of observations116
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.2 KiB
Average record size in memory81.1 B

Variable types

Numeric8
Categorical1

Dataset

Description충청남도 서산시에 등록된 자동차에 대한 등록현행자료로 년별, 월별, 승용차, 화물차, 특수차, 이륜자동차 등록 통계를 낸 자료
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=451&beforeMenuCd=DOM_000000201001001000&publicdatapk=15000832

Alerts

기준일 has constant value ""Constant
년도 is highly overall correlated with 합계 and 5 other fieldsHigh correlation
합계 is highly overall correlated with 년도 and 5 other fieldsHigh correlation
승용차 is highly overall correlated with 년도 and 5 other fieldsHigh correlation
승합차 is highly overall correlated with 년도 and 5 other fieldsHigh correlation
화물차 is highly overall correlated with 년도 and 5 other fieldsHigh correlation
특수차 is highly overall correlated with 년도 and 5 other fieldsHigh correlation
이륜자동차 is highly overall correlated with 년도 and 5 other fieldsHigh correlation

Reproduction

Analysis started2024-01-09 22:34:16.068907
Analysis finished2024-01-09 22:34:21.625752
Duration5.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.3448
Minimum2011
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T07:34:21.675478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2011
Q12013
median2015
Q32018
95-th percentile2020
Maximum2020
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.8071445
Coefficient of variation (CV)0.0013928854
Kurtosis-1.1960954
Mean2015.3448
Median Absolute Deviation (MAD)2
Skewness0.023115393
Sum233780
Variance7.88006
MonotonicityDecreasing
2024-01-10T07:34:21.766536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2019 12
10.3%
2018 12
10.3%
2017 12
10.3%
2016 12
10.3%
2015 12
10.3%
2014 12
10.3%
2013 12
10.3%
2012 12
10.3%
2011 12
10.3%
2020 8
6.9%
ValueCountFrequency (%)
2011 12
10.3%
2012 12
10.3%
2013 12
10.3%
2014 12
10.3%
2015 12
10.3%
2016 12
10.3%
2017 12
10.3%
2018 12
10.3%
2019 12
10.3%
2020 8
6.9%
ValueCountFrequency (%)
2020 8
6.9%
2019 12
10.3%
2018 12
10.3%
2017 12
10.3%
2016 12
10.3%
2015 12
10.3%
2014 12
10.3%
2013 12
10.3%
2012 12
10.3%
2011 12
10.3%

월
Real number (ℝ)

Distinct12
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.362069
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T07:34:21.857215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4373816
Coefficient of variation (CV)0.54029304
Kurtosis-1.1864028
Mean6.362069
Median Absolute Deviation (MAD)3
Skewness0.053715676
Sum738
Variance11.815592
MonotonicityNot monotonic
2024-01-10T07:34:21.962774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8 10
8.6%
7 10
8.6%
6 10
8.6%
5 10
8.6%
4 10
8.6%
3 10
8.6%
2 10
8.6%
1 10
8.6%
12 9
7.8%
11 9
7.8%
Other values (2) 18
15.5%
ValueCountFrequency (%)
1 10
8.6%
2 10
8.6%
3 10
8.6%
4 10
8.6%
5 10
8.6%
6 10
8.6%
7 10
8.6%
8 10
8.6%
9 9
7.8%
10 9
7.8%
ValueCountFrequency (%)
12 9
7.8%
11 9
7.8%
10 9
7.8%
9 9
7.8%
8 10
8.6%
7 10
8.6%
6 10
8.6%
5 10
8.6%
4 10
8.6%
3 10
8.6%

합계
Real number (ℝ)

HIGH CORRELATION 

Distinct115
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92483.621
Minimum75205
Maximum109929
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T07:34:22.073628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum75205
5-th percentile76558.75
Q183403.25
median92666
Q3101665
95-th percentile107953.75
Maximum109929
Range34724
Interquartile range (IQR)18261.75

Descriptive statistics

Standard deviation10582.913
Coefficient of variation (CV)0.11443014
Kurtosis-1.2956347
Mean92483.621
Median Absolute Deviation (MAD)9230.5
Skewness-0.016348358
Sum10728100
Variance1.1199805 × 108
MonotonicityNot monotonic
2024-01-10T07:34:22.206209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
94944 2
 
1.7%
109929 1
 
0.9%
86993 1
 
0.9%
83477 1
 
0.9%
83826 1
 
0.9%
84092 1
 
0.9%
84245 1
 
0.9%
84519 1
 
0.9%
84705 1
 
0.9%
84870 1
 
0.9%
Other values (105) 105
90.5%
ValueCountFrequency (%)
75205 1
0.9%
75427 1
0.9%
75765 1
0.9%
76120 1
0.9%
76209 1
0.9%
76381 1
0.9%
76618 1
0.9%
76861 1
0.9%
77005 1
0.9%
77484 1
0.9%
ValueCountFrequency (%)
109929 1
0.9%
109579 1
0.9%
109184 1
0.9%
108668 1
0.9%
108308 1
0.9%
108280 1
0.9%
107845 1
0.9%
107829 1
0.9%
107309 1
0.9%
107147 1
0.9%

승용차
Real number (ℝ)

HIGH CORRELATION 

Distinct115
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59068.241
Minimum46054
Maximum73395
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T07:34:22.329699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46054
5-th percentile47263
Q151155
median58781.5
Q366555.25
95-th percentile71825.5
Maximum73395
Range27341
Interquartile range (IQR)15400.25

Descriptive statistics

Standard deviation8479.778
Coefficient of variation (CV)0.14355901
Kurtosis-1.3678708
Mean59068.241
Median Absolute Deviation (MAD)7742.5
Skewness0.09083023
Sum6851916
Variance71906635
MonotonicityNot monotonic
2024-01-10T07:34:22.449221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60812 2
 
1.7%
73395 1
 
0.9%
54148 1
 
0.9%
51209 1
 
0.9%
51494 1
 
0.9%
51716 1
 
0.9%
51868 1
 
0.9%
52073 1
 
0.9%
52241 1
 
0.9%
52376 1
 
0.9%
Other values (105) 105
90.5%
ValueCountFrequency (%)
46054 1
0.9%
46194 1
0.9%
46437 1
0.9%
46736 1
0.9%
46924 1
0.9%
47086 1
0.9%
47322 1
0.9%
47448 1
0.9%
47875 1
0.9%
47980 1
0.9%
ValueCountFrequency (%)
73395 1
0.9%
73180 1
0.9%
72826 1
0.9%
72401 1
0.9%
72097 1
0.9%
72031 1
0.9%
71757 1
0.9%
71741 1
0.9%
71289 1
0.9%
71062 1
0.9%

승합차
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3602.0862
Minimum3378
Maximum3840
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T07:34:22.590107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3378
5-th percentile3452
Q13499.5
median3605
Q33684.25
95-th percentile3814.5
Maximum3840
Range462
Interquartile range (IQR)184.75

Descriptive statistics

Standard deviation114.06539
Coefficient of variation (CV)0.031666481
Kurtosis-0.86010535
Mean3602.0862
Median Absolute Deviation (MAD)93
Skewness0.30296842
Sum417842
Variance13010.914
MonotonicityNot monotonic
2024-01-10T07:34:22.704423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3533 2
 
1.7%
3452 2
 
1.7%
3663 2
 
1.7%
3505 2
 
1.7%
3596 2
 
1.7%
3532 2
 
1.7%
3581 2
 
1.7%
3481 2
 
1.7%
3474 2
 
1.7%
3622 2
 
1.7%
Other values (89) 96
82.8%
ValueCountFrequency (%)
3378 1
0.9%
3406 1
0.9%
3441 1
0.9%
3446 1
0.9%
3449 1
0.9%
3452 2
1.7%
3453 1
0.9%
3459 1
0.9%
3461 1
0.9%
3468 1
0.9%
ValueCountFrequency (%)
3840 1
0.9%
3838 1
0.9%
3837 2
1.7%
3831 2
1.7%
3809 1
0.9%
3793 1
0.9%
3792 1
0.9%
3780 1
0.9%
3766 1
0.9%
3743 1
0.9%

화물차
Real number (ℝ)

HIGH CORRELATION 

Distinct113
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17838.431
Minimum11307
Maximum19879
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T07:34:22.819768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11307
5-th percentile16034.5
Q116641.25
median18014.5
Q319020.75
95-th percentile19704
Maximum19879
Range8572
Interquartile range (IQR)2379.5

Descriptive statistics

Standard deviation1413.8257
Coefficient of variation (CV)0.079257291
Kurtosis2.2175697
Mean17838.431
Median Absolute Deviation (MAD)1234.5
Skewness-0.81067271
Sum2069258
Variance1998903.2
MonotonicityNot monotonic
2024-01-10T07:34:22.936349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19767 2
 
1.7%
18287 2
 
1.7%
16167 2
 
1.7%
17237 1
 
0.9%
16729 1
 
0.9%
16752 1
 
0.9%
16808 1
 
0.9%
16800 1
 
0.9%
16853 1
 
0.9%
16931 1
 
0.9%
Other values (103) 103
88.8%
ValueCountFrequency (%)
11307 1
0.9%
15791 1
0.9%
15864 1
0.9%
15929 1
0.9%
15954 1
0.9%
16021 1
0.9%
16039 1
0.9%
16064 1
0.9%
16083 1
0.9%
16130 1
0.9%
ValueCountFrequency (%)
19879 1
0.9%
19772 1
0.9%
19767 2
1.7%
19746 1
0.9%
19716 1
0.9%
19700 1
0.9%
19681 1
0.9%
19674 1
0.9%
19655 1
0.9%
19626 1
0.9%

특수차
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean391.16379
Minimum252
Maximum553
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T07:34:23.050348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum252
5-th percentile264.75
Q1304.25
median412
Q3478
95-th percentile515
Maximum553
Range301
Interquartile range (IQR)173.75

Descriptive statistics

Standard deviation91.501765
Coefficient of variation (CV)0.23392187
Kurtosis-1.4385605
Mean391.16379
Median Absolute Deviation (MAD)84.5
Skewness-0.08479452
Sum45375
Variance8372.5729
MonotonicityNot monotonic
2024-01-10T07:34:23.174555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
265 5
 
4.3%
492 3
 
2.6%
505 3
 
2.6%
272 3
 
2.6%
412 3
 
2.6%
495 3
 
2.6%
267 2
 
1.7%
434 2
 
1.7%
447 2
 
1.7%
322 2
 
1.7%
Other values (79) 88
75.9%
ValueCountFrequency (%)
252 1
 
0.9%
259 1
 
0.9%
261 1
 
0.9%
262 1
 
0.9%
263 1
 
0.9%
264 1
 
0.9%
265 5
4.3%
267 2
 
1.7%
268 2
 
1.7%
269 2
 
1.7%
ValueCountFrequency (%)
553 1
 
0.9%
546 1
 
0.9%
533 1
 
0.9%
523 1
 
0.9%
520 1
 
0.9%
518 1
 
0.9%
514 1
 
0.9%
507 1
 
0.9%
505 3
2.6%
503 2
1.7%

이륜자동차
Real number (ℝ)

HIGH CORRELATION 

Distinct106
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11583.698
Minimum9271
Maximum12661
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T07:34:23.328550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9271
5-th percentile9397
Q111570.75
median11822
Q312146.75
95-th percentile12493
Maximum12661
Range3390
Interquartile range (IQR)576

Descriptive statistics

Standard deviation943.88121
Coefficient of variation (CV)0.081483581
Kurtosis1.29778
Mean11583.698
Median Absolute Deviation (MAD)284
Skewness-1.5601824
Sum1343709
Variance890911.74
MonotonicityNot monotonic
2024-01-10T07:34:23.450617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11639 3
 
2.6%
11917 2
 
1.7%
9397 2
 
1.7%
11916 2
 
1.7%
9409 2
 
1.7%
11842 2
 
1.7%
11959 2
 
1.7%
11824 2
 
1.7%
11821 2
 
1.7%
11651 1
 
0.9%
Other values (96) 96
82.8%
ValueCountFrequency (%)
9271 1
0.9%
9277 1
0.9%
9296 1
0.9%
9320 1
0.9%
9330 1
0.9%
9397 2
1.7%
9402 1
0.9%
9406 1
0.9%
9409 2
1.7%
9410 1
0.9%
ValueCountFrequency (%)
12661 1
0.9%
12634 1
0.9%
12605 1
0.9%
12598 1
0.9%
12558 1
0.9%
12526 1
0.9%
12482 1
0.9%
12479 1
0.9%
12473 1
0.9%
12467 1
0.9%

기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2021-10-27
116 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-10-27
2nd row2021-10-27
3rd row2021-10-27
4th row2021-10-27
5th row2021-10-27

Common Values

ValueCountFrequency (%)
2021-10-27 116
100.0%

Length

2024-01-10T07:34:23.564192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:34:23.655362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-10-27 116
100.0%

Interactions

2024-01-10T07:34:20.588599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:16.279840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:16.905503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:17.524468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:18.193134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:18.772448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.417898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.965725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:20.659622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:16.343854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:16.973237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:17.622464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:18.264305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:18.840905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.480986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:20.045040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:20.733651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:16.421797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:17.050051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:17.704093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:18.345267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:18.925012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.547685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:20.123423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:20.810966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:16.521647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:17.133013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:17.790735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:18.422705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.027261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.626895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:20.213795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:20.886904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:16.613091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:17.210989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:17.878231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:18.489664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.100368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.694871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:20.291988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:21.197705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:16.679719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:17.276648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:17.962081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:18.552973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.189451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.761939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:20.365963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:21.275839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:16.750110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:17.342970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:18.035928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:18.624661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.272685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.824178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:20.440299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:21.364414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:16.826113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:17.430982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:18.115994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:18.698234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.342519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:19.895360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:34:20.512727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:34:23.711323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도월합계승용차승합차화물차특수차이륜자동차
년도1.0000.0000.9330.9210.8660.9580.9200.815
월0.0001.0000.0000.0000.0000.0000.0000.000
합계0.9330.0001.0000.9850.9290.9940.9650.879
승용차0.9210.0000.9851.0000.9320.9940.9720.858
승합차0.8660.0000.9290.9321.0000.9810.9020.826
화물차0.9580.0000.9940.9940.9811.0000.9910.823
특수차0.9200.0000.9650.9720.9020.9911.0000.814
이륜자동차0.8150.0000.8790.8580.8260.8230.8141.000
2024-01-10T07:34:23.816879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도월합계승용차승합차화물차특수차이륜자동차
년도1.000-0.0650.9940.995-0.9030.9930.9880.991
월-0.0651.0000.0330.0370.0330.0270.0330.055
합계0.9940.0331.0000.999-0.8990.9990.9930.997
승용차0.9950.0370.9991.000-0.9010.9970.9920.998
승합차-0.9030.033-0.899-0.9011.000-0.897-0.880-0.898
화물차0.9930.0270.9990.997-0.8971.0000.9920.994
특수차0.9880.0330.9930.992-0.8800.9921.0000.991
이륜자동차0.9910.0550.9970.998-0.8980.9940.9911.000

Missing values

2024-01-10T07:34:21.467695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:34:21.582867image/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

년도월합계승용차승합차화물차특수차이륜자동차기준일
02020810992973395344119879553126612021-10-27
12020710957973180345219767546126342021-10-27
22020610918472826345319767533126052021-10-27
32020510866872401344619700523125982021-10-27
42020410828072097345219655518125582021-10-27
52020310830872031345919772520125262021-10-27
62020210784571741344919674514124672021-10-27
72020110782971757346819626505124732021-10-27
820191210730971289347319564501124822021-10-27
920191110703771062347819518500124792021-10-27
년도월합계승용차승합차화물차특수차이륜자동차기준일
106201110776224798037801618327794022021-10-27
10720119774844787537931613027294142021-10-27
10820118770054744837921608327294102021-10-27
10920117768614732238091606426993972021-10-27
11020116766184708638311603926593972021-10-27
11120115763814692438371602126993302021-10-27
11220114761204673638401595427093202021-10-27
11320113757654643738381592926592962021-10-27
11420112754274619438311586426192772021-10-27
11520111752054605438371579125292712021-10-27