Overview

Dataset statistics

Number of variables8
Number of observations3506
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory236.4 KiB
Average record size in memory69.0 B

Variable types

Categorical4
Numeric4

Dataset

Description연료별 용도별 자동차 등록 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=121LUVAB443NL4V39LRL32095792&infSeq=1

Alerts

승합차수 is highly overall correlated with 화물차수 and 1 other fieldsHigh correlation
화물차수 is highly overall correlated with 승합차수 and 1 other fieldsHigh correlation
특수차수 is highly overall correlated with 승합차수 and 1 other fieldsHigh correlation
승용차수 has 475 (13.5%) zerosZeros
승합차수 has 1900 (54.2%) zerosZeros
화물차수 has 1649 (47.0%) zerosZeros
특수차수 has 2691 (76.8%) zerosZeros

Reproduction

Analysis started2023-12-10 21:16:27.219185
Analysis finished2023-12-10 21:16:29.650487
Duration2.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록연도
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.5 KiB
2022
913 
2021
895 
2020
874 
2019
824 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2022 913
26.0%
2021 895
25.5%
2020 874
24.9%
2019 824
23.5%

Length

2023-12-11T06:16:29.718690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:16:29.824046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 913
26.0%
2021 895
25.5%
2020 874
24.9%
2019 824
23.5%

시군구명
Categorical

Distinct46
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size27.5 KiB
평택시
 
92
화성시
 
90
수원시 권선구
 
89
김포시
 
88
용인시 기흥구
 
87
Other values (41)
3060 

Length

Max length8
Median length3
Mean length4.8031945
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
평택시 92
 
2.6%
화성시 90
 
2.6%
수원시 권선구 89
 
2.5%
김포시 88
 
2.5%
용인시 기흥구 87
 
2.5%
안산시 단원구 87
 
2.5%
성남시 분당구 86
 
2.5%
고양시 일산동구 86
 
2.5%
파주시 85
 
2.4%
고양시 일산서구 84
 
2.4%
Other values (36) 2632
75.1%

Length

2023-12-11T06:16:29.937950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 334
 
6.7%
고양시 253
 
5.1%
성남시 250
 
5.0%
용인시 247
 
5.0%
안산시 170
 
3.4%
안양시 166
 
3.3%
부천시 142
 
2.8%
평택시 92
 
1.8%
화성시 90
 
1.8%
권선구 89
 
1.8%
Other values (42) 3152
63.2%

연료별
Categorical

Distinct17
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size27.5 KiB
경유
360 
휘발유
349 
엘피지
348 
휘발유(무연)
347 
기타연료
340 
Other values (12)
1762 

Length

Max length13
Median length12
Mean length5.4965773
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row기타연료
2nd row기타연료
3rd row수소
4th row엘피지
5th row엘피지

Common Values

ValueCountFrequency (%)
경유 360
10.3%
휘발유 349
10.0%
엘피지 348
9.9%
휘발유(무연) 347
9.9%
기타연료 340
9.7%
전기 325
9.3%
CNG 324
9.2%
하이브리드(휘발유+전기) 315
9.0%
하이브리드(경유+전기) 216
6.2%
수소 188
5.4%
Other values (7) 394
11.2%

Length

2023-12-11T06:16:30.088231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경유 360
10.3%
휘발유 349
10.0%
엘피지 348
9.9%
휘발유(무연 347
9.9%
기타연료 340
9.7%
전기 325
9.3%
cng 324
9.2%
하이브리드(휘발유+전기 315
9.0%
하이브리드(경유+전기 216
6.2%
수소 188
5.4%
Other values (7) 394
11.2%

용도별
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.5 KiB
비사업용
2053 
사업용
1453 

Length

Max length4
Median length4
Mean length3.5855676
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row비사업용
2nd row사업용
3rd row비사업용
4th row비사업용
5th row사업용

Common Values

ValueCountFrequency (%)
비사업용 2053
58.6%
사업용 1453
41.4%

Length

2023-12-11T06:16:30.236353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:16:30.361199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비사업용 2053
58.6%
사업용 1453
41.4%

승용차수
Real number (ℝ)

ZEROS 

Distinct1403
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5753.6791
Minimum0
Maximum163980
Zeros475
Zeros (%)13.5%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2023-12-11T06:16:30.472593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median66
Q31484.5
95-th percentile38013.5
Maximum163980
Range163980
Interquartile range (IQR)1479.5

Descriptive statistics

Standard deviation15200.688
Coefficient of variation (CV)2.6419076
Kurtosis20.295508
Mean5753.6791
Median Absolute Deviation (MAD)66
Skewness3.9698423
Sum20172399
Variance2.3106093 × 108
MonotonicityNot monotonic
2023-12-11T06:16:30.902413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 475
 
13.5%
1 180
 
5.1%
2 96
 
2.7%
3 55
 
1.6%
5 47
 
1.3%
4 42
 
1.2%
8 32
 
0.9%
7 31
 
0.9%
9 30
 
0.9%
6 29
 
0.8%
Other values (1393) 2489
71.0%
ValueCountFrequency (%)
0 475
13.5%
1 180
 
5.1%
2 96
 
2.7%
3 55
 
1.6%
4 42
 
1.2%
5 47
 
1.3%
6 29
 
0.8%
7 31
 
0.9%
8 32
 
0.9%
9 30
 
0.9%
ValueCountFrequency (%)
163980 1
< 0.1%
153899 1
< 0.1%
142726 1
< 0.1%
129730 1
< 0.1%
118239 1
< 0.1%
117972 1
< 0.1%
116363 1
< 0.1%
112633 1
< 0.1%
106730 1
< 0.1%
100154 1
< 0.1%

승합차수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct592
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean228.91101
Minimum0
Maximum10450
Zeros1900
Zeros (%)54.2%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2023-12-11T06:16:31.080239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q326
95-th percentile1190
Maximum10450
Range10450
Interquartile range (IQR)26

Descriptive statistics

Standard deviation883.61682
Coefficient of variation (CV)3.8600888
Kurtosis45.711193
Mean228.91101
Median Absolute Deviation (MAD)0
Skewness6.1742056
Sum802562
Variance780778.68
MonotonicityNot monotonic
2023-12-11T06:16:31.213891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1900
54.2%
1 178
 
5.1%
2 82
 
2.3%
3 41
 
1.2%
5 37
 
1.1%
4 31
 
0.9%
10 30
 
0.9%
7 30
 
0.9%
6 29
 
0.8%
15 26
 
0.7%
Other values (582) 1122
32.0%
ValueCountFrequency (%)
0 1900
54.2%
1 178
 
5.1%
2 82
 
2.3%
3 41
 
1.2%
4 31
 
0.9%
5 37
 
1.1%
6 29
 
0.8%
7 30
 
0.9%
8 26
 
0.7%
9 26
 
0.7%
ValueCountFrequency (%)
10450 1
< 0.1%
10130 1
< 0.1%
9857 1
< 0.1%
9580 1
< 0.1%
9057 1
< 0.1%
8647 1
< 0.1%
8072 1
< 0.1%
8027 1
< 0.1%
7790 1
< 0.1%
7630 1
< 0.1%

화물차수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct785
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean937.05705
Minimum0
Maximum57197
Zeros1649
Zeros (%)47.0%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2023-12-11T06:16:31.347678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q3117.75
95-th percentile4861.25
Maximum57197
Range57197
Interquartile range (IQR)117.75

Descriptive statistics

Standard deviation4090.1332
Coefficient of variation (CV)4.3648711
Kurtosis62.371406
Mean937.05705
Median Absolute Deviation (MAD)1
Skewness7.1144907
Sum3285322
Variance16729190
MonotonicityNot monotonic
2023-12-11T06:16:31.515236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1649
47.0%
1 117
 
3.3%
2 46
 
1.3%
3 40
 
1.1%
15 22
 
0.6%
4 22
 
0.6%
5 19
 
0.5%
12 17
 
0.5%
26 17
 
0.5%
10 16
 
0.5%
Other values (775) 1541
44.0%
ValueCountFrequency (%)
0 1649
47.0%
1 117
 
3.3%
2 46
 
1.3%
3 40
 
1.1%
4 22
 
0.6%
5 19
 
0.5%
6 16
 
0.5%
7 15
 
0.4%
8 12
 
0.3%
9 14
 
0.4%
ValueCountFrequency (%)
57197 1
< 0.1%
55328 1
< 0.1%
53528 1
< 0.1%
51704 1
< 0.1%
39975 1
< 0.1%
39609 1
< 0.1%
39260 1
< 0.1%
38626 1
< 0.1%
34890 1
< 0.1%
34469 1
< 0.1%

특수차수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct294
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.417285
Minimum0
Maximum1026
Zeros2691
Zeros (%)76.8%
Negative0
Negative (%)0.0%
Memory size30.9 KiB
2023-12-11T06:16:31.695373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile189.5
Maximum1026
Range1026
Interquartile range (IQR)0

Descriptive statistics

Standard deviation93.962627
Coefficient of variation (CV)3.5568617
Kurtosis30.105553
Mean26.417285
Median Absolute Deviation (MAD)0
Skewness5.0002893
Sum92619
Variance8828.9753
MonotonicityNot monotonic
2023-12-11T06:16:31.852841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2691
76.8%
1 138
 
3.9%
2 80
 
2.3%
3 38
 
1.1%
5 27
 
0.8%
6 20
 
0.6%
4 19
 
0.5%
8 10
 
0.3%
13 8
 
0.2%
10 7
 
0.2%
Other values (284) 468
 
13.3%
ValueCountFrequency (%)
0 2691
76.8%
1 138
 
3.9%
2 80
 
2.3%
3 38
 
1.1%
4 19
 
0.5%
5 27
 
0.8%
6 20
 
0.6%
7 6
 
0.2%
8 10
 
0.3%
9 5
 
0.1%
ValueCountFrequency (%)
1026 1
< 0.1%
968 1
< 0.1%
921 1
< 0.1%
857 1
< 0.1%
834 1
< 0.1%
830 1
< 0.1%
801 1
< 0.1%
760 1
< 0.1%
753 1
< 0.1%
731 1
< 0.1%

Interactions

2023-12-11T06:16:29.002588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:27.789676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:28.188736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:28.593417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:29.120505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:27.908598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:28.279976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:28.685649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:29.206933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:28.002742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:28.384113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:28.796271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:29.309390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:28.103669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:28.487904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:28.905764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:16:31.959947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록연도시군구명연료별용도별승용차수승합차수화물차수특수차수
등록연도1.0000.0000.0000.0000.0000.0000.0000.000
시군구명0.0001.0000.0000.0000.3460.3550.3920.292
연료별0.0000.0001.0000.3460.4370.4930.4940.590
용도별0.0000.0000.3461.0000.3950.1910.2230.081
승용차수0.0000.3460.4370.3951.0000.8360.7170.566
승합차수0.0000.3550.4930.1910.8361.0000.8950.763
화물차수0.0000.3920.4940.2230.7170.8951.0000.636
특수차수0.0000.2920.5900.0810.5660.7630.6361.000
2023-12-11T06:16:32.075059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록연도시군구명연료별용도별
등록연도1.0000.0000.0000.000
시군구명0.0001.0000.0000.000
연료별0.0000.0001.0000.310
용도별0.0000.0000.3101.000
2023-12-11T06:16:32.167206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
승용차수승합차수화물차수특수차수등록연도시군구명연료별용도별
승용차수1.0000.2650.3640.2070.0000.1250.1860.303
승합차수0.2651.0000.7070.6600.0000.1290.2160.146
화물차수0.3640.7071.0000.7060.0000.1590.2320.168
특수차수0.2070.6600.7061.0000.0000.1040.2750.062
등록연도0.0000.0000.0000.0001.0000.0000.0000.000
시군구명0.1250.1290.1590.1040.0001.0000.0000.000
연료별0.1860.2160.2320.2750.0000.0001.0000.310
용도별0.3030.1460.1680.0620.0000.0000.3101.000

Missing values

2023-12-11T06:16:29.454571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:16:29.599911image/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

등록연도시군구명연료별용도별승용차수승합차수화물차수특수차수
02022양평군기타연료비사업용06722854
12022양평군기타연료사업용00120
22022양평군수소비사업용22000
32022양평군엘피지비사업용27681393713
42022양평군엘피지사업용2611200
52022양평군전기비사업용79402110
62022양평군전기사업용436470
72022양평군하이브리드(LPG+전기)비사업용37000
82022양평군하이브리드(경유+전기)비사업용50000
92022양평군하이브리드(경유+전기)사업용2000
등록연도시군구명연료별용도별승용차수승합차수화물차수특수차수
34962019하남시하이브리드(LPG+전기)비사업용80000
34972019하남시하이브리드(경유+전기)비사업용2000
34982019하남시하이브리드(휘발유+전기)비사업용3194000
34992019하남시하이브리드(휘발유+전기)사업용1000
35002019하남시휘발유비사업용2057611350
35012019하남시휘발유사업용15022
35022019하남시휘발유(무연)비사업용3320912240
35032019하남시휘발유(무연)사업용37000
35042019하남시휘발유(유연)비사업용50000
35052019용인시 처인구CNG비사업용20130