Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells2382
Missing cells (%)3.4%
Duplicate rows213
Duplicate rows (%)2.1%
Total size in memory654.3 KiB
Average record size in memory67.0 B

Variable types

Categorical2
Text3
Numeric2

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21245/F/1/datasetView.do

Alerts

기준년월 has constant value ""Constant
Dataset has 213 (2.1%) duplicate rowsDuplicates
연료 is highly imbalanced (64.7%)Imbalance
현소유자의출생년도 has 2382 (23.8%) missing valuesMissing

Reproduction

Analysis started2024-03-13 07:47:53.603241
Analysis finished2024-03-13 07:47:54.483387
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
202012
10000 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202012
2nd row202012
3rd row202012
4th row202012
5th row202012

Common Values

ValueCountFrequency (%)
202012 10000
100.0%

Length

2024-03-13T16:47:54.535219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T16:47:54.606425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202012 10000
100.0%

사용본거지시읍면동_행정동기준
Text

Distinct424
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T16:47:54.880093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length13.9103
Min length11

Characters and Unicode

Total characters139103
Distinct characters194
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row서울특별시 강서구 가양1동
2nd row서울특별시 용산구 보광동
3rd row서울특별시 서초구 방배3동
4th row서울특별시 강남구 대치1동
5th row서울특별시 구로구 개봉3동
ValueCountFrequency (%)
서울특별시 10000
33.3%
강남구 1482
 
4.9%
서초구 941
 
3.1%
송파구 716
 
2.4%
강서구 624
 
2.1%
구로구 486
 
1.6%
마포구 449
 
1.5%
노원구 437
 
1.5%
영등포구 433
 
1.4%
성동구 426
 
1.4%
Other values (439) 14006
46.7%
2024-03-13T16:47:55.396645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20000
14.4%
서 12307
 
8.8%
동 11522
 
8.3%
구 10840
 
7.8%
시 10077
 
7.2%
특 10000
 
7.2%
별 10000
 
7.2%
울 10000
 
7.2%
1 3116
 
2.2%
강 2834
 
2.0%
Other values (184) 38407
27.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111644
80.3%
Space Separator 20000
 
14.4%
Decimal Number 7317
 
5.3%
Other Punctuation 142
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 12307
 
11.0%
동 11522
 
10.3%
구 10840
 
9.7%
시 10077
 
9.0%
특 10000
 
9.0%
별 10000
 
9.0%
울 10000
 
9.0%
강 2834
 
2.5%
남 1600
 
1.4%
대 1306
 
1.2%
Other values (172) 31158
27.9%
Decimal Number
ValueCountFrequency (%)
1 3116
42.6%
2 2146
29.3%
3 820
 
11.2%
4 815
 
11.1%
5 157
 
2.1%
6 109
 
1.5%
7 87
 
1.2%
8 39
 
0.5%
9 16
 
0.2%
0 12
 
0.2%
Space Separator
ValueCountFrequency (%)
20000
100.0%
Other Punctuation
ValueCountFrequency (%)
. 142
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111644
80.3%
Common 27459
 
19.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 12307
 
11.0%
동 11522
 
10.3%
구 10840
 
9.7%
시 10077
 
9.0%
특 10000
 
9.0%
별 10000
 
9.0%
울 10000
 
9.0%
강 2834
 
2.5%
남 1600
 
1.4%
대 1306
 
1.2%
Other values (172) 31158
27.9%
Common
ValueCountFrequency (%)
20000
72.8%
1 3116
 
11.3%
2 2146
 
7.8%
3 820
 
3.0%
4 815
 
3.0%
5 157
 
0.6%
. 142
 
0.5%
6 109
 
0.4%
7 87
 
0.3%
8 39
 
0.1%
Other values (2) 28
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111644
80.3%
ASCII 27459
 
19.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20000
72.8%
1 3116
 
11.3%
2 2146
 
7.8%
3 820
 
3.0%
4 815
 
3.0%
5 157
 
0.6%
. 142
 
0.5%
6 109
 
0.4%
7 87
 
0.3%
8 39
 
0.1%
Other values (2) 28
 
0.1%
Hangul
ValueCountFrequency (%)
서 12307
 
11.0%
동 11522
 
10.3%
구 10840
 
9.7%
시 10077
 
9.0%
특 10000
 
9.0%
별 10000
 
9.0%
울 10000
 
9.0%
강 2834
 
2.5%
남 1600
 
1.4%
대 1306
 
1.2%
Other values (172) 31158
27.9%

차명
Text

Distinct196
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T16:47:55.717674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length13.4092
Min length2

Characters and Unicode

Total characters134092
Distinct characters177
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)0.4%

Sample

1st row쏘나타 (SONATA) 하이브리드
2nd rowK5 하이브리드
3rd row볼보 XC40B4 AWD
4th row그랜저 하이브리드
5th row토요타 PRIUS
ValueCountFrequency (%)
하이브리드 3725
 
14.6%
렉서스 1565
 
6.2%
그랜저 1344
 
5.3%
니로 1112
 
4.4%
es300h 969
 
3.8%
토요타 869
 
3.4%
hybrid 767
 
3.0%
쏘나타 695
 
2.7%
ev 462
 
1.8%
k5 447
 
1.8%
Other values (247) 13490
53.0%
2024-03-13T16:47:56.165425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15681
 
11.7%
이 5429
 
4.0%
리 4956
 
3.7%
드 4951
 
3.7%
브 4940
 
3.7%
하 4939
 
3.7%
E 4202
 
3.1%
A 3847
 
2.9%
0 3614
 
2.7%
R 3296
 
2.5%
Other values (167) 78237
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50142
37.4%
Uppercase Letter 40531
30.2%
Space Separator 15681
 
11.7%
Lowercase Letter 15097
 
11.3%
Decimal Number 8501
 
6.3%
Open Punctuation 2854
 
2.1%
Close Punctuation 846
 
0.6%
Dash Punctuation 182
 
0.1%
Letter Number 178
 
0.1%
Other Punctuation 75
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 5429
 
10.8%
리 4956
 
9.9%
드 4951
 
9.9%
브 4940
 
9.9%
하 4939
 
9.9%
렉 2165
 
4.3%
타 1763
 
3.5%
스 1619
 
3.2%
서 1571
 
3.1%
그 1526
 
3.0%
Other values (101) 16283
32.5%
Uppercase Letter
ValueCountFrequency (%)
E 4202
 
10.4%
A 3847
 
9.5%
R 3296
 
8.1%
N 3052
 
7.5%
S 2461
 
6.1%
O 2331
 
5.8%
H 2240
 
5.5%
T 2207
 
5.4%
C 2159
 
5.3%
I 2062
 
5.1%
Other values (15) 12674
31.3%
Lowercase Letter
ValueCountFrequency (%)
e 1664
11.0%
h 1584
10.5%
r 1583
10.5%
d 1337
 
8.9%
i 1101
 
7.3%
a 1069
 
7.1%
n 951
 
6.3%
y 903
 
6.0%
o 881
 
5.8%
b 634
 
4.2%
Other values (13) 3390
22.5%
Decimal Number
ValueCountFrequency (%)
0 3614
42.5%
3 1883
22.2%
5 1177
 
13.8%
4 809
 
9.5%
7 424
 
5.0%
2 295
 
3.5%
1 116
 
1.4%
6 76
 
0.9%
8 64
 
0.8%
9 43
 
0.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 118
66.3%
Ⅲ 60
33.7%
Space Separator
ValueCountFrequency (%)
15681
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2854
100.0%
Close Punctuation
ValueCountFrequency (%)
) 846
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%
Other Punctuation
ValueCountFrequency (%)
. 75
100.0%
Math Symbol
ValueCountFrequency (%)
+ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 55806
41.6%
Hangul 50142
37.4%
Common 28144
21.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 5429
 
10.8%
리 4956
 
9.9%
드 4951
 
9.9%
브 4940
 
9.9%
하 4939
 
9.9%
렉 2165
 
4.3%
타 1763
 
3.5%
스 1619
 
3.2%
서 1571
 
3.1%
그 1526
 
3.0%
Other values (101) 16283
32.5%
Latin
ValueCountFrequency (%)
E 4202
 
7.5%
A 3847
 
6.9%
R 3296
 
5.9%
N 3052
 
5.5%
S 2461
 
4.4%
O 2331
 
4.2%
H 2240
 
4.0%
T 2207
 
4.0%
C 2159
 
3.9%
I 2062
 
3.7%
Other values (40) 27949
50.1%
Common
ValueCountFrequency (%)
15681
55.7%
0 3614
 
12.8%
( 2854
 
10.1%
3 1883
 
6.7%
5 1177
 
4.2%
) 846
 
3.0%
4 809
 
2.9%
7 424
 
1.5%
2 295
 
1.0%
- 182
 
0.6%
Other values (6) 379
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83772
62.5%
Hangul 50142
37.4%
Number Forms 178
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15681
 
18.7%
E 4202
 
5.0%
A 3847
 
4.6%
0 3614
 
4.3%
R 3296
 
3.9%
N 3052
 
3.6%
( 2854
 
3.4%
S 2461
 
2.9%
O 2331
 
2.8%
H 2240
 
2.7%
Other values (54) 40194
48.0%
Hangul
ValueCountFrequency (%)
이 5429
 
10.8%
리 4956
 
9.9%
드 4951
 
9.9%
브 4940
 
9.9%
하 4939
 
9.9%
렉 2165
 
4.3%
타 1763
 
3.5%
스 1619
 
3.2%
서 1571
 
3.1%
그 1526
 
3.0%
Other values (101) 16283
32.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 118
66.3%
Ⅲ 60
33.7%

연료
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
하이브리드(휘발유+전기)
7954 
전기
1720 
하이브리드(LPG+전기)
 
131
수소
 
120
하이브리드(경유+전기)
 
74

Length

Max length13
Median length13
Mean length10.9686
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row하이브리드(휘발유+전기)
2nd row하이브리드(휘발유+전기)
3rd row하이브리드(휘발유+전기)
4th row하이브리드(휘발유+전기)
5th row하이브리드(휘발유+전기)

Common Values

ValueCountFrequency (%)
하이브리드(휘발유+전기) 7954
79.5%
전기 1720
 
17.2%
하이브리드(LPG+전기) 131
 
1.3%
수소 120
 
1.2%
하이브리드(경유+전기) 74
 
0.7%
하이브리드(CNG+전기) 1
 
< 0.1%

Length

2024-03-13T16:47:56.281360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T16:47:56.364996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
하이브리드(휘발유+전기 7954
79.5%
전기 1720
 
17.2%
하이브리드(lpg+전기 131
 
1.3%
수소 120
 
1.2%
하이브리드(경유+전기 74
 
0.7%
하이브리드(cng+전기 1
 
< 0.1%

최초등록일
Real number (ℝ)

Distinct2215
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20174951
Minimum20060728
Maximum20201231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T16:47:56.465947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060728
5-th percentile20120516
Q120160921
median20180907
Q320200206
95-th percentile20201113
Maximum20201231
Range140503
Interquartile range (IQR)39285

Descriptive statistics

Standard deviation26504.737
Coefficient of variation (CV)0.0013137448
Kurtosis0.98374876
Mean20174951
Median Absolute Deviation (MAD)19419
Skewness-1.2034084
Sum2.0174951 × 1011
Variance7.0250108 × 108
MonotonicityNot monotonic
2024-03-13T16:47:56.592690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200625 33
 
0.3%
20191127 32
 
0.3%
20201127 29
 
0.3%
20181130 29
 
0.3%
20191205 29
 
0.3%
20201130 26
 
0.3%
20181031 25
 
0.2%
20200914 25
 
0.2%
20201008 22
 
0.2%
20191210 22
 
0.2%
Other values (2205) 9728
97.3%
ValueCountFrequency (%)
20060728 1
< 0.1%
20060920 1
< 0.1%
20061030 1
< 0.1%
20061120 1
< 0.1%
20061122 1
< 0.1%
20061204 1
< 0.1%
20061205 1
< 0.1%
20070118 1
< 0.1%
20070305 1
< 0.1%
20070409 1
< 0.1%
ValueCountFrequency (%)
20201231 18
0.2%
20201230 12
0.1%
20201229 13
0.1%
20201228 10
0.1%
20201224 9
0.1%
20201223 16
0.2%
20201222 12
0.1%
20201221 18
0.2%
20201218 21
0.2%
20201217 19
0.2%

현소유자의출생년도
Real number (ℝ)

MISSING 

Distinct74
Distinct (%)1.0%
Missing2382
Missing (%)23.8%
Infinite0
Infinite (%)0.0%
Mean1972.2331
Minimum1911
Maximum2013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T16:47:56.713993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1911
5-th percentile1952
Q11964
median1973
Q31981
95-th percentile1989
Maximum2013
Range102
Interquartile range (IQR)17

Descriptive statistics

Standard deviation11.741371
Coefficient of variation (CV)0.005953338
Kurtosis-0.2264838
Mean1972.2331
Median Absolute Deviation (MAD)9
Skewness-0.37194705
Sum15024472
Variance137.85978
MonotonicityNot monotonic
2024-03-13T16:47:56.827818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1982 263
 
2.6%
1980 253
 
2.5%
1971 248
 
2.5%
1983 241
 
2.4%
1973 239
 
2.4%
1974 238
 
2.4%
1981 235
 
2.4%
1979 234
 
2.3%
1970 234
 
2.3%
1972 228
 
2.3%
Other values (64) 5205
52.0%
(Missing) 2382
23.8%
ValueCountFrequency (%)
1911 1
 
< 0.1%
1930 1
 
< 0.1%
1932 2
 
< 0.1%
1934 2
 
< 0.1%
1935 3
 
< 0.1%
1936 5
0.1%
1937 5
0.1%
1938 4
 
< 0.1%
1939 9
0.1%
1940 12
0.1%
ValueCountFrequency (%)
2013 1
 
< 0.1%
2012 1
 
< 0.1%
2011 4
 
< 0.1%
2002 1
 
< 0.1%
2000 1
 
< 0.1%
1999 1
 
< 0.1%
1998 2
 
< 0.1%
1997 5
0.1%
1996 8
0.1%
1995 11
0.1%

제원관리번호
Text

Distinct697
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T16:47:57.049535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters170000
Distinct characters22
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique157 ?
Unique (%)1.6%

Sample

1st rowA0810008300351211
2nd rowA0110005801511215
3rd row00920004100031220
4th rowA0810010801171318
5th row01020002500101214
ValueCountFrequency (%)
a0810010801171318 370
 
3.7%
01020006800001318 242
 
2.4%
07020000600021219 216
 
2.2%
a0110006100081217 154
 
1.5%
a0810010800451317 146
 
1.5%
a0110006100261219 131
 
1.3%
01020004500061317 126
 
1.3%
a0810010800691317 120
 
1.2%
a0810008700801315 119
 
1.2%
01020004500041316 113
 
1.1%
Other values (687) 8263
82.6%
2024-03-13T16:47:57.399457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 70601
41.5%
1 38616
22.7%
2 14934
 
8.8%
8 9168
 
5.4%
3 7307
 
4.3%
A 6093
 
3.6%
6 5905
 
3.5%
7 4795
 
2.8%
5 4553
 
2.7%
9 4475
 
2.6%
Other values (12) 3553
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 163759
96.3%
Uppercase Letter 6241
 
3.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 6093
97.6%
D 46
 
0.7%
R 27
 
0.4%
C 21
 
0.3%
G 19
 
0.3%
B 17
 
0.3%
J 10
 
0.2%
M 4
 
0.1%
E 1
 
< 0.1%
S 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 70601
43.1%
1 38616
23.6%
2 14934
 
9.1%
8 9168
 
5.6%
3 7307
 
4.5%
6 5905
 
3.6%
7 4795
 
2.9%
5 4553
 
2.8%
9 4475
 
2.7%
4 3405
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 163759
96.3%
Latin 6241
 
3.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 6093
97.6%
D 46
 
0.7%
R 27
 
0.4%
C 21
 
0.3%
G 19
 
0.3%
B 17
 
0.3%
J 10
 
0.2%
M 4
 
0.1%
E 1
 
< 0.1%
S 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
Common
ValueCountFrequency (%)
0 70601
43.1%
1 38616
23.6%
2 14934
 
9.1%
8 9168
 
5.6%
3 7307
 
4.5%
6 5905
 
3.6%
7 4795
 
2.9%
5 4553
 
2.8%
9 4475
 
2.7%
4 3405
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 170000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 70601
41.5%
1 38616
22.7%
2 14934
 
8.8%
8 9168
 
5.4%
3 7307
 
4.3%
A 6093
 
3.6%
6 5905
 
3.5%
7 4795
 
2.8%
5 4553
 
2.7%
9 4475
 
2.6%
Other values (12) 3553
 
2.1%

Interactions

2024-03-13T16:47:54.137739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T16:47:53.976829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T16:47:54.233379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T16:47:54.060435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T16:47:57.496982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연료최초등록일현소유자의출생년도
연료1.0000.5020.092
최초등록일0.5021.0000.123
현소유자의출생년도0.0920.1231.000
2024-03-13T16:47:57.566952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최초등록일현소유자의출생년도연료
최초등록일1.0000.0900.293
현소유자의출생년도0.0901.0000.052
연료0.2930.0521.000

Missing values

2024-03-13T16:47:54.329039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T16:47:54.428132image/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

기준년월사용본거지시읍면동_행정동기준차명연료최초등록일현소유자의출생년도제원관리번호
62727202012서울특별시 강서구 가양1동쏘나타 (SONATA) 하이브리드하이브리드(휘발유+전기)201207131962A0810008300351211
45987202012서울특별시 용산구 보광동K5 하이브리드하이브리드(휘발유+전기)201607141973A0110005801511215
22848202012서울특별시 서초구 방배3동볼보 XC40B4 AWD하이브리드(휘발유+전기)20200929197400920004100031220
40101202012서울특별시 강남구 대치1동그랜저 하이브리드하이브리드(휘발유+전기)201906141947A0810010801171318
5480202012서울특별시 구로구 개봉3동토요타 PRIUS하이브리드(휘발유+전기)20140919<NA>01020002500101214
8949202012서울특별시 서대문구 홍은2동그랜저 하이브리드(GRANDEUR H하이브리드(휘발유+전기)202010081963A0810012000471319
11263202012서울특별시 서대문구 홍은2동그랜저 하이브리드(GRANDEUR H하이브리드(휘발유+전기)202009291991A0810012000471319
15055202012서울특별시 강남구 역삼1동렉서스 NX300h하이브리드(휘발유+전기)20200429<NA>01020005500071319
35965202012서울특별시 성동구 금호4가동Model X Long Range전기20200819197907020000200161219
69769202012서울특별시 강남구 청담동렉서스 UX250h AWD하이브리드(휘발유+전기)20200529198401020007100021219
기준년월사용본거지시읍면동_행정동기준차명연료최초등록일현소유자의출생년도제원관리번호
51280202012서울특별시 영등포구 문래동그랜저 하이브리드(GRANDEUR H하이브리드(휘발유+전기)20201117<NA>A0810012000911320
11178202012서울특별시 성동구 금호4가동K7 하이브리드하이브리드(휘발유+전기)201811161959A0110006000601317
13230202012서울특별시 송파구 가락1동토요타 Camry Hybrid하이브리드(휘발유+전기)20150409196401020003800041314
5131202012서울특별시 광진구 자양3동니로 하이브리드하이브리드(휘발유+전기)201912231989A0110006100261219
657202012서울특별시 금천구 독산4동토요타 PRIUS하이브리드(휘발유+전기)20091029197601020002500001209
4323202012서울특별시 금천구 가산동쏘나타 하이브리드(SONATA HYB하이브리드(휘발유+전기)20150106<NA>A0810009800161214
11006202012서울특별시 서대문구 북아현동렉서스 CT200h하이브리드(휘발유+전기)20111031197501020003400011211
5448202012서울특별시 노원구 하계1동쏘나타(SONATA) 하이브리드하이브리드(휘발유+전기)201412011970A0810008301331214
10646202012서울특별시 마포구 용강동토요타 PRIUS하이브리드(휘발유+전기)20141209<NA>01020002500101214
38842202012서울특별시 마포구 신수동그랜저 하이브리드하이브리드(휘발유+전기)201904301989A0810010801171318

Duplicate rows

Most frequently occurring

기준년월사용본거지시읍면동_행정동기준차명연료최초등록일현소유자의출생년도제원관리번호# duplicates
3202012서울특별시 강남구 대치1동아반떼 Hybrid(AVANTE Hybrid)하이브리드(휘발유+전기)20200914<NA>A081001230025122010
56202012서울특별시 강남구 대치4동쏘울 EV전기20171206<NA>A011000550079121710
19202012서울특별시 강남구 대치2동쏘울 EV전기20180719<NA>A01100055007912179
18202012서울특별시 강남구 대치2동쏘울 EV전기20180718<NA>A01100055007912178
48202012서울특별시 강남구 대치4동쏘울 EV전기20170905<NA>A01100055007912178
54202012서울특별시 강남구 대치4동쏘울 EV전기20171204<NA>A01100055007912178
64202012서울특별시 강남구 대치4동아이오닉 일렉트릭(IONIQ ELEC전기20170818<NA>A08100105002912178
186202012서울특별시 영등포구 여의동D2C전기20191127<NA>D6J100001000034198
28202012서울특별시 강남구 대치2동코나 일렉트릭 (KONA ELECTRIC전기20201020<NA>A08100109011312197
52202012서울특별시 강남구 대치4동쏘울 EV전기20171121<NA>A01100055007912177