Overview

Dataset statistics

Number of variables7
Number of observations3002
Missing cells1658
Missing cells (%)7.9%
Duplicate rows56
Duplicate rows (%)1.9%
Total size in memory164.3 KiB
Average record size in memory56.0 B

Variable types

Text4
Boolean1
Categorical2

Dataset

Description관용차량 중 전기자동차 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=43X52GYZW0CW8UDF3S6I32475433&infSeq=1

Alerts

Dataset has 56 (1.9%) duplicate rowsDuplicates
전기차여부 is highly overall correlated with 데이터기준일자High correlation
구분 is highly overall correlated with 데이터기준일자High correlation
데이터기준일자 is highly overall correlated with 전기차여부 and 1 other fieldsHigh correlation
자동차등록번호 has 212 (7.1%) missing valuesMissing
비고 has 1446 (48.2%) missing valuesMissing

Reproduction

Analysis started2024-05-03 18:48:45.007073
Analysis finished2024-05-03 18:48:46.880262
Duration1.87 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관명
Text

Distinct67
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2024-05-03T18:48:47.087498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length3
Mean length4.2068621
Min length3

Characters and Unicode

Total characters12629
Distinct characters107
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)0.8%

Sample

1st row용인시
2nd row용인시
3rd row용인시
4th row용인시
5th row용인시
ValueCountFrequency (%)
경기도 698
18.7%
안양시 413
 
11.1%
고양시 245
 
6.6%
가평군 228
 
6.1%
연천군 227
 
6.1%
동두천시 157
 
4.2%
평택시 143
 
3.8%
과천시 129
 
3.5%
화성시 126
 
3.4%
남양주시 122
 
3.3%
Other values (66) 1246
33.4%
2024-05-03T18:48:47.703010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 2295
18.2%
양 894
 
7.1%
천 761
 
6.0%
732
 
5.8%
경 719
 
5.7%
도 703
 
5.6%
기 702
 
5.6%
안 596
 
4.7%
군 550
 
4.4%
평 433
 
3.4%
Other values (97) 4244
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11883
94.1%
Space Separator 732
 
5.8%
Decimal Number 14
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 2295
19.3%
양 894
 
7.5%
천 761
 
6.4%
경 719
 
6.1%
도 703
 
5.9%
기 702
 
5.9%
안 596
 
5.0%
군 550
 
4.6%
평 433
 
3.6%
주 255
 
2.1%
Other values (90) 3975
33.5%
Decimal Number
ValueCountFrequency (%)
2 4
28.6%
1 3
21.4%
3 3
21.4%
4 2
14.3%
5 1
 
7.1%
6 1
 
7.1%
Space Separator
ValueCountFrequency (%)
732
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11883
94.1%
Common 746
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 2295
19.3%
양 894
 
7.5%
천 761
 
6.4%
경 719
 
6.1%
도 703
 
5.9%
기 702
 
5.9%
안 596
 
5.0%
군 550
 
4.6%
평 433
 
3.6%
주 255
 
2.1%
Other values (90) 3975
33.5%
Common
ValueCountFrequency (%)
732
98.1%
2 4
 
0.5%
1 3
 
0.4%
3 3
 
0.4%
4 2
 
0.3%
5 1
 
0.1%
6 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11883
94.1%
ASCII 746
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 2295
19.3%
양 894
 
7.5%
천 761
 
6.4%
경 719
 
6.1%
도 703
 
5.9%
기 702
 
5.9%
안 596
 
5.0%
군 550
 
4.6%
평 433
 
3.6%
주 255
 
2.1%
Other values (90) 3975
33.5%
ASCII
ValueCountFrequency (%)
732
98.1%
2 4
 
0.5%
1 3
 
0.4%
3 3
 
0.4%
4 2
 
0.3%
5 1
 
0.1%
6 1
 
0.1%

차명
Text

Distinct514
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2024-05-03T18:48:48.221389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length6.8627582
Min length2

Characters and Unicode

Total characters20602
Distinct characters304
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique296 ?
Unique (%)9.9%

Sample

1st row아이오닉(일렉트릭)
2nd row아이오닉(일렉트릭)
3rd row아이오닉(일렉트릭)
4th rowZOE
5th rowZOE
ValueCountFrequency (%)
ev 408
 
8.7%
일렉트릭 288
 
6.2%
sm3 258
 
5.5%
아이오닉 234
 
5.0%
z.e 208
 
4.4%
니로 208
 
4.4%
1톤 184
 
3.9%
아이오닉5 179
 
3.8%
니로ev 106
 
2.3%
쏘울ev 91
 
1.9%
Other values (461) 2516
53.8%
2024-05-03T18:48:49.062802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1679
 
8.1%
E 1168
 
5.7%
V 831
 
4.0%
이 743
 
3.6%
오 513
 
2.5%
트 504
 
2.4%
아 503
 
2.4%
닉 479
 
2.3%
니 465
 
2.3%
렉 454
 
2.2%
Other values (294) 13263
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12993
63.1%
Uppercase Letter 3705
 
18.0%
Space Separator 1679
 
8.1%
Decimal Number 1222
 
5.9%
Other Punctuation 429
 
2.1%
Close Punctuation 163
 
0.8%
Open Punctuation 163
 
0.8%
Letter Number 120
 
0.6%
Lowercase Letter 73
 
0.4%
Dash Punctuation 29
 
0.1%
Other values (3) 26
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 743
 
5.7%
오 513
 
3.9%
트 504
 
3.9%
아 503
 
3.9%
닉 479
 
3.7%
니 465
 
3.6%
렉 454
 
3.5%
로 428
 
3.3%
스 423
 
3.3%
차 401
 
3.1%
Other values (231) 8080
62.2%
Uppercase Letter
ValueCountFrequency (%)
E 1168
31.5%
V 831
22.4%
I 411
 
11.1%
Z 287
 
7.7%
M 286
 
7.7%
S 284
 
7.7%
O 81
 
2.2%
C 60
 
1.6%
T 52
 
1.4%
L 50
 
1.3%
Other values (16) 195
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
l 28
38.4%
e 17
23.3%
v 6
 
8.2%
k 5
 
6.8%
c 3
 
4.1%
n 3
 
4.1%
s 2
 
2.7%
t 2
 
2.7%
u 2
 
2.7%
r 1
 
1.4%
Other values (4) 4
 
5.5%
Decimal Number
ValueCountFrequency (%)
3 400
32.7%
1 239
19.6%
5 230
18.8%
6 134
 
11.0%
4 77
 
6.3%
2 64
 
5.2%
0 39
 
3.2%
8 19
 
1.6%
7 12
 
1.0%
9 8
 
0.7%
Letter Number
ValueCountFrequency (%)
Ⅲ 70
58.3%
Ⅱ 49
40.8%
Ⅰ 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 428
99.8%
, 1
 
0.2%
Other Symbol
ValueCountFrequency (%)
㎥ 9
75.0%
㎡ 3
 
25.0%
Space Separator
ValueCountFrequency (%)
1679
100.0%
Close Punctuation
ValueCountFrequency (%)
) 163
100.0%
Open Punctuation
ValueCountFrequency (%)
( 163
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 13
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12993
63.1%
Latin 3898
 
18.9%
Common 3711
 
18.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 743
 
5.7%
오 513
 
3.9%
트 504
 
3.9%
아 503
 
3.9%
닉 479
 
3.7%
니 465
 
3.6%
렉 454
 
3.5%
로 428
 
3.3%
스 423
 
3.3%
차 401
 
3.1%
Other values (231) 8080
62.2%
Latin
ValueCountFrequency (%)
E 1168
30.0%
V 831
21.3%
I 411
 
10.5%
Z 287
 
7.4%
M 286
 
7.3%
S 284
 
7.3%
O 81
 
2.1%
Ⅲ 70
 
1.8%
C 60
 
1.5%
T 52
 
1.3%
Other values (33) 368
 
9.4%
Common
ValueCountFrequency (%)
1679
45.2%
. 428
 
11.5%
3 400
 
10.8%
1 239
 
6.4%
5 230
 
6.2%
) 163
 
4.4%
( 163
 
4.4%
6 134
 
3.6%
4 77
 
2.1%
2 64
 
1.7%
Other values (10) 134
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12993
63.1%
ASCII 7477
36.3%
Number Forms 120
 
0.6%
CJK Compat 12
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1679
22.5%
E 1168
15.6%
V 831
11.1%
. 428
 
5.7%
I 411
 
5.5%
3 400
 
5.3%
Z 287
 
3.8%
M 286
 
3.8%
S 284
 
3.8%
1 239
 
3.2%
Other values (48) 1464
19.6%
Hangul
ValueCountFrequency (%)
이 743
 
5.7%
오 513
 
3.9%
트 504
 
3.9%
아 503
 
3.9%
닉 479
 
3.7%
니 465
 
3.6%
렉 454
 
3.5%
로 428
 
3.3%
스 423
 
3.3%
차 401
 
3.1%
Other values (231) 8080
62.2%
Number Forms
ValueCountFrequency (%)
Ⅲ 70
58.3%
Ⅱ 49
40.8%
Ⅰ 1
 
0.8%
CJK Compat
ValueCountFrequency (%)
㎥ 9
75.0%
㎡ 3
 
25.0%

자동차등록번호
Text

MISSING 

Distinct2599
Distinct (%)93.2%
Missing212
Missing (%)7.1%
Memory size23.6 KiB
2024-05-03T18:48:49.680851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length7
Mean length7.0978495
Min length7

Characters and Unicode

Total characters19803
Distinct characters54
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2414 ?
Unique (%)86.5%

Sample

1st row17가5584
2nd row53구2982
3rd row10보7940
4th row63가8660
5th row63가8359
ValueCountFrequency (%)
15다 9
 
0.3%
40다 8
 
0.3%
17더33 6
 
0.2%
51모 5
 
0.2%
09저 4
 
0.1%
48저 3
 
0.1%
11나 3
 
0.1%
80누 3
 
0.1%
47부 3
 
0.1%
17더35 3
 
0.1%
Other values (2617) 2808
98.4%
2024-05-03T18:48:50.707033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 2045
10.3%
1 1808
9.1%
8 1784
9.0%
9 1711
8.6%
2 1700
8.6%
0 1682
8.5%
3 1588
8.0%
6 1510
7.6%
5 1505
7.6%
7 1487
7.5%
Other values (44) 2983
15.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16820
84.9%
Other Letter 2826
 
14.3%
Other Punctuation 74
 
0.4%
Space Separator 65
 
0.3%
Open Punctuation 9
 
< 0.1%
Close Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 137
 
4.8%
다 126
 
4.5%
더 125
 
4.4%
구 115
 
4.1%
루 112
 
4.0%
저 109
 
3.9%
러 107
 
3.8%
모 107
 
3.8%
호 107
 
3.8%
두 106
 
3.8%
Other values (30) 1675
59.3%
Decimal Number
ValueCountFrequency (%)
4 2045
12.2%
1 1808
10.7%
8 1784
10.6%
9 1711
10.2%
2 1700
10.1%
0 1682
10.0%
3 1588
9.4%
6 1510
9.0%
5 1505
8.9%
7 1487
8.8%
Other Punctuation
ValueCountFrequency (%)
# 74
100.0%
Space Separator
ValueCountFrequency (%)
65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16977
85.7%
Hangul 2826
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 137
 
4.8%
다 126
 
4.5%
더 125
 
4.4%
구 115
 
4.1%
루 112
 
4.0%
저 109
 
3.9%
러 107
 
3.8%
모 107
 
3.8%
호 107
 
3.8%
두 106
 
3.8%
Other values (30) 1675
59.3%
Common
ValueCountFrequency (%)
4 2045
12.0%
1 1808
10.6%
8 1784
10.5%
9 1711
10.1%
2 1700
10.0%
0 1682
9.9%
3 1588
9.4%
6 1510
8.9%
5 1505
8.9%
7 1487
8.8%
Other values (4) 157
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16977
85.7%
Hangul 2826
 
14.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 2045
12.0%
1 1808
10.6%
8 1784
10.5%
9 1711
10.1%
2 1700
10.0%
0 1682
9.9%
3 1588
9.4%
6 1510
8.9%
5 1505
8.9%
7 1487
8.8%
Other values (4) 157
 
0.9%
Hangul
ValueCountFrequency (%)
보 137
 
4.8%
다 126
 
4.5%
더 125
 
4.4%
구 115
 
4.1%
루 112
 
4.0%
저 109
 
3.9%
러 107
 
3.8%
모 107
 
3.8%
호 107
 
3.8%
두 106
 
3.8%
Other values (30) 1675
59.3%

전기차여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
True
1901 
False
1101 
ValueCountFrequency (%)
True 1901
63.3%
False 1101
36.7%
2024-05-03T18:48:51.061899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

구분
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
소유
1652 
<NA>
1019 
임차
 
149
자가출장용
 
98
위탁차량
 
56
Other values (3)
 
28

Length

Max length5
Median length2
Mean length2.8247835
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소유 1652
55.0%
<NA> 1019
33.9%
임차 149
 
5.0%
자가출장용 98
 
3.3%
위탁차량 56
 
1.9%
청소용 15
 
0.5%
사업용 11
 
0.4%
주정차단속 2
 
0.1%

Length

2024-05-03T18:48:51.437892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:48:51.778296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소유 1652
55.0%
na 1019
33.9%
임차 149
 
5.0%
자가출장용 98
 
3.3%
위탁차량 56
 
1.9%
청소용 15
 
0.5%
사업용 11
 
0.4%
주정차단속 2
 
0.1%

비고
Text

MISSING 

Distinct610
Distinct (%)39.2%
Missing1446
Missing (%)48.2%
Memory size23.6 KiB
2024-05-03T18:48:52.343471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length8.8836761
Min length3

Characters and Unicode

Total characters13823
Distinct characters115
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique372 ?
Unique (%)23.9%

Sample

1st row2017-12-12
2nd row2019-08-08
3rd row2019-08-08
4th row2022-03-02
5th row2022-03-02
ValueCountFrequency (%)
등록 174
 
9.2%
위탁차량 114
 
6.0%
’22.06.24 72
 
3.8%
중형전기 55
 
2.9%
5인승 44
 
2.3%
2017 37
 
1.9%
회계과 35
 
1.8%
10 19
 
1.0%
20190605 17
 
0.9%
11 16
 
0.8%
Other values (599) 1318
69.3%
2024-05-03T18:48:53.376969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2793
20.2%
0 2779
20.1%
1 1664
12.0%
- 1386
10.0%
. 446
 
3.2%
7 440
 
3.2%
6 370
 
2.7%
3 367
 
2.7%
8 366
 
2.6%
345
 
2.5%
Other values (105) 2867
20.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9714
70.3%
Other Letter 1786
 
12.9%
Dash Punctuation 1386
 
10.0%
Other Punctuation 490
 
3.5%
Space Separator 345
 
2.5%
Final Punctuation 100
 
0.7%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
록 174
 
9.7%
등 174
 
9.7%
위 115
 
6.4%
량 114
 
6.4%
차 114
 
6.4%
탁 114
 
6.4%
과 95
 
5.3%
기 68
 
3.8%
전 68
 
3.8%
형 64
 
3.6%
Other values (88) 686
38.4%
Decimal Number
ValueCountFrequency (%)
2 2793
28.8%
0 2779
28.6%
1 1664
17.1%
7 440
 
4.5%
6 370
 
3.8%
3 367
 
3.8%
8 366
 
3.8%
9 328
 
3.4%
5 317
 
3.3%
4 290
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 446
91.0%
, 42
 
8.6%
: 2
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 1386
100.0%
Space Separator
ValueCountFrequency (%)
345
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 100
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12037
87.1%
Hangul 1786
 
12.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
록 174
 
9.7%
등 174
 
9.7%
위 115
 
6.4%
량 114
 
6.4%
차 114
 
6.4%
탁 114
 
6.4%
과 95
 
5.3%
기 68
 
3.8%
전 68
 
3.8%
형 64
 
3.6%
Other values (88) 686
38.4%
Common
ValueCountFrequency (%)
2 2793
23.2%
0 2779
23.1%
1 1664
13.8%
- 1386
11.5%
. 446
 
3.7%
7 440
 
3.7%
6 370
 
3.1%
3 367
 
3.0%
8 366
 
3.0%
345
 
2.9%
Other values (7) 1081
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11937
86.4%
Hangul 1786
 
12.9%
Punctuation 100
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2793
23.4%
0 2779
23.3%
1 1664
13.9%
- 1386
11.6%
. 446
 
3.7%
7 440
 
3.7%
6 370
 
3.1%
3 367
 
3.1%
8 366
 
3.1%
345
 
2.9%
Other values (6) 981
 
8.2%
Hangul
ValueCountFrequency (%)
록 174
 
9.7%
등 174
 
9.7%
위 115
 
6.4%
량 114
 
6.4%
차 114
 
6.4%
탁 114
 
6.4%
과 95
 
5.3%
기 68
 
3.8%
전 68
 
3.8%
형 64
 
3.6%
Other values (88) 686
38.4%
Punctuation
ValueCountFrequency (%)
’ 100
100.0%

데이터기준일자
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2023-02-17
402 
2023-02-16
297 
2024-03-06
294 
2024-02-29
265 
2024-02-28
248 
Other values (19)
1496 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-02-15
2nd row2023-02-15
3rd row2023-02-15
4th row2023-02-15
5th row2023-02-15

Common Values

ValueCountFrequency (%)
2023-02-17 402
13.4%
2023-02-16 297
9.9%
2024-03-06 294
9.8%
2024-02-29 265
 
8.8%
2024-02-28 248
 
8.3%
2024-02-20 192
 
6.4%
2024-04-09 157
 
5.2%
2023-12-26 155
 
5.2%
2023-06-30 143
 
4.8%
2023-08-09 129
 
4.3%
Other values (14) 720
24.0%

Length

2024-05-03T18:48:53.700214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-02-17 402
13.4%
2023-02-16 297
9.9%
2024-03-06 294
9.8%
2024-02-29 265
 
8.8%
2024-02-28 248
 
8.3%
2024-02-20 192
 
6.4%
2024-04-09 157
 
5.2%
2023-12-26 155
 
5.2%
2023-06-30 143
 
4.8%
2023-08-09 129
 
4.3%
Other values (14) 720
24.0%

Correlations

2024-05-03T18:48:53.851311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관명전기차여부구분데이터기준일자
기관명1.0000.9500.8990.998
전기차여부0.9501.0000.3300.893
구분0.8990.3301.0000.822
데이터기준일자0.9980.8930.8221.000
2024-05-03T18:48:54.107167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분전기차여부데이터기준일자
구분1.0000.3530.548
전기차여부0.3531.0000.756
데이터기준일자0.5480.7561.000
2024-05-03T18:48:54.369590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전기차여부구분데이터기준일자
전기차여부1.0000.3530.756
구분0.3531.0000.548
데이터기준일자0.7560.5481.000

Missing values

2024-05-03T18:48:46.182372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T18:48:46.424065image/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.
2024-05-03T18:48:46.774424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

기관명차명자동차등록번호전기차여부구분비고데이터기준일자
0용인시아이오닉(일렉트릭)17가5584Y소유2017-12-122023-02-15
1용인시아이오닉(일렉트릭)53구2982Y소유2019-08-082023-02-15
2용인시아이오닉(일렉트릭)10보7940Y소유2019-08-082023-02-15
3용인시ZOE63가8660Y소유2022-03-022023-02-15
4용인시ZOE63가8359Y소유2022-03-022023-02-15
5용인시코나 일렉트릭53구7417Y소유2019-06-172023-02-15
6용인시코나 일렉트릭53구7451Y소유2019-06-172023-02-15
7용인시코나 일렉트릭49구4940Y소유2019-06-172023-02-15
8용인시봉고Ⅲ 1톤 EV94구0354Y소유2021-09-142023-02-15
9용인시니로 플러스09주1934Y소유2022-08-302023-02-15
기관명차명자동차등록번호전기차여부구분비고데이터기준일자
2992동두천시포터285노6838N<NA><NA>2024-04-09
2993동두천시봉고3(4륜구동)85노6872N<NA><NA>2024-04-09
2994동두천시코란도스포츠85누2484N<NA><NA>2024-04-09
2995동두천시코란도스포츠85누2535N<NA><NA>2024-04-09
2996동두천시봉고386루3614N<NA><NA>2024-04-09
2997동두천시마이티86루3684N<NA><NA>2024-04-09
2998동두천시봉고388나5401N<NA><NA>2024-04-09
2999동두천시마이티88나5471N<NA><NA>2024-04-09
3000동두천시봉고3 1톤 EV89무2392Y<NA><NA>2024-04-09
3001동두천시포터289수4649N<NA><NA>2024-04-09

Duplicate rows

Most frequently occurring

기관명차명자동차등록번호전기차여부구분비고데이터기준일자# duplicates
0경기도니로 EV<NA>Y<NA><NA>2023-02-162
1경기도볼트 EV<NA>Y<NA><NA>2023-02-162
2경기도블로온<NA>Y<NA><NA>2023-02-162
3경기도아이오닉 EV<NA>Y<NA><NA>2023-02-162
4경기도아이오닉5<NA>Y<NA><NA>2023-02-162
5경기도아이오닉EV<NA>Y<NA><NA>2023-02-162
6경기도코나 EV<NA>Y<NA><NA>2023-02-162
7경기도포터Ⅱ EV<NA>Y<NA><NA>2023-02-162
8경기도 북부청사EV616하7087Y임차’22.06.24.2023-02-162
9경기도 북부청사EV616하7088Y임차’22.06.24.2023-02-162