Overview

Dataset statistics

Number of variables16
Number of observations300
Missing cells285
Missing cells (%)5.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory38.2 KiB
Average record size in memory130.4 B

Variable types

Categorical8
DateTime6
Numeric2

Dataset

Description자동차관리법 및 자동차종합검사 시행등에 관한 규칙에 따라 한국교통안전공단(KOTSA)에서 관리하는 자동차검사 자료입니다.
URLhttps://www.data.go.kr/data/15088041/fileData.do

Alerts

매연(SMOKE)기준 is highly overall correlated with 검사타입코드 and 1 other fieldsHigh correlation
차종 is highly overall correlated with 공차중량기준최고 and 2 other fieldsHigh correlation
연료 is highly overall correlated with 검사타입코드 and 1 other fieldsHigh correlation
적용법령 is highly overall correlated with 검사타입코드 and 6 other fieldsHigh correlation
일산화탄소(CO)기준 is highly overall correlated with 공차중량기준최소 and 5 other fieldsHigh correlation
검사타입코드 is highly overall correlated with 연료 and 6 other fieldsHigh correlation
탄화수소(HC)기준 is highly overall correlated with 공차중량기준최소 and 5 other fieldsHigh correlation
질소산화물(NOX)기준 is highly overall correlated with 공차중량기준최소 and 5 other fieldsHigh correlation
공차중량기준최소 is highly overall correlated with 일산화탄소(CO)기준 and 2 other fieldsHigh correlation
공차중량기준최고 is highly overall correlated with 차종 and 3 other fieldsHigh correlation
검사타입코드 is highly imbalanced (78.9%)Imbalance
적용법령 is highly imbalanced (78.9%)Imbalance
매연(SMOKE)기준 is highly imbalanced (88.8%)Imbalance
제작일자기준시작일 has 32 (10.7%) missing valuesMissing
제작일자기준종료일 has 103 (34.3%) missing valuesMissing
적용일자기준종료일 has 150 (50.0%) missing valuesMissing
공차중량기준최소 has 125 (41.7%) zerosZeros

Reproduction

Analysis started2023-12-12 21:14:04.637125
Analysis finished2023-12-12 21:14:06.357970
Duration1.72 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

검사타입코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
부하검사(ASM-Idling)
290 
부하검사(KD-147)
 
10

Length

Max length16
Median length16
Mean length15.866667
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부하검사(ASM-Idling)
2nd row부하검사(ASM-Idling)
3rd row부하검사(ASM-Idling)
4th row부하검사(ASM-Idling)
5th row부하검사(ASM-Idling)

Common Values

ValueCountFrequency (%)
부하검사(ASM-Idling) 290
96.7%
부하검사(KD-147) 10
 
3.3%

Length

2023-12-13T06:14:06.430440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:14:06.559073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부하검사(asm-idling 290
96.7%
부하검사(kd-147 10
 
3.3%

연료
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
휘발유(무연)
58 
휘발유(유연)
57 
휘발유
52 
알코올
52 
하이브리드(휘발유+전기)
45 
Other values (4)
36 

Length

Max length13
Median length12
Mean length6.5666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row휘발유
2nd row휘발유
3rd row휘발유
4th row휘발유
5th row알코올

Common Values

ValueCountFrequency (%)
휘발유(무연) 58
19.3%
휘발유(유연) 57
19.0%
휘발유 52
17.3%
알코올 52
17.3%
하이브리드(휘발유+전기) 45
15.0%
엘피지 14
 
4.7%
하이브리드(LPG+전기) 12
 
4.0%
경유 5
 
1.7%
하이브리드(경유+전기) 5
 
1.7%

Length

2023-12-13T06:14:06.704571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:14:06.823246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휘발유(무연 58
19.3%
휘발유(유연 57
19.0%
휘발유 52
17.3%
알코올 52
17.3%
하이브리드(휘발유+전기 45
15.0%
엘피지 14
 
4.7%
하이브리드(lpg+전기 12
 
4.0%
경유 5
 
1.7%
하이브리드(경유+전기 5
 
1.7%

적용법령
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
대기환경보전법
290 
대기관리권역법
 
10

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대기환경보전법 290
96.7%
대기관리권역법 10
 
3.3%

Length

2023-12-13T06:14:06.983009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:14:07.104861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기환경보전법 290
96.7%
대기관리권역법 10
 
3.3%

차종
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
승용중형
44 
승용소형
43 
승용대형
42 
승용경형
21 
승합경형
21 
Other values (9)
129 

Length

Max length4
Median length4
Mean length3.9666667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row승용경형
2nd row승합경형
3rd row화물경형
4th row특수경형
5th row승용경형

Common Values

ValueCountFrequency (%)
승용중형 44
14.7%
승용소형 43
14.3%
승용대형 42
14.0%
승용경형 21
7.0%
승합경형 21
7.0%
화물경형 21
7.0%
특수경형 21
7.0%
승합대형 13
 
4.3%
화물중형 13
 
4.3%
화물대형 13
 
4.3%
Other values (4) 48
16.0%

Length

2023-12-13T06:14:07.236083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
승용중형 44
14.7%
승용소형 43
14.3%
승용대형 42
14.0%
승용경형 21
7.0%
승합경형 21
7.0%
화물경형 21
7.0%
특수경형 21
7.0%
승합대형 13
 
4.3%
화물중형 13
 
4.3%
화물대형 13
 
4.3%
Other values (4) 48
16.0%

제작일자기준시작일
Date

MISSING 

Distinct7
Distinct (%)2.6%
Missing32
Missing (%)10.7%
Memory size2.5 KiB
Minimum1988-01-01 00:00:00
Maximum2008-01-01 00:00:00
2023-12-13T06:14:07.357933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:07.474804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

제작일자기준종료일
Date

MISSING 

Distinct6
Distinct (%)3.0%
Missing103
Missing (%)34.3%
Memory size2.5 KiB
Minimum1992-12-31 00:00:00
Maximum2007-12-31 00:00:00
2023-12-13T06:14:07.580765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:07.698620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)

적용일자기준시작일
Date

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2010-04-01 00:00:00
Maximum2015-01-01 00:00:00
2023-12-13T06:14:07.796465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:07.917047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

적용일자기준종료일
Date

MISSING 

Distinct4
Distinct (%)2.7%
Missing150
Missing (%)50.0%
Memory size2.5 KiB
Minimum2011-12-31 00:00:00
Maximum2100-12-31 00:00:00
2023-12-13T06:14:08.028625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:08.131051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

공차중량기준최소
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1149
Minimum0
Maximum3250
Zeros125
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-13T06:14:08.249895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1200
Q32250
95-th percentile3000
Maximum3250
Range3250
Interquartile range (IQR)2250

Descriptive statistics

Standard deviation1090.7634
Coefficient of variation (CV)0.94931544
Kurtosis-1.4525901
Mean1149
Median Absolute Deviation (MAD)1200
Skewness0.23101387
Sum344700
Variance1189764.9
MonotonicityNot monotonic
2023-12-13T06:14:08.679412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 125
41.7%
2500 30
 
10.0%
1000 19
 
6.3%
1200 17
 
5.7%
1400 17
 
5.7%
2250 17
 
5.7%
1600 15
 
5.0%
1800 15
 
5.0%
2000 15
 
5.0%
3000 15
 
5.0%
Other values (2) 15
 
5.0%
ValueCountFrequency (%)
0 125
41.7%
1000 19
 
6.3%
1200 17
 
5.7%
1400 17
 
5.7%
1600 15
 
5.0%
1800 15
 
5.0%
2000 15
 
5.0%
2250 17
 
5.7%
2500 30
 
10.0%
2750 13
 
4.3%
ValueCountFrequency (%)
3250 2
 
0.7%
3000 15
5.0%
2750 13
4.3%
2500 30
10.0%
2250 17
5.7%
2000 15
5.0%
1800 15
5.0%
1600 15
5.0%
1400 17
5.7%
1200 17
5.7%

공차중량기준최고
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3701247.5
Minimum999
Maximum9999999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-13T06:14:08.820430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum999
5-th percentile999
Q11599
median2749
Q39999999
95-th percentile9999999
Maximum9999999
Range9999000
Interquartile range (IQR)9998400

Descriptive statistics

Standard deviation4835151.6
Coefficient of variation (CV)1.3063573
Kurtosis-1.7185717
Mean3701247.5
Median Absolute Deviation (MAD)1550
Skewness0.54123033
Sum1.1103742 × 109
Variance2.3378691 × 1013
MonotonicityNot monotonic
2023-12-13T06:14:08.970133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
9999999 111
37.0%
999 31
 
10.3%
2749 30
 
10.0%
1199 19
 
6.3%
1399 17
 
5.7%
1599 17
 
5.7%
2499 17
 
5.7%
1799 15
 
5.0%
1999 15
 
5.0%
3249 15
 
5.0%
ValueCountFrequency (%)
999 31
10.3%
1199 19
6.3%
1399 17
5.7%
1599 17
5.7%
1799 15
5.0%
1999 15
5.0%
2499 17
5.7%
2749 30
10.0%
2999 13
4.3%
3249 15
5.0%
ValueCountFrequency (%)
9999999 111
37.0%
3249 15
 
5.0%
2999 13
 
4.3%
2749 30
 
10.0%
2499 17
 
5.7%
1999 15
 
5.0%
1799 15
 
5.0%
1599 17
 
5.7%
1399 17
 
5.7%
1199 19
 
6.3%

일산화탄소(CO)기준
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
1.24
30 
1.83
29 
1
20 
1.38
 
17
4.2
 
16
Other values (20)
188 

Length

Max length4
Median length4
Mean length3.52
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4.2
2nd row4.2
3rd row4.2
4th row4.2
5th row4.2

Common Values

ValueCountFrequency (%)
1.24 30
 
10.0%
1.83 29
 
9.7%
1 20
 
6.7%
1.38 17
 
5.7%
4.2 16
 
5.3%
2.4 16
 
5.3%
1.2 16
 
5.3%
1.05 15
 
5.0%
1.08 15
 
5.0%
0.87 15
 
5.0%
Other values (15) 111
37.0%

Length

2023-12-13T06:14:09.118082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1.24 30
 
10.3%
1.83 29
 
10.0%
1 20
 
6.9%
1.38 17
 
5.9%
4.2 16
 
5.5%
2.4 16
 
5.5%
1.2 16
 
5.5%
0.94 15
 
5.2%
1.47 15
 
5.2%
1.21 15
 
5.2%
Other values (14) 101
34.8%

탄화수소(HC)기준
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
100
30 
210
30 
110
30 
180
20 
230
19 
Other values (17)
171 

Length

Max length4
Median length3
Mean length3
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1090
2nd row1090
3rd row1090
4th row1090
5th row1090

Common Values

ValueCountFrequency (%)
100 30
 
10.0%
210 30
 
10.0%
110 30
 
10.0%
180 20
 
6.7%
230 19
 
6.3%
130 17
 
5.7%
1090 16
 
5.3%
390 16
 
5.3%
120 15
 
5.0%
140 15
 
5.0%
Other values (12) 92
30.7%

Length

2023-12-13T06:14:09.254509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
100 30
 
10.3%
110 30
 
10.3%
210 30
 
10.3%
180 20
 
6.9%
230 19
 
6.6%
130 17
 
5.9%
1090 16
 
5.5%
390 16
 
5.5%
170 15
 
5.2%
280 15
 
5.2%
Other values (11) 82
28.3%

질소산화물(NOX)기준
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
1800
30 
950
30 
1240
20 
1080
 
17
810
 
17
Other values (19)
186 

Length

Max length4
Median length4
Mean length3.6
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2110
2nd row2110
3rd row2110
4th row2110
5th row2110

Common Values

ValueCountFrequency (%)
1800 30
 
10.0%
950 30
 
10.0%
1240 20
 
6.7%
1080 17
 
5.7%
810 17
 
5.7%
2110 16
 
5.3%
1640 16
 
5.3%
1310 15
 
5.0%
1010 15
 
5.0%
840 15
 
5.0%
Other values (14) 109
36.3%

Length

2023-12-13T06:14:09.425144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1800 30
 
10.3%
950 30
 
10.3%
1240 20
 
6.9%
1080 17
 
5.9%
810 17
 
5.9%
2110 16
 
5.5%
1640 16
 
5.5%
930 15
 
5.2%
1590 15
 
5.2%
1160 15
 
5.2%
Other values (13) 99
34.1%

매연(SMOKE)기준
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
290 
40
 
2
30
 
2
20
 
2
35
 
2

Length

Max length2
Median length1
Mean length1.0333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
290
96.7%
40 2
 
0.7%
30 2
 
0.7%
20 2
 
0.7%
35 2
 
0.7%
25 2
 
0.7%

Length

2023-12-13T06:14:09.613047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:14:09.731718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
40 2
20.0%
30 2
20.0%
20 2
20.0%
35 2
20.0%
25 2
20.0%

입력일자
Date

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2010-04-13 00:00:00
Maximum2010-04-24 00:00:00
2023-12-13T06:14:09.839118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:09.953279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

수정일자
Date

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2010-04-13 00:00:00
Maximum2016-01-14 00:00:00
2023-12-13T06:14:10.054686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:10.188704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

Interactions

2023-12-13T06:14:05.627077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:05.441521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:05.737033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:14:05.524486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:14:10.310828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
검사타입코드연료적용법령차종제작일자기준시작일제작일자기준종료일적용일자기준시작일적용일자기준종료일공차중량기준최소공차중량기준최고일산화탄소(CO)기준탄화수소(HC)기준질소산화물(NOX)기준매연(SMOKE)기준입력일자수정일자
검사타입코드1.0001.0000.9971.0000.8040.9790.0001.0000.2130.3181.0001.0001.0001.0001.0001.000
연료1.0001.0001.0000.6130.5770.6090.0000.7200.2140.2740.8080.7790.8100.6840.9340.934
적용법령0.9971.0001.0001.0000.8040.9790.0001.0000.2130.3181.0001.0001.0001.0001.0001.000
차종1.0000.6131.0001.0000.9090.7070.1960.9800.7070.9780.8330.8130.8200.6660.8710.880
제작일자기준시작일0.8040.5770.8040.9091.0000.9910.2040.9190.5980.5990.9310.9040.9100.9160.7340.743
제작일자기준종료일0.9790.6090.9790.7070.9911.0000.0000.7090.3370.8190.9490.9170.9200.9180.9790.979
적용일자기준시작일0.0000.0000.0000.1960.2040.0001.0001.0000.287NaN0.7230.7720.7670.0000.0000.000
적용일자기준종료일1.0000.7201.0000.9800.9190.7091.0001.0000.4820.5020.9250.9951.0000.7230.8761.000
공차중량기준최소0.2130.2140.2130.7070.5980.3370.2870.4821.0000.9921.0000.9821.0000.0000.3480.378
공차중량기준최고0.3180.2740.3180.9780.5990.819NaN0.5020.9921.0001.0000.9981.0000.2680.2550.276
일산화탄소(CO)기준1.0000.8081.0000.8330.9310.9490.7230.9251.0001.0001.0000.9990.9990.6531.0001.000
탄화수소(HC)기준1.0000.7791.0000.8130.9040.9170.7720.9950.9820.9980.9991.0000.9990.6591.0000.983
질소산화물(NOX)기준1.0000.8101.0000.8200.9100.9200.7671.0001.0001.0000.9990.9991.0000.7041.0001.000
매연(SMOKE)기준1.0000.6841.0000.6660.9160.9180.0000.7230.0000.2680.6530.6590.7041.0000.9390.939
입력일자1.0000.9341.0000.8710.7340.9790.0000.8760.3480.2551.0001.0001.0000.9391.0000.999
수정일자1.0000.9341.0000.8800.7430.9790.0001.0000.3780.2761.0000.9831.0000.9390.9991.000
2023-12-13T06:14:10.550215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
매연(SMOKE)기준차종연료적용법령일산화탄소(CO)기준검사타입코드탄화수소(HC)기준질소산화물(NOX)기준
매연(SMOKE)기준1.0000.3990.4200.9930.3490.9930.3630.354
차종0.3991.0000.3110.9800.4300.9800.4130.415
연료0.4200.3111.0000.9880.4600.9880.4330.459
적용법령0.9930.9800.9881.0000.9610.9480.9660.962
일산화탄소(CO)기준0.3490.4300.4600.9611.0000.9610.9760.981
검사타입코드0.9930.9800.9880.9480.9611.0000.9660.962
탄화수소(HC)기준0.3630.4130.4330.9660.9760.9661.0000.978
질소산화물(NOX)기준0.3540.4150.4590.9620.9810.9620.9781.000
2023-12-13T06:14:10.694342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공차중량기준최소공차중량기준최고검사타입코드연료적용법령차종일산화탄소(CO)기준탄화수소(HC)기준질소산화물(NOX)기준매연(SMOKE)기준
공차중량기준최소1.000-0.1460.1580.1060.1580.4040.9700.8880.9720.000
공차중량기준최고-0.1461.0000.2160.2730.2160.8620.9610.8680.8910.205
검사타입코드0.1580.2161.0000.9880.9480.9800.9610.9660.9620.993
연료0.1060.2730.9881.0000.9880.3110.4600.4330.4590.420
적용법령0.1580.2160.9480.9881.0000.9800.9610.9660.9620.993
차종0.4040.8620.9800.3110.9801.0000.4300.4130.4150.399
일산화탄소(CO)기준0.9700.9610.9610.4600.9610.4301.0000.9760.9810.349
탄화수소(HC)기준0.8880.8680.9660.4330.9660.4130.9761.0000.9780.363
질소산화물(NOX)기준0.9720.8910.9620.4590.9620.4150.9810.9781.0000.354
매연(SMOKE)기준0.0000.2050.9930.4200.9930.3990.3490.3630.3541.000

Missing values

2023-12-13T06:14:05.903777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:14:06.127468image/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.
2023-12-13T06:14:06.274414image/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

검사타입코드연료적용법령차종제작일자기준시작일제작일자기준종료일적용일자기준시작일적용일자기준종료일공차중량기준최소공차중량기준최고일산화탄소(CO)기준탄화수소(HC)기준질소산화물(NOX)기준매연(SMOKE)기준입력일자수정일자
0부하검사(ASM-Idling)휘발유대기환경보전법승용경형<NA>1997-12-312010-04-01<NA>099999994.2109021102010-04-132010-04-13
1부하검사(ASM-Idling)휘발유대기환경보전법승합경형<NA>1997-12-312010-04-01<NA>099999994.2109021102010-04-132010-04-13
2부하검사(ASM-Idling)휘발유대기환경보전법화물경형<NA>1997-12-312010-04-01<NA>099999994.2109021102010-04-132010-04-13
3부하검사(ASM-Idling)휘발유대기환경보전법특수경형<NA>1997-12-312010-04-01<NA>099999994.2109021102010-04-132010-04-13
4부하검사(ASM-Idling)알코올대기환경보전법승용경형<NA>1997-12-312010-04-01<NA>099999994.2109021102010-04-132010-04-13
5부하검사(ASM-Idling)알코올대기환경보전법승합경형<NA>1997-12-312010-04-01<NA>099999994.2109021102010-04-132010-04-13
6부하검사(ASM-Idling)알코올대기환경보전법화물경형<NA>1997-12-312010-04-01<NA>099999994.2109021102010-04-132010-04-13
7부하검사(ASM-Idling)알코올대기환경보전법특수경형<NA>1997-12-312010-04-01<NA>099999994.2109021102010-04-132010-04-13
8부하검사(ASM-Idling)휘발유(유연)대기환경보전법승용경형<NA>1997-12-312010-04-01<NA>099999994.2109021102010-04-132010-04-13
9부하검사(ASM-Idling)휘발유(유연)대기환경보전법승합경형<NA>1997-12-312010-04-01<NA>099999994.2109021102010-04-132010-04-13
검사타입코드연료적용법령차종제작일자기준시작일제작일자기준종료일적용일자기준시작일적용일자기준종료일공차중량기준최소공차중량기준최고일산화탄소(CO)기준탄화수소(HC)기준질소산화물(NOX)기준매연(SMOKE)기준입력일자수정일자
290부하검사(ASM-Idling)엘피지대기환경보전법승용중형<NA>1997-12-312010-04-012014-12-3109992.3837023902010-04-132010-04-13
291부하검사(ASM-Idling)하이브리드(LPG+전기)대기환경보전법승용중형<NA>1997-12-312010-04-012014-12-3109992.3837023902010-04-132010-04-13
292부하검사(ASM-Idling)엘피지대기환경보전법승용소형<NA>1997-12-312010-04-012014-12-31100011991.9130019102010-04-132010-04-13
293부하검사(ASM-Idling)엘피지대기환경보전법승용대형<NA>1997-12-312010-04-012014-12-31100011991.9130019102010-04-132010-04-13
294부하검사(ASM-Idling)하이브리드(LPG+전기)대기환경보전법승용소형<NA>1997-12-312010-04-012014-12-31100011991.9130019102010-04-132010-04-13
295부하검사(ASM-Idling)하이브리드(LPG+전기)대기환경보전법승용대형<NA>1997-12-312010-04-012014-12-31100011991.9130019102010-04-132010-04-13
296부하검사(ASM-Idling)엘피지대기환경보전법승용중형<NA>1997-12-312010-04-012014-12-31120013991.5725015802010-04-132010-04-13
297부하검사(ASM-Idling)하이브리드(LPG+전기)대기환경보전법승용중형<NA>1997-12-312010-04-012014-12-31120013991.5725015802010-04-132010-04-13
298부하검사(ASM-Idling)엘피지대기환경보전법승용소형<NA>1997-12-312010-04-012014-12-31140015991.422014002010-04-132010-04-13
299부하검사(ASM-Idling)엘피지대기환경보전법승용대형<NA>1997-12-312010-04-012014-12-31140015991.422014002010-04-132010-04-13