Overview

Dataset statistics

Number of variables29
Number of observations5079
Missing cells61854
Missing cells (%)42.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory247.0 B

Variable types

Text4
Categorical8
DateTime6
Unsupported9
Numeric2

Dataset

Description파일 다운로드
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-21832/F/1/datasetView.do

Alerts

승인자명 has constant value ""Constant
등록자명 has constant value ""Constant
수정자명 has constant value ""Constant
관심차량구분분류명 is highly imbalanced (94.2%)Imbalance
대포차여부 is highly imbalanced (91.8%)Imbalance
상황전파일자 has 1996 (39.3%) missing valuesMissing
상황전파시간 has 1996 (39.3%) missing valuesMissing
승인일시 has 5077 (> 99.9%) missing valuesMissing
승인자명 has 5077 (> 99.9%) missing valuesMissing
취소완료일시 has 1997 (39.3%) missing valuesMissing
취소사유완료처리구분명 has 5079 (100.0%) missing valuesMissing
차량이미지파일명 has 5079 (100.0%) missing valuesMissing
체납전송여부 has 5079 (100.0%) missing valuesMissing
과태료전송여부 has 5079 (100.0%) missing valuesMissing
수배전송여부 has 5079 (100.0%) missing valuesMissing
기타사유 has 5079 (100.0%) missing valuesMissing
완료수정사유 has 5079 (100.0%) missing valuesMissing
완료수정자아이디 has 5079 (100.0%) missing valuesMissing
완료수정일시 has 5079 (100.0%) missing valuesMissing
이벤트발생번호 has unique valuesUnique
차량인식결과순번 has unique valuesUnique
취소사유완료처리구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
차량이미지파일명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
체납전송여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
과태료전송여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수배전송여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기타사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
완료수정사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
완료수정자아이디 is an unsupported type, check if it needs cleaning or further analysisUnsupported
완료수정일시 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 05:12:15.912917
Analysis finished2023-12-11 05:12:16.872186
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

이벤트발생번호
Text

UNIQUE 

Distinct5079
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
2023-12-11T14:12:17.094235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters121896
Distinct characters15
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

Unique5079 ?
Unique (%)100.0%

Sample

1st rowLPRUM0020200106084808823
2nd rowLPRUM0020200106093214248
3rd rowLPRUM0020200106095154324
4th rowLPRUM0020200106104927490
5th rowLPRUM0020200106110045214
ValueCountFrequency (%)
lprum0020200106084808823 1
 
< 0.1%
lprum0020200531121327564 1
 
< 0.1%
lprum0020200531105756204 1
 
< 0.1%
lprum0020200531100632176 1
 
< 0.1%
lprum0020200531100209640 1
 
< 0.1%
lprum0020200531080910054 1
 
< 0.1%
lprum0020200529200531166 1
 
< 0.1%
lprum0020200529185608859 1
 
< 0.1%
lprum0020200529184612054 1
 
< 0.1%
lprum0020200529183301231 1
 
< 0.1%
Other values (5069) 5069
99.8%
2023-12-11T14:12:17.671410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 32989
27.1%
2 17902
14.7%
1 11955
 
9.8%
3 6016
 
4.9%
4 5849
 
4.8%
5 5836
 
4.8%
L 5079
 
4.2%
P 5079
 
4.2%
R 5079
 
4.2%
U 5079
 
4.2%
Other values (5) 21033
17.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96501
79.2%
Uppercase Letter 25395
 
20.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 32989
34.2%
2 17902
18.6%
1 11955
 
12.4%
3 6016
 
6.2%
4 5849
 
6.1%
5 5836
 
6.0%
6 4157
 
4.3%
7 4135
 
4.3%
8 3889
 
4.0%
9 3773
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
L 5079
20.0%
P 5079
20.0%
R 5079
20.0%
U 5079
20.0%
M 5079
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96501
79.2%
Latin 25395
 
20.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 32989
34.2%
2 17902
18.6%
1 11955
 
12.4%
3 6016
 
6.2%
4 5849
 
6.1%
5 5836
 
6.0%
6 4157
 
4.3%
7 4135
 
4.3%
8 3889
 
4.0%
9 3773
 
3.9%
Latin
ValueCountFrequency (%)
L 5079
20.0%
P 5079
20.0%
R 5079
20.0%
U 5079
20.0%
M 5079
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 121896
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 32989
27.1%
2 17902
14.7%
1 11955
 
9.8%
3 6016
 
4.9%
4 5849
 
4.8%
5 5836
 
4.8%
L 5079
 
4.2%
P 5079
 
4.2%
R 5079
 
4.2%
U 5079
 
4.2%
Other values (5) 21033
17.3%

관심차량구분분류명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
3
5023 
5
 
52
30
 
4

Length

Max length2
Median length1
Mean length1.0007876
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 5023
98.9%
5 52
 
1.0%
30 4
 
0.1%

Length

2023-12-11T14:12:17.908181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:12:18.086451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 5023
98.9%
5 52
 
1.0%
30 4
 
0.1%

상황전파단계분류명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
90
3082 
10
1997 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10
2nd row10
3rd row90
4th row10
5th row10

Common Values

ValueCountFrequency (%)
90 3082
60.7%
10 1997
39.3%

Length

2023-12-11T14:12:18.245060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:12:18.395824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
90 3082
60.7%
10 1997
39.3%

상황전파일자
Date

MISSING 

Distinct283
Distinct (%)9.2%
Missing1996
Missing (%)39.3%
Memory size39.8 KiB
Minimum2020-01-01 00:00:00
Maximum2020-10-15 00:00:00
2023-12-11T14:12:18.567332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:12:18.798038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상황전파시간
Text

MISSING 

Distinct2982
Distinct (%)96.7%
Missing1996
Missing (%)39.3%
Memory size39.8 KiB
2023-12-11T14:12:19.314052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9957833
Min length5

Characters and Unicode

Total characters24651
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2883 ?
Unique (%)93.5%

Sample

1st row09:51:48
2nd row11:19:36
3rd row11:24:09
4th row11:45:08
5th row12:11:48
ValueCountFrequency (%)
08:19:42 3
 
0.1%
14:07:34 3
 
0.1%
14:55:11 2
 
0.1%
10:10:24 2
 
0.1%
13:38:39 2
 
0.1%
10:32:47 2
 
0.1%
11:50:24 2
 
0.1%
12:18:07 2
 
0.1%
17:06:24 2
 
0.1%
08:00:53 2
 
0.1%
Other values (2972) 3061
99.3%
2023-12-11T14:12:20.074537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 6166
25.0%
1 4330
17.6%
0 2519
10.2%
2 2057
 
8.3%
5 1995
 
8.1%
4 1963
 
8.0%
3 1908
 
7.7%
8 953
 
3.9%
7 928
 
3.8%
6 919
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18485
75.0%
Other Punctuation 6166
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4330
23.4%
0 2519
13.6%
2 2057
11.1%
5 1995
10.8%
4 1963
10.6%
3 1908
10.3%
8 953
 
5.2%
7 928
 
5.0%
6 919
 
5.0%
9 913
 
4.9%
Other Punctuation
ValueCountFrequency (%)
: 6166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24651
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 6166
25.0%
1 4330
17.6%
0 2519
10.2%
2 2057
 
8.3%
5 1995
 
8.1%
4 1963
 
8.0%
3 1908
 
7.7%
8 953
 
3.9%
7 928
 
3.8%
6 919
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24651
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 6166
25.0%
1 4330
17.6%
0 2519
10.2%
2 2057
 
8.3%
5 1995
 
8.1%
4 1963
 
8.0%
3 1908
 
7.7%
8 953
 
3.9%
7 928
 
3.8%
6 919
 
3.7%

발생일시
Date

Distinct4989
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
Minimum2020-01-01 11:25:00
Maximum2020-10-15 10:27:00
2023-12-11T14:12:20.344870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:12:20.605721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

승인일시
Date

MISSING 

Distinct2
Distinct (%)100.0%
Missing5077
Missing (%)> 99.9%
Memory size39.8 KiB
Minimum2020-01-03 14:52:00
Maximum2020-01-03 14:53:00
2023-12-11T14:12:20.788724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:12:20.941699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

승인자명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing5077
Missing (%)> 99.9%
Memory size39.8 KiB
2023-12-11T14:12:21.101380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters12
Distinct characters6
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

Unique0 ?
Unique (%)0.0%

Sample

1st rowmuser1
2nd rowmuser1
ValueCountFrequency (%)
muser1 2
100.0%
2023-12-11T14:12:21.485746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 2
16.7%
u 2
16.7%
s 2
16.7%
e 2
16.7%
r 2
16.7%
1 2
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10
83.3%
Decimal Number 2
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m 2
20.0%
u 2
20.0%
s 2
20.0%
e 2
20.0%
r 2
20.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
83.3%
Common 2
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 2
20.0%
u 2
20.0%
s 2
20.0%
e 2
20.0%
r 2
20.0%
Common
ValueCountFrequency (%)
1 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m 2
16.7%
u 2
16.7%
s 2
16.7%
e 2
16.7%
r 2
16.7%
1 2
16.7%

취소완료일시
Date

MISSING 

Distinct3057
Distinct (%)99.2%
Missing1997
Missing (%)39.3%
Memory size39.8 KiB
Minimum2020-01-01 23:26:00
Maximum2020-10-15 06:02:00
2023-12-11T14:12:21.683407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:12:21.933759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

취소사유완료처리구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5079
Missing (%)100.0%
Memory size44.8 KiB

취소완료자명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
SYSTEM
3082 
<NA>
1997 

Length

Max length6
Median length6
Mean length5.2136247
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd rowSYSTEM
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
SYSTEM 3082
60.7%
<NA> 1997
39.3%

Length

2023-12-11T14:12:22.154755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:12:22.320809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
system 3082
60.7%
na 1997
39.3%

씨씨티브이번호
Categorical

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
00000001-0000-babe-0000-accc8e0260fb
1662 
00000001-0000-babe-0000-00408cfffe3e
990 
00000001-0000-babe-0000-accc8e1e9cb2
732 
00000001-0000-babe-0000-00408cfffe3d
598 
01000000-0001-babe-004e-001f552f3881
467 
Other values (3)
630 

Length

Max length36
Median length36
Mean length36
Min length36

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00000001-0000-babe-0000-accc8e0260fb
2nd row00000001-0000-babe-0000-accc8e0260fb
3rd row00000001-0000-babe-0000-accc8e02746c
4th row00000001-0000-babe-0000-00408cfffe3e
5th row00000001-0000-babe-0000-accc8e0260fb

Common Values

ValueCountFrequency (%)
00000001-0000-babe-0000-accc8e0260fb 1662
32.7%
00000001-0000-babe-0000-00408cfffe3e 990
19.5%
00000001-0000-babe-0000-accc8e1e9cb2 732
14.4%
00000001-0000-babe-0000-00408cfffe3d 598
 
11.8%
01000000-0001-babe-004e-001f552f3881 467
 
9.2%
00000001-0000-babe-0000-accc8e02746c 398
 
7.8%
00000001-0000-babe-0000-accc8e1e9ca0 198
 
3.9%
00000001-0000-babe-0000-00408ce8c7d2 34
 
0.7%

Length

2023-12-11T14:12:22.472063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:12:22.667294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00000001-0000-babe-0000-accc8e0260fb 1662
32.7%
00000001-0000-babe-0000-00408cfffe3e 990
19.5%
00000001-0000-babe-0000-accc8e1e9cb2 732
14.4%
00000001-0000-babe-0000-00408cfffe3d 598
 
11.8%
01000000-0001-babe-004e-001f552f3881 467
 
9.2%
00000001-0000-babe-0000-accc8e02746c 398
 
7.8%
00000001-0000-babe-0000-accc8e1e9ca0 198
 
3.9%
00000001-0000-babe-0000-00408ce8c7d2 34
 
0.7%

차량인식결과순번
Text

UNIQUE 

Distinct5079
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
2023-12-11T14:12:23.023073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters121896
Distinct characters15
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

Unique5079 ?
Unique (%)100.0%

Sample

1st rowLPRUM0020200106084808652
2nd rowLPRUM0020200106093214079
3rd rowLPRUM0020200106095154157
4th rowLPRUM0020200106104927324
5th rowLPRUM0020200106110045046
ValueCountFrequency (%)
lprum0020200106084808652 1
 
< 0.1%
lprum0020200531121327259 1
 
< 0.1%
lprum0020200531105755980 1
 
< 0.1%
lprum0020200531100631962 1
 
< 0.1%
lprum0020200531100209345 1
 
< 0.1%
lprum0020200531080909808 1
 
< 0.1%
lprum0020200529200530919 1
 
< 0.1%
lprum0020200529185608556 1
 
< 0.1%
lprum0020200529184611772 1
 
< 0.1%
lprum0020200529183300982 1
 
< 0.1%
Other values (5069) 5069
99.8%
2023-12-11T14:12:23.535696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33110
27.2%
2 17863
14.7%
1 11864
 
9.7%
3 6070
 
5.0%
4 5946
 
4.9%
5 5713
 
4.7%
L 5079
 
4.2%
P 5079
 
4.2%
R 5079
 
4.2%
U 5079
 
4.2%
Other values (5) 21014
17.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96501
79.2%
Uppercase Letter 25395
 
20.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 33110
34.3%
2 17863
18.5%
1 11864
 
12.3%
3 6070
 
6.3%
4 5946
 
6.2%
5 5713
 
5.9%
6 4148
 
4.3%
7 4054
 
4.2%
8 3966
 
4.1%
9 3767
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
L 5079
20.0%
P 5079
20.0%
R 5079
20.0%
U 5079
20.0%
M 5079
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96501
79.2%
Latin 25395
 
20.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 33110
34.3%
2 17863
18.5%
1 11864
 
12.3%
3 6070
 
6.3%
4 5946
 
6.2%
5 5713
 
5.9%
6 4148
 
4.3%
7 4054
 
4.2%
8 3966
 
4.1%
9 3767
 
3.9%
Latin
ValueCountFrequency (%)
L 5079
20.0%
P 5079
20.0%
R 5079
20.0%
U 5079
20.0%
M 5079
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 121896
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33110
27.2%
2 17863
14.7%
1 11864
 
9.7%
3 6070
 
5.0%
4 5946
 
4.9%
5 5713
 
4.7%
L 5079
 
4.2%
P 5079
 
4.2%
R 5079
 
4.2%
U 5079
 
4.2%
Other values (5) 21014
17.2%

차량이미지파일명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5079
Missing (%)100.0%
Memory size44.8 KiB

체납건수
Real number (ℝ)

Distinct24
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0612325
Minimum0
Maximum28
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size44.8 KiB
2023-12-11T14:12:23.756538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile6
Maximum28
Range28
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.415812
Coefficient of variation (CV)1.172023
Kurtosis29.661128
Mean2.0612325
Median Absolute Deviation (MAD)0
Skewness4.5003577
Sum10469
Variance5.8361474
MonotonicityNot monotonic
2023-12-11T14:12:23.938560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 3304
65.1%
2 712
 
14.0%
3 363
 
7.1%
4 262
 
5.2%
5 159
 
3.1%
9 53
 
1.0%
12 48
 
0.9%
6 45
 
0.9%
7 41
 
0.8%
8 27
 
0.5%
Other values (14) 65
 
1.3%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 3304
65.1%
2 712
 
14.0%
3 363
 
7.1%
4 262
 
5.2%
5 159
 
3.1%
6 45
 
0.9%
7 41
 
0.8%
8 27
 
0.5%
9 53
 
1.0%
ValueCountFrequency (%)
28 7
0.1%
24 1
 
< 0.1%
23 1
 
< 0.1%
20 1
 
< 0.1%
19 3
0.1%
18 4
0.1%
17 2
 
< 0.1%
16 6
0.1%
15 5
0.1%
14 5
0.1%

체납금액
Real number (ℝ)

Distinct1362
Distinct (%)26.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean312070.1
Minimum0
Maximum6961340
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size44.8 KiB
2023-12-11T14:12:24.207315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile26840
Q186320
median173620
Q3313230
95-th percentile1083392
Maximum6961340
Range6961340
Interquartile range (IQR)226910

Descriptive statistics

Standard deviation467967.39
Coefficient of variation (CV)1.4995586
Kurtosis25.891925
Mean312070.1
Median Absolute Deviation (MAD)107490
Skewness4.3142259
Sum1.585004 × 109
Variance2.1899347 × 1011
MonotonicityNot monotonic
2023-12-11T14:12:24.453643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27880 165
 
3.2%
257380 138
 
2.7%
61200 102
 
2.0%
133750 95
 
1.9%
63600 95
 
1.9%
387880 86
 
1.7%
127200 85
 
1.7%
147120 63
 
1.2%
166890 62
 
1.2%
131520 57
 
1.1%
Other values (1352) 4131
81.3%
ValueCountFrequency (%)
0 1
 
< 0.1%
10 3
 
0.1%
680 1
 
< 0.1%
1800 6
 
0.1%
2170 1
 
< 0.1%
2240 1
 
< 0.1%
2500 1
 
< 0.1%
2650 2
 
< 0.1%
2690 21
0.4%
2720 1
 
< 0.1%
ValueCountFrequency (%)
6961340 1
 
< 0.1%
4110070 1
 
< 0.1%
4005110 6
0.1%
3860160 1
 
< 0.1%
3801870 1
 
< 0.1%
3713880 1
 
< 0.1%
3706710 1
 
< 0.1%
3664160 1
 
< 0.1%
3485720 1
 
< 0.1%
3328340 1
 
< 0.1%

체납전송여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5079
Missing (%)100.0%
Memory size44.8 KiB

과태료전송여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5079
Missing (%)100.0%
Memory size44.8 KiB

수배전송여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5079
Missing (%)100.0%
Memory size44.8 KiB

징수촉탁여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
1
4363 
0
716 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 4363
85.9%
0 716
 
14.1%

Length

2023-12-11T14:12:24.659827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:12:24.830823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4363
85.9%
0 716
 
14.1%

대포차여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
0
5027 
1
 
52

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 5027
99.0%
1 52
 
1.0%

Length

2023-12-11T14:12:24.979057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:12:25.113130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5027
99.0%
1 52
 
1.0%

기타사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5079
Missing (%)100.0%
Memory size44.8 KiB

등록자명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
SYSTEM
5079 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
SYSTEM 5079
100.0%

Length

2023-12-11T14:12:25.688923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:12:25.833916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
system 5079
100.0%

등록시각
Date

Distinct4989
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
Minimum2020-01-01 11:25:00
Maximum2020-10-15 10:27:00
2023-12-11T14:12:25.987539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:12:26.197262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정자명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
SYSTEM
5079 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
SYSTEM 5079
100.0%

Length

2023-12-11T14:12:26.393017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:12:26.560013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
system 5079
100.0%

수정시각
Date

Distinct5027
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
Minimum2020-01-01 13:58:00
Maximum2020-10-15 10:27:00
2023-12-11T14:12:26.771548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:12:26.993623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

완료수정사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5079
Missing (%)100.0%
Memory size44.8 KiB

완료수정자아이디
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5079
Missing (%)100.0%
Memory size44.8 KiB

완료수정일시
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5079
Missing (%)100.0%
Memory size44.8 KiB

Sample

이벤트발생번호관심차량구분분류명상황전파단계분류명상황전파일자상황전파시간발생일시승인일시승인자명취소완료일시취소사유완료처리구분명취소완료자명씨씨티브이번호차량인식결과순번차량이미지파일명체납건수체납금액체납전송여부과태료전송여부수배전송여부징수촉탁여부대포차여부기타사유등록자명등록시각수정자명수정시각완료수정사유완료수정자아이디완료수정일시
0LPRUM0020200106084808823310<NA><NA>2020-01-06 08:48:00<NA><NA><NA><NA><NA>00000001-0000-babe-0000-accc8e0260fbLPRUM0020200106084808652<NA>160970<NA><NA><NA>10<NA>SYSTEM2020-01-06 08:48:00SYSTEM2020-01-06 08:48:00<NA><NA><NA>
1LPRUM0020200106093214248310<NA><NA>2020-01-06 09:32:00<NA><NA><NA><NA><NA>00000001-0000-babe-0000-accc8e0260fbLPRUM0020200106093214079<NA>160970<NA><NA><NA>10<NA>SYSTEM2020-01-06 09:32:00SYSTEM2020-01-06 09:32:00<NA><NA><NA>
2LPRUM00202001060951543243902020-01-0609:51:482020-01-06 09:51:00<NA><NA>2020-01-06 21:52:00<NA>SYSTEM00000001-0000-babe-0000-accc8e02746cLPRUM0020200106095154157<NA>92981180<NA><NA><NA>00<NA>SYSTEM2020-01-06 09:51:00SYSTEM2020-01-06 21:52:00<NA><NA><NA>
3LPRUM0020200106104927490310<NA><NA>2020-01-06 10:49:00<NA><NA><NA><NA><NA>00000001-0000-babe-0000-00408cfffe3eLPRUM0020200106104927324<NA>1133750<NA><NA><NA>10<NA>SYSTEM2020-01-06 10:49:00SYSTEM2020-01-06 10:49:00<NA><NA><NA>
4LPRUM0020200106110045214310<NA><NA>2020-01-06 11:00:00<NA><NA><NA><NA><NA>00000001-0000-babe-0000-accc8e0260fbLPRUM0020200106110045046<NA>183030<NA><NA><NA>10<NA>SYSTEM2020-01-06 11:00:00SYSTEM2020-01-06 11:00:00<NA><NA><NA>
5LPRUM0020200106110647570310<NA><NA>2020-01-06 11:06:00<NA><NA><NA><NA><NA>00000001-0000-babe-0000-00408cfffe3eLPRUM0020200106110647403<NA>1146480<NA><NA><NA>10<NA>SYSTEM2020-01-06 11:06:00SYSTEM2020-01-06 11:06:00<NA><NA><NA>
6LPRUM00202001061119425493902020-01-0611:19:362020-01-06 11:19:00<NA><NA>2020-01-06 23:20:00<NA>SYSTEM00000001-0000-babe-0000-accc8e0260fbLPRUM0020200106111942380<NA>1309850<NA><NA><NA>10<NA>SYSTEM2020-01-06 11:19:00SYSTEM2020-01-06 23:20:00<NA><NA><NA>
7LPRUM00202001061124140743902020-01-0611:24:092020-01-06 11:24:00<NA><NA>2020-01-06 23:25:00<NA>SYSTEM00000001-0000-babe-0000-00408ce8c7d2LPRUM0020200106112413904<NA>1185940<NA><NA><NA>10<NA>SYSTEM2020-01-06 11:24:00SYSTEM2020-01-06 23:25:00<NA><NA><NA>
8LPRUM00202001061145149113902020-01-0611:45:082020-01-06 11:45:00<NA><NA>2020-01-06 23:46:00<NA>SYSTEM00000001-0000-babe-0000-00408cfffe3eLPRUM0020200106114514741<NA>51472150<NA><NA><NA>10<NA>SYSTEM2020-01-06 11:45:00SYSTEM2020-01-06 23:46:00<NA><NA><NA>
9LPRUM00202001061211551023902020-01-0612:11:482020-01-06 12:12:00<NA><NA>2020-01-07 00:12:00<NA>SYSTEM00000001-0000-babe-0000-00408cfffe3dLPRUM0020200106121154931<NA>5650260<NA><NA><NA>00<NA>SYSTEM2020-01-06 12:12:00SYSTEM2020-01-07 00:12:00<NA><NA><NA>
이벤트발생번호관심차량구분분류명상황전파단계분류명상황전파일자상황전파시간발생일시승인일시승인자명취소완료일시취소사유완료처리구분명취소완료자명씨씨티브이번호차량인식결과순번차량이미지파일명체납건수체납금액체납전송여부과태료전송여부수배전송여부징수촉탁여부대포차여부기타사유등록자명등록시각수정자명수정시각완료수정사유완료수정자아이디완료수정일시
5069LPRUM0020200520175343083310<NA><NA>2020-05-20 17:53:00<NA><NA><NA><NA><NA>01000000-0001-babe-004e-001f552f3881LPRUM0020200520175342916<NA>1126730<NA><NA><NA>10<NA>SYSTEM2020-05-20 17:53:00SYSTEM2020-05-20 17:53:00<NA><NA><NA>
5070LPRUM0020200520180313471310<NA><NA>2020-05-20 18:03:00<NA><NA><NA><NA><NA>00000001-0000-babe-0000-00408cfffe3eLPRUM0020200520180313292<NA>1131520<NA><NA><NA>10<NA>SYSTEM2020-05-20 18:03:00SYSTEM2020-05-20 18:03:00<NA><NA><NA>
5071LPRUM0020200520181347745310<NA><NA>2020-05-20 18:13:00<NA><NA><NA><NA><NA>00000001-0000-babe-0000-00408cfffe3eLPRUM0020200520181347578<NA>192580<NA><NA><NA>10<NA>SYSTEM2020-05-20 18:13:00SYSTEM2020-05-20 18:13:00<NA><NA><NA>
5072LPRUM00202005201915106463902020-05-2019:15:052020-05-20 19:15:00<NA><NA>2020-05-21 07:16:00<NA>SYSTEM00000001-0000-babe-0000-00408cfffe3eLPRUM0020200520191510476<NA>2298240<NA><NA><NA>10<NA>SYSTEM2020-05-20 19:15:00SYSTEM2020-05-21 07:16:00<NA><NA><NA>
5073LPRUM00202005210852135683902020-05-2108:52:072020-05-21 08:52:00<NA><NA>2020-05-21 20:53:00<NA>SYSTEM00000001-0000-babe-0000-accc8e02746cLPRUM0020200521085213397<NA>1213370<NA><NA><NA>10<NA>SYSTEM2020-05-21 08:52:00SYSTEM2020-05-21 20:53:00<NA><NA><NA>
5074LPRUM00202005210856008413902020-05-2108:55:552020-05-21 08:56:00<NA><NA>2020-05-21 20:57:00<NA>SYSTEM00000001-0000-babe-0000-00408cfffe3eLPRUM0020200521085600670<NA>1257380<NA><NA><NA>10<NA>SYSTEM2020-05-21 08:56:00SYSTEM2020-05-21 20:57:00<NA><NA><NA>
5075LPRUM0020200521093901341310<NA><NA>2020-05-21 09:39:00<NA><NA><NA><NA><NA>00000001-0000-babe-0000-accc8e02746cLPRUM0020200521093901171<NA>1109530<NA><NA><NA>10<NA>SYSTEM2020-05-21 09:39:00SYSTEM2020-05-21 09:39:00<NA><NA><NA>
5076LPRUM00202005210941322843902020-05-2109:41:262020-05-21 09:41:00<NA><NA>2020-05-21 21:42:00<NA>SYSTEM00000001-0000-babe-0000-accc8e0260fbLPRUM0020200521094132115<NA>1177810<NA><NA><NA>10<NA>SYSTEM2020-05-21 09:41:00SYSTEM2020-05-21 21:42:00<NA><NA><NA>
5077LPRUM00202005210945477493902020-05-2109:45:422020-05-21 09:45:00<NA><NA>2020-05-21 21:46:00<NA>SYSTEM00000001-0000-babe-0000-accc8e1e9cb2LPRUM0020200521094547558<NA>4506940<NA><NA><NA>00<NA>SYSTEM2020-05-21 09:45:00SYSTEM2020-05-21 21:46:00<NA><NA><NA>
5078LPRUM00202005210958511303902020-05-2109:58:452020-05-21 09:58:00<NA><NA>2020-05-21 21:59:00<NA>SYSTEM00000001-0000-babe-0000-accc8e02746cLPRUM0020200521095850959<NA>2454080<NA><NA><NA>10<NA>SYSTEM2020-05-21 09:58:00SYSTEM2020-05-21 21:59:00<NA><NA><NA>