Overview

Dataset statistics

Number of variables8
Number of observations2878
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory182.8 KiB
Average record size in memory65.0 B

Variable types

Numeric1
Categorical5
DateTime2

Dataset

Description밤샘주차단속시스템 단속사유별 처분금액 현황에 대한 데이터로 연번, 단속차종구분, 처분구분, 차종, 관할지자체, 처분금액, 부과일자, 데이터기준일자 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15087095&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일 has constant value ""Constant
차종 is highly overall correlated with 단속차종구분 and 1 other fieldsHigh correlation
처분구분 is highly overall correlated with 단속차종구분 and 2 other fieldsHigh correlation
단속차종구분 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
연번 is highly overall correlated with 단속차종구분High correlation
처분금액 is highly overall correlated with 단속차종구분 and 1 other fieldsHigh correlation
관할지자체 is highly imbalanced (97.8%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 17:47:02.177008
Analysis finished2024-01-28 17:47:02.919800
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2878
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1439.5
Minimum1
Maximum2878
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.4 KiB
2024-01-29T02:47:02.976592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile144.85
Q1720.25
median1439.5
Q32158.75
95-th percentile2734.15
Maximum2878
Range2877
Interquartile range (IQR)1438.5

Descriptive statistics

Standard deviation830.95136
Coefficient of variation (CV)0.57724999
Kurtosis-1.2
Mean1439.5
Median Absolute Deviation (MAD)719.5
Skewness0
Sum4142881
Variance690480.17
MonotonicityStrictly increasing
2024-01-29T02:47:03.098345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1935 1
 
< 0.1%
1915 1
 
< 0.1%
1916 1
 
< 0.1%
1917 1
 
< 0.1%
1918 1
 
< 0.1%
1919 1
 
< 0.1%
1920 1
 
< 0.1%
1921 1
 
< 0.1%
1922 1
 
< 0.1%
Other values (2868) 2868
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2878 1
< 0.1%
2877 1
< 0.1%
2876 1
< 0.1%
2875 1
< 0.1%
2874 1
< 0.1%
2873 1
< 0.1%
2872 1
< 0.1%
2871 1
< 0.1%
2870 1
< 0.1%
2869 1
< 0.1%

단속차종구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.6 KiB
화물자동차
2162 
화물자동차
494 
버스
 
170
버스
 
52

Length

Max length6
Median length5
Mean length4.9583044
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화물자동차
2nd row화물자동차
3rd row화물자동차
4th row화물자동차
5th row버스

Common Values

ValueCountFrequency (%)
화물자동차 2162
75.1%
화물자동차 494
 
17.2%
버스 170
 
5.9%
버스 52
 
1.8%

Length

2024-01-29T02:47:03.232852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:47:03.322481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화물자동차 2656
92.3%
버스 222
 
7.7%

처분구분
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size22.6 KiB
운송사업(개별)
1753 
운송사업(개별)
439 
운송사업(일반)
406 
전세버스
 
160
운송사업(일반)
 
55
Other values (3)
 
65

Length

Max length9
Median length8
Mean length7.8769979
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row운송사업(일반)
2nd row운송사업(일반)
3rd row운송사업(개별)
4th row운송사업(일반)
5th row전세버스

Common Values

ValueCountFrequency (%)
운송사업(개별) 1753
60.9%
운송사업(개별) 439
 
15.3%
운송사업(일반) 406
 
14.1%
전세버스 160
 
5.6%
운송사업(일반) 55
 
1.9%
전세버스 52
 
1.8%
일반택시 10
 
0.3%
<NA> 3
 
0.1%

Length

2024-01-29T02:47:03.412747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:47:03.509077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운송사업(개별 2192
76.2%
운송사업(일반 461
 
16.0%
전세버스 212
 
7.4%
일반택시 10
 
0.3%
na 3
 
0.1%

차종
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size22.6 KiB
화물
1807 
화물
438 
특수
354 
승합
 
161
특수
 
55
Other values (2)
 
63

Length

Max length3
Median length2
Mean length2.1897151
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화물
2nd row특수
3rd row화물
4th row특수
5th row승합

Common Values

ValueCountFrequency (%)
화물 1807
62.8%
화물 438
 
15.2%
특수 354
 
12.3%
승합 161
 
5.6%
특수 55
 
1.9%
승합 53
 
1.8%
승용 10
 
0.3%

Length

2024-01-29T02:47:03.622641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:47:03.731065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화물 2245
78.0%
특수 409
 
14.2%
승합 214
 
7.4%
승용 10
 
0.3%

관할지자체
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.6 KiB
인천광역시 남동구
2866 
인천광역시 서구
 
7
인천광역시 연수구
 
3
인천광역시 부평구
 
2

Length

Max length9
Median length9
Mean length8.9975678
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천광역시 남동구
2nd row인천광역시 남동구
3rd row인천광역시 남동구
4th row인천광역시 남동구
5th row인천광역시 남동구

Common Values

ValueCountFrequency (%)
인천광역시 남동구 2866
99.6%
인천광역시 서구 7
 
0.2%
인천광역시 연수구 3
 
0.1%
인천광역시 부평구 2
 
0.1%

Length

2024-01-29T02:47:03.834319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:47:03.931799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 2878
50.0%
남동구 2866
49.8%
서구 7
 
0.1%
연수구 3
 
0.1%
부평구 2
 
< 0.1%

처분금액
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size22.6 KiB
100000
1425 
50000
573 
100,000
360 
200000
318 
50,000
161 
Other values (4)
 
41

Length

Max length7
Median length6
Mean length5.9252953
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row200000
2nd row200000
3rd row100000
4th row200000
5th row200000

Common Values

ValueCountFrequency (%)
100000 1425
49.5%
50000 573
19.9%
100,000 360
 
12.5%
200000 318
 
11.0%
50,000 161
 
5.6%
200,000 25
 
0.9%
<NA> 13
 
0.5%
150000 2
 
0.1%
25000 1
 
< 0.1%

Length

2024-01-29T02:47:04.048156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:47:04.176910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100000 1425
49.5%
50000 573
19.9%
100,000 360
 
12.5%
200000 318
 
11.0%
50,000 161
 
5.6%
200,000 25
 
0.9%
na 13
 
0.5%
150000 2
 
0.1%
25000 1
 
< 0.1%

부과일자
Date

Distinct61
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size22.6 KiB
Minimum2018-08-07 00:00:00
Maximum2023-07-27 00:00:00
2024-01-29T02:47:04.295219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:47:04.407621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.6 KiB
Minimum2023-09-16 00:00:00
Maximum2023-09-16 00:00:00
2024-01-29T02:47:04.500808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:47:04.581687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-29T02:47:02.629033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T02:47:04.646871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단속차종구분처분구분차종관할지자체처분금액부과일자
연번1.0000.7600.6680.6570.1000.6580.998
단속차종구분0.7601.0001.0000.9830.1920.9100.857
처분구분0.6681.0001.0000.9860.1110.9050.878
차종0.6570.9830.9861.0000.1070.6780.873
관할지자체0.1000.1920.1110.1071.0000.1140.000
처분금액0.6580.9100.9050.6780.1141.0000.775
부과일자0.9980.8570.8780.8730.0000.7751.000
2024-01-29T02:47:04.744085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차종처분금액관할지자체처분구분단속차종구분
차종1.0000.4480.0740.8160.995
처분금액0.4481.0000.0520.5490.616
관할지자체0.0740.0521.0000.0760.077
처분구분0.8160.5490.0761.0000.999
단속차종구분0.9950.6160.0770.9991.000
2024-01-29T02:47:04.849528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단속차종구분처분구분차종관할지자체처분금액
연번1.0000.5710.4190.4080.0600.389
단속차종구분0.5711.0000.9990.9950.0770.616
처분구분0.4190.9991.0000.8160.0760.549
차종0.4080.9950.8161.0000.0740.448
관할지자체0.0600.0770.0760.0741.0000.052
처분금액0.3890.6160.5490.4480.0521.000

Missing values

2024-01-29T02:47:02.746635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T02:47:02.878612image/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

연번단속차종구분처분구분차종관할지자체처분금액부과일자데이터기준일
01화물자동차운송사업(일반)화물인천광역시 남동구2000002018-08-072023-09-16
12화물자동차운송사업(일반)특수인천광역시 남동구2000002018-08-072023-09-16
23화물자동차운송사업(개별)화물인천광역시 남동구1000002018-08-072023-09-16
34화물자동차운송사업(일반)특수인천광역시 남동구2000002018-08-072023-09-16
45버스전세버스승합인천광역시 남동구2000002018-08-072023-09-16
56화물자동차운송사업(개별)화물인천광역시 남동구1000002018-08-072023-09-16
67화물자동차운송사업(개별)화물인천광역시 남동구1000002018-08-072023-09-16
78화물자동차운송사업(개별)특수인천광역시 남동구1000002018-08-072023-09-16
89화물자동차운송사업(개별)화물인천광역시 남동구1000002018-08-072023-09-16
910화물자동차운송사업(일반)화물인천광역시 남동구2000002018-08-072023-09-16
연번단속차종구분처분구분차종관할지자체처분금액부과일자데이터기준일
28682869화물자동차운송사업(개별)특수인천광역시 남동구50,0002023-07-272023-09-16
28692870화물자동차운송사업(일반)화물인천광역시 남동구100,0002023-07-272023-09-16
28702871화물자동차운송사업(개별)특수인천광역시 남동구100,0002023-07-272023-09-16
28712872버스전세버스승합인천광역시 남동구100,0002023-07-272023-09-16
28722873버스전세버스승합인천광역시 남동구100,0002023-07-272023-09-16
28732874화물자동차운송사업(일반)화물인천광역시 남동구100,0002023-07-272023-09-16
28742875버스전세버스승합인천광역시 남동구100,0002023-07-272023-09-16
28752876화물자동차운송사업(개별)화물인천광역시 남동구100,0002023-07-272023-09-16
28762877화물자동차운송사업(일반)특수인천광역시 남동구100,0002023-07-272023-09-16
28772878화물자동차운송사업(개별)특수인천광역시 남동구100,0002023-07-272023-09-16