Overview

Dataset statistics

Number of variables5
Number of observations96
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory45.4 B

Variable types

Numeric4
Categorical1

Dataset

Description- 기상 상태별 제주도 내 교통사고 통계를 제공합니다. - 데이터 제공처: TAAS 교통사고분석시스템
Author제주특별자치도 미래성장과
URLhttps://www.jejudatahub.net/data/view/data/892

Alerts

기준 연도 is highly overall correlated with 부상자 수 and 2 other fieldsHigh correlation
부상자 수 is highly overall correlated with 기준 연도 and 3 other fieldsHigh correlation
사고 건수 is highly overall correlated with 기준 연도 and 3 other fieldsHigh correlation
사망자 수 is highly overall correlated with 기준 연도 and 2 other fieldsHigh correlation
기상 상태 is highly overall correlated with 부상자 수 and 1 other fieldsHigh correlation
사망자 수 has 8 (8.3%) zerosZeros

Reproduction

Analysis started2023-12-11 19:53:00.865065
Analysis finished2023-12-11 19:53:03.879521
Duration3.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준 연도
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.5
Minimum2005
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-12T04:53:03.981843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2005
Q12008.75
median2012.5
Q32016.25
95-th percentile2020
Maximum2020
Range15
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation4.6339707
Coefficient of variation (CV)0.0023025941
Kurtosis-1.2096465
Mean2012.5
Median Absolute Deviation (MAD)4
Skewness0
Sum193200
Variance21.473684
MonotonicityIncreasing
2023-12-12T04:53:04.214849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2005 6
 
6.2%
2014 6
 
6.2%
2020 6
 
6.2%
2019 6
 
6.2%
2018 6
 
6.2%
2017 6
 
6.2%
2016 6
 
6.2%
2015 6
 
6.2%
2013 6
 
6.2%
2006 6
 
6.2%
Other values (6) 36
37.5%
ValueCountFrequency (%)
2005 6
6.2%
2006 6
6.2%
2007 6
6.2%
2008 6
6.2%
2009 6
6.2%
2010 6
6.2%
2011 6
6.2%
2012 6
6.2%
2013 6
6.2%
2014 6
6.2%
ValueCountFrequency (%)
2020 6
6.2%
2019 6
6.2%
2018 6
6.2%
2017 6
6.2%
2016 6
6.2%
2015 6
6.2%
2014 6
6.2%
2013 6
6.2%
2012 6
6.2%
2011 6
6.2%

기상 상태
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size900.0 B
기타/불명
16 
눈
16 
맑음
16 
비
16 
안개
16 

Length

Max length5
Median length3.5
Mean length2.1666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타/불명
2nd row눈
3rd row맑음
4th row비
5th row안개

Common Values

ValueCountFrequency (%)
기타/불명 16
16.7%
눈 16
16.7%
맑음 16
16.7%
비 16
16.7%
안개 16
16.7%
흐림 16
16.7%

Length

2023-12-12T04:53:04.489118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:53:05.176187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타/불명 16
16.7%
눈 16
16.7%
맑음 16
16.7%
비 16
16.7%
안개 16
16.7%
흐림 16
16.7%

부상자 수
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39659.104
Minimum1
Maximum306268
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-12T04:53:05.377421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.75
Q1560.25
median2687
Q321294.25
95-th percentile285306.75
Maximum306268
Range306267
Interquartile range (IQR)20734

Descriptive statistics

Standard deviation89988.69
Coefficient of variation (CV)2.269055
Kurtosis3.9898693
Mean39659.104
Median Absolute Deviation (MAD)2621
Skewness2.4038909
Sum3807274
Variance8.0979644 × 109
MonotonicityNot monotonic
2023-12-12T04:53:05.612431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
78 2
 
2.1%
2161 1
 
1.0%
5940 1
 
1.0%
23 1
 
1.0%
740 1
 
1.0%
5568 1
 
1.0%
108 1
 
1.0%
14632 1
 
1.0%
887 1
 
1.0%
31042 1
 
1.0%
Other values (85) 85
88.5%
ValueCountFrequency (%)
1 1
1.0%
4 1
1.0%
7 1
1.0%
14 1
1.0%
22 1
1.0%
23 1
1.0%
31 1
1.0%
46 1
1.0%
54 1
1.0%
78 2
2.1%
ValueCountFrequency (%)
306268 1
1.0%
300311 1
1.0%
289237 1
1.0%
288297 1
1.0%
285597 1
1.0%
285210 1
1.0%
282473 1
1.0%
282194 1
1.0%
281631 1
1.0%
279244 1
1.0%

사고 건수
Real number (ℝ)

HIGH CORRELATION 

Distinct94
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25542.385
Minimum1
Maximum199816
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-12T04:53:05.835684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.5
Q1339.25
median1636.5
Q313012
95-th percentile185923.25
Maximum199816
Range199815
Interquartile range (IQR)12672.75

Descriptive statistics

Standard deviation58580.271
Coefficient of variation (CV)2.2934534
Kurtosis4.0385757
Mean25542.385
Median Absolute Deviation (MAD)1595.5
Skewness2.414596
Sum2452069
Variance3.4316481 × 109
MonotonicityNot monotonic
2023-12-12T04:53:06.098743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55 2
 
2.1%
20704 2
 
2.1%
1459 1
 
1.0%
34 1
 
1.0%
11 1
 
1.0%
469 1
 
1.0%
3602 1
 
1.0%
48 1
 
1.0%
9581 1
 
1.0%
428 1
 
1.0%
Other values (84) 84
87.5%
ValueCountFrequency (%)
1 1
1.0%
4 1
1.0%
6 1
1.0%
7 1
1.0%
11 1
1.0%
13 1
1.0%
26 1
1.0%
33 1
1.0%
34 1
1.0%
48 1
1.0%
ValueCountFrequency (%)
199816 1
1.0%
198586 1
1.0%
192007 1
1.0%
186840 1
1.0%
186143 1
1.0%
185850 1
1.0%
185655 1
1.0%
184835 1
1.0%
179009 1
1.0%
177447 1
1.0%

사망자 수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct74
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean641.1875
Minimum0
Maximum5019
Zeros8
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-12T04:53:06.352423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111.75
median48.5
Q3461.5
95-th percentile4370.75
Maximum5019
Range5019
Interquartile range (IQR)449.75

Descriptive statistics

Standard deviation1383.0294
Coefficient of variation (CV)2.1569812
Kurtosis4.1862948
Mean641.1875
Median Absolute Deviation (MAD)44.5
Skewness2.4064841
Sum61554
Variance1912770.3
MonotonicityNot monotonic
2023-12-12T04:53:06.571915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8
 
8.3%
1 5
 
5.2%
6 3
 
3.1%
35 2
 
2.1%
45 2
 
2.1%
364 2
 
2.1%
60 2
 
2.1%
36 2
 
2.1%
62 2
 
2.1%
5 2
 
2.1%
Other values (64) 66
68.8%
ValueCountFrequency (%)
0 8
8.3%
1 5
5.2%
2 1
 
1.0%
3 1
 
1.0%
5 2
 
2.1%
6 3
 
3.1%
7 1
 
1.0%
8 1
 
1.0%
10 1
 
1.0%
11 1
 
1.0%
ValueCountFrequency (%)
5019 1
1.0%
4928 1
1.0%
4747 1
1.0%
4744 1
1.0%
4733 1
1.0%
4250 1
1.0%
4233 1
1.0%
4126 1
1.0%
4087 1
1.0%
3825 1
1.0%

Interactions

2023-12-12T04:53:02.912575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:01.044673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:01.509578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:02.153459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:03.079043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:01.153995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:01.687514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:02.395603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:03.232767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:01.259436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:01.831234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:02.565110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:03.398855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:01.388917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:02.000230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:02.762153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:53:06.722997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준 연도기상 상태부상자 수사고 건수사망자 수
기준 연도1.0000.0000.0000.0000.394
기상 상태0.0001.0000.7210.6860.585
부상자 수0.0000.7211.0000.9790.747
사고 건수0.0000.6860.9791.0000.808
사망자 수0.3940.5850.7470.8081.000
2023-12-12T04:53:06.890917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준 연도부상자 수사고 건수사망자 수기상 상태
기준 연도1.000-0.559-0.543-0.6060.000
부상자 수-0.5591.0000.9990.9620.548
사고 건수-0.5430.9991.0000.9580.510
사망자 수-0.6060.9620.9581.0000.443
기상 상태0.0000.5480.5100.4431.000

Missing values

2023-12-12T04:53:03.640465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:53:03.813462image/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

기준 연도기상 상태부상자 수사고 건수사망자 수
02005기타/불명2161145935
12005눈5940305777
22005맑음2824731790095019
32005비2980017361619
42005안개73640444
52005흐림2112312881582
62006기타/불명2046134527
72006눈3221173237
82006맑음2792441774474928
92006비3407320168706
기준 연도기상 상태부상자 수사고 건수사망자 수
862019맑음5930385248
872019비5673538
882019안개1470
892019흐림2121337
902020기타/불명115755
912020눈46330
922020맑음5288345656
932020비4252986
942020안개440
952020흐림2531641