Overview

Dataset statistics

Number of variables7
Number of observations96
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory62.4 B

Variable types

Categorical2
Numeric5

Dataset

Description- 가해운전자 연령층별, 시간대별 교통사고 통계 - 경찰에서 조사, 처리한 교통사고에 대한 통계 정보로 인적 피해가 있는 사고만 집계 됨 - 교통사고분석시스템(http://taas.koroad.or.kr)의 데이터를 바탕으로 함
URLhttps://www.data.go.kr/data/15070189/fileData.do

Alerts

사고건수 is highly overall correlated with 사망자수 and 3 other fieldsHigh correlation
사망자수 is highly overall correlated with 사고건수 and 3 other fieldsHigh correlation
중상자수 is highly overall correlated with 사고건수 and 3 other fieldsHigh correlation
경상자수 is highly overall correlated with 사고건수 and 3 other fieldsHigh correlation
부상신고자수 is highly overall correlated with 사고건수 and 3 other fieldsHigh correlation
사고건수 has unique valuesUnique
경상자수 has unique valuesUnique
사망자수 has 12 (12.5%) zerosZeros

Reproduction

Analysis started2023-12-12 20:10:37.375691
Analysis finished2023-12-12 20:10:40.342787
Duration2.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가해자연령층
Categorical

Distinct8
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size900.0 B
20세이하
12 
21-30세
12 
31-40세
12 
41-50세
12 
51-60세
12 
Other values (3)
36 

Length

Max length6
Median length6
Mean length5.25
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20세이하
2nd row20세이하
3rd row20세이하
4th row20세이하
5th row20세이하

Common Values

ValueCountFrequency (%)
20세이하 12
12.5%
21-30세 12
12.5%
31-40세 12
12.5%
41-50세 12
12.5%
51-60세 12
12.5%
61-64세 12
12.5%
65세이상 12
12.5%
불명 12
12.5%

Length

2023-12-13T05:10:40.425520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:10:40.559762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20세이하 12
12.5%
21-30세 12
12.5%
31-40세 12
12.5%
41-50세 12
12.5%
51-60세 12
12.5%
61-64세 12
12.5%
65세이상 12
12.5%
불명 12
12.5%

시간대
Categorical

Distinct12
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size900.0 B
00시-02시
8 
02시-04시
8 
04시-06시
8 
06시-08시
8 
08시-10시
8 
Other values (7)
56 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00시-02시
2nd row02시-04시
3rd row04시-06시
4th row06시-08시
5th row08시-10시

Common Values

ValueCountFrequency (%)
00시-02시 8
8.3%
02시-04시 8
8.3%
04시-06시 8
8.3%
06시-08시 8
8.3%
08시-10시 8
8.3%
10시-12시 8
8.3%
12시-14시 8
8.3%
14시-16시 8
8.3%
16시-18시 8
8.3%
18시-20시 8
8.3%
Other values (2) 16
16.7%

Length

2023-12-13T05:10:40.697709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00시-02시 8
8.3%
02시-04시 8
8.3%
04시-06시 8
8.3%
06시-08시 8
8.3%
08시-10시 8
8.3%
10시-12시 8
8.3%
12시-14시 8
8.3%
14시-16시 8
8.3%
16시-18시 8
8.3%
18시-20시 8
8.3%
Other values (2) 16
16.7%

사고건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct96
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2050.375
Minimum69
Maximum6373
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-13T05:10:40.820718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum69
5-th percentile176
Q1532.75
median1760
Q33106
95-th percentile4964
Maximum6373
Range6304
Interquartile range (IQR)2573.25

Descriptive statistics

Standard deviation1682.1399
Coefficient of variation (CV)0.82040599
Kurtosis-0.58138447
Mean2050.375
Median Absolute Deviation (MAD)1256
Skewness0.67818031
Sum196836
Variance2829594.7
MonotonicityNot monotonic
2023-12-13T05:10:40.955737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
387 1
 
1.0%
532 1
 
1.0%
921 1
 
1.0%
1573 1
 
1.0%
2539 1
 
1.0%
2774 1
 
1.0%
2486 1
 
1.0%
2285 1
 
1.0%
2190 1
 
1.0%
2131 1
 
1.0%
Other values (86) 86
89.6%
ValueCountFrequency (%)
69 1
1.0%
100 1
1.0%
126 1
1.0%
136 1
1.0%
164 1
1.0%
180 1
1.0%
184 1
1.0%
195 1
1.0%
202 1
1.0%
227 1
1.0%
ValueCountFrequency (%)
6373 1
1.0%
6285 1
1.0%
5391 1
1.0%
5051 1
1.0%
5024 1
1.0%
4944 1
1.0%
4919 1
1.0%
4914 1
1.0%
4907 1
1.0%
4769 1
1.0%

사망자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct47
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.489583
Minimum0
Maximum110
Zeros12
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-13T05:10:41.106912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113
median25
Q340.75
95-th percentile68
Maximum110
Range110
Interquartile range (IQR)27.75

Descriptive statistics

Standard deviation23.646517
Coefficient of variation (CV)0.83000573
Kurtosis1.8726114
Mean28.489583
Median Absolute Deviation (MAD)15
Skewness1.1810909
Sum2735
Variance559.15779
MonotonicityNot monotonic
2023-12-13T05:10:41.261445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 12
 
12.5%
16 5
 
5.2%
25 5
 
5.2%
22 4
 
4.2%
17 4
 
4.2%
37 4
 
4.2%
48 3
 
3.1%
6 3
 
3.1%
19 3
 
3.1%
43 3
 
3.1%
Other values (37) 50
52.1%
ValueCountFrequency (%)
0 12
12.5%
1 2
 
2.1%
3 2
 
2.1%
5 2
 
2.1%
6 3
 
3.1%
7 1
 
1.0%
10 2
 
2.1%
14 1
 
1.0%
15 2
 
2.1%
16 5
5.2%
ValueCountFrequency (%)
110 1
1.0%
105 1
1.0%
95 1
1.0%
92 1
1.0%
74 1
1.0%
66 1
1.0%
63 1
1.0%
62 1
1.0%
59 1
1.0%
55 1
1.0%

중상자수
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean538.69792
Minimum8
Maximum1602
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-13T05:10:41.408029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile20.25
Q1171.75
median477
Q3776
95-th percentile1383.25
Maximum1602
Range1594
Interquartile range (IQR)604.25

Descriptive statistics

Standard deviation437.46478
Coefficient of variation (CV)0.8120781
Kurtosis-0.53773467
Mean538.69792
Median Absolute Deviation (MAD)305.5
Skewness0.67326573
Sum51715
Variance191375.43
MonotonicityNot monotonic
2023-12-13T05:10:41.550534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
293 2
 
2.1%
616 2
 
2.1%
701 2
 
2.1%
29 2
 
2.1%
172 2
 
2.1%
16 2
 
2.1%
18 2
 
2.1%
1174 1
 
1.0%
631 1
 
1.0%
639 1
 
1.0%
Other values (79) 79
82.3%
ValueCountFrequency (%)
8 1
1.0%
16 2
2.1%
18 2
2.1%
21 1
1.0%
25 1
1.0%
27 1
1.0%
29 2
2.1%
44 1
1.0%
50 1
1.0%
54 1
1.0%
ValueCountFrequency (%)
1602 1
1.0%
1537 1
1.0%
1471 1
1.0%
1435 1
1.0%
1399 1
1.0%
1378 1
1.0%
1351 1
1.0%
1323 1
1.0%
1258 1
1.0%
1208 1
1.0%

경상자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct96
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2212.8125
Minimum58
Maximum7115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-13T05:10:41.719000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum58
5-th percentile125.75
Q1530.75
median1845
Q33419
95-th percentile5393.75
Maximum7115
Range7057
Interquartile range (IQR)2888.25

Descriptive statistics

Standard deviation1867.2382
Coefficient of variation (CV)0.8438303
Kurtosis-0.59824765
Mean2212.8125
Median Absolute Deviation (MAD)1413
Skewness0.65493332
Sum212430
Variance3486578.6
MonotonicityNot monotonic
2023-12-13T05:10:41.854434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
411 1
 
1.0%
503 1
 
1.0%
982 1
 
1.0%
1740 1
 
1.0%
2743 1
 
1.0%
3085 1
 
1.0%
2907 1
 
1.0%
2548 1
 
1.0%
2450 1
 
1.0%
2233 1
 
1.0%
Other values (86) 86
89.6%
ValueCountFrequency (%)
58 1
1.0%
82 1
1.0%
104 1
1.0%
107 1
1.0%
110 1
1.0%
131 1
1.0%
149 1
1.0%
155 1
1.0%
164 1
1.0%
178 1
1.0%
ValueCountFrequency (%)
7115 1
1.0%
6858 1
1.0%
6226 1
1.0%
5635 1
1.0%
5468 1
1.0%
5369 1
1.0%
5278 1
1.0%
5167 1
1.0%
5118 1
1.0%
5032 1
1.0%

부상신고자수
Real number (ℝ)

HIGH CORRELATION 

Distinct87
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean183.9375
Minimum13
Maximum555
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2023-12-13T05:10:41.979496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile25.75
Q165.75
median156
Q3294.75
95-th percentile440
Maximum555
Range542
Interquartile range (IQR)229

Descriptive statistics

Standard deviation137.73933
Coefficient of variation (CV)0.74883766
Kurtosis-0.53554436
Mean183.9375
Median Absolute Deviation (MAD)102.5
Skewness0.71891642
Sum17658
Variance18972.122
MonotonicityNot monotonic
2023-12-13T05:10:42.108445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 2
 
2.1%
75 2
 
2.1%
195 2
 
2.1%
47 2
 
2.1%
156 2
 
2.1%
93 2
 
2.1%
63 2
 
2.1%
20 2
 
2.1%
53 2
 
2.1%
437 1
 
1.0%
Other values (77) 77
80.2%
ValueCountFrequency (%)
13 1
1.0%
14 1
1.0%
20 2
2.1%
25 1
1.0%
26 1
1.0%
27 1
1.0%
28 1
1.0%
30 1
1.0%
31 1
1.0%
38 1
1.0%
ValueCountFrequency (%)
555 1
1.0%
505 1
1.0%
459 1
1.0%
454 1
1.0%
449 1
1.0%
437 1
1.0%
433 1
1.0%
410 1
1.0%
403 1
1.0%
377 1
1.0%

Interactions

2023-12-13T05:10:39.621178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:37.611423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:38.279069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:38.679272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:39.158628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:39.705265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:37.698586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:38.358922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:38.766369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:39.254002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:39.801026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:37.782086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:38.443032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:38.863621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:39.341964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:39.900434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:37.867831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:38.530755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:38.967422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:39.436847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:40.005754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:38.204127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:38.608420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:39.062951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:10:39.532108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:10:42.197795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가해자연령층시간대사고건수사망자수중상자수경상자수부상신고자수
가해자연령층1.0000.0000.6180.7090.6250.5720.523
시간대0.0001.0000.3750.0000.5080.4590.471
사고건수0.6180.3751.0000.6540.9710.9880.946
사망자수0.7090.0000.6541.0000.6580.6340.699
중상자수0.6250.5080.9710.6581.0000.9560.939
경상자수0.5720.4590.9880.6340.9561.0000.946
부상신고자수0.5230.4710.9460.6990.9390.9461.000
2023-12-13T05:10:42.298513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간대가해자연령층
시간대1.0000.000
가해자연령층0.0001.000
2023-12-13T05:10:42.381292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사고건수사망자수중상자수경상자수부상신고자수가해자연령층시간대
사고건수1.0000.8070.9910.9970.9580.3490.161
사망자수0.8071.0000.8440.7980.6840.4350.000
중상자수0.9910.8441.0000.9880.9340.3540.235
경상자수0.9970.7980.9881.0000.9520.3120.207
부상신고자수0.9580.6840.9340.9521.0000.2770.213
가해자연령층0.3490.4350.3540.3120.2771.0000.000
시간대0.1610.0000.2350.2070.2130.0001.000

Missing values

2023-12-13T05:10:40.131618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:10:40.291164image/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

가해자연령층시간대사고건수사망자수중상자수경상자수부상신고자수
020세이하00시-02시387714541140
120세이하02시-04시25159122554
220세이하04시-06시195149714931
320세이하06시-08시18065016420
420세이하08시-10시377110030584
520세이하10시-12시28017425665
620세이하12시-14시454312442775
720세이하14시-16시7183172649119
820세이하16시-18시10296253911168
920세이하18시-20시1095102511008173
가해자연령층시간대사고건수사망자수중상자수경상자수부상신고자수
86불명04시-06시1000188214
87불명06시-08시12601810426
88불명08시-10시18401613151
89불명10시-12시16402910750
90불명12시-14시20201615553
91불명14시-16시23602517863
92불명16시-18시346027247105
93불명18시-20시476054364132
94불명20시-22시39604431593
95불명22시-24시27902923263