Overview

Dataset statistics

Number of variables15
Number of observations160
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.1 KiB
Average record size in memory134.8 B

Variable types

Text1
Numeric14

Dataset

Description대검찰청에서 발간하는 범죄분석은 3종의 범죄통계원표를 기반으로 작성하는 자료이며 이 중 본 데이터는 재범자의 재범기간 및 종류에 따른 형법/특별법범 통계임. (단위: 명)
Author대검찰청
URLhttps://www.data.go.kr/data/15086052/fileData.do

Alerts

동종재범_1개월이내 is highly overall correlated with 동종재범_3개월이내 and 12 other fieldsHigh correlation
동종재범_3개월이내 is highly overall correlated with 동종재범_1개월이내 and 12 other fieldsHigh correlation
동종재범_6개월이내 is highly overall correlated with 동종재범_1개월이내 and 12 other fieldsHigh correlation
동종재범_1년이내 is highly overall correlated with 동종재범_1개월이내 and 12 other fieldsHigh correlation
동종재범_2년이내 is highly overall correlated with 동종재범_1개월이내 and 12 other fieldsHigh correlation
동종재범_3년이내 is highly overall correlated with 동종재범_1개월이내 and 12 other fieldsHigh correlation
동종재범_3년초과 is highly overall correlated with 동종재범_1개월이내 and 12 other fieldsHigh correlation
이종재범_1개월이내 is highly overall correlated with 동종재범_1개월이내 and 12 other fieldsHigh correlation
이종재범_3개월이내 is highly overall correlated with 동종재범_1개월이내 and 12 other fieldsHigh correlation
이종재범_6개월이내 is highly overall correlated with 동종재범_1개월이내 and 12 other fieldsHigh correlation
이종재범_1년이내 is highly overall correlated with 동종재범_1개월이내 and 12 other fieldsHigh correlation
이종재범_2년이내 is highly overall correlated with 동종재범_1개월이내 and 12 other fieldsHigh correlation
이종재범_3년이내 is highly overall correlated with 동종재범_1개월이내 and 12 other fieldsHigh correlation
이종재범_3년초과 is highly overall correlated with 동종재범_1개월이내 and 12 other fieldsHigh correlation
범죄분류 has unique valuesUnique
동종재범_1개월이내 has 45 (28.1%) zerosZeros
동종재범_3개월이내 has 41 (25.6%) zerosZeros
동종재범_6개월이내 has 30 (18.8%) zerosZeros
동종재범_1년이내 has 12 (7.5%) zerosZeros
동종재범_2년이내 has 22 (13.8%) zerosZeros
동종재범_3년이내 has 19 (11.9%) zerosZeros
동종재범_3년초과 has 11 (6.9%) zerosZeros
이종재범_1개월이내 has 34 (21.2%) zerosZeros
이종재범_3개월이내 has 17 (10.6%) zerosZeros
이종재범_6개월이내 has 15 (9.4%) zerosZeros
이종재범_1년이내 has 4 (2.5%) zerosZeros
이종재범_2년이내 has 7 (4.4%) zerosZeros
이종재범_3년이내 has 6 (3.8%) zerosZeros
이종재범_3년초과 has 2 (1.2%) zerosZeros

Reproduction

Analysis started2023-12-12 23:05:08.270253
Analysis finished2023-12-12 23:05:29.238334
Duration20.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

범죄분류
Text

UNIQUE 

Distinct160
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T08:05:29.463592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length23
Mean length8.59375
Min length2

Characters and Unicode

Total characters1375
Distinct characters226
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique160 ?
Unique (%)100.0%

Sample

1st row절도
2nd row장물
3rd row사기
4th row횡령
5th row배임
ValueCountFrequency (%)
관한법률 14
 
5.5%
12
 
4.7%
관한 8
 
3.1%
마약류관리에 3
 
1.2%
기타 3
 
1.2%
3
 
1.2%
등에 3
 
1.2%
처벌 2
 
0.8%
과실치사상 2
 
0.8%
규제에 2
 
0.8%
Other values (202) 204
79.7%
2023-12-13T08:05:29.965712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
 
8.2%
96
 
7.0%
66
 
4.8%
39
 
2.8%
39
 
2.8%
33
 
2.4%
31
 
2.3%
26
 
1.9%
24
 
1.7%
23
 
1.7%
Other values (216) 885
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1248
90.8%
Space Separator 96
 
7.0%
Open Punctuation 12
 
0.9%
Close Punctuation 12
 
0.9%
Other Punctuation 7
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
113
 
9.1%
66
 
5.3%
39
 
3.1%
39
 
3.1%
33
 
2.6%
31
 
2.5%
26
 
2.1%
24
 
1.9%
23
 
1.8%
19
 
1.5%
Other values (211) 835
66.9%
Other Punctuation
ValueCountFrequency (%)
· 5
71.4%
, 2
 
28.6%
Space Separator
ValueCountFrequency (%)
96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1248
90.8%
Common 127
 
9.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
113
 
9.1%
66
 
5.3%
39
 
3.1%
39
 
3.1%
33
 
2.6%
31
 
2.5%
26
 
2.1%
24
 
1.9%
23
 
1.8%
19
 
1.5%
Other values (211) 835
66.9%
Common
ValueCountFrequency (%)
96
75.6%
( 12
 
9.4%
) 12
 
9.4%
· 5
 
3.9%
, 2
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1245
90.5%
ASCII 122
 
8.9%
None 5
 
0.4%
Compat Jamo 3
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
113
 
9.1%
66
 
5.3%
39
 
3.1%
39
 
3.1%
33
 
2.7%
31
 
2.5%
26
 
2.1%
24
 
1.9%
23
 
1.8%
19
 
1.5%
Other values (210) 832
66.8%
ASCII
ValueCountFrequency (%)
96
78.7%
( 12
 
9.8%
) 12
 
9.8%
, 2
 
1.6%
None
ValueCountFrequency (%)
· 5
100.0%
Compat Jamo
ValueCountFrequency (%)
3
100.0%

동종재범_1개월이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct51
Distinct (%)31.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.2375
Minimum0
Maximum2863
Zeros45
Zeros (%)28.1%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:30.137480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q316
95-th percentile167.25
Maximum2863
Range2863
Interquartile range (IQR)16

Descriptive statistics

Standard deviation312.62117
Coefficient of variation (CV)4.7197006
Kurtosis64.071254
Mean66.2375
Median Absolute Deviation (MAD)3
Skewness7.7878483
Sum10598
Variance97731.994
MonotonicityNot monotonic
2023-12-13T08:05:30.303820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 45
28.1%
1 20
12.5%
2 14
 
8.8%
3 11
 
6.9%
8 6
 
3.8%
10 5
 
3.1%
9 5
 
3.1%
4 4
 
2.5%
6 3
 
1.9%
15 2
 
1.2%
Other values (41) 45
28.1%
ValueCountFrequency (%)
0 45
28.1%
1 20
12.5%
2 14
 
8.8%
3 11
 
6.9%
4 4
 
2.5%
5 1
 
0.6%
6 3
 
1.9%
7 1
 
0.6%
8 6
 
3.8%
9 5
 
3.1%
ValueCountFrequency (%)
2863 1
0.6%
2526 1
0.6%
787 1
0.6%
524 1
0.6%
517 1
0.6%
463 1
0.6%
219 1
0.6%
191 1
0.6%
166 1
0.6%
165 1
0.6%

동종재범_3개월이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct58
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.6
Minimum0
Maximum3316
Zeros41
Zeros (%)25.6%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:30.450390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.5
Q326.5
95-th percentile339
Maximum3316
Range3316
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation392.64209
Coefficient of variation (CV)3.9821713
Kurtosis45.148393
Mean98.6
Median Absolute Deviation (MAD)4.5
Skewness6.4256536
Sum15776
Variance154167.81
MonotonicityNot monotonic
2023-12-13T08:05:30.581534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41
25.6%
1 16
 
10.0%
3 10
 
6.2%
2 9
 
5.6%
7 6
 
3.8%
8 4
 
2.5%
4 4
 
2.5%
114 3
 
1.9%
16 3
 
1.9%
13 3
 
1.9%
Other values (48) 61
38.1%
ValueCountFrequency (%)
0 41
25.6%
1 16
 
10.0%
2 9
 
5.6%
3 10
 
6.2%
4 4
 
2.5%
5 3
 
1.9%
6 3
 
1.9%
7 6
 
3.8%
8 4
 
2.5%
9 2
 
1.2%
ValueCountFrequency (%)
3316 1
0.6%
2881 1
0.6%
1657 1
0.6%
1194 1
0.6%
938 1
0.6%
929 1
0.6%
370 1
0.6%
358 1
0.6%
338 1
0.6%
265 1
0.6%

동종재범_6개월이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct60
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.8625
Minimum0
Maximum3161
Zeros30
Zeros (%)18.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:30.713963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q335
95-th percentile401.4
Maximum3161
Range3161
Interquartile range (IQR)34

Descriptive statistics

Standard deviation396.60515
Coefficient of variation (CV)3.5454701
Kurtosis34.482572
Mean111.8625
Median Absolute Deviation (MAD)7
Skewness5.6139587
Sum17898
Variance157295.64
MonotonicityNot monotonic
2023-12-13T08:05:30.834958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30
18.8%
1 19
 
11.9%
2 8
 
5.0%
4 7
 
4.4%
7 7
 
4.4%
3 5
 
3.1%
14 4
 
2.5%
6 4
 
2.5%
13 3
 
1.9%
11 3
 
1.9%
Other values (50) 70
43.8%
ValueCountFrequency (%)
0 30
18.8%
1 19
11.9%
2 8
 
5.0%
3 5
 
3.1%
4 7
 
4.4%
5 1
 
0.6%
6 4
 
2.5%
7 7
 
4.4%
8 2
 
1.2%
9 2
 
1.2%
ValueCountFrequency (%)
3161 1
0.6%
2623 1
0.6%
1759 1
0.6%
1619 1
0.6%
1390 1
0.6%
1045 1
0.6%
486 1
0.6%
447 1
0.6%
399 1
0.6%
359 1
0.6%

동종재범_1년이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct91
Distinct (%)56.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean352.5875
Minimum0
Maximum10777
Zeros12
Zeros (%)7.5%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:30.981353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median29.5
Q3100.5
95-th percentile1236.7
Maximum10777
Range10777
Interquartile range (IQR)96.5

Descriptive statistics

Standard deviation1242.5763
Coefficient of variation (CV)3.5241645
Kurtosis38.217659
Mean352.5875
Median Absolute Deviation (MAD)27.5
Skewness5.7813165
Sum56414
Variance1543996
MonotonicityNot monotonic
2023-12-13T08:05:31.116610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12
 
7.5%
2 12
 
7.5%
3 8
 
5.0%
4 5
 
3.1%
1 5
 
3.1%
19 4
 
2.5%
11 3
 
1.9%
30 3
 
1.9%
6 3
 
1.9%
8 3
 
1.9%
Other values (81) 102
63.7%
ValueCountFrequency (%)
0 12
7.5%
1 5
3.1%
2 12
7.5%
3 8
5.0%
4 5
3.1%
5 2
 
1.2%
6 3
 
1.9%
7 1
 
0.6%
8 3
 
1.9%
9 1
 
0.6%
ValueCountFrequency (%)
10777 1
0.6%
6624 1
0.6%
5440 1
0.6%
5303 1
0.6%
4715 1
0.6%
3221 1
0.6%
1814 1
0.6%
1592 1
0.6%
1218 1
0.6%
1091 1
0.6%

동종재범_2년이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct75
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean189.625
Minimum0
Maximum5726
Zeros22
Zeros (%)13.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:31.276202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.75
median14
Q361.75
95-th percentile675.95
Maximum5726
Range5726
Interquartile range (IQR)59

Descriptive statistics

Standard deviation679.55495
Coefficient of variation (CV)3.583678
Kurtosis35.122506
Mean189.625
Median Absolute Deviation (MAD)13
Skewness5.5732543
Sum30340
Variance461794.93
MonotonicityNot monotonic
2023-12-13T08:05:31.399291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22
 
13.8%
1 11
 
6.9%
3 8
 
5.0%
4 7
 
4.4%
2 7
 
4.4%
14 5
 
3.1%
5 5
 
3.1%
10 5
 
3.1%
29 5
 
3.1%
21 4
 
2.5%
Other values (65) 81
50.6%
ValueCountFrequency (%)
0 22
13.8%
1 11
6.9%
2 7
 
4.4%
3 8
 
5.0%
4 7
 
4.4%
5 5
 
3.1%
6 3
 
1.9%
8 3
 
1.9%
9 2
 
1.2%
10 5
 
3.1%
ValueCountFrequency (%)
5726 1
0.6%
3442 1
0.6%
3282 1
0.6%
3146 1
0.6%
2093 1
0.6%
2023 1
0.6%
1345 1
0.6%
1188 1
0.6%
649 1
0.6%
549 1
0.6%

동종재범_3년이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct78
Distinct (%)48.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean188.28125
Minimum0
Maximum6765
Zeros19
Zeros (%)11.9%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:31.538940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median11
Q369.25
95-th percentile647.95
Maximum6765
Range6765
Interquartile range (IQR)66.25

Descriptive statistics

Standard deviation720.96462
Coefficient of variation (CV)3.8291897
Kurtosis49.743885
Mean188.28125
Median Absolute Deviation (MAD)11
Skewness6.5259748
Sum30125
Variance519789.98
MonotonicityNot monotonic
2023-12-13T08:05:31.665805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 19
 
11.9%
1 13
 
8.1%
5 11
 
6.9%
4 7
 
4.4%
2 7
 
4.4%
3 6
 
3.8%
11 5
 
3.1%
8 4
 
2.5%
9 3
 
1.9%
15 3
 
1.9%
Other values (68) 82
51.2%
ValueCountFrequency (%)
0 19
11.9%
1 13
8.1%
2 7
 
4.4%
3 6
 
3.8%
4 7
 
4.4%
5 11
6.9%
6 3
 
1.9%
7 3
 
1.9%
8 4
 
2.5%
9 3
 
1.9%
ValueCountFrequency (%)
6765 1
0.6%
3926 1
0.6%
3092 1
0.6%
2583 1
0.6%
1915 1
0.6%
1421 1
0.6%
1390 1
0.6%
1141 1
0.6%
622 1
0.6%
492 1
0.6%

동종재범_3년초과
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct90
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean558.225
Minimum0
Maximum37257
Zeros11
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:31.817092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median26
Q3113
95-th percentile2265.95
Maximum37257
Range37257
Interquartile range (IQR)108

Descriptive statistics

Standard deviation3126.4613
Coefficient of variation (CV)5.6007189
Kurtosis121.35447
Mean558.225
Median Absolute Deviation (MAD)24
Skewness10.500974
Sum89316
Variance9774760.4
MonotonicityNot monotonic
2023-12-13T08:05:31.968882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11
 
6.9%
2 11
 
6.9%
5 8
 
5.0%
6 6
 
3.8%
9 5
 
3.1%
1 5
 
3.1%
11 4
 
2.5%
4 4
 
2.5%
36 3
 
1.9%
8 3
 
1.9%
Other values (80) 100
62.5%
ValueCountFrequency (%)
0 11
6.9%
1 5
3.1%
2 11
6.9%
3 3
 
1.9%
4 4
 
2.5%
5 8
5.0%
6 6
3.8%
7 2
 
1.2%
8 3
 
1.9%
9 5
3.1%
ValueCountFrequency (%)
37257 1
0.6%
8336 1
0.6%
6197 1
0.6%
5729 1
0.6%
5297 1
0.6%
4281 1
0.6%
3095 1
0.6%
2968 1
0.6%
2229 1
0.6%
745 1
0.6%

이종재범_1개월이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct60
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.2
Minimum0
Maximum1306
Zeros34
Zeros (%)21.2%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:32.149810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q326
95-th percentile260.55
Maximum1306
Range1306
Interquartile range (IQR)25

Descriptive statistics

Standard deviation171.78873
Coefficient of variation (CV)3.056739
Kurtosis32.167179
Mean56.2
Median Absolute Deviation (MAD)5
Skewness5.3448521
Sum8992
Variance29511.369
MonotonicityNot monotonic
2023-12-13T08:05:32.309059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34
21.2%
1 18
 
11.2%
2 13
 
8.1%
3 12
 
7.5%
14 5
 
3.1%
8 4
 
2.5%
5 4
 
2.5%
6 4
 
2.5%
22 4
 
2.5%
11 4
 
2.5%
Other values (50) 58
36.2%
ValueCountFrequency (%)
0 34
21.2%
1 18
11.2%
2 13
 
8.1%
3 12
 
7.5%
4 1
 
0.6%
5 4
 
2.5%
6 4
 
2.5%
7 2
 
1.2%
8 4
 
2.5%
9 1
 
0.6%
ValueCountFrequency (%)
1306 1
0.6%
1196 1
0.6%
882 1
0.6%
502 1
0.6%
482 1
0.6%
422 1
0.6%
329 1
0.6%
290 1
0.6%
259 1
0.6%
245 1
0.6%

이종재범_3개월이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct71
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.95
Minimum0
Maximum2037
Zeros17
Zeros (%)10.6%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:32.489643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median8.5
Q347.25
95-th percentile498.95
Maximum2037
Range2037
Interquartile range (IQR)45.25

Descriptive statistics

Standard deviation328.21758
Coefficient of variation (CV)2.985153
Kurtosis21.464166
Mean109.95
Median Absolute Deviation (MAD)8.5
Skewness4.5506894
Sum17592
Variance107726.78
MonotonicityNot monotonic
2023-12-13T08:05:32.648297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 19
 
11.9%
0 17
 
10.6%
2 14
 
8.8%
3 9
 
5.6%
6 7
 
4.4%
7 5
 
3.1%
10 5
 
3.1%
8 4
 
2.5%
17 3
 
1.9%
5 3
 
1.9%
Other values (61) 74
46.2%
ValueCountFrequency (%)
0 17
10.6%
1 19
11.9%
2 14
8.8%
3 9
5.6%
4 2
 
1.2%
5 3
 
1.9%
6 7
 
4.4%
7 5
 
3.1%
8 4
 
2.5%
9 1
 
0.6%
ValueCountFrequency (%)
2037 1
0.6%
1928 1
0.6%
1878 1
0.6%
1722 1
0.6%
1135 1
0.6%
1118 1
0.6%
669 1
0.6%
536 1
0.6%
497 1
0.6%
453 1
0.6%

이종재범_6개월이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct80
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean143.20625
Minimum0
Maximum2718
Zeros15
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:33.117891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median12
Q365.5
95-th percentile712.15
Maximum2718
Range2718
Interquartile range (IQR)62.5

Descriptive statistics

Standard deviation415.02964
Coefficient of variation (CV)2.8981252
Kurtosis20.074683
Mean143.20625
Median Absolute Deviation (MAD)11
Skewness4.3887702
Sum22913
Variance172249.6
MonotonicityNot monotonic
2023-12-13T08:05:33.281883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15
 
9.4%
1 12
 
7.5%
2 12
 
7.5%
7 8
 
5.0%
5 6
 
3.8%
4 5
 
3.1%
3 4
 
2.5%
11 4
 
2.5%
12 4
 
2.5%
9 4
 
2.5%
Other values (70) 86
53.8%
ValueCountFrequency (%)
0 15
9.4%
1 12
7.5%
2 12
7.5%
3 4
 
2.5%
4 5
 
3.1%
5 6
 
3.8%
6 2
 
1.2%
7 8
5.0%
8 3
 
1.9%
9 4
 
2.5%
ValueCountFrequency (%)
2718 1
0.6%
2274 1
0.6%
2167 1
0.6%
2039 1
0.6%
1806 1
0.6%
1395 1
0.6%
868 1
0.6%
810 1
0.6%
707 1
0.6%
639 1
0.6%

이종재범_1년이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct117
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean526.8
Minimum0
Maximum10210
Zeros4
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:33.467631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q116
median59
Q3228
95-th percentile2827.95
Maximum10210
Range10210
Interquartile range (IQR)212

Descriptive statistics

Standard deviation1456.8135
Coefficient of variation (CV)2.7654014
Kurtosis22.772984
Mean526.8
Median Absolute Deviation (MAD)54
Skewness4.5395724
Sum84288
Variance2122305.5
MonotonicityNot monotonic
2023-12-13T08:05:33.622797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 6
 
3.8%
11 4
 
2.5%
4 4
 
2.5%
5 4
 
2.5%
0 4
 
2.5%
1 3
 
1.9%
31 3
 
1.9%
27 3
 
1.9%
10 3
 
1.9%
40 3
 
1.9%
Other values (107) 123
76.9%
ValueCountFrequency (%)
0 4
2.5%
1 3
1.9%
2 6
3.8%
3 2
 
1.2%
4 4
2.5%
5 4
2.5%
6 1
 
0.6%
8 1
 
0.6%
9 2
 
1.2%
10 3
1.9%
ValueCountFrequency (%)
10210 1
0.6%
9163 1
0.6%
6533 1
0.6%
6056 1
0.6%
5688 1
0.6%
4983 1
0.6%
2989 1
0.6%
2922 1
0.6%
2823 1
0.6%
2038 1
0.6%

이종재범_2년이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct106
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean368.15
Minimum0
Maximum7137
Zeros7
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:33.793995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q112.75
median40
Q3155.75
95-th percentile2049
Maximum7137
Range7137
Interquartile range (IQR)143

Descriptive statistics

Standard deviation1017.9884
Coefficient of variation (CV)2.7651457
Kurtosis22.388278
Mean368.15
Median Absolute Deviation (MAD)36
Skewness4.4960953
Sum58904
Variance1036300.4
MonotonicityNot monotonic
2023-12-13T08:05:33.953670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7
 
4.4%
6 4
 
2.5%
15 4
 
2.5%
18 4
 
2.5%
25 4
 
2.5%
2 4
 
2.5%
3 4
 
2.5%
5 4
 
2.5%
38 3
 
1.9%
8 3
 
1.9%
Other values (96) 119
74.4%
ValueCountFrequency (%)
0 7
4.4%
1 2
 
1.2%
2 4
2.5%
3 4
2.5%
4 2
 
1.2%
5 4
2.5%
6 4
2.5%
7 3
1.9%
8 3
1.9%
9 1
 
0.6%
ValueCountFrequency (%)
7137 1
0.6%
6118 1
0.6%
5380 1
0.6%
3884 1
0.6%
3573 1
0.6%
2956 1
0.6%
2759 1
0.6%
2182 1
0.6%
2042 1
0.6%
1578 1
0.6%

이종재범_3년이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct104
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean391.94375
Minimum0
Maximum7385
Zeros6
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:34.106353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q112
median46.5
Q3191
95-th percentile1997.5
Maximum7385
Range7385
Interquartile range (IQR)179

Descriptive statistics

Standard deviation1074.9221
Coefficient of variation (CV)2.7425416
Kurtosis23.669529
Mean391.94375
Median Absolute Deviation (MAD)42
Skewness4.6236224
Sum62711
Variance1155457.4
MonotonicityNot monotonic
2023-12-13T08:05:34.256392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6
 
3.8%
1 6
 
3.8%
3 5
 
3.1%
4 5
 
3.1%
9 5
 
3.1%
5 4
 
2.5%
7 3
 
1.9%
35 3
 
1.9%
20 3
 
1.9%
10 3
 
1.9%
Other values (94) 117
73.1%
ValueCountFrequency (%)
0 6
3.8%
1 6
3.8%
3 5
3.1%
4 5
3.1%
5 4
2.5%
6 1
 
0.6%
7 3
1.9%
8 1
 
0.6%
9 5
3.1%
10 3
1.9%
ValueCountFrequency (%)
7385 1
0.6%
6505 1
0.6%
6453 1
0.6%
3822 1
0.6%
3546 1
0.6%
3065 1
0.6%
2239 1
0.6%
2178 1
0.6%
1988 1
0.6%
1752 1
0.6%

이종재범_3년초과
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct150
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1861.5187
Minimum0
Maximum35830
Zeros2
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T08:05:34.412625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.9
Q164.5
median262
Q3917
95-th percentile7749.7
Maximum35830
Range35830
Interquartile range (IQR)852.5

Descriptive statistics

Standard deviation5065.0927
Coefficient of variation (CV)2.7209464
Kurtosis23.912846
Mean1861.5187
Median Absolute Deviation (MAD)224
Skewness4.6418486
Sum297843
Variance25655164
MonotonicityNot monotonic
2023-12-13T08:05:34.568279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 2
 
1.2%
302 2
 
1.2%
31 2
 
1.2%
1 2
 
1.2%
42 2
 
1.2%
61 2
 
1.2%
0 2
 
1.2%
45 2
 
1.2%
63 2
 
1.2%
917 2
 
1.2%
Other values (140) 140
87.5%
ValueCountFrequency (%)
0 2
1.2%
1 2
1.2%
2 1
0.6%
3 1
0.6%
6 1
0.6%
9 1
0.6%
11 1
0.6%
12 2
1.2%
13 1
0.6%
18 1
0.6%
ValueCountFrequency (%)
35830 1
0.6%
32462 1
0.6%
23380 1
0.6%
22508 1
0.6%
16801 1
0.6%
16581 1
0.6%
11618 1
0.6%
9587 1
0.6%
7653 1
0.6%
6829 1
0.6%

Interactions

2023-12-13T08:05:26.942221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:08.864232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:10.526696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:11.839596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:13.120683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:14.289196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:15.382084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:16.779652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:17.930097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:19.159798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:20.753134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:22.601605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:24.196324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:25.496310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:27.057374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:08.993437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:10.602889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:11.938504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:13.221879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:14.367774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:15.457343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:16.880478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:18.006697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:19.252583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:20.837679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:22.735787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:24.291015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:25.579149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:27.159256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:09.095321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:10.683178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:12.026993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:13.318713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:14.445007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:15.537595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:16.961256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:18.081867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:19.363015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:21.251932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:22.854763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:24.375406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:25.657774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:27.267941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:09.193470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:10.764297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:12.105206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:13.399360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:14.549601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:15.869318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:17.037231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:18.157787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:19.462354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:21.353460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:22.957391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:24.458166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:25.740376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:27.368601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:09.290433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:10.844275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:12.212873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:13.485167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:14.622030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:15.950757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:17.114508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:18.242586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:19.563000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:21.466031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:23.059733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:24.551357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:25.816834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:27.481840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:09.368097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:10.930937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:12.296243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:13.572380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:14.696217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:16.026853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:17.202041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:18.338987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:19.662165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:21.558575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:23.166008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:24.651891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:25.925884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:27.911647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:09.455148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:11.017009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:12.379894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:13.644013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:14.781628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:16.109596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:17.286673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:18.433659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:19.762013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:21.664786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:23.273843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:24.744807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:26.016051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:28.017286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:09.539332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:11.137825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:12.461232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:13.724336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:14.857697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:16.194504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:17.365158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:18.513191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:19.858270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:21.787570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:23.413264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:24.829017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:26.158604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:28.127840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:09.622773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:11.239456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:12.540558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:13.813431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:14.928759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:16.272012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:17.451630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:18.587175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:20.007190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:21.896899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:23.569583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:24.913990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:26.256708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:28.249743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:09.726478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:11.349808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:12.630687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:13.900888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:15.006013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:16.374478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:17.543102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:18.674878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:20.154524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:22.014845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:23.719714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:25.016762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:26.357336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:28.358795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:09.805026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:11.426760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:12.722969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:13.972881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:15.082700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:16.463300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:17.614316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:18.746451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:20.276439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:22.129619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:23.815820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:25.119333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:26.439538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:28.461331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:09.907527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:11.518940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:12.820470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:14.052589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:15.151608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:16.536538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:17.687777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:18.832973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:20.399108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:22.240615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:23.915761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:25.212810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:26.571358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:28.565637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:10.343341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:11.618685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:12.920067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:14.134016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:15.230132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:16.616904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:17.763005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:18.915330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:20.516089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:22.351887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:24.004788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:25.302983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:26.687709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:28.677745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:10.432956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:11.730537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:13.023638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:14.212758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:15.305173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:16.694394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:17.843318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:19.024235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:20.637259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:22.499275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:24.093586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:25.405704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:26.808477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:05:34.678154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동종재범_1개월이내동종재범_3개월이내동종재범_6개월이내동종재범_1년이내동종재범_2년이내동종재범_3년이내동종재범_3년초과이종재범_1개월이내이종재범_3개월이내이종재범_6개월이내이종재범_1년이내이종재범_2년이내이종재범_3년이내이종재범_3년초과
동종재범_1개월이내1.0001.0000.9341.0000.9080.9680.8240.9110.8080.9540.9410.9540.8810.789
동종재범_3개월이내1.0001.0000.9950.9970.9890.9920.8960.9090.9800.9490.9430.9610.9000.944
동종재범_6개월이내0.9340.9951.0000.9980.9850.9900.9080.8500.9560.9510.9480.9430.8990.947
동종재범_1년이내1.0000.9970.9981.0000.9850.9900.9080.9020.9530.9510.9480.9430.9130.947
동종재범_2년이내0.9080.9890.9850.9851.0000.9900.9550.9160.9600.9280.9340.9390.9030.945
동종재범_3년이내0.9680.9920.9900.9900.9901.0000.9640.8900.9300.9310.9420.9450.9260.971
동종재범_3년초과0.8240.8960.9080.9080.9550.9641.0000.9250.7690.9600.9980.9770.9930.871
이종재범_1개월이내0.9110.9090.8500.9020.9160.8900.9251.0000.8940.9730.9370.9870.8880.825
이종재범_3개월이내0.8080.9800.9560.9530.9600.9300.7690.8941.0000.9620.9090.9330.8800.941
이종재범_6개월이내0.9540.9490.9510.9510.9280.9310.9600.9730.9621.0000.9830.9930.9440.903
이종재범_1년이내0.9410.9430.9480.9480.9340.9420.9980.9370.9090.9831.0000.9730.9880.910
이종재범_2년이내0.9540.9610.9430.9430.9390.9450.9770.9870.9330.9930.9731.0000.9430.936
이종재범_3년이내0.8810.9000.8990.9130.9030.9260.9930.8880.8800.9440.9880.9431.0000.924
이종재범_3년초과0.7890.9440.9470.9470.9450.9710.8710.8250.9410.9030.9100.9360.9241.000
2023-12-13T08:05:34.830427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동종재범_1개월이내동종재범_3개월이내동종재범_6개월이내동종재범_1년이내동종재범_2년이내동종재범_3년이내동종재범_3년초과이종재범_1개월이내이종재범_3개월이내이종재범_6개월이내이종재범_1년이내이종재범_2년이내이종재범_3년이내이종재범_3년초과
동종재범_1개월이내1.0000.9040.8900.8950.8650.8740.8470.8180.8480.8540.8430.8460.8430.796
동종재범_3개월이내0.9041.0000.9370.9390.9230.9140.8760.8230.8740.8750.8730.8760.8720.828
동종재범_6개월이내0.8900.9371.0000.9350.9200.9130.9010.8200.8830.8780.8760.8790.8780.827
동종재범_1년이내0.8950.9390.9351.0000.9610.9630.9280.8440.8730.8880.9060.9050.9050.873
동종재범_2년이내0.8650.9230.9200.9611.0000.9570.9360.8460.8700.8800.8920.8910.8930.876
동종재범_3년이내0.8740.9140.9130.9630.9571.0000.9530.8320.8610.8760.8950.8960.9000.870
동종재범_3년초과0.8470.8760.9010.9280.9360.9531.0000.8370.8550.8690.8830.8970.9040.901
이종재범_1개월이내0.8180.8230.8200.8440.8460.8320.8371.0000.9330.9270.9320.9140.9150.890
이종재범_3개월이내0.8480.8740.8830.8730.8700.8610.8550.9331.0000.9550.9630.9490.9450.904
이종재범_6개월이내0.8540.8750.8780.8880.8800.8760.8690.9270.9551.0000.9660.9640.9540.916
이종재범_1년이내0.8430.8730.8760.9060.8920.8950.8830.9320.9630.9661.0000.9810.9840.950
이종재범_2년이내0.8460.8760.8790.9050.8910.8960.8970.9140.9490.9640.9811.0000.9820.960
이종재범_3년이내0.8430.8720.8780.9050.8930.9000.9040.9150.9450.9540.9840.9821.0000.973
이종재범_3년초과0.7960.8280.8270.8730.8760.8700.9010.8900.9040.9160.9500.9600.9731.000

Missing values

2023-12-13T08:05:28.839154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:05:29.106208image/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

범죄분류동종재범_1개월이내동종재범_3개월이내동종재범_6개월이내동종재범_1년이내동종재범_2년이내동종재범_3년이내동종재범_3년초과이종재범_1개월이내이종재범_3개월이내이종재범_6개월이내이종재범_1년이내이종재범_2년이내이종재범_3년이내이종재범_3년초과
0절도252628812623662431462583428113061878203956883573354616801
1장물224033985755109386275202123180639
2사기28633316316110777328239265729119619282274102105380645323380
3횡령791361455242002354502033083871780102112455916
4배임387461427361227432491442031206
5손괴1662652597584544247353296698682989218221789587
6살인32713582271324865849220
7강도2537246628265432518616811299222
8방화388161211232941421169788342
9성폭력661001113803042595682594245912038142214826829
범죄분류동종재범_1개월이내동종재범_3개월이내동종재범_6개월이내동종재범_1년이내동종재범_2년이내동종재범_3년이내동종재범_3년초과이종재범_1개월이내이종재범_3개월이내이종재범_6개월이내이종재범_1년이내이종재범_2년이내이종재범_3년이내이종재범_3년초과
150특허법000000001135429
151폐기물관리법81722782429411120261078084443
152풍속영업의 규제에 관한법률36929178211221161763
153하천법231843223520151986
154학교보건법126153300104549
155학원의설립운영및과외교습에관한법률011220710147560
156화물자동차운수사업법821237554557582319901161391049
157화재예방·소방시설설치유지 및 안전관리에 관한법률00001000000001
158화학물질관리법1616175029212214191850151836
159기타 특별법165358486181411881141309523749770728232042223911618