Overview

Dataset statistics

Number of variables15
Number of observations108
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.3 KiB
Average record size in memory135.2 B

Variable types

Text1
Numeric14

Dataset

Description대검찰청에서 발간하는 범죄분석은 3종의 범죄통계원표를 기반으로 작성하는 자료이며 이 중 본 데이터는 전과자의 전회처분에 관한 통계임.
Author대검찰청
URLhttps://www.data.go.kr/data/15085329/fileData.do

Alerts

초범 is highly overall correlated with 즉결심판 and 12 other fieldsHigh correlation
즉결심판 is highly overall correlated with 초범 and 1 other fieldsHigh correlation
기소유예 is highly overall correlated with 초범 and 11 other fieldsHigh correlation
선도유예 is highly overall correlated with 초범 and 10 other fieldsHigh correlation
수배중 is highly overall correlated with 초범 and 10 other fieldsHigh correlation
보호처분 is highly overall correlated with 초범 and 10 other fieldsHigh correlation
선고유예 is highly overall correlated with 초범 and 11 other fieldsHigh correlation
집행유예중 is highly overall correlated with 초범 and 10 other fieldsHigh correlation
보석_형집행정지중 is highly overall correlated with 초범 and 11 other fieldsHigh correlation
가석방 is highly overall correlated with 초범 and 10 other fieldsHigh correlation
형(재산형포함)집행종료 is highly overall correlated with 초범 and 11 other fieldsHigh correlation
감호소출소 is highly overall correlated with 초범 and 10 other fieldsHigh correlation
기타 is highly overall correlated with 초범 and 11 other fieldsHigh correlation
미상 is highly overall correlated with 초범 and 6 other fieldsHigh correlation
범죄분류 has unique valuesUnique
초범 has 16 (14.8%) zerosZeros
즉결심판 has 81 (75.0%) zerosZeros
기소유예 has 3 (2.8%) zerosZeros
선도유예 has 60 (55.6%) zerosZeros
수배중 has 36 (33.3%) zerosZeros
보호처분 has 25 (23.1%) zerosZeros
선고유예 has 28 (25.9%) zerosZeros
집행유예중 has 10 (9.3%) zerosZeros
보석_형집행정지중 has 27 (25.0%) zerosZeros
가석방 has 76 (70.4%) zerosZeros
감호소출소 has 76 (70.4%) zerosZeros
미상 has 24 (22.2%) zerosZeros

Reproduction

Analysis started2023-12-12 23:11:09.992633
Analysis finished2023-12-12 23:11:29.606815
Duration19.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

범죄분류
Text

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-13T08:11:29.794457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length6.712963
Min length2

Characters and Unicode

Total characters725
Distinct characters182
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)100.0%

Sample

1st row절도
2nd row장물
3rd row사기
4th row횡령
5th row배임
ValueCountFrequency (%)
절도 1
 
0.9%
마약류관리에관한법률 1
 
0.9%
성매매알선등행위의처벌에관한법률 1
 
0.9%
선박직원법 1
 
0.9%
선박안전법 1
 
0.9%
상표법 1
 
0.9%
산지관리법 1
 
0.9%
산업안전보건법 1
 
0.9%
산림자원의조성및관리에관한법률 1
 
0.9%
사행행위등규제및처벌특례법 1
 
0.9%
Other values (98) 98
90.7%
2023-12-13T08:11:30.218876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61
 
8.4%
27
 
3.7%
17
 
2.3%
16
 
2.2%
16
 
2.2%
14
 
1.9%
13
 
1.8%
12
 
1.7%
12
 
1.7%
11
 
1.5%
Other values (172) 526
72.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 708
97.7%
Other Punctuation 7
 
1.0%
Close Punctuation 5
 
0.7%
Open Punctuation 5
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
61
 
8.6%
27
 
3.8%
17
 
2.4%
16
 
2.3%
16
 
2.3%
14
 
2.0%
13
 
1.8%
12
 
1.7%
12
 
1.7%
11
 
1.6%
Other values (168) 509
71.9%
Other Punctuation
ValueCountFrequency (%)
· 4
57.1%
, 3
42.9%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 708
97.7%
Common 17
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
61
 
8.6%
27
 
3.8%
17
 
2.4%
16
 
2.3%
16
 
2.3%
14
 
2.0%
13
 
1.8%
12
 
1.7%
12
 
1.7%
11
 
1.6%
Other values (168) 509
71.9%
Common
ValueCountFrequency (%)
) 5
29.4%
( 5
29.4%
· 4
23.5%
, 3
17.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 708
97.7%
ASCII 13
 
1.8%
None 4
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
61
 
8.6%
27
 
3.8%
17
 
2.4%
16
 
2.3%
16
 
2.3%
14
 
2.0%
13
 
1.8%
12
 
1.7%
12
 
1.7%
11
 
1.6%
Other values (168) 509
71.9%
ASCII
ValueCountFrequency (%)
) 5
38.5%
( 5
38.5%
, 3
23.1%
None
ValueCountFrequency (%)
· 4
100.0%

초범
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct53
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.407407
Minimum0
Maximum873
Zeros16
Zeros (%)14.8%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:30.368447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median8
Q332.5
95-th percentile283.45
Maximum873
Range873
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation119.20477
Coefficient of variation (CV)2.3648264
Kurtosis23.033075
Mean50.407407
Median Absolute Deviation (MAD)8
Skewness4.3182864
Sum5444
Variance14209.776
MonotonicityNot monotonic
2023-12-13T08:11:30.516684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16
 
14.8%
1 10
 
9.3%
2 6
 
5.6%
8 6
 
5.6%
4 5
 
4.6%
7 5
 
4.6%
3 4
 
3.7%
5 3
 
2.8%
14 3
 
2.8%
16 3
 
2.8%
Other values (43) 47
43.5%
ValueCountFrequency (%)
0 16
14.8%
1 10
9.3%
2 6
 
5.6%
3 4
 
3.7%
4 5
 
4.6%
5 3
 
2.8%
6 1
 
0.9%
7 5
 
4.6%
8 6
 
5.6%
9 1
 
0.9%
ValueCountFrequency (%)
873 1
0.9%
469 1
0.9%
430 1
0.9%
365 1
0.9%
336 1
0.9%
288 1
0.9%
275 1
0.9%
221 1
0.9%
209 1
0.9%
166 1
0.9%

즉결심판
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1851852
Minimum0
Maximum249
Zeros81
Zeros (%)75.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:30.641253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.25
95-th percentile15.65
Maximum249
Range249
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation25.419894
Coefficient of variation (CV)4.9024081
Kurtosis80.967039
Mean5.1851852
Median Absolute Deviation (MAD)0
Skewness8.588709
Sum560
Variance646.17099
MonotonicityNot monotonic
2023-12-13T08:11:31.028704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 81
75.0%
1 5
 
4.6%
2 4
 
3.7%
13 2
 
1.9%
3 2
 
1.9%
4 2
 
1.9%
11 2
 
1.9%
59 1
 
0.9%
34 1
 
0.9%
27 1
 
0.9%
Other values (7) 7
 
6.5%
ValueCountFrequency (%)
0 81
75.0%
1 5
 
4.6%
2 4
 
3.7%
3 2
 
1.9%
4 2
 
1.9%
6 1
 
0.9%
8 1
 
0.9%
11 2
 
1.9%
13 2
 
1.9%
14 1
 
0.9%
ValueCountFrequency (%)
249 1
0.9%
59 1
0.9%
57 1
0.9%
34 1
0.9%
27 1
0.9%
16 1
0.9%
15 1
0.9%
14 1
0.9%
13 2
1.9%
11 2
1.9%

기소유예
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct85
Distinct (%)78.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean396.91667
Minimum0
Maximum6088
Zeros3
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:31.154349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.35
Q113.75
median46
Q3238.75
95-th percentile1738
Maximum6088
Range6088
Interquartile range (IQR)225

Descriptive statistics

Standard deviation1059.3114
Coefficient of variation (CV)2.6688509
Kurtosis17.401056
Mean396.91667
Median Absolute Deviation (MAD)41
Skewness4.1084419
Sum42867
Variance1122140.7
MonotonicityNot monotonic
2023-12-13T08:11:31.293302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 4
 
3.7%
6 4
 
3.7%
0 3
 
2.8%
47 3
 
2.8%
1 3
 
2.8%
18 3
 
2.8%
7 3
 
2.8%
14 2
 
1.9%
24 2
 
1.9%
46 2
 
1.9%
Other values (75) 79
73.1%
ValueCountFrequency (%)
0 3
2.8%
1 3
2.8%
2 4
3.7%
3 1
 
0.9%
4 2
1.9%
6 4
3.7%
7 3
2.8%
8 1
 
0.9%
9 2
1.9%
10 1
 
0.9%
ValueCountFrequency (%)
6088 1
0.9%
5769 1
0.9%
5198 1
0.9%
3702 1
0.9%
3267 1
0.9%
1745 1
0.9%
1725 1
0.9%
1289 1
0.9%
1272 1
0.9%
1055 1
0.9%

선도유예
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.564815
Minimum0
Maximum387
Zeros60
Zeros (%)55.6%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:31.420648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile48.05
Maximum387
Range387
Interquartile range (IQR)3

Descriptive statistics

Standard deviation45.98136
Coefficient of variation (CV)3.6595335
Kurtosis43.343704
Mean12.564815
Median Absolute Deviation (MAD)0
Skewness6.0760492
Sum1357
Variance2114.2855
MonotonicityNot monotonic
2023-12-13T08:11:31.563566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 60
55.6%
1 12
 
11.1%
3 6
 
5.6%
2 5
 
4.6%
7 2
 
1.9%
13 2
 
1.9%
11 2
 
1.9%
17 1
 
0.9%
6 1
 
0.9%
18 1
 
0.9%
Other values (16) 16
 
14.8%
ValueCountFrequency (%)
0 60
55.6%
1 12
 
11.1%
2 5
 
4.6%
3 6
 
5.6%
5 1
 
0.9%
6 1
 
0.9%
7 2
 
1.9%
8 1
 
0.9%
9 1
 
0.9%
10 1
 
0.9%
ValueCountFrequency (%)
387 1
0.9%
173 1
0.9%
145 1
0.9%
133 1
0.9%
124 1
0.9%
54 1
0.9%
37 1
0.9%
33 1
0.9%
32 1
0.9%
25 1
0.9%

수배중
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.833333
Minimum0
Maximum555
Zeros36
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:31.688203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q39.25
95-th percentile67.95
Maximum555
Range555
Interquartile range (IQR)9.25

Descriptive statistics

Standard deviation69.484147
Coefficient of variation (CV)3.5034024
Kurtosis41.680848
Mean19.833333
Median Absolute Deviation (MAD)1
Skewness6.1801743
Sum2142
Variance4828.0467
MonotonicityNot monotonic
2023-12-13T08:11:31.794383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 36
33.3%
1 21
19.4%
4 4
 
3.7%
5 4
 
3.7%
2 4
 
3.7%
3 4
 
3.7%
12 3
 
2.8%
9 3
 
2.8%
7 2
 
1.9%
10 2
 
1.9%
Other values (22) 25
23.1%
ValueCountFrequency (%)
0 36
33.3%
1 21
19.4%
2 4
 
3.7%
3 4
 
3.7%
4 4
 
3.7%
5 4
 
3.7%
6 2
 
1.9%
7 2
 
1.9%
8 1
 
0.9%
9 3
 
2.8%
ValueCountFrequency (%)
555 1
0.9%
407 1
0.9%
193 1
0.9%
129 1
0.9%
72 1
0.9%
69 1
0.9%
66 1
0.9%
49 1
0.9%
48 1
0.9%
43 1
0.9%

보호처분
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct52
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean147.16667
Minimum0
Maximum3884
Zeros25
Zeros (%)23.1%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:31.932431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5.5
Q363.5
95-th percentile481.55
Maximum3884
Range3884
Interquartile range (IQR)62.5

Descriptive statistics

Standard deviation508.53713
Coefficient of variation (CV)3.4555184
Kurtosis31.880448
Mean147.16667
Median Absolute Deviation (MAD)5.5
Skewness5.3344242
Sum15894
Variance258610.01
MonotonicityNot monotonic
2023-12-13T08:11:32.093081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25
23.1%
1 11
 
10.2%
2 6
 
5.6%
3 6
 
5.6%
4 4
 
3.7%
9 3
 
2.8%
11 2
 
1.9%
8 2
 
1.9%
5 2
 
1.9%
10 2
 
1.9%
Other values (42) 45
41.7%
ValueCountFrequency (%)
0 25
23.1%
1 11
10.2%
2 6
 
5.6%
3 6
 
5.6%
4 4
 
3.7%
5 2
 
1.9%
6 1
 
0.9%
7 1
 
0.9%
8 2
 
1.9%
9 3
 
2.8%
ValueCountFrequency (%)
3884 1
0.9%
2420 1
0.9%
1755 1
0.9%
1624 1
0.9%
1505 1
0.9%
512 1
0.9%
425 1
0.9%
396 1
0.9%
345 1
0.9%
257 1
0.9%

선고유예
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)28.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.648148
Minimum0
Maximum193
Zeros28
Zeros (%)25.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:32.269728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q39.25
95-th percentile90.3
Maximum193
Range193
Interquartile range (IQR)9.25

Descriptive statistics

Standard deviation32.007392
Coefficient of variation (CV)2.3451821
Kurtosis14.424102
Mean13.648148
Median Absolute Deviation (MAD)3
Skewness3.6779087
Sum1474
Variance1024.4732
MonotonicityNot monotonic
2023-12-13T08:11:32.390839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 28
25.9%
1 12
11.1%
2 10
 
9.3%
3 10
 
9.3%
4 9
 
8.3%
6 5
 
4.6%
15 4
 
3.7%
5 3
 
2.8%
111 2
 
1.9%
16 2
 
1.9%
Other values (21) 23
21.3%
ValueCountFrequency (%)
0 28
25.9%
1 12
11.1%
2 10
 
9.3%
3 10
 
9.3%
4 9
 
8.3%
5 3
 
2.8%
6 5
 
4.6%
7 1
 
0.9%
8 2
 
1.9%
9 1
 
0.9%
ValueCountFrequency (%)
193 1
0.9%
162 1
0.9%
111 2
1.9%
110 1
0.9%
91 1
0.9%
89 1
0.9%
51 1
0.9%
47 1
0.9%
43 1
0.9%
41 1
0.9%

집행유예중
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct61
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean160.4537
Minimum0
Maximum2783
Zeros10
Zeros (%)9.3%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:32.507421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median15.5
Q389.25
95-th percentile799.55
Maximum2783
Range2783
Interquartile range (IQR)84.25

Descriptive statistics

Standard deviation447.73207
Coefficient of variation (CV)2.7904128
Kurtosis21.407951
Mean160.4537
Median Absolute Deviation (MAD)14.5
Skewness4.4534244
Sum17329
Variance200464.01
MonotonicityNot monotonic
2023-12-13T08:11:32.631242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
9.3%
12 6
 
5.6%
5 6
 
5.6%
1 5
 
4.6%
4 4
 
3.7%
2 3
 
2.8%
8 3
 
2.8%
17 3
 
2.8%
43 3
 
2.8%
11 3
 
2.8%
Other values (51) 62
57.4%
ValueCountFrequency (%)
0 10
9.3%
1 5
4.6%
2 3
 
2.8%
3 2
 
1.9%
4 4
 
3.7%
5 6
5.6%
6 2
 
1.9%
7 2
 
1.9%
8 3
 
2.8%
9 2
 
1.9%
ValueCountFrequency (%)
2783 1
0.9%
2706 1
0.9%
1676 1
0.9%
1546 1
0.9%
1122 1
0.9%
935 1
0.9%
548 1
0.9%
546 1
0.9%
519 1
0.9%
449 1
0.9%

보석_형집행정지중
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)28.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.592593
Minimum0
Maximum330
Zeros27
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:32.737965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.75
median2
Q38
95-th percentile70.6
Maximum330
Range330
Interquartile range (IQR)7.25

Descriptive statistics

Standard deviation42.066044
Coefficient of variation (CV)2.8826985
Kurtosis33.528121
Mean14.592593
Median Absolute Deviation (MAD)2
Skewness5.3561343
Sum1576
Variance1769.5521
MonotonicityNot monotonic
2023-12-13T08:11:32.854604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 27
25.0%
1 17
15.7%
2 14
13.0%
3 11
10.2%
8 3
 
2.8%
4 3
 
2.8%
5 3
 
2.8%
10 2
 
1.9%
23 2
 
1.9%
6 2
 
1.9%
Other values (21) 24
22.2%
ValueCountFrequency (%)
0 27
25.0%
1 17
15.7%
2 14
13.0%
3 11
10.2%
4 3
 
2.8%
5 3
 
2.8%
6 2
 
1.9%
7 2
 
1.9%
8 3
 
2.8%
9 1
 
0.9%
ValueCountFrequency (%)
330 1
0.9%
201 1
0.9%
155 1
0.9%
95 1
0.9%
94 1
0.9%
79 1
0.9%
55 1
0.9%
44 2
1.9%
37 1
0.9%
35 1
0.9%

가석방
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8796296
Minimum0
Maximum78
Zeros76
Zeros (%)70.4%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:32.956705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile7.65
Maximum78
Range78
Interquartile range (IQR)1

Descriptive statistics

Standard deviation8.5497091
Coefficient of variation (CV)4.5486137
Kurtosis63.376012
Mean1.8796296
Median Absolute Deviation (MAD)0
Skewness7.6452443
Sum203
Variance73.097525
MonotonicityNot monotonic
2023-12-13T08:11:33.056579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 76
70.4%
1 13
 
12.0%
2 9
 
8.3%
9 2
 
1.9%
8 2
 
1.9%
41 1
 
0.9%
78 1
 
0.9%
4 1
 
0.9%
7 1
 
0.9%
3 1
 
0.9%
ValueCountFrequency (%)
0 76
70.4%
1 13
 
12.0%
2 9
 
8.3%
3 1
 
0.9%
4 1
 
0.9%
5 1
 
0.9%
7 1
 
0.9%
8 2
 
1.9%
9 2
 
1.9%
41 1
 
0.9%
ValueCountFrequency (%)
78 1
 
0.9%
41 1
 
0.9%
9 2
 
1.9%
8 2
 
1.9%
7 1
 
0.9%
5 1
 
0.9%
4 1
 
0.9%
3 1
 
0.9%
2 9
8.3%
1 13
12.0%

형(재산형포함)집행종료
Real number (ℝ)

HIGH CORRELATION 

Distinct105
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5821.6019
Minimum3
Maximum141576
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:33.202322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile34.8
Q1291.25
median786
Q33222.75
95-th percentile35193.15
Maximum141576
Range141573
Interquartile range (IQR)2931.5

Descriptive statistics

Standard deviation17138.269
Coefficient of variation (CV)2.9439095
Kurtosis38.857558
Mean5821.6019
Median Absolute Deviation (MAD)695
Skewness5.6748033
Sum628733
Variance2.9372027 × 108
MonotonicityNot monotonic
2023-12-13T08:11:33.329710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
91 2
 
1.9%
77 2
 
1.9%
849 2
 
1.9%
293 1
 
0.9%
127 1
 
0.9%
232 1
 
0.9%
1283 1
 
0.9%
517 1
 
0.9%
702 1
 
0.9%
185 1
 
0.9%
Other values (95) 95
88.0%
ValueCountFrequency (%)
3 1
0.9%
5 1
0.9%
9 1
0.9%
13 1
0.9%
26 1
0.9%
32 1
0.9%
40 1
0.9%
63 1
0.9%
64 1
0.9%
72 1
0.9%
ValueCountFrequency (%)
141576 1
0.9%
65858 1
0.9%
61806 1
0.9%
38495 1
0.9%
36675 1
0.9%
35267 1
0.9%
35056 1
0.9%
17297 1
0.9%
13967 1
0.9%
13668 1
0.9%

감호소출소
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5
Minimum0
Maximum38
Zeros76
Zeros (%)70.4%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:33.448933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile7.3
Maximum38
Range38
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.9151682
Coefficient of variation (CV)3.2767788
Kurtosis35.810697
Mean1.5
Median Absolute Deviation (MAD)0
Skewness5.6218641
Sum162
Variance24.158879
MonotonicityNot monotonic
2023-12-13T08:11:33.567075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 76
70.4%
1 12
 
11.1%
2 7
 
6.5%
3 3
 
2.8%
6 2
 
1.9%
4 2
 
1.9%
28 1
 
0.9%
38 1
 
0.9%
8 1
 
0.9%
12 1
 
0.9%
Other values (2) 2
 
1.9%
ValueCountFrequency (%)
0 76
70.4%
1 12
 
11.1%
2 7
 
6.5%
3 3
 
2.8%
4 2
 
1.9%
6 2
 
1.9%
8 1
 
0.9%
10 1
 
0.9%
11 1
 
0.9%
12 1
 
0.9%
ValueCountFrequency (%)
38 1
 
0.9%
28 1
 
0.9%
12 1
 
0.9%
11 1
 
0.9%
10 1
 
0.9%
8 1
 
0.9%
6 2
 
1.9%
4 2
 
1.9%
3 3
2.8%
2 7
6.5%

기타
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean755.7963
Minimum0
Maximum15240
Zeros1
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:33.698992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.35
Q136.75
median105.5
Q3431.25
95-th percentile4438.6
Maximum15240
Range15240
Interquartile range (IQR)394.5

Descriptive statistics

Standard deviation2137.1852
Coefficient of variation (CV)2.8277265
Kurtosis25.303953
Mean755.7963
Median Absolute Deviation (MAD)88
Skewness4.7569336
Sum81626
Variance4567560.5
MonotonicityNot monotonic
2023-12-13T08:11:33.826563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 2
 
1.9%
14 2
 
1.9%
17 2
 
1.9%
29 2
 
1.9%
88 2
 
1.9%
13 2
 
1.9%
20 2
 
1.9%
21 2
 
1.9%
44 2
 
1.9%
2 2
 
1.9%
Other values (87) 88
81.5%
ValueCountFrequency (%)
0 1
0.9%
1 1
0.9%
2 2
1.9%
4 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
12 1
0.9%
13 2
1.9%
14 2
1.9%
ValueCountFrequency (%)
15240 1
0.9%
10838 1
0.9%
8703 1
0.9%
6317 1
0.9%
4730 1
0.9%
4510 1
0.9%
4306 1
0.9%
1970 1
0.9%
1710 1
0.9%
1371 1
0.9%

미상
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct49
Distinct (%)45.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.75926
Minimum0
Maximum3972
Zeros24
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:11:33.982204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q335.25
95-th percentile454.35
Maximum3972
Range3972
Interquartile range (IQR)34.25

Descriptive statistics

Standard deviation471.14735
Coefficient of variation (CV)4.1416176
Kurtosis49.924799
Mean113.75926
Median Absolute Deviation (MAD)7
Skewness6.7992559
Sum12286
Variance221979.83
MonotonicityNot monotonic
2023-12-13T08:11:34.116819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0 24
22.2%
2 8
 
7.4%
1 8
 
7.4%
3 8
 
7.4%
8 3
 
2.8%
11 3
 
2.8%
17 3
 
2.8%
5 3
 
2.8%
24 2
 
1.9%
50 2
 
1.9%
Other values (39) 44
40.7%
ValueCountFrequency (%)
0 24
22.2%
1 8
 
7.4%
2 8
 
7.4%
3 8
 
7.4%
4 1
 
0.9%
5 3
 
2.8%
6 1
 
0.9%
7 2
 
1.9%
8 3
 
2.8%
9 2
 
1.9%
ValueCountFrequency (%)
3972 1
0.9%
2661 1
0.9%
916 1
0.9%
627 1
0.9%
554 1
0.9%
489 1
0.9%
390 1
0.9%
285 1
0.9%
250 1
0.9%
231 1
0.9%

Interactions

2023-12-13T08:11:27.874356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:10.491638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:11.753472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:12.958653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:14.120425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.398778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:16.423164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:17.602523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:19.120401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:20.615015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:22.120444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:23.502229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:25.134721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:26.479846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:27.956570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:10.561291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:11.822628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:13.046694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:14.184227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.474701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:16.484514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:17.673982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:19.195641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:20.718455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:22.213566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:23.599840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:25.208932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:26.576771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:28.037894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:10.632967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:11.890343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:13.136055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:14.249167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.550465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:16.564614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:17.750244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:19.292014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:20.816304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:22.309149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:23.706996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:25.289447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:26.671143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:28.117056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:10.711735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:11.964481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:13.208889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:14.332262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.614444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:16.632406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:17.825690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:19.459983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:20.920513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:22.410738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:23.801294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:25.377744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:26.757861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:28.217998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:10.811712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:12.045258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:13.288602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:14.640989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.683923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:16.710746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:17.912184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:19.565461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:21.033448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:22.510125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:23.905099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:25.478854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:26.856632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:28.302496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:10.883875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:12.124508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:13.365785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:14.706779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.746839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:16.783373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:17.985917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:19.655283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:21.124045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:22.628530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:23.992276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:25.576288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:26.964162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:28.394939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:10.977445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:12.211234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:13.493255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:14.778112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.818044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:16.861132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:18.073112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:19.767127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:21.264483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:22.739440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:24.087263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:25.674341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:27.074282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:28.500871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:11.068939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:12.298438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:13.574146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:14.861681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.901847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:16.939132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:18.170548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:19.871894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:21.383328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:22.836730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:24.175797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:25.784461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:27.187603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:28.583304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:11.153481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:12.372502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:13.657173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:14.933970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.966374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:17.019001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:18.258843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:19.950252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:21.495191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:22.925537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:24.262792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:25.893152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:27.284509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:28.670043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:11.271915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:12.451420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:13.736391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.006444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:16.031016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:17.104498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:18.336838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:20.050670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:21.600197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:23.013119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:24.359834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:25.995502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:27.394299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:28.771940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:11.354590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:12.543801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:13.816767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.088147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:16.104042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:17.271786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:18.423965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:20.165966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:21.694696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:23.115431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:24.461330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:26.106566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:27.516993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:28.878808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:11.458624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:12.636659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:13.895602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.163321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:16.172960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:17.351162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:18.520437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:20.276354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:21.788110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:23.201583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:24.552713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:26.201942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:27.609833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:28.975657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:11.553049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:12.760382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:13.976770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.240314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:16.249216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:17.433973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:18.624827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:20.385417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:21.898215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:23.296560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:24.656562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:26.296238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:27.689089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:29.098032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:11.650269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:12.864515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:14.050419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:15.322936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:16.331992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:17.514788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:18.724848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:20.499227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:21.997220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:23.393477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:24.744225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:26.385365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:11:27.786283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:11:34.229883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
초범즉결심판기소유예선도유예수배중보호처분선고유예집행유예중보석_형집행정지중가석방형(재산형포함)집행종료감호소출소기타미상
초범1.0000.7370.9540.8540.8780.8540.9800.9640.8700.7470.8630.8130.9060.664
즉결심판0.7371.0000.0000.0000.3860.0000.0000.4710.1300.0000.0470.1280.2870.882
기소유예0.9540.0001.0000.8680.9040.9190.9600.9820.9100.8840.8470.8580.9520.000
선도유예0.8540.0000.8681.0000.8890.9350.8540.9190.8390.8220.9200.8110.9510.000
수배중0.8780.3860.9040.8891.0000.9830.8650.9070.9860.9860.8410.9870.9730.281
보호처분0.8540.0000.9190.9350.9831.0000.8570.9540.9650.9350.7750.9620.9630.000
선고유예0.9800.0000.9600.8540.8650.8571.0000.9620.8900.7470.8840.8190.9130.000
집행유예중0.9640.4710.9820.9190.9070.9540.9621.0000.9160.8840.8270.8890.9590.262
보석_형집행정지중0.8700.1300.9100.8390.9860.9650.8900.9161.0000.9020.9080.9710.9720.000
가석방0.7470.0000.8840.8220.9860.9350.7470.8840.9021.0000.6730.9690.9990.000
형(재산형포함)집행종료0.8630.0470.8470.9200.8410.7750.8840.8270.9080.6731.0000.8070.9510.000
감호소출소0.8130.1280.8580.8110.9870.9620.8190.8890.9710.9690.8071.0000.9460.000
기타0.9060.2870.9520.9510.9730.9630.9130.9590.9720.9990.9510.9461.0000.000
미상0.6640.8820.0000.0000.2810.0000.0000.2620.0000.0000.0000.0000.0001.000
2023-12-13T08:11:34.404138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
초범즉결심판기소유예선도유예수배중보호처분선고유예집행유예중보석_형집행정지중가석방형(재산형포함)집행종료감호소출소기타미상
초범1.0000.6430.8000.5910.6500.5460.7680.7130.7320.6060.8480.5400.8280.784
즉결심판0.6431.0000.4560.3820.4080.2620.4560.3960.4820.4840.4880.4410.4690.675
기소유예0.8000.4561.0000.7810.8380.8490.8760.9170.8270.6980.9570.7090.9590.540
선도유예0.5910.3820.7811.0000.7260.7800.6760.7550.6150.6810.6950.6270.7210.398
수배중0.6500.4080.8380.7261.0000.7960.7090.8690.7030.7160.7940.7150.8050.400
보호처분0.5460.2620.8490.7800.7961.0000.7120.8460.6610.6660.7610.6640.8010.293
선고유예0.7680.4560.8760.6760.7090.7121.0000.8240.7900.6160.8930.6680.8810.586
집행유예중0.7130.3960.9170.7550.8690.8460.8241.0000.7870.7140.9150.7110.9400.487
보석_형집행정지중0.7320.4820.8270.6150.7030.6610.7900.7871.0000.6830.8750.6590.8570.561
가석방0.6060.4840.6980.6810.7160.6660.6160.7140.6831.0000.6960.8030.7020.396
형(재산형포함)집행종료0.8480.4880.9570.6950.7940.7610.8930.9150.8750.6961.0000.6870.9810.615
감호소출소0.5400.4410.7090.6270.7150.6640.6680.7110.6590.8030.6871.0000.6830.369
기타0.8280.4690.9590.7210.8050.8010.8810.9400.8570.7020.9810.6831.0000.603
미상0.7840.6750.5400.3980.4000.2930.5860.4870.5610.3960.6150.3690.6031.000

Missing values

2023-12-13T08:11:29.286425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:11:29.516806image/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

범죄분류초범즉결심판기소유예선도유예수배중보호처분선고유예집행유예중보석_형집행정지중가석방형(재산형포함)집행종료감호소출소기타미상
0절도2881660883874073884111154679413849528631736
1장물1001721658844331119801520
2사기3361337021245551755111278320178618063810838390
3횡령67174432481884325223297391133058
4배임16047111840301721019222
5손괴10331272233134541546354172973197013
6살인1030037124004040410
7강도6073112742542266511110
8방화10635518331106001951
9성폭력9301289374342547519247107276134951
범죄분류초범즉결심판기소유예선도유예수배중보호처분선고유예집행유예중보석_형집행정지중가석방형(재산형포함)집행종료감호소출소기타미상
98청소년보호법22029713145223260321003799
99축산물위생관리법7124003181056407249
100출입국관리법1204502411020108501418
101통신비밀보호법004000000063090
102특가법(도주차량)90115153945340234103353
103폐기물관리법1712304311720849010035
104풍속영업의규제에관한법률401000001001620210
105학원의설립운영및과외교습에관한법률0060000000720100
106화물자동차운수사업법506502161770146711562
107기타특별법365341725114925711093594535056114306627