Overview

Dataset statistics

Number of variables12
Number of observations162
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.1 KiB
Average record size in memory107.8 B

Variable types

Text1
Numeric11

Dataset

Description대검찰청에서 발간하는 범죄분석은 3종의 범죄통계원표를 기반으로 작성하는 자료이며, 이 중 본 데이터는 범죄발생부터 인지까지의 기간에 따른 범죄 통계임. (단위: 건)
Author대검찰청
URLhttps://www.data.go.kr/data/15085618/fileData.do

Alerts

1시간 이내 is highly overall correlated with 2시간 이내 and 9 other fieldsHigh correlation
2시간 이내 is highly overall correlated with 1시간 이내 and 8 other fieldsHigh correlation
5시간 이내 is highly overall correlated with 1시간 이내 and 8 other fieldsHigh correlation
12시간 이내 is highly overall correlated with 1시간 이내 and 9 other fieldsHigh correlation
24시간 이내 is highly overall correlated with 1시간 이내 and 9 other fieldsHigh correlation
2일 이내 is highly overall correlated with 1시간 이내 and 9 other fieldsHigh correlation
5일 이내 is highly overall correlated with 1시간 이내 and 9 other fieldsHigh correlation
10일 이내 is highly overall correlated with 1시간 이내 and 9 other fieldsHigh correlation
1개월 이내 is highly overall correlated with 1시간 이내 and 9 other fieldsHigh correlation
3개월 이내 is highly overall correlated with 1시간 이내 and 9 other fieldsHigh correlation
3개월 초과 is highly overall correlated with 1시간 이내 and 7 other fieldsHigh correlation
범죄분류 has unique valuesUnique
1시간 이내 has 5 (3.1%) zerosZeros
2시간 이내 has 43 (26.5%) zerosZeros
5시간 이내 has 30 (18.5%) zerosZeros
12시간 이내 has 9 (5.6%) zerosZeros
24시간 이내 has 11 (6.8%) zerosZeros
2일 이내 has 9 (5.6%) zerosZeros
5일 이내 has 5 (3.1%) zerosZeros
10일 이내 has 4 (2.5%) zerosZeros
3개월 초과 has 2 (1.2%) zerosZeros

Reproduction

Analysis started2023-12-12 18:07:04.016119
Analysis finished2023-12-12 18:07:17.227221
Duration13.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

범죄분류
Text

UNIQUE 

Distinct162
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T03:07:17.390208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length19
Mean length8.037037
Min length2

Characters and Unicode

Total characters1302
Distinct characters225
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

Unique162 ?
Unique (%)100.0%

Sample

1st row절도
2nd row장물
3rd row사기
4th row횡령
5th row배임
ValueCountFrequency (%)
절도 1
 
0.6%
약사법 1
 
0.6%
사행행위등규제및처벌특례법 1
 
0.6%
성매매알선등행위의처벌에관한법률 1
 
0.6%
산림자원의조성및관리에관한법률 1
 
0.6%
산업안전보건법 1
 
0.6%
산지관리법 1
 
0.6%
상표법 1
 
0.6%
석유및석유대체연료사업법 1
 
0.6%
선박안전법 1
 
0.6%
Other values (152) 152
93.8%
2023-12-13T03:07:17.771077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
114
 
8.8%
67
 
5.1%
41
 
3.1%
40
 
3.1%
34
 
2.6%
31
 
2.4%
27
 
2.1%
26
 
2.0%
23
 
1.8%
19
 
1.5%
Other values (215) 880
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1268
97.4%
Open Punctuation 12
 
0.9%
Close Punctuation 12
 
0.9%
Other Punctuation 10
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
114
 
9.0%
67
 
5.3%
41
 
3.2%
40
 
3.2%
34
 
2.7%
31
 
2.4%
27
 
2.1%
26
 
2.1%
23
 
1.8%
19
 
1.5%
Other values (211) 846
66.7%
Other Punctuation
ValueCountFrequency (%)
, 8
80.0%
· 2
 
20.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1268
97.4%
Common 34
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
114
 
9.0%
67
 
5.3%
41
 
3.2%
40
 
3.2%
34
 
2.7%
31
 
2.4%
27
 
2.1%
26
 
2.1%
23
 
1.8%
19
 
1.5%
Other values (211) 846
66.7%
Common
ValueCountFrequency (%)
( 12
35.3%
) 12
35.3%
, 8
23.5%
· 2
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1268
97.4%
ASCII 32
 
2.5%
None 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
114
 
9.0%
67
 
5.3%
41
 
3.2%
40
 
3.2%
34
 
2.7%
31
 
2.4%
27
 
2.1%
26
 
2.1%
23
 
1.8%
19
 
1.5%
Other values (211) 846
66.7%
ASCII
ValueCountFrequency (%)
( 12
37.5%
) 12
37.5%
, 8
25.0%
None
ValueCountFrequency (%)
· 2
100.0%

1시간 이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct124
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2382.6667
Minimum0
Maximum89596
Zeros5
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:07:17.902391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.05
Q119.25
median89
Q3479.5
95-th percentile9354.35
Maximum89596
Range89596
Interquartile range (IQR)460.25

Descriptive statistics

Standard deviation10314.738
Coefficient of variation (CV)4.3290728
Kurtosis52.116966
Mean2382.6667
Median Absolute Deviation (MAD)84
Skewness6.936982
Sum385992
Variance1.0639381 × 108
MonotonicityNot monotonic
2023-12-13T03:07:18.022042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5
 
3.1%
1 4
 
2.5%
12 4
 
2.5%
14 3
 
1.9%
3 3
 
1.9%
40 3
 
1.9%
2 3
 
1.9%
18 3
 
1.9%
31 3
 
1.9%
65 3
 
1.9%
Other values (114) 128
79.0%
ValueCountFrequency (%)
0 5
3.1%
1 4
2.5%
2 3
1.9%
3 3
1.9%
4 1
 
0.6%
5 3
1.9%
6 2
 
1.2%
7 1
 
0.6%
8 2
 
1.2%
9 1
 
0.6%
ValueCountFrequency (%)
89596 1
0.6%
79961 1
0.6%
41822 1
0.6%
24262 1
0.6%
20191 1
0.6%
15764 1
0.6%
10814 1
0.6%
9777 1
0.6%
9380 1
0.6%
8867 1
0.6%

2시간 이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct71
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean334.68519
Minimum0
Maximum13841
Zeros43
Zeros (%)26.5%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:07:18.146113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.5
Q352.25
95-th percentile1861.65
Maximum13841
Range13841
Interquartile range (IQR)52.25

Descriptive statistics

Standard deviation1380.6528
Coefficient of variation (CV)4.1252284
Kurtosis61.263673
Mean334.68519
Median Absolute Deviation (MAD)4.5
Skewness7.1671662
Sum54219
Variance1906202.2
MonotonicityNot monotonic
2023-12-13T03:07:18.305961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 43
26.5%
1 17
 
10.5%
2 8
 
4.9%
4 8
 
4.9%
3 5
 
3.1%
8 4
 
2.5%
15 3
 
1.9%
5 3
 
1.9%
46 2
 
1.2%
11 2
 
1.2%
Other values (61) 67
41.4%
ValueCountFrequency (%)
0 43
26.5%
1 17
 
10.5%
2 8
 
4.9%
3 5
 
3.1%
4 8
 
4.9%
5 3
 
1.9%
6 1
 
0.6%
7 1
 
0.6%
8 4
 
2.5%
9 1
 
0.6%
ValueCountFrequency (%)
13841 1
0.6%
6836 1
0.6%
5212 1
0.6%
5202 1
0.6%
2306 1
0.6%
2292 1
0.6%
2136 1
0.6%
2044 1
0.6%
1871 1
0.6%
1684 1
0.6%

5시간 이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct77
Distinct (%)47.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean412.62346
Minimum0
Maximum14632
Zeros30
Zeros (%)18.5%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:07:18.445868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median10.5
Q383.25
95-th percentile2306.6
Maximum14632
Range14632
Interquartile range (IQR)81.25

Descriptive statistics

Standard deviation1579.0966
Coefficient of variation (CV)3.8269675
Kurtosis48.809497
Mean412.62346
Median Absolute Deviation (MAD)10.5
Skewness6.4599553
Sum66845
Variance2493546
MonotonicityNot monotonic
2023-12-13T03:07:18.588866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30
 
18.5%
2 12
 
7.4%
1 10
 
6.2%
3 7
 
4.3%
4 6
 
3.7%
22 4
 
2.5%
7 4
 
2.5%
12 3
 
1.9%
8 3
 
1.9%
40 3
 
1.9%
Other values (67) 80
49.4%
ValueCountFrequency (%)
0 30
18.5%
1 10
 
6.2%
2 12
 
7.4%
3 7
 
4.3%
4 6
 
3.7%
5 2
 
1.2%
6 2
 
1.2%
7 4
 
2.5%
8 3
 
1.9%
9 3
 
1.9%
ValueCountFrequency (%)
14632 1
0.6%
9485 1
0.6%
7087 1
0.6%
3810 1
0.6%
3674 1
0.6%
3069 1
0.6%
2859 1
0.6%
2536 1
0.6%
2330 1
0.6%
1862 1
0.6%

12시간 이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct87
Distinct (%)53.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean395.89506
Minimum0
Maximum12017
Zeros9
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:07:18.736368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.05
Q15
median17.5
Q3115
95-th percentile1700.65
Maximum12017
Range12017
Interquartile range (IQR)110

Descriptive statistics

Standard deviation1520.9976
Coefficient of variation (CV)3.841921
Kurtosis40.398202
Mean395.89506
Median Absolute Deviation (MAD)15.5
Skewness6.1067585
Sum64135
Variance2313433.5
MonotonicityNot monotonic
2023-12-13T03:07:19.137280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 9
 
5.6%
0 9
 
5.6%
1 9
 
5.6%
3 7
 
4.3%
7 6
 
3.7%
14 6
 
3.7%
5 5
 
3.1%
6 5
 
3.1%
22 4
 
2.5%
4 4
 
2.5%
Other values (77) 98
60.5%
ValueCountFrequency (%)
0 9
5.6%
1 9
5.6%
2 9
5.6%
3 7
4.3%
4 4
2.5%
5 5
3.1%
6 5
3.1%
7 6
3.7%
8 3
 
1.9%
9 4
2.5%
ValueCountFrequency (%)
12017 1
0.6%
11259 1
0.6%
8128 1
0.6%
4117 1
0.6%
3375 1
0.6%
2878 1
0.6%
2176 1
0.6%
2024 1
0.6%
1713 1
0.6%
1466 1
0.6%

24시간 이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct89
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean392.75926
Minimum0
Maximum13189
Zeros11
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:07:19.265815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median19
Q3100
95-th percentile2323.15
Maximum13189
Range13189
Interquartile range (IQR)95

Descriptive statistics

Standard deviation1416.393
Coefficient of variation (CV)3.6062626
Kurtosis45.685612
Mean392.75926
Median Absolute Deviation (MAD)18
Skewness6.1338665
Sum63627
Variance2006169.3
MonotonicityNot monotonic
2023-12-13T03:07:19.394859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11
 
6.8%
3 8
 
4.9%
4 7
 
4.3%
1 7
 
4.3%
2 6
 
3.7%
10 6
 
3.7%
9 5
 
3.1%
6 5
 
3.1%
13 4
 
2.5%
5 4
 
2.5%
Other values (79) 99
61.1%
ValueCountFrequency (%)
0 11
6.8%
1 7
4.3%
2 6
3.7%
3 8
4.9%
4 7
4.3%
5 4
 
2.5%
6 5
3.1%
7 2
 
1.2%
8 2
 
1.2%
9 5
3.1%
ValueCountFrequency (%)
13189 1
0.6%
6984 1
0.6%
5304 1
0.6%
5254 1
0.6%
4744 1
0.6%
3765 1
0.6%
3176 1
0.6%
2487 1
0.6%
2352 1
0.6%
1775 1
0.6%

2일 이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct90
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean493.17901
Minimum0
Maximum13597
Zeros9
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:07:19.544820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.05
Q14
median19.5
Q3100.25
95-th percentile2861.8
Maximum13597
Range13597
Interquartile range (IQR)96.25

Descriptive statistics

Standard deviation1801.7591
Coefficient of variation (CV)3.6533572
Kurtosis30.774974
Mean493.17901
Median Absolute Deviation (MAD)18.5
Skewness5.3334809
Sum79895
Variance3246335.8
MonotonicityNot monotonic
2023-12-13T03:07:19.800164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 10
 
6.2%
1 10
 
6.2%
0 9
 
5.6%
3 8
 
4.9%
2 6
 
3.7%
13 6
 
3.7%
6 5
 
3.1%
10 5
 
3.1%
5 4
 
2.5%
7 4
 
2.5%
Other values (80) 95
58.6%
ValueCountFrequency (%)
0 9
5.6%
1 10
6.2%
2 6
3.7%
3 8
4.9%
4 10
6.2%
5 4
 
2.5%
6 5
3.1%
7 4
 
2.5%
8 2
 
1.2%
9 2
 
1.2%
ValueCountFrequency (%)
13597 1
0.6%
11792 1
0.6%
9157 1
0.6%
7893 1
0.6%
5357 1
0.6%
3815 1
0.6%
3704 1
0.6%
3023 1
0.6%
2877 1
0.6%
2573 1
0.6%

5일 이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct112
Distinct (%)69.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1021.9877
Minimum0
Maximum25543
Zeros5
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:07:19.965345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q113
median41
Q3251.75
95-th percentile5332.35
Maximum25543
Range25543
Interquartile range (IQR)238.75

Descriptive statistics

Standard deviation3694.7982
Coefficient of variation (CV)3.6153061
Kurtosis27.593595
Mean1021.9877
Median Absolute Deviation (MAD)38
Skewness5.1490593
Sum165562
Variance13651534
MonotonicityNot monotonic
2023-12-13T03:07:20.133162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 8
 
4.9%
0 5
 
3.1%
2 5
 
3.1%
4 4
 
2.5%
13 4
 
2.5%
3 4
 
2.5%
19 3
 
1.9%
17 3
 
1.9%
25 3
 
1.9%
26 3
 
1.9%
Other values (102) 120
74.1%
ValueCountFrequency (%)
0 5
3.1%
1 8
4.9%
2 5
3.1%
3 4
2.5%
4 4
2.5%
5 3
 
1.9%
6 1
 
0.6%
7 1
 
0.6%
8 2
 
1.2%
10 2
 
1.2%
ValueCountFrequency (%)
25543 1
0.6%
22506 1
0.6%
21788 1
0.6%
19374 1
0.6%
10169 1
0.6%
7566 1
0.6%
7159 1
0.6%
6777 1
0.6%
5370 1
0.6%
4617 1
0.6%

10일 이내
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct117
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean941.83333
Minimum0
Maximum24791
Zeros4
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:07:20.300139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q117.5
median62
Q3317.25
95-th percentile5026.45
Maximum24791
Range24791
Interquartile range (IQR)299.75

Descriptive statistics

Standard deviation3213.4094
Coefficient of variation (CV)3.4118663
Kurtosis30.376844
Mean941.83333
Median Absolute Deviation (MAD)57
Skewness5.269529
Sum152577
Variance10326000
MonotonicityNot monotonic
2023-12-13T03:07:20.466439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 5
 
3.1%
2 5
 
3.1%
20 4
 
2.5%
0 4
 
2.5%
19 4
 
2.5%
9 3
 
1.9%
35 3
 
1.9%
5 3
 
1.9%
8 3
 
1.9%
3 3
 
1.9%
Other values (107) 125
77.2%
ValueCountFrequency (%)
0 4
2.5%
1 3
1.9%
2 5
3.1%
3 3
1.9%
4 5
3.1%
5 3
1.9%
6 3
1.9%
7 3
1.9%
8 3
1.9%
9 3
1.9%
ValueCountFrequency (%)
24791 1
0.6%
19489 1
0.6%
17726 1
0.6%
12254 1
0.6%
11470 1
0.6%
6932 1
0.6%
6001 1
0.6%
5792 1
0.6%
5049 1
0.6%
4598 1
0.6%

1개월 이내
Real number (ℝ)

HIGH CORRELATION 

Distinct136
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1488.4444
Minimum1
Maximum32386
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:07:20.620444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.05
Q130.75
median167.5
Q3639.75
95-th percentile6877.1
Maximum32386
Range32385
Interquartile range (IQR)609

Descriptive statistics

Standard deviation4613.779
Coefficient of variation (CV)3.0997321
Kurtosis29.628142
Mean1488.4444
Median Absolute Deviation (MAD)147.5
Skewness5.250341
Sum241128
Variance21286957
MonotonicityNot monotonic
2023-12-13T03:07:20.781100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84 4
 
2.5%
29 4
 
2.5%
1 4
 
2.5%
27 3
 
1.9%
6 3
 
1.9%
42 2
 
1.2%
85 2
 
1.2%
265 2
 
1.2%
26 2
 
1.2%
30 2
 
1.2%
Other values (126) 134
82.7%
ValueCountFrequency (%)
1 4
2.5%
3 2
1.2%
4 2
1.2%
5 1
 
0.6%
6 3
1.9%
7 1
 
0.6%
8 2
1.2%
10 2
1.2%
11 1
 
0.6%
12 1
 
0.6%
ValueCountFrequency (%)
32386 1
0.6%
31049 1
0.6%
27759 1
0.6%
20611 1
0.6%
9234 1
0.6%
8563 1
0.6%
8234 1
0.6%
7683 1
0.6%
6878 1
0.6%
6860 1
0.6%

3개월 이내
Real number (ℝ)

HIGH CORRELATION 

Distinct145
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1274.6543
Minimum0
Maximum48664
Zeros1
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:07:20.952196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.15
Q151.5
median195
Q3652
95-th percentile4831.65
Maximum48664
Range48664
Interquartile range (IQR)600.5

Descriptive statistics

Standard deviation4424.6805
Coefficient of variation (CV)3.4712788
Kurtosis84.109158
Mean1274.6543
Median Absolute Deviation (MAD)173.5
Skewness8.3860725
Sum206494
Variance19577798
MonotonicityNot monotonic
2023-12-13T03:07:21.120684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 4
 
2.5%
142 2
 
1.2%
28 2
 
1.2%
5 2
 
1.2%
50 2
 
1.2%
26 2
 
1.2%
137 2
 
1.2%
16 2
 
1.2%
236 2
 
1.2%
17 2
 
1.2%
Other values (135) 140
86.4%
ValueCountFrequency (%)
0 1
 
0.6%
2 4
2.5%
3 1
 
0.6%
5 2
1.2%
6 1
 
0.6%
9 2
1.2%
11 2
1.2%
14 1
 
0.6%
16 2
1.2%
17 2
1.2%
ValueCountFrequency (%)
48664 1
0.6%
19478 1
0.6%
12175 1
0.6%
10970 1
0.6%
8857 1
0.6%
6577 1
0.6%
6172 1
0.6%
6112 1
0.6%
4840 1
0.6%
4673 1
0.6%

3개월 초과
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct153
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2125.9383
Minimum0
Maximum109448
Zeros2
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T03:07:21.277763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q1111.5
median328
Q31015.75
95-th percentile8180.1
Maximum109448
Range109448
Interquartile range (IQR)904.25

Descriptive statistics

Standard deviation9159.4695
Coefficient of variation (CV)4.3084362
Kurtosis119.00154
Mean2125.9383
Median Absolute Deviation (MAD)282
Skewness10.339322
Sum344402
Variance83895881
MonotonicityNot monotonic
2023-12-13T03:07:21.420145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
328 2
 
1.2%
113 2
 
1.2%
31 2
 
1.2%
9 2
 
1.2%
10 2
 
1.2%
1 2
 
1.2%
0 2
 
1.2%
120 2
 
1.2%
61 2
 
1.2%
842 1
 
0.6%
Other values (143) 143
88.3%
ValueCountFrequency (%)
0 2
1.2%
1 2
1.2%
3 1
0.6%
6 1
0.6%
9 2
1.2%
10 2
1.2%
11 1
0.6%
13 1
0.6%
14 1
0.6%
21 1
0.6%
ValueCountFrequency (%)
109448 1
0.6%
27844 1
0.6%
19115 1
0.6%
15200 1
0.6%
15096 1
0.6%
10688 1
0.6%
9224 1
0.6%
8417 1
0.6%
8232 1
0.6%
7194 1
0.6%

Interactions

2023-12-13T03:07:15.919154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:04.519369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:05.748938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:07.052825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:08.439810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:09.379932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:10.314564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:11.406872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:12.358191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:13.650464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:14.832468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:15.997370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:04.611647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:05.877329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:07.161431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:08.517160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:09.450190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:10.407411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:11.487644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:12.433103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:13.818016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:14.931975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:16.098731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:04.730806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:06.001947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:07.287432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:08.615720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:09.540542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:10.506519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:11.588886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:12.533329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:13.937179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:15.025372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:16.207335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:04.847464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:06.109857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:07.689098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:08.707506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:09.625499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:10.639485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:11.681657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:12.624745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:14.056087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:15.123599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:16.291446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:04.962048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:06.216574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:07.783901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:08.782407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:09.712838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:10.734303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:11.777058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:12.715431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:14.158439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:15.245902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:16.388964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:05.082968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:06.338930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:07.879691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:08.865179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:09.800716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:10.830538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:11.854684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:12.801430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:14.250510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:15.346061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:16.504119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:05.187909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:06.456323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:07.979960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:08.972756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:09.885558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:10.930372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:11.946573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:12.905698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:14.352941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:15.441769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:16.591228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:05.293275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:06.566417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:08.091636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:09.055628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:09.974938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:11.020553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:12.036068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:12.984219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:14.447411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:15.533517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:16.666410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:05.404240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:06.679724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:08.178639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:09.138306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:10.050585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:11.118235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:12.117724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:13.056623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:14.535812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:15.639840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:16.756106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:05.503999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:06.795841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:08.268973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:09.224719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:10.135332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:11.215840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:12.200768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:13.457413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:14.634454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:15.732331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:16.843553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:05.633701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:06.922349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:08.353719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:09.300702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:10.229571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:11.307256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:12.276246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:13.544980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:14.717002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:15.826553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:07:21.526921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1시간 이내2시간 이내5시간 이내12시간 이내24시간 이내2일 이내5일 이내10일 이내1개월 이내3개월 이내3개월 초과
1시간 이내1.0000.9090.9790.9660.9160.9620.8910.9590.9670.7240.419
2시간 이내0.9091.0000.9310.8760.9180.9580.8710.8320.8210.8780.212
5시간 이내0.9790.9311.0000.9950.9610.9690.9010.9730.9550.7850.453
12시간 이내0.9660.8760.9951.0000.9160.9620.9090.9630.9630.8240.735
24시간 이내0.9160.9180.9610.9161.0000.9610.9840.9130.8800.8310.550
2일 이내0.9620.9580.9690.9620.9611.0001.0000.9650.9450.9260.938
5일 이내0.8910.8710.9010.9090.9841.0001.0000.9270.9000.9080.785
10일 이내0.9590.8320.9730.9630.9130.9650.9271.0000.9620.8300.619
1개월 이내0.9670.8210.9550.9630.8800.9450.9000.9621.0000.8200.654
3개월 이내0.7240.8780.7850.8240.8310.9260.9080.8300.8201.0000.810
3개월 초과0.4190.2120.4530.7350.5500.9380.7850.6190.6540.8101.000
2023-12-13T03:07:21.676455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1시간 이내2시간 이내5시간 이내12시간 이내24시간 이내2일 이내5일 이내10일 이내1개월 이내3개월 이내3개월 초과
1시간 이내1.0000.8870.9100.9340.9420.9290.9160.8960.8860.8360.589
2시간 이내0.8871.0000.9550.8740.8930.8820.8550.8220.7770.6940.370
5시간 이내0.9100.9551.0000.8930.9050.9010.8740.8360.7890.7120.418
12시간 이내0.9340.8740.8931.0000.9510.9500.9490.9320.8980.8280.556
24시간 이내0.9420.8930.9050.9511.0000.9570.9500.9430.9160.8430.549
2일 이내0.9290.8820.9010.9500.9571.0000.9740.9520.9200.8400.530
5일 이내0.9160.8550.8740.9490.9500.9741.0000.9780.9480.8670.542
10일 이내0.8960.8220.8360.9320.9430.9520.9781.0000.9760.9050.592
1개월 이내0.8860.7770.7890.8980.9160.9200.9480.9761.0000.9580.666
3개월 이내0.8360.6940.7120.8280.8430.8400.8670.9050.9581.0000.794
3개월 초과0.5890.3700.4180.5560.5490.5300.5420.5920.6660.7941.000

Missing values

2023-12-13T03:07:16.968284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:07:17.146896image/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

범죄분류1시간 이내2시간 이내5시간 이내12시간 이내24시간 이내2일 이내5일 이내10일 이내1개월 이내3개월 이내3개월 초과
0절도2019152129485112591318913597255432479132386194789224
1장물88152229323787113263374874
2사기108142136367441174744535710169114703104948664109448
3횡령415910161536171324872573461750497683657715200
4배임1715924151329431814024345
5손괴82902306306933753765381575666932923461122094
6살인2163811114087484128294476
7강도2254085112616384571135991
8방화34482116134100791059113412548
9성폭력60511684233014661236158332212881472135684083
범죄분류1시간 이내2시간 이내5시간 이내12시간 이내24시간 이내2일 이내5일 이내10일 이내1개월 이내3개월 이내3개월 초과
152폐기물관리법9541222222472166373333515
153풍속영업의규제에관한법률3347611132926491611
154하천법2103637202731113
155학교보건법500043414271114
156학원의설립운영및과외교습에관한법률1200876174095101225
157화물자동차운수사업법2184748375992209322566380132
158화재로인한재해보상과보험가입에관한법률40000123320
159화재예방,소방시설설치유지및안전관리에관한법률00030022459
160화학물질관리법832163301315251542119253
161기타특별법8867870951103711691381325145986878617215096