Overview

Dataset statistics

Number of variables7
Number of observations88
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory63.5 B

Variable types

Text1
Numeric5
Categorical1

Dataset

Description대검찰청에서 발간하는 범죄분석은 3종의 범죄통계원표를 기반으로 작성하는 자료이며 이 중 본 데이터는 해양경찰이 관할하는 범죄 발생의 검거상황과 관련된 통계임
Author대검찰청
URLhttps://www.data.go.kr/data/15084780/fileData.do

Alerts

발생건수(건) is highly overall correlated with 검거건수(건) and 2 other fieldsHigh correlation
검거건수(건) is highly overall correlated with 발생건수(건) and 2 other fieldsHigh correlation
남자검거인원(명) is highly overall correlated with 발생건수(건) and 3 other fieldsHigh correlation
여자검거인원(명) is highly overall correlated with 남자검거인원(명) and 1 other fieldsHigh correlation
법인(개) is highly overall correlated with 미상검거인원(명)High correlation
미상검거인원(명) is highly overall correlated with 발생건수(건) and 4 other fieldsHigh correlation
미상검거인원(명) is highly imbalanced (65.8%)Imbalance
범죄분류 has unique valuesUnique
발생건수(건) has 6 (6.8%) zerosZeros
검거건수(건) has 6 (6.8%) zerosZeros
남자검거인원(명) has 5 (5.7%) zerosZeros
여자검거인원(명) has 47 (53.4%) zerosZeros
법인(개) has 64 (72.7%) zerosZeros

Reproduction

Analysis started2023-12-13 00:54:28.265153
Analysis finished2023-12-13 00:54:30.282007
Duration2.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

범죄분류
Text

UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size836.0 B
2023-12-13T09:54:30.435470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length20
Mean length6.5681818
Min length2

Characters and Unicode

Total characters578
Distinct characters162
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)100.0%

Sample

1st row절도
2nd row불법사용
3rd row침입절도
4th row장물
5th row사기
ValueCountFrequency (%)
관한법률 6
 
4.8%
및 6
 
4.8%
마약류관리에 2
 
1.6%
건설기계관리법 1
 
0.8%
산업안전보건법 1
 
0.8%
보조금관리에관한법률 1
 
0.8%
행사에 1
 
0.8%
주권적권리의 1
 
0.8%
관한 1
 
0.8%
외국인어업등에 1
 
0.8%
Other values (103) 103
83.1%
2023-12-13T09:54:30.738643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
법 44
 
7.6%
36
 
6.2%
관 25
 
4.3%
리 17
 
2.9%
에 11
 
1.9%
기 10
 
1.7%
한 10
 
1.7%
사 10
 
1.7%
수 10
 
1.7%
업 10
 
1.7%
Other values (152) 395
68.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 528
91.3%
Space Separator 36
 
6.2%
Open Punctuation 5
 
0.9%
Close Punctuation 5
 
0.9%
Other Punctuation 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
법 44
 
8.3%
관 25
 
4.7%
리 17
 
3.2%
에 11
 
2.1%
기 10
 
1.9%
한 10
 
1.9%
사 10
 
1.9%
수 10
 
1.9%
업 10
 
1.9%
률 9
 
1.7%
Other values (147) 372
70.5%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
/ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 528
91.3%
Common 50
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
법 44
 
8.3%
관 25
 
4.7%
리 17
 
3.2%
에 11
 
2.1%
기 10
 
1.9%
한 10
 
1.9%
사 10
 
1.9%
수 10
 
1.9%
업 10
 
1.9%
률 9
 
1.7%
Other values (147) 372
70.5%
Common
ValueCountFrequency (%)
36
72.0%
( 5
 
10.0%
) 5
 
10.0%
, 3
 
6.0%
/ 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 528
91.3%
ASCII 50
 
8.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
법 44
 
8.3%
관 25
 
4.7%
리 17
 
3.2%
에 11
 
2.1%
기 10
 
1.9%
한 10
 
1.9%
사 10
 
1.9%
수 10
 
1.9%
업 10
 
1.9%
률 9
 
1.7%
Other values (147) 372
70.5%
ASCII
ValueCountFrequency (%)
36
72.0%
( 5
 
10.0%
) 5
 
10.0%
, 3
 
6.0%
/ 1
 
2.0%

발생건수(건)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct51
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean297.84091
Minimum0
Maximum9546
Zeros6
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size924.0 B
2023-12-13T09:54:30.848741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q3135
95-th percentile944.8
Maximum9546
Range9546
Interquartile range (IQR)134

Descriptive statistics

Standard deviation1132.5445
Coefficient of variation (CV)3.8025148
Kurtosis53.39668
Mean297.84091
Median Absolute Deviation (MAD)8
Skewness6.9214933
Sum26210
Variance1282656.9
MonotonicityNot monotonic
2023-12-13T09:54:30.950689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 19
21.6%
2 7
 
8.0%
0 6
 
6.8%
3 4
 
4.5%
5 3
 
3.4%
17 2
 
2.3%
7 2
 
2.3%
4 2
 
2.3%
2270 1
 
1.1%
303 1
 
1.1%
Other values (41) 41
46.6%
ValueCountFrequency (%)
0 6
 
6.8%
1 19
21.6%
2 7
 
8.0%
3 4
 
4.5%
4 2
 
2.3%
5 3
 
3.4%
6 1
 
1.1%
7 2
 
2.3%
9 1
 
1.1%
10 1
 
1.1%
ValueCountFrequency (%)
9546 1
1.1%
4136 1
1.1%
2270 1
1.1%
966 1
1.1%
949 1
1.1%
937 1
1.1%
921 1
1.1%
651 1
1.1%
584 1
1.1%
582 1
1.1%

검거건수(건)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean295.78409
Minimum0
Maximum9519
Zeros6
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size924.0 B
2023-12-13T09:54:31.052703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7.5
Q3110
95-th percentile944.45
Maximum9519
Range9519
Interquartile range (IQR)109

Descriptive statistics

Standard deviation1129.2141
Coefficient of variation (CV)3.8176971
Kurtosis53.438861
Mean295.78409
Median Absolute Deviation (MAD)7.5
Skewness6.9242471
Sum26029
Variance1275124.4
MonotonicityNot monotonic
2023-12-13T09:54:31.151847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 18
20.5%
2 8
 
9.1%
0 6
 
6.8%
3 5
 
5.7%
48 3
 
3.4%
5 3
 
3.4%
7 3
 
3.4%
579 2
 
2.3%
24 2
 
2.3%
17 2
 
2.3%
Other values (35) 36
40.9%
ValueCountFrequency (%)
0 6
 
6.8%
1 18
20.5%
2 8
9.1%
3 5
 
5.7%
4 1
 
1.1%
5 3
 
3.4%
7 3
 
3.4%
8 1
 
1.1%
10 1
 
1.1%
17 2
 
2.3%
ValueCountFrequency (%)
9519 1
1.1%
4115 1
1.1%
2269 1
1.1%
963 1
1.1%
949 1
1.1%
936 1
1.1%
919 1
1.1%
651 1
1.1%
579 2
2.3%
503 1
1.1%

남자검거인원(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.079545
Minimum0
Maximum1946
Zeros5
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size924.0 B
2023-12-13T09:54:31.255727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.35
Q11.75
median6.5
Q331.75
95-th percentile222.45
Maximum1946
Range1946
Interquartile range (IQR)30

Descriptive statistics

Standard deviation232.32682
Coefficient of variation (CV)3.3631782
Kurtosis50.696161
Mean69.079545
Median Absolute Deviation (MAD)5.5
Skewness6.6592498
Sum6079
Variance53975.752
MonotonicityNot monotonic
2023-12-13T09:54:31.359068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 17
19.3%
2 8
 
9.1%
5 5
 
5.7%
0 5
 
5.7%
6 4
 
4.5%
10 3
 
3.4%
4 3
 
3.4%
11 2
 
2.3%
9 2
 
2.3%
7 2
 
2.3%
Other values (35) 37
42.0%
ValueCountFrequency (%)
0 5
 
5.7%
1 17
19.3%
2 8
9.1%
3 2
 
2.3%
4 3
 
3.4%
5 5
 
5.7%
6 4
 
4.5%
7 2
 
2.3%
8 1
 
1.1%
9 2
 
2.3%
ValueCountFrequency (%)
1946 1
1.1%
772 1
1.1%
580 1
1.1%
301 1
1.1%
227 1
1.1%
214 1
1.1%
191 1
1.1%
160 1
1.1%
150 1
1.1%
144 1
1.1%

여자검거인원(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4
Minimum0
Maximum112
Zeros47
Zeros (%)53.4%
Negative0
Negative (%)0.0%
Memory size924.0 B
2023-12-13T09:54:31.453091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile14.3
Maximum112
Range112
Interquartile range (IQR)3

Descriptive statistics

Standard deviation13.547702
Coefficient of variation (CV)3.3869255
Kurtosis48.698972
Mean4
Median Absolute Deviation (MAD)0
Skewness6.5491015
Sum352
Variance183.54023
MonotonicityNot monotonic
2023-12-13T09:54:31.527247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 47
53.4%
1 16
 
18.2%
3 5
 
5.7%
4 4
 
4.5%
2 2
 
2.3%
5 2
 
2.3%
10 2
 
2.3%
8 2
 
2.3%
13 2
 
2.3%
17 1
 
1.1%
Other values (5) 5
 
5.7%
ValueCountFrequency (%)
0 47
53.4%
1 16
 
18.2%
2 2
 
2.3%
3 5
 
5.7%
4 4
 
4.5%
5 2
 
2.3%
6 1
 
1.1%
8 2
 
2.3%
10 2
 
2.3%
13 2
 
2.3%
ValueCountFrequency (%)
112 1
1.1%
52 1
1.1%
27 1
1.1%
17 1
1.1%
15 1
1.1%
13 2
2.3%
10 2
2.3%
8 2
2.3%
6 1
1.1%
5 2
2.3%

미상검거인원(명)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size836.0 B
0
76 
1
 
7
3
 
2
2
 
2
65
 
1

Length

Max length2
Median length1
Mean length1.0113636
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 76
86.4%
1 7
 
8.0%
3 2
 
2.3%
2 2
 
2.3%
65 1
 
1.1%

Length

2023-12-13T09:54:31.614540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:54:31.692867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 76
86.4%
1 7
 
8.0%
3 2
 
2.3%
2 2
 
2.3%
65 1
 
1.1%

법인(개)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4886364
Minimum0
Maximum361
Zeros64
Zeros (%)72.7%
Negative0
Negative (%)0.0%
Memory size924.0 B
2023-12-13T09:54:31.768318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile11.65
Maximum361
Range361
Interquartile range (IQR)1

Descriptive statistics

Standard deviation39.257767
Coefficient of variation (CV)6.0502338
Kurtosis78.86649
Mean6.4886364
Median Absolute Deviation (MAD)0
Skewness8.7114484
Sum571
Variance1541.1723
MonotonicityNot monotonic
2023-12-13T09:54:31.869776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 64
72.7%
1 10
 
11.4%
7 2
 
2.3%
2 2
 
2.3%
10 2
 
2.3%
13 1
 
1.1%
49 1
 
1.1%
9 1
 
1.1%
11 1
 
1.1%
65 1
 
1.1%
Other values (3) 3
 
3.4%
ValueCountFrequency (%)
0 64
72.7%
1 10
 
11.4%
2 2
 
2.3%
3 1
 
1.1%
7 2
 
2.3%
9 1
 
1.1%
10 2
 
2.3%
11 1
 
1.1%
12 1
 
1.1%
13 1
 
1.1%
ValueCountFrequency (%)
361 1
1.1%
65 1
1.1%
49 1
1.1%
13 1
1.1%
12 1
1.1%
11 1
1.1%
10 2
2.3%
9 1
1.1%
7 2
2.3%
3 1
1.1%

Interactions

2023-12-13T09:54:29.826778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:28.519389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:28.857804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.188480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.515390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.890704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:28.578285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:28.922199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.251702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.580778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.948447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:28.634236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:28.990157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.312876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.635973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:30.017224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:28.725608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.072491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.383297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.703285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:30.077836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:28.792358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.127253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.448395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:54:29.760435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:54:31.947897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
범죄분류발생건수(건)검거건수(건)남자검거인원(명)여자검거인원(명)미상검거인원(명)법인(개)
범죄분류1.0001.0001.0001.0001.0001.0001.000
발생건수(건)1.0001.0001.0000.9690.9520.9591.000
검거건수(건)1.0001.0001.0000.9690.9520.9591.000
남자검거인원(명)1.0000.9690.9691.0000.9920.8840.746
여자검거인원(명)1.0000.9520.9520.9921.0000.8600.706
미상검거인원(명)1.0000.9590.9590.8840.8601.0000.826
법인(개)1.0001.0001.0000.7460.7060.8261.000
2023-12-13T09:54:32.036993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발생건수(건)검거건수(건)남자검거인원(명)여자검거인원(명)법인(개)미상검거인원(명)
발생건수(건)1.0000.9960.8560.4730.3930.712
검거건수(건)0.9961.0000.8590.4770.3950.712
남자검거인원(명)0.8560.8591.0000.5330.3640.538
여자검거인원(명)0.4730.4770.5331.0000.3400.501
법인(개)0.3930.3950.3640.3401.0000.845
미상검거인원(명)0.7120.7120.5380.5010.8451.000

Missing values

2023-12-13T09:54:30.163703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:54:30.248338image/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

범죄분류발생건수(건)검거건수(건)남자검거인원(명)여자검거인원(명)미상검거인원(명)법인(개)
0절도150103144100
1불법사용579000
2침입절도37369000
3장물18318418200
4사기5345032271700
5보험사기방지특별법220000
6횡령16616660300
7배임7718000
8배임수재001000
9배임증재002000
범죄분류발생건수(건)검거건수(건)남자검거인원(명)여자검거인원(명)미상검거인원(명)법인(개)
78전파법252425400
79정보통신망이용촉진 및 정보보호 등에 관한법률115101
80조세범처벌법28928923000
81주민등록법33101500
82직업안정법81815300
83축산물위생관리법4654651000
84출입국관리법3433458110
85폐기물관리법4748341112
86화학물질관리법222000
87기타특별법95469519194611265361