Overview

Dataset statistics

Number of variables3
Number of observations1240
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.4 KiB
Average record size in memory25.1 B

Variable types

Text1
Categorical1
Numeric1

Dataset

Description2022년 서울경찰청 관할 31개 경찰서별 살인, 폭력 죄종 범죄자 연령대 현황으로 구분(경찰서별 살인,폭력), 연령(14세미만에서 미상까지), 범죄자수 등으로 파악한 현황입니다.
Author경찰청 서울특별시경찰청
URLhttps://www.data.go.kr/data/3075829/fileData.do

Alerts

범죄자 수 (인원) has 577 (46.5%) zerosZeros

Reproduction

Analysis started2024-03-14 17:29:27.314419
Analysis finished2024-03-14 17:29:28.075088
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

Distinct62
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
2024-03-15T02:29:29.053952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.1290323
Min length5

Characters and Unicode

Total characters6360
Distinct characters48
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중부 살인
2nd row중부 살인
3rd row중부 살인
4th row중부 살인
5th row중부 살인
ValueCountFrequency (%)
살인 620
25.0%
폭력 620
25.0%
종암 40
 
1.6%
중랑 40
 
1.6%
수서 40
 
1.6%
강남 40
 
1.6%
관악 40
 
1.6%
강서 40
 
1.6%
강동 40
 
1.6%
중부 40
 
1.6%
Other values (23) 920
37.1%
2024-03-15T02:29:31.174607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1240
19.5%
살 620
 
9.7%
인 620
 
9.7%
폭 620
 
9.7%
력 620
 
9.7%
서 200
 
3.1%
동 160
 
2.5%
강 160
 
2.5%
대 120
 
1.9%
문 120
 
1.9%
Other values (38) 1880
29.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5120
80.5%
Space Separator 1240
 
19.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
살 620
 
12.1%
인 620
 
12.1%
폭 620
 
12.1%
력 620
 
12.1%
서 200
 
3.9%
동 160
 
3.1%
강 160
 
3.1%
대 120
 
2.3%
문 120
 
2.3%
중 80
 
1.6%
Other values (37) 1800
35.2%
Space Separator
ValueCountFrequency (%)
1240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5120
80.5%
Common 1240
 
19.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
살 620
 
12.1%
인 620
 
12.1%
폭 620
 
12.1%
력 620
 
12.1%
서 200
 
3.9%
동 160
 
3.1%
강 160
 
3.1%
대 120
 
2.3%
문 120
 
2.3%
중 80
 
1.6%
Other values (37) 1800
35.2%
Common
ValueCountFrequency (%)
1240
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5120
80.5%
ASCII 1240
 
19.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1240
100.0%
Hangul
ValueCountFrequency (%)
살 620
 
12.1%
인 620
 
12.1%
폭 620
 
12.1%
력 620
 
12.1%
서 200
 
3.9%
동 160
 
3.1%
강 160
 
3.1%
대 120
 
2.3%
문 120
 
2.3%
중 80
 
1.6%
Other values (37) 1800
35.2%

연령
Categorical

Distinct20
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size9.8 KiB
14미만
 
62
14세
 
62
15세
 
62
16세
 
62
17세
 
62
Other values (15)
930 

Length

Max length5
Median length4.5
Mean length4.05
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row14미만
2nd row14세
3rd row15세
4th row16세
5th row17세

Common Values

ValueCountFrequency (%)
14미만 62
 
5.0%
14세 62
 
5.0%
15세 62
 
5.0%
16세 62
 
5.0%
17세 62
 
5.0%
18세 62
 
5.0%
19세 62
 
5.0%
20세 62
 
5.0%
21~25 62
 
5.0%
26~30 62
 
5.0%
Other values (10) 620
50.0%

Length

2024-03-15T02:29:31.640487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
14미만 62
 
5.0%
14세 62
 
5.0%
71이상 62
 
5.0%
65~70 62
 
5.0%
61~64 62
 
5.0%
56~60 62
 
5.0%
51~55 62
 
5.0%
46~50 62
 
5.0%
41~45 62
 
5.0%
36~40 62
 
5.0%
Other values (10) 620
50.0%

범죄자 수 (인원)
Real number (ℝ)

ZEROS 

Distinct228
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.754032
Minimum0
Maximum601
Zeros577
Zeros (%)46.5%
Negative0
Negative (%)0.0%
Memory size11.0 KiB
2024-03-15T02:29:32.152873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q360
95-th percentile211.05
Maximum601
Range601
Interquartile range (IQR)60

Descriptive statistics

Standard deviation75.191539
Coefficient of variation (CV)1.7587005
Kurtosis6.0669483
Mean42.754032
Median Absolute Deviation (MAD)1
Skewness2.2651391
Sum53015
Variance5653.7675
MonotonicityNot monotonic
2024-03-15T02:29:32.718931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 577
46.5%
1 69
 
5.6%
2 21
 
1.7%
7 17
 
1.4%
3 14
 
1.1%
11 13
 
1.0%
10 10
 
0.8%
8 10
 
0.8%
14 9
 
0.7%
6 9
 
0.7%
Other values (218) 491
39.6%
ValueCountFrequency (%)
0 577
46.5%
1 69
 
5.6%
2 21
 
1.7%
3 14
 
1.1%
4 7
 
0.6%
5 5
 
0.4%
6 9
 
0.7%
7 17
 
1.4%
8 10
 
0.8%
9 9
 
0.7%
ValueCountFrequency (%)
601 1
0.1%
451 1
0.1%
414 1
0.1%
399 1
0.1%
391 1
0.1%
359 1
0.1%
353 1
0.1%
321 1
0.1%
320 1
0.1%
315 1
0.1%

Interactions

2024-03-15T02:29:27.474649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:29:33.085693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분연령범죄자 수 (인원)
구분1.0000.0000.642
연령0.0001.0000.438
범죄자 수 (인원)0.6420.4381.000
2024-03-15T02:29:33.455382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
범죄자 수 (인원)연령
범죄자 수 (인원)1.0000.189
연령0.1891.000

Missing values

2024-03-15T02:29:27.824107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:29:28.019323image/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

구분연령범죄자 수 (인원)
0중부 살인14미만0
1중부 살인14세0
2중부 살인15세0
3중부 살인16세0
4중부 살인17세0
5중부 살인18세0
6중부 살인19세0
7중부 살인20세0
8중부 살인21~251
9중부 살인26~300
구분연령범죄자 수 (인원)
1230수서 폭력31~35133
1231수서 폭력36~40149
1232수서 폭력41~45151
1233수서 폭력46~50144
1234수서 폭력51~55154
1235수서 폭력56~60106
1236수서 폭력61~6477
1237수서 폭력65~7087
1238수서 폭력71이상102
1239수서 폭력미상43