Overview

Dataset statistics

Number of variables4
Number of observations258
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory35.5 B

Variable types

Numeric2
Categorical1
Text1

Dataset

Description전국 경찰서별 강간/강제추행 발생현황자료입니다. 구분 : 연번, 연도, 관서명, 발생건수입니다. 지방청별 발생현황은 이미 공공데이터 포털에 등록되어 있으니 참고하여 주시기 바랍니다.
URLhttps://www.data.go.kr/data/15104282/fileData.do

Alerts

연도 has constant value ""Constant
연번 is highly overall correlated with 발생건수High correlation
발생건수 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
관서구분 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:35:53.702608
Analysis finished2023-12-12 20:35:54.279160
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct258
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.5
Minimum1
Maximum258
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-13T05:35:54.393327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.85
Q165.25
median129.5
Q3193.75
95-th percentile245.15
Maximum258
Range257
Interquartile range (IQR)128.5

Descriptive statistics

Standard deviation74.622383
Coefficient of variation (CV)0.57623462
Kurtosis-1.2
Mean129.5
Median Absolute Deviation (MAD)64.5
Skewness0
Sum33411
Variance5568.5
MonotonicityStrictly increasing
2023-12-13T05:35:54.576484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
195 1
 
0.4%
165 1
 
0.4%
166 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
172 1
 
0.4%
Other values (248) 248
96.1%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
258 1
0.4%
257 1
0.4%
256 1
0.4%
255 1
0.4%
254 1
0.4%
253 1
0.4%
252 1
0.4%
251 1
0.4%
250 1
0.4%
249 1
0.4%

연도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2021
258 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 258
100.0%

Length

2023-12-13T05:35:54.727272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:35:54.873408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 258
100.0%

관서구분
Text

UNIQUE 

Distinct258
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-13T05:35:55.158345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7.3100775
Min length6

Characters and Unicode

Total characters1886
Distinct characters141
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique258 ?
Unique (%)100.0%

Sample

1st row서울중부경찰서
2nd row서울종로경찰서
3rd row서울남대문경찰서
4th row서울서대문경찰서
5th row서울혜화경찰서
ValueCountFrequency (%)
서울중부경찰서 1
 
0.4%
전남고흥경찰서 1
 
0.4%
충남공주경찰서 1
 
0.4%
전북무주경찰서 1
 
0.4%
충남보령경찰서 1
 
0.4%
충남당진경찰서 1
 
0.4%
충남홍성경찰서 1
 
0.4%
충남예산경찰서 1
 
0.4%
충남부여경찰서 1
 
0.4%
충남서천경찰서 1
 
0.4%
Other values (248) 248
96.1%
2023-12-13T05:35:55.693690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 352
18.7%
서 313
16.6%
찰 258
13.7%
남 79
 
4.2%
부 69
 
3.7%
북 62
 
3.3%
기 45
 
2.4%
전 44
 
2.3%
산 43
 
2.3%
울 39
 
2.1%
Other values (131) 582
30.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1886
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 352
18.7%
서 313
16.6%
찰 258
13.7%
남 79
 
4.2%
부 69
 
3.7%
북 62
 
3.3%
기 45
 
2.4%
전 44
 
2.3%
산 43
 
2.3%
울 39
 
2.1%
Other values (131) 582
30.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1886
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 352
18.7%
서 313
16.6%
찰 258
13.7%
남 79
 
4.2%
부 69
 
3.7%
북 62
 
3.3%
기 45
 
2.4%
전 44
 
2.3%
산 43
 
2.3%
울 39
 
2.1%
Other values (131) 582
30.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1886
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 352
18.7%
서 313
16.6%
찰 258
13.7%
남 79
 
4.2%
부 69
 
3.7%
북 62
 
3.3%
기 45
 
2.4%
전 44
 
2.3%
산 43
 
2.3%
울 39
 
2.1%
Other values (131) 582
30.9%

발생건수
Real number (ℝ)

HIGH CORRELATION 

Distinct142
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.554264
Minimum1
Maximum428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-13T05:35:55.881138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.85
Q122.25
median66
Q3113
95-th percentile208.45
Maximum428
Range427
Interquartile range (IQR)90.75

Descriptive statistics

Standard deviation68.311991
Coefficient of variation (CV)0.86961532
Kurtosis3.2050423
Mean78.554264
Median Absolute Deviation (MAD)45
Skewness1.4758694
Sum20267
Variance4666.5282
MonotonicityNot monotonic
2023-12-13T05:35:56.040664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11 7
 
2.7%
12 5
 
1.9%
13 5
 
1.9%
7 5
 
1.9%
50 4
 
1.6%
40 4
 
1.6%
21 4
 
1.6%
51 4
 
1.6%
9 4
 
1.6%
25 4
 
1.6%
Other values (132) 212
82.2%
ValueCountFrequency (%)
1 1
 
0.4%
2 2
 
0.8%
3 3
1.2%
4 2
 
0.8%
5 4
1.6%
6 1
 
0.4%
7 5
1.9%
8 1
 
0.4%
9 4
1.6%
10 4
1.6%
ValueCountFrequency (%)
428 1
0.4%
321 2
0.8%
279 1
0.4%
265 1
0.4%
259 1
0.4%
257 1
0.4%
247 2
0.8%
246 1
0.4%
237 1
0.4%
221 1
0.4%

Interactions

2023-12-13T05:35:53.963551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:35:53.821297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:35:54.033397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:35:53.892007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:35:56.142908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번발생건수
연번1.0000.460
발생건수0.4601.000
2023-12-13T05:35:56.261934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번발생건수
연번1.000-0.556
발생건수-0.5561.000

Missing values

2023-12-13T05:35:54.137331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:35:54.236722image/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

연번연도관서구분발생건수
012021서울중부경찰서109
122021서울종로경찰서88
232021서울남대문경찰서52
342021서울서대문경찰서137
452021서울혜화경찰서68
562021서울용산경찰서141
672021서울성북경찰서78
782021서울동대문경찰서169
892021서울마포경찰서321
9102021서울영등포경찰서279
연번연도관서구분발생건수
2482492021경남고성경찰서16
2492502021경남하동경찰서11
2502512021경남남해경찰서9
2512522021경남함양경찰서7
2522532021경남산청경찰서4
2532542021경남함안경찰서13
2542552021경남의령경찰서9
2552562021제주서귀포경찰서104
2562572021제주동부경찰서158
2572582021제주서부경찰서139