Overview

Dataset statistics

Number of variables4
Number of observations78
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory35.7 B

Variable types

Categorical3
Numeric1

Dataset

Description경찰청 의무경찰 지역별로 접수 현황은 연도별, 지역별, 유형별(일반, 특기별) 등의 항목으로 의무경찰 접수인원 현황을 제공합니다.※의무경찰 홈페이지는 2023년 7월에 서비스 종료(폐지)되어 더이상 운영되지 않습니다.이에 의무경찰과 관련된 파일 데이터도 업데이트를 진행하지 않음을 안내드립니다.
Author경찰청
URLhttps://www.data.go.kr/data/15064561/fileData.do

Reproduction

Analysis started2024-03-16 04:18:55.284859
Analysis finished2024-03-16 04:18:56.375306
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size756.0 B
2019
26 
2020
26 
2021
26 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 26
33.3%
2020 26
33.3%
2021 26
33.3%

Length

2024-03-16T13:18:56.506545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:18:56.740896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 26
33.3%
2020 26
33.3%
2021 26
33.3%

지역
Categorical

Distinct13
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size756.0 B
강원
6 
강원영동
6 
경기북부
6 
경남
6 
광주전남
6 
Other values (8)
48 

Length

Max length4
Median length2
Mean length2.9230769
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원
2nd row강원
3rd row강원영동
4th row강원영동
5th row경기북부

Common Values

ValueCountFrequency (%)
강원 6
 
7.7%
강원영동 6
 
7.7%
경기북부 6
 
7.7%
경남 6
 
7.7%
광주전남 6
 
7.7%
대구경북 6
 
7.7%
대전충남 6
 
7.7%
부산 6
 
7.7%
서울 6
 
7.7%
인천경기 6
 
7.7%
Other values (3) 18
23.1%

Length

2024-03-16T13:18:56.988637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강원 6
 
7.7%
강원영동 6
 
7.7%
경기북부 6
 
7.7%
경남 6
 
7.7%
광주전남 6
 
7.7%
대구경북 6
 
7.7%
대전충남 6
 
7.7%
부산 6
 
7.7%
서울 6
 
7.7%
인천경기 6
 
7.7%
Other values (3) 18
23.1%

유형
Categorical

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size756.0 B
일반
39 
특기
39 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반
2nd row특기
3rd row일반
4th row특기
5th row일반

Common Values

ValueCountFrequency (%)
일반 39
50.0%
특기 39
50.0%

Length

2024-03-16T13:18:57.255814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:18:57.583046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 39
50.0%
특기 39
50.0%

접수인원
Real number (ℝ)

Distinct75
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2236.641
Minimum1
Maximum24384
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2024-03-16T13:18:57.921945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.25
Q173.25
median323
Q32018
95-th percentile7708.55
Maximum24384
Range24383
Interquartile range (IQR)1944.75

Descriptive statistics

Standard deviation4407.8571
Coefficient of variation (CV)1.9707486
Kurtosis12.288566
Mean2236.641
Median Absolute Deviation (MAD)303
Skewness3.30699
Sum174458
Variance19429204
MonotonicityNot monotonic
2024-03-16T13:18:58.385692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37 3
 
3.8%
55 2
 
2.6%
1376 1
 
1.3%
1688 1
 
1.3%
110 1
 
1.3%
1616 1
 
1.3%
1 1
 
1.3%
16 1
 
1.3%
224 1
 
1.3%
404 1
 
1.3%
Other values (65) 65
83.3%
ValueCountFrequency (%)
1 1
1.3%
3 1
1.3%
5 1
1.3%
8 1
1.3%
13 1
1.3%
16 1
1.3%
24 1
1.3%
25 1
1.3%
26 1
1.3%
29 1
1.3%
ValueCountFrequency (%)
24384 1
1.3%
21097 1
1.3%
15379 1
1.3%
13197 1
1.3%
6740 1
1.3%
6626 1
1.3%
6307 1
1.3%
6111 1
1.3%
5832 1
1.3%
5779 1
1.3%

Interactions

2024-03-16T13:18:55.742522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:18:58.611683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도지역유형접수인원
연도1.0000.0000.0000.084
지역0.0001.0000.0000.258
유형0.0000.0001.0000.480
접수인원0.0840.2580.4801.000
2024-03-16T13:18:58.865538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역유형연도
지역1.0000.0000.000
유형0.0001.0000.000
연도0.0000.0001.000
2024-03-16T13:18:59.052682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
접수인원연도지역유형
접수인원1.0000.0450.1080.497
연도0.0451.0000.0000.000
지역0.1080.0001.0000.000
유형0.4970.0000.0001.000

Missing values

2024-03-16T13:18:56.106463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:18:56.263551image/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

연도지역유형접수인원
02019강원일반1376
12019강원특기5
22019강원영동일반154
32019강원영동특기37
42019경기북부일반6307
52019경기북부특기182
62019경남일반3517
72019경남특기45
82019광주전남일반5369
92019광주전남특기130
연도지역유형접수인원
682021서울일반6111
692021서울특기306
702021인천경기일반3548
712021인천경기특기190
722021전북일반553
732021전북특기26
742021제주일반340
752021제주특기8
762021충북일반379
772021충북특기25