Overview

Dataset statistics

Number of variables5
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory44.3 B

Variable types

Categorical3
Text1
Numeric1

Dataset

Description2023. 1. 1.~2024. 1. 30.까지 광주광역시경찰청 신고접수 건수에 대한 데이터로, 경찰서별 파출소 및 지구대 신고건수를 제공합니다.
Author경찰청 광주광역시경찰청
URLhttps://www.data.go.kr/data/15113437/fileData.do

Alerts

구분 has constant value ""Constant
신고출동 조회기간 has constant value ""Constant
신고출동 건수 has unique valuesUnique

Reproduction

Analysis started2024-04-17 17:39:35.625106
Analysis finished2024-04-17 17:39:35.913789
Duration0.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
광주광역시경찰청
40 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주광역시경찰청 40
100.0%

Length

2024-04-18T02:39:35.957789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:39:36.027016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주광역시경찰청 40
100.0%

경찰서
Categorical

Distinct5
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
광주광산서
13 
광주북부서
9 
광주서부서
7 
광주남부서
6 
광주동부서
5 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주광산서 13
32.5%
광주북부서 9
22.5%
광주서부서 7
17.5%
광주남부서 6
15.0%
광주동부서 5
 
12.5%

Length

2024-04-18T02:39:36.100256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:39:36.180015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주광산서 13
32.5%
광주북부서 9
22.5%
광주서부서 7
17.5%
광주남부서 6
15.0%
광주동부서 5
 
12.5%

파출소 및 지구대
Text

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-04-18T02:39:36.337243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters200
Distinct characters61
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

Unique38 ?
Unique (%)95.0%

Sample

1st row수완지구대
2nd row우산지구대
3rd row월곡지구대
4th row첨단지구대
5th row동곡파출소
ValueCountFrequency (%)
우산지구대 2
 
5.0%
수완지구대 1
 
2.5%
농성파출소 1
 
2.5%
동천파출소 1
 
2.5%
염주파출소 1
 
2.5%
풍암파출소 1
 
2.5%
대촌파출소 1
 
2.5%
백운지구대 1
 
2.5%
방림지구대 1
 
2.5%
건국지구대 1
 
2.5%
Other values (29) 29
72.5%
2024-04-18T02:39:36.585202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 21
 
10.5%
파 21
 
10.5%
출 21
 
10.5%
소 21
 
10.5%
대 20
 
10.0%
구 19
 
9.5%
곡 5
 
2.5%
산 5
 
2.5%
동 4
 
2.0%
우 2
 
1.0%
Other values (51) 61
30.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 200
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 21
 
10.5%
파 21
 
10.5%
출 21
 
10.5%
소 21
 
10.5%
대 20
 
10.0%
구 19
 
9.5%
곡 5
 
2.5%
산 5
 
2.5%
동 4
 
2.0%
우 2
 
1.0%
Other values (51) 61
30.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 200
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 21
 
10.5%
파 21
 
10.5%
출 21
 
10.5%
소 21
 
10.5%
대 20
 
10.0%
구 19
 
9.5%
곡 5
 
2.5%
산 5
 
2.5%
동 4
 
2.0%
우 2
 
1.0%
Other values (51) 61
30.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 200
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 21
 
10.5%
파 21
 
10.5%
출 21
 
10.5%
소 21
 
10.5%
대 20
 
10.0%
구 19
 
9.5%
곡 5
 
2.5%
산 5
 
2.5%
동 4
 
2.0%
우 2
 
1.0%
Other values (51) 61
30.5%

신고출동 조회기간
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-01-01~2024-01-30
40 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-01-01~2024-01-30
2nd row2023-01-01~2024-01-30
3rd row2023-01-01~2024-01-30
4th row2023-01-01~2024-01-30
5th row2023-01-01~2024-01-30

Common Values

ValueCountFrequency (%)
2023-01-01~2024-01-30 40
100.0%

Length

2024-04-18T02:39:36.698740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:39:36.772150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-01-01~2024-01-30 40
100.0%

신고출동 건수
Real number (ℝ)

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8184.05
Minimum202
Maximum27313
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-18T02:39:36.861229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202
5-th percentile552.45
Q12389.5
median7121.5
Q311914
95-th percentile17879.25
Maximum27313
Range27111
Interquartile range (IQR)9524.5

Descriptive statistics

Standard deviation6760.1339
Coefficient of variation (CV)0.82601327
Kurtosis0.60247074
Mean8184.05
Median Absolute Deviation (MAD)4957.5
Skewness0.91032654
Sum327362
Variance45699410
MonotonicityNot monotonic
2024-04-18T02:39:36.958638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
24686 1
 
2.5%
6093 1
 
2.5%
892 1
 
2.5%
931 1
 
2.5%
1243 1
 
2.5%
9609 1
 
2.5%
9275 1
 
2.5%
10215 1
 
2.5%
2725 1
 
2.5%
3954 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
202 1
2.5%
333 1
2.5%
564 1
2.5%
581 1
2.5%
700 1
2.5%
892 1
2.5%
931 1
2.5%
1243 1
2.5%
1675 1
2.5%
1713 1
2.5%
ValueCountFrequency (%)
27313 1
2.5%
24686 1
2.5%
17521 1
2.5%
17004 1
2.5%
16640 1
2.5%
16231 1
2.5%
15481 1
2.5%
13690 1
2.5%
13590 1
2.5%
12775 1
2.5%

Interactions

2024-04-18T02:39:35.733331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T02:39:37.020610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경찰서파출소 및 지구대신고출동 건수
경찰서1.0000.9240.397
파출소 및 지구대0.9241.0000.384
신고출동 건수0.3970.3841.000
2024-04-18T02:39:37.087617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신고출동 건수경찰서
신고출동 건수1.0000.254
경찰서0.2541.000

Missing values

2024-04-18T02:39:35.814081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T02:39:35.884290image/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

구분경찰서파출소 및 지구대신고출동 조회기간신고출동 건수
0광주광역시경찰청광주광산서수완지구대2023-01-01~2024-01-3024686
1광주광역시경찰청광주광산서우산지구대2023-01-01~2024-01-3011627
2광주광역시경찰청광주광산서월곡지구대2023-01-01~2024-01-309988
3광주광역시경찰청광주광산서첨단지구대2023-01-01~2024-01-3017004
4광주광역시경찰청광주광산서동곡파출소2023-01-01~2024-01-30564
5광주광역시경찰청광주광산서하남파출소2023-01-01~2024-01-306661
6광주광역시경찰청광주광산서삼도파출소2023-01-01~2024-01-30581
7광주광역시경찰청광주광산서본량파출소2023-01-01~2024-01-30202
8광주광역시경찰청광주광산서도산파출소2023-01-01~2024-01-308656
9광주광역시경찰청광주광산서송정파출소2023-01-01~2024-01-303499
구분경찰서파출소 및 지구대신고출동 조회기간신고출동 건수
30광주광역시경찰청광주남부서주월파출소2023-01-01~2024-01-303954
31광주광역시경찰청광주북부서동운지구대2023-01-01~2024-01-3012775
32광주광역시경찰청광주북부서두암지구대2023-01-01~2024-01-3011074
33광주광역시경찰청광주북부서용봉지구대2023-01-01~2024-01-308181
34광주광역시경찰청광주북부서일곡지구대2023-01-01~2024-01-3013590
35광주광역시경찰청광주북부서문흥지구대2023-01-01~2024-01-309549
36광주광역시경찰청광주북부서역전지구대2023-01-01~2024-01-307191
37광주광역시경찰청광주북부서건국지구대2023-01-01~2024-01-3013690
38광주광역시경찰청광주북부서우산지구대2023-01-01~2024-01-3016231
39광주광역시경찰청광주북부서석곡파출소2023-01-01~2024-01-30700