Overview

Dataset statistics

Number of variables8
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory75.7 B

Variable types

Categorical2
Numeric6

Dataset

Description세종특별자치시경찰청 관내 연도별(2019~2022) 시간대별(심야, 새벽, 오전, 오후, 초저녁, 밤) 범죄(강력, 절도,폭력, 지능, 풍속, 기타 등) 발생 현황
URLhttps://www.data.go.kr/data/15116636/fileData.do

Alerts

심 야(0시-4시) is highly overall correlated with 새 벽(4시-7시) and 5 other fieldsHigh correlation
새 벽(4시-7시) is highly overall correlated with 심 야(0시-4시) and 5 other fieldsHigh correlation
오 전(7시-12시) is highly overall correlated with 심 야(0시-4시) and 5 other fieldsHigh correlation
오 후(12시-18시) is highly overall correlated with 심 야(0시-4시) and 5 other fieldsHigh correlation
초 저 녁(18시-20시) is highly overall correlated with 심 야(0시-4시) and 5 other fieldsHigh correlation
밤(20시-24시) is highly overall correlated with 심 야(0시-4시) and 5 other fieldsHigh correlation
항목 is highly overall correlated with 심 야(0시-4시) and 5 other fieldsHigh correlation
심 야(0시-4시) has unique valuesUnique
새 벽(4시-7시) has 4 (14.3%) zerosZeros
초 저 녁(18시-20시) has 1 (3.6%) zerosZeros

Reproduction

Analysis started2023-12-12 14:14:43.686048
Analysis finished2023-12-12 14:14:48.302769
Duration4.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
2019
7 
2020
7 
2021
7 
2022
7 

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 7
25.0%
2020 7
25.0%
2021 7
25.0%
2022 7
25.0%

Length

2023-12-12T23:14:48.372538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:14:48.470562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 7
25.0%
2020 7
25.0%
2021 7
25.0%
2022 7
25.0%

항목
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
강력범
4 
절도범
4 
폭력범
4 
지능범
4 
풍속범
4 
Other values (2)
8 

Length

Max length5
Median length3
Mean length3.4285714
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강력범
2nd row절도범
3rd row폭력범
4th row지능범
5th row풍속범

Common Values

ValueCountFrequency (%)
강력범 4
14.3%
절도범 4
14.3%
폭력범 4
14.3%
지능범 4
14.3%
풍속범 4
14.3%
기타형법범 4
14.3%
특별법범 4
14.3%

Length

2023-12-12T23:14:48.595302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:14:48.731313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강력범 4
14.3%
절도범 4
14.3%
폭력범 4
14.3%
지능범 4
14.3%
풍속범 4
14.3%
기타형법범 4
14.3%
특별법범 4
14.3%

심 야(0시-4시)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean364.46429
Minimum2
Maximum1272
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-12T23:14:48.887990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4.05
Q147.5
median227.5
Q3639.25
95-th percentile1192.75
Maximum1272
Range1270
Interquartile range (IQR)591.75

Descriptive statistics

Standard deviation394.98959
Coefficient of variation (CV)1.0837539
Kurtosis0.19680238
Mean364.46429
Median Absolute Deviation (MAD)194.5
Skewness1.1860496
Sum10205
Variance156016.78
MonotonicityNot monotonic
2023-12-12T23:14:49.026973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
20 1
 
3.6%
173 1
 
3.6%
799 1
 
3.6%
246 1
 
3.6%
3 1
 
3.6%
1226 1
 
3.6%
286 1
 
3.6%
231 1
 
3.6%
51 1
 
3.6%
709 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
2 1
3.6%
3 1
3.6%
6 1
3.6%
7 1
3.6%
20 1
3.6%
29 1
3.6%
37 1
3.6%
51 1
3.6%
121 1
3.6%
173 1
3.6%
ValueCountFrequency (%)
1272 1
3.6%
1226 1
3.6%
1131 1
3.6%
930 1
3.6%
799 1
3.6%
739 1
3.6%
709 1
3.6%
616 1
3.6%
286 1
3.6%
252 1
3.6%

새 벽(4시-7시)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.964286
Minimum0
Maximum116
Zeros4
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-12T23:14:49.193048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median13
Q341.75
95-th percentile89.45
Maximum116
Range116
Interquartile range (IQR)35.75

Descriptive statistics

Standard deviation31.812509
Coefficient of variation (CV)1.1376121
Kurtosis1.0737931
Mean27.964286
Median Absolute Deviation (MAD)13
Skewness1.3571601
Sum783
Variance1012.0357
MonotonicityNot monotonic
2023-12-12T23:14:49.331504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 4
 
14.3%
7 3
 
10.7%
31 3
 
10.7%
6 2
 
7.1%
44 1
 
3.6%
72 1
 
3.6%
8 1
 
3.6%
9 1
 
3.6%
68 1
 
3.6%
3 1
 
3.6%
Other values (10) 10
35.7%
ValueCountFrequency (%)
0 4
14.3%
3 1
 
3.6%
4 1
 
3.6%
6 2
7.1%
7 3
10.7%
8 1
 
3.6%
9 1
 
3.6%
10 1
 
3.6%
16 1
 
3.6%
17 1
 
3.6%
ValueCountFrequency (%)
116 1
 
3.6%
94 1
 
3.6%
81 1
 
3.6%
72 1
 
3.6%
68 1
 
3.6%
49 1
 
3.6%
44 1
 
3.6%
41 1
 
3.6%
31 3
10.7%
25 1
 
3.6%

오 전(7시-12시)
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.57143
Minimum1
Maximum324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-12T23:14:49.455971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.05
Q19.25
median118.5
Q3180.25
95-th percentile275.8
Maximum324
Range323
Interquartile range (IQR)171

Descriptive statistics

Standard deviation93.621946
Coefficient of variation (CV)0.83166703
Kurtosis-0.56713394
Mean112.57143
Median Absolute Deviation (MAD)72
Skewness0.46260627
Sum3152
Variance8765.0688
MonotonicityNot monotonic
2023-12-12T23:14:49.598508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
53 2
 
7.1%
6 2
 
7.1%
114 2
 
7.1%
1 2
 
7.1%
7 1
 
3.6%
190 1
 
3.6%
191 1
 
3.6%
192 1
 
3.6%
177 1
 
3.6%
10 1
 
3.6%
Other values (14) 14
50.0%
ValueCountFrequency (%)
1 2
7.1%
4 1
3.6%
5 1
3.6%
6 2
7.1%
7 1
3.6%
10 1
3.6%
52 1
3.6%
53 2
7.1%
69 1
3.6%
114 2
7.1%
ValueCountFrequency (%)
324 1
3.6%
287 1
3.6%
255 1
3.6%
193 1
3.6%
192 1
3.6%
191 1
3.6%
190 1
3.6%
177 1
3.6%
176 1
3.6%
152 1
3.6%

오 후(12시-18시)
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean186.96429
Minimum3
Maximum469
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-12T23:14:49.745023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile5.7
Q119.75
median185.5
Q3311
95-th percentile421
Maximum469
Range466
Interquartile range (IQR)291.25

Descriptive statistics

Standard deviation154.17966
Coefficient of variation (CV)0.82464768
Kurtosis-1.3381167
Mean186.96429
Median Absolute Deviation (MAD)162
Skewness0.25756386
Sum5235
Variance23771.369
MonotonicityNot monotonic
2023-12-12T23:14:49.880605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
11 2
 
7.1%
13 1
 
3.6%
386 1
 
3.6%
347 1
 
3.6%
75 1
 
3.6%
7 1
 
3.6%
348 1
 
3.6%
182 1
 
3.6%
369 1
 
3.6%
22 1
 
3.6%
Other values (17) 17
60.7%
ValueCountFrequency (%)
3 1
3.6%
5 1
3.6%
7 1
3.6%
11 2
7.1%
12 1
3.6%
13 1
3.6%
22 1
3.6%
73 1
3.6%
75 1
3.6%
82 1
3.6%
ValueCountFrequency (%)
469 1
3.6%
428 1
3.6%
408 1
3.6%
386 1
3.6%
369 1
3.6%
348 1
3.6%
347 1
3.6%
299 1
3.6%
286 1
3.6%
272 1
3.6%

초 저 녁(18시-20시)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.25
Minimum0
Maximum218
Zeros1
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-12T23:14:49.998928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q19.75
median57.5
Q395.5
95-th percentile192.1
Maximum218
Range218
Interquartile range (IQR)85.75

Descriptive statistics

Standard deviation64.344343
Coefficient of variation (CV)0.9567932
Kurtosis-0.035087928
Mean67.25
Median Absolute Deviation (MAD)43.5
Skewness0.91283624
Sum1883
Variance4140.1944
MonotonicityNot monotonic
2023-12-12T23:14:50.114847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 3
 
10.7%
78 2
 
7.1%
4 1
 
3.6%
9 1
 
3.6%
161 1
 
3.6%
20 1
 
3.6%
66 1
 
3.6%
120 1
 
3.6%
10 1
 
3.6%
218 1
 
3.6%
Other values (15) 15
53.6%
ValueCountFrequency (%)
0 1
 
3.6%
1 3
10.7%
4 1
 
3.6%
7 1
 
3.6%
9 1
 
3.6%
10 1
 
3.6%
18 1
 
3.6%
20 1
 
3.6%
21 1
 
3.6%
33 1
 
3.6%
ValueCountFrequency (%)
218 1
3.6%
197 1
3.6%
183 1
3.6%
161 1
3.6%
135 1
3.6%
120 1
3.6%
97 1
3.6%
95 1
3.6%
85 1
3.6%
78 2
7.1%

밤(20시-24시)
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.96429
Minimum2
Maximum429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-12T23:14:50.257128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.35
Q124.75
median82
Q3207.5
95-th percentile415.2
Maximum429
Range427
Interquartile range (IQR)182.75

Descriptive statistics

Standard deviation133.90613
Coefficient of variation (CV)1.0303302
Kurtosis0.36815415
Mean129.96429
Median Absolute Deviation (MAD)64
Skewness1.1960468
Sum3639
Variance17930.851
MonotonicityNot monotonic
2023-12-12T23:14:50.404238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
215 2
 
7.1%
17 1
 
3.6%
115 1
 
3.6%
429 1
 
3.6%
60 1
 
3.6%
7 1
 
3.6%
99 1
 
3.6%
233 1
 
3.6%
145 1
 
3.6%
25 1
 
3.6%
Other values (17) 17
60.7%
ValueCountFrequency (%)
2 1
3.6%
5 1
3.6%
6 1
3.6%
7 1
3.6%
17 1
3.6%
22 1
3.6%
24 1
3.6%
25 1
3.6%
40 1
3.6%
43 1
3.6%
ValueCountFrequency (%)
429 1
3.6%
418 1
3.6%
410 1
3.6%
362 1
3.6%
233 1
3.6%
215 2
7.1%
205 1
3.6%
151 1
3.6%
145 1
3.6%
124 1
3.6%

Interactions

2023-12-12T23:14:47.463760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:43.992673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:44.721007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:45.546130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:46.362084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:46.950687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:47.554893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:44.077973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:44.870755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:45.687499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:46.479203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:47.037374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:47.675314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:44.199420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:45.024141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:45.825672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:46.588025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:47.123531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:47.766421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:44.336838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:45.160595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:45.987792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:46.689745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:47.230084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:47.861212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:44.446669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:45.287950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:46.139667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:46.784346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:47.303088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:47.944210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:44.575531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:45.424086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:46.264162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:46.875782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:47.385704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:14:50.804709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도항목심 야(0시-4시)새 벽(4시-7시)오 전(7시-12시)오 후(12시-18시)초 저 녁(18시-20시)밤(20시-24시)
연도1.0000.0000.0000.0000.0000.3890.0000.000
항목0.0001.0000.7690.7750.8030.8800.8620.838
심 야(0시-4시)0.0000.7691.0000.8710.9160.8970.8400.816
새 벽(4시-7시)0.0000.7750.8711.0000.9280.9230.9060.865
오 전(7시-12시)0.0000.8030.9160.9281.0000.9560.8730.797
오 후(12시-18시)0.3890.8800.8970.9230.9561.0000.8810.740
초 저 녁(18시-20시)0.0000.8620.8400.9060.8730.8811.0000.827
밤(20시-24시)0.0000.8380.8160.8650.7970.7400.8271.000
2023-12-12T23:14:50.935058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도항목
연도1.0000.000
항목0.0001.000
2023-12-12T23:14:51.023446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
심 야(0시-4시)새 벽(4시-7시)오 전(7시-12시)오 후(12시-18시)초 저 녁(18시-20시)밤(20시-24시)연도항목
심 야(0시-4시)1.0000.6230.7870.7140.6510.6880.0000.515
새 벽(4시-7시)0.6231.0000.8680.9030.9520.9330.0000.523
오 전(7시-12시)0.7870.8681.0000.9660.9200.8500.0000.562
오 후(12시-18시)0.7140.9030.9661.0000.9520.8490.2040.690
초 저 녁(18시-20시)0.6510.9520.9200.9521.0000.9340.0000.618
밤(20시-24시)0.6880.9330.8500.8490.9341.0000.0000.629
연도0.0000.0000.0000.2040.0000.0001.0000.000
항목0.5150.5230.5620.6900.6180.6290.0001.000

Missing values

2023-12-12T23:14:48.082817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:14:48.228437image/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

연도항목심 야(0시-4시)새 벽(4시-7시)오 전(7시-12시)오 후(12시-18시)초 저 녁(18시-20시)밤(20시-24시)
02019강력범207713417
12019절도범1213115229995151
22019폭력범2522513117578215
32019지능범1131161932726071
42019풍속범704516
52019기타형법범223653821843
62019특별법범616116324469183418
72020강력범377611724
82020절도범1934113428697124
92020폭력범2324911418985205
연도항목심 야(0시-4시)새 벽(4시-7시)오 전(7시-12시)오 후(12시-18시)초 저 녁(18시-20시)밤(20시-24시)
182021풍속범6011115
192021기타형법범226752892140
202021특별법범70981255408218410
212022강력범51310221025
222022절도범23168177369120145
232022폭력범2863111418266233
242022지능범122691923487899
252022풍속범301717
262022기타형법범246853752060
272022특별법범79972191347161429