Overview

Dataset statistics

Number of variables13
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory121.5 B

Variable types

Text1
Numeric12

Dataset

Description경상남도 경찰청 산하 산하 5대범죄 발생 및 검거 현황 자료로 살인,강도,강간,절도,폭력 등 5대 중요범죄에 대한 항목들로 구성되어 있습니다.
URLhttps://www.data.go.kr/data/15037364/fileData.do

Alerts

5대범죄발생건수 is highly overall correlated with 5대범죄검거건수 and 9 other fieldsHigh correlation
5대범죄검거건수 is highly overall correlated with 5대범죄발생건수 and 9 other fieldsHigh correlation
살인발생건수 is highly overall correlated with 5대범죄발생건수 and 8 other fieldsHigh correlation
살인검거건수 is highly overall correlated with 5대범죄발생건수 and 8 other fieldsHigh correlation
강도발생건수 is highly overall correlated with 5대범죄발생건수 and 7 other fieldsHigh correlation
강도검거건수 is highly overall correlated with 강도발생건수High correlation
강간발생건수 is highly overall correlated with 5대범죄발생건수 and 8 other fieldsHigh correlation
강간검거건수 is highly overall correlated with 5대범죄발생건수 and 6 other fieldsHigh correlation
절도발생건수 is highly overall correlated with 5대범죄발생건수 and 9 other fieldsHigh correlation
절도검거건수 is highly overall correlated with 5대범죄발생건수 and 9 other fieldsHigh correlation
폭력발생건수 is highly overall correlated with 5대범죄발생건수 and 8 other fieldsHigh correlation
폭력검거건수 is highly overall correlated with 5대범죄발생건수 and 9 other fieldsHigh correlation
구분 has unique valuesUnique
5대범죄발생건수 has unique valuesUnique
5대범죄검거건수 has unique valuesUnique
절도발생건수 has unique valuesUnique
폭력발생건수 has unique valuesUnique
폭력검거건수 has unique valuesUnique
5대범죄발생건수 has 1 (4.2%) zerosZeros
살인발생건수 has 3 (12.5%) zerosZeros
살인검거건수 has 3 (12.5%) zerosZeros
강도발생건수 has 12 (50.0%) zerosZeros
강도검거건수 has 10 (41.7%) zerosZeros
강간발생건수 has 1 (4.2%) zerosZeros
절도발생건수 has 1 (4.2%) zerosZeros
폭력발생건수 has 1 (4.2%) zerosZeros

Reproduction

Analysis started2023-12-12 11:34:59.578924
Analysis finished2023-12-12 11:35:25.924311
Duration26.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T20:35:26.120399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.5416667
Min length2

Characters and Unicode

Total characters61
Distinct characters33
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

Unique24 ?
Unique (%)100.0%

Sample

1st row지방청
2nd row창원중부
3rd row창원서부
4th row마산중부
5th row마산동부
ValueCountFrequency (%)
지방청 1
 
4.2%
창원중부 1
 
4.2%
함안 1
 
4.2%
산청 1
 
4.2%
함양 1
 
4.2%
남해 1
 
4.2%
하동 1
 
4.2%
고성 1
 
4.2%
창녕 1
 
4.2%
합천 1
 
4.2%
Other values (14) 14
58.3%
2023-12-12T20:35:26.762328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
9.8%
4
 
6.6%
4
 
6.6%
4
 
6.6%
3
 
4.9%
3
 
4.9%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
Other values (23) 29
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6
 
9.8%
4
 
6.6%
4
 
6.6%
4
 
6.6%
3
 
4.9%
3
 
4.9%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
Other values (23) 29
47.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6
 
9.8%
4
 
6.6%
4
 
6.6%
4
 
6.6%
3
 
4.9%
3
 
4.9%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
Other values (23) 29
47.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6
 
9.8%
4
 
6.6%
4
 
6.6%
4
 
6.6%
3
 
4.9%
3
 
4.9%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
Other values (23) 29
47.5%

5대범죄발생건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1131.125
Minimum0
Maximum3686
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:35:26.994209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile164.15
Q1278.5
median741.5
Q31929.5
95-th percentile3217.15
Maximum3686
Range3686
Interquartile range (IQR)1651

Descriptive statistics

Standard deviation1062.4604
Coefficient of variation (CV)0.93929527
Kurtosis0.14147736
Mean1131.125
Median Absolute Deviation (MAD)554.5
Skewness1.0033274
Sum27147
Variance1128822
MonotonicityNot monotonic
2023-12-12T20:35:27.210975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 1
 
4.2%
653 1
 
4.2%
161 1
 
4.2%
339 1
 
4.2%
182 1
 
4.2%
192 1
 
4.2%
201 1
 
4.2%
285 1
 
4.2%
391 1
 
4.2%
343 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
0 1
4.2%
161 1
4.2%
182 1
4.2%
192 1
4.2%
201 1
4.2%
259 1
4.2%
285 1
4.2%
339 1
4.2%
343 1
4.2%
372 1
4.2%
ValueCountFrequency (%)
3686 1
4.2%
3310 1
4.2%
2691 1
4.2%
2037 1
4.2%
2015 1
4.2%
1976 1
4.2%
1914 1
4.2%
1598 1
4.2%
1395 1
4.2%
1168 1
4.2%

5대범죄검거건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean877.04167
Minimum130
Maximum2933
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:35:27.413781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum130
5-th percentile153.9
Q1247.25
median598
Q31376.75
95-th percentile2514.15
Maximum2933
Range2803
Interquartile range (IQR)1129.5

Descriptive statistics

Standard deviation803.62626
Coefficient of variation (CV)0.916292
Kurtosis0.76681602
Mean877.04167
Median Absolute Deviation (MAD)400
Skewness1.1898848
Sum21049
Variance645815.17
MonotonicityNot monotonic
2023-12-12T20:35:27.590250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
248 1
 
4.2%
489 1
 
4.2%
130 1
 
4.2%
288 1
 
4.2%
153 1
 
4.2%
159 1
 
4.2%
167 1
 
4.2%
245 1
 
4.2%
311 1
 
4.2%
278 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
130 1
4.2%
153 1
4.2%
159 1
4.2%
167 1
4.2%
229 1
4.2%
245 1
4.2%
248 1
4.2%
278 1
4.2%
288 1
4.2%
294 1
4.2%
ValueCountFrequency (%)
2933 1
4.2%
2598 1
4.2%
2039 1
4.2%
1572 1
4.2%
1449 1
4.2%
1391 1
4.2%
1372 1
4.2%
1229 1
4.2%
965 1
4.2%
907 1
4.2%

살인발생건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.875
Minimum0
Maximum7
Zeros3
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:35:27.780150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q33
95-th percentile5.7
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7769661
Coefficient of variation (CV)0.94771528
Kurtosis2.5131822
Mean1.875
Median Absolute Deviation (MAD)0.5
Skewness1.6253998
Sum45
Variance3.1576087
MonotonicityNot monotonic
2023-12-12T20:35:27.973114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 12
50.0%
3 4
 
16.7%
0 3
 
12.5%
2 2
 
8.3%
6 1
 
4.2%
4 1
 
4.2%
7 1
 
4.2%
ValueCountFrequency (%)
0 3
 
12.5%
1 12
50.0%
2 2
 
8.3%
3 4
 
16.7%
4 1
 
4.2%
6 1
 
4.2%
7 1
 
4.2%
ValueCountFrequency (%)
7 1
 
4.2%
6 1
 
4.2%
4 1
 
4.2%
3 4
 
16.7%
2 2
 
8.3%
1 12
50.0%
0 3
 
12.5%

살인검거건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8333333
Minimum0
Maximum7
Zeros3
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:35:28.160955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q33
95-th percentile5.55
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7362295
Coefficient of variation (CV)0.94703425
Kurtosis3.1697935
Mean1.8333333
Median Absolute Deviation (MAD)0.5
Skewness1.7470138
Sum44
Variance3.0144928
MonotonicityNot monotonic
2023-12-12T20:35:28.362627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 12
50.0%
3 5
20.8%
0 3
 
12.5%
2 2
 
8.3%
6 1
 
4.2%
7 1
 
4.2%
ValueCountFrequency (%)
0 3
 
12.5%
1 12
50.0%
2 2
 
8.3%
3 5
20.8%
6 1
 
4.2%
7 1
 
4.2%
ValueCountFrequency (%)
7 1
 
4.2%
6 1
 
4.2%
3 5
20.8%
2 2
 
8.3%
1 12
50.0%
0 3
 
12.5%

강도발생건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.375
Minimum0
Maximum11
Zeros12
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:35:28.575181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.5
Q31.25
95-th percentile6.4
Maximum11
Range11
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation2.5675652
Coefficient of variation (CV)1.8673202
Kurtosis9.0818038
Mean1.375
Median Absolute Deviation (MAD)0.5
Skewness2.9231131
Sum33
Variance6.5923913
MonotonicityNot monotonic
2023-12-12T20:35:28.776929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 12
50.0%
1 6
25.0%
2 3
 
12.5%
11 1
 
4.2%
7 1
 
4.2%
3 1
 
4.2%
ValueCountFrequency (%)
0 12
50.0%
1 6
25.0%
2 3
 
12.5%
3 1
 
4.2%
7 1
 
4.2%
11 1
 
4.2%
ValueCountFrequency (%)
11 1
 
4.2%
7 1
 
4.2%
3 1
 
4.2%
2 3
 
12.5%
1 6
25.0%
0 12
50.0%

강도검거건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.375
Minimum0
Maximum10
Zeros10
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:35:28.974238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31.25
95-th percentile5.55
Maximum10
Range10
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation2.2805892
Coefficient of variation (CV)1.6586103
Kurtosis9.1617348
Mean1.375
Median Absolute Deviation (MAD)1
Skewness2.8756949
Sum33
Variance5.201087
MonotonicityNot monotonic
2023-12-12T20:35:29.171893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 10
41.7%
1 8
33.3%
2 3
 
12.5%
10 1
 
4.2%
6 1
 
4.2%
3 1
 
4.2%
ValueCountFrequency (%)
0 10
41.7%
1 8
33.3%
2 3
 
12.5%
3 1
 
4.2%
6 1
 
4.2%
10 1
 
4.2%
ValueCountFrequency (%)
10 1
 
4.2%
6 1
 
4.2%
3 1
 
4.2%
2 3
 
12.5%
1 8
33.3%
0 10
41.7%

강간발생건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.5
Minimum0
Maximum115
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:35:29.377633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.45
Q110.5
median32
Q369.75
95-th percentile97.4
Maximum115
Range115
Interquartile range (IQR)59.25

Descriptive statistics

Standard deviation36.160271
Coefficient of variation (CV)0.87133184
Kurtosis-0.94546461
Mean41.5
Median Absolute Deviation (MAD)23
Skewness0.70649215
Sum996
Variance1307.5652
MonotonicityNot monotonic
2023-12-12T20:35:29.700380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
9 3
 
12.5%
0 1
 
4.2%
35 1
 
4.2%
13 1
 
4.2%
4 1
 
4.2%
7 1
 
4.2%
11 1
 
4.2%
16 1
 
4.2%
17 1
 
4.2%
21 1
 
4.2%
Other values (12) 12
50.0%
ValueCountFrequency (%)
0 1
 
4.2%
4 1
 
4.2%
7 1
 
4.2%
9 3
12.5%
11 1
 
4.2%
13 1
 
4.2%
16 1
 
4.2%
17 1
 
4.2%
21 1
 
4.2%
29 1
 
4.2%
ValueCountFrequency (%)
115 1
4.2%
98 1
4.2%
94 1
4.2%
93 1
4.2%
90 1
4.2%
84 1
4.2%
65 1
4.2%
57 1
4.2%
42 1
4.2%
41 1
4.2%

강간검거건수
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.458333
Minimum1
Maximum148
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:35:29.921059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q15
median28.5
Q371.25
95-th percentile96.75
Maximum148
Range147
Interquartile range (IQR)66.25

Descriptive statistics

Standard deviation39.501215
Coefficient of variation (CV)1.0010868
Kurtosis0.71159217
Mean39.458333
Median Absolute Deviation (MAD)24.5
Skewness1.0635265
Sum947
Variance1560.346
MonotonicityNot monotonic
2023-12-12T20:35:30.624398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
24 2
 
8.3%
82 2
 
8.3%
4 2
 
8.3%
33 2
 
8.3%
5 2
 
8.3%
12 1
 
4.2%
1 1
 
4.2%
3 1
 
4.2%
2 1
 
4.2%
6 1
 
4.2%
Other values (9) 9
37.5%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 2
8.3%
5 2
8.3%
6 1
4.2%
9 1
4.2%
12 1
4.2%
24 2
8.3%
33 2
8.3%
ValueCountFrequency (%)
148 1
4.2%
99 1
4.2%
84 1
4.2%
82 2
8.3%
72 1
4.2%
71 1
4.2%
58 1
4.2%
49 1
4.2%
37 1
4.2%
33 2
8.3%

절도발생건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean480.75
Minimum0
Maximum1860
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:35:30.844903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile42.65
Q184.25
median300.5
Q3776.5
95-th percentile1597.15
Maximum1860
Range1860
Interquartile range (IQR)692.25

Descriptive statistics

Standard deviation515.04962
Coefficient of variation (CV)1.0713461
Kurtosis1.5857283
Mean480.75
Median Absolute Deviation (MAD)236
Skewness1.4063348
Sum11538
Variance265276.11
MonotonicityNot monotonic
2023-12-12T20:35:31.066782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 1
 
4.2%
249 1
 
4.2%
41 1
 
4.2%
88 1
 
4.2%
61 1
 
4.2%
52 1
 
4.2%
72 1
 
4.2%
116 1
 
4.2%
160 1
 
4.2%
108 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
0 1
4.2%
41 1
4.2%
52 1
4.2%
61 1
4.2%
72 1
4.2%
73 1
4.2%
88 1
4.2%
108 1
4.2%
116 1
4.2%
131 1
4.2%
ValueCountFrequency (%)
1860 1
4.2%
1693 1
4.2%
1054 1
4.2%
883 1
4.2%
858 1
4.2%
835 1
4.2%
757 1
4.2%
695 1
4.2%
533 1
4.2%
467 1
4.2%

절도검거건수
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean308.16667
Minimum4
Maximum1339
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:35:31.271047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile28.8
Q169.75
median175
Q3461.75
95-th percentile1138.4
Maximum1339
Range1335
Interquartile range (IQR)392

Descriptive statistics

Standard deviation354.21507
Coefficient of variation (CV)1.149427
Kurtosis3.366722
Mean308.16667
Median Absolute Deviation (MAD)132.5
Skewness1.8683607
Sum7396
Variance125468.32
MonotonicityNot monotonic
2023-12-12T20:35:31.469840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
464 2
 
8.3%
4 1
 
4.2%
81 1
 
4.2%
27 1
 
4.2%
73 1
 
4.2%
46 1
 
4.2%
39 1
 
4.2%
53 1
 
4.2%
98 1
 
4.2%
109 1
 
4.2%
Other values (13) 13
54.2%
ValueCountFrequency (%)
4 1
4.2%
27 1
4.2%
39 1
4.2%
46 1
4.2%
53 1
4.2%
60 1
4.2%
73 1
4.2%
75 1
4.2%
81 1
4.2%
98 1
4.2%
ValueCountFrequency (%)
1339 1
4.2%
1223 1
4.2%
659 1
4.2%
558 1
4.2%
464 2
8.3%
461 1
4.2%
346 1
4.2%
337 1
4.2%
270 1
4.2%
260 1
4.2%

폭력발생건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean605.625
Minimum0
Maximum1716
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:35:31.651055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile110.75
Q1171.25
median407
Q31040.25
95-th percentile1531.95
Maximum1716
Range1716
Interquartile range (IQR)869

Descriptive statistics

Standard deviation520.72164
Coefficient of variation (CV)0.85980869
Kurtosis-0.63867367
Mean605.625
Median Absolute Deviation (MAD)294.5
Skewness0.74587605
Sum14535
Variance271151.03
MonotonicityNot monotonic
2023-12-12T20:35:31.841373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 1
 
4.2%
374 1
 
4.2%
110 1
 
4.2%
237 1
 
4.2%
115 1
 
4.2%
132 1
 
4.2%
119 1
 
4.2%
157 1
 
4.2%
212 1
 
4.2%
216 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
0 1
4.2%
110 1
4.2%
115 1
4.2%
119 1
4.2%
132 1
4.2%
157 1
4.2%
176 1
4.2%
212 1
4.2%
216 1
4.2%
220 1
4.2%
ValueCountFrequency (%)
1716 1
4.2%
1536 1
4.2%
1509 1
4.2%
1091 1
4.2%
1064 1
4.2%
1059 1
4.2%
1034 1
4.2%
834 1
4.2%
823 1
4.2%
725 1
4.2%

폭력검거건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean526.20833
Minimum95
Maximum1494
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T20:35:32.033200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum95
5-th percentile101.15
Q1157.5
median368
Q3884.5
95-th percentile1290.8
Maximum1494
Range1399
Interquartile range (IQR)727

Descriptive statistics

Standard deviation438.19789
Coefficient of variation (CV)0.83274601
Kurtosis-0.54265506
Mean526.20833
Median Absolute Deviation (MAD)266.5
Skewness0.79104381
Sum12629
Variance192017.39
MonotonicityNot monotonic
2023-12-12T20:35:32.208833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
95 1
 
4.2%
326 1
 
4.2%
101 1
 
4.2%
210 1
 
4.2%
102 1
 
4.2%
117 1
 
4.2%
107 1
 
4.2%
141 1
 
4.2%
194 1
 
4.2%
192 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
95 1
4.2%
101 1
4.2%
102 1
4.2%
107 1
4.2%
117 1
4.2%
141 1
4.2%
163 1
4.2%
192 1
4.2%
194 1
4.2%
201 1
4.2%
ValueCountFrequency (%)
1494 1
4.2%
1292 1
4.2%
1284 1
4.2%
946 1
4.2%
914 1
4.2%
910 1
4.2%
876 1
4.2%
706 1
4.2%
670 1
4.2%
661 1
4.2%

Interactions

2023-12-12T20:35:23.514411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:00.111934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:02.698016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:04.685867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:06.768139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:08.885711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:11.367950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:13.169131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:15.194251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:17.288873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:19.276176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:21.487509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:23.719519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:00.271113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:02.856800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:04.858715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:06.962621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:09.068644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:11.523741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:13.335343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:15.365637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:17.463383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:19.414949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:21.668453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:23.881292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:00.428286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:03.006092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:05.002213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:07.141297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:09.219147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:11.671274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:13.498059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:15.546379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:17.614938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:19.547832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:21.805262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:24.054118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:01.149534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:03.179343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:05.260840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:07.320274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:09.385819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:11.828894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:13.638196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:15.738627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:17.787071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:20.198476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:21.982840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:24.219335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:01.382264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:03.325269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:05.419956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:07.500185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:09.556471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:11.984936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:13.813316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:15.917160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:17.975778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:20.345471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:22.159416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:24.360282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:01.549617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:03.473772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:05.587341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:07.655326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:09.714174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:12.135080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:13.989503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:16.078712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:18.149956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:20.469555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:22.306349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:24.500382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:01.699625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:03.621173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:05.734274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:07.806123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:09.871130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:12.264163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:14.140783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:16.223085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:18.305744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:20.599856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:22.475917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:24.644315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:01.865564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:03.802041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:05.905577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:07.978041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:10.042260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:12.393690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:14.303183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:16.375859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:18.479666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:20.753585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:22.628914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:24.810580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:02.019858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:03.982156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:06.066036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:08.163446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:10.208317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:12.537817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:14.486048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:16.555746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:18.652267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:20.904237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:22.788804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:24.967026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:02.182766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:04.158623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:06.222350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:08.345852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:10.883606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:12.696409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:14.656921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:16.769372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:18.807108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:21.038833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:22.973153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:25.142716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:02.357473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:04.335062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:06.397560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:08.532542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:11.046473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:12.876678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:14.851646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:16.950468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:18.969296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:21.178653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:23.165478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:25.304028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:02.529736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:04.508943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:06.576768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:08.715961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:11.207582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:13.031896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:15.025439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:17.124216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:19.148316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:21.328187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:35:23.342283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:35:32.367681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분5대범죄발생건수5대범죄검거건수살인발생건수살인검거건수강도발생건수강도검거건수강간발생건수강간검거건수절도발생건수절도검거건수폭력발생건수폭력검거건수
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
5대범죄발생건수1.0001.0000.9890.8120.7750.9490.9410.9370.8270.9740.8820.9070.971
5대범죄검거건수1.0000.9891.0000.8080.7710.9360.9420.9840.8890.9620.9500.8760.966
살인발생건수1.0000.8120.8081.0001.0000.8000.7620.4610.5360.8910.6660.7450.854
살인검거건수1.0000.7750.7711.0001.0000.6040.7860.5910.5950.5850.7740.7690.919
강도발생건수1.0000.9490.9360.8000.6041.0001.0000.2980.1660.7990.6520.8060.802
강도검거건수1.0000.9410.9420.7620.7861.0001.0000.4330.3790.7780.8640.7970.792
강간발생건수1.0000.9370.9840.4610.5910.2980.4331.0000.9380.9000.9020.8520.933
강간검거건수1.0000.8270.8890.5360.5950.1660.3790.9381.0000.9130.8830.9380.840
절도발생건수1.0000.9740.9620.8910.5850.7990.7780.9000.9131.0000.8800.9120.899
절도검거건수1.0000.8820.9500.6660.7740.6520.8640.9020.8830.8801.0000.8370.923
폭력발생건수1.0000.9070.8760.7450.7690.8060.7970.8520.9380.9120.8371.0000.963
폭력검거건수1.0000.9710.9660.8540.9190.8020.7920.9330.8400.8990.9230.9631.000
2023-12-12T20:35:32.627303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
5대범죄발생건수5대범죄검거건수살인발생건수살인검거건수강도발생건수강도검거건수강간발생건수강간검거건수절도발생건수절도검거건수폭력발생건수폭력검거건수
5대범죄발생건수1.0000.9800.7280.7220.5470.4290.9730.7240.9930.9850.9890.985
5대범죄검거건수0.9801.0000.6840.6770.5130.4370.9570.8280.9710.9640.9710.970
살인발생건수0.7280.6841.0000.9970.5490.4540.6950.4460.7280.7390.7510.760
살인검거건수0.7220.6770.9971.0000.5390.4430.6890.4390.7220.7340.7430.750
강도발생건수0.5470.5130.5490.5391.0000.9290.4810.3920.5680.5680.4990.503
강도검거건수0.4290.4370.4540.4430.9291.0000.3620.4390.4670.4780.3710.377
강간발생건수0.9730.9570.6950.6890.4810.3621.0000.7350.9600.9640.9690.970
강간검거건수0.7240.8280.4460.4390.3920.4390.7351.0000.7140.7170.7180.717
절도발생건수0.9930.9710.7280.7220.5680.4670.9600.7141.0000.9910.9750.974
절도검거건수0.9850.9640.7390.7340.5680.4780.9640.7170.9911.0000.9660.964
폭력발생건수0.9890.9710.7510.7430.4990.3710.9690.7180.9750.9661.0000.996
폭력검거건수0.9850.9700.7600.7500.5030.3770.9700.7170.9740.9640.9961.000

Missing values

2023-12-12T20:35:25.514141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:35:25.807875image/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

구분5대범죄발생건수5대범죄검거건수살인발생건수살인검거건수강도발생건수강도검거건수강간발생건수강간검거건수절도발생건수절도검거건수폭력발생건수폭력검거건수
0지방청02480001014804095
1창원중부201515721100115998355581064914
2창원서부1598122922226558695461834706
3마산중부114989633224137467337636517
4마산동부20371449331184718584641091910
5진주3686293366111093841860133917161494
6김해중부33102598337698821693122315091284
7김해서부19761391111157498834641034876
8양산2691203943339482105465915361292
9거제19141372771190727573461059946
구분5대범죄발생건수5대범죄검거건수살인발생건수살인검거건수강도발생건수강도검거건수강간발생건수강간검거건수절도발생건수절도검거건수폭력발생건수폭력검거건수
14거창3722940000211213181220201
15합천2592291100957360176163
16창녕343278111117910875216192
17고성3913111122165160109212194
18하동285245110111411698157141
19남해2011670011967253119107
20함양1921591100725239132117
21산청1821531111436146115102
22함안33928811001348873237210
23의령1611301100914127110101