Overview

Dataset statistics

Number of variables9
Number of observations90
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 KiB
Average record size in memory80.5 B

Variable types

Numeric7
Categorical2

Dataset

Description광주광역시 자치구별 5대 범죄현황에 대한 데이터로 (살인/강도/성범죄/절도/폭력) 2017~2022년의 데이터를 제공합니다
URLhttps://www.data.go.kr/data/15118790/fileData.do

Alerts

광주광산경찰서 is highly overall correlated with 광주동부경찰서 and 4 other fieldsHigh correlation
광주동부경찰서 is highly overall correlated with 광주광산경찰서 and 4 other fieldsHigh correlation
광주서부경찰서 is highly overall correlated with 광주광산경찰서 and 4 other fieldsHigh correlation
광주남부경찰서 is highly overall correlated with 광주광산경찰서 and 4 other fieldsHigh correlation
광주북부경찰서 is highly overall correlated with 광주광산경찰서 and 4 other fieldsHigh correlation
범죄유형 is highly overall correlated with 광주광산경찰서 and 4 other fieldsHigh correlation
광주경찰청 has 59 (65.6%) zerosZeros
광주광산경찰서 has 2 (2.2%) zerosZeros
광주동부경찰서 has 9 (10.0%) zerosZeros
광주서부경찰서 has 6 (6.7%) zerosZeros
광주남부경찰서 has 11 (12.2%) zerosZeros
광주북부경찰서 has 3 (3.3%) zerosZeros

Reproduction

Analysis started2023-12-12 16:36:19.353876
Analysis finished2023-12-12 16:36:23.999186
Duration4.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct6
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.5
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-13T01:36:24.066336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2019.5
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7173929
Coefficient of variation (CV)0.00085040498
Kurtosis-1.2722257
Mean2019.5
Median Absolute Deviation (MAD)1.5
Skewness0
Sum181755
Variance2.9494382
MonotonicityDecreasing
2023-12-13T01:36:24.201000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2022 15
16.7%
2021 15
16.7%
2020 15
16.7%
2019 15
16.7%
2018 15
16.7%
2017 15
16.7%
ValueCountFrequency (%)
2017 15
16.7%
2018 15
16.7%
2019 15
16.7%
2020 15
16.7%
2021 15
16.7%
2022 15
16.7%
ValueCountFrequency (%)
2022 15
16.7%
2021 15
16.7%
2020 15
16.7%
2019 15
16.7%
2018 15
16.7%
2017 15
16.7%

범죄유형
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size852.0 B
살인
18 
강도
18 
성범죄
18 
절도
18 
폭력
18 

Length

Max length3
Median length2
Mean length2.2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row살인
2nd row살인
3rd row살인
4th row강도
5th row강도

Common Values

ValueCountFrequency (%)
살인 18
20.0%
강도 18
20.0%
성범죄 18
20.0%
절도 18
20.0%
폭력 18
20.0%

Length

2023-12-13T01:36:24.358173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:36:24.506197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
살인 18
20.0%
강도 18
20.0%
성범죄 18
20.0%
절도 18
20.0%
폭력 18
20.0%

구분
Categorical

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size852.0 B
발생건수
30 
검거건수
30 
검거인원
30 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row발생건수
2nd row검거건수
3rd row검거인원
4th row발생건수
5th row검거건수

Common Values

ValueCountFrequency (%)
발생건수 30
33.3%
검거건수 30
33.3%
검거인원 30
33.3%

Length

2023-12-13T01:36:24.659162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:36:24.765582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
발생건수 30
33.3%
검거건수 30
33.3%
검거인원 30
33.3%

광주경찰청
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.022222
Minimum0
Maximum164
Zeros59
Zeros (%)65.6%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-13T01:36:24.891066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q317
95-th percentile109.95
Maximum164
Range164
Interquartile range (IQR)17

Descriptive statistics

Standard deviation40.66138
Coefficient of variation (CV)1.9342094
Kurtosis2.502251
Mean21.022222
Median Absolute Deviation (MAD)0
Skewness1.8877465
Sum1892
Variance1653.3478
MonotonicityNot monotonic
2023-12-13T01:36:25.018534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 59
65.6%
1 4
 
4.4%
2 3
 
3.3%
85 2
 
2.2%
91 2
 
2.2%
37 2
 
2.2%
118 1
 
1.1%
149 1
 
1.1%
105 1
 
1.1%
164 1
 
1.1%
Other values (14) 14
 
15.6%
ValueCountFrequency (%)
0 59
65.6%
1 4
 
4.4%
2 3
 
3.3%
14 1
 
1.1%
18 1
 
1.1%
27 1
 
1.1%
33 1
 
1.1%
34 1
 
1.1%
37 2
 
2.2%
47 1
 
1.1%
ValueCountFrequency (%)
164 1
1.1%
149 1
1.1%
137 1
1.1%
118 1
1.1%
114 1
1.1%
105 1
1.1%
97 1
1.1%
91 2
2.2%
88 1
1.1%
86 1
1.1%

광주광산경찰서
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct61
Distinct (%)67.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean538.95556
Minimum0
Maximum2691
Zeros2
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-13T01:36:25.463280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median131
Q3823
95-th percentile1991.25
Maximum2691
Range2691
Interquartile range (IQR)819

Descriptive statistics

Standard deviation732.61983
Coefficient of variation (CV)1.3593326
Kurtosis0.56646033
Mean538.95556
Median Absolute Deviation (MAD)129.5
Skewness1.3066033
Sum48506
Variance536731.82
MonotonicityNot monotonic
2023-12-13T01:36:25.605077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 8
 
8.9%
4 8
 
8.9%
1 7
 
7.8%
5 6
 
6.7%
0 2
 
2.2%
144 2
 
2.2%
2 2
 
2.2%
140 2
 
2.2%
829 1
 
1.1%
744 1
 
1.1%
Other values (51) 51
56.7%
ValueCountFrequency (%)
0 2
 
2.2%
1 7
7.8%
2 2
 
2.2%
3 8
8.9%
4 8
8.9%
5 6
6.7%
10 1
 
1.1%
12 1
 
1.1%
22 1
 
1.1%
59 1
 
1.1%
ValueCountFrequency (%)
2691 1
1.1%
2495 1
1.1%
2390 1
1.1%
2114 1
1.1%
1998 1
1.1%
1983 1
1.1%
1981 1
1.1%
1970 1
1.1%
1909 1
1.1%
1798 1
1.1%

광주동부경찰서
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct56
Distinct (%)62.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean297.04444
Minimum0
Maximum1538
Zeros9
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-13T01:36:25.730610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median70
Q3574.25
95-th percentile1011.45
Maximum1538
Range1538
Interquartile range (IQR)571.25

Descriptive statistics

Standard deviation386.99842
Coefficient of variation (CV)1.30283
Kurtosis0.61294159
Mean297.04444
Median Absolute Deviation (MAD)69.5
Skewness1.2244255
Sum26734
Variance149767.77
MonotonicityNot monotonic
2023-12-13T01:36:25.860457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
10.0%
2 9
 
10.0%
4 5
 
5.6%
5 4
 
4.4%
3 4
 
4.4%
76 3
 
3.3%
1 3
 
3.3%
68 2
 
2.2%
70 2
 
2.2%
61 2
 
2.2%
Other values (46) 47
52.2%
ValueCountFrequency (%)
0 9
10.0%
1 3
 
3.3%
2 9
10.0%
3 4
4.4%
4 5
5.6%
5 4
4.4%
6 1
 
1.1%
12 1
 
1.1%
57 1
 
1.1%
60 1
 
1.1%
ValueCountFrequency (%)
1538 1
1.1%
1350 1
1.1%
1297 1
1.1%
1090 1
1.1%
1038 1
1.1%
979 1
1.1%
972 1
1.1%
953 1
1.1%
948 1
1.1%
880 1
1.1%

광주서부경찰서
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct60
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean608.48889
Minimum0
Maximum2971
Zeros6
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-13T01:36:25.993957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median176
Q31118.75
95-th percentile2252.1
Maximum2971
Range2971
Interquartile range (IQR)1114.75

Descriptive statistics

Standard deviation803.94396
Coefficient of variation (CV)1.3212139
Kurtosis0.77486735
Mean608.48889
Median Absolute Deviation (MAD)174
Skewness1.3225224
Sum54764
Variance646325.89
MonotonicityNot monotonic
2023-12-13T01:36:26.121874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 12
 
13.3%
3 7
 
7.8%
0 6
 
6.7%
2 5
 
5.6%
7 3
 
3.3%
708 2
 
2.2%
188 2
 
2.2%
206 1
 
1.1%
2971 1
 
1.1%
198 1
 
1.1%
Other values (50) 50
55.6%
ValueCountFrequency (%)
0 6
6.7%
2 5
5.6%
3 7
7.8%
4 12
13.3%
5 1
 
1.1%
7 3
 
3.3%
8 1
 
1.1%
23 1
 
1.1%
133 1
 
1.1%
142 1
 
1.1%
ValueCountFrequency (%)
2971 1
1.1%
2858 1
1.1%
2829 1
1.1%
2293 1
1.1%
2253 1
1.1%
2251 1
1.1%
2146 1
1.1%
2079 1
1.1%
2067 1
1.1%
2065 1
1.1%

광주남부경찰서
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct56
Distinct (%)62.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean285.21111
Minimum0
Maximum1200
Zeros11
Zeros (%)12.2%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-13T01:36:26.250230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median58.5
Q3573
95-th percentile976.2
Maximum1200
Range1200
Interquartile range (IQR)570

Descriptive statistics

Standard deviation366.57389
Coefficient of variation (CV)1.2852721
Kurtosis-0.46516464
Mean285.21111
Median Absolute Deviation (MAD)58.5
Skewness0.99033718
Sum25669
Variance134376.42
MonotonicityNot monotonic
2023-12-13T01:36:26.385424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11
 
12.2%
3 10
 
11.1%
1 9
 
10.0%
51 3
 
3.3%
4 3
 
3.3%
2 2
 
2.2%
68 2
 
2.2%
60 2
 
2.2%
1200 1
 
1.1%
71 1
 
1.1%
Other values (46) 46
51.1%
ValueCountFrequency (%)
0 11
12.2%
1 9
10.0%
2 2
 
2.2%
3 10
11.1%
4 3
 
3.3%
5 1
 
1.1%
47 1
 
1.1%
51 3
 
3.3%
52 1
 
1.1%
54 1
 
1.1%
ValueCountFrequency (%)
1200 1
1.1%
1108 1
1.1%
1107 1
1.1%
1078 1
1.1%
1014 1
1.1%
930 1
1.1%
916 1
1.1%
904 1
1.1%
900 1
1.1%
898 1
1.1%

광주북부경찰서
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct68
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean690.22222
Minimum0
Maximum3066
Zeros3
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-13T01:36:26.523872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median165.5
Q31359
95-th percentile2360.1
Maximum3066
Range3066
Interquartile range (IQR)1353

Descriptive statistics

Standard deviation878.02535
Coefficient of variation (CV)1.2720908
Kurtosis-0.18127237
Mean690.22222
Median Absolute Deviation (MAD)163.5
Skewness1.049584
Sum62120
Variance770928.51
MonotonicityNot monotonic
2023-12-13T01:36:26.644973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 6
 
6.7%
6 5
 
5.6%
2 4
 
4.4%
5 4
 
4.4%
1 3
 
3.3%
0 3
 
3.3%
15 2
 
2.2%
4 2
 
2.2%
217 2
 
2.2%
1416 1
 
1.1%
Other values (58) 58
64.4%
ValueCountFrequency (%)
0 3
3.3%
1 3
3.3%
2 4
4.4%
3 6
6.7%
4 2
 
2.2%
5 4
4.4%
6 5
5.6%
7 1
 
1.1%
9 1
 
1.1%
10 1
 
1.1%
ValueCountFrequency (%)
3066 1
1.1%
2863 1
1.1%
2730 1
1.1%
2627 1
1.1%
2388 1
1.1%
2326 1
1.1%
2176 1
1.1%
2170 1
1.1%
2131 1
1.1%
2087 1
1.1%

Interactions

2023-12-13T01:36:23.050946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:19.856273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.328778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.833365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:21.337922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:21.884451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:22.488974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:23.137305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:19.919172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.399767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.914168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:21.411908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:21.958752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:22.572789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:23.218460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:19.983858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.466880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.988445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:21.498835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:22.044396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:22.649766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:23.319690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.043865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.533022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:21.053863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:21.567978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:22.114667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:22.723128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:23.447042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.116311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.609103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:21.123148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:21.643657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:22.218193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:22.801342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:23.534688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.182694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.679166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:21.190483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:21.719745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:22.298652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:22.882078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:23.624572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.257704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:20.750422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:21.263325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:21.802827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:22.398935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:22.973417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:36:26.729612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도범죄유형구분광주경찰청광주광산경찰서광주동부경찰서광주서부경찰서광주남부경찰서광주북부경찰서
연도1.0000.0000.0000.0000.0000.0000.0000.0000.000
범죄유형0.0001.0000.0000.7520.9110.9230.7920.8100.797
구분0.0000.0001.0000.4140.3090.2720.4790.5830.634
광주경찰청0.0000.7520.4141.0000.7150.7150.6400.5770.496
광주광산경찰서0.0000.9110.3090.7151.0000.9450.8580.8910.873
광주동부경찰서0.0000.9230.2720.7150.9451.0000.9070.8750.865
광주서부경찰서0.0000.7920.4790.6400.8580.9071.0000.9160.884
광주남부경찰서0.0000.8100.5830.5770.8910.8750.9161.0000.975
광주북부경찰서0.0000.7970.6340.4960.8730.8650.8840.9751.000
2023-12-13T01:36:26.849503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
범죄유형구분
범죄유형1.0000.000
구분0.0001.000
2023-12-13T01:36:26.944333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도광주경찰청광주광산경찰서광주동부경찰서광주서부경찰서광주남부경찰서광주북부경찰서범죄유형구분
연도1.000-0.066-0.004-0.127-0.124-0.026-0.1550.0000.000
광주경찰청-0.0661.0000.3640.3590.3730.3580.3440.3960.246
광주광산경찰서-0.0040.3641.0000.9380.9390.9490.9240.5900.183
광주동부경찰서-0.1270.3590.9381.0000.9670.9270.9680.6120.158
광주서부경찰서-0.1240.3730.9390.9671.0000.9450.9770.6340.336
광주남부경찰서-0.0260.3580.9490.9270.9451.0000.9200.6250.300
광주북부경찰서-0.1550.3440.9240.9680.9770.9201.0000.6060.339
범죄유형0.0000.3960.5900.6120.6340.6250.6061.0000.000
구분0.0000.2460.1830.1580.3360.3000.3390.0001.000

Missing values

2023-12-13T01:36:23.761776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:36:23.926929image/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

연도범죄유형구분광주경찰청광주광산경찰서광주동부경찰서광주서부경찰서광주남부경찰서광주북부경찰서
02022살인발생건수030000
12022살인검거건수030010
22022살인검거인원050020
32022강도발생건수012232
42022강도검거건수012232
52022강도검거인원011232
62022성범죄발생건수01307217963139
72022성범죄검거건수801176114451115
82022성범죄검거인원861406816354124
92022절도발생건수0129961011235611614
연도범죄유형구분광주경찰청광주광산경찰서광주동부경찰서광주서부경찰서광주남부경찰서광주북부경찰서
802017강도검거인원12242356
812017성범죄발생건수01697719668215
822017성범죄검거건수911447017251204
832017성범죄검거인원1051487618847260
842017절도발생건수092762411425771546
852017절도검거건수06604707085221127
862017절도검거인원0594483708363898
872017폭력발생건수01909109022938982176
882017폭력검거건수37170295320657991997
892017폭력검거인원14923901538297111072863