Overview

Dataset statistics

Number of variables18
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory163.8 B

Variable types

Categorical1
Text1
Numeric16

Dataset

Description전국 경찰관서에 고소, 고발, 인지 등으로 형사입건된 사건의 발생, 검거, 피의자에 대한 죄종별 분석 현황
Author경찰청
URLhttps://www.data.go.kr/data/3074480/fileData.do

Alerts

이욕(생활비) is highly overall correlated with 이욕(유흥비) and 13 other fieldsHigh correlation
이욕(유흥비) is highly overall correlated with 이욕(생활비) and 12 other fieldsHigh correlation
이욕(도박비) is highly overall correlated with 이욕(생활비) and 12 other fieldsHigh correlation
이욕(허영사치심) is highly overall correlated with 이욕(생활비) and 13 other fieldsHigh correlation
이욕(치부) is highly overall correlated with 이욕(생활비) and 12 other fieldsHigh correlation
이욕(기타) is highly overall correlated with 이욕(생활비) and 15 other fieldsHigh correlation
사행심 is highly overall correlated with 이욕(생활비) and 14 other fieldsHigh correlation
보복 is highly overall correlated with 이욕(생활비) and 13 other fieldsHigh correlation
가정불화 is highly overall correlated with 이욕(기타) and 7 other fieldsHigh correlation
호기심 is highly overall correlated with 이욕(생활비) and 15 other fieldsHigh correlation
유혹 is highly overall correlated with 이욕(생활비) and 14 other fieldsHigh correlation
우발적 is highly overall correlated with 이욕(생활비) and 14 other fieldsHigh correlation
현실불만 is highly overall correlated with 이욕(허영사치심) and 10 other fieldsHigh correlation
부주의 is highly overall correlated with 이욕(생활비) and 15 other fieldsHigh correlation
기타 is highly overall correlated with 이욕(생활비) and 15 other fieldsHigh correlation
미상 is highly overall correlated with 이욕(생활비) and 14 other fieldsHigh correlation
범죄대분류 is highly overall correlated with 이욕(생활비) and 7 other fieldsHigh correlation
범죄중분류 has unique valuesUnique
기타 has unique valuesUnique
이욕(생활비) has 2 (5.7%) zerosZeros
이욕(유흥비) has 6 (17.1%) zerosZeros
이욕(도박비) has 17 (48.6%) zerosZeros
이욕(허영사치심) has 12 (34.3%) zerosZeros
이욕(치부) has 5 (14.3%) zerosZeros
사행심 has 8 (22.9%) zerosZeros
보복 has 13 (37.1%) zerosZeros
가정불화 has 8 (22.9%) zerosZeros
호기심 has 6 (17.1%) zerosZeros
유혹 has 6 (17.1%) zerosZeros
우발적 has 1 (2.9%) zerosZeros
현실불만 has 5 (14.3%) zerosZeros
부주의 has 2 (5.7%) zerosZeros

Reproduction

Analysis started2023-12-12 09:26:39.647646
Analysis finished2023-12-12 09:27:11.614508
Duration31.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

범죄대분류
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
지능범죄
폭력범죄
강력범죄
풍속범죄
절도범죄
 
1
Other values (10)
10 

Length

Max length6
Median length4
Mean length4
Min length2

Unique

Unique11 ?
Unique (%)31.4%

Sample

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

Common Values

ValueCountFrequency (%)
지능범죄 9
25.7%
폭력범죄 8
22.9%
강력범죄 5
14.3%
풍속범죄 2
 
5.7%
절도범죄 1
 
2.9%
특별경제범죄 1
 
2.9%
마약범죄 1
 
2.9%
보건범죄 1
 
2.9%
환경범죄 1
 
2.9%
교통범죄 1
 
2.9%
Other values (5) 5
14.3%

Length

2023-12-12T18:27:11.705467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지능범죄 9
25.7%
폭력범죄 8
22.9%
강력범죄 5
14.3%
풍속범죄 2
 
5.7%
절도범죄 1
 
2.9%
특별경제범죄 1
 
2.9%
마약범죄 1
 
2.9%
보건범죄 1
 
2.9%
환경범죄 1
 
2.9%
교통범죄 1
 
2.9%
Other values (5) 5
14.3%

범죄중분류
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-12T18:27:11.962144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.5428571
Min length2

Characters and Unicode

Total characters124
Distinct characters72
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

Unique35 ?
Unique (%)100.0%

Sample

1st row살인기수
2nd row살인미수등
3rd row강도
4th row강간강제추행
5th row방화
ValueCountFrequency (%)
살인기수 1
 
2.9%
문서인장 1
 
2.9%
사기 1
 
2.9%
횡령 1
 
2.9%
배임 1
 
2.9%
성풍속범죄 1
 
2.9%
도박범죄 1
 
2.9%
특별경제범죄 1
 
2.9%
유가증권인지 1
 
2.9%
마약범죄 1
 
2.9%
Other values (25) 25
71.4%
2023-12-12T18:27:12.404821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
9.7%
12
 
9.7%
5
 
4.0%
4
 
3.2%
3
 
2.4%
3
 
2.4%
3
 
2.4%
3
 
2.4%
3
 
2.4%
2
 
1.6%
Other values (62) 74
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 124
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12
 
9.7%
12
 
9.7%
5
 
4.0%
4
 
3.2%
3
 
2.4%
3
 
2.4%
3
 
2.4%
3
 
2.4%
3
 
2.4%
2
 
1.6%
Other values (62) 74
59.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 124
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12
 
9.7%
12
 
9.7%
5
 
4.0%
4
 
3.2%
3
 
2.4%
3
 
2.4%
3
 
2.4%
3
 
2.4%
3
 
2.4%
2
 
1.6%
Other values (62) 74
59.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 124
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
12
 
9.7%
12
 
9.7%
5
 
4.0%
4
 
3.2%
3
 
2.4%
3
 
2.4%
3
 
2.4%
3
 
2.4%
3
 
2.4%
2
 
1.6%
Other values (62) 74
59.7%

이욕(생활비)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1523.6286
Minimum0
Maximum13872
Zeros2
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:12.604424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.7
Q117.5
median62
Q3671
95-th percentile12214.9
Maximum13872
Range13872
Interquartile range (IQR)653.5

Descriptive statistics

Standard deviation3656.7975
Coefficient of variation (CV)2.4000583
Kurtosis6.6510746
Mean1523.6286
Median Absolute Deviation (MAD)61
Skewness2.7871726
Sum53327
Variance13372168
MonotonicityNot monotonic
2023-12-12T18:27:12.774730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 2
 
5.7%
6 2
 
5.7%
0 2
 
5.7%
214 1
 
2.9%
13872 1
 
2.9%
27 1
 
2.9%
513 1
 
2.9%
258 1
 
2.9%
12518 1
 
2.9%
2723 1
 
2.9%
Other values (22) 22
62.9%
ValueCountFrequency (%)
0 2
5.7%
1 2
5.7%
6 2
5.7%
7 1
2.9%
14 1
2.9%
15 1
2.9%
20 1
2.9%
22 1
2.9%
23 1
2.9%
25 1
2.9%
ValueCountFrequency (%)
13872 1
2.9%
12518 1
2.9%
12085 1
2.9%
5313 1
2.9%
2723 1
2.9%
1370 1
2.9%
1005 1
2.9%
754 1
2.9%
711 1
2.9%
631 1
2.9%

이욕(유흥비)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)65.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean320.42857
Minimum0
Maximum5564
Zeros6
Zeros (%)17.1%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:12.930156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q362
95-th percentile1479.6
Maximum5564
Range5564
Interquartile range (IQR)61

Descriptive statistics

Standard deviation1011.5743
Coefficient of variation (CV)3.1569415
Kurtosis22.596987
Mean320.42857
Median Absolute Deviation (MAD)7
Skewness4.5723787
Sum11215
Variance1023282.5
MonotonicityNot monotonic
2023-12-12T18:27:13.093950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 6
17.1%
1 5
 
14.3%
6 2
 
5.7%
4 2
 
5.7%
11 2
 
5.7%
15 1
 
2.9%
174 1
 
2.9%
512 1
 
2.9%
12 1
 
2.9%
10 1
 
2.9%
Other values (13) 13
37.1%
ValueCountFrequency (%)
0 6
17.1%
1 5
14.3%
3 1
 
2.9%
4 2
 
5.7%
5 1
 
2.9%
6 2
 
5.7%
7 1
 
2.9%
10 1
 
2.9%
11 2
 
5.7%
12 1
 
2.9%
ValueCountFrequency (%)
5564 1
2.9%
2307 1
2.9%
1125 1
2.9%
512 1
2.9%
456 1
2.9%
439 1
2.9%
367 1
2.9%
174 1
2.9%
91 1
2.9%
33 1
2.9%

이욕(도박비)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.028571
Minimum0
Maximum418
Zeros17
Zeros (%)48.6%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:13.243376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q310
95-th percentile223.4
Maximum418
Range418
Interquartile range (IQR)10

Descriptive statistics

Standard deviation98.06435
Coefficient of variation (CV)2.9690764
Kurtosis12.31026
Mean33.028571
Median Absolute Deviation (MAD)1
Skewness3.5952182
Sum1156
Variance9616.6168
MonotonicityNot monotonic
2023-12-12T18:27:13.387925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 17
48.6%
1 3
 
8.6%
4 2
 
5.7%
12 2
 
5.7%
24 1
 
2.9%
146 1
 
2.9%
2 1
 
2.9%
8 1
 
2.9%
418 1
 
2.9%
58 1
 
2.9%
Other values (5) 5
 
14.3%
ValueCountFrequency (%)
0 17
48.6%
1 3
 
8.6%
2 1
 
2.9%
3 1
 
2.9%
4 2
 
5.7%
6 1
 
2.9%
8 1
 
2.9%
12 2
 
5.7%
17 1
 
2.9%
24 1
 
2.9%
ValueCountFrequency (%)
418 1
2.9%
404 1
2.9%
146 1
2.9%
58 1
2.9%
35 1
2.9%
24 1
2.9%
17 1
2.9%
12 2
5.7%
8 1
2.9%
6 1
2.9%

이욕(허영사치심)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.485714
Minimum0
Maximum488
Zeros12
Zeros (%)34.3%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:13.539431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q39.5
95-th percentile113
Maximum488
Range488
Interquartile range (IQR)9.5

Descriptive statistics

Standard deviation89.354012
Coefficient of variation (CV)3.0304171
Kurtosis21.86278
Mean29.485714
Median Absolute Deviation (MAD)2
Skewness4.519666
Sum1032
Variance7984.1395
MonotonicityNot monotonic
2023-12-12T18:27:13.706941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 12
34.3%
1 4
 
11.4%
4 4
 
11.4%
2 3
 
8.6%
34 1
 
2.9%
55 1
 
2.9%
3 1
 
2.9%
28 1
 
2.9%
32 1
 
2.9%
6 1
 
2.9%
Other values (6) 6
17.1%
ValueCountFrequency (%)
0 12
34.3%
1 4
 
11.4%
2 3
 
8.6%
3 1
 
2.9%
4 4
 
11.4%
6 1
 
2.9%
9 1
 
2.9%
10 1
 
2.9%
28 1
 
2.9%
32 1
 
2.9%
ValueCountFrequency (%)
488 1
2.9%
225 1
2.9%
65 1
2.9%
55 1
2.9%
51 1
2.9%
34 1
2.9%
32 1
2.9%
28 1
2.9%
10 1
2.9%
9 1
2.9%

이욕(치부)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.285714
Minimum0
Maximum689
Zeros5
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:13.878956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q335
95-th percentile370.7
Maximum689
Range689
Interquartile range (IQR)34

Descriptive statistics

Standard deviation154.28441
Coefficient of variation (CV)2.3275666
Kurtosis9.7387926
Mean66.285714
Median Absolute Deviation (MAD)5
Skewness3.12834
Sum2320
Variance23803.681
MonotonicityNot monotonic
2023-12-12T18:27:14.054853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 5
14.3%
0 5
14.3%
2 5
14.3%
5 3
 
8.6%
86 1
 
2.9%
552 1
 
2.9%
23 1
 
2.9%
63 1
 
2.9%
293 1
 
2.9%
111 1
 
2.9%
Other values (11) 11
31.4%
ValueCountFrequency (%)
0 5
14.3%
1 5
14.3%
2 5
14.3%
3 1
 
2.9%
5 3
8.6%
6 1
 
2.9%
7 1
 
2.9%
12 1
 
2.9%
17 1
 
2.9%
23 1
 
2.9%
ValueCountFrequency (%)
689 1
2.9%
552 1
2.9%
293 1
2.9%
253 1
2.9%
111 1
2.9%
86 1
2.9%
75 1
2.9%
63 1
2.9%
37 1
2.9%
33 1
2.9%

이욕(기타)
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2038.9429
Minimum8
Maximum13207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:14.231221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile12.8
Q162.5
median351
Q31698.5
95-th percentile11457.4
Maximum13207
Range13199
Interquartile range (IQR)1636

Descriptive statistics

Standard deviation3574.0142
Coefficient of variation (CV)1.7528761
Kurtosis4.1144368
Mean2038.9429
Median Absolute Deviation (MAD)343
Skewness2.2431512
Sum71363
Variance12773578
MonotonicityNot monotonic
2023-12-12T18:27:14.391108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
787 2
 
5.7%
22 1
 
2.9%
36 1
 
2.9%
1671 1
 
2.9%
351 1
 
2.9%
1236 1
 
2.9%
3015 1
 
2.9%
5861 1
 
2.9%
252 1
 
2.9%
1249 1
 
2.9%
Other values (24) 24
68.6%
ValueCountFrequency (%)
8 1
2.9%
10 1
2.9%
14 1
2.9%
18 1
2.9%
21 1
2.9%
22 1
2.9%
33 1
2.9%
36 1
2.9%
56 1
2.9%
69 1
2.9%
ValueCountFrequency (%)
13207 1
2.9%
12170 1
2.9%
11152 1
2.9%
7555 1
2.9%
5861 1
2.9%
3863 1
2.9%
3015 1
2.9%
1966 1
2.9%
1726 1
2.9%
1671 1
2.9%

사행심
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean634
Minimum0
Maximum12969
Zeros8
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:14.544011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.5
median22
Q3128
95-th percentile2567.1
Maximum12969
Range12969
Interquartile range (IQR)126.5

Descriptive statistics

Standard deviation2250.9222
Coefficient of variation (CV)3.5503504
Kurtosis28.415061
Mean634
Median Absolute Deviation (MAD)22
Skewness5.1652531
Sum22190
Variance5066650.6
MonotonicityNot monotonic
2023-12-12T18:27:14.684185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 8
22.9%
2 3
 
8.6%
2520 1
 
2.9%
2677 1
 
2.9%
7 1
 
2.9%
30 1
 
2.9%
76 1
 
2.9%
140 1
 
2.9%
19 1
 
2.9%
507 1
 
2.9%
Other values (16) 16
45.7%
ValueCountFrequency (%)
0 8
22.9%
1 1
 
2.9%
2 3
 
8.6%
3 1
 
2.9%
7 1
 
2.9%
10 1
 
2.9%
17 1
 
2.9%
19 1
 
2.9%
22 1
 
2.9%
29 1
 
2.9%
ValueCountFrequency (%)
12969 1
2.9%
2677 1
2.9%
2520 1
2.9%
2023 1
2.9%
507 1
2.9%
341 1
2.9%
266 1
2.9%
165 1
2.9%
140 1
2.9%
116 1
2.9%

보복
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.6
Minimum0
Maximum117
Zeros13
Zeros (%)37.1%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:14.822625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q36
95-th percentile44.7
Maximum117
Range117
Interquartile range (IQR)6

Descriptive statistics

Standard deviation22.236959
Coefficient of variation (CV)2.3163499
Kurtosis16.44509
Mean9.6
Median Absolute Deviation (MAD)1
Skewness3.7945478
Sum336
Variance494.48235
MonotonicityNot monotonic
2023-12-12T18:27:14.968613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 13
37.1%
1 5
 
14.3%
3 4
 
11.4%
4 2
 
5.7%
2 2
 
5.7%
12 1
 
2.9%
18 1
 
2.9%
117 1
 
2.9%
11 1
 
2.9%
42 1
 
2.9%
Other values (4) 4
 
11.4%
ValueCountFrequency (%)
0 13
37.1%
1 5
 
14.3%
2 2
 
5.7%
3 4
 
11.4%
4 2
 
5.7%
8 1
 
2.9%
11 1
 
2.9%
12 1
 
2.9%
17 1
 
2.9%
18 1
 
2.9%
ValueCountFrequency (%)
117 1
2.9%
51 1
2.9%
42 1
2.9%
31 1
2.9%
18 1
2.9%
17 1
2.9%
12 1
2.9%
11 1
2.9%
8 1
2.9%
4 2
5.7%

가정불화
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean173.4
Minimum0
Maximum1724
Zeros8
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:15.113949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median16
Q386
95-th percentile1155.7
Maximum1724
Range1724
Interquartile range (IQR)85

Descriptive statistics

Standard deviation419.62786
Coefficient of variation (CV)2.4199992
Kurtosis9.2889023
Mean173.4
Median Absolute Deviation (MAD)16
Skewness3.1324196
Sum6069
Variance176087.54
MonotonicityNot monotonic
2023-12-12T18:27:15.236970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 8
22.9%
6 2
 
5.7%
1 2
 
5.7%
51 1
 
2.9%
455 1
 
2.9%
35 1
 
2.9%
2 1
 
2.9%
174 1
 
2.9%
75 1
 
2.9%
8 1
 
2.9%
Other values (16) 16
45.7%
ValueCountFrequency (%)
0 8
22.9%
1 2
 
5.7%
2 1
 
2.9%
3 1
 
2.9%
6 2
 
5.7%
8 1
 
2.9%
10 1
 
2.9%
15 1
 
2.9%
16 1
 
2.9%
17 1
 
2.9%
ValueCountFrequency (%)
1724 1
2.9%
1666 1
2.9%
937 1
2.9%
455 1
2.9%
346 1
2.9%
174 1
2.9%
115 1
2.9%
114 1
2.9%
97 1
2.9%
75 1
2.9%

호기심
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean463.71429
Minimum0
Maximum5583
Zeros6
Zeros (%)17.1%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:15.390702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median16
Q3378.5
95-th percentile2089.7
Maximum5583
Range5583
Interquartile range (IQR)375.5

Descriptive statistics

Standard deviation1069.469
Coefficient of variation (CV)2.3063101
Kurtosis15.813139
Mean463.71429
Median Absolute Deviation (MAD)16
Skewness3.7066991
Sum16230
Variance1143763.9
MonotonicityNot monotonic
2023-12-12T18:27:15.514675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 6
 
17.1%
16 2
 
5.7%
5 2
 
5.7%
2 2
 
5.7%
2537 1
 
2.9%
7 1
 
2.9%
4 1
 
2.9%
1535 1
 
2.9%
15 1
 
2.9%
399 1
 
2.9%
Other values (17) 17
48.6%
ValueCountFrequency (%)
0 6
17.1%
1 1
 
2.9%
2 2
 
5.7%
4 1
 
2.9%
5 2
 
5.7%
6 1
 
2.9%
7 1
 
2.9%
8 1
 
2.9%
15 1
 
2.9%
16 2
 
5.7%
ValueCountFrequency (%)
5583 1
2.9%
2537 1
2.9%
1898 1
2.9%
1535 1
2.9%
1026 1
2.9%
720 1
2.9%
684 1
2.9%
590 1
2.9%
399 1
2.9%
358 1
2.9%

유혹
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean310.54286
Minimum0
Maximum3251
Zeros6
Zeros (%)17.1%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:15.650023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median16
Q3229
95-th percentile1692.8
Maximum3251
Range3251
Interquartile range (IQR)226

Descriptive statistics

Standard deviation674.40537
Coefficient of variation (CV)2.1716982
Kurtosis10.79963
Mean310.54286
Median Absolute Deviation (MAD)16
Skewness3.1305783
Sum10869
Variance454822.61
MonotonicityNot monotonic
2023-12-12T18:27:15.777228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 6
 
17.1%
3 2
 
5.7%
15 2
 
5.7%
16 2
 
5.7%
10 2
 
5.7%
17 1
 
2.9%
24 1
 
2.9%
1661 1
 
2.9%
6 1
 
2.9%
1767 1
 
2.9%
Other values (16) 16
45.7%
ValueCountFrequency (%)
0 6
17.1%
1 1
 
2.9%
2 1
 
2.9%
3 2
 
5.7%
6 1
 
2.9%
10 2
 
5.7%
11 1
 
2.9%
15 2
 
5.7%
16 2
 
5.7%
17 1
 
2.9%
ValueCountFrequency (%)
3251 1
2.9%
1767 1
2.9%
1661 1
2.9%
974 1
2.9%
758 1
2.9%
664 1
2.9%
391 1
2.9%
312 1
2.9%
264 1
2.9%
194 1
2.9%

우발적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8097.9429
Minimum0
Maximum55814
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:15.916119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.4
Q135
median489
Q34531.5
95-th percentile51187.3
Maximum55814
Range55814
Interquartile range (IQR)4496.5

Descriptive statistics

Standard deviation16118.93
Coefficient of variation (CV)1.9904969
Kurtosis3.5319531
Mean8097.9429
Median Absolute Deviation (MAD)485
Skewness2.1549832
Sum283428
Variance2.598199 × 108
MonotonicityNot monotonic
2023-12-12T18:27:16.056400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
4 2
 
5.7%
147 1
 
2.9%
489 1
 
2.9%
3195 1
 
2.9%
1273 1
 
2.9%
27 1
 
2.9%
1051 1
 
2.9%
2116 1
 
2.9%
9002 1
 
2.9%
223 1
 
2.9%
Other values (24) 24
68.6%
ValueCountFrequency (%)
0 1
2.9%
1 1
2.9%
3 1
2.9%
4 2
5.7%
5 1
2.9%
19 1
2.9%
27 1
2.9%
30 1
2.9%
40 1
2.9%
70 1
2.9%
ValueCountFrequency (%)
55814 1
2.9%
52784 1
2.9%
50503 1
2.9%
33334 1
2.9%
29104 1
2.9%
18745 1
2.9%
15196 1
2.9%
9002 1
2.9%
5868 1
2.9%
3195 1
2.9%

현실불만
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean302.8
Minimum0
Maximum1969
Zeros5
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:16.224592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median38
Q3131.5
95-th percentile1851.7
Maximum1969
Range1969
Interquartile range (IQR)125.5

Descriptive statistics

Standard deviation593.72344
Coefficient of variation (CV)1.9607775
Kurtosis2.8946543
Mean302.8
Median Absolute Deviation (MAD)37
Skewness2.0696855
Sum10598
Variance352507.52
MonotonicityNot monotonic
2023-12-12T18:27:16.394299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 5
 
14.3%
3 2
 
5.7%
6 2
 
5.7%
23 2
 
5.7%
28 1
 
2.9%
1969 1
 
2.9%
50 1
 
2.9%
43 1
 
2.9%
139 1
 
2.9%
39 1
 
2.9%
Other values (18) 18
51.4%
ValueCountFrequency (%)
0 5
14.3%
1 1
 
2.9%
3 2
 
5.7%
6 2
 
5.7%
9 1
 
2.9%
15 1
 
2.9%
17 1
 
2.9%
23 2
 
5.7%
27 1
 
2.9%
28 1
 
2.9%
ValueCountFrequency (%)
1969 1
2.9%
1879 1
2.9%
1840 1
2.9%
1407 1
2.9%
1206 1
2.9%
873 1
2.9%
304 1
2.9%
193 1
2.9%
139 1
2.9%
124 1
2.9%

부주의
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6627.6286
Minimum0
Maximum182010
Zeros2
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:16.537182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.4
Q117
median260
Q31292.5
95-th percentile11058.3
Maximum182010
Range182010
Interquartile range (IQR)1275.5

Descriptive statistics

Standard deviation30738.665
Coefficient of variation (CV)4.6379583
Kurtosis33.909807
Mean6627.6286
Median Absolute Deviation (MAD)260
Skewness5.7893912
Sum231967
Variance9.4486552 × 108
MonotonicityNot monotonic
2023-12-12T18:27:16.672942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
2 2
 
5.7%
0 2
 
5.7%
336 1
 
2.9%
668 1
 
2.9%
145 1
 
2.9%
1266 1
 
2.9%
737 1
 
2.9%
6816 1
 
2.9%
2160 1
 
2.9%
11 1
 
2.9%
Other values (23) 23
65.7%
ValueCountFrequency (%)
0 2
5.7%
2 2
5.7%
3 1
2.9%
10 1
2.9%
11 1
2.9%
12 1
2.9%
16 1
2.9%
18 1
2.9%
21 1
2.9%
35 1
2.9%
ValueCountFrequency (%)
182010 1
2.9%
20957 1
2.9%
6816 1
2.9%
4075 1
2.9%
3666 1
2.9%
2342 1
2.9%
2160 1
2.9%
1383 1
2.9%
1319 1
2.9%
1266 1
2.9%

기타
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15142.971
Minimum44
Maximum165428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:16.844322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile64.4
Q1302
median1969
Q311563
95-th percentile68727.2
Maximum165428
Range165384
Interquartile range (IQR)11261

Descriptive statistics

Standard deviation32092.965
Coefficient of variation (CV)2.1193307
Kurtosis14.673742
Mean15142.971
Median Absolute Deviation (MAD)1913
Skewness3.6028014
Sum530004
Variance1.0299584 × 109
MonotonicityNot monotonic
2023-12-12T18:27:17.013696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
118 1
 
2.9%
183 1
 
2.9%
60689 1
 
2.9%
8697 1
 
2.9%
1969 1
 
2.9%
6712 1
 
2.9%
11167 1
 
2.9%
33508 1
 
2.9%
2195 1
 
2.9%
10661 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
44 1
2.9%
56 1
2.9%
68 1
2.9%
84 1
2.9%
118 1
2.9%
153 1
2.9%
165 1
2.9%
183 1
2.9%
265 1
2.9%
339 1
2.9%
ValueCountFrequency (%)
165428 1
2.9%
87483 1
2.9%
60689 1
2.9%
33508 1
2.9%
29067 1
2.9%
24953 1
2.9%
24599 1
2.9%
22212 1
2.9%
11959 1
2.9%
11167 1
2.9%

미상
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13477.457
Minimum18
Maximum120868
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:27:17.191811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile55.9
Q1285
median1230
Q36803.5
95-th percentile91925.8
Maximum120868
Range120850
Interquartile range (IQR)6518.5

Descriptive statistics

Standard deviation30886.817
Coefficient of variation (CV)2.2917392
Kurtosis7.5817151
Mean13477.457
Median Absolute Deviation (MAD)1156
Skewness2.8752272
Sum471711
Variance9.5399546 × 108
MonotonicityNot monotonic
2023-12-12T18:27:17.347173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
450 2
 
5.7%
77 1
 
2.9%
436 1
 
2.9%
120868 1
 
2.9%
14477 1
 
2.9%
4820 1
 
2.9%
2768 1
 
2.9%
1659 1
 
2.9%
29765 1
 
2.9%
2216 1
 
2.9%
Other values (24) 24
68.6%
ValueCountFrequency (%)
18 1
2.9%
51 1
2.9%
58 1
2.9%
74 1
2.9%
77 1
2.9%
104 1
2.9%
171 1
2.9%
210 1
2.9%
253 1
2.9%
317 1
2.9%
ValueCountFrequency (%)
120868 1
2.9%
119776 1
2.9%
79990 1
2.9%
43723 1
2.9%
29765 1
2.9%
14477 1
2.9%
13655 1
2.9%
8824 1
2.9%
7454 1
2.9%
6153 1
2.9%

Interactions

2023-12-12T18:27:08.670206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:40.429146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:42.256383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:44.350005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:45.899390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:47.413096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:49.345776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:51.392809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:53.240959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:55.036294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:57.166476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:58.844566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:00.785589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:02.704694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:04.994934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:06.866409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:08.790688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:40.531432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:42.356225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:44.460000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:45.996840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:47.559242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:49.466650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:51.481931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:53.362940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:55.172209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:57.258920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:58.946334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:00.943452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:02.839878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:05.126753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:06.995932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:08.902148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:40.647022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:42.451087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:44.543941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:46.084311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:47.672474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:49.573551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:51.590405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2023-12-12T18:27:08.379386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:10.616401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:42.148253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:44.250706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:45.800360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:47.312008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:49.224205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:51.300108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:53.121867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:54.919962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:56.732693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:26:58.758719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:00.618857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:02.598030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:04.871709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:06.735780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:27:08.575359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:27:17.463090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
범죄대분류범죄중분류이욕(생활비)이욕(유흥비)이욕(도박비)이욕(허영사치심)이욕(치부)이욕(기타)사행심보복가정불화호기심유혹우발적현실불만부주의기타미상
범죄대분류1.0001.0000.9950.0000.4760.6480.8740.8770.8480.7160.6480.9430.9550.8310.7551.0000.9100.758
범죄중분류1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
이욕(생활비)0.9951.0001.0000.7170.6460.7540.9000.8950.6540.7640.0000.7120.8680.6500.7910.4520.8050.717
이욕(유흥비)0.0001.0000.7171.0000.9380.9900.9520.8440.8610.8300.5740.6490.6730.5460.7500.0000.7900.631
이욕(도박비)0.4761.0000.6460.9381.0000.9390.8960.8110.9080.2000.0000.6800.7550.2770.6510.0000.4910.484
이욕(허영사치심)0.6481.0000.7540.9900.9391.0000.9640.8140.9170.7430.2690.7540.7070.5940.7750.2940.8230.622
이욕(치부)0.8741.0000.9000.9520.8960.9641.0000.9200.9520.9650.3780.9250.7870.9030.9350.9140.9770.972
이욕(기타)0.8771.0000.8950.8440.8110.8140.9201.0000.8020.8460.8180.8370.8230.8010.8250.8520.9140.852
사행심0.8481.0000.6540.8610.9080.9170.9520.8021.0000.8310.2940.8450.8440.7250.5460.6500.8220.724
보복0.7161.0000.7640.8300.2000.7430.9650.8460.8311.0000.7900.8300.4310.9330.9500.9140.9740.986
가정불화0.6481.0000.0000.5740.0000.2690.3780.8180.2940.7901.0000.6630.6460.8410.7010.8160.8020.756
호기심0.9431.0000.7120.6490.6800.7540.9250.8370.8450.8300.6631.0000.8130.9400.8301.0000.9390.861
유혹0.9551.0000.8680.6730.7550.7070.7870.8230.8440.4310.6460.8131.0000.6300.5510.6830.6720.438
우발적0.8311.0000.6500.5460.2770.5940.9030.8010.7250.9330.8410.9400.6301.0000.9700.9820.9610.914
현실불만0.7551.0000.7910.7500.6510.7750.9350.8250.5460.9500.7010.8300.5510.9701.0000.3220.9150.876
부주의1.0001.0000.4520.0000.0000.2940.9140.8520.6500.9140.8161.0000.6830.9820.3221.0001.0000.982
기타0.9101.0000.8050.7900.4910.8230.9770.9140.8220.9740.8020.9390.6720.9610.9151.0001.0000.979
미상0.7581.0000.7170.6310.4840.6220.9720.8520.7240.9860.7560.8610.4380.9140.8760.9820.9791.000
2023-12-12T18:27:17.665519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이욕(생활비)이욕(유흥비)이욕(도박비)이욕(허영사치심)이욕(치부)이욕(기타)사행심보복가정불화호기심유혹우발적현실불만부주의기타미상범죄대분류
이욕(생활비)1.0000.7900.8240.7870.8460.8550.9030.5180.2570.6820.8090.5190.3780.7590.7760.6640.730
이욕(유흥비)0.7901.0000.8450.8410.8010.7270.8390.5100.3830.7150.7910.6410.4340.5100.6210.6160.000
이욕(도박비)0.8240.8451.0000.8540.8730.8150.8860.5260.2960.6340.7830.6150.3990.5900.7000.6890.205
이욕(허영사치심)0.7870.8410.8541.0000.7750.8100.8020.5830.3960.6910.7480.6670.5190.6300.6990.6410.329
이욕(치부)0.8460.8010.8730.7751.0000.8140.8780.4890.3530.5760.7180.5730.3990.6420.7270.6480.529
이욕(기타)0.8550.7270.8150.8100.8141.0000.9080.7750.6100.7700.8560.8240.6930.9140.9700.8720.541
사행심0.9030.8390.8860.8020.8780.9081.0000.6450.4660.7550.8340.7170.5340.7720.8490.7920.532
보복0.5180.5100.5260.5830.4890.7750.6451.0000.7400.6950.6680.8520.8660.7220.7940.7120.344
가정불화0.2570.3830.2960.3960.3530.6100.4660.7401.0000.5630.4520.8740.8760.5680.6490.5750.251
호기심0.6820.7150.6340.6910.5760.7700.7550.6950.5631.0000.8580.7680.6870.6760.7170.6680.655
유혹0.8090.7910.7830.7480.7180.8560.8340.6680.4520.8581.0000.7190.5620.7180.8000.7430.586
우발적0.5190.6410.6150.6670.5730.8240.7170.8520.8740.7680.7191.0000.8880.6940.8120.7540.468
현실불만0.3780.4340.3990.5190.3990.6930.5340.8660.8760.6870.5620.8881.0000.6410.7180.6300.381
부주의0.7590.5100.5900.6300.6420.9140.7720.7220.5680.6760.7180.6940.6411.0000.9610.8560.791
기타0.7760.6210.7000.6990.7270.9700.8490.7940.6490.7170.8000.8120.7180.9611.0000.9010.589
미상0.6640.6160.6890.6410.6480.8720.7920.7120.5750.6680.7430.7540.6300.8560.9011.0000.385
범죄대분류0.7300.0000.2050.3290.5290.5410.5320.3440.2510.6550.5860.4680.3810.7910.5890.3851.000

Missing values

2023-12-12T18:27:10.821559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:27:11.477669image/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

범죄대분류범죄중분류이욕(생활비)이욕(유흥비)이욕(도박비)이욕(허영사치심)이욕(치부)이욕(기타)사행심보복가정불화호기심유혹우발적현실불만부주의기타미상
0강력범죄살인기수160252200510014715211877
1강력범죄살인미수등000023300440125538318351
2강력범죄강도63143924973475311516376422716805253
3강력범죄강간강제추행6219413390922430102697458687426046144112
4강력범죄방화6000169219762054712440339104
5절도범죄절도범죄120855564146488253111522023127455833251291043042342245997454
6폭력범죄상해26624617264218166627175050314071035222126153
7폭력범죄폭행43151451966511171724452455814184013832495379990
8폭력범죄체포감금71001562017132831710265450
9폭력범죄협박1430001491011115161612551233510471938
범죄대분류범죄중분류이욕(생활비)이욕(유흥비)이욕(도박비)이욕(허영사치심)이욕(치부)이욕(기타)사행심보복가정불화호기심유혹우발적현실불만부주의기타미상
25특별경제범죄특별경제범죄5313911728293586150731757201949002120668163350829765
26마약범죄마약범죄5750122521936399758223393362195436
27보건범죄보건범죄272310646312491401655622562160106612216
28환경범죄환경범죄12210212262001534037561574450
29교통범죄교통범죄2581234275557631741535176733334139182010165428119776
30노동범죄노동범죄51311002316130025101931401251210
31안보범죄안보범죄60000140104042305618
32선거범죄선거범죄2700311750217157043128948435
33병역범죄병역범죄2140002980733526205503666119591230
34기타기타1387251235555521320726775145525371661187451969209578748343723