Overview

Dataset statistics

Number of variables14
Number of observations185
Missing cells187
Missing cells (%)7.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.5 KiB
Average record size in memory113.7 B

Variable types

Text2
Categorical11
Unsupported1

Dataset

Description범죄발생원표를 활용한 범죄자의 국적별, 범죄분류별 현황
Author대검찰청
URLhttps://www.data.go.kr/data/2504159/fileData.do

Alerts

기타 is highly overall correlated with 중국 and 9 other fieldsHigh correlation
파키스탄 is highly overall correlated with 중국 and 9 other fieldsHigh correlation
중국 is highly overall correlated with 몽고리아 and 9 other fieldsHigh correlation
몽고리아 is highly overall correlated with 중국 and 9 other fieldsHigh correlation
미국 is highly overall correlated with 중국 and 9 other fieldsHigh correlation
타이 is highly overall correlated with 중국 and 9 other fieldsHigh correlation
베트남 is highly overall correlated with 중국 and 9 other fieldsHigh correlation
자유중국 is highly overall correlated with 중국 and 9 other fieldsHigh correlation
우즈베키스탄 is highly overall correlated with 중국 and 9 other fieldsHigh correlation
필리핀 is highly overall correlated with 중국 and 9 other fieldsHigh correlation
러시아 is highly overall correlated with 중국 and 9 other fieldsHigh correlation
몽고리아 is highly imbalanced (65.2%)Imbalance
미국 is highly imbalanced (50.9%)Imbalance
타이 is highly imbalanced (65.2%)Imbalance
베트남 is highly imbalanced (68.6%)Imbalance
자유중국 is highly imbalanced (64.1%)Imbalance
우즈베키스탄 is highly imbalanced (68.5%)Imbalance
필리핀 is highly imbalanced (71.2%)Imbalance
러시아 is highly imbalanced (66.1%)Imbalance
파키스탄 is highly imbalanced (73.5%)Imbalance
Unnamed: 13 has 185 (100.0%) missing valuesMissing
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 17:48:04.894598
Analysis finished2023-12-12 17:48:06.998366
Duration2.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2008년
Text

Distinct184
Distinct (%)100.0%
Missing1
Missing (%)0.5%
Memory size1.6 KiB
2023-12-13T02:48:07.175187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length10.146739
Min length4

Characters and Unicode

Total characters1867
Distinct characters243
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique184 ?
Unique (%)100.0%

Sample

1st row 절도
2nd row 장물
3rd row 사기
4th row 횡령
5th row 배임
ValueCountFrequency (%)
절도 1
 
0.5%
신용정보의이용및보호에관한법률위반 1
 
0.5%
소방기본법위반 1
 
0.5%
유해화학물질관리법위반 1
 
0.5%
소음．진동규제법위반 1
 
0.5%
수도법위반 1
 
0.5%
수산업법위반 1
 
0.5%
수산자원보호령위반 1
 
0.5%
수상레저안전법위반 1
 
0.5%
수질환경보전법위반 1
 
0.5%
Other values (174) 174
94.6%
2023-12-13T02:48:07.585900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
368
 
19.7%
위 135
 
7.2%
법 131
 
7.0%
반 126
 
6.7%
관 46
 
2.5%
한 30
 
1.6%
에 29
 
1.6%
업 24
 
1.3%
률 23
 
1.2%
보 22
 
1.2%
Other values (233) 933
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1474
79.0%
Space Separator 368
 
19.7%
Other Punctuation 9
 
0.5%
Open Punctuation 8
 
0.4%
Close Punctuation 8
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
위 135
 
9.2%
법 131
 
8.9%
반 126
 
8.5%
관 46
 
3.1%
한 30
 
2.0%
에 29
 
2.0%
업 24
 
1.6%
률 23
 
1.6%
보 22
 
1.5%
수 22
 
1.5%
Other values (228) 886
60.1%
Other Punctuation
ValueCountFrequency (%)
． 6
66.7%
. 3
33.3%
Space Separator
ValueCountFrequency (%)
368
100.0%
Open Punctuation
ValueCountFrequency (%)
（ 8
100.0%
Close Punctuation
ValueCountFrequency (%)
） 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1474
79.0%
Common 393
 
21.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
위 135
 
9.2%
법 131
 
8.9%
반 126
 
8.5%
관 46
 
3.1%
한 30
 
2.0%
에 29
 
2.0%
업 24
 
1.6%
률 23
 
1.6%
보 22
 
1.5%
수 22
 
1.5%
Other values (228) 886
60.1%
Common
ValueCountFrequency (%)
368
93.6%
（ 8
 
2.0%
） 8
 
2.0%
． 6
 
1.5%
. 3
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1474
79.0%
ASCII 371
 
19.9%
None 22
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
368
99.2%
. 3
 
0.8%
Hangul
ValueCountFrequency (%)
위 135
 
9.2%
법 131
 
8.9%
반 126
 
8.5%
관 46
 
3.1%
한 30
 
2.0%
에 29
 
2.0%
업 24
 
1.6%
률 23
 
1.6%
보 22
 
1.5%
수 22
 
1.5%
Other values (228) 886
60.1%
None
ValueCountFrequency (%)
（ 8
36.4%
） 8
36.4%
． 6
27.3%

내국인
Text

Distinct172
Distinct (%)93.5%
Missing1
Missing (%)0.5%
Memory size1.6 KiB
2023-12-13T02:48:07.930876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.4619565
Min length1

Characters and Unicode

Total characters637
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)90.2%

Sample

1st row84530
2nd row3901
3rd row256390
4th row30160
5th row7811
ValueCountFrequency (%)
7
 
3.8%
1 3
 
1.6%
14 2
 
1.1%
8 2
 
1.1%
52 2
 
1.1%
102 2
 
1.1%
197 1
 
0.5%
148 1
 
0.5%
84530 1
 
0.5%
12055 1
 
0.5%
Other values (162) 162
88.0%
2023-12-13T02:48:08.502906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 98
15.4%
2 75
11.8%
4 64
10.0%
5 64
10.0%
3 61
9.6%
7 55
8.6%
9 51
8.0%
8 50
7.8%
0 49
7.7%
6 49
7.7%
Other values (2) 21
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 616
96.7%
Space Separator 14
 
2.2%
Dash Punctuation 7
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 98
15.9%
2 75
12.2%
4 64
10.4%
5 64
10.4%
3 61
9.9%
7 55
8.9%
9 51
8.3%
8 50
8.1%
0 49
8.0%
6 49
8.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 637
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 98
15.4%
2 75
11.8%
4 64
10.0%
5 64
10.0%
3 61
9.6%
7 55
8.6%
9 51
8.0%
8 50
7.8%
0 49
7.7%
6 49
7.7%
Other values (2) 21
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 637
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 98
15.4%
2 75
11.8%
4 64
10.0%
5 64
10.0%
3 61
9.6%
7 55
8.6%
9 51
8.0%
8 50
7.8%
0 49
7.7%
6 49
7.7%
Other values (2) 21
 
3.3%

중국
Categorical

HIGH CORRELATION 

Distinct44
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
-
96 
1
17 
2
12 
4
 
9
3
 
5
Other values (39)
46 

Length

Max length4
Median length3
Mean length2.3567568
Min length1

Unique

Unique35 ?
Unique (%)18.9%

Sample

1st row405
2nd row4
3rd row1507
4th row19
5th row2

Common Values

ValueCountFrequency (%)
- 96
51.9%
1 17
 
9.2%
2 12
 
6.5%
4 9
 
4.9%
3 5
 
2.7%
6 4
 
2.2%
7 3
 
1.6%
15 2
 
1.1%
11 2
 
1.1%
45 1
 
0.5%
Other values (34) 34
 
18.4%

Length

2023-12-13T02:48:08.655281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
96
51.9%
1 17
 
9.2%
2 12
 
6.5%
4 9
 
4.9%
3 5
 
2.7%
6 4
 
2.2%
7 3
 
1.6%
15 2
 
1.1%
11 2
 
1.1%
22 1
 
0.5%
Other values (34) 34
 
18.4%

몽고리아
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct26
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
-
146 
1
 
8
2
 
4
8
 
3
7
 
2
Other values (21)
22 

Length

Max length4
Median length3
Mean length2.6918919
Min length1

Unique

Unique20 ?
Unique (%)10.8%

Sample

1st row333
2nd row15
3rd row23
4th row7
5th row -

Common Values

ValueCountFrequency (%)
- 146
78.9%
1 8
 
4.3%
2 4
 
2.2%
8 3
 
1.6%
7 2
 
1.1%
3 2
 
1.1%
14 1
 
0.5%
23 1
 
0.5%
58 1
 
0.5%
11 1
 
0.5%
Other values (16) 16
 
8.6%

Length

2023-12-13T02:48:08.794063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
146
78.9%
1 8
 
4.3%
2 4
 
2.2%
8 3
 
1.6%
7 2
 
1.1%
3 2
 
1.1%
61 1
 
0.5%
333 1
 
0.5%
17 1
 
0.5%
10 1
 
0.5%
Other values (16) 16
 
8.6%

미국
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct25
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
-
117 
1
19 
2
12 
3
 
9
8
 
3
Other values (20)
25 

Length

Max length4
Median length3
Mean length2.372973
Min length1

Unique

Unique16 ?
Unique (%)8.6%

Sample

1st row41
2nd row1
3rd row62
4th row5
5th row3

Common Values

ValueCountFrequency (%)
- 117
63.2%
1 19
 
10.3%
2 12
 
6.5%
3 9
 
4.9%
8 3
 
1.6%
4 3
 
1.6%
6 2
 
1.1%
11 2
 
1.1%
7 2
 
1.1%
9 1
 
0.5%
Other values (15) 15
 
8.1%

Length

2023-12-13T02:48:08.939779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
117
63.2%
1 19
 
10.3%
2 12
 
6.5%
3 9
 
4.9%
8 3
 
1.6%
4 3
 
1.6%
6 2
 
1.1%
11 2
 
1.1%
7 2
 
1.1%
112 1
 
0.5%
Other values (15) 15
 
8.1%

타이
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct18
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
-
145 
1
16 
3
 
5
14
 
2
4
 
2
Other values (13)
15 

Length

Max length4
Median length3
Mean length2.6540541
Min length1

Unique

Unique11 ?
Unique (%)5.9%

Sample

1st row14
2nd row -
3rd row1
4th row1
5th row -

Common Values

ValueCountFrequency (%)
- 145
78.4%
1 16
 
8.6%
3 5
 
2.7%
14 2
 
1.1%
4 2
 
1.1%
5 2
 
1.1%
2 2
 
1.1%
25 1
 
0.5%
57 1
 
0.5%
109 1
 
0.5%
Other values (8) 8
 
4.3%

Length

2023-12-13T02:48:09.096372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
145
78.4%
1 16
 
8.6%
3 5
 
2.7%
14 2
 
1.1%
4 2
 
1.1%
5 2
 
1.1%
2 2
 
1.1%
70 1
 
0.5%
12 1
 
0.5%
42 1
 
0.5%
Other values (8) 8
 
4.3%

베트남
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct19
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
-
152 
1
 
10
18
 
2
8
 
2
3
 
2
Other values (14)
17 

Length

Max length4
Median length3
Mean length2.7513514
Min length1

Unique

Unique11 ?
Unique (%)5.9%

Sample

1st row128
2nd row12
3rd row8
4th row8
5th row -

Common Values

ValueCountFrequency (%)
- 152
82.2%
1 10
 
5.4%
18 2
 
1.1%
8 2
 
1.1%
3 2
 
1.1%
16 2
 
1.1%
2 2
 
1.1%
4 2
 
1.1%
129 1
 
0.5%
13 1
 
0.5%
Other values (9) 9
 
4.9%

Length

2023-12-13T02:48:09.321376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
152
82.2%
1 10
 
5.4%
18 2
 
1.1%
8 2
 
1.1%
3 2
 
1.1%
16 2
 
1.1%
2 2
 
1.1%
4 2
 
1.1%
23 1
 
0.5%
17 1
 
0.5%
Other values (9) 9
 
4.9%

자유중국
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct17
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
-
143 
1
18 
7
 
4
6
 
4
5
 
3
Other values (12)
 
13

Length

Max length4
Median length3
Mean length2.6054054
Min length1

Unique

Unique11 ?
Unique (%)5.9%

Sample

1st row31
2nd row -
3rd row170
4th row5
5th row -

Common Values

ValueCountFrequency (%)
- 143
77.3%
1 18
 
9.7%
7 4
 
2.2%
6 4
 
2.2%
5 3
 
1.6%
2 2
 
1.1%
31 1
 
0.5%
170 1
 
0.5%
41 1
 
0.5%
38 1
 
0.5%
Other values (7) 7
 
3.8%

Length

2023-12-13T02:48:09.569229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
143
77.3%
1 18
 
9.7%
7 4
 
2.2%
6 4
 
2.2%
5 3
 
1.6%
2 2
 
1.1%
4 1
 
0.5%
3 1
 
0.5%
10 1
 
0.5%
9 1
 
0.5%
Other values (7) 7
 
3.8%

우즈베키스탄
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct15
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
-
154 
1
 
7
3
 
5
5
 
3
2
 
3
Other values (10)
 
13

Length

Max length4
Median length3
Mean length2.7189189
Min length1

Unique

Unique7 ?
Unique (%)3.8%

Sample

1st row70
2nd row5
3rd row2
4th row1
5th row -

Common Values

ValueCountFrequency (%)
- 154
83.2%
1 7
 
3.8%
3 5
 
2.7%
5 3
 
1.6%
2 3
 
1.6%
19 2
 
1.1%
6 2
 
1.1%
4 2
 
1.1%
70 1
 
0.5%
7 1
 
0.5%
Other values (5) 5
 
2.7%

Length

2023-12-13T02:48:09.741837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
154
83.2%
1 7
 
3.8%
3 5
 
2.7%
5 3
 
1.6%
2 3
 
1.6%
19 2
 
1.1%
6 2
 
1.1%
4 2
 
1.1%
70 1
 
0.5%
7 1
 
0.5%
Other values (5) 5
 
2.7%

필리핀
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct17
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
-
156 
1
 
7
3
 
6
7
 
2
2
 
2
Other values (12)
 
12

Length

Max length4
Median length3
Mean length2.7513514
Min length1

Unique

Unique12 ?
Unique (%)6.5%

Sample

1st row19
2nd row2
3rd row4
4th row1
5th row -

Common Values

ValueCountFrequency (%)
- 156
84.3%
1 7
 
3.8%
3 6
 
3.2%
7 2
 
1.1%
2 2
 
1.1%
15 1
 
0.5%
4 1
 
0.5%
10 1
 
0.5%
44 1
 
0.5%
35 1
 
0.5%
Other values (7) 7
 
3.8%

Length

2023-12-13T02:48:09.957510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
156
84.3%
1 7
 
3.8%
3 6
 
3.2%
7 2
 
1.1%
2 2
 
1.1%
13 1
 
0.5%
19 1
 
0.5%
41 1
 
0.5%
17 1
 
0.5%
33 1
 
0.5%
Other values (7) 7
 
3.8%

러시아
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct17
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
-
147 
1
15 
2
 
5
5
 
3
6
 
2
Other values (12)
 
13

Length

Max length4
Median length3
Mean length2.6486486
Min length1

Unique

Unique11 ?
Unique (%)5.9%

Sample

1st row47
2nd row1
3rd row13
4th row1
5th row -

Common Values

ValueCountFrequency (%)
- 147
79.5%
1 15
 
8.1%
2 5
 
2.7%
5 3
 
1.6%
6 2
 
1.1%
18 2
 
1.1%
10 1
 
0.5%
13 1
 
0.5%
8 1
 
0.5%
12 1
 
0.5%
Other values (7) 7
 
3.8%

Length

2023-12-13T02:48:10.157800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
147
79.5%
1 15
 
8.1%
2 5
 
2.7%
5 3
 
1.6%
6 2
 
1.1%
18 2
 
1.1%
15 1
 
0.5%
47 1
 
0.5%
3 1
 
0.5%
7 1
 
0.5%
Other values (7) 7
 
3.8%

파키스탄
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct16
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
-
160 
4
 
4
3
 
4
2
 
4
1
 
2
Other values (11)
 
11

Length

Max length4
Median length3
Mean length2.7783784
Min length1

Unique

Unique11 ?
Unique (%)5.9%

Sample

1st row4
2nd row4
3rd row9
4th row3
5th row -

Common Values

ValueCountFrequency (%)
- 160
86.5%
4 4
 
2.2%
3 4
 
2.2%
2 4
 
2.2%
1 2
 
1.1%
9 1
 
0.5%
15 1
 
0.5%
11 1
 
0.5%
22 1
 
0.5%
18 1
 
0.5%
Other values (6) 6
 
3.2%

Length

2023-12-13T02:48:10.345144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
160
86.5%
4 4
 
2.2%
3 4
 
2.2%
2 4
 
2.2%
1 2
 
1.1%
9 1
 
0.5%
15 1
 
0.5%
11 1
 
0.5%
22 1
 
0.5%
18 1
 
0.5%
Other values (6) 6
 
3.2%

기타
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
-
109 
1
20 
5
 
10
2
 
10
3
 
6
Other values (23)
30 

Length

Max length4
Median length3
Mean length2.3351351
Min length1

Unique

Unique20 ?
Unique (%)10.8%

Sample

1st row132
2nd row3
3rd row87
4th row5
5th row5

Common Values

ValueCountFrequency (%)
- 109
58.9%
1 20
 
10.8%
5 10
 
5.4%
2 10
 
5.4%
3 6
 
3.2%
4 4
 
2.2%
6 3
 
1.6%
10 3
 
1.6%
86 1
 
0.5%
14 1
 
0.5%
Other values (18) 18
 
9.7%

Length

2023-12-13T02:48:10.535113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
109
58.9%
1 20
 
10.8%
5 10
 
5.4%
2 10
 
5.4%
3 6
 
3.2%
4 4
 
2.2%
6 3
 
1.6%
10 3
 
1.6%
138 1
 
0.5%
83 1
 
0.5%
Other values (18) 18
 
9.7%

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing185
Missing (%)100.0%
Memory size1.8 KiB

Correlations

2023-12-13T02:48:10.673862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
중국몽고리아미국타이베트남자유중국우즈베키스탄필리핀러시아파키스탄기타
중국1.0000.9970.9940.9930.9950.9950.9940.9960.9910.9960.993
몽고리아0.9971.0000.9800.9720.9880.9820.9880.9890.9800.9940.989
미국0.9940.9801.0000.9780.9790.9810.9750.9850.9830.9800.984
타이0.9930.9720.9781.0000.9520.9260.9490.9640.9410.9560.981
베트남0.9950.9880.9790.9521.0000.9570.9720.9750.9450.9700.989
자유중국0.9950.9820.9810.9260.9571.0000.9520.9860.9830.9670.983
우즈베키스탄0.9940.9880.9750.9490.9720.9521.0000.9670.9500.9620.990
필리핀0.9960.9890.9850.9640.9750.9860.9671.0000.9800.9750.988
러시아0.9910.9800.9830.9410.9450.9830.9500.9801.0000.9490.983
파키스탄0.9960.9940.9800.9560.9700.9670.9620.9750.9491.0000.995
기타0.9930.9890.9840.9810.9890.9830.9900.9880.9830.9951.000
2023-12-13T02:48:10.848458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자유중국우즈베키스탄필리핀미국몽고리아러시아기타타이파키스탄중국베트남
자유중국1.0000.7430.7380.7780.8200.7170.8170.6280.7890.8590.729
우즈베키스탄0.7431.0000.8020.7920.8740.7320.8690.7250.7800.8410.814
필리핀0.7380.8021.0000.8030.8720.6940.8570.7620.8290.8610.817
미국0.7780.7920.8031.0000.7660.7940.7900.7910.8110.8240.776
몽고리아0.8200.8740.8720.7661.0000.8080.8320.7490.8960.8690.858
러시아0.7170.7320.6940.7940.8081.0000.8180.6740.7140.8110.684
기타0.8170.8690.8570.7900.8320.8181.0000.7980.9120.8060.820
타이0.6280.7250.7620.7910.7490.6740.7981.0000.7420.8250.698
파키스탄0.7890.7800.8290.8110.8960.7140.9120.7421.0000.8660.792
중국0.8590.8410.8610.8240.8690.8110.8060.8250.8661.0000.856
베트남0.7290.8140.8170.7760.8580.6840.8200.6980.7920.8561.000
2023-12-13T02:48:11.359802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
중국몽고리아미국타이베트남자유중국우즈베키스탄필리핀러시아파키스탄기타
중국1.0000.8690.8240.8250.8560.8590.8410.8610.8110.8660.806
몽고리아0.8691.0000.7660.7490.8580.8200.8740.8720.8080.8960.832
미국0.8240.7661.0000.7910.7760.7780.7920.8030.7940.8110.790
타이0.8250.7490.7911.0000.6980.6280.7250.7620.6740.7420.798
베트남0.8560.8580.7760.6981.0000.7290.8140.8170.6840.7920.820
자유중국0.8590.8200.7780.6280.7291.0000.7430.7380.7170.7890.817
우즈베키스탄0.8410.8740.7920.7250.8140.7431.0000.8020.7320.7800.869
필리핀0.8610.8720.8030.7620.8170.7380.8021.0000.6940.8290.857
러시아0.8110.8080.7940.6740.6840.7170.7320.6941.0000.7140.818
파키스탄0.8660.8960.8110.7420.7920.7890.7800.8290.7141.0000.912
기타0.8060.8320.7900.7980.8200.8170.8690.8570.8180.9121.000

Missing values

2023-12-13T02:48:06.452250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:48:06.689378image/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.
2023-12-13T02:48:06.853366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

2008년내국인중국몽고리아미국타이베트남자유중국우즈베키스탄필리핀러시아파키스탄기타Unnamed: 13
0절도845304053334114128317019474132<NA>
1장물39014151-12-52143<NA>
2사기25639015072362181702413987<NA>
3횡령30160197518511135<NA>
4배임78112-3-------5<NA>
5손괴3289716858382137728324<NA>
6살인9323911331112-5<NA>
7강도394141118216-275-6<NA>
8방화1434422-------1<NA>
9강간13210453714367336340<NA>
2008년내국인중국몽고리아미국타이베트남자유중국우즈베키스탄필리핀러시아파키스탄기타Unnamed: 13
175풍속영업의규제에관한법률위반246-----------<NA>
176하천법위반135-----------<NA>
177학교보건법위반432-----------<NA>
178항만법위반102-----------<NA>
179항만운송사업법위반190-----------<NA>
180해양오염방지법위반128-----1--2-1<NA>
181향토예비군설치법위반175593---1------<NA>
182화재보험위반------------<NA>
183기타특별법104507844101844104315734<NA>
184<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>