Overview

Dataset statistics

Number of variables20
Number of observations401
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory69.4 KiB
Average record size in memory177.3 B

Variable types

Categorical2
Text1
Numeric17

Dataset

Description국내 체류중인 외국인에 대한 외국인 정책 수립의 기초자료로 활용되는 자료로 제공되는 항목은 대륙별, 국적별, 성별, 체류기간별 출국자수 입니다.
URLhttps://www.data.go.kr/data/3074940/fileData.do

Alerts

1일 is highly overall correlated with 2일 and 13 other fieldsHigh correlation
2일 is highly overall correlated with 1일 and 13 other fieldsHigh correlation
3일 is highly overall correlated with 1일 and 14 other fieldsHigh correlation
4일 is highly overall correlated with 1일 and 15 other fieldsHigh correlation
5일 is highly overall correlated with 1일 and 15 other fieldsHigh correlation
6_10일 is highly overall correlated with 1일 and 15 other fieldsHigh correlation
11_20일 is highly overall correlated with 1일 and 15 other fieldsHigh correlation
1개월 이하 is highly overall correlated with 1일 and 15 other fieldsHigh correlation
2개월 이하 is highly overall correlated with 1일 and 15 other fieldsHigh correlation
3개월 이하 is highly overall correlated with 1일 and 15 other fieldsHigh correlation
6개월 이하 is highly overall correlated with 1일 and 15 other fieldsHigh correlation
1년 이하 is highly overall correlated with 1일 and 15 other fieldsHigh correlation
2년 이하 is highly overall correlated with 1일 and 15 other fieldsHigh correlation
3년 이하 is highly overall correlated with 1일 and 15 other fieldsHigh correlation
5년 이하 is highly overall correlated with 1일 and 15 other fieldsHigh correlation
10년 이하 is highly overall correlated with 4일 and 12 other fieldsHigh correlation
10년 초과 is highly overall correlated with 3일 and 13 other fieldsHigh correlation
1일 has 136 (33.9%) zerosZeros
2일 has 126 (31.4%) zerosZeros
3일 has 67 (16.7%) zerosZeros
4일 has 50 (12.5%) zerosZeros
5일 has 40 (10.0%) zerosZeros
6_10일 has 20 (5.0%) zerosZeros
11_20일 has 35 (8.7%) zerosZeros
1개월 이하 has 72 (18.0%) zerosZeros
2개월 이하 has 82 (20.4%) zerosZeros
3개월 이하 has 85 (21.2%) zerosZeros
6개월 이하 has 74 (18.5%) zerosZeros
1년 이하 has 71 (17.7%) zerosZeros
2년 이하 has 99 (24.7%) zerosZeros
3년 이하 has 106 (26.4%) zerosZeros
5년 이하 has 145 (36.2%) zerosZeros
10년 이하 has 241 (60.1%) zerosZeros
10년 초과 has 321 (80.0%) zerosZeros

Reproduction

Analysis started2023-12-12 19:19:37.925604
Analysis finished2023-12-12 19:20:11.538991
Duration33.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대륙
Categorical

Distinct7
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
아프리카주
107 
유럽주
96 
아시아주
94 
남아메리카주
66 
오세아니아주
30 
Other values (2)
 
8

Length

Max length6
Median length5
Mean length4.5261845
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아프리카주 107
26.7%
유럽주 96
23.9%
아시아주 94
23.4%
남아메리카주 66
16.5%
오세아니아주 30
 
7.5%
북아메리카주 6
 
1.5%
기타 2
 
0.5%

Length

2023-12-13T04:20:11.622071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:20:11.780486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아프리카주 107
26.7%
유럽주 96
23.9%
아시아주 94
23.4%
남아메리카주 66
16.5%
오세아니아주 30
 
7.5%
북아메리카주 6
 
1.5%
기타 2
 
0.5%

국적
Text

Distinct199
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-13T04:20:12.109487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length3.9800499
Min length2

Characters and Unicode

Total characters1596
Distinct characters183
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row일본
2nd row일본
3rd row베트남
4th row베트남
5th row중국
ValueCountFrequency (%)
캐나다 3
 
0.7%
미국 3
 
0.7%
오스트레일리아 3
 
0.7%
뉴질랜드 3
 
0.7%
조지아 2
 
0.5%
리히텐슈타인 2
 
0.5%
솔로몬군도 2
 
0.5%
일본 2
 
0.5%
키리바시 2
 
0.5%
교황청 2
 
0.5%
Other values (190) 379
94.0%
2023-12-13T04:20:12.564319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
107
 
6.7%
65
 
4.1%
57
 
3.6%
48
 
3.0%
44
 
2.8%
42
 
2.6%
40
 
2.5%
31
 
1.9%
30
 
1.9%
30
 
1.9%
Other values (173) 1102
69.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1590
99.6%
Space Separator 2
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
107
 
6.7%
65
 
4.1%
57
 
3.6%
48
 
3.0%
44
 
2.8%
42
 
2.6%
40
 
2.5%
31
 
1.9%
30
 
1.9%
30
 
1.9%
Other values (170) 1096
68.9%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1590
99.6%
Common 6
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
107
 
6.7%
65
 
4.1%
57
 
3.6%
48
 
3.0%
44
 
2.8%
42
 
2.6%
40
 
2.5%
31
 
1.9%
30
 
1.9%
30
 
1.9%
Other values (170) 1096
68.9%
Common
ValueCountFrequency (%)
2
33.3%
( 2
33.3%
) 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1590
99.6%
ASCII 6
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
107
 
6.7%
65
 
4.1%
57
 
3.6%
48
 
3.0%
44
 
2.8%
42
 
2.6%
40
 
2.5%
31
 
1.9%
30
 
1.9%
30
 
1.9%
Other values (170) 1096
68.9%
ASCII
ValueCountFrequency (%)
2
33.3%
( 2
33.3%
) 2
33.3%

성별
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
남성
199 
여성
198 
제3의성
 
4

Length

Max length4
Median length2
Mean length2.0199501
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남성
2nd row여성
3rd row남성
4th row여성
5th row남성

Common Values

ValueCountFrequency (%)
남성 199
49.6%
여성 198
49.4%
제3의성 4
 
1.0%

Length

2023-12-13T04:20:12.722073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:20:12.851687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남성 199
49.6%
여성 198
49.4%
제3의성 4
 
1.0%

1일
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct123
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean341.38155
Minimum0
Maximum18964
Zeros136
Zeros (%)33.9%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:12.975906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q345
95-th percentile1041
Maximum18964
Range18964
Interquartile range (IQR)45

Descriptive statistics

Standard deviation1686.51
Coefficient of variation (CV)4.9402496
Kurtosis70.610039
Mean341.38155
Median Absolute Deviation (MAD)3
Skewness7.9334256
Sum136894
Variance2844316.1
MonotonicityNot monotonic
2023-12-13T04:20:13.145630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 136
33.9%
1 37
 
9.2%
3 17
 
4.2%
5 15
 
3.7%
4 13
 
3.2%
2 13
 
3.2%
8 7
 
1.7%
6 7
 
1.7%
10 5
 
1.2%
7 5
 
1.2%
Other values (113) 146
36.4%
ValueCountFrequency (%)
0 136
33.9%
1 37
 
9.2%
2 13
 
3.2%
3 17
 
4.2%
4 13
 
3.2%
5 15
 
3.7%
6 7
 
1.7%
7 5
 
1.2%
8 7
 
1.7%
9 2
 
0.5%
ValueCountFrequency (%)
18964 1
0.2%
16712 1
0.2%
11710 1
0.2%
11273 1
0.2%
9773 1
0.2%
6846 1
0.2%
6023 1
0.2%
5071 1
0.2%
3966 1
0.2%
3752 1
0.2%

2일
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct127
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean418.64838
Minimum0
Maximum52023
Zeros126
Zeros (%)31.4%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:13.301692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q335
95-th percentile1198
Maximum52023
Range52023
Interquartile range (IQR)35

Descriptive statistics

Standard deviation3185.4237
Coefficient of variation (CV)7.6088284
Kurtosis201.70939
Mean418.64838
Median Absolute Deviation (MAD)4
Skewness13.62504
Sum167878
Variance10146924
MonotonicityNot monotonic
2023-12-13T04:20:13.460839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 126
31.4%
1 27
 
6.7%
2 27
 
6.7%
5 15
 
3.7%
3 14
 
3.5%
4 13
 
3.2%
6 8
 
2.0%
9 7
 
1.7%
11 6
 
1.5%
8 6
 
1.5%
Other values (117) 152
37.9%
ValueCountFrequency (%)
0 126
31.4%
1 27
 
6.7%
2 27
 
6.7%
3 14
 
3.5%
4 13
 
3.2%
5 15
 
3.7%
6 8
 
2.0%
7 6
 
1.5%
8 6
 
1.5%
9 7
 
1.7%
ValueCountFrequency (%)
52023 1
0.2%
33533 1
0.2%
9600 1
0.2%
8295 1
0.2%
5487 1
0.2%
3831 1
0.2%
3551 1
0.2%
3231 1
0.2%
2959 1
0.2%
2941 1
0.2%

3일
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct140
Distinct (%)34.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean543.57357
Minimum0
Maximum44807
Zeros67
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:13.972111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q363
95-th percentile2068
Maximum44807
Range44807
Interquartile range (IQR)62

Descriptive statistics

Standard deviation2977.7879
Coefficient of variation (CV)5.4781691
Kurtosis137.11594
Mean543.57357
Median Absolute Deviation (MAD)7
Skewness10.627459
Sum217973
Variance8867220.9
MonotonicityNot monotonic
2023-12-13T04:20:14.135453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 67
 
16.7%
1 44
 
11.0%
3 28
 
7.0%
2 24
 
6.0%
5 14
 
3.5%
6 9
 
2.2%
10 9
 
2.2%
4 8
 
2.0%
16 8
 
2.0%
7 8
 
2.0%
Other values (130) 182
45.4%
ValueCountFrequency (%)
0 67
16.7%
1 44
11.0%
2 24
 
6.0%
3 28
7.0%
4 8
 
2.0%
5 14
 
3.5%
6 9
 
2.2%
7 8
 
2.0%
8 6
 
1.5%
9 5
 
1.2%
ValueCountFrequency (%)
44807 1
0.2%
25387 1
0.2%
16140 1
0.2%
13909 1
0.2%
11469 1
0.2%
10305 1
0.2%
8570 1
0.2%
6685 1
0.2%
6253 1
0.2%
5668 1
0.2%

4일
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct151
Distinct (%)37.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean476.33416
Minimum0
Maximum17261
Zeros50
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:14.283516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median10
Q372
95-th percentile2800
Maximum17261
Range17261
Interquartile range (IQR)70

Descriptive statistics

Standard deviation1815.749
Coefficient of variation (CV)3.8119226
Kurtosis36.516282
Mean476.33416
Median Absolute Deviation (MAD)10
Skewness5.63195
Sum191010
Variance3296944.3
MonotonicityNot monotonic
2023-12-13T04:20:14.432051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 50
 
12.5%
1 29
 
7.2%
2 29
 
7.2%
3 25
 
6.2%
5 20
 
5.0%
4 17
 
4.2%
11 8
 
2.0%
10 8
 
2.0%
9 7
 
1.7%
8 7
 
1.7%
Other values (141) 201
50.1%
ValueCountFrequency (%)
0 50
12.5%
1 29
7.2%
2 29
7.2%
3 25
6.2%
4 17
 
4.2%
5 20
 
5.0%
6 7
 
1.7%
7 6
 
1.5%
8 7
 
1.7%
9 7
 
1.7%
ValueCountFrequency (%)
17261 1
0.2%
14047 1
0.2%
11862 1
0.2%
11603 1
0.2%
10266 1
0.2%
7610 1
0.2%
7559 1
0.2%
7330 1
0.2%
6946 1
0.2%
6805 1
0.2%

5일
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct154
Distinct (%)38.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean362.96259
Minimum0
Maximum10597
Zeros40
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:14.635724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median14
Q374
95-th percentile2164
Maximum10597
Range10597
Interquartile range (IQR)71

Descriptive statistics

Standard deviation1281.1043
Coefficient of variation (CV)3.5295767
Kurtosis28.772561
Mean362.96259
Median Absolute Deviation (MAD)13
Skewness5.081417
Sum145548
Variance1641228.3
MonotonicityNot monotonic
2023-12-13T04:20:14.857977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 40
 
10.0%
1 25
 
6.2%
3 24
 
6.0%
2 23
 
5.7%
5 20
 
5.0%
4 15
 
3.7%
6 11
 
2.7%
14 9
 
2.2%
10 8
 
2.0%
13 8
 
2.0%
Other values (144) 218
54.4%
ValueCountFrequency (%)
0 40
10.0%
1 25
6.2%
2 23
5.7%
3 24
6.0%
4 15
 
3.7%
5 20
5.0%
6 11
 
2.7%
7 7
 
1.7%
8 5
 
1.2%
9 7
 
1.7%
ValueCountFrequency (%)
10597 1
0.2%
10336 1
0.2%
7569 1
0.2%
7564 1
0.2%
6759 1
0.2%
6628 1
0.2%
5746 1
0.2%
5570 1
0.2%
5550 1
0.2%
5161 1
0.2%

6_10일
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct216
Distinct (%)53.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1185.8454
Minimum0
Maximum51094
Zeros20
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:15.029219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median39
Q3278
95-th percentile6067
Maximum51094
Range51094
Interquartile range (IQR)271

Descriptive statistics

Standard deviation4728.5048
Coefficient of variation (CV)3.9874548
Kurtosis62.159621
Mean1185.8454
Median Absolute Deviation (MAD)38
Skewness7.3049692
Sum475524
Variance22358758
MonotonicityNot monotonic
2023-12-13T04:20:15.212620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20
 
5.0%
3 17
 
4.2%
6 15
 
3.7%
1 15
 
3.7%
7 14
 
3.5%
2 13
 
3.2%
4 11
 
2.7%
9 7
 
1.7%
10 6
 
1.5%
30 6
 
1.5%
Other values (206) 277
69.1%
ValueCountFrequency (%)
0 20
5.0%
1 15
3.7%
2 13
3.2%
3 17
4.2%
4 11
2.7%
5 2
 
0.5%
6 15
3.7%
7 14
3.5%
8 6
 
1.5%
9 7
 
1.7%
ValueCountFrequency (%)
51094 1
0.2%
44638 1
0.2%
35922 1
0.2%
35158 1
0.2%
20882 1
0.2%
16159 1
0.2%
12877 1
0.2%
11238 1
0.2%
10723 1
0.2%
10695 1
0.2%

11_20일
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct190
Distinct (%)47.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean827.95012
Minimum0
Maximum55729
Zeros35
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:15.372297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median25
Q3190
95-th percentile3988
Maximum55729
Range55729
Interquartile range (IQR)186

Descriptive statistics

Standard deviation4122.2034
Coefficient of variation (CV)4.9788064
Kurtosis141.86236
Mean827.95012
Median Absolute Deviation (MAD)24
Skewness11.234981
Sum332008
Variance16992561
MonotonicityNot monotonic
2023-12-13T04:20:15.514419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 35
 
8.7%
1 26
 
6.5%
3 22
 
5.5%
5 15
 
3.7%
2 13
 
3.2%
4 12
 
3.0%
7 8
 
2.0%
12 8
 
2.0%
31 6
 
1.5%
6 6
 
1.5%
Other values (180) 250
62.3%
ValueCountFrequency (%)
0 35
8.7%
1 26
6.5%
2 13
 
3.2%
3 22
5.5%
4 12
 
3.0%
5 15
3.7%
6 6
 
1.5%
7 8
 
2.0%
8 4
 
1.0%
9 1
 
0.2%
ValueCountFrequency (%)
55729 1
0.2%
52863 1
0.2%
14814 1
0.2%
10673 1
0.2%
8553 1
0.2%
8336 1
0.2%
7962 1
0.2%
7518 1
0.2%
7333 1
0.2%
7225 1
0.2%

1개월 이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct145
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean344.57606
Minimum0
Maximum27783
Zeros72
Zeros (%)18.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:15.694554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q371
95-th percentile1563
Maximum27783
Range27783
Interquartile range (IQR)70

Descriptive statistics

Standard deviation1937.6889
Coefficient of variation (CV)5.6233996
Kurtosis159.98317
Mean344.57606
Median Absolute Deviation (MAD)9
Skewness12.099623
Sum138175
Variance3754638.2
MonotonicityNot monotonic
2023-12-13T04:20:15.857420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 72
 
18.0%
1 43
 
10.7%
2 23
 
5.7%
3 16
 
4.0%
5 13
 
3.2%
4 10
 
2.5%
6 9
 
2.2%
11 8
 
2.0%
9 7
 
1.7%
8 7
 
1.7%
Other values (135) 193
48.1%
ValueCountFrequency (%)
0 72
18.0%
1 43
10.7%
2 23
 
5.7%
3 16
 
4.0%
4 10
 
2.5%
5 13
 
3.2%
6 9
 
2.2%
7 2
 
0.5%
8 7
 
1.7%
9 7
 
1.7%
ValueCountFrequency (%)
27783 1
0.2%
24445 1
0.2%
4586 1
0.2%
4352 1
0.2%
4298 1
0.2%
3994 1
0.2%
3110 1
0.2%
3040 1
0.2%
2941 1
0.2%
2817 1
0.2%

2개월 이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct147
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean345.3591
Minimum0
Maximum28595
Zeros82
Zeros (%)20.4%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:16.007512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q373
95-th percentile1573
Maximum28595
Range28595
Interquartile range (IQR)72

Descriptive statistics

Standard deviation2006.1952
Coefficient of variation (CV)5.8090121
Kurtosis159.53941
Mean345.3591
Median Absolute Deviation (MAD)8
Skewness12.09677
Sum138489
Variance4024819.2
MonotonicityNot monotonic
2023-12-13T04:20:16.196189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 82
20.4%
2 26
 
6.5%
1 26
 
6.5%
3 23
 
5.7%
4 14
 
3.5%
5 11
 
2.7%
7 8
 
2.0%
8 7
 
1.7%
10 7
 
1.7%
13 7
 
1.7%
Other values (137) 190
47.4%
ValueCountFrequency (%)
0 82
20.4%
1 26
 
6.5%
2 26
 
6.5%
3 23
 
5.7%
4 14
 
3.5%
5 11
 
2.7%
6 6
 
1.5%
7 8
 
2.0%
8 7
 
1.7%
9 6
 
1.5%
ValueCountFrequency (%)
28595 1
0.2%
25480 1
0.2%
5194 1
0.2%
4444 1
0.2%
4201 1
0.2%
3907 1
0.2%
3844 1
0.2%
3248 1
0.2%
3183 1
0.2%
2875 1
0.2%

3개월 이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct140
Distinct (%)34.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean247.12718
Minimum0
Maximum13309
Zeros85
Zeros (%)21.2%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:16.369028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q363
95-th percentile898
Maximum13309
Range13309
Interquartile range (IQR)62

Descriptive statistics

Standard deviation1113.5857
Coefficient of variation (CV)4.506124
Kurtosis90.129036
Mean247.12718
Median Absolute Deviation (MAD)6
Skewness8.7102545
Sum99098
Variance1240073.2
MonotonicityNot monotonic
2023-12-13T04:20:16.576534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 85
21.2%
1 37
 
9.2%
2 30
 
7.5%
3 23
 
5.7%
4 16
 
4.0%
7 9
 
2.2%
5 7
 
1.7%
13 7
 
1.7%
11 6
 
1.5%
6 6
 
1.5%
Other values (130) 175
43.6%
ValueCountFrequency (%)
0 85
21.2%
1 37
9.2%
2 30
 
7.5%
3 23
 
5.7%
4 16
 
4.0%
5 7
 
1.7%
6 6
 
1.5%
7 9
 
2.2%
8 3
 
0.7%
9 6
 
1.5%
ValueCountFrequency (%)
13309 1
0.2%
12796 1
0.2%
5524 1
0.2%
4958 1
0.2%
4762 1
0.2%
4485 1
0.2%
4386 1
0.2%
3165 1
0.2%
3161 1
0.2%
2858 1
0.2%

6개월 이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct157
Distinct (%)39.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean305.5212
Minimum0
Maximum18081
Zeros74
Zeros (%)18.5%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:16.732624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median10
Q388
95-th percentile1164
Maximum18081
Range18081
Interquartile range (IQR)87

Descriptive statistics

Standard deviation1429.4639
Coefficient of variation (CV)4.6787717
Kurtosis86.529047
Mean305.5212
Median Absolute Deviation (MAD)10
Skewness8.6674997
Sum122514
Variance2043367.1
MonotonicityNot monotonic
2023-12-13T04:20:16.919174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 74
 
18.5%
1 29
 
7.2%
3 25
 
6.2%
2 15
 
3.7%
4 14
 
3.5%
5 13
 
3.2%
7 12
 
3.0%
8 7
 
1.7%
6 7
 
1.7%
15 6
 
1.5%
Other values (147) 199
49.6%
ValueCountFrequency (%)
0 74
18.5%
1 29
 
7.2%
2 15
 
3.7%
3 25
 
6.2%
4 14
 
3.5%
5 13
 
3.2%
6 7
 
1.7%
7 12
 
3.0%
8 7
 
1.7%
9 4
 
1.0%
ValueCountFrequency (%)
18081 1
0.2%
12714 1
0.2%
11666 1
0.2%
8011 1
0.2%
6969 1
0.2%
6132 1
0.2%
4796 1
0.2%
2371 1
0.2%
2225 1
0.2%
2118 1
0.2%

1년 이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct148
Distinct (%)36.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean328.00748
Minimum0
Maximum24494
Zeros71
Zeros (%)17.7%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:17.112850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q357
95-th percentile1266
Maximum24494
Range24494
Interquartile range (IQR)56

Descriptive statistics

Standard deviation1699.8432
Coefficient of variation (CV)5.1823307
Kurtosis118.65464
Mean328.00748
Median Absolute Deviation (MAD)8
Skewness9.9469296
Sum131531
Variance2889467.1
MonotonicityNot monotonic
2023-12-13T04:20:17.276611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 71
 
17.7%
1 35
 
8.7%
3 26
 
6.5%
2 23
 
5.7%
4 13
 
3.2%
6 11
 
2.7%
8 11
 
2.7%
5 9
 
2.2%
7 9
 
2.2%
11 8
 
2.0%
Other values (138) 185
46.1%
ValueCountFrequency (%)
0 71
17.7%
1 35
8.7%
2 23
 
5.7%
3 26
 
6.5%
4 13
 
3.2%
5 9
 
2.2%
6 11
 
2.7%
7 9
 
2.2%
8 11
 
2.7%
9 4
 
1.0%
ValueCountFrequency (%)
24494 1
0.2%
12647 1
0.2%
12459 1
0.2%
10724 1
0.2%
6714 1
0.2%
5421 1
0.2%
4554 1
0.2%
3174 1
0.2%
3159 1
0.2%
3086 1
0.2%

2년 이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct116
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean185.57606
Minimum0
Maximum8917
Zeros99
Zeros (%)24.7%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:17.470350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q329
95-th percentile632
Maximum8917
Range8917
Interquartile range (IQR)28

Descriptive statistics

Standard deviation942.07863
Coefficient of variation (CV)5.0765095
Kurtosis62.691417
Mean185.57606
Median Absolute Deviation (MAD)5
Skewness7.7430109
Sum74416
Variance887512.14
MonotonicityNot monotonic
2023-12-13T04:20:17.633953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 99
24.7%
1 42
 
10.5%
2 26
 
6.5%
4 15
 
3.7%
3 15
 
3.7%
7 13
 
3.2%
5 11
 
2.7%
6 9
 
2.2%
10 8
 
2.0%
8 7
 
1.7%
Other values (106) 156
38.9%
ValueCountFrequency (%)
0 99
24.7%
1 42
10.5%
2 26
 
6.5%
3 15
 
3.7%
4 15
 
3.7%
5 11
 
2.7%
6 9
 
2.2%
7 13
 
3.2%
8 7
 
1.7%
9 6
 
1.5%
ValueCountFrequency (%)
8917 1
0.2%
8602 1
0.2%
8585 1
0.2%
7465 1
0.2%
6009 1
0.2%
5132 1
0.2%
2287 1
0.2%
1861 1
0.2%
1162 1
0.2%
1138 1
0.2%

3년 이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct112
Distinct (%)27.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean361.98254
Minimum0
Maximum21528
Zeros106
Zeros (%)26.4%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:17.815968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q323
95-th percentile1797
Maximum21528
Range21528
Interquartile range (IQR)23

Descriptive statistics

Standard deviation1771.5987
Coefficient of variation (CV)4.894155
Kurtosis80.520808
Mean361.98254
Median Absolute Deviation (MAD)4
Skewness8.3833528
Sum145155
Variance3138561.9
MonotonicityNot monotonic
2023-12-13T04:20:17.987685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 106
26.4%
1 38
 
9.5%
2 29
 
7.2%
3 19
 
4.7%
4 17
 
4.2%
9 11
 
2.7%
16 10
 
2.5%
6 9
 
2.2%
14 9
 
2.2%
8 7
 
1.7%
Other values (102) 146
36.4%
ValueCountFrequency (%)
0 106
26.4%
1 38
 
9.5%
2 29
 
7.2%
3 19
 
4.7%
4 17
 
4.2%
5 6
 
1.5%
6 9
 
2.2%
7 5
 
1.2%
8 7
 
1.7%
9 11
 
2.7%
ValueCountFrequency (%)
21528 1
0.2%
15987 1
0.2%
13783 1
0.2%
13368 1
0.2%
6268 1
0.2%
5618 1
0.2%
4239 1
0.2%
3952 1
0.2%
3891 1
0.2%
3471 1
0.2%

5년 이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct103
Distinct (%)25.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.3616
Minimum0
Maximum10437
Zeros145
Zeros (%)36.2%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:18.498602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q314
95-th percentile1358
Maximum10437
Range10437
Interquartile range (IQR)14

Descriptive statistics

Standard deviation1105.3303
Coefficient of variation (CV)4.4326403
Kurtosis44.068573
Mean249.3616
Median Absolute Deviation (MAD)2
Skewness6.3264363
Sum99994
Variance1221755
MonotonicityNot monotonic
2023-12-13T04:20:18.702704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 145
36.2%
2 36
 
9.0%
1 34
 
8.5%
3 23
 
5.7%
5 13
 
3.2%
4 8
 
2.0%
9 8
 
2.0%
7 6
 
1.5%
10 6
 
1.5%
8 5
 
1.2%
Other values (93) 117
29.2%
ValueCountFrequency (%)
0 145
36.2%
1 34
 
8.5%
2 36
 
9.0%
3 23
 
5.7%
4 8
 
2.0%
5 13
 
3.2%
6 4
 
1.0%
7 6
 
1.5%
8 5
 
1.2%
9 8
 
2.0%
ValueCountFrequency (%)
10437 1
0.2%
8581 1
0.2%
8494 1
0.2%
8082 1
0.2%
6868 1
0.2%
5265 1
0.2%
4834 1
0.2%
4355 1
0.2%
4351 1
0.2%
2970 1
0.2%

10년 이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct64
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.386534
Minimum0
Maximum1964
Zeros241
Zeros (%)60.1%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:18.866304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile233
Maximum1964
Range1964
Interquartile range (IQR)2

Descriptive statistics

Standard deviation216.50512
Coefficient of variation (CV)4.5689166
Kurtosis43.772705
Mean47.386534
Median Absolute Deviation (MAD)0
Skewness6.3664596
Sum19002
Variance46874.468
MonotonicityNot monotonic
2023-12-13T04:20:19.076606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 241
60.1%
1 45
 
11.2%
2 16
 
4.0%
10 8
 
2.0%
3 8
 
2.0%
4 6
 
1.5%
7 4
 
1.0%
5 4
 
1.0%
8 3
 
0.7%
12 3
 
0.7%
Other values (54) 63
 
15.7%
ValueCountFrequency (%)
0 241
60.1%
1 45
 
11.2%
2 16
 
4.0%
3 8
 
2.0%
4 6
 
1.5%
5 4
 
1.0%
6 2
 
0.5%
7 4
 
1.0%
8 3
 
0.7%
9 2
 
0.5%
ValueCountFrequency (%)
1964 1
0.2%
1812 1
0.2%
1587 1
0.2%
1439 1
0.2%
1415 1
0.2%
1367 1
0.2%
957 1
0.2%
771 1
0.2%
703 1
0.2%
647 1
0.2%

10년 초과
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0822943
Minimum0
Maximum739
Zeros321
Zeros (%)80.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T04:20:19.263799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile15
Maximum739
Range739
Interquartile range (IQR)0

Descriptive statistics

Standard deviation47.771547
Coefficient of variation (CV)6.7452079
Kurtosis157.69882
Mean7.0822943
Median Absolute Deviation (MAD)0
Skewness11.654724
Sum2840
Variance2282.1207
MonotonicityNot monotonic
2023-12-13T04:20:19.404146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 321
80.0%
1 28
 
7.0%
2 13
 
3.2%
4 5
 
1.2%
14 3
 
0.7%
40 2
 
0.5%
10 2
 
0.5%
3 2
 
0.5%
6 2
 
0.5%
5 1
 
0.2%
Other values (22) 22
 
5.5%
ValueCountFrequency (%)
0 321
80.0%
1 28
 
7.0%
2 13
 
3.2%
3 2
 
0.5%
4 5
 
1.2%
5 1
 
0.2%
6 2
 
0.5%
7 1
 
0.2%
8 1
 
0.2%
9 1
 
0.2%
ValueCountFrequency (%)
739 1
0.2%
442 1
0.2%
280 1
0.2%
185 1
0.2%
130 1
0.2%
113 1
0.2%
92 1
0.2%
81 1
0.2%
80 1
0.2%
77 1
0.2%

Interactions

2023-12-13T04:20:09.166788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:38.985394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:41.038512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:42.829851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:44.207525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:46.497165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:48.275254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:50.093024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:51.768169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:53.764754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:55.341233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:57.267701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:59.386055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:00.852423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:02.756632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:04.794574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:06.855704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:09.266984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:39.087576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:41.180600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:42.916646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2023-12-13T04:20:06.304766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:08.630676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:10.574291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:40.537321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:42.486579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:43.849447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:46.038437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:47.812279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:49.613695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:51.303824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:53.390966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:54.946526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:56.804232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:58.739706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:00.494632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:02.317029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:04.229971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:06.421978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:08.738817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:10.703465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:40.645614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:42.572141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:43.921300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:46.154491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:47.920874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:49.747183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:51.427583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:53.476813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:55.048904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:56.908290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:58.818695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:00.573038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:02.410056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:04.367704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:06.524794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:08.845509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:10.839279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:40.780187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:42.648392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:43.999525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:46.242344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:48.032498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:49.857938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:51.546971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:53.578926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:55.140486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:57.010120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:58.910681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:00.660746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:02.527043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:04.490643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:06.617963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:08.947427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:10.959932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:40.908410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:42.748167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:44.114913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:46.375966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:48.159583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:49.968301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:51.651689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:53.681904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:55.243468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:57.146528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:19:59.002272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:00.750780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:02.630633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:04.651720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:06.744675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:20:09.053187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:20:19.530342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대륙성별1일2일3일4일5일6_10일11_20일1개월 이하2개월 이하3개월 이하6개월 이하1년 이하2년 이하3년 이하5년 이하10년 이하10년 초과
대륙1.0000.3920.3610.1560.2360.2760.3480.4270.4870.4960.5020.4770.4510.3510.4910.4330.2180.1510.100
성별0.3921.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
1일0.3610.0001.0000.9870.8880.7990.8010.7790.8440.9740.9740.8180.9560.8970.8250.8170.7000.8020.737
2일0.1560.0000.9871.0000.9750.9010.8380.7240.5090.6740.7930.7110.8970.6300.5940.5020.3530.4530.338
3일0.2360.0000.8880.9751.0000.9300.8610.8070.4890.6990.7480.9190.8350.8860.7910.9040.7510.7650.857
4일0.2760.0000.7990.9010.9301.0000.9530.9630.6520.6700.7060.7770.7440.7450.7210.7290.7770.6220.659
5일0.3480.0000.8010.8380.8610.9531.0000.9620.7930.8120.7870.8050.7730.7810.7600.8160.8200.6250.752
6_10일0.4270.0000.7790.7240.8070.9630.9621.0000.9270.9230.9160.7860.8050.8300.7490.7830.6910.5470.497
11_20일0.4870.0000.8440.5090.4890.6520.7930.9271.0000.9330.9080.7580.9230.6920.6100.7470.3590.0000.220
1개월 이하0.4960.0000.9740.6740.6990.6700.8120.9230.9331.0000.9940.8410.9960.9130.8400.8410.6270.6360.558
2개월 이하0.5020.0000.9740.7930.7480.7060.7870.9160.9080.9941.0000.8790.9990.8880.8310.8260.5490.5310.488
3개월 이하0.4770.0000.8180.7110.9190.7770.8050.7860.7580.8410.8791.0000.8700.9220.8430.9740.8550.7080.920
6개월 이하0.4510.0000.9560.8970.8350.7440.7730.8050.9230.9960.9990.8701.0000.9530.9130.9330.8370.9410.930
1년 이하0.3510.0000.8970.6300.8860.7450.7810.8300.6920.9130.8880.9220.9531.0000.8760.9740.8700.8110.971
2년 이하0.4910.0000.8250.5940.7910.7210.7600.7490.6100.8400.8310.8430.9130.8761.0000.9280.8320.8190.872
3년 이하0.4330.0000.8170.5020.9040.7290.8160.7830.7470.8410.8260.9740.9330.9740.9281.0000.9340.8780.988
5년 이하0.2180.0000.7000.3530.7510.7770.8200.6910.3590.6270.5490.8550.8370.8700.8320.9341.0000.9530.961
10년 이하0.1510.0000.8020.4530.7650.6220.6250.5470.0000.6360.5310.7080.9410.8110.8190.8780.9531.0000.922
10년 초과0.1000.0000.7370.3380.8570.6590.7520.4970.2200.5580.4880.9200.9300.9710.8720.9880.9610.9221.000
2023-12-13T04:20:19.695859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별대륙
성별1.0000.285
대륙0.2851.000
2023-12-13T04:20:19.802790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1일2일3일4일5일6_10일11_20일1개월 이하2개월 이하3개월 이하6개월 이하1년 이하2년 이하3년 이하5년 이하10년 이하10년 초과대륙성별
1일1.0000.9060.8820.8640.8430.8620.8420.8320.8220.7740.7640.7410.6480.6510.5160.3990.4610.2020.000
2일0.9061.0000.9240.9080.8940.9040.8770.8630.8650.8330.8240.8020.7240.7150.6020.4790.4770.1070.000
3일0.8820.9241.0000.9200.9110.9280.9030.8810.8920.8570.8550.8220.7670.7300.6080.4760.5000.1420.000
4일0.8640.9080.9201.0000.9320.9510.9220.9000.8990.8720.8740.8470.7940.7660.6460.5110.5010.1480.000
5일0.8430.8940.9110.9321.0000.9480.9190.8980.8940.8750.8750.8510.8010.7750.6630.5250.5090.1910.000
6_10일0.8620.9040.9280.9510.9481.0000.9600.9330.9290.9070.9040.8700.8240.7720.6460.5230.5120.2410.000
11_20일0.8420.8770.9030.9220.9190.9601.0000.9430.9360.9130.9120.8830.8420.7830.6520.5350.5060.3550.000
1개월 이하0.8320.8630.8810.9000.8980.9330.9431.0000.9370.9220.9160.8960.8480.8070.6860.5700.5250.3630.000
2개월 이하0.8220.8650.8920.8990.8940.9290.9360.9371.0000.9430.9390.9240.8690.8340.7140.5860.5550.3670.000
3개월 이하0.7740.8330.8570.8720.8750.9070.9130.9220.9431.0000.9410.9260.8850.8420.7370.6210.5790.3080.000
6개월 이하0.7640.8240.8550.8740.8750.9040.9120.9160.9390.9411.0000.9400.9050.8660.7660.6330.5810.2610.000
1년 이하0.7410.8020.8220.8470.8510.8700.8830.8960.9240.9260.9401.0000.9190.9160.8240.6930.6090.2170.000
2년 이하0.6480.7240.7670.7940.8010.8240.8420.8480.8690.8850.9050.9191.0000.8980.8300.7320.6280.1890.000
3년 이하0.6510.7150.7300.7660.7750.7720.7830.8070.8340.8420.8660.9160.8981.0000.8980.7750.6360.2750.000
5년 이하0.5160.6020.6080.6460.6630.6460.6520.6860.7140.7370.7660.8240.8300.8981.0000.8110.6470.1160.000
10년 이하0.3990.4790.4760.5110.5250.5230.5350.5700.5860.6210.6330.6930.7320.7750.8111.0000.6900.0810.000
10년 초과0.4610.4770.5000.5010.5090.5120.5060.5250.5550.5790.5810.6090.6280.6360.6470.6901.0000.0590.000
대륙0.2020.1070.1420.1480.1910.2410.3550.3630.3670.3080.2610.2170.1890.2750.1160.0810.0591.0000.285
성별0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.2851.000

Missing values

2023-12-13T04:20:11.146890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:20:11.411958image/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

대륙국적성별1일2일3일4일5일6_10일11_20일1개월 이하2개월 이하3개월 이하6개월 이하1년 이하2년 이하3년 이하5년 이하10년 이하10년 초과
0아시아주일본남성11710335332538711603574695474809218132482858209814177631102110102
1아시아주일본여성11273520234480717261756412877522923762875316561324554228738918607615
2아시아주베트남남성507123201030552122351465423293040201743864796542151321598785811587739
3아시아주베트남여성3966194313909755935948638402443523183552469696714746521528104371439280
4아시아주중국남성230927353154245820206282833639944444476280111072485851336884941964442
5아시아주중국여성800112218501692157953604346281739074958116661245989171378380821367185
6아시아주싱가포르남성66713082940490455503515810673985813255196804740300
7아시아주싱가포르여성50079923815499756951094148141123101429231817374721400
8아시아주타이남성71829598570694651619458199544356510714681755468231452651812130
9아시아주타이여성967548716140140471059720882486012831869448517732339104634234834141577
대륙국적성별1일2일3일4일5일6_10일11_20일1개월 이하2개월 이하3개월 이하6개월 이하1년 이하2년 이하3년 이하5년 이하10년 이하10년 초과
391아프리카주세이셸여성00020701000000000
392아프리카주에리트레아남성00003000000101210
393아프리카주에리트레아여성00001000000301100
394아프리카주남수단공화국남성00001200000208000
395아프리카주지부티남성00010410000000000
396아프리카주지부티여성00011000001100000
397아프리카주상투메프린시페남성00025000000000000
398아프리카주상투메프린시페여성00001000000000000
399기타기타남성80616666551376122199221138700
400기타기타여성24173136458218108310717400