Overview

Dataset statistics

Number of variables4
Number of observations2339
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory80.1 KiB
Average record size in memory35.1 B

Variable types

Categorical1
Numeric2
Text1

Dataset

Description「재외동포의 출입국과 법적지위에 관한 법률」제2조제2호에 따라 91일 이상 체류하기 위해 지방 출입국· 외국인관서의 장에게 국내 거소신고를 한 외국국적동포 국내거소 신고자의 국적(지역)별 현황을 월별로 제공
Author법무부
URLhttps://www.data.go.kr/data/15100027/fileData.do

Reproduction

Analysis started2024-04-29 22:58:58.089867
Analysis finished2024-04-29 22:59:00.239322
Duration2.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.4 KiB
2023
1054 
2022
1012 
2024
273 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2023 1054
45.1%
2022 1012
43.3%
2024 273
 
11.7%

Length

2024-04-30T07:59:00.301254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:59:00.394511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 1054
45.1%
2022 1012
43.3%
2024 273
 
11.7%

월
Real number (ℝ)

Distinct12
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0153912
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.7 KiB
2024-04-30T07:59:00.483338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.5698724
Coefficient of variation (CV)0.5934564
Kurtosis-1.2860308
Mean6.0153912
Median Absolute Deviation (MAD)3
Skewness0.16907298
Sum14070
Variance12.743989
MonotonicityNot monotonic
2024-04-30T07:59:00.597555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 261
11.2%
2 260
11.1%
3 260
11.1%
9 175
7.5%
10 175
7.5%
11 175
7.5%
12 175
7.5%
8 174
7.4%
7 173
7.4%
6 172
7.4%
Other values (2) 339
14.5%
ValueCountFrequency (%)
1 261
11.2%
2 260
11.1%
3 260
11.1%
4 171
7.3%
5 168
7.2%
6 172
7.4%
7 173
7.4%
8 174
7.4%
9 175
7.5%
10 175
7.5%
ValueCountFrequency (%)
12 175
7.5%
11 175
7.5%
10 175
7.5%
9 175
7.5%
8 174
7.4%
7 173
7.4%
6 172
7.4%
5 168
7.2%
4 171
7.3%
3 260
11.1%

국적지역
Text

Distinct191
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size18.4 KiB
2024-04-30T07:59:00.861387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.0474562
Min length2

Characters and Unicode

Total characters9467
Distinct characters142
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row중국
2nd row미국
3rd row러시아
4th row캐나다
5th row우즈베키스탄
ValueCountFrequency (%)
우즈베키스탄 27
 
1.2%
미국 27
 
1.2%
바베이도스 27
 
1.2%
브루나이 27
 
1.2%
세인트크리스토퍼네비스 27
 
1.2%
에스와티니 27
 
1.2%
그리스 27
 
1.2%
파나마 27
 
1.2%
이스라엘 27
 
1.2%
이란 27
 
1.2%
Other values (93) 2069
88.5%
2024-04-30T07:59:01.282344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 548
 
5.8%
아 546
 
5.8%
이 365
 
3.9%
리 329
 
3.5%
국 239
 
2.5%
르 238
 
2.5%
라 215
 
2.3%
인 194
 
2.0%
도 179
 
1.9%
176
 
1.9%
Other values (132) 6438
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9291
98.1%
Control 176
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 548
 
5.9%
아 546
 
5.9%
이 365
 
3.9%
리 329
 
3.5%
국 239
 
2.6%
르 238
 
2.6%
라 215
 
2.3%
인 194
 
2.1%
도 179
 
1.9%
트 172
 
1.9%
Other values (131) 6266
67.4%
Control
ValueCountFrequency (%)
176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9291
98.1%
Common 176
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 548
 
5.9%
아 546
 
5.9%
이 365
 
3.9%
리 329
 
3.5%
국 239
 
2.6%
르 238
 
2.6%
라 215
 
2.3%
인 194
 
2.1%
도 179
 
1.9%
트 172
 
1.9%
Other values (131) 6266
67.4%
Common
ValueCountFrequency (%)
176
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9291
98.1%
ASCII 176
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 548
 
5.9%
아 546
 
5.9%
이 365
 
3.9%
리 329
 
3.5%
국 239
 
2.6%
르 238
 
2.6%
라 215
 
2.3%
인 194
 
2.1%
도 179
 
1.9%
트 172
 
1.9%
Other values (131) 6266
67.4%
ASCII
ValueCountFrequency (%)
176
100.0%

거소신고자 수
Real number (ℝ)

Distinct536
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5833.059
Minimum1
Maximum380563
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.7 KiB
2024-04-30T07:59:01.426374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median7
Q393
95-th percentile17514.8
Maximum380563
Range380562
Interquartile range (IQR)91

Descriptive statistics

Standard deviation39048.928
Coefficient of variation (CV)6.6944168
Kurtosis77.320666
Mean5833.059
Median Absolute Deviation (MAD)6
Skewness8.7888505
Sum13643525
Variance1.5248188 × 109
MonotonicityNot monotonic
2024-04-30T07:59:01.582036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 459
19.6%
2 232
 
9.9%
3 131
 
5.6%
7 121
 
5.2%
4 97
 
4.1%
8 94
 
4.0%
5 82
 
3.5%
6 58
 
2.5%
9 41
 
1.8%
18 25
 
1.1%
Other values (526) 999
42.7%
ValueCountFrequency (%)
1 459
19.6%
2 232
9.9%
3 131
 
5.6%
4 97
 
4.1%
5 82
 
3.5%
6 58
 
2.5%
7 121
 
5.2%
8 94
 
4.0%
9 41
 
1.8%
10 10
 
0.4%
ValueCountFrequency (%)
380563 1
< 0.1%
379495 1
< 0.1%
378746 1
< 0.1%
376803 1
< 0.1%
374742 1
< 0.1%
372156 1
< 0.1%
370018 1
< 0.1%
368258 1
< 0.1%
366325 1
< 0.1%
363590 1
< 0.1%

Interactions

2024-04-30T07:58:59.873299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:58:59.610449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:58:59.973485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:58:59.775252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:59:01.668538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월거소신고자 수
년1.0000.5130.000
월0.5131.0000.000
거소신고자 수0.0000.0001.000
2024-04-30T07:59:01.752794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월거소신고자 수년
월1.0000.0030.358
거소신고자 수0.0031.0000.000
년0.3580.0001.000

Missing values

2024-04-30T07:59:00.121751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:59:00.200485image/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

년월국적지역거소신고자 수
020221중국353508
120221미국42314
220221러시아25573
320221캐나다16269
420221우즈베키스탄18508
520221카자흐스탄7730
620221오스트레일리아4029
720221뉴질랜드2190
820221키르기즈1513
920221일본666
년월국적지역거소신고자 수
232920243산마리노1
233020243벨리즈1
233120243베트남1
233220243몽골1
233320243마카오1
233420243마샬군도1
233520243리투아니아1
233620243루마니아1
233720243라트비아1
233820243라오스1