Overview

Dataset statistics

Number of variables7
Number of observations160
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.8 KiB
Average record size in memory62.8 B

Variable types

Text1
Numeric6

Dataset

Description국외인적자원관리시스템을 통해 관리중인 정부초청외국인장학생의 국가연도별 현황※ 시스템에 등록된 데이터 기준으로 실제 사업부서의 보유자료와 일부 차이가 있을 수 있음
Author교육부 국립국제교육원
URLhttps://www.data.go.kr/data/15067905/fileData.do

Alerts

2018년까지 is highly overall correlated with 2019년 and 4 other fieldsHigh correlation
2019년 is highly overall correlated with 2018년까지 and 4 other fieldsHigh correlation
2020년 is highly overall correlated with 2018년까지 and 4 other fieldsHigh correlation
2021년 is highly overall correlated with 2018년까지 and 4 other fieldsHigh correlation
2022년 is highly overall correlated with 2018년까지 and 4 other fieldsHigh correlation
2023년 is highly overall correlated with 2018년까지 and 4 other fieldsHigh correlation
구분 has unique valuesUnique
2018년까지 has 2 (1.2%) zerosZeros
2019년 has 23 (14.4%) zerosZeros
2020년 has 26 (16.2%) zerosZeros
2021년 has 26 (16.2%) zerosZeros
2022년 has 29 (18.1%) zerosZeros
2023년 has 33 (20.6%) zerosZeros

Reproduction

Analysis started2023-12-12 01:03:43.325857
Analysis finished2023-12-12 01:03:47.943967
Duration4.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct160
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-12T10:03:48.326715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length3.81875
Min length2

Characters and Unicode

Total characters611
Distinct characters155
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique160 ?
Unique (%)100.0%

Sample

1st row가나
2nd row가봉
3rd row가이아나
4th row감비아
5th row과테말라
ValueCountFrequency (%)
기니 2
 
1.2%
가나 1
 
0.6%
중국 1
 
0.6%
우루과이 1
 
0.6%
우즈베키스탄 1
 
0.6%
우크라이나 1
 
0.6%
유고슬라비아 1
 
0.6%
이라크 1
 
0.6%
이란 1
 
0.6%
이스라엘 1
 
0.6%
Other values (152) 152
93.3%
2023-12-12T10:03:48.881184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 48
 
7.9%
스 28
 
4.6%
리 24
 
3.9%
르 20
 
3.3%
니 20
 
3.3%
이 19
 
3.1%
라 19
 
3.1%
비 13
 
2.1%
나 13
 
2.1%
바 12
 
2.0%
Other values (145) 395
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 607
99.3%
Space Separator 3
 
0.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 48
 
7.9%
스 28
 
4.6%
리 24
 
4.0%
르 20
 
3.3%
니 20
 
3.3%
이 19
 
3.1%
라 19
 
3.1%
비 13
 
2.1%
나 13
 
2.1%
바 12
 
2.0%
Other values (143) 391
64.4%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 607
99.3%
Common 4
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 48
 
7.9%
스 28
 
4.6%
리 24
 
4.0%
르 20
 
3.3%
니 20
 
3.3%
이 19
 
3.1%
라 19
 
3.1%
비 13
 
2.1%
나 13
 
2.1%
바 12
 
2.0%
Other values (143) 391
64.4%
Common
ValueCountFrequency (%)
3
75.0%
· 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 607
99.3%
ASCII 3
 
0.5%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 48
 
7.9%
스 28
 
4.6%
리 24
 
4.0%
르 20
 
3.3%
니 20
 
3.3%
이 19
 
3.1%
라 19
 
3.1%
비 13
 
2.1%
나 13
 
2.1%
바 12
 
2.0%
Other values (143) 391
64.4%
ASCII
ValueCountFrequency (%)
3
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

2018년까지
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct82
Distinct (%)51.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.5625
Minimum0
Maximum410
Zeros2
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T10:03:49.134608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.95
Q18.75
median23.5
Q369.5
95-th percentile210.1
Maximum410
Range410
Interquartile range (IQR)60.75

Descriptive statistics

Standard deviation76.75516
Coefficient of variation (CV)1.3814202
Kurtosis5.9415358
Mean55.5625
Median Absolute Deviation (MAD)19.5
Skewness2.3533294
Sum8890
Variance5891.3546
MonotonicityNot monotonic
2023-12-12T10:03:49.345306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 6
 
3.8%
1 6
 
3.8%
10 6
 
3.8%
3 6
 
3.8%
2 6
 
3.8%
9 5
 
3.1%
5 5
 
3.1%
14 5
 
3.1%
6 5
 
3.1%
35 4
 
2.5%
Other values (72) 106
66.2%
ValueCountFrequency (%)
0 2
 
1.2%
1 6
3.8%
2 6
3.8%
3 6
3.8%
4 2
 
1.2%
5 5
3.1%
6 5
3.1%
7 2
 
1.2%
8 6
3.8%
9 5
3.1%
ValueCountFrequency (%)
410 1
0.6%
347 2
1.2%
340 1
0.6%
303 1
0.6%
281 1
0.6%
213 1
0.6%
212 1
0.6%
210 1
0.6%
206 1
0.6%
204 1
0.6%

2019년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3375
Minimum0
Maximum38
Zeros23
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T10:03:49.508611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q36
95-th percentile21
Maximum38
Range38
Interquartile range (IQR)5

Descriptive statistics

Standard deviation7.0254591
Coefficient of variation (CV)1.3162453
Kurtosis4.0771346
Mean5.3375
Median Absolute Deviation (MAD)2
Skewness2.011055
Sum854
Variance49.357075
MonotonicityNot monotonic
2023-12-12T10:03:49.688557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 39
24.4%
0 23
14.4%
2 20
12.5%
3 14
 
8.8%
5 12
 
7.5%
4 10
 
6.2%
9 5
 
3.1%
16 4
 
2.5%
8 4
 
2.5%
18 3
 
1.9%
Other values (18) 26
16.2%
ValueCountFrequency (%)
0 23
14.4%
1 39
24.4%
2 20
12.5%
3 14
 
8.8%
4 10
 
6.2%
5 12
 
7.5%
6 3
 
1.9%
7 1
 
0.6%
8 4
 
2.5%
9 5
 
3.1%
ValueCountFrequency (%)
38 1
 
0.6%
29 2
1.2%
26 1
 
0.6%
24 1
 
0.6%
23 1
 
0.6%
22 1
 
0.6%
21 2
1.2%
20 1
 
0.6%
19 1
 
0.6%
18 3
1.9%

2020년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.2375
Minimum0
Maximum89
Zeros26
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T10:03:49.841001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q38.25
95-th percentile45.1
Maximum89
Range89
Interquartile range (IQR)7.25

Descriptive statistics

Standard deviation14.866487
Coefficient of variation (CV)1.8047328
Kurtosis10.456104
Mean8.2375
Median Absolute Deviation (MAD)2
Skewness3.0855377
Sum1318
Variance221.01242
MonotonicityNot monotonic
2023-12-12T10:03:49.981229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 35
21.9%
0 26
16.2%
3 15
9.4%
2 14
 
8.8%
4 14
 
8.8%
5 11
 
6.9%
9 5
 
3.1%
11 4
 
2.5%
10 3
 
1.9%
6 3
 
1.9%
Other values (23) 30
18.8%
ValueCountFrequency (%)
0 26
16.2%
1 35
21.9%
2 14
 
8.8%
3 15
9.4%
4 14
 
8.8%
5 11
 
6.9%
6 3
 
1.9%
8 2
 
1.2%
9 5
 
3.1%
10 3
 
1.9%
ValueCountFrequency (%)
89 1
0.6%
82 1
0.6%
56 1
0.6%
55 1
0.6%
54 1
0.6%
51 2
1.2%
47 1
0.6%
45 1
0.6%
42 1
0.6%
39 1
0.6%

2021년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.44375
Minimum0
Maximum101
Zeros26
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T10:03:50.141473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q38
95-th percentile46
Maximum101
Range101
Interquartile range (IQR)7

Descriptive statistics

Standard deviation15.314624
Coefficient of variation (CV)1.813723
Kurtosis12.314598
Mean8.44375
Median Absolute Deviation (MAD)2
Skewness3.2776789
Sum1351
Variance234.5377
MonotonicityNot monotonic
2023-12-12T10:03:50.286937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 29
18.1%
0 26
16.2%
2 22
13.8%
5 11
 
6.9%
4 11
 
6.9%
3 9
 
5.6%
6 6
 
3.8%
8 5
 
3.1%
11 4
 
2.5%
7 4
 
2.5%
Other values (22) 33
20.6%
ValueCountFrequency (%)
0 26
16.2%
1 29
18.1%
2 22
13.8%
3 9
 
5.6%
4 11
 
6.9%
5 11
 
6.9%
6 6
 
3.8%
7 4
 
2.5%
8 5
 
3.1%
9 3
 
1.9%
ValueCountFrequency (%)
101 1
0.6%
78 1
0.6%
63 1
0.6%
57 1
0.6%
51 1
0.6%
50 1
0.6%
49 1
0.6%
46 2
1.2%
45 1
0.6%
42 2
1.2%

2022년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.8125
Minimum0
Maximum111
Zeros29
Zeros (%)18.1%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T10:03:50.433746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q38
95-th percentile48.05
Maximum111
Range111
Interquartile range (IQR)7

Descriptive statistics

Standard deviation16.940216
Coefficient of variation (CV)1.922294
Kurtosis12.085219
Mean8.8125
Median Absolute Deviation (MAD)2
Skewness3.2760793
Sum1410
Variance286.97091
MonotonicityNot monotonic
2023-12-12T10:03:50.577256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 29
18.1%
1 28
17.5%
2 27
16.9%
4 11
 
6.9%
3 11
 
6.9%
7 6
 
3.8%
5 5
 
3.1%
8 5
 
3.1%
18 3
 
1.9%
9 3
 
1.9%
Other values (24) 32
20.0%
ValueCountFrequency (%)
0 29
18.1%
1 28
17.5%
2 27
16.9%
3 11
 
6.9%
4 11
 
6.9%
5 5
 
3.1%
6 2
 
1.2%
7 6
 
3.8%
8 5
 
3.1%
9 3
 
1.9%
ValueCountFrequency (%)
111 1
0.6%
78 1
0.6%
70 2
1.2%
64 1
0.6%
60 1
0.6%
53 1
0.6%
49 1
0.6%
48 1
0.6%
45 2
1.2%
43 1
0.6%

2023년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3375
Minimum0
Maximum121
Zeros33
Zeros (%)20.6%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T10:03:50.748296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q37
95-th percentile46
Maximum121
Range121
Interquartile range (IQR)6

Descriptive statistics

Standard deviation17.102314
Coefficient of variation (CV)2.0512521
Kurtosis16.135406
Mean8.3375
Median Absolute Deviation (MAD)2
Skewness3.6925076
Sum1334
Variance292.48915
MonotonicityNot monotonic
2023-12-12T10:03:50.919161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 33
20.6%
1 32
20.0%
2 24
15.0%
3 10
 
6.2%
4 9
 
5.6%
5 6
 
3.8%
9 5
 
3.1%
7 4
 
2.5%
13 3
 
1.9%
6 3
 
1.9%
Other values (22) 31
19.4%
ValueCountFrequency (%)
0 33
20.6%
1 32
20.0%
2 24
15.0%
3 10
 
6.2%
4 9
 
5.6%
5 6
 
3.8%
6 3
 
1.9%
7 4
 
2.5%
8 2
 
1.2%
9 5
 
3.1%
ValueCountFrequency (%)
121 1
 
0.6%
85 1
 
0.6%
71 1
 
0.6%
70 1
 
0.6%
67 1
 
0.6%
51 1
 
0.6%
49 1
 
0.6%
46 3
1.9%
34 1
 
0.6%
33 2
1.2%

Interactions

2023-12-12T10:03:46.735810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:43.612875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:44.254462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:44.907811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:45.497703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:46.153253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:46.816261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:43.699403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:44.359711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:44.985083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:45.608028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:46.251132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:46.926669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:43.827865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:44.466414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:45.095291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:45.733252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:46.363941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:47.006999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:43.946767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:44.567802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:45.189814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:45.835931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:46.456167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:47.095864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:44.050668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:44.689341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:45.292860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:45.943558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:46.554021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:47.509877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:44.159158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:44.804054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:45.399659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:46.047331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:46.646102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:03:51.024559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2018년까지2019년2020년2021년2022년2023년
2018년까지1.0000.8480.8570.8980.8630.855
2019년0.8481.0000.8390.9540.9610.820
2020년0.8570.8391.0000.9130.8620.930
2021년0.8980.9540.9131.0000.9800.875
2022년0.8630.9610.8620.9801.0000.913
2023년0.8550.8200.9300.8750.9131.000
2023-12-12T10:03:51.137374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2018년까지2019년2020년2021년2022년2023년
2018년까지1.0000.9210.9010.8810.8660.856
2019년0.9211.0000.9470.9360.9100.884
2020년0.9010.9471.0000.9520.9290.906
2021년0.8810.9360.9521.0000.9330.902
2022년0.8660.9100.9290.9331.0000.920
2023년0.8560.8840.9060.9020.9201.000

Missing values

2023-12-12T10:03:47.689440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:03:47.863722image/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

구분2018년까지2019년2020년2021년2022년2023년
0가나110131313137
1가봉5334322
2가이아나101010
3감비아911021
4과테말라4023233
5그리스1622222
6기니2000000
7기니비사우400000
8나미비아200000
9나이지리아901615161816
구분2018년까지2019년2020년2021년2022년2023년
150팔레스타인511122
151페루749101088
152포르투갈1011111
153폴란드7855544
154프랑스7455552
155피지823320
156핀란드2033322
157필리핀1711645465351
158헝가리5343543
159홍콩912322