Overview

Dataset statistics

Number of variables15
Number of observations387
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory50.0 KiB
Average record size in memory132.3 B

Variable types

Text1
Categorical2
Numeric12

Dataset

Description- 전년도 장학금 수혜현황(대학정보공시 항목) 조사를 통해, 대학별 재원구분에 따른 교외장학금 수혜 금액 및 성격유형에 따른 교내장학금 연간 수혜금액 제공- 2020 회계연도부터 재난을 사유로 지급한 교내장학금 추가 조사
Author한국장학재단
URLhttps://www.data.go.kr/data/15038576/fileData.do

Alerts

교외장학금 소계(원) is highly overall correlated with 교외장학금 국가 and 9 other fieldsHigh correlation
교외장학금 국가 is highly overall correlated with 교외장학금 소계(원) and 9 other fieldsHigh correlation
교외장학금 지방자치단체 is highly overall correlated with 교외장학금 소계(원) and 8 other fieldsHigh correlation
교외장학금 사설및기타 is highly overall correlated with 교외장학금 소계(원) and 8 other fieldsHigh correlation
교내장학금 소계(원) is highly overall correlated with 교외장학금 소계(원) and 9 other fieldsHigh correlation
교내장학금 성적우수장학금 is highly overall correlated with 교외장학금 소계(원) and 8 other fieldsHigh correlation
교내장학금 저소득층장학금 is highly overall correlated with 교외장학금 소계(원) and 8 other fieldsHigh correlation
교내장학금 근로장학금 is highly overall correlated with 교외장학금 소계(원) and 8 other fieldsHigh correlation
교내장학금 교직원장학금 is highly overall correlated with 교외장학금 소계(원) and 4 other fieldsHigh correlation
교내장학금 기타장학금 is highly overall correlated with 교외장학금 소계(원) and 9 other fieldsHigh correlation
총계(원) is highly overall correlated with 교외장학금 소계(원) and 9 other fieldsHigh correlation
학교명 has unique valuesUnique
교외장학금 소계(원) has unique valuesUnique
교내장학금 소계(원) has unique valuesUnique
총계(원) has unique valuesUnique
교외장학금 지방자치단체 has 67 (17.3%) zerosZeros
교외장학금 사설및기타 has 11 (2.8%) zerosZeros
교내장학금 성적우수장학금 has 7 (1.8%) zerosZeros
교내장학금 저소득층장학금 has 21 (5.4%) zerosZeros
교내장학금 근로장학금 has 21 (5.4%) zerosZeros
교내장학금 재난장학금 has 325 (84.0%) zerosZeros
교내장학금 교직원장학금 has 119 (30.7%) zerosZeros
교내장학금 기타장학금 has 10 (2.6%) zerosZeros

Reproduction

Analysis started2023-12-12 07:30:42.874844
Analysis finished2023-12-12 07:31:00.586608
Duration17.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

학교명
Text

UNIQUE 

Distinct387
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T16:31:00.777454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length7.1627907
Min length5

Characters and Unicode

Total characters2772
Distinct characters193
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique387 ?
Unique (%)100.0%

Sample

1st rowICT폴리텍대학
2nd row가야대학교(김해)
3rd row가천대학교
4th row가톨릭관동대학교
5th row가톨릭꽃동네대학교
ValueCountFrequency (%)
한국폴리텍 28
 
6.0%
대학 24
 
5.1%
iv 4
 
0.9%
vi 4
 
0.9%
v 4
 
0.9%
i 4
 
0.9%
특성화대학 4
 
0.9%
vii 3
 
0.6%
iii 3
 
0.6%
ii 2
 
0.4%
Other values (387) 387
82.9%
2023-12-12T16:31:01.253789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
415
 
15.0%
405
 
14.6%
360
 
13.0%
80
 
2.9%
76
 
2.7%
69
 
2.5%
I 34
 
1.2%
32
 
1.2%
32
 
1.2%
32
 
1.2%
Other values (183) 1237
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2620
94.5%
Space Separator 80
 
2.9%
Uppercase Letter 58
 
2.1%
Open Punctuation 7
 
0.3%
Close Punctuation 7
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
415
 
15.8%
405
 
15.5%
360
 
13.7%
76
 
2.9%
69
 
2.6%
32
 
1.2%
32
 
1.2%
32
 
1.2%
30
 
1.1%
29
 
1.1%
Other values (171) 1140
43.5%
Uppercase Letter
ValueCountFrequency (%)
I 34
58.6%
V 15
25.9%
C 2
 
3.4%
E 2
 
3.4%
A 1
 
1.7%
R 1
 
1.7%
T 1
 
1.7%
W 1
 
1.7%
S 1
 
1.7%
Space Separator
ValueCountFrequency (%)
80
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2620
94.5%
Common 94
 
3.4%
Latin 58
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
415
 
15.8%
405
 
15.5%
360
 
13.7%
76
 
2.9%
69
 
2.6%
32
 
1.2%
32
 
1.2%
32
 
1.2%
30
 
1.1%
29
 
1.1%
Other values (171) 1140
43.5%
Latin
ValueCountFrequency (%)
I 34
58.6%
V 15
25.9%
C 2
 
3.4%
E 2
 
3.4%
A 1
 
1.7%
R 1
 
1.7%
T 1
 
1.7%
W 1
 
1.7%
S 1
 
1.7%
Common
ValueCountFrequency (%)
80
85.1%
( 7
 
7.4%
) 7
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2620
94.5%
ASCII 152
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
415
 
15.8%
405
 
15.5%
360
 
13.7%
76
 
2.9%
69
 
2.6%
32
 
1.2%
32
 
1.2%
32
 
1.2%
30
 
1.1%
29
 
1.1%
Other values (171) 1140
43.5%
ASCII
ValueCountFrequency (%)
80
52.6%
I 34
22.4%
V 15
 
9.9%
( 7
 
4.6%
) 7
 
4.6%
C 2
 
1.3%
E 2
 
1.3%
A 1
 
0.7%
R 1
 
0.7%
T 1
 
0.7%
Other values (2) 2
 
1.3%

설립별
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
사립
330 
국공립
57 

Length

Max length3
Median length2
Mean length2.1472868
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 330
85.3%
국공립 57
 
14.7%

Length

2023-12-12T16:31:01.405470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:31:01.543986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 330
85.3%
국공립 57
 
14.7%

지역별
Categorical

Distinct17
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
경기
64 
서울
62 
경북
38 
충남
25 
부산
24 
Other values (12)
174 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기
2nd row경남
3rd row경기
4th row강원
5th row충북

Common Values

ValueCountFrequency (%)
경기 64
16.5%
서울 62
16.0%
경북 38
9.8%
충남 25
 
6.5%
부산 24
 
6.2%
경남 23
 
5.9%
강원 21
 
5.4%
전북 21
 
5.4%
전남 19
 
4.9%
충북 19
 
4.9%
Other values (7) 71
18.3%

Length

2023-12-12T16:31:01.666018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 64
16.5%
서울 62
16.0%
경북 38
9.8%
충남 25
 
6.5%
부산 24
 
6.2%
경남 23
 
5.9%
강원 21
 
5.4%
전북 21
 
5.4%
충북 19
 
4.9%
전남 19
 
4.9%
Other values (7) 71
18.3%

교외장학금 소계(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct387
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1821597 × 1010
Minimum0
Maximum5.567901 × 1010
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T16:31:01.825469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.8802149 × 108
Q12.7076773 × 109
median8.6349422 × 109
Q31.7727619 × 1010
95-th percentile3.4586913 × 1010
Maximum5.567901 × 1010
Range5.567901 × 1010
Interquartile range (IQR)1.5019942 × 1010

Descriptive statistics

Standard deviation1.1159936 × 1010
Coefficient of variation (CV)0.9440295
Kurtosis1.8809137
Mean1.1821597 × 1010
Median Absolute Deviation (MAD)6.8019586 × 109
Skewness1.3677505
Sum4.5749579 × 1012
Variance1.2454417 × 1020
MonotonicityNot monotonic
2023-12-12T16:31:01.995176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
462312000 1
 
0.3%
12666826407 1
 
0.3%
5515813518 1
 
0.3%
1639274600 1
 
0.3%
40165646639 1
 
0.3%
11945475082 1
 
0.3%
8198426212 1
 
0.3%
2092373680 1
 
0.3%
36747077151 1
 
0.3%
18798737990 1
 
0.3%
Other values (377) 377
97.4%
ValueCountFrequency (%)
0 1
0.3%
10900000 1
0.3%
41200000 1
0.3%
50690000 1
0.3%
64265000 1
0.3%
68286000 1
0.3%
70002000 1
0.3%
71681093 1
0.3%
85584436 1
0.3%
87412000 1
0.3%
ValueCountFrequency (%)
55679010200 1
0.3%
54934540456 1
0.3%
51902509983 1
0.3%
49151842357 1
0.3%
48541449128 1
0.3%
47627319896 1
0.3%
46690615650 1
0.3%
45033696742 1
0.3%
44446198528 1
0.3%
41865701809 1
0.3%

교외장학금 국가
Real number (ℝ)

HIGH CORRELATION 

Distinct386
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1358635 × 1010
Minimum0
Maximum5.4010998 × 1010
Zeros2
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T16:31:02.154767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.1182687 × 108
Q12.6650713 × 109
median8.5750029 × 109
Q31.7183314 × 1010
95-th percentile3.2014859 × 1010
Maximum5.4010998 × 1010
Range5.4010998 × 1010
Interquartile range (IQR)1.4518243 × 1010

Descriptive statistics

Standard deviation1.0584011 × 1010
Coefficient of variation (CV)0.93180303
Kurtosis1.9920668
Mean1.1358635 × 1010
Median Absolute Deviation (MAD)6.8200948 × 109
Skewness1.3498262
Sum4.3957918 × 1012
Variance1.1202128 × 1020
MonotonicityNot monotonic
2023-12-12T16:31:02.310908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2
 
0.5%
280892000 1
 
0.3%
1498106547 1
 
0.3%
1560282600 1
 
0.3%
38033591209 1
 
0.3%
11890375082 1
 
0.3%
8170749212 1
 
0.3%
1986300680 1
 
0.3%
34434296536 1
 
0.3%
18675749920 1
 
0.3%
Other values (376) 376
97.2%
ValueCountFrequency (%)
0 2
0.5%
10900000 1
0.3%
46139000 1
0.3%
48090000 1
0.3%
62265000 1
0.3%
62902000 1
0.3%
68043093 1
0.3%
72067036 1
0.3%
81652000 1
0.3%
102178000 1
0.3%
ValueCountFrequency (%)
54010997840 1
0.3%
54009173885 1
0.3%
49768120575 1
0.3%
47759877507 1
0.3%
47365966523 1
0.3%
46910124796 1
0.3%
43310114133 1
0.3%
41995581412 1
0.3%
40502751210 1
0.3%
38729024330 1
0.3%

교외장학금 지방자치단체
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct308
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86327751
Minimum0
Maximum2.7875913 × 109
Zeros67
Zeros (%)17.3%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T16:31:02.485147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12650300
median16000000
Q385704570
95-th percentile3.7877407 × 108
Maximum2.7875913 × 109
Range2.7875913 × 109
Interquartile range (IQR)83054270

Descriptive statistics

Standard deviation2.0893961 × 108
Coefficient of variation (CV)2.4203064
Kurtosis78.209759
Mean86327751
Median Absolute Deviation (MAD)16000000
Skewness7.2759776
Sum3.340884 × 1010
Variance4.3655759 × 1016
MonotonicityNot monotonic
2023-12-12T16:31:02.686667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 67
 
17.3%
6000000 3
 
0.8%
1247000 3
 
0.8%
2000000 3
 
0.8%
3000000 3
 
0.8%
5000000 2
 
0.5%
2216000 2
 
0.5%
7000000 2
 
0.5%
1000000 2
 
0.5%
4500000 2
 
0.5%
Other values (298) 298
77.0%
ValueCountFrequency (%)
0 67
17.3%
650000 1
 
0.3%
776880 1
 
0.3%
786480 1
 
0.3%
816600 1
 
0.3%
1000000 2
 
0.5%
1050300 1
 
0.3%
1200000 1
 
0.3%
1247000 3
 
0.8%
1395000 1
 
0.3%
ValueCountFrequency (%)
2787591340 1
0.3%
1371631480 1
0.3%
1124416400 1
0.3%
1008221310 1
0.3%
892313890 1
0.3%
678645140 1
0.3%
586682350 1
0.3%
577020880 1
0.3%
568318910 1
0.3%
511149710 1
0.3%

교외장학금 사설및기타
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct371
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7663389 × 108
Minimum0
Maximum1.2208692 × 1010
Zeros11
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T16:31:02.858439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2837880
Q131848000
median94102000
Q32.8095166 × 108
95-th percentile2.0204244 × 109
Maximum1.2208692 × 1010
Range1.2208692 × 1010
Interquartile range (IQR)2.4910366 × 108

Descriptive statistics

Standard deviation9.7481235 × 108
Coefficient of variation (CV)2.5882226
Kurtosis66.964167
Mean3.7663389 × 108
Median Absolute Deviation (MAD)78502000
Skewness6.9484015
Sum1.4575731 × 1011
Variance9.5025911 × 1017
MonotonicityNot monotonic
2023-12-12T16:31:03.065775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11
 
2.8%
4000000 4
 
1.0%
54000000 2
 
0.5%
2600000 2
 
0.5%
29000000 2
 
0.5%
673407820 1
 
0.3%
52100000 1
 
0.3%
27677000 1
 
0.3%
100073000 1
 
0.3%
2117185005 1
 
0.3%
Other values (361) 361
93.3%
ValueCountFrequency (%)
0 11
2.8%
1000000 1
 
0.3%
2000000 1
 
0.3%
2100000 1
 
0.3%
2200000 1
 
0.3%
2259550 1
 
0.3%
2500000 1
 
0.3%
2600000 2
 
0.5%
2768400 1
 
0.3%
3000000 1
 
0.3%
ValueCountFrequency (%)
12208692338 1
0.3%
7762411212 1
0.3%
5171268260 1
0.3%
4349096820 1
0.3%
4031785249 1
0.3%
3575523018 1
0.3%
3541570208 1
0.3%
3000868177 1
0.3%
2976989350 1
0.3%
2942364236 1
0.3%

교내장학금 소계(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct387
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2687495 × 109
Minimum10488000
Maximum3.7266046 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T16:31:03.239592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10488000
5-th percentile1.034706 × 108
Q11.0216001 × 109
median3.0170013 × 109
Q37.243933 × 109
95-th percentile1.75098 × 1010
Maximum3.7266046 × 1010
Range3.7255558 × 1010
Interquartile range (IQR)6.222333 × 109

Descriptive statistics

Standard deviation6.2913753 × 109
Coefficient of variation (CV)1.1940927
Kurtosis5.6489295
Mean5.2687495 × 109
Median Absolute Deviation (MAD)2.4722438 × 109
Skewness2.1759462
Sum2.0390061 × 1012
Variance3.9581403 × 1019
MonotonicityNot monotonic
2023-12-12T16:31:03.392576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101728000 1
 
0.3%
3524930708 1
 
0.3%
1531786002 1
 
0.3%
635423205 1
 
0.3%
12082371998 1
 
0.3%
2284657458 1
 
0.3%
3109312178 1
 
0.3%
503072440 1
 
0.3%
20112633117 1
 
0.3%
7063425302 1
 
0.3%
Other values (377) 377
97.4%
ValueCountFrequency (%)
10488000 1
0.3%
10938000 1
0.3%
14964000 1
0.3%
16315000 1
0.3%
20750000 1
0.3%
22709000 1
0.3%
25940000 1
0.3%
32132000 1
0.3%
32940000 1
0.3%
33693580 1
0.3%
ValueCountFrequency (%)
37266046466 1
0.3%
34817485284 1
0.3%
33143002842 1
0.3%
29957444542 1
0.3%
29849494910 1
0.3%
28987606385 1
0.3%
27726101831 1
0.3%
27071668942 1
0.3%
26101845792 1
0.3%
25715286585 1
0.3%

교내장학금 성적우수장학금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct380
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4463561 × 109
Minimum0
Maximum1.7648206 × 1010
Zeros7
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T16:31:03.567219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17789900
Q11.493365 × 108
median5.187965 × 108
Q31.8362698 × 109
95-th percentile6.2411222 × 109
Maximum1.7648206 × 1010
Range1.7648206 × 1010
Interquartile range (IQR)1.6869333 × 109

Descriptive statistics

Standard deviation2.1747188 × 109
Coefficient of variation (CV)1.5035846
Kurtosis11.193113
Mean1.4463561 × 109
Median Absolute Deviation (MAD)4.543485 × 108
Skewness2.8239664
Sum5.5973979 × 1011
Variance4.7294016 × 1018
MonotonicityNot monotonic
2023-12-12T16:31:03.762797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7
 
1.8%
64448000 2
 
0.5%
33524000 1
 
0.3%
2306160900 1
 
0.3%
6150780810 1
 
0.3%
122400000 1
 
0.3%
809791000 1
 
0.3%
175625300 1
 
0.3%
5660237400 1
 
0.3%
1413391140 1
 
0.3%
Other values (370) 370
95.6%
ValueCountFrequency (%)
0 7
1.8%
1400000 1
 
0.3%
2174000 1
 
0.3%
4328000 1
 
0.3%
5400000 1
 
0.3%
5410000 1
 
0.3%
7030000 1
 
0.3%
7035000 1
 
0.3%
7652000 1
 
0.3%
8850000 1
 
0.3%
ValueCountFrequency (%)
17648206300 1
0.3%
11627885300 1
0.3%
10259596300 1
0.3%
10253048080 1
0.3%
9440796200 1
0.3%
9308987000 1
0.3%
9223085908 1
0.3%
8352595070 1
0.3%
7760643790 1
0.3%
7563398680 1
0.3%

교내장학금 저소득층장학금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct365
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2380358 × 109
Minimum0
Maximum1.5133482 × 1010
Zeros21
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T16:31:04.005891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q141591500
median3.5522607 × 108
Q31.5307807 × 109
95-th percentile5.2136685 × 109
Maximum1.5133482 × 1010
Range1.5133482 × 1010
Interquartile range (IQR)1.4891892 × 109

Descriptive statistics

Standard deviation2.1065969 × 109
Coefficient of variation (CV)1.7015638
Kurtosis12.222727
Mean1.2380358 × 109
Median Absolute Deviation (MAD)3.4868477 × 108
Skewness3.0891147
Sum4.7911985 × 1011
Variance4.4377507 × 1018
MonotonicityNot monotonic
2023-12-12T16:31:04.208179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21
 
5.4%
4864000 2
 
0.5%
52000000 2
 
0.5%
317418000 1
 
0.3%
146541600 1
 
0.3%
5261217800 1
 
0.3%
1635266370 1
 
0.3%
904744340 1
 
0.3%
2685905890 1
 
0.3%
93540000 1
 
0.3%
Other values (355) 355
91.7%
ValueCountFrequency (%)
0 21
5.4%
108000 1
 
0.3%
270000 1
 
0.3%
325000 1
 
0.3%
348000 1
 
0.3%
600000 1
 
0.3%
800000 1
 
0.3%
1000000 1
 
0.3%
1200000 1
 
0.3%
1450000 1
 
0.3%
ValueCountFrequency (%)
15133481547 1
0.3%
13324400502 1
0.3%
12307661765 1
0.3%
12167906820 1
0.3%
9598000132 1
0.3%
9434905677 1
0.3%
8743546200 1
0.3%
7994354780 1
0.3%
7670018200 1
0.3%
7065479427 1
0.3%

교내장학금 근로장학금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct367
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.200114 × 108
Minimum0
Maximum4.3542889 × 109
Zeros21
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T16:31:04.401477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q143158980
median1.3705999 × 108
Q35.2039917 × 108
95-th percentile1.7440557 × 109
Maximum4.3542889 × 109
Range4.3542889 × 109
Interquartile range (IQR)4.7724019 × 108

Descriptive statistics

Standard deviation6.4779722 × 108
Coefficient of variation (CV)1.5423325
Kurtosis10.778393
Mean4.200114 × 108
Median Absolute Deviation (MAD)1.3211204 × 108
Skewness2.9011764
Sum1.6254441 × 1011
Variance4.1964124 × 1017
MonotonicityNot monotonic
2023-12-12T16:31:04.919564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21
 
5.4%
41818802 1
 
0.3%
34064205 1
 
0.3%
638283968 1
 
0.3%
110508968 1
 
0.3%
34421938 1
 
0.3%
80991440 1
 
0.3%
3070685327 1
 
0.3%
1383134972 1
 
0.3%
93740024 1
 
0.3%
Other values (357) 357
92.2%
ValueCountFrequency (%)
0 21
5.4%
300000 1
 
0.3%
473000 1
 
0.3%
1200000 1
 
0.3%
1613692 1
 
0.3%
1619876 1
 
0.3%
2980000 1
 
0.3%
3000000 1
 
0.3%
3135468 1
 
0.3%
3154414 1
 
0.3%
ValueCountFrequency (%)
4354288864 1
0.3%
4026109794 1
0.3%
3880231891 1
0.3%
3840406241 1
0.3%
3226232940 1
0.3%
3070685327 1
0.3%
2441512395 1
0.3%
2297174270 1
0.3%
2175644086 1
0.3%
2041006638 1
0.3%

교내장학금 재난장학금
Real number (ℝ)

ZEROS 

Distinct63
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7621080.1
Minimum0
Maximum4.5040947 × 108
Zeros325
Zeros (%)84.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T16:31:05.099946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile34437960
Maximum4.5040947 × 108
Range4.5040947 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation41579156
Coefficient of variation (CV)5.4558088
Kurtosis80.950056
Mean7621080.1
Median Absolute Deviation (MAD)0
Skewness8.6126594
Sum2.949358 × 109
Variance1.7288262 × 1015
MonotonicityNot monotonic
2023-12-12T16:31:05.277682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 325
84.0%
5000000 1
 
0.3%
12425000 1
 
0.3%
19616200 1
 
0.3%
25478000 1
 
0.3%
1740200 1
 
0.3%
41000000 1
 
0.3%
81334500 1
 
0.3%
383700000 1
 
0.3%
1800000 1
 
0.3%
Other values (53) 53
 
13.7%
ValueCountFrequency (%)
0 325
84.0%
176820 1
 
0.3%
239000 1
 
0.3%
455000 1
 
0.3%
500000 1
 
0.3%
719400 1
 
0.3%
872200 1
 
0.3%
1000000 1
 
0.3%
1200000 1
 
0.3%
1260000 1
 
0.3%
ValueCountFrequency (%)
450409470 1
0.3%
433351900 1
0.3%
383700000 1
0.3%
243387400 1
0.3%
175105300 1
0.3%
101869660 1
0.3%
88327000 1
0.3%
81334500 1
0.3%
78553010 1
0.3%
65094230 1
0.3%

교내장학금 교직원장학금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct262
Distinct (%)67.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43857575
Minimum0
Maximum7.534637 × 108
Zeros119
Zeros (%)30.7%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T16:31:05.455433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median13568000
Q357189500
95-th percentile1.7991813 × 108
Maximum7.534637 × 108
Range7.534637 × 108
Interquartile range (IQR)57189500

Descriptive statistics

Standard deviation76385816
Coefficient of variation (CV)1.741679
Kurtosis25.270126
Mean43857575
Median Absolute Deviation (MAD)13568000
Skewness4.0159171
Sum1.6972882 × 1010
Variance5.8347928 × 1015
MonotonicityNot monotonic
2023-12-12T16:31:05.634749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 119
30.7%
2432000 4
 
1.0%
4864000 4
 
1.0%
6080000 2
 
0.5%
9844000 1
 
0.3%
202535200 1
 
0.3%
109761000 1
 
0.3%
55817430 1
 
0.3%
103582000 1
 
0.3%
99709000 1
 
0.3%
Other values (252) 252
65.1%
ValueCountFrequency (%)
0 119
30.7%
762750 1
 
0.3%
856200 1
 
0.3%
963000 1
 
0.3%
1000000 1
 
0.3%
1100000 1
 
0.3%
1216000 1
 
0.3%
1247000 1
 
0.3%
1258000 1
 
0.3%
1260000 1
 
0.3%
ValueCountFrequency (%)
753463700 1
0.3%
521090800 1
0.3%
419483000 1
0.3%
357129417 1
0.3%
336805800 1
0.3%
315799000 1
0.3%
294755200 1
0.3%
264523000 1
0.3%
229329000 1
0.3%
228116900 1
0.3%

교내장학금 기타장학금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct378
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1128676 × 109
Minimum0
Maximum1.643325 × 1010
Zeros10
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T16:31:05.767573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8258550
Q14.0455055 × 108
median1.3700148 × 109
Q32.9433865 × 109
95-th percentile6.8252324 × 109
Maximum1.643325 × 1010
Range1.643325 × 1010
Interquartile range (IQR)2.5388359 × 109

Descriptive statistics

Standard deviation2.4705646 × 109
Coefficient of variation (CV)1.1692946
Kurtosis8.4267786
Mean2.1128676 × 109
Median Absolute Deviation (MAD)1.0875447 × 109
Skewness2.4410121
Sum8.1767976 × 1011
Variance6.1036893 × 1018
MonotonicityNot monotonic
2023-12-12T16:31:05.939419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
2.6%
268733330 1
 
0.3%
5940432590 1
 
0.3%
2624992820 1
 
0.3%
1546619310 1
 
0.3%
2072427215 1
 
0.3%
498474296 1
 
0.3%
3015619485 1
 
0.3%
556834050 1
 
0.3%
4957050470 1
 
0.3%
Other values (368) 368
95.1%
ValueCountFrequency (%)
0 10
2.6%
1216000 1
 
0.3%
1824000 1
 
0.3%
4256000 1
 
0.3%
4328000 1
 
0.3%
5472000 1
 
0.3%
5940000 1
 
0.3%
6384000 1
 
0.3%
6593750 1
 
0.3%
7235000 1
 
0.3%
ValueCountFrequency (%)
16433250090 1
0.3%
16113787423 1
0.3%
14421228016 1
0.3%
13323271742 1
0.3%
11842199040 1
0.3%
11262940624 1
0.3%
10974191528 1
0.3%
9094094724 1
0.3%
8830573070 1
0.3%
8697218180 1
0.3%

총계(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct387
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7090346 × 1010
Minimum31650000
Maximum8.2006209 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T16:31:06.120540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31650000
5-th percentile5.469775 × 108
Q13.7938842 × 109
median1.193001 × 1010
Q32.4763434 × 1010
95-th percentile5.3440317 × 1010
Maximum8.2006209 × 1010
Range8.1974559 × 1010
Interquartile range (IQR)2.0969549 × 1010

Descriptive statistics

Standard deviation1.6923401 × 1010
Coefficient of variation (CV)0.99023161
Kurtosis2.146885
Mean1.7090346 × 1010
Median Absolute Deviation (MAD)9.596272 × 109
Skewness1.4938558
Sum6.613964 × 1012
Variance2.864015 × 1020
MonotonicityNot monotonic
2023-12-12T16:31:06.293908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
564040000 1
 
0.3%
16191757115 1
 
0.3%
7047599520 1
 
0.3%
2274697805 1
 
0.3%
52248018637 1
 
0.3%
14230132540 1
 
0.3%
11307738390 1
 
0.3%
2595446120 1
 
0.3%
56859710268 1
 
0.3%
25862163292 1
 
0.3%
Other values (377) 377
97.4%
ValueCountFrequency (%)
31650000 1
0.3%
61628000 1
0.3%
80490000 1
0.3%
83250000 1
0.3%
110121000 1
0.3%
115200000 1
0.3%
134505000 1
0.3%
137093000 1
0.3%
160312500 1
0.3%
216562580 1
0.3%
ValueCountFrequency (%)
82006209398 1
0.3%
81508100934 1
0.3%
77889667805 1
0.3%
75253688149 1
0.3%
74403643070 1
0.3%
70859107143 1
0.3%
68275484745 1
0.3%
67751051090 1
0.3%
67013384816 1
0.3%
66612070869 1
0.3%

Interactions

2023-12-12T16:30:58.845623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:43.732563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:45.396603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:46.514780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:47.737433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:48.845242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:50.133326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:51.773291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:53.148881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:54.488343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:55.877274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:57.204088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:58.948774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:43.857064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:45.490468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:46.597319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:47.823650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:48.944164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:50.255859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:51.886137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:53.238439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:54.597199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:55.967960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:57.288298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.035131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:43.963096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:45.594752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:46.688014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:47.907435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:49.038520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:50.376909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:52.007500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:53.353827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:54.710701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:56.081248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:57.370897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.163084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:44.069293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:45.695096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:46.780718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:48.007698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:49.122998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:50.489751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:52.108193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:53.462809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:54.834347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:56.216168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:57.451961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.267424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:44.187244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:45.781651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:46.919849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:48.107902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:49.211843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:50.602053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:52.206115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:53.589660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:54.974615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:56.340482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:57.534218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.384962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:44.302519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:45.879189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:47.040491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:48.205499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:49.322554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:50.724236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:52.305526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:53.704544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:55.107790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:56.468434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:57.638172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.494409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:44.724423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:45.979985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:47.147260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:48.308248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:49.425888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:50.820611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:52.468678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:53.825502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:55.223113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:56.564825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:57.759034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.606496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:44.847791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:46.074767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:47.242930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:48.399128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:49.551872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:50.938151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:52.570443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:53.966535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:55.327752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:56.680644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:57.861729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.705572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:44.949776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:46.154638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:47.337631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:48.483350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:49.660614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:51.034212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:52.683918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:54.054114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:55.431596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:56.793536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:57.971510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.808831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:45.045760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:46.235865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:47.423693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:48.556660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:49.762800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:51.138237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:52.801338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:54.148003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:55.540097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:56.901951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:58.075667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.933434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:45.189550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:46.328514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:47.557096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:48.666905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:49.882466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:51.538648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:52.916414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:54.271420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:55.648152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:57.022388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:58.237736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:31:00.095990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:45.293198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:46.433578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:47.643239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:48.755014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:49.993536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:51.652093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:53.028538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:54.387678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:55.764368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:57.109556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:58.390713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:31:06.452454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립별지역별교외장학금 소계(원)교외장학금 국가교외장학금 지방자치단체교외장학금 사설및기타교내장학금 소계(원)교내장학금 성적우수장학금교내장학금 저소득층장학금교내장학금 근로장학금교내장학금 재난장학금교내장학금 교직원장학금교내장학금 기타장학금총계(원)
설립별1.0000.0780.2370.2400.1460.0910.0000.1790.0000.2120.0000.2030.1640.237
지역별0.0781.0000.1030.0000.0870.0000.0000.1520.0000.2160.0000.0000.0000.000
교외장학금 소계(원)0.2370.1031.0000.9950.4930.6250.8690.7170.6960.6140.4150.6400.7880.963
교외장학금 국가0.2400.0000.9951.0000.4600.5640.8580.7310.7030.6300.4200.6420.8030.956
교외장학금 지방자치단체0.1460.0870.4930.4601.0000.5600.4640.3350.5450.6520.3680.5350.4150.419
교외장학금 사설및기타0.0910.0000.6250.5640.5601.0000.7500.5330.8240.7130.7630.7990.7250.692
교내장학금 소계(원)0.0000.0000.8690.8580.4640.7501.0000.8050.8060.6750.5950.6670.8830.913
교내장학금 성적우수장학금0.1790.1520.7170.7310.3350.5330.8051.0000.7280.6600.3600.6620.6500.759
교내장학금 저소득층장학금0.0000.0000.6960.7030.5450.8240.8060.7281.0000.7510.5820.7750.6920.752
교내장학금 근로장학금0.2120.2160.6140.6300.6520.7130.6750.6600.7511.0000.3790.5500.5750.643
교내장학금 재난장학금0.0000.0000.4150.4200.3680.7630.5950.3600.5820.3791.0000.5620.5880.483
교내장학금 교직원장학금0.2030.0000.6400.6420.5350.7990.6670.6620.7750.5500.5621.0000.6400.589
교내장학금 기타장학금0.1640.0000.7880.8030.4150.7250.8830.6500.6920.5750.5880.6401.0000.822
총계(원)0.2370.0000.9630.9560.4190.6920.9130.7590.7520.6430.4830.5890.8221.000
2023-12-12T16:31:06.635504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역별설립별
지역별1.0000.068
설립별0.0681.000
2023-12-12T16:31:06.774958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교외장학금 소계(원)교외장학금 국가교외장학금 지방자치단체교외장학금 사설및기타교내장학금 소계(원)교내장학금 성적우수장학금교내장학금 저소득층장학금교내장학금 근로장학금교내장학금 재난장학금교내장학금 교직원장학금교내장학금 기타장학금총계(원)설립별지역별
교외장학금 소계(원)1.0000.9990.6720.7530.9390.8630.7790.7850.3390.6090.8270.9900.1800.038
교외장학금 국가0.9991.0000.6610.7380.9360.8600.7730.7790.3390.6140.8280.9890.1820.000
교외장학금 지방자치단체0.6720.6611.0000.6850.6680.7040.6450.6500.2550.3100.5010.6800.1040.039
교외장학금 사설및기타0.7530.7380.6851.0000.7380.7790.7330.7700.2820.3680.5330.7590.0960.000
교내장학금 소계(원)0.9390.9360.6680.7381.0000.8940.7970.7810.3300.5820.8950.9740.0000.000
교내장학금 성적우수장학금0.8630.8600.7040.7790.8941.0000.8050.7930.3070.4530.6690.8870.1330.062
교내장학금 저소득층장학금0.7790.7730.6450.7330.7970.8051.0000.7530.3020.4430.5480.7930.0000.000
교내장학금 근로장학금0.7850.7790.6500.7700.7810.7930.7531.0000.3220.3520.5550.7920.2100.086
교내장학금 재난장학금0.3390.3390.2550.2820.3300.3070.3020.3221.0000.2620.2860.3360.0000.000
교내장학금 교직원장학금0.6090.6140.3100.3680.5820.4530.4430.3520.2621.0000.6440.6050.1510.000
교내장학금 기타장학금0.8270.8280.5010.5330.8950.6690.5480.5550.2860.6441.0000.8640.1240.000
총계(원)0.9900.9890.6800.7590.9740.8870.7930.7920.3360.6050.8641.0000.1790.000
설립별0.1800.1820.1040.0960.0000.1330.0000.2100.0000.1510.1240.1791.0000.068
지역별0.0380.0000.0390.0000.0000.0620.0000.0860.0000.0000.0000.0000.0681.000

Missing values

2023-12-12T16:31:00.249854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:31:00.479007image/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

학교명설립별지역별교외장학금 소계(원)교외장학금 국가교외장학금 지방자치단체교외장학금 사설및기타교내장학금 소계(원)교내장학금 성적우수장학금교내장학금 저소득층장학금교내장학금 근로장학금교내장학금 재난장학금교내장학금 교직원장학금교내장학금 기타장학금총계(원)
0ICT폴리텍대학사립경기462312000280892000018142000010172800033524000682040000000564040000
1가야대학교(김해)사립경남4752931433470119287354385604630000020340707225925489908352402701174974620142480004745360006787002155
2가천대학교사립경기40024949259385658668799755044013615319402772610183162798400007994354780144509401150000001596140001184219904067751051090
3가톨릭관동대학교사립강원1865790019217562903302430489570664507320603302606220451347904056315002365067740139239500320651349824690926254
4가톨릭꽃동네대학교사립충북1653654391157211575123306407920800059352177096244000207192000125041136033090001617356342247176161
5가톨릭대학교사립경기166033937561555316035686756476963476924973704965838850181002822671300574840354033988000242053190426340443414
6가톨릭상지대학교사립경북519795876051252937600726650001667728325217243000363340002212254602201400013700147796865687085
7감리교신학대학교사립서울2490615439222298470820500000247130731390906512230396800561570004735471206304000506940002881521951
8강남대학교사립경기15335987766151807801666390600148817000691926226422615075002934517840298030334058824000136638259022255250030
9강동대학교사립충북913499803690167871664088087077330000259796647923247050055881700047429122120000077900000168014985711732964515
학교명설립별지역별교외장학금 소계(원)교외장학금 국가교외장학금 지방자치단체교외장학금 사설및기타교내장학금 소계(원)교내장학금 성적우수장학금교내장학금 저소득층장학금교내장학금 근로장학금교내장학금 재난장학금교내장학금 교직원장학금교내장학금 기타장학금총계(원)
377협성대학교사립경기10561131301105043313011600000040800000560946288214894972392789660971314939104167015503157680096708721816170594183
378혜전대학교사립충남710749820070011909500106307250234005877512649880055792109027930640004824806013280844259447556975
379호남대학교사립광주18643218924184515097643910186015260730085858311942418907700355226070465936984074396600527136384027229050118
380호남신학대학교사립광주1858616196182145799603715820056378337025442570080000078869750002296879202422399566
381호산대학교사립경북48314229394823620939440200034000001677861696199400250017510386076275014601883106509284635
382호서대학교사립충남2896653608628201647866475156680289731540151788791214422236200341610790018736842480100771000536607977344145415207
383호원대학교사립전북1684687771916766637439388282804141200068013141411181016900982880002239465963939650135273000515884999523648191860
384홍익대학교사립서울335930606773258335696750567180959136530372660464661764820630087435462004354288864077652000644235310270859107143
385화성의과학대학교사립경기85584436720670366816400670100029748017410532800078350250914856400104653360383064610
386화신사이버대학교사립부산3511804582351080458201000000587156618017881500073586180534450003475380004098961200