Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells11909
Missing cells (%)7.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory135.0 B

Variable types

Numeric7
Categorical5
Text2
Boolean1

Alerts

시군명 is highly overall correlated with 지역교육청명 and 1 other fieldsHigh correlation
지역명 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
장학금인원수(명) is highly overall correlated with 장학금금액(원) and 3 other fieldsHigh correlation
장학금금액(원) is highly overall correlated with 장학금인원수(명) and 5 other fieldsHigh correlation
학비지원인원수(명) is highly overall correlated with 장학금금액(원) and 4 other fieldsHigh correlation
학비지원금액(원) is highly overall correlated with 장학금금액(원) and 4 other fieldsHigh correlation
합계인원수(명) is highly overall correlated with 장학금인원수(명) and 5 other fieldsHigh correlation
합계금액(원) is highly overall correlated with 장학금인원수(명) and 5 other fieldsHigh correlation
지역교육청명 is highly overall correlated with 시군명 and 3 other fieldsHigh correlation
학교급명 is highly overall correlated with 지역교육청명High correlation
설립구분명 is highly overall correlated with 지역교육청명High correlation
제외여부 is highly overall correlated with 장학금인원수(명) and 5 other fieldsHigh correlation
설립구분명 is highly imbalanced (52.0%)Imbalance
제외여부 is highly imbalanced (85.9%)Imbalance
기준년도 has 914 (9.1%) missing valuesMissing
제외사유 has 9801 (98.0%) missing valuesMissing
장학금인원수(명) has 199 (2.0%) missing valuesMissing
장학금금액(원) has 199 (2.0%) missing valuesMissing
학비지원인원수(명) has 199 (2.0%) missing valuesMissing
학비지원금액(원) has 199 (2.0%) missing valuesMissing
합계인원수(명) has 199 (2.0%) missing valuesMissing
합계금액(원) has 199 (2.0%) missing valuesMissing
장학금인원수(명) has 403 (4.0%) zerosZeros
장학금금액(원) has 403 (4.0%) zerosZeros
학비지원인원수(명) has 5687 (56.9%) zerosZeros
학비지원금액(원) has 5687 (56.9%) zerosZeros
합계인원수(명) has 357 (3.6%) zerosZeros
합계금액(원) has 357 (3.6%) zerosZeros

Reproduction

Analysis started2023-12-10 21:37:23.549811
Analysis finished2023-12-10 21:37:32.038141
Duration8.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)0.1%
Missing914
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean2017.1208
Minimum2015
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:37:32.111017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12016
median2017
Q32018
95-th percentile2020
Maximum2020
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5848523
Coefficient of variation (CV)0.00078570025
Kurtosis-0.96904795
Mean2017.1208
Median Absolute Deviation (MAD)1
Skewness0.27803941
Sum18327560
Variance2.511757
MonotonicityNot monotonic
2023-12-11T06:37:32.251858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2018 1835
18.4%
2017 1808
18.1%
2015 1802
18.0%
2016 1785
17.8%
2020 940
9.4%
2019 916
9.2%
(Missing) 914
9.1%
ValueCountFrequency (%)
2015 1802
18.0%
2016 1785
17.8%
2017 1808
18.1%
2018 1835
18.4%
2019 916
9.2%
2020 940
9.4%
ValueCountFrequency (%)
2020 940
9.4%
2019 916
9.2%
2018 1835
18.4%
2017 1808
18.1%
2016 1785
17.8%
2015 1802
18.0%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원시
913 
성남시
748 
용인시
727 
고양시
706 
화성시
 
559
Other values (26)
6347 

Length

Max length4
Median length3
Mean length3.0903
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용인시
2nd row광주시
3rd row용인시
4th row포천시
5th row구리시

Common Values

ValueCountFrequency (%)
수원시 913
 
9.1%
성남시 748
 
7.5%
용인시 727
 
7.3%
고양시 706
 
7.1%
화성시 559
 
5.6%
부천시 556
 
5.6%
안산시 491
 
4.9%
남양주시 473
 
4.7%
평택시 428
 
4.3%
파주시 399
 
4.0%
Other values (21) 4000
40.0%

Length

2023-12-11T06:37:32.409452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 913
 
9.1%
성남시 748
 
7.5%
용인시 727
 
7.3%
고양시 706
 
7.1%
화성시 559
 
5.6%
부천시 556
 
5.6%
안산시 491
 
4.9%
남양주시 473
 
4.7%
평택시 428
 
4.3%
파주시 399
 
4.0%
Other values (21) 4000
40.0%

지역교육청명
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도교육청
4441 
경기도수원교육지원청
488 
경기도용인교육지원청
448 
경기도성남교육지원청
 
404
경기도화성오산교육지원청
 
399
Other values (22)
3820 

Length

Max length13
Median length12
Mean length8.5727
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도용인교육지원청
2nd row경기도광주하남교육지원청
3rd row경기도용인교육지원청
4th row경기도교육청
5th row경기도구리남양주교육지원청

Common Values

ValueCountFrequency (%)
경기도교육청 4441
44.4%
경기도수원교육지원청 488
 
4.9%
경기도용인교육지원청 448
 
4.5%
경기도성남교육지원청 404
 
4.0%
경기도화성오산교육지원청 399
 
4.0%
경기도고양교육지원청 359
 
3.6%
경기도구리남양주교육지원청 353
 
3.5%
경기도부천교육지원청 283
 
2.8%
경기도안산교육지원청 259
 
2.6%
경기도안양과천교육지원청 230
 
2.3%
Other values (17) 2336
23.4%

Length

2023-12-11T06:37:32.551018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도교육청 4441
44.4%
경기도수원교육지원청 488
 
4.9%
경기도용인교육지원청 448
 
4.5%
경기도성남교육지원청 404
 
4.0%
경기도화성오산교육지원청 399
 
4.0%
경기도고양교육지원청 359
 
3.6%
경기도구리남양주교육지원청 353
 
3.5%
경기도부천교육지원청 283
 
2.8%
경기도안산교육지원청 259
 
2.6%
경기도안양과천교육지원청 230
 
2.3%
Other values (17) 2336
23.4%

지역명
Categorical

HIGH CORRELATION 

Distinct42
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도 화성시
 
559
경기도 부천시
 
556
경기도 남양주시
 
473
경기도 성남시 분당구
 
462
경기도 평택시
 
428
Other values (37)
7522 

Length

Max length12
Median length7
Mean length8.7247
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 용인시 기흥구
2nd row경기도 광주시
3rd row경기도 용인시 처인구
4th row경기도 포천시
5th row경기도 구리시

Common Values

ValueCountFrequency (%)
경기도 화성시 559
 
5.6%
경기도 부천시 556
 
5.6%
경기도 남양주시 473
 
4.7%
경기도 성남시 분당구 462
 
4.6%
경기도 평택시 428
 
4.3%
경기도 파주시 399
 
4.0%
경기도 시흥시 337
 
3.4%
경기도 의정부시 332
 
3.3%
경기도 김포시 319
 
3.2%
경기도 용인시 기흥구 290
 
2.9%
Other values (32) 5845
58.5%

Length

2023-12-11T06:37:32.711772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 10000
41.7%
수원시 913
 
3.8%
성남시 748
 
3.1%
용인시 727
 
3.0%
고양시 706
 
2.9%
화성시 559
 
2.3%
부천시 556
 
2.3%
안산시 491
 
2.0%
남양주시 473
 
2.0%
분당구 462
 
1.9%
Other values (39) 8346
34.8%

학교명
Text

Distinct1188
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:37:32.991775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length6.0381
Min length4

Characters and Unicode

Total characters60381
Distinct characters288
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)0.1%

Sample

1st row신갈중학교
2nd row신현중학교
3rd row백암중학교
4th row영북고등학교
5th row교문중학교
ValueCountFrequency (%)
신갈중학교 11
 
0.1%
반송고등학교 11
 
0.1%
고천중학교 11
 
0.1%
마송고등학교 11
 
0.1%
예당중학교 11
 
0.1%
이동중학교 11
 
0.1%
향남고등학교 11
 
0.1%
양영디지털고등학교 11
 
0.1%
만정중학교 11
 
0.1%
이현고등학교 11
 
0.1%
Other values (1179) 9900
98.9%
2023-12-11T06:37:33.492212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 10228
16.9%
교 10169
16.8%
중 5765
 
9.5%
고 4404
 
7.3%
등 4248
 
7.0%
원 642
 
1.1%
자 618
 
1.0%
천 608
 
1.0%
양 604
 
1.0%
동 598
 
1.0%
Other values (278) 22497
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60193
99.7%
Lowercase Letter 140
 
0.2%
Uppercase Letter 38
 
0.1%
Space Separator 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 10228
17.0%
교 10169
16.9%
중 5765
 
9.6%
고 4404
 
7.3%
등 4248
 
7.1%
원 642
 
1.1%
자 618
 
1.0%
천 608
 
1.0%
양 604
 
1.0%
동 598
 
1.0%
Other values (265) 22309
37.1%
Lowercase Letter
ValueCountFrequency (%)
s 40
28.6%
e 20
14.3%
i 20
14.3%
n 20
14.3%
g 10
 
7.1%
l 10
 
7.1%
h 10
 
7.1%
u 10
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
E 10
26.3%
B 10
26.3%
T 9
23.7%
I 9
23.7%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60193
99.7%
Latin 178
 
0.3%
Common 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 10228
17.0%
교 10169
16.9%
중 5765
 
9.6%
고 4404
 
7.3%
등 4248
 
7.1%
원 642
 
1.1%
자 618
 
1.0%
천 608
 
1.0%
양 604
 
1.0%
동 598
 
1.0%
Other values (265) 22309
37.1%
Latin
ValueCountFrequency (%)
s 40
22.5%
e 20
11.2%
i 20
11.2%
n 20
11.2%
E 10
 
5.6%
g 10
 
5.6%
l 10
 
5.6%
h 10
 
5.6%
B 10
 
5.6%
u 10
 
5.6%
Other values (2) 18
10.1%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60193
99.7%
ASCII 188
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 10228
17.0%
교 10169
16.9%
중 5765
 
9.6%
고 4404
 
7.3%
등 4248
 
7.1%
원 642
 
1.1%
자 618
 
1.0%
천 608
 
1.0%
양 604
 
1.0%
동 598
 
1.0%
Other values (265) 22309
37.1%
ASCII
ValueCountFrequency (%)
s 40
21.3%
e 20
10.6%
i 20
10.6%
n 20
10.6%
E 10
 
5.3%
g 10
 
5.3%
l 10
 
5.3%
h 10
 
5.3%
10
 
5.3%
B 10
 
5.3%
Other values (3) 28
14.9%

학교급명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6396 
중학교
1977 
고등학교
1507 
특수학교
 
95
방통고
 
15

Length

Max length4
Median length4
Mean length3.7998
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row중학교
4th row고등학교
5th row중학교

Common Values

ValueCountFrequency (%)
<NA> 6396
64.0%
중학교 1977
 
19.8%
고등학교 1507
 
15.1%
특수학교 95
 
0.9%
방통고 15
 
0.1%
방통중 10
 
0.1%

Length

2023-12-11T06:37:33.658382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:37:33.762069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6396
64.0%
중학교 1977
 
19.8%
고등학교 1507
 
15.1%
특수학교 95
 
0.9%
방통고 15
 
0.1%
방통중 10
 
0.1%

설립구분명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
공립
7872 
사립
2112 
국립
 
16

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공립 7872
78.7%
사립 2112
 
21.1%
국립 16
 
0.2%

Length

2023-12-11T06:37:33.880253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:37:33.984316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공립 7872
78.7%
사립 2112
 
21.1%
국립 16
 
0.2%

제외여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9801 
True
 
199
ValueCountFrequency (%)
False 9801
98.0%
True 199
 
2.0%
2023-12-11T06:37:34.089288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

제외사유
Text

MISSING 

Distinct111
Distinct (%)55.8%
Missing9801
Missing (%)98.0%
Memory size156.2 KiB
2023-12-11T06:37:34.322150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length37
Mean length20.251256
Min length4

Characters and Unicode

Total characters4030
Distinct characters144
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)19.6%

Sample

1st row2018학년도 장학금 지급 내역 없음.
2nd row2016학년도 장학급 수혜 실적이 없음.
3rd row2018년 3월 1일 개교
4th row2016학년도 장학금 수혜 현황 없음.
5th row학교특성사제외처리
ValueCountFrequency (%)
없음 107
 
12.3%
장학금 46
 
5.3%
전년도 23
 
2.6%
해당사항 23
 
2.6%
수혜 22
 
2.5%
본교는 19
 
2.2%
2015년 18
 
2.1%
신설학교이므로 16
 
1.8%
없으므로 15
 
1.7%
신설학교로 13
 
1.5%
Other values (183) 568
65.3%
2023-12-11T06:37:34.830164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
677
 
16.8%
학 208
 
5.2%
교 182
 
4.5%
없 154
 
3.8%
음 134
 
3.3%
1 132
 
3.3%
0 119
 
3.0%
. 113
 
2.8%
년 108
 
2.7%
2 102
 
2.5%
Other values (134) 2101
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2722
67.5%
Space Separator 677
 
16.8%
Decimal Number 489
 
12.1%
Other Punctuation 131
 
3.3%
Close Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 208
 
7.6%
교 182
 
6.7%
없 154
 
5.7%
음 134
 
4.9%
년 108
 
4.0%
로 91
 
3.3%
신 77
 
2.8%
해 72
 
2.6%
금 69
 
2.5%
설 68
 
2.5%
Other values (118) 1559
57.3%
Decimal Number
ValueCountFrequency (%)
1 132
27.0%
0 119
24.3%
2 102
20.9%
5 34
 
7.0%
6 31
 
6.3%
3 26
 
5.3%
8 16
 
3.3%
7 14
 
2.9%
9 9
 
1.8%
4 6
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 113
86.3%
, 18
 
13.7%
Space Separator
ValueCountFrequency (%)
677
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2722
67.5%
Common 1308
32.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 208
 
7.6%
교 182
 
6.7%
없 154
 
5.7%
음 134
 
4.9%
년 108
 
4.0%
로 91
 
3.3%
신 77
 
2.8%
해 72
 
2.6%
금 69
 
2.5%
설 68
 
2.5%
Other values (118) 1559
57.3%
Common
ValueCountFrequency (%)
677
51.8%
1 132
 
10.1%
0 119
 
9.1%
. 113
 
8.6%
2 102
 
7.8%
5 34
 
2.6%
6 31
 
2.4%
3 26
 
2.0%
, 18
 
1.4%
8 16
 
1.2%
Other values (6) 40
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2722
67.5%
ASCII 1308
32.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
677
51.8%
1 132
 
10.1%
0 119
 
9.1%
. 113
 
8.6%
2 102
 
7.8%
5 34
 
2.6%
6 31
 
2.4%
3 26
 
2.0%
, 18
 
1.4%
8 16
 
1.2%
Other values (6) 40
 
3.1%
Hangul
ValueCountFrequency (%)
학 208
 
7.6%
교 182
 
6.7%
없 154
 
5.7%
음 134
 
4.9%
년 108
 
4.0%
로 91
 
3.3%
신 77
 
2.8%
해 72
 
2.6%
금 69
 
2.5%
설 68
 
2.5%
Other values (118) 1559
57.3%

장학금인원수(명)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct219
Distinct (%)2.2%
Missing199
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean28.702785
Minimum0
Maximum1152
Zeros403
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:37:35.017884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median15
Q333
95-th percentile81
Maximum1152
Range1152
Interquartile range (IQR)28

Descriptive statistics

Standard deviation63.249244
Coefficient of variation (CV)2.2035925
Kurtosis109.05102
Mean28.702785
Median Absolute Deviation (MAD)12
Skewness9.2166409
Sum281316
Variance4000.4669
MonotonicityNot monotonic
2023-12-11T06:37:35.212483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 673
 
6.7%
2 632
 
6.3%
0 403
 
4.0%
3 376
 
3.8%
4 352
 
3.5%
6 300
 
3.0%
5 297
 
3.0%
10 242
 
2.4%
7 236
 
2.4%
8 232
 
2.3%
Other values (209) 6058
60.6%
ValueCountFrequency (%)
0 403
4.0%
1 673
6.7%
2 632
6.3%
3 376
3.8%
4 352
3.5%
5 297
3.0%
6 300
3.0%
7 236
 
2.4%
8 232
 
2.3%
9 218
 
2.2%
ValueCountFrequency (%)
1152 1
< 0.1%
1042 2
< 0.1%
1029 1
< 0.1%
987 2
< 0.1%
954 2
< 0.1%
929 1
< 0.1%
887 2
< 0.1%
880 2
< 0.1%
794 2
< 0.1%
781 2
< 0.1%

장학금금액(원)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct3072
Distinct (%)31.3%
Missing199
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean18025360
Minimum0
Maximum1.5419523 × 109
Zeros403
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:37:35.373337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile100000
Q11300000
median5050000
Q314777040
95-th percentile54450560
Maximum1.5419523 × 109
Range1.5419523 × 109
Interquartile range (IQR)13477040

Descriptive statistics

Standard deviation71778797
Coefficient of variation (CV)3.9821007
Kurtosis192.66122
Mean18025360
Median Absolute Deviation (MAD)4550000
Skewness12.717978
Sum1.7666655 × 1011
Variance5.1521957 × 1015
MonotonicityNot monotonic
2023-12-11T06:37:35.530586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 528
 
5.3%
0 403
 
4.0%
200000 339
 
3.4%
600000 110
 
1.1%
1000000 107
 
1.1%
300000 92
 
0.9%
1200000 89
 
0.9%
400000 79
 
0.8%
700000 78
 
0.8%
500000 77
 
0.8%
Other values (3062) 7899
79.0%
(Missing) 199
 
2.0%
ValueCountFrequency (%)
0 403
4.0%
100000 528
5.3%
103800 2
 
< 0.1%
110000 2
 
< 0.1%
120000 3
 
< 0.1%
150000 24
 
0.2%
170000 1
 
< 0.1%
189050 2
 
< 0.1%
189480 1
 
< 0.1%
200000 339
3.4%
ValueCountFrequency (%)
1541952290 1
< 0.1%
1406989550 2
< 0.1%
1370321530 1
< 0.1%
1350104650 2
< 0.1%
1342897540 1
< 0.1%
1289985090 2
< 0.1%
1208070900 2
< 0.1%
1140934970 2
< 0.1%
950361570 2
< 0.1%
940309850 2
< 0.1%

학비지원인원수(명)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct636
Distinct (%)6.5%
Missing199
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean92.897459
Minimum0
Maximum1619
Zeros5687
Zeros (%)56.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:37:35.686333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3126
95-th percentile414
Maximum1619
Range1619
Interquartile range (IQR)126

Descriptive statistics

Standard deviation185.59882
Coefficient of variation (CV)1.9978891
Kurtosis14.409752
Mean92.897459
Median Absolute Deviation (MAD)0
Skewness3.4301813
Sum910488
Variance34446.921
MonotonicityNot monotonic
2023-12-11T06:37:35.876487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5687
56.9%
104 29
 
0.3%
183 28
 
0.3%
79 26
 
0.3%
66 26
 
0.3%
77 25
 
0.2%
67 25
 
0.2%
96 24
 
0.2%
163 24
 
0.2%
86 23
 
0.2%
Other values (626) 3884
38.8%
(Missing) 199
 
2.0%
ValueCountFrequency (%)
0 5687
56.9%
1 22
 
0.2%
2 14
 
0.1%
3 15
 
0.1%
4 13
 
0.1%
5 11
 
0.1%
6 6
 
0.1%
7 9
 
0.1%
8 11
 
0.1%
9 8
 
0.1%
ValueCountFrequency (%)
1619 1
 
< 0.1%
1454 2
< 0.1%
1445 1
 
< 0.1%
1421 2
< 0.1%
1355 1
 
< 0.1%
1344 2
< 0.1%
1300 2
< 0.1%
1285 3
< 0.1%
1283 1
 
< 0.1%
1282 4
< 0.1%

학비지원금액(원)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct2596
Distinct (%)26.5%
Missing199
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean1.2181884 × 108
Minimum0
Maximum2.5820785 × 109
Zeros5687
Zeros (%)56.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:37:36.107917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.6702128 × 108
95-th percentile5.0265245 × 108
Maximum2.5820785 × 109
Range2.5820785 × 109
Interquartile range (IQR)1.6702128 × 108

Descriptive statistics

Standard deviation2.4904263 × 108
Coefficient of variation (CV)2.0443688
Kurtosis18.098636
Mean1.2181884 × 108
Median Absolute Deviation (MAD)0
Skewness3.7273632
Sum1.1939464 × 1012
Variance6.2022231 × 1016
MonotonicityNot monotonic
2023-12-11T06:37:36.288461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5687
56.9%
1420440 6
 
0.1%
1667040 6
 
0.1%
305806170 6
 
0.1%
5001120 4
 
< 0.1%
524500000 4
 
< 0.1%
494232430 4
 
< 0.1%
2374080 4
 
< 0.1%
24588840 4
 
< 0.1%
449939380 4
 
< 0.1%
Other values (2586) 4072
40.7%
(Missing) 199
 
2.0%
ValueCountFrequency (%)
0 5687
56.9%
143890 1
 
< 0.1%
243970 2
 
< 0.1%
334160 1
 
< 0.1%
498000 1
 
< 0.1%
566760 2
 
< 0.1%
576250 2
 
< 0.1%
616544 2
 
< 0.1%
833520 2
 
< 0.1%
900000 1
 
< 0.1%
ValueCountFrequency (%)
2582078540 1
< 0.1%
2501740290 2
< 0.1%
2115600860 2
< 0.1%
2086400390 1
< 0.1%
2014624130 1
< 0.1%
1970037850 2
< 0.1%
1956816830 1
< 0.1%
1930639930 2
< 0.1%
1929655000 2
< 0.1%
1923733860 1
< 0.1%

합계인원수(명)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct705
Distinct (%)7.2%
Missing199
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean121.60024
Minimum0
Maximum1667
Zeros357
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:37:36.442795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median31
Q3162
95-th percentile495
Maximum1667
Range1667
Interquartile range (IQR)156

Descriptive statistics

Standard deviation208.4979
Coefficient of variation (CV)1.7146175
Kurtosis12.973707
Mean121.60024
Median Absolute Deviation (MAD)30
Skewness3.2567102
Sum1191804
Variance43471.376
MonotonicityNot monotonic
2023-12-11T06:37:36.603033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 621
 
6.2%
2 544
 
5.4%
0 357
 
3.6%
3 284
 
2.8%
4 280
 
2.8%
5 218
 
2.2%
6 205
 
2.1%
10 168
 
1.7%
7 162
 
1.6%
12 138
 
1.4%
Other values (695) 6824
68.2%
(Missing) 199
 
2.0%
ValueCountFrequency (%)
0 357
3.6%
1 621
6.2%
2 544
5.4%
3 284
2.8%
4 280
2.8%
5 218
 
2.2%
6 205
 
2.1%
7 162
 
1.6%
8 136
 
1.4%
9 116
 
1.2%
ValueCountFrequency (%)
1667 1
< 0.1%
1661 2
< 0.1%
1516 2
< 0.1%
1498 2
< 0.1%
1497 2
< 0.1%
1493 2
< 0.1%
1490 2
< 0.1%
1486 1
< 0.1%
1482 1
< 0.1%
1474 2
< 0.1%

합계금액(원)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct3421
Distinct (%)34.9%
Missing199
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean1.398442 × 108
Minimum0
Maximum2.6079467 × 109
Zeros357
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:37:37.049484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile100000
Q11500000
median6700000
Q31.9336792 × 108
95-th percentile5.8104767 × 108
Maximum2.6079467 × 109
Range2.6079467 × 109
Interquartile range (IQR)1.9186792 × 108

Descriptive statistics

Standard deviation2.7137222 × 108
Coefficient of variation (CV)1.9405326
Kurtosis15.753648
Mean1.398442 × 108
Median Absolute Deviation (MAD)6600000
Skewness3.5121817
Sum1.370613 × 1012
Variance7.3642879 × 1016
MonotonicityNot monotonic
2023-12-11T06:37:37.277397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 528
 
5.3%
0 357
 
3.6%
200000 336
 
3.4%
600000 110
 
1.1%
1000000 98
 
1.0%
300000 89
 
0.9%
1200000 81
 
0.8%
700000 78
 
0.8%
500000 76
 
0.8%
400000 76
 
0.8%
Other values (3411) 7972
79.7%
(Missing) 199
 
2.0%
ValueCountFrequency (%)
0 357
3.6%
100000 528
5.3%
110000 2
 
< 0.1%
120000 3
 
< 0.1%
150000 5
 
0.1%
170000 1
 
< 0.1%
189050 2
 
< 0.1%
189480 1
 
< 0.1%
200000 336
3.4%
210000 2
 
< 0.1%
ValueCountFrequency (%)
2607946700 1
< 0.1%
2553684130 2
< 0.1%
2299671130 2
< 0.1%
2168179540 2
< 0.1%
2110578690 1
< 0.1%
2038904770 1
< 0.1%
1984509450 2
< 0.1%
1974414640 2
< 0.1%
1965789440 2
< 0.1%
1965067010 1
< 0.1%

Interactions

2023-12-11T06:37:30.926883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:26.078758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:26.925508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:27.784037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:28.596730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:29.367955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:30.000557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:31.010582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:26.165700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:27.059719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:27.888379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:28.701438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:29.452085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:30.085631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:31.094556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:26.273129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:27.188038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:27.991776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:28.821931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:29.534880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:30.174195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:31.185203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:26.415699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:27.323414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:28.137452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:28.957148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:29.646522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:30.281835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:31.273161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:26.553596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:27.441653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:28.255262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:29.055097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:29.745721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:30.383931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:31.351093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:26.670010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:27.556117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:28.369362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:29.148702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:29.832567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:30.480074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:31.435564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:26.778601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:27.664657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:28.500149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:29.259742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:29.921476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:30.581651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:37:37.438736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명지역교육청명지역명학교급명설립구분명제외여부장학금인원수(명)장학금금액(원)학비지원인원수(명)학비지원금액(원)합계인원수(명)합계금액(원)
기준년도1.0000.0000.0000.0000.0000.0000.0000.0380.0350.1130.1260.1320.134
시군명0.0001.0000.9791.0000.1530.4050.1450.1940.2040.2610.2650.2540.257
지역교육청명0.0000.9791.0000.9820.7790.9300.0870.0420.0000.4490.4000.4980.429
지역명0.0001.0000.9821.0000.2250.5340.1780.3090.3160.3240.3450.3400.356
학교급명0.0000.1530.7790.2251.0000.3110.2180.1570.0850.4890.5700.6790.603
설립구분명0.0000.4050.9300.5340.3111.0000.0150.2170.2230.1400.1430.2100.192
제외여부0.0000.1450.0870.1780.2180.0151.000NaNNaNNaNNaNNaNNaN
장학금인원수(명)0.0380.1940.0420.3090.1570.217NaN1.0000.9330.3170.2580.7410.626
장학금금액(원)0.0350.2040.0000.3160.0850.223NaN0.9331.0000.2110.1800.5900.518
학비지원인원수(명)0.1130.2610.4490.3240.4890.140NaN0.3170.2111.0000.9320.9690.912
학비지원금액(원)0.1260.2650.4000.3450.5700.143NaN0.2580.1800.9321.0000.8980.994
합계인원수(명)0.1320.2540.4980.3400.6790.210NaN0.7410.5900.9690.8981.0000.923
합계금액(원)0.1340.2570.4290.3560.6030.192NaN0.6260.5180.9120.9940.9231.000
2023-12-11T06:37:37.630367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립구분명지역교육청명시군명학교급명제외여부지역명
설립구분명1.0000.7340.2240.2470.0250.295
지역교육청명0.7341.0000.7230.5140.0750.724
시군명0.2240.7231.0000.0720.1240.999
학교급명0.2470.5140.0721.0000.2660.105
제외여부0.0250.0750.1240.2661.0000.141
지역명0.2950.7240.9990.1050.1411.000
2023-12-11T06:37:37.804691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도장학금인원수(명)장학금금액(원)학비지원인원수(명)학비지원금액(원)합계인원수(명)합계금액(원)시군명지역교육청명지역명학교급명설립구분명제외여부
기준년도1.000-0.007-0.005-0.039-0.031-0.032-0.0220.0000.0000.0000.0000.0000.000
장학금인원수(명)-0.0071.0000.8460.4020.3970.7350.6680.0690.0150.1110.0660.1321.000
장학금금액(원)-0.0050.8461.0000.6830.6850.8580.8780.0770.0000.1190.0490.1001.000
학비지원인원수(명)-0.0390.4020.6831.0000.9850.8740.8750.0940.1790.1170.3090.0841.000
학비지원금액(원)-0.0310.3970.6850.9851.0000.8610.8880.0960.1560.1260.2720.0851.000
합계인원수(명)-0.0320.7350.8580.8740.8611.0000.9630.0920.2040.1240.3470.1281.000
합계금액(원)-0.0220.6680.8780.8750.8880.9631.0000.0930.1690.1300.2930.1161.000
시군명0.0000.0690.0770.0940.0960.0920.0931.0000.7230.9990.0720.2240.124
지역교육청명0.0000.0150.0000.1790.1560.2040.1690.7231.0000.7240.5140.7340.075
지역명0.0000.1110.1190.1170.1260.1240.1300.9990.7241.0000.1050.2950.141
학교급명0.0000.0660.0490.3090.2720.3470.2930.0720.5140.1051.0000.2470.266
설립구분명0.0000.1320.1000.0840.0850.1280.1160.2240.7340.2950.2471.0000.025
제외여부0.0001.0001.0001.0001.0001.0001.0000.1240.0750.1410.2660.0251.000

Missing values

2023-12-11T06:37:31.554102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:37:31.745335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T06:37:31.910784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

기준년도시군명지역교육청명지역명학교명학교급명설립구분명제외여부제외사유장학금인원수(명)장학금금액(원)학비지원인원수(명)학비지원금액(원)합계인원수(명)합계금액(원)
72872017용인시경기도용인교육지원청경기도 용인시 기흥구신갈중학교<NA>공립N<NA>18410000000184100000
12712020광주시경기도광주하남교육지원청경기도 광주시신현중학교<NA>공립N<NA>831000000083100000
119172015용인시경기도용인교육지원청경기도 용인시 처인구백암중학교중학교공립N<NA>16320000000163200000
100832016포천시경기도교육청경기도 포천시영북고등학교고등학교공립N<NA>188200000163120831550181129031550
82832016구리시경기도구리남양주교육지원청경기도 구리시교문중학교중학교공립N<NA>3580000003580000
62832017부천시경기도부천교육지원청경기도 부천시덕산중학교중학교공립N<NA>610000000061000000
231<NA>남양주시경기도교육청경기도 남양주시경은학교<NA>공립Y2018학년도 장학금 지급 내역 없음.<NA><NA><NA><NA><NA><NA>
22982019고양시경기도고양교육지원청경기도 고양시 덕양구고양중학교<NA>공립N<NA>61750000000617500000
78292017하남시경기도광주하남교육지원청경기도 하남시신장중학교중학교공립N<NA>26647000000266470000
27162019수원시경기도교육청경기도 수원시 권선구곡정고등학교<NA>공립N<NA>7584670097157369510104163216210
기준년도시군명지역교육청명지역명학교명학교급명설립구분명제외여부제외사유장학금인원수(명)장학금금액(원)학비지원인원수(명)학비지원금액(원)합계인원수(명)합계금액(원)
55112018포천시경기도포천교육지원청경기도 포천시삼성중학교<NA>공립N<NA>118000000011800000
84112016남양주시경기도교육청경기도 남양주시남양주공업고등학교<NA>공립N<NA>276200000739572454900766578654900
81<NA>고양시경기도고양교육지원청경기도 고양시 덕양구원당중학교<NA>공립N<NA>38644000000386440000
84792016남양주시경기도교육청경기도 남양주시심석고등학교고등학교사립N<NA>3738851500349480532840386519384340
72392017연천군경기도연천교육지원청경기도 연천군군남중학교중학교공립N<NA>25217485000252174850
102572015가평군경기도교육청경기도 가평군설악고등학교고등학교공립N<NA>7039150000521536288012254512880
55692018하남시경기도교육청경기도 하남시위례고등학교고등학교공립N<NA>21515000046648160621798160
124012015화성시경기도화성오산교육지원청경기도 화성시푸른중학교<NA>공립N<NA>945500000094550000
98192016이천시경기도이천교육지원청경기도 이천시모가중학교<NA>공립N<NA>24440000000244400000
90382016수원시경기도수원교육지원청경기도 수원시 영통구연무중학교중학교공립N<NA>1100000001100000