Overview

Dataset statistics

Number of variables20
Number of observations27
Missing cells86
Missing cells (%)15.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory171.9 B

Variable types

Numeric1
Text5
Categorical7
Unsupported2
Boolean3
DateTime2

Dataset

Description한국사학진흥재단에서 사학진흥기금통계연보발행에 대한 통계 관련 항목을 공개하고자 생성된 공개데이터 자료입니다.
Author한국사학진흥재단
URLhttps://www.data.go.kr/data/15042304/fileData.do

Alerts

리포트파일위치 has constant value ""Constant
등록자 has constant value ""Constant
등록일자 has constant value ""Constant
수정자 has constant value ""Constant
수정일자 has constant value ""Constant
단위적용여부 is highly overall correlated with 리포트레벨 and 3 other fieldsHigh correlation
리포트레벨 is highly overall correlated with 단위 and 3 other fieldsHigh correlation
단위기준값 is highly overall correlated with 리포트코드 and 4 other fieldsHigh correlation
단위 is highly overall correlated with 리포트코드 and 4 other fieldsHigh correlation
단위기준값적용여부 is highly overall correlated with 리포트레벨 and 3 other fieldsHigh correlation
리포트코드 is highly overall correlated with 단위 and 1 other fieldsHigh correlation
리포트레벨 is highly imbalanced (61.9%)Imbalance
리포트적용_시작일 is highly imbalanced (77.1%)Imbalance
리포트적용_종료일 is highly imbalanced (77.1%)Imbalance
리포트파일위치 has 26 (96.3%) missing valuesMissing
리포트파일명 has 2 (7.4%) missing valuesMissing
리포트테이블명 has 2 (7.4%) missing valuesMissing
리포트그리드명 has 2 (7.4%) missing valuesMissing
리포트데이터셋명 has 27 (100.0%) missing valuesMissing
비고 has 27 (100.0%) missing valuesMissing
리포트코드 has unique valuesUnique
리포트명 has unique valuesUnique
리포트데이터셋명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 20:00:22.696709
Analysis finished2023-12-12 20:00:24.079071
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

리포트코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18528.111
Minimum10000
Maximum20022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T05:00:24.140921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile10001.3
Q120002.5
median20009
Q320015.5
95-th percentile20020.7
Maximum20022
Range10022
Interquartile range (IQR)13

Descriptive statistics

Standard deviation3623.5845
Coefficient of variation (CV)0.19557225
Kurtosis2.5943166
Mean18528.111
Median Absolute Deviation (MAD)7
Skewness-2.0993532
Sum500259
Variance13130364
MonotonicityStrictly increasing
2023-12-13T05:00:24.274035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
10000 1
 
3.7%
10001 1
 
3.7%
20022 1
 
3.7%
20021 1
 
3.7%
20020 1
 
3.7%
20019 1
 
3.7%
20018 1
 
3.7%
20017 1
 
3.7%
20016 1
 
3.7%
20015 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
10000 1
3.7%
10001 1
3.7%
10002 1
3.7%
10003 1
3.7%
20000 1
3.7%
20001 1
3.7%
20002 1
3.7%
20003 1
3.7%
20004 1
3.7%
20005 1
3.7%
ValueCountFrequency (%)
20022 1
3.7%
20021 1
3.7%
20020 1
3.7%
20019 1
3.7%
20018 1
3.7%
20017 1
3.7%
20016 1
3.7%
20015 1
3.7%
20014 1
3.7%
20013 1
3.7%

리포트명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-13T05:00:24.525380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length26
Mean length22.296296
Min length13

Characters and Unicode

Total characters602
Distinct characters89
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st rowI. 사학진흥기금 조성/운용
2nd row1-1. 융자금 지급현황
3rd row1-2. 융자원리금 수납 실적 및 계획
4th row1-3. 융자금 조기상환 현황
5th rowII. 사학교육환경개선자금 융자사업
ValueCountFrequency (%)
현황 11
 
8.9%
학교급별 7
 
5.6%
지급현황 7
 
5.6%
연도별 7
 
5.6%
융자지원 5
 
4.0%
융자사업 5
 
4.0%
지원현황 4
 
3.2%
학교별 4
 
3.2%
교육시설별 3
 
2.4%
상위 3
 
2.4%
Other values (60) 68
54.8%
2023-12-13T05:00:24.920949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
 
16.1%
별 29
 
4.8%
2 29
 
4.8%
. 27
 
4.5%
- 25
 
4.2%
황 25
 
4.2%
현 25
 
4.2%
지 22
 
3.7%
자 20
 
3.3%
교 20
 
3.3%
Other values (79) 283
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 353
58.6%
Space Separator 97
 
16.1%
Decimal Number 69
 
11.5%
Other Punctuation 31
 
5.1%
Dash Punctuation 25
 
4.2%
Close Punctuation 12
 
2.0%
Open Punctuation 12
 
2.0%
Uppercase Letter 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
별 29
 
8.2%
황 25
 
7.1%
현 25
 
7.1%
지 22
 
6.2%
자 20
 
5.7%
교 20
 
5.7%
학 19
 
5.4%
융 18
 
5.1%
급 17
 
4.8%
사 15
 
4.2%
Other values (61) 143
40.5%
Decimal Number
ValueCountFrequency (%)
2 29
42.0%
1 17
24.6%
0 5
 
7.2%
5 5
 
7.2%
3 3
 
4.3%
8 2
 
2.9%
9 2
 
2.9%
7 2
 
2.9%
6 2
 
2.9%
4 2
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 27
87.1%
, 3
 
9.7%
/ 1
 
3.2%
Space Separator
ValueCountFrequency (%)
97
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Uppercase Letter
ValueCountFrequency (%)
I 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 353
58.6%
Common 246
40.9%
Latin 3
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
별 29
 
8.2%
황 25
 
7.1%
현 25
 
7.1%
지 22
 
6.2%
자 20
 
5.7%
교 20
 
5.7%
학 19
 
5.4%
융 18
 
5.1%
급 17
 
4.8%
사 15
 
4.2%
Other values (61) 143
40.5%
Common
ValueCountFrequency (%)
97
39.4%
2 29
 
11.8%
. 27
 
11.0%
- 25
 
10.2%
1 17
 
6.9%
) 12
 
4.9%
( 12
 
4.9%
0 5
 
2.0%
5 5
 
2.0%
, 3
 
1.2%
Other values (7) 14
 
5.7%
Latin
ValueCountFrequency (%)
I 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 353
58.6%
ASCII 249
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
97
39.0%
2 29
 
11.6%
. 27
 
10.8%
- 25
 
10.0%
1 17
 
6.8%
) 12
 
4.8%
( 12
 
4.8%
0 5
 
2.0%
5 5
 
2.0%
, 3
 
1.2%
Other values (8) 17
 
6.8%
Hangul
ValueCountFrequency (%)
별 29
 
8.2%
황 25
 
7.1%
현 25
 
7.1%
지 22
 
6.2%
자 20
 
5.7%
교 20
 
5.7%
학 19
 
5.4%
융 18
 
5.1%
급 17
 
4.8%
사 15
 
4.2%
Other values (61) 143
40.5%

리포트레벨
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
2
25 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 25
92.6%
1 2
 
7.4%

Length

2023-12-13T05:00:25.067315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:00:25.165319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 25
92.6%
1 2
 
7.4%

리포트적용_시작일
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
20110623
26 
20110611
 
1

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row20110623
2nd row20110611
3rd row20110623
4th row20110623
5th row20110623

Common Values

ValueCountFrequency (%)
20110623 26
96.3%
20110611 1
 
3.7%

Length

2023-12-13T05:00:25.253373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:00:25.352316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20110623 26
96.3%
20110611 1
 
3.7%

리포트적용_종료일
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
20991231
26 
21001231
 
1

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row20991231
2nd row21001231
3rd row20991231
4th row20991231
5th row20991231

Common Values

ValueCountFrequency (%)
20991231 26
96.3%
21001231 1
 
3.7%

Length

2023-12-13T05:00:25.448886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:00:25.557065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20991231 26
96.3%
21001231 1
 
3.7%

리포트파일위치
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing26
Missing (%)96.3%
Memory size348.0 B
2023-12-13T05:00:25.620995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row./STAT
ValueCountFrequency (%)
stat 1
100.0%
2023-12-13T05:00:25.818703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 2
33.3%
. 1
16.7%
/ 1
16.7%
S 1
16.7%
A 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4
66.7%
Other Punctuation 2
33.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 2
50.0%
S 1
25.0%
A 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
/ 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4
66.7%
Common 2
33.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 2
50.0%
S 1
25.0%
A 1
25.0%
Common
ValueCountFrequency (%)
. 1
50.0%
/ 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 2
33.3%
. 1
16.7%
/ 1
16.7%
S 1
16.7%
A 1
16.7%

리포트파일명
Text

MISSING 

Distinct21
Distinct (%)84.0%
Missing2
Missing (%)7.4%
Memory size348.0 B
2023-12-13T05:00:25.998906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length23.04
Min length14

Characters and Unicode

Total characters576
Distinct characters27
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)72.0%

Sample

1st rowLOAN_PAYMENT_LIST.jrf
2nd rowLONE_REPAY_LIST.jrf
3rd rowLOAN_PRI_EARLY_LIST.jrf
4th rowSUPP_LIST.jrf
5th rowSUPP_LIST_2.jrf
ValueCountFrequency (%)
supp_school_order_list.jrf 3
 
12.0%
supp_sch_cls_list_2.jrf 2
 
8.0%
supp_list_2.jrf 2
 
8.0%
supp_edu_year_list.jrf 1
 
4.0%
supp_busi_sch_cls_list.jrf 1
 
4.0%
loan_rate_list.jrf 1
 
4.0%
supp_scale_schcls_list.jrf 1
 
4.0%
supp_year_remain_list.jrf 1
 
4.0%
supp_repay_extend_list.jrf 1
 
4.0%
supp_year_giveup_list.jrf 1
 
4.0%
Other values (11) 11
44.0%
2023-12-13T05:00:26.329355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 71
 
12.3%
S 68
 
11.8%
P 48
 
8.3%
L 41
 
7.1%
I 33
 
5.7%
U 28
 
4.9%
T 28
 
4.9%
f 25
 
4.3%
r 25
 
4.3%
j 25
 
4.3%
Other values (17) 184
31.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 381
66.1%
Lowercase Letter 75
 
13.0%
Connector Punctuation 71
 
12.3%
Other Punctuation 25
 
4.3%
Space Separator 20
 
3.5%
Decimal Number 4
 
0.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 68
17.8%
P 48
12.6%
L 41
10.8%
I 33
8.7%
U 28
7.3%
T 28
7.3%
E 22
 
5.8%
C 19
 
5.0%
R 18
 
4.7%
A 17
 
4.5%
Other values (10) 59
15.5%
Lowercase Letter
ValueCountFrequency (%)
f 25
33.3%
r 25
33.3%
j 25
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 71
100.0%
Other Punctuation
ValueCountFrequency (%)
. 25
100.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Decimal Number
ValueCountFrequency (%)
2 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 456
79.2%
Common 120
 
20.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 68
14.9%
P 48
10.5%
L 41
 
9.0%
I 33
 
7.2%
U 28
 
6.1%
T 28
 
6.1%
f 25
 
5.5%
r 25
 
5.5%
j 25
 
5.5%
E 22
 
4.8%
Other values (13) 113
24.8%
Common
ValueCountFrequency (%)
_ 71
59.2%
. 25
 
20.8%
20
 
16.7%
2 4
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 576
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 71
 
12.3%
S 68
 
11.8%
P 48
 
8.3%
L 41
 
7.1%
I 33
 
5.7%
U 28
 
4.9%
T 28
 
4.9%
f 25
 
4.3%
r 25
 
4.3%
j 25
 
4.3%
Other values (17) 184
31.9%

리포트테이블명
Text

MISSING 

Distinct19
Distinct (%)76.0%
Missing2
Missing (%)7.4%
Memory size348.0 B
2023-12-13T05:00:26.556933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length25.76
Min length17

Characters and Unicode

Total characters644
Distinct characters21
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)64.0%

Sample

1st rowTB_STAT_LOAN_PAY_LIST
2nd rowTB_STAT_LOAN_REPAY_LIST
3rd rowTB_STAT_LOAN_PRI_EARLY_LIST
4th rowTB_STAT_SUPP_LIST
5th rowTB_STAT_SUPP_LIST
ValueCountFrequency (%)
tb_stat_supp_school_order_list 3
 
12.0%
tb_stat_supp_list 3
 
12.0%
tb_stat_supp_sch_cls_list 3
 
12.0%
tb_stat_supp_busi_sch_cls_list 1
 
4.0%
tb_stat_supp_busi_year_list 1
 
4.0%
tb_stat_loan_rate_list 1
 
4.0%
tb_stat_supp_scale_schcls_list 1
 
4.0%
tb_stat_supp_year_remain_list 1
 
4.0%
tb_stat_supp_repay_extend_list 1
 
4.0%
tb_stat_supp_year_giveup_list 1
 
4.0%
Other values (9) 9
36.0%
2023-12-13T05:00:26.931791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 117
18.2%
T 102
15.8%
S 93
14.4%
P 48
7.5%
A 43
 
6.7%
L 41
 
6.4%
I 33
 
5.1%
B 29
 
4.5%
U 28
 
4.3%
E 20
 
3.1%
Other values (11) 90
14.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 527
81.8%
Connector Punctuation 117
 
18.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 102
19.4%
S 93
17.6%
P 48
9.1%
A 43
8.2%
L 41
7.8%
I 33
 
6.3%
B 29
 
5.5%
U 28
 
5.3%
E 20
 
3.8%
C 19
 
3.6%
Other values (10) 71
13.5%
Connector Punctuation
ValueCountFrequency (%)
_ 117
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 527
81.8%
Common 117
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 102
19.4%
S 93
17.6%
P 48
9.1%
A 43
8.2%
L 41
7.8%
I 33
 
6.3%
B 29
 
5.5%
U 28
 
5.3%
E 20
 
3.8%
C 19
 
3.6%
Other values (10) 71
13.5%
Common
ValueCountFrequency (%)
_ 117
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 644
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 117
18.2%
T 102
15.8%
S 93
14.4%
P 48
7.5%
A 43
 
6.7%
L 41
 
6.4%
I 33
 
5.1%
B 29
 
4.5%
U 28
 
4.3%
E 20
 
3.1%
Other values (11) 90
14.0%

리포트그리드명
Text

MISSING 

Distinct19
Distinct (%)76.0%
Missing2
Missing (%)7.4%
Memory size348.0 B
2023-12-13T05:00:27.142808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.52
Min length19

Characters and Unicode

Total characters538
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)64.0%

Sample

1st rowDiv_subDetail.Grid0
2nd rowDiv_subDetail_1.Grid0
3rd rowDiv_subDetail_2.Grid0
4th rowDiv_subDetail_3.Grid0
5th rowDiv_subDetail_3.Grid0
ValueCountFrequency (%)
div_subdetail_20.grid0 3
 
12.0%
div_subdetail_3.grid0 3
 
12.0%
div_subdetail_6.grid0 3
 
12.0%
div_subdetail_13.grid0 1
 
4.0%
div_subdetail_14.grid0 1
 
4.0%
div_subdetail_23.grid0 1
 
4.0%
div_subdetail_19.grid0 1
 
4.0%
div_subdetail_18.grid0 1
 
4.0%
div_subdetail_17.grid0 1
 
4.0%
div_subdetail_16.grid0 1
 
4.0%
Other values (9) 9
36.0%
2023-12-13T05:00:27.479552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 75
13.9%
D 50
 
9.3%
_ 49
 
9.1%
0 29
 
5.4%
s 25
 
4.6%
v 25
 
4.6%
d 25
 
4.6%
r 25
 
4.6%
u 25
 
4.6%
. 25
 
4.6%
Other values (15) 185
34.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 325
60.4%
Uppercase Letter 75
 
13.9%
Decimal Number 64
 
11.9%
Connector Punctuation 49
 
9.1%
Other Punctuation 25
 
4.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 75
23.1%
s 25
 
7.7%
v 25
 
7.7%
d 25
 
7.7%
r 25
 
7.7%
u 25
 
7.7%
l 25
 
7.7%
a 25
 
7.7%
t 25
 
7.7%
e 25
 
7.7%
Decimal Number
ValueCountFrequency (%)
0 29
45.3%
1 12
18.8%
2 7
 
10.9%
3 5
 
7.8%
6 4
 
6.2%
9 2
 
3.1%
4 2
 
3.1%
5 1
 
1.6%
7 1
 
1.6%
8 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
D 50
66.7%
G 25
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 49
100.0%
Other Punctuation
ValueCountFrequency (%)
. 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 400
74.3%
Common 138
 
25.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 75
18.8%
D 50
12.5%
s 25
 
6.2%
v 25
 
6.2%
d 25
 
6.2%
r 25
 
6.2%
u 25
 
6.2%
G 25
 
6.2%
l 25
 
6.2%
a 25
 
6.2%
Other values (3) 75
18.8%
Common
ValueCountFrequency (%)
_ 49
35.5%
0 29
21.0%
. 25
18.1%
1 12
 
8.7%
2 7
 
5.1%
3 5
 
3.6%
6 4
 
2.9%
9 2
 
1.4%
4 2
 
1.4%
5 1
 
0.7%
Other values (2) 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 538
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 75
13.9%
D 50
 
9.3%
_ 49
 
9.1%
0 29
 
5.4%
s 25
 
4.6%
v 25
 
4.6%
d 25
 
4.6%
r 25
 
4.6%
u 25
 
4.6%
. 25
 
4.6%
Other values (15) 185
34.4%

리포트데이터셋명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing27
Missing (%)100.0%
Memory size375.0 B

단위
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size348.0 B
억원
17 
백만원
5 
<NA>
3 
천원
2 

Length

Max length4
Median length2
Mean length2.4074074
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row억원
3rd row천원
4th row천원
5th row<NA>

Common Values

ValueCountFrequency (%)
억원 17
63.0%
백만원 5
 
18.5%
<NA> 3
 
11.1%
천원 2
 
7.4%

Length

2023-12-13T05:00:27.640631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:00:27.760400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
억원 17
63.0%
백만원 5
 
18.5%
na 3
 
11.1%
천원 2
 
7.4%

단위적용여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size159.0 B
True
24 
False
3 
ValueCountFrequency (%)
True 24
88.9%
False 3
 
11.1%
2023-12-13T05:00:27.860995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

단위기준값
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size348.0 B
100000000
17 
1000000
5 
1
3 
1000
2 

Length

Max length9
Median length9
Mean length7.3703704
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row100000000
3rd row1000
4th row1000
5th row1

Common Values

ValueCountFrequency (%)
100000000 17
63.0%
1000000 5
 
18.5%
1 3
 
11.1%
1000 2
 
7.4%

Length

2023-12-13T05:00:28.278422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:00:28.404367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100000000 17
63.0%
1000000 5
 
18.5%
1 3
 
11.1%
1000 2
 
7.4%

단위기준값적용여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size159.0 B
True
24 
False
3 
ValueCountFrequency (%)
True 24
88.9%
False 3
 
11.1%
2023-12-13T05:00:28.524296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

사용여부
Boolean

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size159.0 B
True
23 
False
4 
ValueCountFrequency (%)
True 23
85.2%
False 4
 
14.8%
2023-12-13T05:00:28.609526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing27
Missing (%)100.0%
Memory size375.0 B

등록자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
system
27 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
system 27
100.0%

Length

2023-12-13T05:00:28.715908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:00:28.819625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
system 27
100.0%

등록일자
Date

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
Minimum2011-09-06 00:00:00
Maximum2011-09-06 00:00:00
2023-12-13T05:00:28.905663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:00:28.995057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

수정자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
system
27 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
system 27
100.0%

Length

2023-12-13T05:00:29.108628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:00:29.200004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
system 27
100.0%

수정일자
Date

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
Minimum2011-09-06 00:00:00
Maximum2011-09-06 00:00:00
2023-12-13T05:00:29.278771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:00:29.377748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T05:00:23.395902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:00:29.482928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
리포트코드리포트명리포트레벨리포트적용_시작일리포트적용_종료일리포트파일명리포트테이블명리포트그리드명단위단위적용여부단위기준값단위기준값적용여부사용여부
리포트코드1.0001.0000.0000.2220.2221.0001.0001.0000.5170.0000.9370.0000.000
리포트명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
리포트레벨0.0001.0001.0000.0000.000NaNNaNNaNNaN0.7630.9360.7630.000
리포트적용_시작일0.2221.0000.0001.0000.6481.0001.0001.0000.0000.0000.0000.0000.000
리포트적용_종료일0.2221.0000.0000.6481.0001.0001.0001.0000.0000.0000.0000.0000.000
리포트파일명1.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0000.000
리포트테이블명1.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0000.000
리포트그리드명1.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0000.000
단위0.5171.000NaN0.0000.0001.0001.0001.0001.000NaN1.000NaN0.104
단위적용여부0.0001.0000.7630.0000.0001.0001.0001.000NaN1.0001.0000.9530.000
단위기준값0.9371.0000.9360.0000.0001.0001.0001.0001.0001.0001.0001.0000.219
단위기준값적용여부0.0001.0000.7630.0000.0001.0001.0001.000NaN0.9531.0001.0000.000
사용여부0.0001.0000.0000.0000.0000.0000.0000.0000.1040.0000.2190.0001.000
2023-12-13T05:00:29.645356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단위적용여부리포트레벨리포트적용_시작일리포트적용_종료일단위기준값사용여부단위단위기준값적용여부
단위적용여부1.0000.5510.0000.0000.9590.0001.0000.804
리포트레벨0.5511.0000.0000.0000.7390.0001.0000.551
리포트적용_시작일0.0000.0001.0000.4480.0000.0000.0000.000
리포트적용_종료일0.0000.0000.4481.0000.0000.0000.0000.000
단위기준값0.9590.7390.0000.0001.0000.1231.0000.959
사용여부0.0000.0000.0000.0000.1231.0000.1570.000
단위1.0001.0000.0000.0001.0000.1571.0001.000
단위기준값적용여부0.8040.5510.0000.0000.9590.0001.0001.000
2023-12-13T05:00:29.772762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
리포트코드리포트레벨리포트적용_시작일리포트적용_종료일단위단위적용여부단위기준값단위기준값적용여부사용여부
리포트코드1.0000.0000.0000.0000.7610.0000.6550.0000.000
리포트레벨0.0001.0000.0000.0001.0000.5510.7390.5510.000
리포트적용_시작일0.0000.0001.0000.4480.0000.0000.0000.0000.000
리포트적용_종료일0.0000.0000.4481.0000.0000.0000.0000.0000.000
단위0.7611.0000.0000.0001.0001.0001.0001.0000.157
단위적용여부0.0000.5510.0000.0001.0001.0000.9590.8040.000
단위기준값0.6550.7390.0000.0001.0000.9591.0000.9590.123
단위기준값적용여부0.0000.5510.0000.0001.0000.8040.9591.0000.000
사용여부0.0000.0000.0000.0000.1570.0000.1230.0001.000

Missing values

2023-12-13T05:00:23.535256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:00:23.815533image/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.
2023-12-13T05:00:24.004010image/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

리포트코드리포트명리포트레벨리포트적용_시작일리포트적용_종료일리포트파일위치리포트파일명리포트테이블명리포트그리드명리포트데이터셋명단위단위적용여부단위기준값단위기준값적용여부사용여부비고등록자등록일자수정자수정일자
010000I. 사학진흥기금 조성/운용12011062320991231<NA><NA><NA><NA><NA><NA>N1NY<NA>system2011-09-06system2011-09-06
1100011-1. 융자금 지급현황22011061121001231./STATLOAN_PAYMENT_LIST.jrfTB_STAT_LOAN_PAY_LISTDiv_subDetail.Grid0<NA>억원Y100000000YY<NA>system2011-09-06system2011-09-06
2100021-2. 융자원리금 수납 실적 및 계획22011062320991231<NA>LONE_REPAY_LIST.jrfTB_STAT_LOAN_REPAY_LISTDiv_subDetail_1.Grid0<NA>천원Y1000YY<NA>system2011-09-06system2011-09-06
3100031-3. 융자금 조기상환 현황22011062320991231<NA>LOAN_PRI_EARLY_LIST.jrfTB_STAT_LOAN_PRI_EARLY_LISTDiv_subDetail_2.Grid0<NA>천원Y1000YY<NA>system2011-09-06system2011-09-06
420000II. 사학교육환경개선자금 융자사업12011062320991231<NA><NA><NA><NA><NA><NA>N1NY<NA>system2011-09-06system2011-09-06
5200012-1. 연도별 융자지원 현황 (총괄)22011062320991231<NA>SUPP_LIST.jrfTB_STAT_SUPP_LISTDiv_subDetail_3.Grid0<NA>억원Y100000000YY<NA>system2011-09-06system2011-09-06
6200022-2. 연도별 사학시설 융자사업 지원현황22011062320991231<NA>SUPP_LIST_2.jrfTB_STAT_SUPP_LISTDiv_subDetail_3.Grid0<NA>억원Y100000000YY<NA>system2011-09-06system2011-09-06
7200032-3. 연도별 지발대학기숙사 융자사업 지원현황22011062320991231<NA>SUPP_LIST_2.jrfTB_STAT_SUPP_LISTDiv_subDetail_3.Grid0<NA>억원Y100000000YN<NA>system2011-09-06system2011-09-06
8200042-4. 학교급별 융자지원현황 (총괄)22011062320991231<NA>SUPP_SCH_CLS_LIST.jrfTB_STAT_SUPP_SCH_CLS_LISTDiv_subDetail_6.Grid0<NA>억원Y100000000YY<NA>system2011-09-06system2011-09-06
9200052-5. 학교급별 사학시설 융자사업 지원현황22011062320991231<NA>SUPP_SCH_CLS_LIST_2.jrfTB_STAT_SUPP_SCH_CLS_LISTDiv_subDetail_6.Grid0<NA>억원Y100000000YY<NA>system2011-09-06system2011-09-06
리포트코드리포트명리포트레벨리포트적용_시작일리포트적용_종료일리포트파일위치리포트파일명리포트테이블명리포트그리드명리포트데이터셋명단위단위적용여부단위기준값단위기준값적용여부사용여부비고등록자등록일자수정자수정일자
17200132-13. 사업형태별, 교육시설별 지급현황22011062320991231<NA>SUPP_BUSI_LIST.jrfTB_STAT_SUPP_BUSI_LISTDiv_subDetail_15.Grid0<NA>억원Y100000000YY<NA>system2011-09-06system2011-09-06
18200142-14. 연도별 융자포기현황22011062320991231<NA>SUPP_YEAR_GIVEUP_LIST.jrfTB_STAT_SUPP_YEAR_GIVEUP_LISTDiv_subDetail_16.Grid0<NA>억원Y100000000YY<NA>system2011-09-06system2011-09-06
19200152-15. 융자금 상환기간 연장내역22011062320991231<NA>SUPP_REPAY_EXTEND_LIST.jrfTB_STAT_SUPP_REPAY_EXTEND_LISTDiv_subDetail_17.Grid0<NA>백만원Y1000000YY<NA>system2011-09-06system2011-09-06
20200162-16. 배정연도별 융자잔액22011062320991231<NA>SUPP_YEAR_REMAIN_LIST.jrfTB_STAT_SUPP_YEAR_REMAIN_LISTDiv_subDetail_18.Grid0<NA>억원Y100000000YY<NA>system2011-09-06system2011-09-06
21200172-17. 지급규모별 학교급별 지급현황22011062320991231<NA>SUPP_SCALE_SCHCLS_LIST.jrfTB_STAT_SUPP_SCALE_SCHCLS_LISTDiv_subDetail_19.Grid0<NA>억원Y100000000YY<NA>system2011-09-06system2011-09-06
22200182-18. 학교별 융자지원 현황 (상위 50교) (대학교)22011062320991231<NA>SUPP_SCHOOL_ORDER_LIST.jrfTB_STAT_SUPP_SCHOOL_ORDER_LISTDiv_subDetail_20.Grid0<NA>백만원Y1000000YY<NA>system2011-09-06system2011-09-06
23200192-19. 학교별 융자지원 현황 (상위 50교) (전문대학)22011062320991231<NA>SUPP_SCHOOL_ORDER_LIST.jrfTB_STAT_SUPP_SCHOOL_ORDER_LISTDiv_subDetail_20.Grid0<NA>백만원Y1000000YN<NA>system2011-09-06system2011-09-06
24200202-20. 학교별 융자지원 현황 (상위 50교) (중등이하교)22011062320991231<NA>SUPP_SCHOOL_ORDER_LIST.jrfTB_STAT_SUPP_SCHOOL_ORDER_LISTDiv_subDetail_20.Grid0<NA>백만원Y1000000YN<NA>system2011-09-06system2011-09-06
25200212-21. 이자율 변동추이22011062320991231<NA>LOAN_RATE_LIST.jrfTB_STAT_LOAN_RATE_LISTDiv_subDetail_23.Grid0<NA><NA>N1NY<NA>system2011-09-06system2011-09-06
26200222-22. 학교별 사업별 융자지원 현황22011062320991231<NA>SUPP_SCHOOL_BUSI_LIST.jrfTB_STAT_SUPP_SCHOOL_BUSI_LISTDiv_subDetail_24.Grid0<NA>백만원Y1000000YY<NA>system2011-09-06system2011-09-06