Overview

Dataset statistics

Number of variables7
Number of observations566
Missing cells90
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.6 KiB
Average record size in memory57.2 B

Variable types

Text3
Numeric1
Boolean1
DateTime2

Dataset

Description한국사학진흥재단 대학재정정보시스템 명세서계정과목 정보(계정과목코드, 계정과목명, 상위 계정과목코드, 사용유무, 입력일시, 최종변경일시)를 포함한 파일데이터
URLhttps://www.data.go.kr/data/15120090/fileData.do

Alerts

사용유무 has constant value ""Constant
입력일시 has constant value ""Constant
최종변경일시 has constant value ""Constant
상위 계정과목코드 has 90 (15.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 03:21:30.891365
Analysis finished2023-12-12 03:21:31.460883
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

계정과목코드
Text

Distinct170
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2023-12-12T12:21:31.820696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2830
Distinct characters14
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

Unique26 ?
Unique (%)4.6%

Sample

1st rowSG006
2nd rowSG007
3rd rowSG008
4th rowSG009
5th rowSG010
ValueCountFrequency (%)
sg006 6
 
1.1%
sy004 6
 
1.1%
sy012 6
 
1.1%
sg004 6
 
1.1%
sg005 6
 
1.1%
sy001 6
 
1.1%
sg003 6
 
1.1%
sy002 6
 
1.1%
sy005 6
 
1.1%
sy013 6
 
1.1%
Other values (160) 506
89.4%
2023-12-12T12:21:32.489840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 741
26.2%
S 508
18.0%
G 312
11.0%
Y 254
 
9.0%
1 197
 
7.0%
2 158
 
5.6%
3 141
 
5.0%
4 120
 
4.2%
5 98
 
3.5%
6 78
 
2.8%
Other values (4) 223
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1698
60.0%
Uppercase Letter 1132
40.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 741
43.6%
1 197
 
11.6%
2 158
 
9.3%
3 141
 
8.3%
4 120
 
7.1%
5 98
 
5.8%
6 78
 
4.6%
7 57
 
3.4%
8 55
 
3.2%
9 53
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
S 508
44.9%
G 312
27.6%
Y 254
22.4%
E 58
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1698
60.0%
Latin 1132
40.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 741
43.6%
1 197
 
11.6%
2 158
 
9.3%
3 141
 
8.3%
4 120
 
7.1%
5 98
 
5.8%
6 78
 
4.6%
7 57
 
3.4%
8 55
 
3.2%
9 53
 
3.1%
Latin
ValueCountFrequency (%)
S 508
44.9%
G 312
27.6%
Y 254
22.4%
E 58
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2830
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 741
26.2%
S 508
18.0%
G 312
11.0%
Y 254
 
9.0%
1 197
 
7.0%
2 158
 
5.6%
3 141
 
5.0%
4 120
 
4.2%
5 98
 
3.5%
6 78
 
2.8%
Other values (4) 223
 
7.9%

계정과목명
Text

Distinct160
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2023-12-12T12:21:32.873077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length6.1731449
Min length2

Characters and Unicode

Total characters3494
Distinct characters127
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)4.1%

Sample

1st row직원인건비
2nd row임시직인건비
3rd row임시직인건비
4th row퇴직적립금
5th row퇴직적립금
ValueCountFrequency (%)
이자수입 15
 
2.6%
다음연도이월금 14
 
2.4%
지난연도이월금 14
 
2.4%
잡수입 13
 
2.2%
환차익 12
 
2.1%
기부금수입 10
 
1.7%
잡지출 10
 
1.7%
환차손 10
 
1.7%
예비비 10
 
1.7%
전출금 10
 
1.7%
Other values (148) 466
79.8%
2023-12-12T12:21:33.438911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 232
 
6.6%
금 230
 
6.6%
입 227
 
6.5%
수 221
 
6.3%
지 141
 
4.0%
차 98
 
2.8%
기 97
 
2.8%
이 87
 
2.5%
원 74
 
2.1%
도 74
 
2.1%
Other values (117) 2013
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3464
99.1%
Space Separator 18
 
0.5%
Open Punctuation 6
 
0.2%
Close Punctuation 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 232
 
6.7%
금 230
 
6.6%
입 227
 
6.6%
수 221
 
6.4%
지 141
 
4.1%
차 98
 
2.8%
기 97
 
2.8%
이 87
 
2.5%
원 74
 
2.1%
도 74
 
2.1%
Other values (114) 1983
57.2%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3464
99.1%
Common 30
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 232
 
6.7%
금 230
 
6.6%
입 227
 
6.6%
수 221
 
6.4%
지 141
 
4.1%
차 98
 
2.8%
기 97
 
2.8%
이 87
 
2.5%
원 74
 
2.1%
도 74
 
2.1%
Other values (114) 1983
57.2%
Common
ValueCountFrequency (%)
18
60.0%
( 6
 
20.0%
) 6
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3458
99.0%
ASCII 30
 
0.9%
Compat Jamo 6
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 232
 
6.7%
금 230
 
6.7%
입 227
 
6.6%
수 221
 
6.4%
지 141
 
4.1%
차 98
 
2.8%
기 97
 
2.8%
이 87
 
2.5%
원 74
 
2.1%
도 74
 
2.1%
Other values (113) 1977
57.2%
ASCII
ValueCountFrequency (%)
18
60.0%
( 6
 
20.0%
) 6
 
20.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 6
100.0%

상위 계정과목코드
Text

MISSING 

Distinct134
Distinct (%)28.2%
Missing90
Missing (%)15.9%
Memory size4.6 KiB
2023-12-12T12:21:33.931610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2380
Distinct characters14
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

Unique34 ?
Unique (%)7.1%

Sample

1st rowSG005
2nd rowSG004
3rd rowSG007
4th rowSG004
5th rowSG009
ValueCountFrequency (%)
sy009 14
 
2.9%
sg009 14
 
2.9%
eg002 11
 
2.3%
sg002 11
 
2.3%
sy002 11
 
2.3%
sg010 10
 
2.1%
sy001 10
 
2.1%
sy010 10
 
2.1%
sy017 10
 
2.1%
sg017 10
 
2.1%
Other values (124) 365
76.7%
2023-12-12T12:21:34.562380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 668
28.1%
S 426
17.9%
G 263
 
11.1%
Y 213
 
8.9%
1 150
 
6.3%
2 131
 
5.5%
3 96
 
4.0%
4 87
 
3.7%
5 74
 
3.1%
9 70
 
2.9%
Other values (4) 202
 
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1428
60.0%
Uppercase Letter 952
40.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 668
46.8%
1 150
 
10.5%
2 131
 
9.2%
3 96
 
6.7%
4 87
 
6.1%
5 74
 
5.2%
9 70
 
4.9%
6 60
 
4.2%
7 59
 
4.1%
8 33
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
S 426
44.7%
G 263
27.6%
Y 213
22.4%
E 50
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1428
60.0%
Latin 952
40.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 668
46.8%
1 150
 
10.5%
2 131
 
9.2%
3 96
 
6.7%
4 87
 
6.1%
5 74
 
5.2%
9 70
 
4.9%
6 60
 
4.2%
7 59
 
4.1%
8 33
 
2.3%
Latin
ValueCountFrequency (%)
S 426
44.7%
G 263
27.6%
Y 213
22.4%
E 50
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2380
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 668
28.1%
S 426
17.9%
G 263
 
11.1%
Y 213
 
8.9%
1 150
 
6.3%
2 131
 
5.5%
3 96
 
4.0%
4 87
 
3.7%
5 74
 
3.1%
9 70
 
2.9%
Other values (4) 202
 
8.5%

정렬번호
Real number (ℝ)

Distinct69
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.821555
Minimum1
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2023-12-12T12:21:34.814499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q111
median21
Q337
95-th percentile57
Maximum69
Range68
Interquartile range (IQR)26

Descriptive statistics

Standard deviation17.147614
Coefficient of variation (CV)0.69083561
Kurtosis-0.56410919
Mean24.821555
Median Absolute Deviation (MAD)12
Skewness0.59501763
Sum14049
Variance294.04067
MonotonicityNot monotonic
2023-12-12T12:21:35.054772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 14
 
2.5%
15 14
 
2.5%
1 14
 
2.5%
2 14
 
2.5%
3 14
 
2.5%
4 14
 
2.5%
5 14
 
2.5%
17 14
 
2.5%
16 14
 
2.5%
7 14
 
2.5%
Other values (59) 426
75.3%
ValueCountFrequency (%)
1 14
2.5%
2 14
2.5%
3 14
2.5%
4 14
2.5%
5 14
2.5%
6 14
2.5%
7 14
2.5%
8 14
2.5%
9 14
2.5%
10 14
2.5%
ValueCountFrequency (%)
69 2
0.4%
68 2
0.4%
67 2
0.4%
66 2
0.4%
65 2
0.4%
64 2
0.4%
63 2
0.4%
62 2
0.4%
61 2
0.4%
60 2
0.4%

사용유무
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size698.0 B
True
566 
ValueCountFrequency (%)
True 566
100.0%
2023-12-12T12:21:35.216447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

입력일시
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
Minimum2021-09-28 00:00:00
Maximum2021-09-28 00:00:00
2023-12-12T12:21:35.319447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:21:35.465474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

최종변경일시
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
Minimum2021-09-28 00:00:00
Maximum2021-09-28 00:00:00
2023-12-12T12:21:35.625345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:21:35.792678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T12:21:31.111892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T12:21:31.263200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:21:31.403015image/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

계정과목코드계정과목명상위 계정과목코드정렬번호사용유무입력일시최종변경일시
0SG006직원인건비SG0056Y2021-09-282021-09-28
1SG007임시직인건비SG0047Y2021-09-282021-09-28
2SG008임시직인건비SG0078Y2021-09-282021-09-28
3SG009퇴직적립금SG0049Y2021-09-282021-09-28
4SG010퇴직적립금SG00910Y2021-09-282021-09-28
5SG011법인운영비<NA>11Y2021-09-282021-09-28
6SG012이사회운영비SG01112Y2021-09-282021-09-28
7SG013이사회운영비SG01213Y2021-09-282021-09-28
8SG014일반운영비SG01114Y2021-09-282021-09-28
9SG015일반수용비SG01415Y2021-09-282021-09-28
계정과목코드계정과목명상위 계정과목코드정렬번호사용유무입력일시최종변경일시
556EG017기타지출<NA>17Y2021-09-282021-09-28
557EG018반납금EG01718Y2021-09-282021-09-28
558EG019교육부지원금반납금EG01819Y2021-09-282021-09-28
559EG020타기관지원금반납금EG01820Y2021-09-282021-09-28
560EG021잡비용EG01721Y2021-09-282021-09-28
561EG022잡비용EG02122Y2021-09-282021-09-28
562EG023다음연도이월금<NA>23Y2021-09-282021-09-28
563EG024다음연도이월금EG02324Y2021-09-282021-09-28
564EG025다음연도이월사업비EG02425Y2021-09-282021-09-28
565EG026다음연도이월순세계잉여금EG02426Y2021-09-282021-09-28