Overview

Dataset statistics

Number of variables12
Number of observations86
Missing cells180
Missing cells (%)17.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.5 KiB
Average record size in memory101.5 B

Variable types

Numeric4
Text3
DateTime1
Categorical4

Dataset

Description연구종합관리시스템 연구보고서의 논문게재실적 관리를 제공합니다. 논문제목, 논문게재일, 학술지명, 작성년도 등 의 항목을 제공합니다.
Author통계청
URLhttps://www.data.go.kr/data/15088173/fileData.do

Alerts

순번 is highly overall correlated with 작성년도 and 1 other fieldsHigh correlation
발간호(권) is highly overall correlated with 작성년도 and 2 other fieldsHigh correlation
작성년도 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
발간호(호) is highly overall correlated with 학술지명High correlation
학술지명 is highly overall correlated with 발간호(권) and 2 other fieldsHigh correlation
작성일 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
부서명 is highly overall correlated with 학술지명High correlation
게제일 has 33 (38.4%) missing valuesMissing
발간호(권) has 9 (10.5%) missing valuesMissing
관련 연구과제명 has 65 (75.6%) missing valuesMissing
발간기관 has 61 (70.9%) missing valuesMissing
발간호(호) has 12 (14.0%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:24:56.668032
Analysis finished2023-12-12 14:24:59.494224
Duration2.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct86
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean754.83721
Minimum22
Maximum1692
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-12T23:24:59.865056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile37.25
Q1149.25
median431.5
Q31569.25
95-th percentile1652.75
Maximum1692
Range1670
Interquartile range (IQR)1420

Descriptive statistics

Standard deviation692.1229
Coefficient of variation (CV)0.91691678
Kurtosis-1.7568911
Mean754.83721
Median Absolute Deviation (MAD)369
Skewness0.38466784
Sum64916
Variance479034.11
MonotonicityNot monotonic
2023-12-12T23:24:59.996717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25 1
 
1.2%
1630 1
 
1.2%
1565 1
 
1.2%
1691 1
 
1.2%
1613 1
 
1.2%
1612 1
 
1.2%
1640 1
 
1.2%
1610 1
 
1.2%
1567 1
 
1.2%
1670 1
 
1.2%
Other values (76) 76
88.4%
ValueCountFrequency (%)
22 1
1.2%
25 1
1.2%
34 1
1.2%
36 1
1.2%
37 1
1.2%
38 1
1.2%
39 1
1.2%
40 1
1.2%
41 1
1.2%
62 1
1.2%
ValueCountFrequency (%)
1692 1
1.2%
1691 1
1.2%
1690 1
1.2%
1670 1
1.2%
1653 1
1.2%
1652 1
1.2%
1651 1
1.2%
1650 1
1.2%
1640 1
1.2%
1638 1
1.2%

논문제목
Text

Distinct78
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-12T23:25:00.316085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length144
Median length60.5
Mean length40.44186
Min length13

Characters and Unicode

Total characters3478
Distinct characters297
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)81.4%

Sample

1st row잡음을 이용한 가계조사자료의 정보노출제한방법
2nd row통계조사자료와 행정자료 간의 통계적 매칭기법에 관한 연구
3rd row생활시간조사 개선을 위한 방법론 제안
4th row사회보험자료의 통계목적 활용가능성 연구: 사업체 기본정보 중심으로
5th row한국 고령근로자의 노동시장 이탈에 관한 종단적 분석
ValueCountFrequency (%)
연구 14
 
2.2%
of 12
 
1.9%
a 12
 
1.9%
and 11
 
1.7%
중심으로 11
 
1.7%
관한 11
 
1.7%
분석 10
 
1.6%
for 9
 
1.4%
mortality 9
 
1.4%
대한 8
 
1.3%
Other values (358) 525
83.1%
2023-12-12T23:25:00.747996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
549
 
15.8%
i 138
 
4.0%
o 136
 
3.9%
e 133
 
3.8%
t 124
 
3.6%
n 113
 
3.2%
a 105
 
3.0%
r 105
 
3.0%
s 72
 
2.1%
d 59
 
1.7%
Other values (287) 1944
55.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1412
40.6%
Lowercase Letter 1345
38.7%
Space Separator 549
 
15.8%
Uppercase Letter 111
 
3.2%
Other Punctuation 22
 
0.6%
Decimal Number 13
 
0.4%
Open Punctuation 9
 
0.3%
Close Punctuation 9
 
0.3%
Dash Punctuation 7
 
0.2%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 53
 
3.8%
의 46
 
3.3%
한 41
 
2.9%
사 38
 
2.7%
에 35
 
2.5%
인 35
 
2.5%
이 34
 
2.4%
조 29
 
2.1%
자 26
 
1.8%
정 25
 
1.8%
Other values (228) 1050
74.4%
Lowercase Letter
ValueCountFrequency (%)
i 138
10.3%
o 136
10.1%
e 133
9.9%
t 124
9.2%
n 113
 
8.4%
a 105
 
7.8%
r 105
 
7.8%
s 72
 
5.4%
d 59
 
4.4%
c 59
 
4.4%
Other values (15) 301
22.4%
Uppercase Letter
ValueCountFrequency (%)
A 17
15.3%
S 11
9.9%
C 11
9.9%
F 8
 
7.2%
K 7
 
6.3%
T 7
 
6.3%
I 7
 
6.3%
P 6
 
5.4%
G 6
 
5.4%
E 5
 
4.5%
Other values (9) 26
23.4%
Other Punctuation
ValueCountFrequency (%)
: 14
63.6%
; 3
 
13.6%
· 2
 
9.1%
, 2
 
9.1%
& 1
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 5
38.5%
0 3
23.1%
2 3
23.1%
5 1
 
7.7%
9 1
 
7.7%
Space Separator
ValueCountFrequency (%)
549
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1457
41.9%
Hangul 1412
40.6%
Common 609
17.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 53
 
3.8%
의 46
 
3.3%
한 41
 
2.9%
사 38
 
2.7%
에 35
 
2.5%
인 35
 
2.5%
이 34
 
2.4%
조 29
 
2.1%
자 26
 
1.8%
정 25
 
1.8%
Other values (228) 1050
74.4%
Latin
ValueCountFrequency (%)
i 138
 
9.5%
o 136
 
9.3%
e 133
 
9.1%
t 124
 
8.5%
n 113
 
7.8%
a 105
 
7.2%
r 105
 
7.2%
s 72
 
4.9%
d 59
 
4.0%
c 59
 
4.0%
Other values (35) 413
28.3%
Common
ValueCountFrequency (%)
549
90.1%
: 14
 
2.3%
( 9
 
1.5%
) 9
 
1.5%
- 7
 
1.1%
1 5
 
0.8%
; 3
 
0.5%
0 3
 
0.5%
2 3
 
0.5%
· 2
 
0.3%
Other values (4) 5
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2063
59.3%
Hangul 1412
40.6%
None 2
 
0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
549
26.6%
i 138
 
6.7%
o 136
 
6.6%
e 133
 
6.4%
t 124
 
6.0%
n 113
 
5.5%
a 105
 
5.1%
r 105
 
5.1%
s 72
 
3.5%
d 59
 
2.9%
Other values (47) 529
25.6%
Hangul
ValueCountFrequency (%)
구 53
 
3.8%
의 46
 
3.3%
한 41
 
2.9%
사 38
 
2.7%
에 35
 
2.5%
인 35
 
2.5%
이 34
 
2.4%
조 29
 
2.1%
자 26
 
1.8%
정 25
 
1.8%
Other values (228) 1050
74.4%
None
ValueCountFrequency (%)
· 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

게제일
Date

MISSING 

Distinct39
Distinct (%)73.6%
Missing33
Missing (%)38.4%
Memory size820.0 B
Minimum2007-04-01 00:00:00
Maximum2014-12-31 00:00:00
2023-12-12T23:25:00.856302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:25:00.975626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)

발간호(권)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct30
Distinct (%)39.0%
Missing9
Missing (%)10.5%
Infinite0
Infinite (%)0.0%
Mean165.48052
Minimum1
Maximum11126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-12T23:25:01.083928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q114
median21
Q331
95-th percentile46
Maximum11126
Range11125
Interquartile range (IQR)17

Descriptive statistics

Standard deviation1265.5657
Coefficient of variation (CV)7.6478231
Kurtosis76.983923
Mean165.48052
Median Absolute Deviation (MAD)9
Skewness8.7736094
Sum12742
Variance1601656.6
MonotonicityNot monotonic
2023-12-12T23:25:01.196691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
15 10
 
11.6%
22 7
 
8.1%
31 6
 
7.0%
32 4
 
4.7%
23 4
 
4.7%
21 4
 
4.7%
3 4
 
4.7%
12 3
 
3.5%
14 3
 
3.5%
9 3
 
3.5%
Other values (20) 29
33.7%
(Missing) 9
 
10.5%
ValueCountFrequency (%)
1 2
 
2.3%
3 4
 
4.7%
4 1
 
1.2%
9 3
 
3.5%
10 1
 
1.2%
11 3
 
3.5%
12 3
 
3.5%
13 2
 
2.3%
14 3
 
3.5%
15 10
11.6%
ValueCountFrequency (%)
11126 1
 
1.2%
80 1
 
1.2%
47 1
 
1.2%
46 2
 
2.3%
41 1
 
1.2%
38 2
 
2.3%
34 1
 
1.2%
33 1
 
1.2%
32 4
4.7%
31 6
7.0%

학술지명
Categorical

HIGH CORRELATION 

Distinct39
Distinct (%)45.3%
Missing0
Missing (%)0.0%
Memory size820.0 B
통계연구
20 
The Korean Journal of Applied Statistics
7 
응용통계연구
7 
한국통계학회 응용통계연구
5 
한국지역지리학회지
 
4
Other values (34)
43 

Length

Max length61
Median length47
Mean length13.465116
Min length4

Unique

Unique28 ?
Unique (%)32.6%

Sample

1st row응용통계연구
2nd row통계연구
3rd row통계연구
4th row통계연구
5th row고용과 직업 연구

Common Values

ValueCountFrequency (%)
통계연구 20
23.3%
The Korean Journal of Applied Statistics 7
 
8.1%
응용통계연구 7
 
8.1%
한국통계학회 응용통계연구 5
 
5.8%
한국지역지리학회지 4
 
4.7%
한국지도학회지 3
 
3.5%
조사연구 3
 
3.5%
Journal of the Korean Data Analysis Society 3
 
3.5%
품질경영학회지 2
 
2.3%
통계연구지 2
 
2.3%
Other values (29) 30
34.9%

Length

2023-12-12T23:25:01.336699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
통계연구 20
 
11.0%
journal 12
 
6.6%
of 12
 
6.6%
응용통계연구 12
 
6.6%
korean 11
 
6.0%
the 11
 
6.0%
statistics 9
 
4.9%
applied 7
 
3.8%
한국통계학회 6
 
3.3%
한국지역지리학회지 4
 
2.2%
Other values (57) 78
42.9%

작성년도
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.1512
Minimum2007
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-12T23:25:01.468203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2009
Q12009
median2011
Q32018
95-th percentile2020
Maximum2021
Range14
Interquartile range (IQR)9

Descriptive statistics

Standard deviation4.4045897
Coefficient of variation (CV)0.0021879081
Kurtosis-1.465778
Mean2013.1512
Median Absolute Deviation (MAD)2
Skewness0.44441833
Sum173131
Variance19.40041
MonotonicityNot monotonic
2023-12-12T23:25:01.588057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2009 23
26.7%
2010 15
17.4%
2020 10
11.6%
2018 10
11.6%
2013 5
 
5.8%
2011 4
 
4.7%
2019 4
 
4.7%
2017 4
 
4.7%
2014 3
 
3.5%
2012 2
 
2.3%
Other values (4) 6
 
7.0%
ValueCountFrequency (%)
2007 2
 
2.3%
2008 1
 
1.2%
2009 23
26.7%
2010 15
17.4%
2011 4
 
4.7%
2012 2
 
2.3%
2013 5
 
5.8%
2014 3
 
3.5%
2016 2
 
2.3%
2017 4
 
4.7%
ValueCountFrequency (%)
2021 1
 
1.2%
2020 10
11.6%
2019 4
 
4.7%
2018 10
11.6%
2017 4
 
4.7%
2016 2
 
2.3%
2014 3
 
3.5%
2013 5
5.8%
2012 2
 
2.3%
2011 4
 
4.7%

관련 연구과제명
Text

MISSING 

Distinct20
Distinct (%)95.2%
Missing65
Missing (%)75.6%
Memory size820.0 B
2023-12-12T23:25:01.893370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length21.571429
Min length10

Characters and Unicode

Total characters453
Distinct characters138
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)90.5%

Sample

1st row승법잡음모형을 이용한 가계조사 자료의 비밀보호
2nd row통계조사자료와 행정자료 간의 자료매칭기법 연구
3rd row생활시간조사의 방법론 개선방안
4th row사업체모집단 보완을 위한 행정자료 활용방안 연구
5th row현장조사 개선 방안
ValueCountFrequency (%)
연구 5
 
4.8%
소지역 3
 
2.9%
조사표 3
 
2.9%
및 3
 
2.9%
모형기반 3
 
2.9%
고용통계 2
 
1.9%
행정자료 2
 
1.9%
설계 2
 
1.9%
해외사례 2
 
1.9%
대상으로 2
 
1.9%
Other values (72) 78
74.3%
2023-12-12T23:25:02.388596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
85
 
18.8%
사 19
 
4.2%
조 14
 
3.1%
계 12
 
2.6%
방 9
 
2.0%
통 8
 
1.8%
구 7
 
1.5%
의 7
 
1.5%
이 7
 
1.5%
한 6
 
1.3%
Other values (128) 279
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 342
75.5%
Space Separator 85
 
18.8%
Decimal Number 12
 
2.6%
Uppercase Letter 8
 
1.8%
Dash Punctuation 3
 
0.7%
Lowercase Letter 2
 
0.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 19
 
5.6%
조 14
 
4.1%
계 12
 
3.5%
방 9
 
2.6%
통 8
 
2.3%
구 7
 
2.0%
의 7
 
2.0%
이 7
 
2.0%
한 6
 
1.8%
법 6
 
1.8%
Other values (110) 247
72.2%
Uppercase Letter
ValueCountFrequency (%)
I 2
25.0%
S 1
12.5%
A 1
12.5%
C 1
12.5%
G 1
12.5%
W 1
12.5%
T 1
12.5%
Decimal Number
ValueCountFrequency (%)
0 5
41.7%
2 3
25.0%
5 1
 
8.3%
1 1
 
8.3%
9 1
 
8.3%
8 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
b 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 342
75.5%
Common 101
 
22.3%
Latin 10
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 19
 
5.6%
조 14
 
4.1%
계 12
 
3.5%
방 9
 
2.6%
통 8
 
2.3%
구 7
 
2.0%
의 7
 
2.0%
이 7
 
2.0%
한 6
 
1.8%
법 6
 
1.8%
Other values (110) 247
72.2%
Common
ValueCountFrequency (%)
85
84.2%
0 5
 
5.0%
2 3
 
3.0%
- 3
 
3.0%
· 1
 
1.0%
5 1
 
1.0%
1 1
 
1.0%
9 1
 
1.0%
8 1
 
1.0%
Latin
ValueCountFrequency (%)
I 2
20.0%
S 1
10.0%
A 1
10.0%
C 1
10.0%
G 1
10.0%
b 1
10.0%
e 1
10.0%
W 1
10.0%
T 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 342
75.5%
ASCII 110
 
24.3%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
85
77.3%
0 5
 
4.5%
2 3
 
2.7%
- 3
 
2.7%
I 2
 
1.8%
S 1
 
0.9%
5 1
 
0.9%
A 1
 
0.9%
C 1
 
0.9%
1 1
 
0.9%
Other values (7) 7
 
6.4%
Hangul
ValueCountFrequency (%)
사 19
 
5.6%
조 14
 
4.1%
계 12
 
3.5%
방 9
 
2.6%
통 8
 
2.3%
구 7
 
2.0%
의 7
 
2.0%
이 7
 
2.0%
한 6
 
1.8%
법 6
 
1.8%
Other values (110) 247
72.2%
None
ValueCountFrequency (%)
· 1
100.0%

작성일
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Memory size820.0 B
<NA>
33 
2009-10-08
9 
2011-02-07
5 
2011-12-30
5 
2013-09-13
 
3
Other values (22)
31 

Length

Max length10
Median length10
Mean length7.6976744
Min length4

Unique

Unique17 ?
Unique (%)19.8%

Sample

1st row2009-10-08
2nd row2009-10-08
3rd row2009-06-08
4th row2009-06-08
5th row2009-06-08

Common Values

ValueCountFrequency (%)
<NA> 33
38.4%
2009-10-08 9
 
10.5%
2011-02-07 5
 
5.8%
2011-12-30 5
 
5.8%
2013-09-13 3
 
3.5%
2009-12-17 3
 
3.5%
2012-03-23 3
 
3.5%
2009-06-08 3
 
3.5%
2010-08-18 3
 
3.5%
2012-05-30 2
 
2.3%
Other values (17) 17
19.8%

Length

2023-12-12T23:25:02.544867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 33
38.4%
2009-10-08 9
 
10.5%
2011-02-07 5
 
5.8%
2011-12-30 5
 
5.8%
2013-09-13 3
 
3.5%
2009-12-17 3
 
3.5%
2012-03-23 3
 
3.5%
2009-06-08 3
 
3.5%
2010-08-18 3
 
3.5%
2012-05-30 2
 
2.3%
Other values (17) 17
19.8%

발간기관
Text

MISSING 

Distinct16
Distinct (%)64.0%
Missing61
Missing (%)70.9%
Memory size820.0 B
2023-12-12T23:25:02.719046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length10
Mean length7.44
Min length3

Characters and Unicode

Total characters186
Distinct characters54
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)40.0%

Sample

1st row서울대학교 출판부
2nd row조사연구학회
3rd row품질경역학회
4th row한국노인인력개발원
5th row통계청
ValueCountFrequency (%)
통계개발원 5
17.2%
통계청 3
 
10.3%
한국통계학회 3
 
10.3%
한국지도학회 2
 
6.9%
한국지역지리학회 2
 
6.9%
한국조사연구학회 2
 
6.9%
출판부 1
 
3.4%
한국데이타베이스학회 1
 
3.4%
조사연구학회 1
 
3.4%
한국노인인력개발원 1
 
3.4%
Other values (8) 8
27.6%
2023-12-12T23:25:03.110281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 17
 
9.1%
한 15
 
8.1%
회 15
 
8.1%
국 14
 
7.5%
통 11
 
5.9%
계 11
 
5.9%
원 8
 
4.3%
지 7
 
3.8%
발 6
 
3.2%
개 6
 
3.2%
Other values (44) 76
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 181
97.3%
Space Separator 4
 
2.2%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 17
 
9.4%
한 15
 
8.3%
회 15
 
8.3%
국 14
 
7.7%
통 11
 
6.1%
계 11
 
6.1%
원 8
 
4.4%
지 7
 
3.9%
발 6
 
3.3%
개 6
 
3.3%
Other values (42) 71
39.2%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 181
97.3%
Common 5
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 17
 
9.4%
한 15
 
8.3%
회 15
 
8.3%
국 14
 
7.7%
통 11
 
6.1%
계 11
 
6.1%
원 8
 
4.4%
지 7
 
3.9%
발 6
 
3.3%
개 6
 
3.3%
Other values (42) 71
39.2%
Common
ValueCountFrequency (%)
4
80.0%
, 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 181
97.3%
ASCII 5
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 17
 
9.4%
한 15
 
8.3%
회 15
 
8.3%
국 14
 
7.7%
통 11
 
6.1%
계 11
 
6.1%
원 8
 
4.4%
지 7
 
3.9%
발 6
 
3.3%
개 6
 
3.3%
Other values (42) 71
39.2%
ASCII
ValueCountFrequency (%)
4
80.0%
, 1
 
20.0%

발간호(호)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)12.2%
Missing12
Missing (%)14.0%
Infinite0
Infinite (%)0.0%
Mean3.3243243
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-12T23:25:03.251715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile9
Maximum19
Range18
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.6154467
Coefficient of variation (CV)1.0875734
Kurtosis8.9649632
Mean3.3243243
Median Absolute Deviation (MAD)1
Skewness2.7774639
Sum246
Variance13.071455
MonotonicityNot monotonic
2023-12-12T23:25:03.394991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 29
33.7%
2 14
16.3%
5 10
 
11.6%
3 7
 
8.1%
4 6
 
7.0%
9 4
 
4.7%
19 2
 
2.3%
6 1
 
1.2%
14 1
 
1.2%
(Missing) 12
14.0%
ValueCountFrequency (%)
1 29
33.7%
2 14
16.3%
3 7
 
8.1%
4 6
 
7.0%
5 10
 
11.6%
6 1
 
1.2%
9 4
 
4.7%
14 1
 
1.2%
19 2
 
2.3%
ValueCountFrequency (%)
19 2
 
2.3%
14 1
 
1.2%
9 4
 
4.7%
6 1
 
1.2%
5 10
 
11.6%
4 6
 
7.0%
3 7
 
8.1%
2 14
16.3%
1 29
33.7%

부서명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size820.0 B
연구기획실
25 
동향분석실
13 
통계방법연구실
9 
경제사회통계연구실
9 
조사연구실
8 
Other values (6)
22 

Length

Max length9
Median length5
Mean length5.6046512
Min length4

Unique

Unique2 ?
Unique (%)2.3%

Sample

1st row연구기획실
2nd row연구기획실
3rd row사회통계실
4th row연구기획실
5th row경제통계실

Common Values

ValueCountFrequency (%)
연구기획실 25
29.1%
동향분석실 13
15.1%
통계방법연구실 9
 
10.5%
경제사회통계연구실 9
 
10.5%
조사연구실 8
 
9.3%
통계분석실 8
 
9.3%
사회통계실 5
 
5.8%
<NA> 4
 
4.7%
통계개발원 3
 
3.5%
경제통계실 1
 
1.2%

Length

2023-12-12T23:25:03.603505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연구기획실 25
29.1%
동향분석실 13
15.1%
통계방법연구실 9
 
10.5%
경제사회통계연구실 9
 
10.5%
조사연구실 8
 
9.3%
통계분석실 8
 
9.3%
사회통계실 5
 
5.8%
na 4
 
4.7%
통계개발원 3
 
3.5%
경제통계실 1
 
1.2%

연구자명
Categorical

Distinct28
Distinct (%)32.6%
Missing0
Missing (%)0.0%
Memory size820.0 B
오진호
10 
박시내
7 
최은영
7 
김순영
7 
정동명
 
5
Other values (23)
50 

Length

Max length4
Median length3
Mean length3.0465116
Min length3

Unique

Unique10 ?
Unique (%)11.6%

Sample

1st row정동명
2nd row임경은
3rd row심수진
4th row정미옥
5th row박시내

Common Values

ValueCountFrequency (%)
오진호 10
 
11.6%
박시내 7
 
8.1%
최은영 7
 
8.1%
김순영 7
 
8.1%
정동명 5
 
5.8%
권태구 4
 
4.7%
<NA> 4
 
4.7%
김서영 4
 
4.7%
박영실 4
 
4.7%
정재호 3
 
3.5%
Other values (18) 31
36.0%

Length

2023-12-12T23:25:03.762665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
오진호 10
 
11.6%
최은영 7
 
8.1%
김순영 7
 
8.1%
박시내 7
 
8.1%
정동명 5
 
5.8%
권태구 4
 
4.7%
na 4
 
4.7%
김서영 4
 
4.7%
박영실 4
 
4.7%
김경미 3
 
3.5%
Other values (18) 31
36.0%

Interactions

2023-12-12T23:24:58.717567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:57.555093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:57.956027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:58.333528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:58.818511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:57.646693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:58.051180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:58.438729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:58.906325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:57.739793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:58.143662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:58.536173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:58.990192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:57.844052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:58.248772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:58.631871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:25:03.882878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번논문제목게제일발간호(권)학술지명작성년도관련 연구과제명작성일발간기관발간호(호)부서명연구자명
순번1.0000.9271.0000.0000.6290.7621.0000.9920.8670.0000.8140.676
논문제목0.9271.0000.9681.0000.9970.8871.0000.9721.0001.0000.6940.992
게제일1.0000.9681.000NaN0.9621.0000.9170.9820.9410.6390.9160.799
발간호(권)0.0001.000NaN1.0001.0000.000NaNNaNNaNNaN0.0000.597
학술지명0.6290.9970.9621.0001.0000.8440.9820.8440.9930.9520.9360.908
작성년도0.7620.8871.0000.0000.8441.0001.0000.9300.8340.4040.7190.865
관련 연구과제명1.0001.0000.917NaN0.9821.0001.0001.0001.0000.7771.0001.000
작성일0.9920.9720.982NaN0.8440.9301.0001.0000.8430.5940.8590.877
발간기관0.8671.0000.941NaN0.9930.8341.0000.8431.0000.9190.8180.756
발간호(호)0.0001.0000.639NaN0.9520.4040.7770.5940.9191.0000.0000.492
부서명0.8140.6940.9160.0000.9360.7191.0000.8590.8180.0001.0000.861
연구자명0.6760.9920.7990.5970.9080.8651.0000.8770.7560.4920.8611.000
2023-12-12T23:25:04.075145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학술지명작성일연구자명부서명
학술지명1.0000.3460.3840.532
작성일0.3461.0000.3860.434
연구자명0.3840.3861.0000.463
부서명0.5320.4340.4631.000
2023-12-12T23:25:04.214016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번발간호(권)작성년도발간호(호)학술지명작성일부서명연구자명
순번1.0000.3990.8980.2010.2570.7200.4550.338
발간호(권)0.3991.0000.5020.2470.7481.0000.0000.385
작성년도0.8980.5021.0000.1600.4100.4540.4370.432
발간호(호)0.2010.2470.1601.0000.6250.2040.0000.193
학술지명0.2570.7480.4100.6251.0000.3460.5320.384
작성일0.7201.0000.4540.2040.3461.0000.4340.386
부서명0.4550.0000.4370.0000.5320.4341.0000.463
연구자명0.3380.3850.4320.1930.3840.3860.4631.000

Missing values

2023-12-12T23:24:59.113433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:24:59.289194image/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.
2023-12-12T23:24:59.413530image/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

순번논문제목게제일발간호(권)학술지명작성년도관련 연구과제명작성일발간기관발간호(호)부서명연구자명
025잡음을 이용한 가계조사자료의 정보노출제한방법2009-02-0122응용통계연구2009승법잡음모형을 이용한 가계조사 자료의 비밀보호2009-10-08<NA>1연구기획실정동명
122통계조사자료와 행정자료 간의 통계적 매칭기법에 관한 연구2009-04-0114통계연구2009통계조사자료와 행정자료 간의 자료매칭기법 연구2009-10-08<NA>1연구기획실임경은
234생활시간조사 개선을 위한 방법론 제안2009-04-0114통계연구2009생활시간조사의 방법론 개선방안2009-06-08<NA>1사회통계실심수진
336사회보험자료의 통계목적 활용가능성 연구: 사업체 기본정보 중심으로2009-04-0114통계연구2009사업체모집단 보완을 위한 행정자료 활용방안 연구2009-06-08<NA>1연구기획실정미옥
437한국 고령근로자의 노동시장 이탈에 관한 종단적 분석2009-05-013고용과 직업 연구2009<NA>2009-06-08<NA>1경제통계실박시내
538자기통제력의 세대간 전이과정에 대한 연구2008-05-0133사회이론2009<NA>2009-06-09<NA><NA>사회통계실이희길
639Fellegi-Holt 기법을 이용한 에디팅의 시도 및 분석2009-08-0122응용통계연구2009<NA>2012-03-27<NA>4연구기획실이의규
740응답거부와 부재율이 무응답오차에 미치는 영향2009-06-0122응용통계연구2009현장조사 개선 방안2009-10-08<NA>3연구기획실김서영
841청소년의 범죄피해경험: 자기통제이론의 적용2009-06-0112한국사회연구2009<NA>2009-12-17<NA><NA>사회통계실박영실
9428도시-농촌 간 인구이동 특성: 고령 인구를 중심으로2012-02-291농촌사회 변화의 인식론적 이해(학술서적)2012<NA>2011-12-30서울대학교 출판부1동향분석실최은영
순번논문제목게제일발간호(권)학술지명작성년도관련 연구과제명작성일발간기관발간호(호)부서명연구자명
761560A comparison of mortality projection by different time period in time series<NA>31한국통계학회 응용통계연구2018<NA><NA><NA>1통계분석실오진호
771561A Study on Forecasting Cohort Incomplete Fertility for Korea<NA>41한국인구학2018<NA><NA><NA>1통계분석실오진호
781614Stochastic projection on International Migration Using Coherent Functional Data Model<NA>32The Korean Journal of Applied Statistics2019<NA><NA><NA>4통계방법연구실김순영
791632자영업가구의 채무불이행 결정요인에 관한 실증연구<NA>22Journal of the Korean Data Analysis Society2020<NA><NA><NA>1경제사회통계연구실권태구
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