Overview

Dataset statistics

Number of variables3
Number of observations181
Missing cells0
Missing cells (%)0.0%
Duplicate rows12
Duplicate rows (%)6.6%
Total size in memory4.5 KiB
Average record size in memory25.7 B

Variable types

Text1
Numeric1
Categorical1

Dataset

Description2014-2019년 문예진흥기금 공모사업 중 문학 분야 "문예지발간" 지원 사업의 전자책/웹진 서비스 여부
Author한국문화예술위원회
URLhttps://www.data.go.kr/data/15076421/fileData.do

Alerts

Dataset has 12 (6.6%) duplicate rowsDuplicates
사업연도 is highly overall correlated with 온라인문예지서비스추진여부High correlation
온라인문예지서비스추진여부 is highly overall correlated with 사업연도High correlation

Reproduction

Analysis started2023-12-12 02:35:36.334155
Analysis finished2023-12-12 02:35:36.689179
Duration0.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

문학단체명
Text

Distinct62
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T11:35:36.850134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters905
Distinct characters68
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

Unique19 ?
Unique (%)10.5%

Sample

1st row*제**부
2nd row*국**회
3rd row*1**학
4th row*학**네
5th row*학**상
ValueCountFrequency (%)
국**회 45
24.9%
대**학 8
 
4.4%
제**부 5
 
2.8%
학**네 4
 
2.2%
학**상 4
 
2.2%
비**비 4
 
2.2%
학**사 4
 
2.2%
음**음 4
 
2.2%
년**작 3
 
1.7%
학**당 3
 
1.7%
Other values (52) 97
53.6%
2023-12-12T11:35:37.171911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 543
60.0%
국 54
 
6.0%
회 48
 
5.3%
학 41
 
4.5%
사 17
 
1.9%
음 11
 
1.2%
대 10
 
1.1%
시 9
 
1.0%
서 9
 
1.0%
비 8
 
0.9%
Other values (58) 155
 
17.1%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 543
60.0%
Other Letter 360
39.8%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 54
 
15.0%
회 48
 
13.3%
학 41
 
11.4%
사 17
 
4.7%
음 11
 
3.1%
대 10
 
2.8%
시 9
 
2.5%
서 9
 
2.5%
비 8
 
2.2%
린 7
 
1.9%
Other values (56) 146
40.6%
Other Punctuation
ValueCountFrequency (%)
* 543
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 545
60.2%
Hangul 360
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 54
 
15.0%
회 48
 
13.3%
학 41
 
11.4%
사 17
 
4.7%
음 11
 
3.1%
대 10
 
2.8%
시 9
 
2.5%
서 9
 
2.5%
비 8
 
2.2%
린 7
 
1.9%
Other values (56) 146
40.6%
Common
ValueCountFrequency (%)
* 543
99.6%
1 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 545
60.2%
Hangul 360
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 543
99.6%
1 2
 
0.4%
Hangul
ValueCountFrequency (%)
국 54
 
15.0%
회 48
 
13.3%
학 41
 
11.4%
사 17
 
4.7%
음 11
 
3.1%
대 10
 
2.8%
시 9
 
2.5%
서 9
 
2.5%
비 8
 
2.2%
린 7
 
1.9%
Other values (56) 146
40.6%

사업연도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.7624
Minimum2014
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T11:35:37.293170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12014
median2018
Q32019
95-th percentile2019
Maximum2019
Range5
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.0395867
Coefficient of variation (CV)0.0010113173
Kurtosis-1.5893876
Mean2016.7624
Median Absolute Deviation (MAD)1
Skewness-0.35284142
Sum365034
Variance4.1599141
MonotonicityIncreasing
2023-12-12T11:35:37.415651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2014 51
28.2%
2018 50
27.6%
2019 47
26.0%
2015 14
 
7.7%
2017 13
 
7.2%
2016 6
 
3.3%
ValueCountFrequency (%)
2014 51
28.2%
2015 14
 
7.7%
2016 6
 
3.3%
2017 13
 
7.2%
2018 50
27.6%
2019 47
26.0%
ValueCountFrequency (%)
2019 47
26.0%
2018 50
27.6%
2017 13
 
7.2%
2016 6
 
3.3%
2015 14
 
7.7%
2014 51
28.2%

온라인문예지서비스추진여부
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
134 
N
22 
Y
17 
미응답
 
8

Length

Max length4
Median length4
Mean length3.3093923
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 134
74.0%
N 22
 
12.2%
Y 17
 
9.4%
미응답 8
 
4.4%

Length

2023-12-12T11:35:37.557796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:35:37.695553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 134
74.0%
n 22
 
12.2%
y 17
 
9.4%
미응답 8
 
4.4%

Interactions

2023-12-12T11:35:36.433965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:35:37.771262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
문학단체명사업연도온라인문예지서비스추진여부
문학단체명1.0000.0000.324
사업연도0.0001.000NaN
온라인문예지서비스추진여부0.324NaN1.000
2023-12-12T11:35:37.863067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업연도온라인문예지서비스추진여부
사업연도1.0001.000
온라인문예지서비스추진여부1.0001.000

Missing values

2023-12-12T11:35:36.572543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:35:36.659942image/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

문학단체명사업연도온라인문예지서비스추진여부
0*제**부2014<NA>
1*국**회2014<NA>
2*1**학2014<NA>
3*학**네2014<NA>
4*학**상2014<NA>
5*음**사2014<NA>
6*천**학2014<NA>
7*행**사2014<NA>
8*년**작2014<NA>
9*간**선2014<NA>
문학단체명사업연도온라인문예지서비스추진여부
171*서**망2019N
172*와**시2019미응답
173*국**회2019Y
174*시**아2019N
175*국**회2019Y
176*행**사2019미응답
177*국**연2019Y
178*대**학2019N
179*국**회2019미응답
180*천**학2019N

Duplicate rows

Most frequently occurring

문학단체명사업연도온라인문예지서비스추진여부# duplicates
0*국**회2014<NA>10
3*국**회2017<NA>10
4*국**회2018<NA>10
2*국**회2016<NA>5
6*국**회2019Y4
1*국**회2015<NA>2
5*국**회2019N2
7*국**회2019미응답2
8*대**학2014<NA>2
9*대**학2015<NA>2