Overview

Dataset statistics

Number of variables5
Number of observations42
Missing cells32
Missing cells (%)15.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory45.1 B

Variable types

Categorical2
Numeric1
DateTime2

Dataset

Description2014-2019년 문예진흥기금 공모사업 중 문학 분야 "집필공간운영" 지원 사업의 타 사업 연계 실적(예: 타 사업 시작일, 타 사업 종료일, 연계 건수)
Author한국문화예술위원회
URLhttps://www.data.go.kr/data/15076485/fileData.do

Alerts

문학단체명 is highly overall correlated with 연계건수(건)High correlation
연계건수(건) is highly overall correlated with 문학단체명High correlation
타사업시작일 has 16 (38.1%) missing valuesMissing
타사업종료일 has 16 (38.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 17:41:39.145597
Analysis finished2023-12-12 17:41:39.643772
Duration0.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

문학단체명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size468.0 B
*지**단
9 
*날**날
9 
*버**집
8 
*을**집
6 
*1**학
5 
Other values (2)
5 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row*악**원
2nd row*을**집
3rd row*1**학
4th row*지**단
5th row*날**날

Common Values

ValueCountFrequency (%)
*지**단 9
21.4%
*날**날 9
21.4%
*버**집 8
19.0%
*을**집 6
14.3%
*1**학 5
11.9%
*악**원 4
9.5%
*산**꽃 1
 
2.4%

Length

2023-12-13T02:41:39.703692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:41:39.810145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지**단 9
21.4%
날**날 9
21.4%
버**집 8
19.0%
을**집 6
14.3%
1**학 5
11.9%
악**원 4
9.5%
산**꽃 1
 
2.4%

사업연도
Real number (ℝ)

Distinct6
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.5476
Minimum2014
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-13T02:41:39.939707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12015
median2017
Q32018
95-th percentile2019
Maximum2019
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.5957624
Coefficient of variation (CV)0.00079133385
Kurtosis-1.1645278
Mean2016.5476
Median Absolute Deviation (MAD)1
Skewness0.04147244
Sum84695
Variance2.5464576
MonotonicityIncreasing
2023-12-13T02:41:40.056702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2015 10
23.8%
2017 9
21.4%
2018 7
16.7%
2016 6
14.3%
2019 6
14.3%
2014 4
 
9.5%
ValueCountFrequency (%)
2014 4
 
9.5%
2015 10
23.8%
2016 6
14.3%
2017 9
21.4%
2018 7
16.7%
2019 6
14.3%
ValueCountFrequency (%)
2019 6
14.3%
2018 7
16.7%
2017 9
21.4%
2016 6
14.3%
2015 10
23.8%
2014 4
 
9.5%

타사업시작일
Date

MISSING 

Distinct25
Distinct (%)96.2%
Missing16
Missing (%)38.1%
Memory size468.0 B
Minimum2014-09-02 00:00:00
Maximum2019-10-01 00:00:00
2023-12-13T02:41:40.164922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:40.295021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

타사업종료일
Date

MISSING 

Distinct26
Distinct (%)100.0%
Missing16
Missing (%)38.1%
Memory size468.0 B
Minimum2014-09-27 00:00:00
Maximum2019-10-31 00:00:00
2023-12-13T02:41:40.410283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:40.530442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

연계건수(건)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
1
27 
0
15 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 27
64.3%
0 15
35.7%

Length

2023-12-13T02:41:40.655941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:41:40.958986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 27
64.3%
0 15
35.7%

Interactions

2023-12-13T02:41:39.319414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:41:41.020480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
문학단체명사업연도타사업시작일타사업종료일연계건수(건)
문학단체명1.0000.0000.6991.0000.879
사업연도0.0001.0001.0001.0000.000
타사업시작일0.6991.0001.0001.000NaN
타사업종료일1.0001.0001.0001.000NaN
연계건수(건)0.8790.000NaNNaN1.000
2023-12-13T02:41:41.123724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연계건수(건)문학단체명
연계건수(건)1.0000.887
문학단체명0.8871.000
2023-12-13T02:41:41.213113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업연도문학단체명연계건수(건)
사업연도1.0000.0000.133
문학단체명0.0001.0000.887
연계건수(건)0.1330.8871.000

Missing values

2023-12-13T02:41:39.433809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:41:39.520230image/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.
2023-12-13T02:41:39.599603image/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

문학단체명사업연도타사업시작일타사업종료일연계건수(건)
0*악**원2014<NA><NA>0
1*을**집2014<NA><NA>0
2*1**학2014<NA><NA>0
3*지**단20142014-09-022014-09-271
4*날**날20152015-11-172015-11-181
5*날**날20152015-10-302015-10-301
6*날**날20152015-11-202015-11-211
7*악**원2015<NA><NA>0
8*산**꽃2015<NA><NA>0
9*을**집2015<NA><NA>0
문학단체명사업연도타사업시작일타사업종료일연계건수(건)
32*날**날20182018-10-292018-11-021
33*을**집2018<NA><NA>0
34*1**학2018<NA><NA>0
35*지**단20182018-08-312018-10-011
36*을**집2019<NA><NA>0
37*지**단20192019-09-012019-10-021
38*지**단20192019-09-182019-09-181
39*버**집20192019-08-312019-08-311
40*버**집20192019-10-012019-10-311
41*악**원2019<NA><NA>0