Overview

Dataset statistics

Number of variables3
Number of observations30
Missing cells8
Missing cells (%)8.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory912.0 B
Average record size in memory30.4 B

Variable types

Categorical1
Numeric2

Dataset

Description큐넷에 제공되는 국가자격(시행, 미시행 포함)과 관련한 통계 자료에 대해서 기준년도, 등록일시, 통계기준년도 정보 등을 제공한다
URLhttps://www.data.go.kr/data/15120653/fileData.do

Alerts

기준년도 is highly overall correlated with 등록일시High correlation
등록일시 is highly overall correlated with 기준년도High correlation
등록일시 has 8 (26.7%) missing valuesMissing

Reproduction

Analysis started2023-12-13 00:57:28.528373
Analysis finished2023-12-13 00:57:29.007418
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계기준년도구분
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
I
15 
Q
15 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowQ
3rd rowQ
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
I 15
50.0%
Q 15
50.0%

Length

2023-12-13T09:57:29.057075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:57:29.131224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 15
50.0%
q 15
50.0%

기준년도
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015
Minimum2008
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T09:57:29.196004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2008.45
Q12011.25
median2015
Q32018.75
95-th percentile2021.55
Maximum2022
Range14
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation4.3943537
Coefficient of variation (CV)0.0021808207
Kurtosis-1.2095663
Mean2015
Median Absolute Deviation (MAD)4
Skewness0
Sum60450
Variance19.310345
MonotonicityNot monotonic
2023-12-13T09:57:29.280150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2009 2
 
6.7%
2011 2
 
6.7%
2015 2
 
6.7%
2014 2
 
6.7%
2008 2
 
6.7%
2010 2
 
6.7%
2012 2
 
6.7%
2013 2
 
6.7%
2018 2
 
6.7%
2019 2
 
6.7%
Other values (5) 10
33.3%
ValueCountFrequency (%)
2008 2
6.7%
2009 2
6.7%
2010 2
6.7%
2011 2
6.7%
2012 2
6.7%
2013 2
6.7%
2014 2
6.7%
2015 2
6.7%
2016 2
6.7%
2017 2
6.7%
ValueCountFrequency (%)
2022 2
6.7%
2021 2
6.7%
2020 2
6.7%
2019 2
6.7%
2018 2
6.7%
2017 2
6.7%
2016 2
6.7%
2015 2
6.7%
2014 2
6.7%
2013 2
6.7%

등록일시
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)63.6%
Missing8
Missing (%)26.7%
Infinite0
Infinite (%)0.0%
Mean1.4723193 × 1013
Minimum20160310
Maximum2.0230306 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T09:57:29.373710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20160310
5-th percentile1.0084255 × 1010
Q15.1886032 × 1012
median2.0180418 × 1013
Q32.0207783 × 1013
95-th percentile2.0229811 × 1013
Maximum2.0230306 × 1013
Range2.0230286 × 1013
Interquartile range (IQR)1.501918 × 1013

Descriptive statistics

Standard deviation9.144276 × 1012
Coefficient of variation (CV)0.62107968
Kurtosis-0.88605834
Mean1.4723193 × 1013
Median Absolute Deviation (MAD)3.0212064 × 1010
Skewness-1.0969616
Sum3.2391024 × 1014
Variance8.3617784 × 1025
MonotonicityNot monotonic
2023-12-13T09:57:29.471471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
20160310 2
 
6.7%
20150206091959 2
 
6.7%
201302061405 2
 
6.7%
201402191010 2
 
6.7%
20220408094400 2
 
6.7%
20170315095959 2
 
6.7%
20180418155959 2
 
6.7%
20230306111200 2
 
6.7%
20190221131039 1
 
3.3%
20190221131148 1
 
3.3%
Other values (4) 4
13.3%
(Missing) 8
26.7%
ValueCountFrequency (%)
20160310 2
6.7%
201302061405 2
6.7%
201402191010 2
6.7%
20150206091959 2
6.7%
20170315095959 2
6.7%
20180418155959 2
6.7%
20190221131039 1
3.3%
20190221131148 1
3.3%
20200219161529 1
3.3%
20200219161558 1
3.3%
ValueCountFrequency (%)
20230306111200 2
6.7%
20220408094400 2
6.7%
20210304153456 1
3.3%
20210304153433 1
3.3%
20200219161558 1
3.3%
20200219161529 1
3.3%
20190221131148 1
3.3%
20190221131039 1
3.3%
20180418155959 2
6.7%
20170315095959 2
6.7%

Interactions

2023-12-13T09:57:28.776629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:57:28.602312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:57:28.841659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:57:28.687812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:57:29.541538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계기준년도구분기준년도등록일시
통계기준년도구분1.0000.0000.000
기준년도0.0001.0001.000
등록일시0.0001.0001.000
2023-12-13T09:57:29.614884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도등록일시통계기준년도구분
기준년도1.0000.9450.000
등록일시0.9451.0000.000
통계기준년도구분0.0000.0001.000

Missing values

2023-12-13T09:57:28.930891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:57:28.985755image/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

통계기준년도구분기준년도등록일시
0I2009<NA>
1Q2009<NA>
2Q2011<NA>
3I2011<NA>
4I201520160310
5Q201520160310
6I201420150206091959
7Q201420150206091959
8I2008<NA>
9Q2008<NA>
통계기준년도구분기준년도등록일시
20Q202020210304153433
21I202020210304153456
22I202120220408094400
23Q202120220408094400
24I201620170315095959
25Q201620170315095959
26I201720180418155959
27Q201720180418155959
28I202220230306111200
29Q202220230306111200