Overview

Dataset statistics

Number of variables6
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory58.7 B

Variable types

Numeric5
Categorical1

Dataset

Description1999년부터 2021년까지의 연도별 예비타당성 조사 시계열 자료입니다. *수치가 기본단위보다 적거나 수치가 없을 경우 0으로 표시했습니다. *2018년 2개, 2019년 6개, 2020년 4개, 2021년 1개의 철회사업 사업비는 제외했습니다.
URLhttps://www.data.go.kr/data/15086899/fileData.do

Alerts

데이터기준일 has constant value ""Constant
조사대상_사업수(개) is highly overall correlated with 타당성 있음_사업수(개)High correlation
조사대상_사업비(조원) is highly overall correlated with 타당성 있음_사업비(조원)High correlation
타당성 있음_사업수(개) is highly overall correlated with 조사대상_사업수(개) and 1 other fieldsHigh correlation
타당성 있음_사업비(조원) is highly overall correlated with 조사대상_사업비(조원) and 1 other fieldsHigh correlation
연도 has unique valuesUnique
조사대상_사업비(조원) has unique valuesUnique
타당성 있음_사업비(조원) has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:13:15.996329
Analysis finished2023-12-12 17:13:19.298685
Duration3.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2010
Minimum1999
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T02:13:19.377017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1999
5-th percentile2000.1
Q12004.5
median2010
Q32015.5
95-th percentile2019.9
Maximum2021
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.0033742935
Kurtosis-1.2
Mean2010
Median Absolute Deviation (MAD)6
Skewness0
Sum46230
Variance46
MonotonicityStrictly increasing
2023-12-13T02:13:19.538398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1999 1
 
4.3%
2000 1
 
4.3%
2021 1
 
4.3%
2020 1
 
4.3%
2019 1
 
4.3%
2018 1
 
4.3%
2017 1
 
4.3%
2016 1
 
4.3%
2015 1
 
4.3%
2014 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1999 1
4.3%
2000 1
4.3%
2001 1
4.3%
2002 1
4.3%
2003 1
4.3%
2004 1
4.3%
2005 1
4.3%
2006 1
4.3%
2007 1
4.3%
2008 1
4.3%
ValueCountFrequency (%)
2021 1
4.3%
2020 1
4.3%
2019 1
4.3%
2018 1
4.3%
2017 1
4.3%
2016 1
4.3%
2015 1
4.3%
2014 1
4.3%
2013 1
4.3%
2012 1
4.3%

조사대상_사업수(개)
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.347826
Minimum19
Maximum77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T02:13:19.689703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile20.4
Q130
median39
Q348.5
95-th percentile70.9
Maximum77
Range58
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation15.443765
Coefficient of variation (CV)0.38276573
Kurtosis0.34679146
Mean40.347826
Median Absolute Deviation (MAD)9
Skewness0.87097681
Sum928
Variance238.50988
MonotonicityNot monotonic
2023-12-13T02:13:19.906633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
30 3
 
13.0%
20 1
 
4.3%
19 1
 
4.3%
24 1
 
4.3%
33 1
 
4.3%
29 1
 
4.3%
40 1
 
4.3%
39 1
 
4.3%
34 1
 
4.3%
44 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
19 1
 
4.3%
20 1
 
4.3%
24 1
 
4.3%
26 1
 
4.3%
29 1
 
4.3%
30 3
13.0%
32 1
 
4.3%
33 1
 
4.3%
34 1
 
4.3%
39 1
 
4.3%
ValueCountFrequency (%)
77 1
4.3%
72 1
4.3%
61 1
4.3%
55 1
4.3%
52 1
4.3%
51 1
4.3%
46 1
4.3%
44 1
4.3%
43 1
4.3%
41 1
4.3%

조사대상_사업비(조원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.852174
Minimum7
Maximum35.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T02:13:20.054329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile8.3
Q113.75
median17.8
Q322.45
95-th percentile34.4
Maximum35.3
Range28.3
Interquartile range (IQR)8.7

Descriptive statistics

Standard deviation7.2809758
Coefficient of variation (CV)0.38621412
Kurtosis0.64844969
Mean18.852174
Median Absolute Deviation (MAD)4.3
Skewness0.71640825
Sum433.6
Variance53.012609
MonotonicityNot monotonic
2023-12-13T02:13:20.226923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
27.2 1
 
4.3%
14.0 1
 
4.3%
17.8 1
 
4.3%
23.2 1
 
4.3%
15.0 1
 
4.3%
13.1 1
 
4.3%
21.9 1
 
4.3%
17.1 1
 
4.3%
8.0 1
 
4.3%
13.5 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
7.0 1
4.3%
8.0 1
4.3%
11.0 1
4.3%
12.4 1
4.3%
13.1 1
4.3%
13.5 1
4.3%
14.0 1
4.3%
15.0 1
4.3%
16.7 1
4.3%
17.1 1
4.3%
ValueCountFrequency (%)
35.3 1
4.3%
35.2 1
4.3%
27.2 1
4.3%
24.5 1
4.3%
23.2 1
4.3%
23.0 1
4.3%
21.9 1
4.3%
21.5 1
4.3%
20.1 1
4.3%
19.8 1
4.3%

타당성 있음_사업수(개)
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.391304
Minimum12
Maximum59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T02:13:20.398415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile14
Q117
median25
Q331.5
95-th percentile47.7
Maximum59
Range47
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation12.568862
Coefficient of variation (CV)0.47625011
Kurtosis0.59931282
Mean26.391304
Median Absolute Deviation (MAD)9
Skewness1.1078472
Sum607
Variance157.97628
MonotonicityNot monotonic
2023-12-13T02:13:20.557965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
14 2
 
8.7%
19 2
 
8.7%
28 2
 
8.7%
26 2
 
8.7%
20 2
 
8.7%
15 2
 
8.7%
25 2
 
8.7%
12 1
 
4.3%
16 1
 
4.3%
18 1
 
4.3%
Other values (6) 6
26.1%
ValueCountFrequency (%)
12 1
4.3%
14 2
8.7%
15 2
8.7%
16 1
4.3%
18 1
4.3%
19 2
8.7%
20 2
8.7%
25 2
8.7%
26 2
8.7%
28 2
8.7%
ValueCountFrequency (%)
59 1
4.3%
48 1
4.3%
45 1
4.3%
41 1
4.3%
39 1
4.3%
35 1
4.3%
28 2
8.7%
26 2
8.7%
25 2
8.7%
20 2
8.7%

타당성 있음_사업비(조원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.513043
Minimum4.2
Maximum24.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T02:13:20.689397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.2
5-th percentile4.66
Q17.9
median10.2
Q314.25
95-th percentile22.5
Maximum24.9
Range20.7
Interquartile range (IQR)6.35

Descriptive statistics

Standard deviation5.4828082
Coefficient of variation (CV)0.47622579
Kurtosis0.60298088
Mean11.513043
Median Absolute Deviation (MAD)3.4
Skewness0.94072108
Sum264.8
Variance30.061186
MonotonicityNot monotonic
2023-12-13T02:13:20.828080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
7.4 1
 
4.3%
6.1 1
 
4.3%
16.8 1
 
4.3%
9.7 1
 
4.3%
14.9 1
 
4.3%
10.1 1
 
4.3%
10.7 1
 
4.3%
11.1 1
 
4.3%
4.6 1
 
4.3%
10.2 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
4.2 1
4.3%
4.6 1
4.3%
5.2 1
4.3%
6.1 1
4.3%
6.5 1
4.3%
7.4 1
4.3%
8.4 1
4.3%
9.3 1
4.3%
9.7 1
4.3%
10.0 1
4.3%
ValueCountFrequency (%)
24.9 1
4.3%
23.0 1
4.3%
18.0 1
4.3%
16.8 1
4.3%
16.3 1
4.3%
14.9 1
4.3%
13.6 1
4.3%
13.3 1
4.3%
11.1 1
4.3%
10.7 1
4.3%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2022-04-08
23 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-04-08
2nd row2022-04-08
3rd row2022-04-08
4th row2022-04-08
5th row2022-04-08

Common Values

ValueCountFrequency (%)
2022-04-08 23
100.0%

Length

2023-12-13T02:13:20.970806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:13:21.074079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-04-08 23
100.0%

Interactions

2023-12-13T02:13:18.492413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:16.203129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:17.000523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:17.466300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:17.946898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:18.594639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:16.312642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:17.109627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:17.566360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:18.059589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:18.722457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:16.397581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:17.200344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:17.673168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:18.179952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:18.825294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:16.496164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:17.286766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:17.750742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:18.289142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:18.943699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:16.894778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:17.373747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:17.834790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:18.390011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:13:21.135653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도조사대상_사업수(개)조사대상_사업비(조원)타당성 있음_사업수(개)타당성 있음_사업비(조원)
연도1.0000.5780.3060.5720.261
조사대상_사업수(개)0.5781.0000.6430.8760.741
조사대상_사업비(조원)0.3060.6431.0000.7010.722
타당성 있음_사업수(개)0.5720.8760.7011.0000.595
타당성 있음_사업비(조원)0.2610.7410.7220.5951.000
2023-12-13T02:13:21.335536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도조사대상_사업수(개)조사대상_사업비(조원)타당성 있음_사업수(개)타당성 있음_사업비(조원)
연도1.000-0.147-0.1320.2010.286
조사대상_사업수(개)-0.1471.0000.3520.8680.454
조사대상_사업비(조원)-0.1320.3521.0000.2140.582
타당성 있음_사업수(개)0.2010.8680.2141.0000.553
타당성 있음_사업비(조원)0.2860.4540.5820.5531.000

Missing values

2023-12-13T02:13:19.105589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:13:19.243159image/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

연도조사대상_사업수(개)조사대상_사업비(조원)타당성 있음_사업수(개)타당성 있음_사업비(조원)데이터기준일
019992027.2127.42022-04-08
120003014.0156.12022-04-08
220014119.8146.52022-04-08
320023020.11410.02022-04-08
420033217.61913.62022-04-08
520045518.74113.32022-04-08
620053012.4198.42022-04-08
720065221.5289.32022-04-08
820074616.72610.52022-04-08
920084311.0285.22022-04-08
연도조사대상_사업수(개)조사대상_사업비(조원)타당성 있음_사업수(개)타당성 있음_사업비(조원)데이터기준일
1320125124.53918.02022-04-08
142013267.0164.22022-04-08
1520144413.53510.22022-04-08
162015348.0254.62022-04-08
1720163917.12611.12022-04-08
1820174021.92010.72022-04-08
1920182913.12010.12022-04-08
2020193315.02514.92022-04-08
2120202423.2189.72022-04-08
2220211917.81516.82022-04-08