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

Description국가채무(금융성, 적자성), GDP 대비비중 등 국가채무 시계열 자료
Author한국재정정보원
URLhttps://www.data.go.kr/data/15077718/fileData.do

Alerts

연도 is highly overall correlated with 국가채무(조원) and 3 other fieldsHigh correlation
국가채무(조원) is highly overall correlated with 연도 and 4 other fieldsHigh correlation
적자성 채무(조원) is highly overall correlated with 연도 and 4 other fieldsHigh correlation
금융성 채무(조원) is highly overall correlated with 연도 and 3 other fieldsHigh correlation
국내총생산(GDP)대비비중(퍼센트) is highly overall correlated with 연도 and 3 other fieldsHigh correlation
기준 is highly overall correlated with 국가채무(조원) and 1 other fieldsHigh correlation
기준 is highly imbalanced (67.6%)Imbalance
연도 has unique valuesUnique
국가채무(조원) has unique valuesUnique
적자성 채무(조원) has unique valuesUnique
금융성 채무(조원) has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:44:06.637137
Analysis finished2023-12-12 12:44:09.839811
Duration3.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011
Minimum2000
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:44:09.892776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2001.1
Q12005.5
median2011
Q32016.5
95-th percentile2020.9
Maximum2022
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.0033726156
Kurtosis-1.2
Mean2011
Median Absolute Deviation (MAD)6
Skewness0
Sum46253
Variance46
MonotonicityStrictly increasing
2023-12-12T21:44:09.995696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
2000 1
 
4.3%
2001 1
 
4.3%
2022 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%
Other values (13) 13
56.5%
ValueCountFrequency (%)
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%
2009 1
4.3%
ValueCountFrequency (%)
2022 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%
2013 1
4.3%

기준
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
결산
21 
2차 추경
 
1
1차 추경
 
1

Length

Max length5
Median length2
Mean length2.2608696
Min length2

Unique

Unique2 ?
Unique (%)8.7%

Sample

1st row결산
2nd row결산
3rd row결산
4th row결산
5th row결산

Common Values

ValueCountFrequency (%)
결산 21
91.3%
2차 추경 1
 
4.3%
1차 추경 1
 
4.3%

Length

2023-12-12T21:44:10.107068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:44:10.196480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
결산 21
84.0%
추경 2
 
8.0%
2차 1
 
4.0%
1차 1
 
4.0%

국가채무(조원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean464.49565
Minimum111.2
Maximum1075.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:44:10.288251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum111.2
5-th percentile123
Q1265.3
median420.5
Q3643.55
95-th percentile953.43
Maximum1075.7
Range964.5
Interquartile range (IQR)378.25

Descriptive statistics

Standard deviation272.11884
Coefficient of variation (CV)0.58583722
Kurtosis-0.28043742
Mean464.49565
Median Absolute Deviation (MAD)206.4
Skewness0.6431416
Sum10683.4
Variance74048.664
MonotonicityStrictly increasing
2023-12-12T21:44:10.400933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
111.2 1
 
4.3%
121.8 1
 
4.3%
1075.7 1
 
4.3%
965.3 1
 
4.3%
846.6 1
 
4.3%
723.2 1
 
4.3%
680.5 1
 
4.3%
660.2 1
 
4.3%
626.9 1
 
4.3%
591.5 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
111.2 1
4.3%
121.8 1
4.3%
133.8 1
4.3%
165.8 1
4.3%
203.7 1
4.3%
247.9 1
4.3%
282.7 1
4.3%
299.2 1
4.3%
309.0 1
4.3%
359.6 1
4.3%
ValueCountFrequency (%)
1075.7 1
4.3%
965.3 1
4.3%
846.6 1
4.3%
723.2 1
4.3%
680.5 1
4.3%
660.2 1
4.3%
626.9 1
4.3%
591.5 1
4.3%
533.2 1
4.3%
489.8 1
4.3%

적자성 채무(조원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.83913
Minimum42
Maximum696.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:44:10.511115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42
5-th percentile43.01
Q1110.35
median206.9
Q3367.35
95-th percentile599.64
Maximum696.4
Range654.4
Interquartile range (IQR)257

Descriptive statistics

Standard deviation184.57454
Coefficient of variation (CV)0.73877356
Kurtosis0.22362013
Mean249.83913
Median Absolute Deviation (MAD)128.7
Skewness0.91281443
Sum5746.3
Variance34067.762
MonotonicityStrictly increasing
2023-12-12T21:44:10.609978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
42.0 1
 
4.3%
43.0 1
 
4.3%
696.4 1
 
4.3%
609.3 1
 
4.3%
512.7 1
 
4.3%
407.6 1
 
4.3%
379.2 1
 
4.3%
374.8 1
 
4.3%
359.9 1
 
4.3%
330.8 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
42.0 1
4.3%
43.0 1
4.3%
43.1 1
4.3%
60.1 1
4.3%
78.2 1
4.3%
100.8 1
4.3%
119.9 1
4.3%
127.4 1
4.3%
132.6 1
4.3%
168.8 1
4.3%
ValueCountFrequency (%)
696.4 1
4.3%
609.3 1
4.3%
512.7 1
4.3%
407.6 1
4.3%
379.2 1
4.3%
374.8 1
4.3%
359.9 1
4.3%
330.8 1
4.3%
286.4 1
4.3%
253.1 1
4.3%

금융성 채무(조원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean214.65652
Minimum69.1
Maximum379.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:44:10.718492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum69.1
5-th percentile80.07
Q1154.95
median213.6
Q3276.2
95-th percentile353.79
Maximum379.3
Range310.2
Interquartile range (IQR)121.25

Descriptive statistics

Standard deviation89.600796
Coefficient of variation (CV)0.41741474
Kurtosis-0.86372627
Mean214.65652
Median Absolute Deviation (MAD)66.5
Skewness0.083297935
Sum4937.1
Variance8028.3026
MonotonicityStrictly increasing
2023-12-12T21:44:10.817692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
69.1 1
 
4.3%
78.9 1
 
4.3%
379.3 1
 
4.3%
356.0 1
 
4.3%
333.9 1
 
4.3%
315.6 1
 
4.3%
301.3 1
 
4.3%
285.4 1
 
4.3%
267.0 1
 
4.3%
260.6 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
69.1 1
4.3%
78.9 1
4.3%
90.6 1
4.3%
105.7 1
4.3%
125.5 1
4.3%
147.1 1
4.3%
162.8 1
4.3%
171.9 1
4.3%
176.4 1
4.3%
190.9 1
4.3%
ValueCountFrequency (%)
379.3 1
4.3%
356.0 1
4.3%
333.9 1
4.3%
315.6 1
4.3%
301.3 1
4.3%
285.4 1
4.3%
267.0 1
4.3%
260.6 1
4.3%
246.7 1
4.3%
236.7 1
4.3%

국내총생산(GDP)대비비중(퍼센트)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.93913
Minimum17
Maximum50.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:44:10.919625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile17.11
Q126.35
median30.3
Q335.95
95-th percentile46.95
Maximum50.1
Range33.1
Interquartile range (IQR)9.6

Descriptive statistics

Standard deviation9.0313464
Coefficient of variation (CV)0.29190692
Kurtosis-0.13151898
Mean30.93913
Median Absolute Deviation (MAD)5.6
Skewness0.28064081
Sum711.6
Variance81.565217
MonotonicityNot monotonic
2023-12-12T21:44:11.041179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
36.0 2
 
8.7%
17.1 1
 
4.3%
30.8 1
 
4.3%
50.1 1
 
4.3%
47.3 1
 
4.3%
43.8 1
 
4.3%
37.7 1
 
4.3%
35.9 1
 
4.3%
35.7 1
 
4.3%
34.1 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
17.0 1
4.3%
17.1 1
4.3%
17.2 1
4.3%
19.8 1
4.3%
22.4 1
4.3%
25.9 1
4.3%
26.8 1
4.3%
27.5 1
4.3%
28.1 1
4.3%
29.7 1
4.3%
ValueCountFrequency (%)
50.1 1
4.3%
47.3 1
4.3%
43.8 1
4.3%
37.7 1
4.3%
36.0 2
8.7%
35.9 1
4.3%
35.7 1
4.3%
34.1 1
4.3%
32.6 1
4.3%
30.8 1
4.3%

Interactions

2023-12-12T21:44:09.120863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:06.859863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:07.335174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:07.800823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:08.339419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:09.242794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:06.954619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:07.435102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:07.910062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:08.739369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:09.352063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:07.051640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:07.534565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:08.013258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:08.834644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:09.451181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:07.143411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:07.628505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:08.093456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:08.930931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:09.577472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:07.245058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:07.712474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:08.203393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:09.024968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:44:11.122782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도기준국가채무(조원)적자성 채무(조원)금융성 채무(조원)국내총생산(GDP)대비비중(퍼센트)
연도1.0000.0000.9410.6940.9660.800
기준0.0001.0001.0001.0000.5790.778
국가채무(조원)0.9411.0001.0000.9130.9290.929
적자성 채무(조원)0.6941.0000.9131.0000.9500.921
금융성 채무(조원)0.9660.5790.9290.9501.0000.903
국내총생산(GDP)대비비중(퍼센트)0.8000.7780.9290.9210.9031.000
2023-12-12T21:44:11.239035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도국가채무(조원)적자성 채무(조원)금융성 채무(조원)국내총생산(GDP)대비비중(퍼센트)기준
연도1.0001.0001.0001.0000.9890.000
국가채무(조원)1.0001.0001.0001.0000.9890.806
적자성 채무(조원)1.0001.0001.0001.0000.9890.837
금융성 채무(조원)1.0001.0001.0001.0000.9890.316
국내총생산(GDP)대비비중(퍼센트)0.9890.9890.9890.9891.0000.387
기준0.0000.8060.8370.3160.3871.000

Missing values

2023-12-12T21:44:09.685007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:44:09.795851image/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

연도기준국가채무(조원)적자성 채무(조원)금융성 채무(조원)국내총생산(GDP)대비비중(퍼센트)
02000결산111.242.069.117.1
12001결산121.843.078.917.2
22002결산133.843.190.617.0
32003결산165.860.1105.719.8
42004결산203.778.2125.522.4
52005결산247.9100.8147.125.9
62006결산282.7119.9162.828.1
72007결산299.2127.4171.927.5
82008결산309.0132.6176.426.8
92009결산359.6168.8190.929.8
연도기준국가채무(조원)적자성 채무(조원)금융성 채무(조원)국내총생산(GDP)대비비중(퍼센트)
132013결산489.8253.1236.732.6
142014결산533.2286.4246.734.1
152015결산591.5330.8260.635.7
162016결산626.9359.9267.036.0
172017결산660.2374.8285.436.0
182018결산680.5379.2301.335.9
192019결산723.2407.6315.637.7
202020결산846.6512.7333.943.8
2120212차 추경965.3609.3356.047.3
2220221차 추경1075.7696.4379.350.1