Overview

Dataset statistics

Number of variables10
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory94.7 B

Variable types

Numeric9
Categorical1

Dataset

Description2012년부터 2022년까지 총수입 시계열 자료
Author한국재정정보원
URLhttps://www.data.go.kr/data/15084177/fileData.do

Alerts

연도 is highly overall correlated with 총수입(조원) and 6 other fieldsHigh correlation
총수입(조원) is highly overall correlated with 연도 and 6 other fieldsHigh correlation
국세수입(조원) is highly overall correlated with 연도 and 6 other fieldsHigh correlation
국세수입_소득세(조원) is highly overall correlated with 연도 and 6 other fieldsHigh correlation
국세수입_법인세(조원) is highly overall correlated with 연도 and 6 other fieldsHigh correlation
국세수입_부가가치세(조원) is highly overall correlated with 연도 and 6 other fieldsHigh correlation
국세수입_기타(조원) is highly overall correlated with 연도 and 6 other fieldsHigh correlation
국세수입_세외수입(조원) is highly overall correlated with 기준High correlation
국세수입_기금수입(조원) is highly overall correlated with 연도 and 6 other fieldsHigh correlation
기준 is highly overall correlated with 국세수입_세외수입(조원)High correlation
총수입(조원) has unique valuesUnique
국세수입(조원) has unique valuesUnique
국세수입_부가가치세(조원) has unique valuesUnique
국세수입_기금수입(조원) has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:58:01.690376
Analysis finished2023-12-12 12:58:10.183815
Duration8.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.2609
Minimum2011
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:58:10.242273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2011.1
Q12013.5
median2016
Q32019
95-th percentile2021
Maximum2022
Range11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.4007672
Coefficient of variation (CV)0.0016866702
Kurtosis-1.1833698
Mean2016.2609
Median Absolute Deviation (MAD)3
Skewness0.020845742
Sum46374
Variance11.565217
MonotonicityIncreasing
2023-12-12T21:58:10.337363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2011 2
8.7%
2012 2
8.7%
2013 2
8.7%
2014 2
8.7%
2015 2
8.7%
2016 2
8.7%
2017 2
8.7%
2018 2
8.7%
2019 2
8.7%
2020 2
8.7%
Other values (2) 3
13.0%
ValueCountFrequency (%)
2011 2
8.7%
2012 2
8.7%
2013 2
8.7%
2014 2
8.7%
2015 2
8.7%
2016 2
8.7%
2017 2
8.7%
2018 2
8.7%
2019 2
8.7%
2020 2
8.7%
ValueCountFrequency (%)
2022 1
4.3%
2021 2
8.7%
2020 2
8.7%
2019 2
8.7%
2018 2
8.7%
2017 2
8.7%
2016 2
8.7%
2015 2
8.7%
2014 2
8.7%
2013 2
8.7%

기준
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
예산
12 
결산
11 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
예산 12
52.2%
결산 11
47.8%

Length

2023-12-12T21:58:10.456116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:58:10.537058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
예산 12
52.2%
결산 11
47.8%

총수입(조원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean420.56522
Minimum314.4
Maximum609.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:58:10.625869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum314.4
5-th percentile324.88
Q1358.6
median401.8
Q3471.9
95-th percentile564.91
Maximum609.1
Range294.7
Interquartile range (IQR)113.3

Descriptive statistics

Standard deviation78.15407
Coefficient of variation (CV)0.18583104
Kurtosis0.13943052
Mean420.56522
Median Absolute Deviation (MAD)58.3
Skewness0.77561725
Sum9673
Variance6108.0587
MonotonicityNot monotonic
2023-12-12T21:58:10.730096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
314.4 1
 
4.3%
323.0 1
 
4.3%
609.1 1
 
4.3%
570.5 1
 
4.3%
514.6 1
 
4.3%
478.8 1
 
4.3%
470.7 1
 
4.3%
473.1 1
 
4.3%
476.1 1
 
4.3%
465.3 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
314.4 1
4.3%
323.0 1
4.3%
341.8 1
4.3%
343.5 1
4.3%
351.9 1
4.3%
356.4 1
4.3%
360.8 1
4.3%
369.3 1
4.3%
371.8 1
4.3%
377.7 1
4.3%
ValueCountFrequency (%)
609.1 1
4.3%
570.5 1
4.3%
514.6 1
4.3%
478.8 1
4.3%
476.1 1
4.3%
473.1 1
4.3%
470.7 1
4.3%
465.3 1
4.3%
447.7 1
4.3%
430.6 1
4.3%

국세수입(조원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean252.98696
Minimum187.6
Maximum396.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:58:10.900827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum187.6
5-th percentile193.35
Q1208.1
median242.6
Q3289.5
95-th percentile341.12
Maximum396.6
Range209
Interquartile range (IQR)81.4

Descriptive statistics

Standard deviation53.810951
Coefficient of variation (CV)0.21270247
Kurtosis0.69062917
Mean252.98696
Median Absolute Deviation (MAD)37.1
Skewness0.96220175
Sum5818.7
Variance2895.6185
MonotonicityNot monotonic
2023-12-12T21:58:11.073272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
187.6 1
 
4.3%
192.4 1
 
4.3%
396.6 1
 
4.3%
344.1 1
 
4.3%
314.3 1
 
4.3%
285.5 1
 
4.3%
279.7 1
 
4.3%
293.5 1
 
4.3%
294.8 1
 
4.3%
293.6 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
187.6 1
4.3%
192.4 1
4.3%
201.9 1
4.3%
203.0 1
4.3%
205.5 1
4.3%
205.8 1
4.3%
210.4 1
4.3%
215.7 1
4.3%
216.5 1
4.3%
217.9 1
4.3%
ValueCountFrequency (%)
396.6 1
4.3%
344.1 1
4.3%
314.3 1
4.3%
294.8 1
4.3%
293.6 1
4.3%
293.5 1
4.3%
285.5 1
4.3%
279.7 1
4.3%
268.1 1
4.3%
265.4 1
4.3%

국세수입_소득세(조원)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.417391
Minimum40
Maximum127.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:58:11.205688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile42.65
Q151.55
median68.5
Q384.05
95-th percentile112.64
Maximum127.8
Range87.8
Interquartile range (IQR)32.5

Descriptive statistics

Standard deviation23.438966
Coefficient of variation (CV)0.33285763
Kurtosis0.20253986
Mean70.417391
Median Absolute Deviation (MAD)16
Skewness0.80475207
Sum1619.6
Variance549.38514
MonotonicityNot monotonic
2023-12-12T21:58:11.325885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
45.8 2
 
8.7%
40.0 1
 
4.3%
75.1 1
 
4.3%
127.8 1
 
4.3%
114.1 1
 
4.3%
99.5 1
 
4.3%
93.1 1
 
4.3%
88.5 1
 
4.3%
83.6 1
 
4.3%
80.4 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
40.0 1
4.3%
42.3 1
4.3%
45.8 2
8.7%
47.8 1
4.3%
49.8 1
4.3%
53.3 1
4.3%
54.4 1
4.3%
58.8 1
4.3%
60.7 1
4.3%
63.3 1
4.3%
ValueCountFrequency (%)
127.8 1
4.3%
114.1 1
4.3%
99.5 1
4.3%
93.1 1
4.3%
88.5 1
4.3%
84.5 1
4.3%
83.6 1
4.3%
80.4 1
4.3%
75.1 1
4.3%
72.9 1
4.3%

국세수입_법인세(조원)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.682609
Minimum41.3
Maximum104.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:58:11.452518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41.3
5-th percentile42.82
Q144.95
median52.1
Q364.25
95-th percentile78.59
Maximum104.1
Range62.8
Interquartile range (IQR)19.3

Descriptive statistics

Standard deviation15.212305
Coefficient of variation (CV)0.26837694
Kurtosis2.907765
Mean56.682609
Median Absolute Deviation (MAD)7.6
Skewness1.5400975
Sum1303.7
Variance231.41423
MonotonicityNot monotonic
2023-12-12T21:58:11.567104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
46.0 2
 
8.7%
41.3 1
 
4.3%
59.2 1
 
4.3%
104.1 1
 
4.3%
70.4 1
 
4.3%
65.5 1
 
4.3%
55.5 1
 
4.3%
58.5 1
 
4.3%
72.2 1
 
4.3%
79.3 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
41.3 1
4.3%
42.7 1
4.3%
43.9 1
4.3%
44.1 1
4.3%
44.5 1
4.3%
44.9 1
4.3%
45.0 1
4.3%
45.9 1
4.3%
46.0 2
8.7%
51.4 1
4.3%
ValueCountFrequency (%)
104.1 1
4.3%
79.3 1
4.3%
72.2 1
4.3%
70.9 1
4.3%
70.4 1
4.3%
65.5 1
4.3%
63.0 1
4.3%
59.2 1
4.3%
58.5 1
4.3%
57.3 1
4.3%

국세수입_부가가치세(조원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.286957
Minimum51.9
Maximum79.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:58:11.676236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51.9
5-th percentile53.03
Q156.3
median61.8
Q368.05
95-th percentile71.16
Maximum79.3
Range27.4
Interquartile range (IQR)11.75

Descriptive statistics

Standard deviation7.2453311
Coefficient of variation (CV)0.1163218
Kurtosis-0.49500668
Mean62.286957
Median Absolute Deviation (MAD)5.8
Skewness0.48443779
Sum1432.6
Variance52.494822
MonotonicityNot monotonic
2023-12-12T21:58:11.780618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
52.9 1
 
4.3%
51.9 1
 
4.3%
79.3 1
 
4.3%
71.2 1
 
4.3%
69.3 1
 
4.3%
64.9 1
 
4.3%
64.6 1
 
4.3%
70.8 1
 
4.3%
68.8 1
 
4.3%
70.0 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
51.9 1
4.3%
52.9 1
4.3%
54.2 1
4.3%
55.4 1
4.3%
55.7 1
4.3%
56.0 1
4.3%
56.6 1
4.3%
56.8 1
4.3%
57.1 1
4.3%
58.5 1
4.3%
ValueCountFrequency (%)
79.3 1
4.3%
71.2 1
4.3%
70.8 1
4.3%
70.0 1
4.3%
69.3 1
4.3%
68.8 1
4.3%
67.3 1
4.3%
67.1 1
4.3%
64.9 1
4.3%
64.6 1
4.3%

국세수입_기타(조원)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.969565
Minimum29.2
Maximum88.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:58:11.887787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29.2
5-th percentile52.49
Q156.5
median58.6
Q367.2
95-th percentile84.86
Maximum88.4
Range59.2
Interquartile range (IQR)10.7

Descriptive statistics

Standard deviation12.237849
Coefficient of variation (CV)0.1974816
Kurtosis2.1037789
Mean61.969565
Median Absolute Deviation (MAD)5.3
Skewness0.008992431
Sum1425.3
Variance149.76494
MonotonicityNot monotonic
2023-12-12T21:58:12.007785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
58.0 2
 
8.7%
53.4 1
 
4.3%
64.1 1
 
4.3%
85.4 1
 
4.3%
88.4 1
 
4.3%
80.0 1
 
4.3%
72.0 1
 
4.3%
68.1 1
 
4.3%
29.2 1
 
4.3%
66.3 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
29.2 1
4.3%
52.4 1
4.3%
53.3 1
4.3%
53.4 1
4.3%
54.3 1
4.3%
55.6 1
4.3%
57.4 1
4.3%
57.6 1
4.3%
58.0 2
8.7%
58.3 1
4.3%
ValueCountFrequency (%)
88.4 1
4.3%
85.4 1
4.3%
80.0 1
4.3%
72.0 1
4.3%
68.2 1
4.3%
68.1 1
4.3%
66.3 1
4.3%
64.9 1
4.3%
64.1 1
4.3%
61.7 1
4.3%

국세수입_세외수입(조원)
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.986957
Minimum23.5
Maximum36.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:58:12.131364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.5
5-th percentile23.73
Q125.3
median26.7
Q327.95
95-th percentile30.38
Maximum36.9
Range13.4
Interquartile range (IQR)2.65

Descriptive statistics

Standard deviation2.8462582
Coefficient of variation (CV)0.10546792
Kurtosis5.9252431
Mean26.986957
Median Absolute Deviation (MAD)1.4
Skewness1.93133
Sum620.7
Variance8.1011858
MonotonicityNot monotonic
2023-12-12T21:58:12.283147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
28.3 2
 
8.7%
25.3 2
 
8.7%
27.3 2
 
8.7%
24.4 1
 
4.3%
25.5 1
 
4.3%
30.5 1
 
4.3%
29.3 1
 
4.3%
26.9 1
 
4.3%
29.1 1
 
4.3%
26.6 1
 
4.3%
Other values (10) 10
43.5%
ValueCountFrequency (%)
23.5 1
4.3%
23.7 1
4.3%
24.0 1
4.3%
24.4 1
4.3%
24.6 1
4.3%
25.3 2
8.7%
25.5 1
4.3%
26.0 1
4.3%
26.4 1
4.3%
26.6 1
4.3%
ValueCountFrequency (%)
36.9 1
4.3%
30.5 1
4.3%
29.3 1
4.3%
29.1 1
4.3%
28.3 2
8.7%
27.6 1
4.3%
27.3 2
8.7%
27.2 1
4.3%
26.9 1
4.3%
26.7 1
4.3%

국세수입_기금수입(조원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean140.7
Minimum102.3
Maximum195.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T21:58:12.474587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102.3
5-th percentile106.8
Q1124.1
median139.5
Q3154.35
95-th percentile182.79
Maximum195.8
Range93.5
Interquartile range (IQR)30.25

Descriptive statistics

Standard deviation24.560686
Coefficient of variation (CV)0.17456066
Kurtosis-0.20575346
Mean140.7
Median Absolute Deviation (MAD)15.2
Skewness0.46512118
Sum3236.1
Variance603.22727
MonotonicityNot monotonic
2023-12-12T21:58:12.625521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
102.3 1
 
4.3%
106.5 1
 
4.3%
184.1 1
 
4.3%
195.8 1
 
4.3%
171.0 1
 
4.3%
166.2 1
 
4.3%
161.9 1
 
4.3%
154.0 1
 
4.3%
154.7 1
 
4.3%
145.1 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
102.3 1
4.3%
106.5 1
4.3%
109.5 1
4.3%
113.3 1
4.3%
119.3 1
4.3%
122.6 1
4.3%
125.6 1
4.3%
126.2 1
4.3%
130.2 1
4.3%
133.6 1
4.3%
ValueCountFrequency (%)
195.8 1
4.3%
184.1 1
4.3%
171.0 1
4.3%
166.2 1
4.3%
161.9 1
4.3%
154.7 1
4.3%
154.0 1
4.3%
152.4 1
4.3%
145.6 1
4.3%
145.1 1
4.3%

Interactions

2023-12-12T21:58:09.195256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:02.020711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:02.910822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:03.840421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:04.627608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:05.350697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.275807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:07.473016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:08.339929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:09.281992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:02.100874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:03.021070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:03.915721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:04.711065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:05.432059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.690300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:07.558151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:08.417396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:09.379755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:02.204813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:03.110700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:04.006021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:04.787450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:05.520941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.789103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:07.667750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:08.518499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:09.471928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:02.310652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:03.210283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:04.101899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:04.861613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:05.593966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.885598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:07.762791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:08.610041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:09.553747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:02.410550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:03.302696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:04.186751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:04.932976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:05.679398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.988994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:07.843665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:08.690704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:09.639144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:02.508923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:03.403317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:04.272234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:05.027776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:05.791356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:07.095091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:07.956706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:08.788353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:09.714748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:02.601445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:03.515780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:04.363719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:05.112218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:05.915751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:07.194256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:08.046675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:08.897447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:09.795035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:02.706548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:03.636835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:04.463439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:05.192373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.018476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:07.289803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:08.143802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:09.012917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:09.874835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:02.810503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:03.739601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:04.547533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:05.274587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.132415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:07.391122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:08.242089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:09.102272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:58:13.087646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도기준총수입(조원)국세수입(조원)국세수입_소득세(조원)국세수입_법인세(조원)국세수입_부가가치세(조원)국세수입_기타(조원)국세수입_세외수입(조원)국세수입_기금수입(조원)
연도1.0000.0000.8530.8570.8180.7980.7010.7540.0000.811
기준0.0001.0000.0000.0000.0000.2230.0000.0000.6390.000
총수입(조원)0.8530.0001.0000.9820.9580.8690.9130.7970.5610.907
국세수입(조원)0.8570.0000.9821.0000.9680.9130.9670.8150.6290.884
국세수입_소득세(조원)0.8180.0000.9580.9681.0000.7680.9310.8430.5220.848
국세수입_법인세(조원)0.7980.2230.8690.9130.7681.0000.8040.6940.2530.789
국세수입_부가가치세(조원)0.7010.0000.9130.9670.9310.8041.0000.7230.6620.834
국세수입_기타(조원)0.7540.0000.7970.8150.8430.6940.7231.0000.1530.791
국세수입_세외수입(조원)0.0000.6390.5610.6290.5220.2530.6620.1531.0000.754
국세수입_기금수입(조원)0.8110.0000.9070.8840.8480.7890.8340.7910.7541.000
2023-12-12T21:58:13.254056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도총수입(조원)국세수입(조원)국세수입_소득세(조원)국세수입_법인세(조원)국세수입_부가가치세(조원)국세수입_기타(조원)국세수입_세외수입(조원)국세수입_기금수입(조원)기준
연도1.0000.9910.9680.9920.8620.8980.7840.3700.9920.000
총수입(조원)0.9911.0000.9820.9880.8890.9110.7910.3760.9810.000
국세수입(조원)0.9680.9821.0000.9730.9350.9350.8080.3470.9490.000
국세수입_소득세(조원)0.9920.9880.9731.0000.8690.9030.8040.3520.9750.000
국세수입_법인세(조원)0.8620.8890.9350.8691.0000.9230.7010.2430.8370.178
국세수입_부가가치세(조원)0.8980.9110.9350.9030.9231.0000.7090.3300.8770.000
국세수입_기타(조원)0.7840.7910.8080.8040.7010.7091.0000.4940.7710.000
국세수입_세외수입(조원)0.3700.3760.3470.3520.2430.3300.4941.0000.3790.596
국세수입_기금수입(조원)0.9920.9810.9490.9750.8370.8770.7710.3791.0000.000
기준0.0000.0000.0000.0000.1780.0000.0000.5960.0001.000

Missing values

2023-12-12T21:58:09.986991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:58:10.123165image/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

연도기준총수입(조원)국세수입(조원)국세수입_소득세(조원)국세수입_법인세(조원)국세수입_부가가치세(조원)국세수입_기타(조원)국세수입_세외수입(조원)국세수입_기금수입(조원)
02011예산314.4187.640.041.352.953.424.4102.3
12011결산323.0192.442.344.951.953.324.0106.5
22012예산343.5205.845.844.556.858.628.3109.5
32012결산341.8203.045.845.955.755.625.3113.3
42013예산360.8210.449.846.056.658.036.9119.3
52013결산351.9201.947.843.956.054.327.3122.6
62014예산369.3216.554.446.058.557.627.3125.6
72014결산356.4205.553.342.757.152.424.6126.2
82015예산377.7215.758.844.155.457.427.6133.6
92015결산371.8217.960.745.054.258.023.7130.2
연도기준총수입(조원)국세수입(조원)국세수입_소득세(조원)국세수입_법인세(조원)국세수입_부가가치세(조원)국세수입_기타(조원)국세수입_세외수입(조원)국세수입_기금수입(조원)
132017결산430.6265.475.159.267.164.125.5139.5
142018예산447.7268.172.963.067.364.926.7152.4
152018결산465.3293.684.570.970.068.226.0145.1
162019예산476.1294.880.479.368.866.326.6154.7
172019결산473.1293.583.672.270.829.225.3154.0
182020예산470.7279.788.558.564.668.129.1161.9
192020결산478.8285.593.155.564.972.026.9166.2
202021예산514.6314.399.565.569.380.029.3171.0
212021결산570.5344.1114.170.471.288.430.5195.8
222022예산609.1396.6127.8104.179.385.428.3184.1