Overview

Dataset statistics

Number of variables8
Number of observations111
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.8 KiB
Average record size in memory72.2 B

Variable types

DateTime1
Numeric7

Dataset

Description비거주자가 거주자에 대해 가지고 있는 채무 잔액(대외채무) 및 거주자가 비거주자에 대해 가지고 있는 채권 잔액(대외채권)에 대한 시계열 자료입니다. 만기별(단기/장기) 및 주체별(일반정부/중앙은행/예금취급기관/기타부문)으로 구분되어 있습니다.
Author기획재정부
URLhttps://www.data.go.kr/data/15105535/fileData.do

Alerts

대외채무 총합 is highly overall correlated with 단기 and 5 other fieldsHigh correlation
단기 is highly overall correlated with 대외채무 총합 and 5 other fieldsHigh correlation
장기 is highly overall correlated with 대외채무 총합 and 5 other fieldsHigh correlation
일반정부 is highly overall correlated with 대외채무 총합 and 5 other fieldsHigh correlation
중앙은행 is highly overall correlated with 대외채무 총합 and 5 other fieldsHigh correlation
예금취급기관 is highly overall correlated with 대외채무 총합 and 5 other fieldsHigh correlation
기타부문 is highly overall correlated with 대외채무 총합 and 5 other fieldsHigh correlation
연도별분기 has unique valuesUnique
대외채무 총합 has unique valuesUnique
단기 has unique valuesUnique
장기 has unique valuesUnique
일반정부 has unique valuesUnique
중앙은행 has unique valuesUnique
예금취급기관 has unique valuesUnique
기타부문 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:43:21.031636
Analysis finished2023-12-12 22:43:25.953915
Duration4.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도별분기
Date

UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1020.0 B
Minimum1995-01-01 00:00:00
Maximum2022-03-01 00:00:00
2023-12-13T07:43:26.015708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:26.130212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대외채무 총합
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean302769.92
Minimum89369.8
Maximum662038.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T07:43:26.236738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum89369.8
5-th percentile116250.3
Q1144713.7
median336236.6
Q3415490.9
95-th percentile588578
Maximum662038.1
Range572668.3
Interquartile range (IQR)270777.2

Descriptive statistics

Standard deviation156924.91
Coefficient of variation (CV)0.51829756
Kurtosis-0.98398611
Mean302769.92
Median Absolute Deviation (MAD)154639.4
Skewness0.31665767
Sum33607461
Variance2.4625429 × 1010
MonotonicityNot monotonic
2023-12-13T07:43:26.368644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89369.8 1
 
0.9%
97831.6 1
 
0.9%
408022.5 1
 
0.9%
420514.0 1
 
0.9%
415905.6 1
 
0.9%
423034.1 1
 
0.9%
436099.2 1
 
0.9%
451814.9 1
 
0.9%
434768.3 1
 
0.9%
422096.1 1
 
0.9%
Other values (101) 101
91.0%
ValueCountFrequency (%)
89369.8 1
0.9%
97831.6 1
0.9%
104879.5 1
0.9%
109065.5 1
0.9%
114666.1 1
0.9%
115624.7 1
0.9%
116875.9 1
0.9%
119780.6 1
0.9%
120710.9 1
0.9%
122333.5 1
0.9%
ValueCountFrequency (%)
662038.1 1
0.9%
654097.8 1
0.9%
638980.8 1
0.9%
632393.6 1
0.9%
614897.2 1
0.9%
607178.8 1
0.9%
569977.2 1
0.9%
550628.2 1
0.9%
516291.4 1
0.9%
507945.4 1
0.9%

단기
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101262.46
Minimum33738.9
Maximum187847.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T07:43:26.506501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33738.9
5-th percentile36501.4
Q149887.85
median114485.3
Q3140077.65
95-th percentile172928.45
Maximum187847.5
Range154108.6
Interquartile range (IQR)90189.8

Descriptive statistics

Standard deviation46897.679
Coefficient of variation (CV)0.46312994
Kurtosis-1.4138281
Mean101262.46
Median Absolute Deviation (MAD)40258.3
Skewness-0.058845758
Sum11240134
Variance2.1993923 × 109
MonotonicityNot monotonic
2023-12-13T07:43:26.639729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41946.8 1
 
0.9%
45914.1 1
 
0.9%
115327.1 1
 
0.9%
120655.8 1
 
0.9%
113106.9 1
 
0.9%
114658.3 1
 
0.9%
125515.2 1
 
0.9%
131392.2 1
 
0.9%
122291.1 1
 
0.9%
109892.0 1
 
0.9%
Other values (101) 101
91.0%
ValueCountFrequency (%)
33738.9 1
0.9%
34655.9 1
0.9%
35123.6 1
0.9%
35451.9 1
0.9%
35668.7 1
0.9%
36206.6 1
0.9%
36796.2 1
0.9%
37296.7 1
0.9%
37699.2 1
0.9%
37977.3 1
0.9%
ValueCountFrequency (%)
187847.5 1
0.9%
183848.8 1
0.9%
176793.1 1
0.9%
176149.1 1
0.9%
175643.1 1
0.9%
174917.7 1
0.9%
170939.2 1
0.9%
164921.4 1
0.9%
164735.8 1
0.9%
163481.6 1
0.9%

장기
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201507.45
Minimum47422.9
Maximum479180.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T07:43:27.005448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47422.9
5-th percentile67727.15
Q193125.2
median175292.8
Q3294379.4
95-th percentile418042.75
Maximum479180.1
Range431757.2
Interquartile range (IQR)201254.2

Descriptive statistics

Standard deviation117630.81
Coefficient of variation (CV)0.58375415
Kurtosis-0.80390348
Mean201507.45
Median Absolute Deviation (MAD)93211.4
Skewness0.53444468
Sum22367327
Variance1.3837008 × 1010
MonotonicityNot monotonic
2023-12-13T07:43:27.131770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47422.9 1
 
0.9%
51917.5 1
 
0.9%
292695.4 1
 
0.9%
299858.2 1
 
0.9%
302798.7 1
 
0.9%
308375.8 1
 
0.9%
310584.0 1
 
0.9%
320422.7 1
 
0.9%
312477.2 1
 
0.9%
312204.1 1
 
0.9%
Other values (101) 101
91.0%
ValueCountFrequency (%)
47422.9 1
0.9%
51917.5 1
0.9%
54524.4 1
0.9%
57702.4 1
0.9%
60890.5 1
0.9%
64779.4 1
0.9%
70674.9 1
0.9%
74665.0 1
0.9%
78931.9 1
0.9%
79579.1 1
0.9%
ValueCountFrequency (%)
479180.1 1
0.9%
478189.3 1
0.9%
468041.6 1
0.9%
467657.8 1
0.9%
451415.6 1
0.9%
431029.7 1
0.9%
405055.8 1
0.9%
390561.8 1
0.9%
368891.2 1
0.9%
350440.3 1
0.9%

일반정부
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46984.98
Minimum5930.8
Maximum151658
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T07:43:27.294279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5930.8
5-th percentile6478.95
Q116287.85
median32049.4
Q367928.7
95-th percentile131350.65
Maximum151658
Range145727.2
Interquartile range (IQR)51640.85

Descriptive statistics

Standard deviation37794.389
Coefficient of variation (CV)0.804393
Kurtosis0.26954689
Mean46984.98
Median Absolute Deviation (MAD)24718.3
Skewness0.9941492
Sum5215332.8
Variance1.4284159 × 109
MonotonicityNot monotonic
2023-12-13T07:43:27.413929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6984.9 1
 
0.9%
7403.1 1
 
0.9%
63724.9 1
 
0.9%
69246.3 1
 
0.9%
70838.1 1
 
0.9%
67063.0 1
 
0.9%
68236.6 1
 
0.9%
70725.3 1
 
0.9%
64653.5 1
 
0.9%
62981.1 1
 
0.9%
Other values (101) 101
91.0%
ValueCountFrequency (%)
5930.8 1
0.9%
5970.6 1
0.9%
6090.7 1
0.9%
6168.0 1
0.9%
6356.7 1
0.9%
6404.1 1
0.9%
6553.8 1
0.9%
6635.7 1
0.9%
6984.9 1
0.9%
7331.1 1
0.9%
ValueCountFrequency (%)
151658.0 1
0.9%
146218.4 1
0.9%
144411.4 1
0.9%
139588.7 1
0.9%
138838.6 1
0.9%
135100.9 1
0.9%
127600.4 1
0.9%
121511.5 1
0.9%
112755.4 1
0.9%
104947.1 1
0.9%

중앙은행
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17356.112
Minimum267
Maximum45939.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T07:43:27.561895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum267
5-th percentile304.7
Q11297.9
median20904.8
Q327946
95-th percentile38279.9
Maximum45939.9
Range45672.9
Interquartile range (IQR)26648.1

Descriptive statistics

Standard deviation14077.409
Coefficient of variation (CV)0.81109232
Kurtosis-1.3925609
Mean17356.112
Median Absolute Deviation (MAD)13764.2
Skewness0.091872875
Sum1926528.4
Variance1.9817344 × 108
MonotonicityNot monotonic
2023-12-13T07:43:27.688774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
412.7 1
 
0.9%
371.7 1
 
0.9%
32200.3 1
 
0.9%
35546.0 1
 
0.9%
34669.0 1
 
0.9%
35244.4 1
 
0.9%
37692.4 1
 
0.9%
38163.6 1
 
0.9%
36128.8 1
 
0.9%
37197.7 1
 
0.9%
Other values (101) 101
91.0%
ValueCountFrequency (%)
267.0 1
0.9%
267.5 1
0.9%
271.9 1
0.9%
281.6 1
0.9%
283.4 1
0.9%
299.8 1
0.9%
309.6 1
0.9%
311.7 1
0.9%
361.3 1
0.9%
371.7 1
0.9%
ValueCountFrequency (%)
45939.9 1
0.9%
45496.4 1
0.9%
43056.0 1
0.9%
38897.0 1
0.9%
38672.4 1
0.9%
38396.2 1
0.9%
38163.6 1
0.9%
37692.4 1
0.9%
37670.8 1
0.9%
37197.7 1
0.9%

예금취급기관
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean144969.93
Minimum51299.7
Maximum280147.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T07:43:27.799808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51299.7
5-th percentile56633.65
Q173582.55
median172275.2
Q3192096.6
95-th percentile241607.4
Maximum280147.4
Range228847.7
Interquartile range (IQR)118514.05

Descriptive statistics

Standard deviation64305.416
Coefficient of variation (CV)0.44357763
Kurtosis-1.3437869
Mean144969.93
Median Absolute Deviation (MAD)48333.8
Skewness-0.038372454
Sum16091662
Variance4.1351866 × 109
MonotonicityNot monotonic
2023-12-13T07:43:27.916664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56037.0 1
 
0.9%
62039.6 1
 
0.9%
187089.2 1
 
0.9%
192519.6 1
 
0.9%
187663.2 1
 
0.9%
185444.7 1
 
0.9%
190813.1 1
 
0.9%
199018.4 1
 
0.9%
190313.6 1
 
0.9%
181496.6 1
 
0.9%
Other values (101) 101
91.0%
ValueCountFrequency (%)
51299.7 1
0.9%
51857.0 1
0.9%
54245.6 1
0.9%
54924.2 1
0.9%
55549.7 1
0.9%
56037.0 1
0.9%
57230.3 1
0.9%
58471.3 1
0.9%
58827.3 1
0.9%
61463.8 1
0.9%
ValueCountFrequency (%)
280147.4 1
0.9%
273526.7 1
0.9%
262434.6 1
0.9%
252808.7 1
0.9%
251652.9 1
0.9%
243785.6 1
0.9%
239429.2 1
0.9%
234165.9 1
0.9%
220960.2 1
0.9%
220609.0 1
0.9%

기타부문
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92100.012
Minimum25935.3
Maximum196949.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T07:43:28.051653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25935.3
5-th percentile35230.15
Q146437.8
median93697.6
Q3129767.55
95-th percentile170987.55
Maximum196949.2
Range171013.9
Interquartile range (IQR)83329.75

Descriptive statistics

Standard deviation45986.321
Coefficient of variation (CV)0.49930852
Kurtosis-1.0192317
Mean92100.012
Median Absolute Deviation (MAD)42144.1
Skewness0.33006416
Sum10223101
Variance2.1147417 × 109
MonotonicityNot monotonic
2023-12-13T07:43:28.185480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25935.3 1
 
0.9%
28017.3 1
 
0.9%
125008.1 1
 
0.9%
123202.1 1
 
0.9%
122735.3 1
 
0.9%
135282.0 1
 
0.9%
139357.1 1
 
0.9%
143907.6 1
 
0.9%
143672.4 1
 
0.9%
140420.7 1
 
0.9%
Other values (101) 101
91.0%
ValueCountFrequency (%)
25935.3 1
0.9%
28017.3 1
0.9%
28748.1 1
0.9%
30136.4 1
0.9%
32460.9 1
0.9%
33829.0 1
0.9%
36631.3 1
0.9%
39163.7 1
0.9%
39977.4 1
0.9%
40293.7 1
0.9%
ValueCountFrequency (%)
196949.2 1
0.9%
196775.3 1
0.9%
190832.9 1
0.9%
185583.0 1
0.9%
181156.8 1
0.9%
172853.4 1
0.9%
169121.7 1
0.9%
157364.8 1
0.9%
150616.4 1
0.9%
149668.4 1
0.9%

Interactions

2023-12-13T07:43:25.206810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:21.257598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:22.236810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:22.826177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:23.394652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:24.069565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:24.645706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:25.287472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:21.351654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:22.316729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:22.909927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:23.487605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:24.165613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:24.726759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:25.368129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:21.453079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:22.402172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:22.991942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:23.596583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:24.247010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:24.819016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:25.438612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:21.524695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:22.487208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:23.073232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:23.690345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:24.332680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:24.899462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:25.517972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:21.616866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:22.574836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:23.162935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:23.785516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:24.410379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:24.978775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:25.599425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:22.012037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:22.650342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:23.227190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:23.869997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:24.476990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:25.042428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:25.681450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:22.109785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:22.721165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:23.305615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:23.968879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:24.550627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:43:25.119710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:43:28.266987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대외채무 총합단기장기일반정부중앙은행예금취급기관기타부문
대외채무 총합1.0000.7990.9730.9630.8280.9610.979
단기0.7991.0000.7420.7610.6460.8260.791
장기0.9730.7421.0000.9510.8630.9250.963
일반정부0.9630.7610.9511.0000.8410.8990.945
중앙은행0.8280.6460.8630.8411.0000.7660.809
예금취급기관0.9610.8260.9250.8990.7661.0000.916
기타부문0.9790.7910.9630.9450.8090.9161.000
2023-12-13T07:43:28.362152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대외채무 총합단기장기일반정부중앙은행예금취급기관기타부문
대외채무 총합1.0000.7900.9730.8810.8530.9320.933
단기0.7901.0000.7200.6440.6370.9100.745
장기0.9730.7201.0000.9350.9010.8750.918
일반정부0.8810.6440.9351.0000.8500.7770.863
중앙은행0.8530.6370.9010.8501.0000.7620.815
예금취급기관0.9320.9100.8750.7770.7621.0000.838
기타부문0.9330.7450.9180.8630.8150.8381.000

Missing values

2023-12-13T07:43:25.803473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:43:25.911978image/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

연도별분기대외채무 총합단기장기일반정부중앙은행예금취급기관기타부문
01995 189369.841946.847422.96984.9412.756037.025935.3
11995 297831.645914.151917.57403.1371.762039.628017.3
21995 3104879.550355.054524.47331.1361.368439.028748.1
31995 4109065.551363.157702.46635.7299.871993.630136.4
41996 1115624.754734.260890.56553.8283.476326.632460.9
51996 2124604.959825.564779.46404.1271.984099.933829.0
61996 3133274.662599.770674.96356.7267.090019.636631.3
71996 4144939.070273.974665.06090.7267.599417.139163.7
81997 1153125.774193.978931.95970.6281.6104260.642612.9
91997 2161579.177690.783888.45930.8311.7110566.044770.6
연도별분기대외채무 총합단기장기일반정부중앙은행예금취급기관기타부문
1012020 2507945.4157505.1350440.3104947.138396.2213985.7150616.4
1022020 3516291.4147400.2368891.2112755.426104.3220066.9157364.8
1032020 4550628.2160066.4390561.8121511.525829.1234165.9169121.7
1042021 1569977.2164921.4405055.8127600.430094.2239429.2172853.4
1052021 2607178.8176149.1431029.7138838.634374.7252808.7181156.8
1062021 3614897.2163481.6451415.6139588.745939.9243785.6185583.0
1072021 4632393.6164735.8467657.8144411.445496.4251652.9190832.9
1082022 1654097.8174917.7479180.1151658.043056.0262434.6196949.2
1092022 2662038.1183848.8478189.3146218.438897.0280147.4196775.3
1102022 3638980.8170939.2468041.6135100.933394.7273526.746121.6