Overview

Dataset statistics

Number of variables8
Number of observations294
Missing cells261
Missing cells (%)11.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.2 KiB
Average record size in memory70.4 B

Variable types

Categorical1
Text2
Numeric5

Alerts

합계금액(A+B+C-D)(원) is highly overall correlated with 자치단체금액(A)(원) and 3 other fieldsHigh correlation
자치단체금액(A)(원) is highly overall correlated with 합계금액(A+B+C-D)(원) and 3 other fieldsHigh correlation
지방공공기관금액(B)(원) is highly overall correlated with 합계금액(A+B+C-D)(원) and 3 other fieldsHigh correlation
교육재정금액(C)(원) is highly overall correlated with 합계금액(A+B+C-D)(원) and 3 other fieldsHigh correlation
내외부거래금액(D)(원) is highly overall correlated with 합계금액(A+B+C-D)(원) and 3 other fieldsHigh correlation
시군명 has 261 (88.8%) missing valuesMissing
지방공공기관금액(B)(원) has 20 (6.8%) zerosZeros
교육재정금액(C)(원) has 257 (87.4%) zerosZeros
내외부거래금액(D)(원) has 107 (36.4%) zerosZeros

Reproduction

Analysis started2023-12-10 22:29:56.724402
Analysis finished2023-12-10 22:29:59.903033
Duration3.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회계연도
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2020
261 
2021
33 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2020 261
88.8%
2021 33
 
11.2%

Length

2023-12-11T07:29:59.964074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:30:00.067810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 261
88.8%
2021 33
 
11.2%

시군명
Text

MISSING 

Distinct33
Distinct (%)100.0%
Missing261
Missing (%)88.8%
Memory size2.4 KiB
2023-12-11T07:30:00.245327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.030303
Min length1

Characters and Unicode

Total characters100
Distinct characters42
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row가평군
2nd row경기도
3rd row계
4th row고양시
5th row과천시
ValueCountFrequency (%)
김포시 1
 
3.0%
안양시 1
 
3.0%
양주시 1
 
3.0%
양평군 1
 
3.0%
여주시 1
 
3.0%
연천군 1
 
3.0%
오산시 1
 
3.0%
용인시 1
 
3.0%
의정부시 1
 
3.0%
경기도 1
 
3.0%
Other values (23) 23
69.7%
2023-12-11T07:30:00.584107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
29.0%
천 6
 
6.0%
주 5
 
5.0%
양 5
 
5.0%
군 4
 
4.0%
안 3
 
3.0%
포 3
 
3.0%
평 3
 
3.0%
성 3
 
3.0%
남 3
 
3.0%
Other values (32) 36
36.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 100
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
29.0%
천 6
 
6.0%
주 5
 
5.0%
양 5
 
5.0%
군 4
 
4.0%
안 3
 
3.0%
포 3
 
3.0%
평 3
 
3.0%
성 3
 
3.0%
남 3
 
3.0%
Other values (32) 36
36.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 100
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
29.0%
천 6
 
6.0%
주 5
 
5.0%
양 5
 
5.0%
군 4
 
4.0%
안 3
 
3.0%
포 3
 
3.0%
평 3
 
3.0%
성 3
 
3.0%
남 3
 
3.0%
Other values (32) 36
36.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 100
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
29.0%
천 6
 
6.0%
주 5
 
5.0%
양 5
 
5.0%
군 4
 
4.0%
안 3
 
3.0%
포 3
 
3.0%
평 3
 
3.0%
성 3
 
3.0%
남 3
 
3.0%
Other values (32) 36
36.0%

자치단체명
Text

Distinct223
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-11T07:30:00.891123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.8945578
Min length2

Characters and Unicode

Total characters851
Distinct characters134
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique183 ?
Unique (%)62.2%

Sample

1st row가평군
2nd row본청
3rd row경기계
4th row고양시
5th row과천시
ValueCountFrequency (%)
본청 18
 
6.1%
동구 6
 
2.0%
중구 6
 
2.0%
서구 5
 
1.7%
남구 4
 
1.4%
북구 4
 
1.4%
의왕시 2
 
0.7%
양주시 2
 
0.7%
이천시 2
 
0.7%
연천군 2
 
0.7%
Other values (213) 243
82.7%
2023-12-11T07:30:01.662222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 105
 
12.3%
군 89
 
10.5%
구 76
 
8.9%
천 29
 
3.4%
주 26
 
3.1%
청 23
 
2.7%
양 23
 
2.7%
계 21
 
2.5%
성 21
 
2.5%
산 20
 
2.4%
Other values (124) 418
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 851
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 105
 
12.3%
군 89
 
10.5%
구 76
 
8.9%
천 29
 
3.4%
주 26
 
3.1%
청 23
 
2.7%
양 23
 
2.7%
계 21
 
2.5%
성 21
 
2.5%
산 20
 
2.4%
Other values (124) 418
49.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 851
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 105
 
12.3%
군 89
 
10.5%
구 76
 
8.9%
천 29
 
3.4%
주 26
 
3.1%
청 23
 
2.7%
양 23
 
2.7%
계 21
 
2.5%
성 21
 
2.5%
산 20
 
2.4%
Other values (124) 418
49.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 851
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 105
 
12.3%
군 89
 
10.5%
구 76
 
8.9%
천 29
 
3.4%
주 26
 
3.1%
청 23
 
2.7%
양 23
 
2.7%
계 21
 
2.5%
성 21
 
2.5%
산 20
 
2.4%
Other values (124) 418
49.1%

합계금액(A+B+C-D)(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct292
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7861512 × 1013
Minimum3.8037348 × 1011
Maximum1.5304424 × 1015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T07:30:01.850088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.8037348 × 1011
5-th percentile9.4871973 × 1011
Q12.0645405 × 1012
median3.115612 × 1012
Q37.1326477 × 1012
95-th percentile7.171038 × 1013
Maximum1.5304424 × 1015
Range1.5300621 × 1015
Interquartile range (IQR)5.0681072 × 1012

Descriptive statistics

Standard deviation9.54659 × 1013
Coefficient of variation (CV)5.3447827
Kurtosis217.39669
Mean1.7861512 × 1013
Median Absolute Deviation (MAD)1.4087011 × 1012
Skewness13.973504
Sum5.2512845 × 1015
Variance9.113738 × 1027
MonotonicityNot monotonic
2023-12-11T07:30:02.033802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28013075660801 2
 
0.7%
10852935249520 2
 
0.7%
2375376998857 1
 
0.3%
1150612806938 1
 
0.3%
2940575577246 1
 
0.3%
1613909258420 1
 
0.3%
1979539006504 1
 
0.3%
3476060898511 1
 
0.3%
2381883907006 1
 
0.3%
4299133560804 1
 
0.3%
Other values (282) 282
95.9%
ValueCountFrequency (%)
380373476833 1
0.3%
524410176802 1
0.3%
563340703829 1
0.3%
607249356789 1
0.3%
639590016277 1
0.3%
681027401103 1
0.3%
701623414933 1
0.3%
704225811091 1
0.3%
737520967115 1
0.3%
780546994131 1
0.3%
ValueCountFrequency (%)
1530442431505160 1
0.3%
329978617431509 1
0.3%
312773665682380 1
0.3%
253222033923808 1
0.3%
183640240480310 1
0.3%
120134193095010 1
0.3%
110085529476345 1
0.3%
99316559486941 1
0.3%
88908688778679 1
0.3%
85983537444018 1
0.3%

자치단체금액(A)(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct292
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5627839 × 1013
Minimum3.7768489 × 1011
Maximum1.3442779 × 1015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T07:30:02.202348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.7768489 × 1011
5-th percentile9.4704252 × 1011
Q12.0383459 × 1012
median3.0886566 × 1012
Q36.9938079 × 1012
95-th percentile4.9623875 × 1013
Maximum1.3442779 × 1015
Range1.3439002 × 1015
Interquartile range (IQR)4.955462 × 1012

Descriptive statistics

Standard deviation8.3368878 × 1013
Coefficient of variation (CV)5.334639
Kurtosis222.48389
Mean1.5627839 × 1013
Median Absolute Deviation (MAD)1.3995178 × 1012
Skewness14.186273
Sum4.5945846 × 1015
Variance6.9503698 × 1027
MonotonicityNot monotonic
2023-12-11T07:30:02.402307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25407634783325 2
 
0.7%
8317239621401 2
 
0.7%
2366989613617 1
 
0.3%
1145593972032 1
 
0.3%
2926271186100 1
 
0.3%
1592242412358 1
 
0.3%
1979539006504 1
 
0.3%
3444879988526 1
 
0.3%
2359862521338 1
 
0.3%
4283857162667 1
 
0.3%
Other values (282) 282
95.9%
ValueCountFrequency (%)
377684892354 1
0.3%
524410176802 1
0.3%
563340703829 1
0.3%
600887299025 1
0.3%
628718155930 1
0.3%
652135343732 1
0.3%
681027401103 1
0.3%
700404028005 1
0.3%
737520967115 1
0.3%
780314710263 1
0.3%
ValueCountFrequency (%)
1344277930595849 1
0.3%
280875395793526 1
0.3%
268274213662971 1
0.3%
210665172544655 1
0.3%
141257533321371 1
0.3%
110559797535114 1
0.3%
99389647039394 1
0.3%
91207790285430 1
0.3%
75830770981551 1
0.3%
73722795454850 1
0.3%

지방공공기관금액(B)(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct273
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3643256 × 1012
Minimum0
Maximum1.1993929 × 1014
Zeros20
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T07:30:02.572978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.8370029 × 109
median1.665731 × 1010
Q31.4874234 × 1011
95-th percentile3.2437374 × 1012
Maximum1.1993929 × 1014
Range1.1993929 × 1014
Interquartile range (IQR)1.4190533 × 1011

Descriptive statistics

Standard deviation8.1654065 × 1012
Coefficient of variation (CV)5.9849396
Kurtosis157.09526
Mean1.3643256 × 1012
Median Absolute Deviation (MAD)1.5312909 × 1010
Skewness11.598331
Sum4.0111174 × 1014
Variance6.6673864 × 1025
MonotonicityNot monotonic
2023-12-11T07:30:02.731829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20
 
6.8%
70633374476 2
 
0.7%
1318137710297 2
 
0.7%
9427385240 1
 
0.3%
10794616575 1
 
0.3%
14304391146 1
 
0.3%
21666846062 1
 
0.3%
31480909985 1
 
0.3%
22021385668 1
 
0.3%
19569633869 1
 
0.3%
Other values (263) 263
89.5%
ValueCountFrequency (%)
0 20
6.8%
379399127 1
 
0.3%
460000000 1
 
0.3%
479468967 1
 
0.3%
646554690 1
 
0.3%
689402360 1
 
0.3%
961606038 1
 
0.3%
1071124512 1
 
0.3%
1195421976 1
 
0.3%
1219386928 1
 
0.3%
ValueCountFrequency (%)
119939286946655 1
0.3%
43639189597966 1
0.3%
43443479935938 1
0.3%
20646938585852 1
0.3%
18290637045169 1
0.3%
14381920876344 1
0.3%
14286271302321 1
0.3%
13620249918514 1
0.3%
12536116298174 1
0.3%
8330711247072 1
0.3%

교육재정금액(C)(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.427296 × 1012
Minimum0
Maximum1.1757577 × 1014
Zeros257
Zeros (%)87.4%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T07:30:02.865149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6.1498442 × 1012
Maximum1.1757577 × 1014
Range1.1757577 × 1014
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.9756235 × 1012
Coefficient of variation (CV)5.5879254
Kurtosis156.85353
Mean1.427296 × 1012
Median Absolute Deviation (MAD)0
Skewness11.4551
Sum4.1962502 × 1014
Variance6.361057 × 1025
MonotonicityNot monotonic
2023-12-11T07:30:02.978845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 257
87.4%
33448849081385 2
 
0.7%
1593064252179 2
 
0.7%
7131289116416 2
 
0.7%
7161646422849 2
 
0.7%
5947885610635 2
 
0.7%
4482508920165 2
 
0.7%
5360800382263 2
 
0.7%
4255013900217 2
 
0.7%
4095724363027 2
 
0.7%
Other values (10) 19
 
6.5%
ValueCountFrequency (%)
0 257
87.4%
1593064252179 2
 
0.7%
2523176489911 2
 
0.7%
2916470848761 2
 
0.7%
3271782478058 2
 
0.7%
3276526193175 2
 
0.7%
4095724363027 2
 
0.7%
4255013900217 2
 
0.7%
4482508920165 2
 
0.7%
5347520162269 2
 
0.7%
ValueCountFrequency (%)
117575773131040 1
0.3%
33448849081385 2
0.7%
30948397651017 2
0.7%
15839819466075 2
0.7%
7161646422849 2
0.7%
7131289116416 2
0.7%
6899236655030 2
0.7%
6524910218993 2
0.7%
5947885610635 2
0.7%
5360800382263 2
0.7%

내외부거래금액(D)(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct141
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5794833 × 1011
Minimum0
Maximum5.1350559 × 1013
Zeros107
Zeros (%)36.4%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T07:30:03.163869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5 × 108
Q33.14075 × 1010
95-th percentile1.9380881 × 1012
Maximum5.1350559 × 1013
Range5.1350559 × 1013
Interquartile range (IQR)3.14075 × 1010

Descriptive statistics

Standard deviation3.4669884 × 1012
Coefficient of variation (CV)6.2138163
Kurtosis161.22972
Mean5.5794833 × 1011
Median Absolute Deviation (MAD)5 × 108
Skewness11.695031
Sum1.6403681 × 1014
Variance1.2020009 × 1025
MonotonicityNot monotonic
2023-12-11T07:30:03.315820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 107
36.4%
500000000 10
 
3.4%
200000000 8
 
2.7%
300000000 7
 
2.4%
100000000 3
 
1.0%
400000000 3
 
1.0%
20000000 3
 
1.0%
800000000 3
 
1.0%
150000000 2
 
0.7%
2609650416950 2
 
0.7%
Other values (131) 146
49.7%
ValueCountFrequency (%)
0 107
36.4%
20000000 3
 
1.0%
24489450 1
 
0.3%
40000000 1
 
0.3%
60000000 1
 
0.3%
100000000 3
 
1.0%
150000000 2
 
0.7%
200000000 8
 
2.7%
210000000 2
 
0.7%
250000000 2
 
0.7%
ValueCountFrequency (%)
51350559168384 1
0.3%
16922147684888 1
0.3%
16900592243074 1
0.3%
7828913298209 1
0.3%
7823128816209 1
0.3%
7555058415585 1
0.3%
7554758415585 1
0.3%
6592923037285 1
0.3%
6592423037285 1
0.3%
4992566029254 1
0.3%

Interactions

2023-12-11T07:29:59.243849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:57.077460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:57.663684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:58.209635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:58.726229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:59.337833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:57.186499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:57.774961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:58.317716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:58.832232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:59.424674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:57.308335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:57.882988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:58.439304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:58.958440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:59.509714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:57.422528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:57.976588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:58.539207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:59.049023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:59.603563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:57.560514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:58.094513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:58.636141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:29:59.140844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:30:03.450599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도시군명합계금액(A+B+C-D)(원)자치단체금액(A)(원)지방공공기관금액(B)(원)교육재정금액(C)(원)내외부거래금액(D)(원)
회계연도1.000NaN0.0550.2050.0530.1650.000
시군명NaN1.0001.0001.0001.0001.000NaN
합계금액(A+B+C-D)(원)0.0551.0001.0000.9920.9920.9960.981
자치단체금액(A)(원)0.2051.0000.9921.0000.9760.9810.963
지방공공기관금액(B)(원)0.0531.0000.9920.9761.0000.9980.985
교육재정금액(C)(원)0.1651.0000.9960.9810.9981.0000.981
내외부거래금액(D)(원)0.000NaN0.9810.9630.9850.9811.000
2023-12-11T07:30:03.585265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
합계금액(A+B+C-D)(원)자치단체금액(A)(원)지방공공기관금액(B)(원)교육재정금액(C)(원)내외부거래금액(D)(원)회계연도
합계금액(A+B+C-D)(원)1.0001.0000.8160.5690.7250.037
자치단체금액(A)(원)1.0001.0000.8080.5610.7220.136
지방공공기관금액(B)(원)0.8160.8081.0000.5620.7410.034
교육재정금액(C)(원)0.5690.5610.5621.0000.5690.109
내외부거래금액(D)(원)0.7250.7220.7410.5691.0000.000
회계연도0.0370.1360.0340.1090.0001.000

Missing values

2023-12-11T07:29:59.713787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:29:59.847957image/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

회계연도시군명자치단체명합계금액(A+B+C-D)(원)자치단체금액(A)(원)지방공공기관금액(B)(원)교육재정금액(C)(원)내외부거래금액(D)(원)
02021가평군가평군23753769988572366989613617942738524001040000000
12021경기도본청859835374440184105706068036913620249918514334488490813852142622236250
22021계경기계32997861743150928087539579352620646938585852334488490813854992566029254
32021고양시고양시20394745457502200125121464846018372160180219603905000
42021과천시과천시246820881352523043665567823528422567430189000000000
52021광명시광명시3894217421464388327689115835940530306025000000000
62021광주시광주시420535990942541252706887128008922071300
72021구리시구리시372486230926536682495142392609077950260204295000000
82021군포시군포시4476887325753445703586021751421465536031570000000
92021김포시김포시767797075931476517337658561945293722080168292378750
회계연도시군명자치단체명합계금액(A+B+C-D)(원)자치단체금액(A)(원)지방공공기관금액(B)(원)교육재정금액(C)(원)내외부거래금액(D)(원)
2842020<NA>함양군30185172788633018517278863000
2852020<NA>거창군246837033539024568172422461155309314400
2862020<NA>경남계1100855294763459938964703939440296163245747131289116416465023004039
2872020<NA>합천군229561524443422853022640081031298042600
2882020<NA>전국계1530442431505160134427793059584911993928694665511757577313104051350559168384
2892020<NA>제주계280130756608012540763478332513181377102971593064252179305761085000
2902020<NA>본청280130756608012540763478332513181377102971593064252179305761085000
2912020<NA>종로구35503045795893547227320635411263788301035378929
2922020<NA>중구23927409378092386105106523841583128601780000000
2932020<NA>용산구26855827320422674305700518117770315240500000000