Overview

Dataset statistics

Number of variables8
Number of observations275
Missing cells243
Missing cells (%)11.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.9 KiB
Average record size in memory70.5 B

Variable types

Categorical1
Text2
Numeric5

Alerts

전년도말현재액(원) is highly overall correlated with 발생액(원) and 2 other fieldsHigh correlation
발생액(원) is highly overall correlated with 전년도말현재액(원) and 2 other fieldsHigh correlation
소멸액(원) is highly overall correlated with 전년도말현재액(원) and 2 other fieldsHigh correlation
당해년도 현재액(원) is highly overall correlated with 전년도말현재액(원) and 2 other fieldsHigh correlation
시군명 has 243 (88.4%) missing valuesMissing
전년도말현재액(원) has 10 (3.6%) zerosZeros
증감액(원) has 15 (5.5%) zerosZeros
발생액(원) has 18 (6.5%) zerosZeros
소멸액(원) has 14 (5.1%) zerosZeros
당해년도 현재액(원) has 10 (3.6%) zerosZeros

Reproduction

Analysis started2023-12-10 23:11:37.182948
Analysis finished2023-12-10 23:11:40.167548
Duration2.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회계연도
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2020
243 
2021
32 

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 243
88.4%
2021 32
 
11.6%

Length

2023-12-11T08:11:40.231551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:11:40.333091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 243
88.4%
2021 32
 
11.6%

시군명
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing243
Missing (%)88.4%
Memory size2.3 KiB
2023-12-11T08:11:40.506940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.09375
Min length3

Characters and Unicode

Total characters99
Distinct characters41
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

Unique32 ?
Unique (%)100.0%

Sample

1st row가평군
2nd row경기도
3rd row고양시
4th row과천시
5th row광명시
ValueCountFrequency (%)
경기도 1
 
3.1%
고양시 1
 
3.1%
화성시 1
 
3.1%
하남시 1
 
3.1%
포천시 1
 
3.1%
평택시 1
 
3.1%
파주시 1
 
3.1%
이천시 1
 
3.1%
의정부시 1
 
3.1%
의왕시 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T08:11:40.827255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

자치단체명
Text

Distinct243
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-11T08:11:41.124851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.8872727
Min length4

Characters and Unicode

Total characters1344
Distinct characters133
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

Unique211 ?
Unique (%)76.7%

Sample

1st row경기가평군
2nd row경기본청
3rd row경기고양시
4th row경기과천시
5th row경기광명시
ValueCountFrequency (%)
경기가평군 2
 
0.7%
경기평택시 2
 
0.7%
경기안성시 2
 
0.7%
경기여주시 2
 
0.7%
경기용인시 2
 
0.7%
경기연천군 2
 
0.7%
경기양평군 2
 
0.7%
경기의왕시 2
 
0.7%
경기하남시 2
 
0.7%
경기이천시 2
 
0.7%
Other values (233) 255
92.7%
2023-12-11T08:11:41.582340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1344
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1344
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1344
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

전년도말현재액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct266
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3242677 × 1010
Minimum0
Maximum2.5089034 × 1012
Zeros10
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T08:11:41.704462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.5175407 × 109
Q13.8380348 × 109
median6.5523303 × 109
Q31.4403978 × 1010
95-th percentile1.520089 × 1011
Maximum2.5089034 × 1012
Range2.5089034 × 1012
Interquartile range (IQR)1.0565943 × 1010

Descriptive statistics

Standard deviation2.4575175 × 1011
Coefficient of variation (CV)4.6156911
Kurtosis55.203807
Mean5.3242677 × 1010
Median Absolute Deviation (MAD)3.6296327 × 109
Skewness7.0857315
Sum1.4641736 × 1013
Variance6.0393921 × 1022
MonotonicityNot monotonic
2023-12-11T08:11:41.820185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
3.6%
3451312073 1
 
0.4%
8873933824 1
 
0.4%
2756196976 1
 
0.4%
1640355463 1
 
0.4%
2429781416 1
 
0.4%
4235601165 1
 
0.4%
2629393242 1
 
0.4%
5408684667 1
 
0.4%
5700528076 1
 
0.4%
Other values (256) 256
93.1%
ValueCountFrequency (%)
0 10
3.6%
315000000 1
 
0.4%
830041660 1
 
0.4%
863985430 1
 
0.4%
1428187030 1
 
0.4%
1555835170 1
 
0.4%
1640355463 1
 
0.4%
1664778460 1
 
0.4%
1688390830 1
 
0.4%
1738496540 1
 
0.4%
ValueCountFrequency (%)
2508903414075 1
0.4%
1665173885239 1
0.4%
1636195940771 1
0.4%
1624842363085 1
0.4%
976066734359 1
0.4%
890148008482 1
0.4%
712676597217 1
0.4%
442688677830 1
0.4%
349084125978 1
0.4%
318689772420 1
0.4%

증감액(원)
Real number (ℝ)

ZEROS 

Distinct260
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.319279 × 1010
Minimum-1.0950706 × 1011
Maximum1.0436138 × 1012
Zeros15
Zeros (%)5.5%
Negative152
Negative (%)55.3%
Memory size2.5 KiB
2023-12-11T08:11:41.933036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.0950706 × 1011
5-th percentile-2.6275734 × 109
Q1-3.4718996 × 108
median-33943770
Q33.617388 × 108
95-th percentile7.0018442 × 109
Maximum1.0436138 × 1012
Range1.1531208 × 1012
Interquartile range (IQR)7.0892877 × 108

Descriptive statistics

Standard deviation1.0096842 × 1011
Coefficient of variation (CV)7.6533025
Kurtosis74.544486
Mean1.319279 × 1010
Median Absolute Deviation (MAD)3.4204979 × 108
Skewness8.4541064
Sum3.6280174 × 1012
Variance1.0194621 × 1022
MonotonicityNot monotonic
2023-12-11T08:11:42.047400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15
 
5.5%
50000000 2
 
0.7%
1778477570 1
 
0.4%
-2969177965 1
 
0.4%
-2202051005 1
 
0.4%
-693922458 1
 
0.4%
-42155680 1
 
0.4%
-729516742 1
 
0.4%
-169629626 1
 
0.4%
-219282553 1
 
0.4%
Other values (250) 250
90.9%
ValueCountFrequency (%)
-109507062660 1
0.4%
-24003902170 1
0.4%
-23077153570 1
0.4%
-21211154500 1
0.4%
-12430172770 1
0.4%
-11293968580 1
0.4%
-10280044700 1
0.4%
-8345272250 1
0.4%
-4812456200 1
0.4%
-4652174500 1
0.4%
ValueCountFrequency (%)
1043613753149 1
0.4%
865345625926 1
0.4%
843729528836 1
0.4%
418780035182 1
0.4%
233713229535 1
0.4%
198240276693 1
0.4%
52050700000 1
0.4%
43451864366 1
0.4%
41281647551 1
0.4%
27151553310 1
0.4%

발생액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct254
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1829543 × 1010
Minimum0
Maximum1.7476748 × 1012
Zeros18
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T08:11:42.167565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.3192005 × 108
median7.9824775 × 108
Q33.5369433 × 109
95-th percentile5.0562183 × 1010
Maximum1.7476748 × 1012
Range1.7476748 × 1012
Interquartile range (IQR)3.4050232 × 109

Descriptive statistics

Standard deviation1.8543783 × 1011
Coefficient of variation (CV)5.825966
Kurtosis59.628933
Mean3.1829543 × 1010
Median Absolute Deviation (MAD)7.7061078 × 108
Skewness7.5458
Sum8.7531243 × 1012
Variance3.438719 × 1022
MonotonicityNot monotonic
2023-12-11T08:11:42.345195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18
 
6.5%
40000000 3
 
1.1%
10000000 2
 
0.7%
20000000 2
 
0.7%
2600247600 1
 
0.4%
1483245289 1
 
0.4%
518913342 1
 
0.4%
382455920 1
 
0.4%
825455429325 1
 
0.4%
488919860 1
 
0.4%
Other values (244) 244
88.7%
ValueCountFrequency (%)
0 18
6.5%
3115590 1
 
0.4%
3300000 1
 
0.4%
3942440 1
 
0.4%
4100000 1
 
0.4%
6549660 1
 
0.4%
7400520 1
 
0.4%
10000000 2
 
0.7%
17611436 1
 
0.4%
19000000 1
 
0.4%
ValueCountFrequency (%)
1747674787141 1
0.4%
1669034014201 1
0.4%
1305193919070 1
0.4%
1006243924292 1
0.4%
825455429325 1
0.4%
561723948696 1
0.4%
275606378000 1
0.4%
119069820528 1
0.4%
117385622060 1
0.4%
96038455500 1
0.4%

소멸액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct262
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8636752 × 1010
Minimum0
Maximum9.0394526 × 1011
Zeros14
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T08:11:42.474433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile519533
Q12.4200698 × 108
median7.6251698 × 108
Q33.5262708 × 109
95-th percentile5.0208286 × 1010
Maximum9.0394526 × 1011
Range9.0394526 × 1011
Interquartile range (IQR)3.2842638 × 109

Descriptive statistics

Standard deviation9.3350921 × 1010
Coefficient of variation (CV)5.0089693
Kurtosis56.175716
Mean1.8636752 × 1010
Median Absolute Deviation (MAD)6.8635557 × 108
Skewness7.1892727
Sum5.1251069 × 1012
Variance8.7143944 × 1021
MonotonicityNot monotonic
2023-12-11T08:11:42.598447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14
 
5.1%
235259132 1
 
0.4%
162380680 1
 
0.4%
800788866 1
 
0.4%
5569425565 1
 
0.4%
3685296294 1
 
0.4%
1212835800 1
 
0.4%
424611600 1
 
0.4%
1218436602 1
 
0.4%
363625420 1
 
0.4%
Other values (252) 252
91.6%
ValueCountFrequency (%)
0 14
5.1%
742190 1
 
0.4%
6549660 1
 
0.4%
20000000 1
 
0.4%
25913710 1
 
0.4%
27800040 1
 
0.4%
27816497 1
 
0.4%
30818860 1
 
0.4%
35000000 1
 
0.4%
37447420 1
 
0.4%
ValueCountFrequency (%)
903945258305 1
0.4%
808003647599 1
0.4%
625420261052 1
0.4%
439848293144 1
0.4%
406675394143 1
0.4%
328010719161 1
0.4%
226892684720 1
0.4%
223555678000 1
0.4%
119115609070 1
0.4%
115442859910 1
0.4%

당해년도 현재액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct266
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.6435467 × 1010
Minimum0
Maximum3.5525172 × 1012
Zeros10
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T08:11:42.722029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.552074 × 109
Q13.6298871 × 109
median6.285304 × 109
Q31.5337724 × 1010
95-th percentile1.4121099 × 1011
Maximum3.5525172 × 1012
Range3.5525172 × 1012
Interquartile range (IQR)1.1707837 × 1010

Descriptive statistics

Standard deviation3.3397809 × 1011
Coefficient of variation (CV)5.0271054
Kurtosis61.033167
Mean6.6435467 × 1010
Median Absolute Deviation (MAD)3.2693931 × 109
Skewness7.4176884
Sum1.8269753 × 1013
Variance1.1154137 × 1023
MonotonicityNot monotonic
2023-12-11T08:11:42.861927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
3.6%
3418395011 1
 
0.4%
8654651271 1
 
0.4%
3175399936 1
 
0.4%
1637173573 1
 
0.4%
2293144789 1
 
0.4%
4139575218 1
 
0.4%
2126171992 1
 
0.4%
5239055041 1
 
0.4%
5103159120 1
 
0.4%
Other values (256) 256
93.1%
ValueCountFrequency (%)
0 10
3.6%
365000000 1
 
0.4%
830041660 1
 
0.4%
1417745170 1
 
0.4%
1536210830 1
 
0.4%
1558872540 1
 
0.4%
1637173573 1
 
0.4%
1641516740 1
 
0.4%
1896342978 1
 
0.4%
2018637030 1
 
0.4%
ValueCountFrequency (%)
3552517167224 1
0.4%
2508903414075 1
0.4%
1858555592620 1
0.4%
1834436217464 1
0.4%
1755493634408 1
0.4%
1131456632399 1
0.4%
1028117434359 1
0.4%
376235679288 1
0.4%
333181615170 1
0.4%
294685870250 1
0.4%

Interactions

2023-12-11T08:11:39.450647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:37.487596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:37.888990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:38.277826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:38.765967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:39.561336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:37.561796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:37.966271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:38.380078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:38.846875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:39.647990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:37.632209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:38.039356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:38.501743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:39.200681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:39.780350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:37.727220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:38.124784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:38.589904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:39.293469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:39.867696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:37.809678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:38.193731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:38.667898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:11:39.365719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:11:42.960998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도시군명전년도말현재액(원)증감액(원)발생액(원)소멸액(원)당해년도 현재액(원)
회계연도1.000NaN0.1670.1540.0000.1130.100
시군명NaN1.0001.0001.0001.0001.0001.000
전년도말현재액(원)0.1671.0001.0000.9800.9080.9250.970
증감액(원)0.1541.0000.9801.0000.9080.9200.966
발생액(원)0.0001.0000.9080.9081.0000.9460.964
소멸액(원)0.1131.0000.9250.9200.9461.0000.989
당해년도 현재액(원)0.1001.0000.9700.9660.9640.9891.000
2023-12-11T08:11:43.101959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전년도말현재액(원)증감액(원)발생액(원)소멸액(원)당해년도 현재액(원)회계연도
전년도말현재액(원)1.0000.1620.7460.7310.9620.119
증감액(원)0.1621.0000.341-0.0250.3060.110
발생액(원)0.7460.3411.0000.8520.7790.000
소멸액(원)0.731-0.0250.8521.0000.6770.083
당해년도 현재액(원)0.9620.3060.7790.6771.0000.074
회계연도0.1190.1100.0000.0830.0741.000

Missing values

2023-12-11T08:11:40.001419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:11:40.119794image/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

회계연도시군명자치단체명전년도말현재액(원)증감액(원)발생액(원)소멸액(원)당해년도 현재액(원)
02021가평군경기가평군3451312073-329170622023420702352591323418395011
12021경기도경기본청2508903414075104361375314916690340142016254202610523552517167224
22021고양시경기고양시21097718867-7040400402302886870300692691020393678827
32021과천시경기과천시3594273671-1485068482765986034251054513445766823
42021광명시경기광명시6003540470-493736520849059205786424405509803950
52021광주시경기광주시830041660409548005143362978322408177814925521711
62021구리시경기구리시4686475070-4510553547071580921771154641369535
72021군포시경기군포시524048449527392749119050140916573915267877244
82021김포시경기김포시4721982215-3694818796724631479709411324718287397
92021남양주시경기남양주시10691613324-6678682671827728200249559646710023745057
회계연도시군명자치단체명전년도말현재액(원)증감액(원)발생액(원)소멸액(원)당해년도 현재액(원)
2652020<NA>경북문경시7766857640-138608190270967783028482860207628249450
2662020<NA>경북경산시15785123076-834527225038729678087325690307439850826
2672020<NA>경북군위군4224437620-1127470990236643550034939064903096966630
2682020<NA>경북의성군4604404660-3779740001158439404938179404226430660
2692020<NA>경북청송군2479118850-761614100761614102402957440
2702020<NA>경북영양군1555835170-138090000200000001580900001417745170
2712020<NA>경북영덕군4477653537-38248400710152501092636504439405137
2722020<NA>경북청도군34658076100654966065496603465807610
2732020<NA>경북고령군3212186970-31398193033000003172819302898205040
2742020<NA>경북성주군2859807080-27477916002747791602585027920