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

Dataset

Description통합재정 수지비율[당초] 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=NGV9AH4OOVX7NF6X1FX222934545&infSeq=1

Alerts

세입금액(원) is highly overall correlated with 지출금액(원) and 1 other fieldsHigh correlation
지출금액(원) is highly overall correlated with 세입금액(원) and 1 other fieldsHigh correlation
통합재정규모금액(원) is highly overall correlated with 세입금액(원) and 1 other fieldsHigh correlation
시군명 has 243 (88.4%) missing valuesMissing
세입금액(원) has unique valuesUnique
지출금액(원) has unique valuesUnique
통합재정규모금액(원) has unique valuesUnique
순융자금액(원) has 17 (6.2%) zerosZeros

Reproduction

Analysis started2023-12-10 21:24:38.626131
Analysis finished2023-12-10 21:24:41.119509
Duration2.49 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
2022
243 
2023
32 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2022 243
88.4%
2023 32
 
11.6%

Length

2023-12-11T06:24:41.176318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:24:41.245396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 243
88.4%
2023 32
 
11.6%

시군명
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing243
Missing (%)88.4%
Memory size2.3 KiB
2023-12-11T06:24:41.385689image/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%
2023-12-11T06:24:41.674105image/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
2023-12-11T06:24:41.947297image/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%
2023-12-11T06:24:42.330387image/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%

세입금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5839016 × 1012
Minimum1.6716091 × 1011
Maximum3.4355909 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:24:42.454319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.6716091 × 1011
5-th percentile3.4188324 × 1011
Q15.0286931 × 1011
median7.1861523 × 1011
Q31.0927821 × 1012
95-th percentile5.6299428 × 1012
Maximum3.4355909 × 1013
Range3.4188748 × 1013
Interquartile range (IQR)5.8991274 × 1011

Descriptive statistics

Standard deviation3.7387398 × 1012
Coefficient of variation (CV)2.3604622
Kurtosis53.583354
Mean1.5839016 × 1012
Median Absolute Deviation (MAD)2.4743352 × 1011
Skewness6.8870583
Sum4.3557294 × 1014
Variance1.3978175 × 1025
MonotonicityNot monotonic
2023-12-11T06:24:42.575696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
511372702000 1
 
0.4%
654061216000 1
 
0.4%
365490102000 1
 
0.4%
604147173000 1
 
0.4%
1005654634000 1
 
0.4%
592366016000 1
 
0.4%
968378686000 1
 
0.4%
962162661000 1
 
0.4%
831518173000 1
 
0.4%
420888575000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
167160912000 1
0.4%
189315359000 1
0.4%
215395879000 1
0.4%
249446490000 1
0.4%
265182458000 1
0.4%
285711710000 1
0.4%
299273624000 1
0.4%
305626093000 1
0.4%
306702557000 1
0.4%
307889018000 1
0.4%
ValueCountFrequency (%)
34355908516000 1
0.4%
32318135417000 1
0.4%
32160947775000 1
0.4%
12418108388000 1
0.4%
10956642564000 1
0.4%
10526258946000 1
0.4%
10355698759000 1
0.4%
9330640198000 1
0.4%
8845392337000 1
0.4%
8004062640000 1
0.4%

지출금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6424822 × 1012
Minimum1.680857 × 1011
Maximum3.4891881 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:24:42.692735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.680857 × 1011
5-th percentile3.622425 × 1011
Q15.2743934 × 1011
median7.5627703 × 1011
Q31.1648857 × 1012
95-th percentile5.9838871 × 1012
Maximum3.4891881 × 1013
Range3.4723795 × 1013
Interquartile range (IQR)6.3744632 × 1011

Descriptive statistics

Standard deviation3.766485 × 1012
Coefficient of variation (CV)2.2931664
Kurtosis52.317699
Mean1.6424822 × 1012
Median Absolute Deviation (MAD)2.6984472 × 1011
Skewness6.7811681
Sum4.516826 × 1014
Variance1.4186409 × 1025
MonotonicityNot monotonic
2023-12-11T06:24:42.811845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
513487949000 1
 
0.4%
688891540000 1
 
0.4%
379405021000 1
 
0.4%
597822910000 1
 
0.4%
1038706760000 1
 
0.4%
615756848000 1
 
0.4%
1001393423000 1
 
0.4%
1004187713000 1
 
0.4%
872313406000 1
 
0.4%
404848903000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
168085695000 1
0.4%
212199833000 1
0.4%
233072823000 1
0.4%
255632869000 1
0.4%
278139690000 1
0.4%
283415810000 1
0.4%
306206863000 1
0.4%
317616371000 1
0.4%
327967629000 1
0.4%
328608666000 1
0.4%
ValueCountFrequency (%)
34891880831000 1
0.4%
32393880534000 1
0.4%
31731769640000 1
0.4%
12691970382000 1
0.4%
11391443942000 1
0.4%
10763042013000 1
0.4%
10399341428000 1
0.4%
9578864190000 1
0.4%
9168957684000 1
0.4%
8248683835000 1
0.4%

순융자금액(원)
Real number (ℝ)

ZEROS 

Distinct240
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3498283 × 1010
Minimum-1.9948605 × 1011
Maximum1.5451075 × 1012
Zeros17
Zeros (%)6.2%
Negative38
Negative (%)13.8%
Memory size2.5 KiB
2023-12-11T06:24:42.933129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.9948605 × 1011
5-th percentile-72281500
Q124468500
median2.255 × 108
Q31.1462145 × 109
95-th percentile7.0084561 × 109
Maximum1.5451075 × 1012
Range1.7445935 × 1012
Interquartile range (IQR)1.121746 × 109

Descriptive statistics

Standard deviation1.1602619 × 1011
Coefficient of variation (CV)8.5956258
Kurtosis126.92028
Mean1.3498283 × 1010
Median Absolute Deviation (MAD)2.42016 × 108
Skewness10.700621
Sum3.712028 × 1012
Variance1.3462078 × 1022
MonotonicityNot monotonic
2023-12-11T06:24:43.051681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17
 
6.2%
20000000 4
 
1.5%
30000000 4
 
1.5%
50000000 3
 
1.1%
100000000 3
 
1.1%
-1000000 3
 
1.1%
250000000 2
 
0.7%
-70000000 2
 
0.7%
40000000 2
 
0.7%
70000000 2
 
0.7%
Other values (230) 233
84.7%
ValueCountFrequency (%)
-199486053000 1
0.4%
-50599889000 1
0.4%
-5223830000 1
0.4%
-1056000000 1
0.4%
-679933000 1
0.4%
-581080000 1
0.4%
-543084000 1
0.4%
-489135000 1
0.4%
-224172000 1
0.4%
-159500000 1
0.4%
ValueCountFrequency (%)
1545107470000 1
0.4%
930787812000 1
0.4%
570833176000 1
0.4%
235528486000 1
0.4%
196740893000 1
0.4%
135485152000 1
0.4%
38719000000 1
0.4%
31785003000 1
0.4%
17920606000 1
0.4%
17662000000 1
0.4%

통합재정규모금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6559805 × 1012
Minimum1.681857 × 1011
Maximum3.5462714 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:24:43.171247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.681857 × 1011
5-th percentile3.6348641 × 1011
Q15.2760592 × 1011
median7.5637703 × 1011
Q31.1676075 × 1012
95-th percentile5.9908472 × 1012
Maximum3.5462714 × 1013
Range3.5294528 × 1013
Interquartile range (IQR)6.4000156 × 1011

Descriptive statistics

Standard deviation3.8615064 × 1012
Coefficient of variation (CV)2.331855
Kurtosis53.383871
Mean1.6559805 × 1012
Median Absolute Deviation (MAD)2.6989732 × 1011
Skewness6.8668341
Sum4.5539463 × 1014
Variance1.4911232 × 1025
MonotonicityNot monotonic
2023-12-11T06:24:43.293902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
513540949000 1
 
0.4%
688921440000 1
 
0.4%
380166407000 1
 
0.4%
597865466000 1
 
0.4%
1038806760000 1
 
0.4%
615802463000 1
 
0.4%
1001393423000 1
 
0.4%
1004237213000 1
 
0.4%
872403406000 1
 
0.4%
404907903000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
168185695000 1
0.4%
212292833000 1
0.4%
233072823000 1
0.4%
255633869000 1
0.4%
278209690000 1
0.4%
283455810000 1
0.4%
306511863000 1
0.4%
317798371000 1
0.4%
328017629000 1
0.4%
328662946000 1
0.4%
ValueCountFrequency (%)
35462714007000 1
0.4%
33324668346000 1
0.4%
33276877110000 1
0.4%
12723755385000 1
0.4%
11403984405000 1
0.4%
10712442124000 1
0.4%
10634869914000 1
0.4%
9775605083000 1
0.4%
9186878290000 1
0.4%
8251857811000 1
0.4%

통합재정수지비율(%)
Real number (ℝ)

Distinct242
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-4.6601455
Minimum-18.29
Maximum4.36
Zeros0
Zeros (%)0.0%
Negative256
Negative (%)93.1%
Memory size2.5 KiB
2023-12-11T06:24:43.448419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-18.29
5-th percentile-10.778
Q1-6.51
median-3.94
Q3-2.38
95-th percentile0.772
Maximum4.36
Range22.65
Interquartile range (IQR)4.13

Descriptive statistics

Standard deviation3.7193541
Coefficient of variation (CV)-0.79811974
Kurtosis1.8253394
Mean-4.6601455
Median Absolute Deviation (MAD)2.02
Skewness-0.9169707
Sum-1281.54
Variance13.833595
MonotonicityNot monotonic
2023-12-11T06:24:43.605292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-2.08 3
 
1.1%
-1.73 3
 
1.1%
-4.33 3
 
1.1%
-4.36 2
 
0.7%
-3.68 2
 
0.7%
-3.12 2
 
0.7%
-7.45 2
 
0.7%
-2.79 2
 
0.7%
-3.92 2
 
0.7%
-6.62 2
 
0.7%
Other values (232) 252
91.6%
ValueCountFrequency (%)
-18.29 1
0.4%
-17.98 1
0.4%
-17.8 1
0.4%
-17.46 1
0.4%
-16.12 1
0.4%
-15.56 1
0.4%
-15.32 1
0.4%
-14.19 1
0.4%
-12.28 1
0.4%
-12.1 1
0.4%
ValueCountFrequency (%)
4.36 1
0.4%
3.95 1
0.4%
2.91 1
0.4%
2.21 1
0.4%
2.18 1
0.4%
1.85 1
0.4%
1.8 1
0.4%
1.24 1
0.4%
1.19 1
0.4%
1.18 1
0.4%

Interactions

2023-12-11T06:24:40.443436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:38.895559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:39.296309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:39.709004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:40.079499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:40.512859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:38.973984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:39.382161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:39.784427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:40.151427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:40.579894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:39.053300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:39.471725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:39.860946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:40.224155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:40.647445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:39.139756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:39.556809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:39.937998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:40.297767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:40.717173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:39.221745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:39.641433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:40.013201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:40.369260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:24:43.677016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도시군명세입금액(원)지출금액(원)순융자금액(원)통합재정규모금액(원)통합재정수지비율(%)
회계연도1.000NaN0.0000.0000.1520.0000.231
시군명NaN1.0001.0001.0001.0001.0001.000
세입금액(원)0.0001.0001.0001.0000.7700.9980.000
지출금액(원)0.0001.0001.0001.0000.7700.9980.000
순융자금액(원)0.1521.0000.7700.7701.0000.7320.000
통합재정규모금액(원)0.0001.0000.9980.9980.7321.0000.000
통합재정수지비율(%)0.2311.0000.0000.0000.0000.0001.000
2023-12-11T06:24:43.793865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세입금액(원)지출금액(원)순융자금액(원)통합재정규모금액(원)통합재정수지비율(%)회계연도
세입금액(원)1.0000.9970.2980.997-0.0970.000
지출금액(원)0.9971.0000.2991.000-0.1540.000
순융자금액(원)0.2980.2991.0000.301-0.1140.111
통합재정규모금액(원)0.9971.0000.3011.000-0.1550.000
통합재정수지비율(%)-0.097-0.154-0.114-0.1551.0000.174
회계연도0.0000.0000.1110.0000.1741.000

Missing values

2023-12-11T06:24:40.987722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:24:41.080527image/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

회계연도시군명자치단체명세입금액(원)지출금액(원)순융자금액(원)통합재정규모금액(원)통합재정수지비율(%)
02023가평군경기가평군51137270200051348794900053000000513540949000-0.42
12023경기도경기본청323181354170003239388053400093078781200033324668346000-3.02
22023고양시경기고양시2673236725000275857260900029000000002761472609000-3.2
32023과천시경기과천시376214879000448154688000370000000448524688000-16.12
42023광명시경기광명시9200548610001006629494000316190001006661113000-8.6
52023광주시경기광주시121074806900013001568020004628750001300619677000-6.91
62023구리시경기구리시609303311000668430312000-30000000668400312000-8.84
72023군포시경기군포시779208443000844658735000-1000000844657735000-7.75
82023김포시경기김포시15046527630001589433440000-50000001589428440000-5.33
92023남양주시경기남양주시204973878400021182361260001788200002118414946000-3.24
회계연도시군명자치단체명세입금액(원)지출금액(원)순융자금액(원)통합재정규모금액(원)통합재정수지비율(%)
2652022<NA>충북영동군55752029000058103690000091600000581128500000-4.06
2662022<NA>충북증평군2494464900002556328690001000000255633869000-2.42
2672022<NA>충북진천군5668456150005751637410001000000575164741000-1.45
2682022<NA>충북괴산군522161965000535080633000449534000535530167000-2.5
2692022<NA>충북음성군713650556000734227738000221000000734448738000-2.83
2702022<NA>충북단양군3642923830003988861360000398886136000-8.67
2712022<NA>충남본청8004062640000824868383500031739760008251857811000-3.0
2722022<NA>충남천안시187325858100020684434440006089070002069052351000-9.46
2732022<NA>충남공주시7737400830007967972100001000000000797797210000-3.02
2742022<NA>충남보령시8434997720008555990390001335453000856934492000-1.57