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[최종] 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=KY3NBKPDCPFA1F4G0J4522943109&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 9 (3.3%) zerosZeros

Reproduction

Analysis started2023-12-10 21:43:42.974959
Analysis finished2023-12-10 21:43:46.206430
Duration3.23 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

2023-12-11T06:43:46.274939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:43:46.367306image/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
2023-12-11T06:43:46.558100image/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%
2023-12-11T06:43:46.933444image/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
2023-12-11T06:43:47.255823image/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%
2023-12-11T06:43:47.771891image/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%
Mean1.6399549 × 1012
Minimum1.9422586 × 1011
Maximum3.4868532 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:43:47.917997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9422586 × 1011
5-th percentile3.7418636 × 1011
Q15.3618152 × 1011
median7.9634905 × 1011
Q31.2712636 × 1012
95-th percentile5.4605403 × 1012
Maximum3.4868532 × 1013
Range3.4674306 × 1013
Interquartile range (IQR)7.3508211 × 1011

Descriptive statistics

Standard deviation3.7439657 × 1012
Coefficient of variation (CV)2.2829687
Kurtosis53.840568
Mean1.6399549 × 1012
Median Absolute Deviation (MAD)2.9701127 × 1011
Skewness6.8888455
Sum4.5098759 × 1014
Variance1.4017279 × 1025
MonotonicityNot monotonic
2023-12-11T06:43:48.065454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
635248815000 1
 
0.4%
2983356222000 1
 
0.4%
251379733000 1
 
0.4%
541567733000 1
 
0.4%
497216072000 1
 
0.4%
436188938000 1
 
0.4%
925247121000 1
 
0.4%
1276908836000 1
 
0.4%
5747371920000 1
 
0.4%
512830531000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
194225856000 1
0.4%
226817695000 1
0.4%
234409199000 1
0.4%
251379733000 1
0.4%
273539068000 1
0.4%
295042842000 1
0.4%
331997372000 1
0.4%
335463063000 1
0.4%
340720719000 1
0.4%
341588254000 1
0.4%
ValueCountFrequency (%)
34868531515000 1
0.4%
33502134482000 1
0.4%
30559780613000 1
0.4%
12525587120000 1
0.4%
11132801106000 1
0.4%
10718598515000 1
0.4%
10522325065000 1
0.4%
9145690979000 1
0.4%
8974206278000 1
0.4%
7864924774000 1
0.4%

지출금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8059721 × 1012
Minimum1.987098 × 1011
Maximum3.8801159 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:43:48.235646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.987098 × 1011
5-th percentile4.137396 × 1011
Q15.8618201 × 1011
median8.7720297 × 1011
Q31.3791835 × 1012
95-th percentile6.0670775 × 1012
Maximum3.8801159 × 1013
Range3.8602449 × 1013
Interquartile range (IQR)7.9300152 × 1011

Descriptive statistics

Standard deviation4.1062504 × 1012
Coefficient of variation (CV)2.2737065
Kurtosis55.395902
Mean1.8059721 × 1012
Median Absolute Deviation (MAD)3.2751676 × 1011
Skewness6.9870749
Sum4.9664232 × 1014
Variance1.6861293 × 1025
MonotonicityNot monotonic
2023-12-11T06:43:48.410552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
604748521000 1
 
0.4%
3200295434000 1
 
0.4%
269477491000 1
 
0.4%
605606677000 1
 
0.4%
547961837000 1
 
0.4%
468833211000 1
 
0.4%
1053235223000 1
 
0.4%
1510841171000 1
 
0.4%
6102701771000 1
 
0.4%
553096002000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
198709800000 1
0.4%
255150939000 1
0.4%
269477491000 1
0.4%
283469494000 1
0.4%
294790842000 1
0.4%
324552096000 1
0.4%
340344004000 1
0.4%
359780396000 1
0.4%
360176631000 1
0.4%
368281962000 1
0.4%
ValueCountFrequency (%)
38801158611000 1
0.4%
36940486942000 1
0.4%
33418122043000 1
0.4%
13400664216000 1
0.4%
11607603403000 1
0.4%
11341264299000 1
0.4%
10984091471000 1
0.4%
10138606046000 1
0.4%
9403862736000 1
0.4%
8391086867000 1
0.4%

순융자금액(원)
Real number (ℝ)

ZEROS 

Distinct256
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1992681 × 1010
Minimum-9.2090858 × 1010
Maximum1.0397558 × 1012
Zeros9
Zeros (%)3.3%
Negative43
Negative (%)15.6%
Memory size2.5 KiB
2023-12-11T06:43:48.584929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9.2090858 × 1010
5-th percentile-1.883418 × 108
Q128052000
median2.93129 × 108
Q32.2991135 × 109
95-th percentile3.3607038 × 1010
Maximum1.0397558 × 1012
Range1.1318467 × 1012
Interquartile range (IQR)2.2710615 × 109

Descriptive statistics

Standard deviation7.5474018 × 1010
Coefficient of variation (CV)6.2933401
Kurtosis132.88838
Mean1.1992681 × 1010
Median Absolute Deviation (MAD)3.38129 × 108
Skewness10.694476
Sum3.2979872 × 1012
Variance5.6963274 × 1021
MonotonicityNot monotonic
2023-12-11T06:43:48.755717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
3.3%
60000000 3
 
1.1%
100000000 3
 
1.1%
1000000 3
 
1.1%
30000000 2
 
0.7%
183000000 2
 
0.7%
28000000 2
 
0.7%
200000000 2
 
0.7%
80000000 2
 
0.7%
-249806000 1
 
0.4%
Other values (246) 246
89.5%
ValueCountFrequency (%)
-92090858000 1
0.4%
-1058630000 1
0.4%
-1049000000 1
0.4%
-722487000 1
0.4%
-708140000 1
0.4%
-684919000 1
0.4%
-508279000 1
0.4%
-380120000 1
0.4%
-338033000 1
0.4%
-331414000 1
0.4%
ValueCountFrequency (%)
1039755827000 1
0.4%
461878690000 1
0.4%
395501450000 1
0.4%
249164153000 1
0.4%
147376394000 1
0.4%
120665000000 1
0.4%
110376476000 1
0.4%
88523737000 1
0.4%
69960000000 1
0.4%
64310000000 1
0.4%

통합재정규모금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8179648 × 1012
Minimum1.987698 × 1011
Maximum3.9840914 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:43:48.899207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.987698 × 1011
5-th percentile4.1375594 × 1011
Q15.9376712 × 1011
median8.8482775 × 1011
Q31.3941748 × 1012
95-th percentile6.0664578 × 1012
Maximum3.9840914 × 1013
Range3.9642145 × 1013
Interquartile range (IQR)8.0040771 × 1011

Descriptive statistics

Standard deviation4.170182 × 1012
Coefficient of variation (CV)2.2938739
Kurtosis56.136279
Mean1.8179648 × 1012
Median Absolute Deviation (MAD)3.3189375 × 1011
Skewness7.0373326
Sum4.9994031 × 1014
Variance1.7390418 × 1025
MonotonicityNot monotonic
2023-12-11T06:43:49.038584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
604946921000 1
 
0.4%
3199972601000 1
 
0.4%
269478491000 1
 
0.4%
605668977000 1
 
0.4%
547712031000 1
 
0.4%
469254401000 1
 
0.4%
1053255223000 1
 
0.4%
1511024171000 1
 
0.4%
6102321651000 1
 
0.4%
552934002000 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
198769800000 1
0.4%
255631878000 1
0.4%
269478491000 1
0.4%
283466197000 1
0.4%
294840742000 1
0.4%
324652096000 1
0.4%
340354004000 1
0.4%
360114410000 1
0.4%
360476631000 1
0.4%
368004482000 1
0.4%
ValueCountFrequency (%)
39840914438000 1
0.4%
37335988392000 1
0.4%
33880000733000 1
0.4%
13435445717000 1
0.4%
11717979879000 1
0.4%
11249173441000 1
0.4%
11233255624000 1
0.4%
10139448804000 1
0.4%
9492386473000 1
0.4%
8416703142000 1
0.4%

통합재정수지비율(%)
Real number (ℝ)

Distinct258
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-9.5534909
Minimum-32.42
Maximum6.34
Zeros0
Zeros (%)0.0%
Negative271
Negative (%)98.5%
Memory size2.5 KiB
2023-12-11T06:43:49.204647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-32.42
5-th percentile-18.24
Q1-12.095
median-9.09
Q3-6.53
95-th percentile-2.458
Maximum6.34
Range38.76
Interquartile range (IQR)5.565

Descriptive statistics

Standard deviation5.1151929
Coefficient of variation (CV)-0.53542658
Kurtosis2.3620873
Mean-9.5534909
Median Absolute Deviation (MAD)2.76
Skewness-0.78389687
Sum-2627.21
Variance26.165199
MonotonicityNot monotonic
2023-12-11T06:43:49.640704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-7.25 3
 
1.1%
-8.89 2
 
0.7%
-11.79 2
 
0.7%
-5.45 2
 
0.7%
-8.35 2
 
0.7%
-7.5 2
 
0.7%
-9.25 2
 
0.7%
-6.84 2
 
0.7%
-9.8 2
 
0.7%
-9.11 2
 
0.7%
Other values (248) 254
92.4%
ValueCountFrequency (%)
-32.42 1
0.4%
-28.83 1
0.4%
-25.01 1
0.4%
-24.95 1
0.4%
-23.91 1
0.4%
-23.23 1
0.4%
-22.22 1
0.4%
-20.59 1
0.4%
-20.44 1
0.4%
-19.98 1
0.4%
ValueCountFrequency (%)
6.34 1
0.4%
5.01 1
0.4%
2.72 1
0.4%
2.26 1
0.4%
-1.12 1
0.4%
-1.28 1
0.4%
-1.38 1
0.4%
-1.39 1
0.4%
-1.61 1
0.4%
-1.86 1
0.4%

Interactions

2023-12-11T06:43:45.453766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:43.331571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:44.099607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:44.568652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:44.995190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:45.550545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:43.443131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:44.197483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:44.660946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:45.083297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:45.642153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:43.561683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:44.298409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:44.750234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:45.174965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:45.733598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:43.911955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:44.382244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:44.821594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:45.259797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:45.844684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:43.993906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:44.481523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:44.911989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:43:45.360380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:43:49.747846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도시군명세입금액(원)지출금액(원)순융자금액(원)통합재정규모금액(원)통합재정수지비율(%)
회계연도1.000NaN0.0080.0080.2380.0080.420
시군명NaN1.0001.0001.0001.0001.0001.000
세입금액(원)0.0081.0001.0000.9970.9230.9970.000
지출금액(원)0.0081.0000.9971.0000.9201.0000.000
순융자금액(원)0.2381.0000.9230.9201.0000.9200.000
통합재정규모금액(원)0.0081.0000.9971.0000.9201.0000.000
통합재정수지비율(%)0.4201.0000.0000.0000.0000.0001.000
2023-12-11T06:43:49.886959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세입금액(원)지출금액(원)순융자금액(원)통합재정규모금액(원)통합재정수지비율(%)회계연도
세입금액(원)1.0000.9950.3630.994-0.0300.000
지출금액(원)0.9951.0000.3650.999-0.1100.000
순융자금액(원)0.3630.3651.0000.372-0.0730.170
통합재정규모금액(원)0.9940.9990.3721.000-0.1150.000
통합재정수지비율(%)-0.030-0.110-0.073-0.1151.0000.317
회계연도0.0000.0000.1700.0000.3171.000

Missing values

2023-12-11T06:43:45.995896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:43:46.153378image/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(%)
02021가평군경기가평군6352488150006047485210001984000006049469210005.01
12021경기도경기본청348685315150003694048694200039550145000037335988392000-6.61
22021고양시경기고양시28899815260003125748432000546600000003180408432000-9.13
32021과천시경기과천시447278088000541171737000120665000000661836737000-32.42
42021광명시경기광명시9700678110001154043030000-458370001153997193000-15.94
52021광주시경기광주시1541033709000164713425600010411440001648175400000-6.5
62021구리시경기구리시762520608000802244711000-40785000802203926000-4.95
72021군포시경기군포시834717985000899235816000680000000899915816000-7.24
82021김포시경기김포시161341192400018284836430002000000001828683643000-11.77
92021남양주시경기남양주시224639231200024166704390004101370002417080576000-7.06
회계연도시군명자치단체명세입금액(원)지출금액(원)순융자금액(원)통합재정규모금액(원)통합재정수지비율(%)
2652020<NA>경북성주군4641499430005106261070001044000000511670107000-9.29
2662020<NA>경북칠곡군5721768440006051813360000605181336000-5.45
2672020<NA>경북예천군522114985000554123388000663136000554786524000-5.89
2682020<NA>경북봉화군4565193870004909391450003482000000494421145000-7.67
2692020<NA>경북울진군5465072300006309931810003116640000634109821000-13.82
2702020<NA>경북울릉군234409199000255150939000480939000255631878000-8.3
2712020<NA>경남본청1071859851500011341264299000-9209085800011249173441000-4.72
2722020<NA>경남창원시37224510510004153141358000129379000004166079258000-10.65
2732020<NA>경남진주시14569273610001760996325000125095210001773505846000-17.85
2742020<NA>경남통영시727500924000796114849000341908000796456757000-8.66