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 2 other fieldsHigh correlation
자치단체금액(A)(원) is highly overall correlated with 합계금액(A+B+C-D)(원) and 2 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 지방공공기관금액(B)(원) and 1 other fieldsHigh correlation
시군명 has 261 (88.8%) missing valuesMissing
지방공공기관금액(B)(원) has 41 (13.9%) zerosZeros
교육재정금액(C)(원) has 257 (87.4%) zerosZeros
내외부거래금액(D)(원) has 237 (80.6%) zerosZeros

Reproduction

Analysis started2023-12-10 21:57:54.151604
Analysis finished2023-12-10 21:57:57.117198
Duration2.97 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

2023-12-11T06:57:57.184150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:57:57.269729image/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
2023-12-11T06:57:57.432119image/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%
2023-12-11T06:57:57.752740image/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
2023-12-11T06:57:58.051818image/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%
북구 4
 
1.4%
남구 4
 
1.4%
의왕시 2
 
0.7%
양평군 2
 
0.7%
가평군 2
 
0.7%
파주시 2
 
0.7%
Other values (213) 243
82.7%
2023-12-11T06:57:58.487471image/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%
양 23
 
2.7%
청 23
 
2.7%
성 21
 
2.5%
계 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%
양 23
 
2.7%
청 23
 
2.7%
성 21
 
2.5%
계 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%
양 23
 
2.7%
청 23
 
2.7%
성 21
 
2.5%
계 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%
양 23
 
2.7%
청 23
 
2.7%
성 21
 
2.5%
계 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%
Mean1.322801 × 1012
Minimum7.7783147 × 109
Maximum1.167852 × 1014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T06:57:58.622736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.7783147 × 109
5-th percentile1.2341582 × 1010
Q12.5245073 × 1010
median4.7274275 × 1010
Q32.0783406 × 1011
95-th percentile4.3298226 × 1012
Maximum1.167852 × 1014
Range1.1677742 × 1014
Interquartile range (IQR)1.8258898 × 1011

Descriptive statistics

Standard deviation7.7724583 × 1012
Coefficient of variation (CV)5.8757577
Kurtosis170.67772
Mean1.322801 × 1012
Median Absolute Deviation (MAD)3.1701568 × 1010
Skewness12.152703
Sum3.889035 × 1014
Variance6.0411108 × 1025
MonotonicityNot monotonic
2023-12-11T06:57:58.748144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1596113408403 2
 
0.7%
452277546406 2
 
0.7%
29388196679 1
 
0.3%
123374510690 1
 
0.3%
10209331033 1
 
0.3%
466142170446 1
 
0.3%
109481844935 1
 
0.3%
46260295955 1
 
0.3%
68566089782 1
 
0.3%
411248209936 1
 
0.3%
Other values (282) 282
95.9%
ValueCountFrequency (%)
7778314689 1
0.3%
8633290718 1
0.3%
8810500070 1
0.3%
9656523848 1
0.3%
10209331033 1
0.3%
10801837220 1
0.3%
11203877275 1
0.3%
11304312818 1
0.3%
11639579822 1
0.3%
11666788204 1
0.3%
ValueCountFrequency (%)
116785198308618 1
0.3%
39541261361208 1
0.3%
38455359086373 1
0.3%
19273952285457 1
0.3%
17429964488140 1
0.3%
12572124055454 1
0.3%
11869735496496 1
0.3%
10698061151908 1
0.3%
10261084036995 1
0.3%
6888530729389 1
0.3%

자치단체금액(A)(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct292
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4844529 × 1011
Minimum7.7733878 × 109
Maximum5.8461312 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T06:57:58.904757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.7733878 × 109
5-th percentile1.1857219 × 1010
Q12.2929482 × 1010
median4.2975928 × 1010
Q31.203848 × 1011
95-th percentile2.5987252 × 1012
Maximum5.8461312 × 1013
Range5.8453539 × 1013
Interquartile range (IQR)9.7455315 × 1010

Descriptive statistics

Standard deviation3.7165685 × 1012
Coefficient of variation (CV)5.7315067
Kurtosis202.62038
Mean6.4844529 × 1011
Median Absolute Deviation (MAD)2.7103247 × 1010
Skewness13.394525
Sum1.9064292 × 1014
Variance1.3812882 × 1025
MonotonicityNot monotonic
2023-12-11T06:57:59.043548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1332956920853 2
 
0.7%
352030030545 2
 
0.7%
27742467913 1
 
0.3%
120590938515 1
 
0.3%
9800769948 1
 
0.3%
132331732354 1
 
0.3%
108756090029 1
 
0.3%
46039688821 1
 
0.3%
68528089782 1
 
0.3%
363195043908 1
 
0.3%
Other values (282) 282
95.9%
ValueCountFrequency (%)
7773387838 1
0.3%
8558946781 1
0.3%
8791606648 1
0.3%
9252055367 1
0.3%
9527939100 1
0.3%
9800769948 1
0.3%
10676900928 1
0.3%
10934620787 1
0.3%
11185284081 1
0.3%
11203877275 1
0.3%
ValueCountFrequency (%)
58461311971702 1
0.3%
15618251627888 1
0.3%
14562810729859 1
0.3%
7629489587382 1
0.3%
6465712137262 1
0.3%
4864990727457 1
0.3%
4560385074690 1
0.3%
4071694444539 1
0.3%
3782524163794 1
0.3%
3775397804884 1
0.3%

지방공공기관금액(B)(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct252
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4239414 × 1011
Minimum0
Maximum5.6376339 × 1013
Zeros41
Zeros (%)13.9%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T06:57:59.165320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.0208277 × 108
median1.5993591 × 109
Q34.2792805 × 1010
95-th percentile1.9141741 × 1012
Maximum5.6376339 × 1013
Range5.6376339 × 1013
Interquartile range (IQR)4.2590722 × 1010

Descriptive statistics

Standard deviation3.9971156 × 1012
Coefficient of variation (CV)6.2222168
Kurtosis138.04324
Mean6.4239414 × 1011
Median Absolute Deviation (MAD)1.5993591 × 109
Skewness10.933498
Sum1.8886388 × 1014
Variance1.5976933 × 1025
MonotonicityNot monotonic
2023-12-11T06:57:59.282039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41
 
13.9%
262624978866 2
 
0.7%
13484316521 2
 
0.7%
48053166028 1
 
0.3%
333810438092 1
 
0.3%
725754906 1
 
0.3%
220607134 1
 
0.3%
38000000 1
 
0.3%
1645728766 1
 
0.3%
408561085 1
 
0.3%
Other values (242) 242
82.3%
ValueCountFrequency (%)
0 41
13.9%
1000 1
 
0.3%
193600 1
 
0.3%
325002 1
 
0.3%
386141 1
 
0.3%
4926851 1
 
0.3%
5898191 1
 
0.3%
6227500 1
 
0.3%
18893422 1
 
0.3%
20858995 1
 
0.3%
ValueCountFrequency (%)
56376339454326 1
0.3%
24729710117337 1
0.3%
24697183264637 1
0.3%
9867428831693 1
0.3%
8613489458244 1
0.3%
6992476317981 1
0.3%
6987387820221 1
0.3%
6827646905474 1
0.3%
6073726587514 1
0.3%
2661282522977 1
0.3%

교육재정금액(C)(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.2378391 × 1010
Minimum0
Maximum6.610964 × 1012
Zeros257
Zeros (%)87.4%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T06:57:59.400902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.1084386 × 1011
Maximum6.610964 × 1012
Range6.610964 × 1012
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.9068025 × 1011
Coefficient of variation (CV)5.9564195
Kurtosis115.26663
Mean8.2378391 × 1010
Median Absolute Deviation (MAD)0
Skewness9.868119
Sum2.4219247 × 1013
Variance2.4076711 × 1023
MonotonicityNot monotonic
2023-12-11T06:57:59.512701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 257
87.4%
2193177381346 2
 
0.7%
531508684 2
 
0.7%
392738280840 2
 
0.7%
193070100229 2
 
0.7%
223399652234 2
 
0.7%
146150666672 2
 
0.7%
204083050815 2
 
0.7%
109571748040 2
 
0.7%
56336532233 2
 
0.7%
Other values (10) 19
 
6.5%
ValueCountFrequency (%)
0 257
87.4%
531508684 2
 
0.7%
56336532233 2
 
0.7%
109571748040 2
 
0.7%
116032559608 2
 
0.7%
119885575739 2
 
0.7%
146150666672 2
 
0.7%
168851306076 2
 
0.7%
183165105504 2
 
0.7%
193070100229 2
 
0.7%
ValueCountFrequency (%)
6610964025045 1
0.3%
2809454361751 2
0.7%
2193177381346 2
0.7%
1011421952472 2
0.7%
417314723805 2
0.7%
392738280840 2
0.7%
264898916972 2
0.7%
223399652234 2
0.7%
204083050815 2
0.7%
194057983371 2
0.7%

내외부거래금액(D)(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct49
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0416797 × 1010
Minimum0
Maximum4.6634171 × 1012
Zeros237
Zeros (%)80.6%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-11T06:57:59.632375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1.5573456 × 1011
Maximum4.6634171 × 1012
Range4.6634171 × 1012
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.2234543 × 1011
Coefficient of variation (CV)6.3936118
Kurtosis149.65121
Mean5.0416797 × 1010
Median Absolute Deviation (MAD)0
Skewness11.335396
Sum1.4822538 × 1013
Variance1.0390658 × 1023
MonotonicityNot monotonic
2023-12-11T06:57:59.809787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0 237
80.6%
831800504416 2
 
0.7%
220895650 2
 
0.7%
54628108670 2
 
0.7%
18402000000 2
 
0.7%
63425439065 2
 
0.7%
494254053672 2
 
0.7%
362395357571 2
 
0.7%
29269360268 2
 
0.7%
11808942030 2
 
0.7%
Other values (39) 39
 
13.3%
ValueCountFrequency (%)
0 237
80.6%
11847052 1
 
0.3%
24489450 1
 
0.3%
43235732 1
 
0.3%
44796306 1
 
0.3%
60000071 1
 
0.3%
154576950 1
 
0.3%
183871890 1
 
0.3%
220895650 2
 
0.7%
273230500 1
 
0.3%
ValueCountFrequency (%)
4663417142455 1
0.3%
1818122336489 1
0.3%
1816056860595 1
0.3%
831800504416 2
0.7%
494254053672 2
0.7%
458691469117 1
0.3%
416143514964 1
0.3%
362395357571 2
0.7%
230001782995 1
0.3%
224098036250 1
0.3%

Interactions

2023-12-11T06:57:56.297717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:54.471243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:54.904764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:55.404461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:55.841587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:56.385620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:54.565241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:54.994561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:55.497078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:55.944381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:56.679997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:54.652705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:55.086587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:55.592656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:56.023214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:56.750540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:54.736119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:55.170521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:55.681566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:56.101502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:56.827708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:54.826904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:55.271960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:55.760714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:57:56.189122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:57:59.895615image/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)
회계연도1.000NaN0.1640.0550.0530.1700.000
시군명NaN1.0001.0001.0001.0001.000NaN
합계금액(A+B+C-D)(원)0.1641.0001.0000.9960.9981.0000.981
자치단체금액(A)(원)0.0551.0000.9961.0000.9920.9060.981
지방공공기관금액(B)(원)0.0531.0000.9980.9921.0000.9260.987
교육재정금액(C)(원)0.1701.0001.0000.9060.9261.0000.840
내외부거래금액(D)(원)0.000NaN0.9810.9810.9870.8401.000
2023-12-11T06:58:00.009463image/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)1.0000.9530.7760.5720.4710.109
자치단체금액(A)(원)0.9531.0000.6540.5730.4720.037
지방공공기관금액(B)(원)0.7760.6541.0000.5540.5060.034
교육재정금액(C)(원)0.5720.5730.5541.0000.6620.206
내외부거래금액(D)(원)0.4710.4720.5060.6621.0000.000
회계연도0.1090.0370.0340.2060.0001.000

Missing values

2023-12-11T06:57:56.943469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:57:57.071291image/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)
02021가평군가평군2938819667927742467913164572876600
12021경기도본청12572124055454377539780488468276469054742193177381346224098036250
22021계경기계19273952285457762948958738298674288316932193177381346416143514964
32021고양시고양시21020137738010651990626310368147111700
42021과천시과천시1719565252982923134500114272518029700
52021광명시광명시3240530488029260408381314489649900
62021광주시광주시2112043980511776080601893359633786200
72021구리시구리시73195375472547941816401840119383200
82021군포시군포시3037419973725925596835444860290200
92021김포시김포시1970385678421869397398071009882803500
회계연도시군명자치단체명합계금액(A+B+C-D)(원)자치단체금액(A)(원)지방공공기관금액(B)(원)교육재정금액(C)(원)내외부거래금액(D)(원)
2842020<NA>광진구347235224073389645418182706822600
2852020<NA>동대문구404928291733954017932195264985200
2862020<NA>중랑구21781525293214946501276104766270323601461
2872020<NA>성북구3093887321028984301130195457208000
2882020<NA>강북구273377995352635471072098308881500
2892020<NA>도봉구2904106209827670860035137020206300
2902020<NA>노원구62670700966596569139833025634035011847052
2912020<NA>은평구433856655514291216205347350349800
2922020<NA>서대문구4435113345543099901547125123190800
2932020<NA>양천구6218726250060932345184125491731600