Overview

Dataset statistics

Number of variables8
Number of observations615
Missing cells0
Missing cells (%)0.0%
Duplicate rows12
Duplicate rows (%)2.0%
Total size in memory39.8 KiB
Average record size in memory66.2 B

Variable types

Categorical1
DateTime1
Text5
Numeric1

Dataset

Description부산광역시 상수도본부 성과단위사업예산월간집계정보(신청)입니다. 성과단위사업과 관련된 예산의 신청정보를 가진 데이터로 월간집계정보 제공(예산종류, 예산코드 등)
Author부산광역시
URLhttps://www.data.go.kr/data/15083551/fileData.do

Alerts

Dataset has 12 (2.0%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 10:00:11.742362
Analysis finished2023-12-12 10:00:12.565721
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

예산종류
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
1
339 
2
276 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 339
55.1%
2 276
44.9%

Length

2023-12-12T19:00:12.653848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:00:12.769755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 339
55.1%
2 276
44.9%

예산년월
Date

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum2020-03-01 00:00:00
Maximum2020-12-01 00:00:00
2023-12-12T19:00:12.881626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:00:13.010254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

예산코드
Text

Distinct105
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-12T19:00:13.270131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters3075
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)6.3%

Sample

1st row12111
2nd row12112
3rd row12112
4th row12211
5th row12211
ValueCountFrequency (%)
22142 103
16.7%
22152 89
 
14.5%
22176 35
 
5.7%
1257f 27
 
4.4%
12552 26
 
4.2%
12511 23
 
3.7%
12503 17
 
2.8%
22132 17
 
2.8%
12553 17
 
2.8%
12559 16
 
2.6%
Other values (95) 245
39.8%
2023-12-12T19:00:13.711570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1225
39.8%
1 804
26.1%
5 403
 
13.1%
4 187
 
6.1%
3 177
 
5.8%
7 78
 
2.5%
6 78
 
2.5%
9 39
 
1.3%
0 38
 
1.2%
F 29
 
0.9%
Other values (3) 17
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3035
98.7%
Uppercase Letter 40
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1225
40.4%
1 804
26.5%
5 403
 
13.3%
4 187
 
6.2%
3 177
 
5.8%
7 78
 
2.6%
6 78
 
2.6%
9 39
 
1.3%
0 38
 
1.3%
8 6
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
F 29
72.5%
B 7
 
17.5%
E 4
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3035
98.7%
Latin 40
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1225
40.4%
1 804
26.5%
5 403
 
13.3%
4 187
 
6.2%
3 177
 
5.8%
7 78
 
2.6%
6 78
 
2.6%
9 39
 
1.3%
0 38
 
1.3%
8 6
 
0.2%
Latin
ValueCountFrequency (%)
F 29
72.5%
B 7
 
17.5%
E 4
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3075
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1225
39.8%
1 804
26.1%
5 403
 
13.1%
4 187
 
6.1%
3 177
 
5.8%
7 78
 
2.5%
6 78
 
2.5%
9 39
 
1.3%
0 38
 
1.2%
F 29
 
0.9%
Other values (3) 17
 
0.6%

분류코드
Text

Distinct401
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-12T19:00:14.122654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.998374
Min length3

Characters and Unicode

Total characters2459
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique334 ?
Unique (%)54.3%

Sample

1st row5371
2nd row5381
3rd row5388
4th row5362
5th row5372
ValueCountFrequency (%)
0832 16
 
2.6%
0285 15
 
2.4%
5375 13
 
2.1%
5386 11
 
1.8%
0870 11
 
1.8%
0540 11
 
1.8%
0290 11
 
1.8%
0026 10
 
1.6%
0604 10
 
1.6%
b704 8
 
1.3%
Other values (391) 499
81.1%
2023-12-12T19:00:14.685436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 557
22.7%
1 220
 
8.9%
2 216
 
8.8%
3 213
 
8.7%
8 201
 
8.2%
5 201
 
8.2%
9 176
 
7.2%
4 158
 
6.4%
B 151
 
6.1%
6 150
 
6.1%
Other values (4) 216
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2226
90.5%
Uppercase Letter 231
 
9.4%
Space Separator 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 557
25.0%
1 220
 
9.9%
2 216
 
9.7%
3 213
 
9.6%
8 201
 
9.0%
5 201
 
9.0%
9 176
 
7.9%
4 158
 
7.1%
6 150
 
6.7%
7 134
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
B 151
65.4%
A 41
 
17.7%
C 39
 
16.9%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2228
90.6%
Latin 231
 
9.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 557
25.0%
1 220
 
9.9%
2 216
 
9.7%
3 213
 
9.6%
8 201
 
9.0%
5 201
 
9.0%
9 176
 
7.9%
4 158
 
7.1%
6 150
 
6.7%
7 134
 
6.0%
Latin
ValueCountFrequency (%)
B 151
65.4%
A 41
 
17.7%
C 39
 
16.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2459
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 557
22.7%
1 220
 
8.9%
2 216
 
8.8%
3 213
 
8.7%
8 201
 
8.2%
5 201
 
8.2%
9 176
 
7.2%
4 158
 
6.4%
B 151
 
6.1%
6 150
 
6.1%
Other values (4) 216
 
8.8%

성과예산코드
Real number (ℝ)

Distinct53
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean284342.92
Minimum111001
Maximum612001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-12-12T19:00:14.850316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum111001
5-th percentile212006
Q1221001
median231101
Q3411001
95-th percentile412001
Maximum612001
Range501000
Interquartile range (IQR)190000

Descriptive statistics

Standard deviation97620.9
Coefficient of variation (CV)0.34332101
Kurtosis-0.5297438
Mean284342.92
Median Absolute Deviation (MAD)19094
Skewness0.79125853
Sum1.748709 × 108
Variance9.52984 × 109
MonotonicityNot monotonic
2023-12-12T19:00:15.025432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
411001 113
18.4%
412001 81
13.2%
221001 66
10.7%
212007 61
 
9.9%
232106 40
 
6.5%
231101 31
 
5.0%
212006 24
 
3.9%
221002 14
 
2.3%
111001 13
 
2.1%
212012 11
 
1.8%
Other values (43) 161
26.2%
ValueCountFrequency (%)
111001 13
 
2.1%
211002 5
 
0.8%
211003 4
 
0.7%
211101 1
 
0.2%
212006 24
 
3.9%
212007 61
9.9%
212008 1
 
0.2%
212012 11
 
1.8%
212017 4
 
0.7%
212019 1
 
0.2%
ValueCountFrequency (%)
612001 5
 
0.8%
511001 4
 
0.7%
412001 81
13.2%
411001 113
18.4%
242106 1
 
0.2%
241101 3
 
0.5%
241001 1
 
0.2%
232108 6
 
1.0%
232107 4
 
0.7%
232106 40
 
6.5%

성과예산명
Text

Distinct53
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-12T19:00:15.298062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length9.6260163
Min length3

Characters and Unicode

Total characters5920
Distinct characters133
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)2.4%

Sample

1st row인력운영비
2nd row인력운영비
3rd row인력운영비
4th row인력운영비
5th row인력운영비
ValueCountFrequency (%)
및 114
 
8.9%
인력운영비 113
 
8.8%
정비 105
 
8.2%
기본경비 81
 
6.3%
상수도관 72
 
5.6%
개량ㆍ정비 66
 
5.2%
취·정수시설(기전 61
 
4.8%
운영 45
 
3.5%
상수도사업 40
 
3.1%
운영관리 40
 
3.1%
Other values (92) 541
42.3%
2023-12-12T19:00:15.710325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
762
 
12.9%
비 405
 
6.8%
수 368
 
6.2%
정 319
 
5.4%
운 198
 
3.3%
영 198
 
3.3%
설 176
 
3.0%
기 159
 
2.7%
도 155
 
2.6%
상 151
 
2.6%
Other values (123) 3029
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4820
81.4%
Space Separator 762
 
12.9%
Other Punctuation 136
 
2.3%
Open Punctuation 100
 
1.7%
Close Punctuation 100
 
1.7%
Math Symbol 1
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 405
 
8.4%
수 368
 
7.6%
정 319
 
6.6%
운 198
 
4.1%
영 198
 
4.1%
설 176
 
3.7%
기 159
 
3.3%
도 155
 
3.2%
상 151
 
3.1%
시 142
 
2.9%
Other values (116) 2549
52.9%
Other Punctuation
ValueCountFrequency (%)
· 103
75.7%
, 33
 
24.3%
Space Separator
ValueCountFrequency (%)
762
100.0%
Open Punctuation
ValueCountFrequency (%)
( 100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 100
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4820
81.4%
Common 1100
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 405
 
8.4%
수 368
 
7.6%
정 319
 
6.6%
운 198
 
4.1%
영 198
 
4.1%
설 176
 
3.7%
기 159
 
3.3%
도 155
 
3.2%
상 151
 
3.1%
시 142
 
2.9%
Other values (116) 2549
52.9%
Common
ValueCountFrequency (%)
762
69.3%
· 103
 
9.4%
( 100
 
9.1%
) 100
 
9.1%
, 33
 
3.0%
~ 1
 
0.1%
3 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4739
80.1%
ASCII 997
 
16.8%
None 103
 
1.7%
Compat Jamo 81
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
762
76.4%
( 100
 
10.0%
) 100
 
10.0%
, 33
 
3.3%
~ 1
 
0.1%
3 1
 
0.1%
Hangul
ValueCountFrequency (%)
비 405
 
8.5%
수 368
 
7.8%
정 319
 
6.7%
운 198
 
4.2%
영 198
 
4.2%
설 176
 
3.7%
기 159
 
3.4%
도 155
 
3.3%
상 151
 
3.2%
시 142
 
3.0%
Other values (115) 2468
52.1%
None
ValueCountFrequency (%)
· 103
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 81
100.0%

예산과목명
Text

Distinct52
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-12T19:00:15.928394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.8894309
Min length2

Characters and Unicode

Total characters3007
Distinct characters110
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)2.0%

Sample

1st row무기계약근로자보수
2nd row기간제근로자등보수
3rd row기간제근로자등보수
4th row무기계약근로자보수
5th row무기계약근로자보수
ValueCountFrequency (%)
시설비 212
34.4%
자산취득비 39
 
6.3%
무기계약근로자보수 33
 
5.3%
보수 32
 
5.2%
사회보험부담금 30
 
4.9%
민간위탁금 29
 
4.7%
기타복리후생비 25
 
4.1%
수선유지비 25
 
4.1%
사무관리비 17
 
2.8%
기간제근로자등보수 15
 
2.4%
Other values (42) 160
25.9%
2023-12-12T19:00:16.289669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 440
 
14.6%
설 222
 
7.4%
시 217
 
7.2%
수 144
 
4.8%
보 138
 
4.6%
기 100
 
3.3%
자 91
 
3.0%
금 85
 
2.8%
사 72
 
2.4%
무 71
 
2.4%
Other values (100) 1427
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3005
99.9%
Space Separator 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 440
 
14.6%
설 222
 
7.4%
시 217
 
7.2%
수 144
 
4.8%
보 138
 
4.6%
기 100
 
3.3%
자 91
 
3.0%
금 85
 
2.8%
사 72
 
2.4%
무 71
 
2.4%
Other values (99) 1425
47.4%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3005
99.9%
Common 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 440
 
14.6%
설 222
 
7.4%
시 217
 
7.2%
수 144
 
4.8%
보 138
 
4.6%
기 100
 
3.3%
자 91
 
3.0%
금 85
 
2.8%
사 72
 
2.4%
무 71
 
2.4%
Other values (99) 1425
47.4%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3005
99.9%
ASCII 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 440
 
14.6%
설 222
 
7.4%
시 217
 
7.2%
수 144
 
4.8%
보 138
 
4.6%
기 100
 
3.3%
자 91
 
3.0%
금 85
 
2.8%
사 72
 
2.4%
무 71
 
2.4%
Other values (99) 1425
47.4%
ASCII
ValueCountFrequency (%)
2
100.0%

추경예산
Text

Distinct493
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-12T19:00:16.572805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10.380488
Min length5

Characters and Unicode

Total characters6384
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique424 ?
Unique (%)68.9%

Sample

1st row36,439,000
2nd row53,027,000
3rd row600,780,000
4th row22,024,000
5th row72,877,000
ValueCountFrequency (%)
20,000,000 10
 
1.6%
50,000,000 8
 
1.3%
200,000,000 7
 
1.1%
100,000,000 6
 
1.0%
90,000,000 6
 
1.0%
80,000,000 6
 
1.0%
10,000,000 5
 
0.8%
150,000,000 5
 
0.8%
5,000,000 5
 
0.8%
15,000,000 5
 
0.8%
Other values (460) 552
89.8%
2023-12-12T19:00:16.980085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2864
44.9%
, 1219
19.1%
1 343
 
5.4%
- 314
 
4.9%
2 279
 
4.4%
5 253
 
4.0%
3 223
 
3.5%
4 211
 
3.3%
6 198
 
3.1%
8 173
 
2.7%
Other values (2) 307
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4851
76.0%
Other Punctuation 1219
 
19.1%
Dash Punctuation 314
 
4.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2864
59.0%
1 343
 
7.1%
2 279
 
5.8%
5 253
 
5.2%
3 223
 
4.6%
4 211
 
4.3%
6 198
 
4.1%
8 173
 
3.6%
9 164
 
3.4%
7 143
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 1219
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 314
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6384
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2864
44.9%
, 1219
19.1%
1 343
 
5.4%
- 314
 
4.9%
2 279
 
4.4%
5 253
 
4.0%
3 223
 
3.5%
4 211
 
3.3%
6 198
 
3.1%
8 173
 
2.7%
Other values (2) 307
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2864
44.9%
, 1219
19.1%
1 343
 
5.4%
- 314
 
4.9%
2 279
 
4.4%
5 253
 
4.0%
3 223
 
3.5%
4 211
 
3.3%
6 198
 
3.1%
8 173
 
2.7%
Other values (2) 307
 
4.8%

Interactions

2023-12-12T19:00:12.244948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:00:17.097461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산종류예산년월성과예산코드성과예산명예산과목명
예산종류1.0000.3500.6910.9181.000
예산년월0.3501.0000.3440.6900.813
성과예산코드0.6910.3441.0001.0000.953
성과예산명0.9180.6901.0001.0000.961
예산과목명1.0000.8130.9530.9611.000
2023-12-12T19:00:17.206252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성과예산코드예산종류
성과예산코드1.0000.500
예산종류0.5001.000

Missing values

2023-12-12T19:00:12.374719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:00:12.512300image/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

예산종류예산년월예산코드분류코드성과예산코드성과예산명예산과목명추경예산
012020-03121115371411001인력운영비무기계약근로자보수36,439,000
112020-03121125381411001인력운영비기간제근로자등보수53,027,000
212020-03121125388411001인력운영비기간제근로자등보수600,780,000
312020-03122115362411001인력운영비무기계약근로자보수22,024,000
412020-03122115372411001인력운영비무기계약근로자보수72,877,000
512020-03122125387411001인력운영비기간제근로자등보수247,382,000
612020-03122520282411001인력운영비사회보험부담금10,372,000
712020-03122520287411001인력운영비사회보험부담금102,335,000
812020-031227F0833231101상수도업무 민간위탁 추진민간위탁금-850,743,000
912020-03124230604412001기본경비사무관리비128,000,000
예산종류예산년월예산코드분류코드성과예산코드성과예산명예산과목명추경예산
60522020-12221769257412001기본경비자산취득비-9,944,000
60622020-12221769260211002수질시험장비 구입자산취득비-15,718,000
60722020-12221769261211002수질시험장비 구입자산취득비-3,699,000
60822020-12221769271232002정보화 인프라 확충ㆍ개선자산취득비-9,921,000
60922020-12223319250232002정보화 인프라 확충ㆍ개선정보화시스템취득비-23,050,000
61022020-12223319252232002정보화 인프라 확충ㆍ개선정보화시스템취득비-19,291,000
61122020-1222612B075221002가압장 신설 및 시설개선국고보조금반환금4,788,000
61222020-1222612B322212012취·정수시설 운영 및 수선국고보조금반환금39,511,000
61322020-1222612B442212012취·정수시설 운영 및 수선국고보조금반환금34,204,000
61422020-12227110999511001예비비예비비-1,800,000,000

Duplicate rows

Most frequently occurring

예산종류예산년월예산코드분류코드성과예산코드성과예산명예산과목명추경예산# duplicates
812020-07125410540412001기본경비부서운영업무추진비450,0005
1122020-03221769277412001기본경비자산취득비18,000,0003
012020-03125115365411001인력운영비무기계약근로자보수22,024,0002
112020-03125115375411001인력운영비무기계약근로자보수111,563,0002
212020-03125125386411001인력운영비기간제근로자등보수106,162,0002
312020-03125125386411001인력운영비기간제근로자등보수21,234,0002
412020-03125125386411001인력운영비기간제근로자등보수63,698,0002
512020-03125520290411001인력운영비사회보험부담금11,602,0002
612020-03125520290411001인력운영비사회보험부담금2,322,0002
712020-03125530865232106상수도사업 운영관리기타복리후생비770,0002