Overview

Dataset statistics

Number of variables13
Number of observations1727
Missing cells0
Missing cells (%)0.0%
Duplicate rows55
Duplicate rows (%)3.2%
Total size in memory178.9 KiB
Average record size in memory106.1 B

Variable types

Categorical4
Text9

Dataset

Description부산광역시_상수도본부_승인연간집계정보입니다. 승인된 예산에 대한 년간 집계정보 제공. 예산코드, 분류코드, 본예산, 배정예산, 추경예산, 전용예산 정보 제공
Author부산광역시
URLhttps://www.data.go.kr/data/15083545/fileData.do

Alerts

예산년도 has constant value ""Constant
Dataset has 55 (3.2%) duplicate rowsDuplicates
불용액(합계) is highly overall correlated with 계획변경,취소High correlation
계획변경,취소 is highly overall correlated with 불용액(합계)High correlation

Reproduction

Analysis started2023-12-12 15:41:43.985771
Analysis finished2023-12-12 15:41:44.998888
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

예산종류
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
1
1233 
2
493 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 1233
71.4%
2 493
 
28.5%
3 1
 
0.1%

Length

2023-12-13T00:41:45.070720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:41:45.205555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1233
71.4%
2 493
 
28.5%
3 1
 
0.1%

예산년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2020
1727 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 1727
100.0%

Length

2023-12-13T00:41:45.332272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:41:45.441924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 1727
100.0%

예산코드
Text

Distinct178
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-13T00:41:45.704035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters8635
Distinct characters17
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

Unique44 ?
Unique (%)2.5%

Sample

1st row11111
2nd row11111
3rd row11111
4th row11111
5th row11111
ValueCountFrequency (%)
22142 171
 
9.9%
11176 120
 
6.9%
22152 109
 
6.3%
22176 91
 
5.3%
12559 83
 
4.8%
12259 50
 
2.9%
12511 37
 
2.1%
11630 34
 
2.0%
12503 26
 
1.5%
12359 23
 
1.3%
Other values (168) 983
56.9%
2023-12-13T00:41:46.110817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2814
32.6%
2 2619
30.3%
5 965
 
11.2%
3 521
 
6.0%
4 494
 
5.7%
6 416
 
4.8%
7 314
 
3.6%
0 203
 
2.4%
9 203
 
2.4%
8 45
 
0.5%
Other values (7) 41
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8594
99.5%
Uppercase Letter 41
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2814
32.7%
2 2619
30.5%
5 965
 
11.2%
3 521
 
6.1%
4 494
 
5.7%
6 416
 
4.8%
7 314
 
3.7%
0 203
 
2.4%
9 203
 
2.4%
8 45
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
F 16
39.0%
B 13
31.7%
E 8
19.5%
A 1
 
2.4%
G 1
 
2.4%
H 1
 
2.4%
I 1
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 8594
99.5%
Latin 41
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2814
32.7%
2 2619
30.5%
5 965
 
11.2%
3 521
 
6.1%
4 494
 
5.7%
6 416
 
4.8%
7 314
 
3.7%
0 203
 
2.4%
9 203
 
2.4%
8 45
 
0.5%
Latin
ValueCountFrequency (%)
F 16
39.0%
B 13
31.7%
E 8
19.5%
A 1
 
2.4%
G 1
 
2.4%
H 1
 
2.4%
I 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8635
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2814
32.6%
2 2619
30.3%
5 965
 
11.2%
3 521
 
6.0%
4 494
 
5.7%
6 416
 
4.8%
7 314
 
3.6%
0 203
 
2.4%
9 203
 
2.4%
8 45
 
0.5%
Other values (7) 41
 
0.5%

분류코드
Text

Distinct841
Distinct (%)48.7%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-13T00:41:46.470047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.9988419
Min length3

Characters and Unicode

Total characters6906
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique663 ?
Unique (%)38.4%

Sample

1st row6001
2nd row6001
3rd row6001
4th row6001
5th row6001
ValueCountFrequency (%)
6461 17
 
1.0%
6315 16
 
0.9%
6902 13
 
0.8%
0943 12
 
0.7%
6173 12
 
0.7%
6131 12
 
0.7%
6423 12
 
0.7%
0015 12
 
0.7%
6005 12
 
0.7%
6201 12
 
0.7%
Other values (827) 1597
92.5%
2023-12-13T00:41:46.963892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1539
22.3%
1 854
12.4%
6 755
10.9%
2 644
9.3%
3 574
 
8.3%
8 539
 
7.8%
5 479
 
6.9%
4 450
 
6.5%
9 411
 
6.0%
7 298
 
4.3%
Other values (5) 363
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6543
94.7%
Uppercase Letter 299
 
4.3%
Lowercase Letter 63
 
0.9%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1539
23.5%
1 854
13.1%
6 755
11.5%
2 644
9.8%
3 574
 
8.8%
8 539
 
8.2%
5 479
 
7.3%
4 450
 
6.9%
9 411
 
6.3%
7 298
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 188
62.9%
A 59
 
19.7%
C 52
 
17.4%
Lowercase Letter
ValueCountFrequency (%)
c 63
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6544
94.8%
Latin 362
 
5.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1539
23.5%
1 854
13.1%
6 755
11.5%
2 644
9.8%
3 574
 
8.8%
8 539
 
8.2%
5 479
 
7.3%
4 450
 
6.9%
9 411
 
6.3%
7 298
 
4.6%
Latin
ValueCountFrequency (%)
B 188
51.9%
c 63
 
17.4%
A 59
 
16.3%
C 52
 
14.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6906
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1539
22.3%
1 854
12.4%
6 755
10.9%
2 644
9.3%
3 574
 
8.3%
8 539
 
7.8%
5 479
 
6.9%
4 450
 
6.5%
9 411
 
6.0%
7 298
 
4.3%
Other values (5) 363
 
5.3%

예산과목명
Text

Distinct112
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-13T00:41:47.175812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length5.7365373
Min length1

Characters and Unicode

Total characters9907
Distinct characters136
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)1.7%

Sample

1st row가정용
2nd row가정용
3rd row가정용
4th row가정용
5th row가정용
ValueCountFrequency (%)
시설비 315
18.1%
수선유지비 156
 
9.0%
기타수수료수익 120
 
6.9%
자산취득비 102
 
5.9%
보수 61
 
3.5%
일반재료비 48
 
2.8%
공공운영비 43
 
2.5%
기타복리후생비 40
 
2.3%
무기계약근로자보수 39
 
2.2%
감리비 38
 
2.2%
Other values (104) 776
44.6%
2023-12-13T00:41:47.583599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 1199
 
12.1%
수 1046
 
10.6%
기 396
 
4.0%
설 346
 
3.5%
시 338
 
3.4%
익 272
 
2.7%
타 264
 
2.7%
보 236
 
2.4%
금 222
 
2.2%
자 204
 
2.1%
Other values (126) 5384
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9777
98.7%
Dash Punctuation 114
 
1.2%
Space Separator 11
 
0.1%
Other Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 1199
 
12.3%
수 1046
 
10.7%
기 396
 
4.1%
설 346
 
3.5%
시 338
 
3.5%
익 272
 
2.8%
타 264
 
2.7%
보 236
 
2.4%
금 222
 
2.3%
자 204
 
2.1%
Other values (123) 5254
53.7%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
· 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9777
98.7%
Common 130
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 1199
 
12.3%
수 1046
 
10.7%
기 396
 
4.1%
설 346
 
3.5%
시 338
 
3.5%
익 272
 
2.8%
타 264
 
2.7%
보 236
 
2.4%
금 222
 
2.3%
자 204
 
2.1%
Other values (123) 5254
53.7%
Common
ValueCountFrequency (%)
- 114
87.7%
11
 
8.5%
· 5
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9777
98.7%
ASCII 125
 
1.3%
None 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 1199
 
12.3%
수 1046
 
10.7%
기 396
 
4.1%
설 346
 
3.5%
시 338
 
3.5%
익 272
 
2.8%
타 264
 
2.7%
보 236
 
2.4%
금 222
 
2.3%
자 204
 
2.1%
Other values (123) 5254
53.7%
ASCII
ValueCountFrequency (%)
- 114
91.2%
11
 
8.8%
None
ValueCountFrequency (%)
· 5
100.0%

분류코드명
Text

Distinct741
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-13T00:41:47.883687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length11.997684
Min length1

Characters and Unicode

Total characters20720
Distinct characters430
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique600 ?
Unique (%)34.7%

Sample

1st row가정용 사용료
2nd row가정용 사용료
3rd row가정용 사용료
4th row가정용 사용료
5th row가정용 사용료
ValueCountFrequency (%)
및 120
 
3.0%
교체 92
 
2.3%
주변 78
 
2.0%
구입 54
 
1.4%
구입(대체 44
 
1.1%
사용료 43
 
1.1%
구경별기본요금 42
 
1.1%
유지관리 40
 
1.0%
상수도관 37
 
0.9%
등 34
 
0.9%
Other values (1157) 3359
85.2%
2023-12-13T00:41:48.413304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2223
 
10.7%
수 858
 
4.1%
비 623
 
3.0%
사 577
 
2.8%
공 487
 
2.4%
( 402
 
1.9%
) 402
 
1.9%
기 395
 
1.9%
설 375
 
1.8%
관 353
 
1.7%
Other values (420) 14025
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16980
81.9%
Space Separator 2223
 
10.7%
Open Punctuation 402
 
1.9%
Close Punctuation 402
 
1.9%
Decimal Number 372
 
1.8%
Lowercase Letter 181
 
0.9%
Other Punctuation 71
 
0.3%
Uppercase Letter 57
 
0.3%
Math Symbol 19
 
0.1%
Dash Punctuation 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 858
 
5.1%
비 623
 
3.7%
사 577
 
3.4%
공 487
 
2.9%
기 395
 
2.3%
설 375
 
2.2%
관 353
 
2.1%
정 332
 
2.0%
용 316
 
1.9%
장 284
 
1.7%
Other values (380) 12380
72.9%
Uppercase Letter
ValueCountFrequency (%)
C 10
17.5%
S 7
12.3%
T 6
10.5%
A 4
 
7.0%
I 4
 
7.0%
V 4
 
7.0%
E 4
 
7.0%
L 3
 
5.3%
P 3
 
5.3%
D 2
 
3.5%
Other values (8) 10
17.5%
Decimal Number
ValueCountFrequency (%)
2 152
40.9%
3 69
18.5%
1 58
 
15.6%
5 58
 
15.6%
4 11
 
3.0%
0 10
 
2.7%
7 7
 
1.9%
8 4
 
1.1%
6 2
 
0.5%
9 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 38
53.5%
· 32
45.1%
. 1
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
m 180
99.4%
e 1
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 17
89.5%
∼ 2
 
10.5%
Space Separator
ValueCountFrequency (%)
2223
100.0%
Open Punctuation
ValueCountFrequency (%)
( 402
100.0%
Close Punctuation
ValueCountFrequency (%)
) 402
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16980
81.9%
Common 3502
 
16.9%
Latin 238
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 858
 
5.1%
비 623
 
3.7%
사 577
 
3.4%
공 487
 
2.9%
기 395
 
2.3%
설 375
 
2.2%
관 353
 
2.1%
정 332
 
2.0%
용 316
 
1.9%
장 284
 
1.7%
Other values (380) 12380
72.9%
Common
ValueCountFrequency (%)
2223
63.5%
( 402
 
11.5%
) 402
 
11.5%
2 152
 
4.3%
3 69
 
2.0%
1 58
 
1.7%
5 58
 
1.7%
, 38
 
1.1%
· 32
 
0.9%
~ 17
 
0.5%
Other values (10) 51
 
1.5%
Latin
ValueCountFrequency (%)
m 180
75.6%
C 10
 
4.2%
S 7
 
2.9%
T 6
 
2.5%
A 4
 
1.7%
I 4
 
1.7%
V 4
 
1.7%
E 4
 
1.7%
L 3
 
1.3%
P 3
 
1.3%
Other values (10) 13
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16980
81.9%
ASCII 3706
 
17.9%
None 32
 
0.2%
Math Operators 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2223
60.0%
( 402
 
10.8%
) 402
 
10.8%
m 180
 
4.9%
2 152
 
4.1%
3 69
 
1.9%
1 58
 
1.6%
5 58
 
1.6%
, 38
 
1.0%
~ 17
 
0.5%
Other values (28) 107
 
2.9%
Hangul
ValueCountFrequency (%)
수 858
 
5.1%
비 623
 
3.7%
사 577
 
3.4%
공 487
 
2.9%
기 395
 
2.3%
설 375
 
2.2%
관 353
 
2.1%
정 332
 
2.0%
용 316
 
1.9%
장 284
 
1.7%
Other values (380) 12380
72.9%
None
ValueCountFrequency (%)
· 32
100.0%
Math Operators
ValueCountFrequency (%)
∼ 2
100.0%

이월예산
Text

Distinct64
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-13T00:41:48.699992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length2
Mean length2.0793283
Min length1

Characters and Unicode

Total characters3591
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

Unique62 ?
Unique (%)3.6%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
0 1311
75.9%
354
 
20.5%
220308000 1
 
0.1%
23535590 1
 
0.1%
47695000 1
 
0.1%
290206610 1
 
0.1%
301006090 1
 
0.1%
256744000 1
 
0.1%
310744000 1
 
0.1%
934000000 1
 
0.1%
Other values (54) 54
 
3.1%
2023-12-13T00:41:49.463166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1525
42.5%
1373
38.2%
- 354
 
9.9%
2 51
 
1.4%
1 44
 
1.2%
4 43
 
1.2%
3 39
 
1.1%
6 36
 
1.0%
7 35
 
1.0%
9 33
 
0.9%
Other values (2) 58
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1864
51.9%
Space Separator 1373
38.2%
Dash Punctuation 354
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1525
81.8%
2 51
 
2.7%
1 44
 
2.4%
4 43
 
2.3%
3 39
 
2.1%
6 36
 
1.9%
7 35
 
1.9%
9 33
 
1.8%
5 31
 
1.7%
8 27
 
1.4%
Space Separator
ValueCountFrequency (%)
1373
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 354
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3591
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1525
42.5%
1373
38.2%
- 354
 
9.9%
2 51
 
1.4%
1 44
 
1.2%
4 43
 
1.2%
3 39
 
1.1%
6 36
 
1.0%
7 35
 
1.0%
9 33
 
0.9%
Other values (2) 58
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3591
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1525
42.5%
1373
38.2%
- 354
 
9.9%
2 51
 
1.4%
1 44
 
1.2%
4 43
 
1.2%
3 39
 
1.1%
6 36
 
1.0%
7 35
 
1.0%
9 33
 
0.9%
Other values (2) 58
 
1.6%

본예산
Text

Distinct927
Distinct (%)53.7%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-13T00:41:49.781492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.074117
Min length1

Characters and Unicode

Total characters13944
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

Unique754 ?
Unique (%)43.7%

Sample

1st row5126504000
2nd row29092556000
3rd row4688703000
4th row4067309000
5th row4533355000
ValueCountFrequency (%)
187
 
10.8%
0 38
 
2.2%
3000000 23
 
1.3%
1000000 22
 
1.3%
5000000 19
 
1.1%
3135000 18
 
1.0%
150000000 16
 
0.9%
20000000 15
 
0.9%
28860000 14
 
0.8%
300000000 13
 
0.8%
Other values (917) 1362
78.9%
2023-12-13T00:41:50.182353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7612
54.6%
1540
 
11.0%
1 808
 
5.8%
2 631
 
4.5%
5 560
 
4.0%
3 507
 
3.6%
4 504
 
3.6%
6 467
 
3.3%
8 456
 
3.3%
7 366
 
2.6%
Other values (2) 493
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12217
87.6%
Space Separator 1540
 
11.0%
Dash Punctuation 187
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7612
62.3%
1 808
 
6.6%
2 631
 
5.2%
5 560
 
4.6%
3 507
 
4.1%
4 504
 
4.1%
6 467
 
3.8%
8 456
 
3.7%
7 366
 
3.0%
9 306
 
2.5%
Space Separator
ValueCountFrequency (%)
1540
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 187
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13944
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7612
54.6%
1540
 
11.0%
1 808
 
5.8%
2 631
 
4.5%
5 560
 
4.0%
3 507
 
3.6%
4 504
 
3.6%
6 467
 
3.3%
8 456
 
3.3%
7 366
 
2.6%
Other values (2) 493
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13944
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7612
54.6%
1540
 
11.0%
1 808
 
5.8%
2 631
 
4.5%
5 560
 
4.0%
3 507
 
3.6%
4 504
 
3.6%
6 467
 
3.3%
8 456
 
3.3%
7 366
 
2.6%
Other values (2) 493
 
3.5%

배정예산
Text

Distinct937
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-13T00:41:50.488577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.0567458
Min length1

Characters and Unicode

Total characters12187
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

Unique832 ?
Unique (%)48.2%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
354
 
20.5%
0 116
 
6.7%
3135000 18
 
1.0%
5000000 15
 
0.9%
3000000 14
 
0.8%
20000000 11
 
0.6%
1800000 10
 
0.6%
28920000 10
 
0.6%
50000000 10
 
0.6%
10000000 10
 
0.6%
Other values (927) 1159
67.1%
2023-12-13T00:41:50.945817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6112
50.2%
1373
 
11.3%
1 746
 
6.1%
2 588
 
4.8%
5 517
 
4.2%
3 509
 
4.2%
4 467
 
3.8%
6 429
 
3.5%
8 411
 
3.4%
- 354
 
2.9%
Other values (2) 681
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10460
85.8%
Space Separator 1373
 
11.3%
Dash Punctuation 354
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6112
58.4%
1 746
 
7.1%
2 588
 
5.6%
5 517
 
4.9%
3 509
 
4.9%
4 467
 
4.5%
6 429
 
4.1%
8 411
 
3.9%
7 349
 
3.3%
9 332
 
3.2%
Space Separator
ValueCountFrequency (%)
1373
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 354
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12187
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6112
50.2%
1373
 
11.3%
1 746
 
6.1%
2 588
 
4.8%
5 517
 
4.2%
3 509
 
4.2%
4 467
 
3.8%
6 429
 
3.5%
8 411
 
3.4%
- 354
 
2.9%
Other values (2) 681
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12187
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6112
50.2%
1373
 
11.3%
1 746
 
6.1%
2 588
 
4.8%
5 517
 
4.2%
3 509
 
4.2%
4 467
 
3.8%
6 429
 
3.5%
8 411
 
3.4%
- 354
 
2.9%
Other values (2) 681
 
5.6%

추경예산
Text

Distinct419
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-13T00:41:51.200932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length4.0718008
Min length1

Characters and Unicode

Total characters7032
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

Unique360 ?
Unique (%)20.8%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
0 846
49.0%
354
20.5%
20000000 11
 
0.6%
90000000 9
 
0.5%
50000000 8
 
0.5%
300000000 7
 
0.4%
80000000 7
 
0.4%
100000000 6
 
0.3%
150000000 6
 
0.3%
40000000 6
 
0.3%
Other values (385) 467
27.0%
2023-12-13T00:41:51.649331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3404
48.4%
1373
19.5%
- 652
 
9.3%
1 290
 
4.1%
5 219
 
3.1%
2 200
 
2.8%
4 180
 
2.6%
3 177
 
2.5%
8 149
 
2.1%
9 143
 
2.0%
Other values (2) 245
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5007
71.2%
Space Separator 1373
 
19.5%
Dash Punctuation 652
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3404
68.0%
1 290
 
5.8%
5 219
 
4.4%
2 200
 
4.0%
4 180
 
3.6%
3 177
 
3.5%
8 149
 
3.0%
9 143
 
2.9%
6 128
 
2.6%
7 117
 
2.3%
Space Separator
ValueCountFrequency (%)
1373
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7032
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3404
48.4%
1373
19.5%
- 652
 
9.3%
1 290
 
4.1%
5 219
 
3.1%
2 200
 
2.8%
4 180
 
2.6%
3 177
 
2.5%
8 149
 
2.1%
9 143
 
2.0%
Other values (2) 245
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7032
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3404
48.4%
1373
19.5%
- 652
 
9.3%
1 290
 
4.1%
5 219
 
3.1%
2 200
 
2.8%
4 180
 
2.6%
3 177
 
2.5%
8 149
 
2.1%
9 143
 
2.0%
Other values (2) 245
 
3.5%

전용예산
Text

Distinct256
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-13T00:41:51.956933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length2
Mean length3.0700637
Min length1

Characters and Unicode

Total characters5302
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

Unique220 ?
Unique (%)12.7%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
0 1059
61.3%
354
 
20.5%
60000 12
 
0.7%
100000000 7
 
0.4%
50000000 7
 
0.4%
3000000 6
 
0.3%
20000000 6
 
0.3%
2000000 5
 
0.3%
100000 5
 
0.3%
1000000 4
 
0.2%
Other values (211) 262
 
15.2%
2023-12-13T00:41:52.439814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2502
47.2%
1373
25.9%
- 487
 
9.2%
1 167
 
3.1%
2 139
 
2.6%
3 111
 
2.1%
6 105
 
2.0%
5 97
 
1.8%
8 88
 
1.7%
4 87
 
1.6%
Other values (2) 146
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3442
64.9%
Space Separator 1373
 
25.9%
Dash Punctuation 487
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2502
72.7%
1 167
 
4.9%
2 139
 
4.0%
3 111
 
3.2%
6 105
 
3.1%
5 97
 
2.8%
8 88
 
2.6%
4 87
 
2.5%
7 81
 
2.4%
9 65
 
1.9%
Space Separator
ValueCountFrequency (%)
1373
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 487
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5302
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2502
47.2%
1373
25.9%
- 487
 
9.2%
1 167
 
3.1%
2 139
 
2.6%
3 111
 
2.1%
6 105
 
2.0%
5 97
 
1.8%
8 88
 
1.7%
4 87
 
1.6%
Other values (2) 146
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2502
47.2%
1373
25.9%
- 487
 
9.2%
1 167
 
3.1%
2 139
 
2.6%
3 111
 
2.1%
6 105
 
2.0%
5 97
 
1.8%
8 88
 
1.7%
4 87
 
1.6%
Other values (2) 146
 
2.8%

불용액(합계)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
0
1173 
-
554 

Length

Max length2
Median length2
Mean length1.6792125
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
0 1173
67.9%
- 554
32.1%

Length

2023-12-13T00:41:52.638779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:41:52.756485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1173
67.9%
554
32.1%

계획변경,취소
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
0
1173 
-
554 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
0 1173
67.9%
- 554
32.1%

Length

2023-12-13T00:41:52.893931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:41:53.033060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1173
67.9%
554
32.1%

Correlations

2023-12-13T00:41:53.116288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산종류이월예산불용액(합계)계획변경,취소
예산종류1.0000.3030.0370.037
이월예산0.3031.0000.9260.926
불용액(합계)0.0370.9261.0001.000
계획변경,취소0.0370.9261.0001.000
2023-12-13T00:41:53.226356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
불용액(합계)예산종류계획변경,취소
불용액(합계)1.0000.0610.999
예산종류0.0611.0000.061
계획변경,취소0.9990.0611.000
2023-12-13T00:41:53.352656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산종류불용액(합계)계획변경,취소
예산종류1.0000.0610.061
불용액(합계)0.0611.0000.999
계획변경,취소0.0610.9991.000

Missing values

2023-12-13T00:41:44.738125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:41:44.916812image/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

예산종류예산년도예산코드분류코드예산과목명분류코드명이월예산본예산배정예산추경예산전용예산불용액(합계)계획변경,취소
012020111116001가정용가정용 사용료-5126504000-----
112020111116001가정용가정용 사용료-29092556000-----
212020111116001가정용가정용 사용료-4688703000-----
312020111116001가정용가정용 사용료-4067309000-----
412020111116001가정용가정용 사용료-4533355000-----
512020111116001가정용가정용 사용료-19051388000-----
612020111116001가정용가정용 사용료-14405052000-----
712020111116001가정용가정용 사용료-13416470000-----
812020111116001가정용가정용 사용료-17780354000-----
912020111116001가정용가정용 사용료-22228973000-----
예산종류예산년도예산코드분류코드예산과목명분류코드명이월예산본예산배정예산추경예산전용예산불용액(합계)계획변경,취소
17172202022413c019감리비당감2배수지 설치공사 건설사업관리용역(이월)24470000-000--
17182202022414A805시설부대비사직배수지 설치공사 시설부대비0800000080000000000
17192202022414c020시설부대비당감2배수지 설치공사 시설부대비(이월)0-000--
17202202022612A911국고보조금반환금덕산정수장 태양광발전장치 설치 집행잔액 반환금0-19000000190000000--
17212202022612A912국고보조금반환금매리취수장 태양광발전장치 설치 집행잔액 반환금0-1197000001197000000--
17222202022612B075국고보조금반환금사상가압장 비효율 펌프모터 교체 집행잔액 반환0-478800047880000--
17232202022612B322국고보조금반환금물금취수장 취수펌프 제작교체 집행잔액 반환0-39511000395110000--
17242202022612B442국고보조금반환금매리취수장 고압펌프모터 제작교체 집행잔액 반환0-34204000342040000--
172522020227110999예비비자본예산 예비비030000000000-19000000000--
172632020331104000자금교부자금교부0-000--

Duplicate rows

Most frequently occurring

예산종류예산년도예산코드분류코드예산과목명분류코드명이월예산본예산배정예산추경예산전용예산불용액(합계)계획변경,취소# duplicates
312020111766202기타수수료수익성능검사료(32mm이상)-50000-----11
3512020125380525기관운영업무추진비기관운영업무추진비031350003135000000011
712020111766212기타수수료수익정수해제료(32mm이상)-40000-----9
2912020125140335직책급업무수행경비직책급업무수행경비01800000180000000009
3012020125230615징수및수용가관리비-일반운영비-사무관리비운영수당02886000028920000060000008
912020115146315기타이자수익기타이자수익-1000000-----7
1312020118006461기타영업외수익기타영업외수익-200000-----7
3812020125438087일반재료비계량기교체용 자재 및 공구03000000300000000007
3112020125240690공공운영비차량선박비07200000720000000005
212020111766201기타수수료수익성능검사료(25mm이하)-539000-----4