Overview

Dataset statistics

Number of variables13
Number of observations1724
Missing cells0
Missing cells (%)0.0%
Duplicate rows56
Duplicate rows (%)3.2%
Total size in memory178.6 KiB
Average record size in memory106.1 B

Variable types

Categorical4
Text9

Dataset

Description부산광역시 상수도본부 사업소예산연간집계정보입니다. 각사업소에서 신청한 예산에 대해 승인된 예산들로 월간집계정보를 기초로 한 연간집계정보 입니다.(예산종류, 예산코드, 예산과목명 등)
Author부산광역시
URLhttps://www.data.go.kr/data/15083538/fileData.do

Alerts

예산년도 has constant value ""Constant
Dataset has 56 (3.2%) duplicate rowsDuplicates
이월예산이체 is highly overall correlated with 본예산이체High correlation
본예산이체 is highly overall correlated with 이월예산이체High correlation

Reproduction

Analysis started2023-12-12 07:56:42.994914
Analysis finished2023-12-12 07:56:44.180917
Duration1.19 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
1231 
2
492 
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 1231
71.4%
2 492
 
28.5%
3 1
 
0.1%

Length

2023-12-12T16:56:44.261668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:56:44.392963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1231
71.4%
2 492
 
28.5%
3 1
 
0.1%

예산년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2020
1724 

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 1724
100.0%

Length

2023-12-12T16:56:44.548717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:56:44.667283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 1724
100.0%

예산코드
Text

Distinct178
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-12T16:56:44.954077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters8620
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 (%)2.6%

Sample

1st row11111
2nd row11111
3rd row11111
4th row11111
5th row11111
ValueCountFrequency (%)
22142 171
 
9.9%
11176 120
 
7.0%
22152 109
 
6.3%
22176 91
 
5.3%
12559 82
 
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) 981
56.9%
2023-12-12T16:56:45.474015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2811
32.6%
2 2613
30.3%
5 963
 
11.2%
3 520
 
6.0%
4 492
 
5.7%
6 416
 
4.8%
7 314
 
3.6%
0 203
 
2.4%
9 202
 
2.3%
8 45
 
0.5%
Other values (7) 41
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8579
99.5%
Uppercase Letter 41
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2811
32.8%
2 2613
30.5%
5 963
 
11.2%
3 520
 
6.1%
4 492
 
5.7%
6 416
 
4.8%
7 314
 
3.7%
0 203
 
2.4%
9 202
 
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 8579
99.5%
Latin 41
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2811
32.8%
2 2613
30.5%
5 963
 
11.2%
3 520
 
6.1%
4 492
 
5.7%
6 416
 
4.8%
7 314
 
3.7%
0 203
 
2.4%
9 202
 
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 8620
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2811
32.6%
2 2613
30.3%
5 963
 
11.2%
3 520
 
6.0%
4 492
 
5.7%
6 416
 
4.8%
7 314
 
3.6%
0 203
 
2.4%
9 202
 
2.3%
8 45
 
0.5%
Other values (7) 41
 
0.5%

분류코드
Text

Distinct841
Distinct (%)48.8%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-12T16:56:45.844956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.6479118
Min length1

Characters and Unicode

Total characters6289
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

Unique664 ?
Unique (%)38.5%

Sample

1st row6001
2nd row6001
3rd row6001
4th row6001
5th row6001
ValueCountFrequency (%)
6461 17
 
1.0%
6315 16
 
0.9%
6902 13
 
0.8%
6173 12
 
0.7%
6202 12
 
0.7%
943 12
 
0.7%
6201 12
 
0.7%
6005 12
 
0.7%
6423 12
 
0.7%
15 12
 
0.7%
Other values (827) 1594
92.5%
2023-12-12T16:56:46.696608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 931
14.8%
1 853
13.6%
6 753
12.0%
2 643
10.2%
3 574
9.1%
8 538
8.6%
5 479
7.6%
4 447
7.1%
9 411
6.5%
7 298
 
4.7%
Other values (5) 362
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5927
94.2%
Uppercase Letter 298
 
4.7%
Lowercase Letter 63
 
1.0%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 931
15.7%
1 853
14.4%
6 753
12.7%
2 643
10.8%
3 574
9.7%
8 538
9.1%
5 479
8.1%
4 447
7.5%
9 411
6.9%
7 298
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 188
63.1%
A 58
 
19.5%
C 52
 
17.4%
Lowercase Letter
ValueCountFrequency (%)
c 63
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5928
94.3%
Latin 361
 
5.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 931
15.7%
1 853
14.4%
6 753
12.7%
2 643
10.8%
3 574
9.7%
8 538
9.1%
5 479
8.1%
4 447
7.5%
9 411
6.9%
7 298
 
5.0%
Latin
ValueCountFrequency (%)
B 188
52.1%
c 63
 
17.5%
A 58
 
16.1%
C 52
 
14.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6289
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 931
14.8%
1 853
13.6%
6 753
12.0%
2 643
10.2%
3 574
9.1%
8 538
8.6%
5 479
7.6%
4 447
7.1%
9 411
6.5%
7 298
 
4.7%
Other values (5) 362
 
5.8%

예산과목명
Text

Distinct111
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-12T16:56:46.929647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length5.7436195
Min length2

Characters and Unicode

Total characters9902
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 314
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 (103) 774
44.6%
2023-12-12T16:56:47.311727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 1198
 
12.1%
수 1046
 
10.6%
기 396
 
4.0%
설 345
 
3.5%
시 337
 
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) 5382
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9774
98.7%
Dash Punctuation 112
 
1.1%
Space Separator 11
 
0.1%
Other Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 1198
 
12.3%
수 1046
 
10.7%
기 396
 
4.1%
설 345
 
3.5%
시 337
 
3.4%
익 272
 
2.8%
타 264
 
2.7%
보 236
 
2.4%
금 222
 
2.3%
자 204
 
2.1%
Other values (123) 5254
53.8%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
· 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9774
98.7%
Common 128
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 1198
 
12.3%
수 1046
 
10.7%
기 396
 
4.1%
설 345
 
3.5%
시 337
 
3.4%
익 272
 
2.8%
타 264
 
2.7%
보 236
 
2.4%
금 222
 
2.3%
자 204
 
2.1%
Other values (123) 5254
53.8%
Common
ValueCountFrequency (%)
- 112
87.5%
11
 
8.6%
· 5
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9774
98.7%
ASCII 123
 
1.2%
None 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 1198
 
12.3%
수 1046
 
10.7%
기 396
 
4.1%
설 345
 
3.5%
시 337
 
3.4%
익 272
 
2.8%
타 264
 
2.7%
보 236
 
2.4%
금 222
 
2.3%
자 204
 
2.1%
Other values (123) 5254
53.8%
ASCII
ValueCountFrequency (%)
- 112
91.1%
11
 
8.9%
None
ValueCountFrequency (%)
· 5
100.0%

분류코드명
Text

Distinct740
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-12T16:56:47.622895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length12.00348
Min length2

Characters and Unicode

Total characters20694
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

Unique601 ?
Unique (%)34.9%

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 (1156) 3352
85.2%
2023-12-12T16:56:48.087110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2219
 
10.7%
수 857
 
4.1%
비 623
 
3.0%
사 577
 
2.8%
공 487
 
2.4%
( 401
 
1.9%
) 401
 
1.9%
기 395
 
1.9%
설 375
 
1.8%
관 351
 
1.7%
Other values (420) 14008
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16963
82.0%
Space Separator 2219
 
10.7%
Open Punctuation 401
 
1.9%
Close Punctuation 401
 
1.9%
Decimal Number 371
 
1.8%
Lowercase Letter 181
 
0.9%
Other Punctuation 71
 
0.3%
Uppercase Letter 57
 
0.3%
Math Symbol 19
 
0.1%
Dash Punctuation 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 857
 
5.1%
비 623
 
3.7%
사 577
 
3.4%
공 487
 
2.9%
기 395
 
2.3%
설 375
 
2.2%
관 351
 
2.1%
정 332
 
2.0%
용 316
 
1.9%
장 284
 
1.7%
Other values (380) 12366
72.9%
Uppercase Letter
ValueCountFrequency (%)
C 10
17.5%
S 7
12.3%
T 6
10.5%
I 4
 
7.0%
E 4
 
7.0%
V 4
 
7.0%
A 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
41.0%
3 69
18.6%
5 58
 
15.6%
1 57
 
15.4%
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 (%)
2219
100.0%
Open Punctuation
ValueCountFrequency (%)
( 401
100.0%
Close Punctuation
ValueCountFrequency (%)
) 401
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16963
82.0%
Common 3493
 
16.9%
Latin 238
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 857
 
5.1%
비 623
 
3.7%
사 577
 
3.4%
공 487
 
2.9%
기 395
 
2.3%
설 375
 
2.2%
관 351
 
2.1%
정 332
 
2.0%
용 316
 
1.9%
장 284
 
1.7%
Other values (380) 12366
72.9%
Common
ValueCountFrequency (%)
2219
63.5%
( 401
 
11.5%
) 401
 
11.5%
2 152
 
4.4%
3 69
 
2.0%
5 58
 
1.7%
1 57
 
1.6%
, 38
 
1.1%
· 32
 
0.9%
~ 17
 
0.5%
Other values (10) 49
 
1.4%
Latin
ValueCountFrequency (%)
m 180
75.6%
C 10
 
4.2%
S 7
 
2.9%
T 6
 
2.5%
I 4
 
1.7%
E 4
 
1.7%
V 4
 
1.7%
A 4
 
1.7%
L 3
 
1.3%
P 3
 
1.3%
Other values (10) 13
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16963
82.0%
ASCII 3697
 
17.9%
None 32
 
0.2%
Math Operators 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2219
60.0%
( 401
 
10.8%
) 401
 
10.8%
m 180
 
4.9%
2 152
 
4.1%
3 69
 
1.9%
5 58
 
1.6%
1 57
 
1.5%
, 38
 
1.0%
~ 17
 
0.5%
Other values (28) 105
 
2.8%
Hangul
ValueCountFrequency (%)
수 857
 
5.1%
비 623
 
3.7%
사 577
 
3.4%
공 487
 
2.9%
기 395
 
2.3%
설 375
 
2.2%
관 351
 
2.1%
정 332
 
2.0%
용 316
 
1.9%
장 284
 
1.7%
Other values (380) 12366
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
2023-12-12T16:56:48.288517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length1
Mean length1.3636891
Min length1

Characters and Unicode

Total characters2351
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 1310
76.0%
352
 
20.4%
220,308,000 1
 
0.1%
23,535,590 1
 
0.1%
47,695,000 1
 
0.1%
290,206,610 1
 
0.1%
301,006,090 1
 
0.1%
256,744,000 1
 
0.1%
310,744,000 1
 
0.1%
934,000,000 1
 
0.1%
Other values (54) 54
 
3.1%
2023-12-12T16:56:48.698456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1524
64.8%
- 352
 
15.0%
, 136
 
5.8%
2 51
 
2.2%
1 44
 
1.9%
4 43
 
1.8%
3 39
 
1.7%
6 36
 
1.5%
7 35
 
1.5%
9 33
 
1.4%
Other values (2) 58
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1863
79.2%
Dash Punctuation 352
 
15.0%
Other Punctuation 136
 
5.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1524
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%
Dash Punctuation
ValueCountFrequency (%)
- 352
100.0%
Other Punctuation
ValueCountFrequency (%)
, 136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2351
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1524
64.8%
- 352
 
15.0%
, 136
 
5.8%
2 51
 
2.2%
1 44
 
1.9%
4 43
 
1.8%
3 39
 
1.7%
6 36
 
1.5%
7 35
 
1.5%
9 33
 
1.4%
Other values (2) 58
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2351
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1524
64.8%
- 352
 
15.0%
, 136
 
5.8%
2 51
 
2.2%
1 44
 
1.9%
4 43
 
1.8%
3 39
 
1.7%
6 36
 
1.5%
7 35
 
1.5%
9 33
 
1.4%
Other values (2) 58
 
2.5%

본예산
Text

Distinct927
Distinct (%)53.8%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-12T16:56:48.946638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.1931555
Min length1

Characters and Unicode

Total characters12401
Distinct characters11
Distinct categories2 ?
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 row4688703000
2nd row17780354000
3rd row13416470000
4th row4067309000
5th row6835336000
ValueCountFrequency (%)
186
 
10.8%
0 36
 
2.1%
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
79.0%
2023-12-12T16:56:49.348589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7610
61.4%
1 808
 
6.5%
2 631
 
5.1%
5 560
 
4.5%
3 507
 
4.1%
4 504
 
4.1%
6 467
 
3.8%
8 456
 
3.7%
7 366
 
3.0%
9 306
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12215
98.5%
Dash Punctuation 186
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7610
62.3%
1 808
 
6.6%
2 631
 
5.2%
5 560
 
4.6%
3 507
 
4.2%
4 504
 
4.1%
6 467
 
3.8%
8 456
 
3.7%
7 366
 
3.0%
9 306
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12401
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7610
61.4%
1 808
 
6.5%
2 631
 
5.1%
5 560
 
4.5%
3 507
 
4.1%
4 504
 
4.1%
6 467
 
3.8%
8 456
 
3.7%
7 366
 
3.0%
9 306
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12401
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7610
61.4%
1 808
 
6.5%
2 631
 
5.1%
5 560
 
4.5%
3 507
 
4.1%
4 504
 
4.1%
6 467
 
3.8%
8 456
 
3.7%
7 366
 
3.0%
9 306
 
2.5%

배정예산
Text

Distinct937
Distinct (%)54.4%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-12T16:56:49.591538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.2708817
Min length1

Characters and Unicode

Total characters10811
Distinct characters11
Distinct categories2 ?
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 (%)48.3%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
352
 
20.4%
0 115
 
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
67.2%
2023-12-12T16:56:49.957267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6111
56.5%
1 746
 
6.9%
2 588
 
5.4%
5 517
 
4.8%
3 509
 
4.7%
4 467
 
4.3%
6 429
 
4.0%
8 411
 
3.8%
- 352
 
3.3%
7 349
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10459
96.7%
Dash Punctuation 352
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6111
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%
Dash Punctuation
ValueCountFrequency (%)
- 352
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10811
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6111
56.5%
1 746
 
6.9%
2 588
 
5.4%
5 517
 
4.8%
3 509
 
4.7%
4 467
 
4.3%
6 429
 
4.0%
8 411
 
3.8%
- 352
 
3.3%
7 349
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10811
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6111
56.5%
1 746
 
6.9%
2 588
 
5.4%
5 517
 
4.8%
3 509
 
4.7%
4 467
 
4.3%
6 429
 
4.0%
8 411
 
3.8%
- 352
 
3.3%
7 349
 
3.2%

추경예산
Text

Distinct419
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-12T16:56:50.205274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length1
Mean length3.2807425
Min length1

Characters and Unicode

Total characters5656
Distinct characters11
Distinct categories2 ?
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 (%)20.9%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
0 845
49.0%
352
20.4%
20000000 11
 
0.6%
90000000 9
 
0.5%
50000000 8
 
0.5%
300000000 7
 
0.4%
80000000 7
 
0.4%
100000000 6
 
0.3%
10000000 6
 
0.3%
40000000 6
 
0.3%
Other values (385) 467
27.1%
2023-12-12T16:56:50.627076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3403
60.2%
- 650
 
11.5%
1 290
 
5.1%
5 219
 
3.9%
2 200
 
3.5%
4 180
 
3.2%
3 177
 
3.1%
8 149
 
2.6%
9 143
 
2.5%
6 128
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5006
88.5%
Dash Punctuation 650
 
11.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3403
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%
Dash Punctuation
ValueCountFrequency (%)
- 650
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5656
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3403
60.2%
- 650
 
11.5%
1 290
 
5.1%
5 219
 
3.9%
2 200
 
3.5%
4 180
 
3.2%
3 177
 
3.1%
8 149
 
2.6%
9 143
 
2.5%
6 128
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5656
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3403
60.2%
- 650
 
11.5%
1 290
 
5.1%
5 219
 
3.9%
2 200
 
3.5%
4 180
 
3.2%
3 177
 
3.1%
8 149
 
2.6%
9 143
 
2.5%
6 128
 
2.3%

전용예산
Text

Distinct256
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
2023-12-12T16:56:50.884538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length1
Mean length2.2772622
Min length1

Characters and Unicode

Total characters3926
Distinct characters11
Distinct categories2 ?
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 (%)12.8%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
0 1058
61.4%
352
 
20.4%
60000 12
 
0.7%
50000000 7
 
0.4%
100000000 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%
2023-12-12T16:56:51.259156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2501
63.7%
- 485
 
12.4%
1 167
 
4.3%
2 139
 
3.5%
3 111
 
2.8%
6 105
 
2.7%
5 97
 
2.5%
8 88
 
2.2%
4 87
 
2.2%
7 81
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3441
87.6%
Dash Punctuation 485
 
12.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2501
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%
Dash Punctuation
ValueCountFrequency (%)
- 485
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3926
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2501
63.7%
- 485
 
12.4%
1 167
 
4.3%
2 139
 
3.5%
3 111
 
2.8%
6 105
 
2.7%
5 97
 
2.5%
8 88
 
2.2%
4 87
 
2.2%
7 81
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3926
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2501
63.7%
- 485
 
12.4%
1 167
 
4.3%
2 139
 
3.5%
3 111
 
2.8%
6 105
 
2.7%
5 97
 
2.5%
8 88
 
2.2%
4 87
 
2.2%
7 81
 
2.1%

본예산이체
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
0
1372 
-
352 

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 1372
79.6%
- 352
 
20.4%

Length

2023-12-12T16:56:51.445085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:56:51.568040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1372
79.6%
352
 
20.4%

이월예산이체
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.6 KiB
0
1372 
-
352 

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 1372
79.6%
- 352
 
20.4%

Length

2023-12-12T16:56:51.687289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:56:51.808598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1372
79.6%
352
 
20.4%

Correlations

2023-12-12T16:56:51.872150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산종류이월예산본예산이체이월예산이체
예산종류1.0000.3020.1230.123
이월예산0.3021.0001.0001.000
본예산이체0.1231.0001.0001.000
이월예산이체0.1231.0001.0001.000
2023-12-12T16:56:51.975323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이월예산이체본예산이체예산종류
이월예산이체1.0000.9980.203
본예산이체0.9981.0000.203
예산종류0.2030.2031.000
2023-12-12T16:56:52.066716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산종류본예산이체이월예산이체
예산종류1.0000.2030.203
본예산이체0.2031.0000.998
이월예산이체0.2030.9981.000

Missing values

2023-12-12T16:56:43.895592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:56:44.109213image/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

예산종류예산년도예산코드분류코드예산과목명분류코드명이월예산본예산배정예산추경예산전용예산본예산이체이월예산이체
012020111116001가정용가정용 사용료-4688703000-----
112020111116001가정용가정용 사용료-17780354000-----
212020111116001가정용가정용 사용료-13416470000-----
312020111116001가정용가정용 사용료-4067309000-----
412020111116001가정용가정용 사용료-6835336000-----
512020111116001가정용가정용 사용료-14405052000-----
612020111116001가정용가정용 사용료-4533355000-----
712020111116001가정용가정용 사용료-19051388000-----
812020111116001가정용가정용 사용료-22228973000-----
912020111116001가정용가정용 사용료-29092556000-----
예산종류예산년도예산코드분류코드예산과목명분류코드명이월예산본예산배정예산추경예산전용예산본예산이체이월예산이체
17142202022413c019감리비당감2배수지 설치공사 건설사업관리용역(이월)24,470,000-00000
17152202022414A805시설부대비사직배수지 설치공사 시설부대비0800000080000000000
17162202022414c020시설부대비당감2배수지 설치공사 시설부대비(이월)0-00000
17172202022612A911국고보조금반환금덕산정수장 태양광발전장치 설치 집행잔액 반환금0-1900000019000000000
17182202022612A912국고보조금반환금매리취수장 태양광발전장치 설치 집행잔액 반환금0-119700000119700000000
17192202022612B075국고보조금반환금사상가압장 비효율 펌프모터 교체 집행잔액 반환0-47880004788000000
17202202022612B322국고보조금반환금물금취수장 취수펌프 제작교체 집행잔액 반환0-3951100039511000000
17212202022612B442국고보조금반환금매리취수장 고압펌프모터 제작교체 집행잔액 반환0-3420400034204000000
17222202022711999예비비자본예산 예비비030000000000-1900000000000
172332020331104000자금교부자금교부0-00000

Duplicate rows

Most frequently occurring

예산종류예산년도예산코드분류코드예산과목명분류코드명이월예산본예산배정예산추경예산전용예산본예산이체이월예산이체# duplicates
312020111766202기타수수료수익성능검사료(32mm이상)-50000-----11
351202012538525기관운영업무추진비기관운영업무추진비031350003135000000011
712020111766212기타수수료수익정수해제료(32mm이상)-40000-----9
291202012514335직책급업무수행경비직책급업무수행경비01800000180000000009
301202012523615징수및수용가관리비-일반운영비-사무관리비운영수당02886000028920000060000008
912020115146315기타이자수익기타이자수익-1000000-----7
1312020118006461기타영업외수익기타영업외수익-200000-----7
3812020125438087일반재료비계량기교체용 자재 및 공구03000000300000000007
311202012524690공공운영비차량선박비07200000720000000005
212020111766201기타수수료수익성능검사료(25mm이하)-539000-----4