Overview

Dataset statistics

Number of variables9
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows955
Duplicate rows (%)9.6%
Total size in memory791.0 KiB
Average record size in memory81.0 B

Variable types

Categorical1
DateTime1
Text7

Dataset

Description부산광역시 상수도본부 승인월간집계정보입니다. 승인된 예산에 대한 월간 집계정보 제공. 예산코드, 분류코드, 예산과목명, 분류코드명, 배정예산, 추경예산, 전용예산 항목 공개
Author부산광역시
URLhttps://www.data.go.kr/data/15083544/fileData.do

Alerts

Dataset has 955 (9.6%) duplicate rowsDuplicates
예산종류 is highly imbalanced (55.3%)Imbalance

Reproduction

Analysis started2023-12-12 21:25:38.130889
Analysis finished2023-12-12 21:25:38.918592
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

예산종류
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
8114 
2
1874 
3
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 8114
81.1%
2 1874
 
18.7%
3 12
 
0.1%

Length

2023-12-13T06:25:38.978411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:25:39.068766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8114
81.1%
2 1874
 
18.7%
3 12
 
0.1%

예산년월
Date

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-01-01 00:00:00
Maximum2020-12-01 00:00:00
2023-12-13T06:25:39.163178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:39.656831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

예산코드
Text

Distinct159
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:25:39.997771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters50000
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

Unique12 ?
Unique (%)0.1%

Sample

1st row12259
2nd row22152
3rd row12443
4th row12553
5th row12533
ValueCountFrequency (%)
22142 879
 
8.8%
12559 732
 
7.3%
22152 524
 
5.2%
12259 408
 
4.1%
12511 386
 
3.9%
12503 295
 
2.9%
12524 262
 
2.6%
12523 256
 
2.6%
12552 222
 
2.2%
22176 200
 
2.0%
Other values (149) 5836
58.4%
2023-12-13T06:25:40.509569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 17059
34.1%
1 13682
27.4%
5 7555
15.1%
3 3692
 
7.4%
4 3255
 
6.5%
9 1603
 
3.2%
6 1157
 
2.3%
0 955
 
1.9%
7 560
 
1.1%
8 184
 
0.4%
Other values (7) 298
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49702
99.4%
Uppercase Letter 298
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 17059
34.3%
1 13682
27.5%
5 7555
15.2%
3 3692
 
7.4%
4 3255
 
6.5%
9 1603
 
3.2%
6 1157
 
2.3%
0 955
 
1.9%
7 560
 
1.1%
8 184
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
B 148
49.7%
F 87
29.2%
E 23
 
7.7%
H 12
 
4.0%
G 12
 
4.0%
A 12
 
4.0%
I 4
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 49702
99.4%
Latin 298
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2 17059
34.3%
1 13682
27.5%
5 7555
15.2%
3 3692
 
7.4%
4 3255
 
6.5%
9 1603
 
3.2%
6 1157
 
2.3%
0 955
 
1.9%
7 560
 
1.1%
8 184
 
0.4%
Latin
ValueCountFrequency (%)
B 148
49.7%
F 87
29.2%
E 23
 
7.7%
H 12
 
4.0%
G 12
 
4.0%
A 12
 
4.0%
I 4
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 17059
34.1%
1 13682
27.4%
5 7555
15.1%
3 3692
 
7.4%
4 3255
 
6.5%
9 1603
 
3.2%
6 1157
 
2.3%
0 955
 
1.9%
7 560
 
1.1%
8 184
 
0.4%
Other values (7) 298
 
0.6%

분류코드
Text

Distinct786
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:25:40.923713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.9993
Min length3

Characters and Unicode

Total characters39993
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

Unique51 ?
Unique (%)0.5%

Sample

1st row8122
2nd rowB415
3rd row8076
4th row0870
5th row0502
ValueCountFrequency (%)
0015 141
 
1.4%
0690 132
 
1.3%
0279 132
 
1.3%
0502 131
 
1.3%
0904 131
 
1.3%
8200 131
 
1.3%
0345 130
 
1.3%
0605 130
 
1.3%
0675 130
 
1.3%
0501 129
 
1.3%
Other values (772) 8683
86.8%
2023-12-13T06:25:41.503146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10328
25.8%
3 3989
 
10.0%
1 3968
 
9.9%
8 3850
 
9.6%
5 3784
 
9.5%
2 3566
 
8.9%
4 2444
 
6.1%
6 2440
 
6.1%
9 2091
 
5.2%
7 1872
 
4.7%
Other values (5) 1661
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38332
95.8%
Uppercase Letter 1419
 
3.5%
Lowercase Letter 240
 
0.6%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10328
26.9%
3 3989
 
10.4%
1 3968
 
10.4%
8 3850
 
10.0%
5 3784
 
9.9%
2 3566
 
9.3%
4 2444
 
6.4%
6 2440
 
6.4%
9 2091
 
5.5%
7 1872
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
B 891
62.8%
C 279
 
19.7%
A 249
 
17.5%
Lowercase Letter
ValueCountFrequency (%)
c 240
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38334
95.9%
Latin 1659
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10328
26.9%
3 3989
 
10.4%
1 3968
 
10.4%
8 3850
 
10.0%
5 3784
 
9.9%
2 3566
 
9.3%
4 2444
 
6.4%
6 2440
 
6.4%
9 2091
 
5.5%
7 1872
 
4.9%
Latin
ValueCountFrequency (%)
B 891
53.7%
C 279
 
16.8%
A 249
 
15.0%
c 240
 
14.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39993
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10328
25.8%
3 3989
 
10.0%
1 3968
 
9.9%
8 3850
 
9.6%
5 3784
 
9.5%
2 3566
 
8.9%
4 2444
 
6.1%
6 2440
 
6.1%
9 2091
 
5.2%
7 1872
 
4.7%
Other values (5) 1661
 
4.2%

예산과목명
Text

Distinct98
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:25:41.777155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length5.4492
Min length2

Characters and Unicode

Total characters54492
Distinct characters131
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

Unique20 ?
Unique (%)0.2%

Sample

1st row수선유지비
2nd row시설비
3rd row일반재료비
4th row기타복리후생비
5th row월액여비
ValueCountFrequency (%)
시설비 1557
15.5%
수선유지비 1438
 
14.3%
보수 669
 
6.7%
무기계약근로자보수 578
 
5.7%
공공운영비 509
 
5.1%
사무관리비 474
 
4.7%
사회보험부담금 339
 
3.4%
기타복리후생비 287
 
2.9%
국내여비 285
 
2.8%
일반재료비 265
 
2.6%
Other values (90) 3654
36.3%
2023-12-13T06:25:42.188885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 7831
 
14.4%
수 4088
 
7.5%
보 2356
 
4.3%
무 2064
 
3.8%
설 1730
 
3.2%
시 1704
 
3.1%
기 1624
 
3.0%
지 1562
 
2.9%
선 1518
 
2.8%
유 1507
 
2.8%
Other values (121) 28508
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54246
99.5%
Dash Punctuation 184
 
0.3%
Space Separator 55
 
0.1%
Other Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 7831
 
14.4%
수 4088
 
7.5%
보 2356
 
4.3%
무 2064
 
3.8%
설 1730
 
3.2%
시 1704
 
3.1%
기 1624
 
3.0%
지 1562
 
2.9%
선 1518
 
2.8%
유 1507
 
2.8%
Other values (118) 28262
52.1%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%
Space Separator
ValueCountFrequency (%)
55
100.0%
Other Punctuation
ValueCountFrequency (%)
· 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54246
99.5%
Common 246
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 7831
 
14.4%
수 4088
 
7.5%
보 2356
 
4.3%
무 2064
 
3.8%
설 1730
 
3.2%
시 1704
 
3.1%
기 1624
 
3.0%
지 1562
 
2.9%
선 1518
 
2.8%
유 1507
 
2.8%
Other values (118) 28262
52.1%
Common
ValueCountFrequency (%)
- 184
74.8%
55
 
22.4%
· 7
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54246
99.5%
ASCII 239
 
0.4%
None 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 7831
 
14.4%
수 4088
 
7.5%
보 2356
 
4.3%
무 2064
 
3.8%
설 1730
 
3.2%
시 1704
 
3.1%
기 1624
 
3.0%
지 1562
 
2.9%
선 1518
 
2.8%
유 1507
 
2.8%
Other values (118) 28262
52.1%
ASCII
ValueCountFrequency (%)
- 184
77.0%
55
 
23.0%
None
ValueCountFrequency (%)
· 7
100.0%

분류코드명
Text

Distinct697
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:25:42.502701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length10.748
Min length2

Characters and Unicode

Total characters107480
Distinct characters423
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

Unique69 ?
Unique (%)0.7%

Sample

1st row슬러지처리비
2nd row덕산정수장 제2정수 침전지 유입밸브 제작 교체
3rd row가정수돗물 무료점검서비스용 자재
4th row급량비
5th row월액여비
ValueCountFrequency (%)
및 798
 
3.7%
교체 527
 
2.5%
주변 411
 
1.9%
유지관리 313
 
1.5%
수당 295
 
1.4%
일반수용비 272
 
1.3%
직급보조비 261
 
1.2%
제세 260
 
1.2%
공공요금 260
 
1.2%
정액급식비 258
 
1.2%
Other values (1111) 17724
82.9%
2023-12-13T06:25:43.009615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11410
 
10.6%
수 5211
 
4.8%
비 4931
 
4.6%
공 2472
 
2.3%
사 2470
 
2.3%
관 2337
 
2.2%
무 2142
 
2.0%
설 2141
 
2.0%
기 1838
 
1.7%
시 1754
 
1.6%
Other values (413) 70774
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91938
85.5%
Space Separator 11410
 
10.6%
Open Punctuation 1200
 
1.1%
Close Punctuation 1200
 
1.1%
Decimal Number 875
 
0.8%
Other Punctuation 363
 
0.3%
Uppercase Letter 313
 
0.3%
Math Symbol 116
 
0.1%
Dash Punctuation 54
 
0.1%
Control 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 5211
 
5.7%
비 4931
 
5.4%
공 2472
 
2.7%
사 2470
 
2.7%
관 2337
 
2.5%
무 2142
 
2.3%
설 2141
 
2.3%
기 1838
 
2.0%
시 1754
 
1.9%
정 1665
 
1.8%
Other values (374) 64977
70.7%
Uppercase Letter
ValueCountFrequency (%)
C 73
23.3%
T 47
15.0%
S 36
11.5%
V 34
10.9%
A 18
 
5.8%
E 15
 
4.8%
I 13
 
4.2%
L 12
 
3.8%
M 12
 
3.8%
P 11
 
3.5%
Other values (8) 42
13.4%
Decimal Number
ValueCountFrequency (%)
2 267
30.5%
1 265
30.3%
3 125
14.3%
5 77
 
8.8%
4 60
 
6.9%
7 30
 
3.4%
0 25
 
2.9%
8 13
 
1.5%
6 11
 
1.3%
9 2
 
0.2%
Other Punctuation
ValueCountFrequency (%)
· 223
61.4%
, 138
38.0%
. 2
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 99
85.3%
∼ 17
 
14.7%
Space Separator
ValueCountFrequency (%)
11410
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1200
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1200
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Control
ValueCountFrequency (%)
6
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91938
85.5%
Common 15224
 
14.2%
Latin 318
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 5211
 
5.7%
비 4931
 
5.4%
공 2472
 
2.7%
사 2470
 
2.7%
관 2337
 
2.5%
무 2142
 
2.3%
설 2141
 
2.3%
기 1838
 
2.0%
시 1754
 
1.9%
정 1665
 
1.8%
Other values (374) 64977
70.7%
Common
ValueCountFrequency (%)
11410
74.9%
( 1200
 
7.9%
) 1200
 
7.9%
2 267
 
1.8%
1 265
 
1.7%
· 223
 
1.5%
, 138
 
0.9%
3 125
 
0.8%
~ 99
 
0.7%
5 77
 
0.5%
Other values (10) 220
 
1.4%
Latin
ValueCountFrequency (%)
C 73
23.0%
T 47
14.8%
S 36
11.3%
V 34
10.7%
A 18
 
5.7%
E 15
 
4.7%
I 13
 
4.1%
L 12
 
3.8%
M 12
 
3.8%
P 11
 
3.5%
Other values (9) 47
14.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91938
85.5%
ASCII 15302
 
14.2%
None 223
 
0.2%
Math Operators 17
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11410
74.6%
( 1200
 
7.8%
) 1200
 
7.8%
2 267
 
1.7%
1 265
 
1.7%
, 138
 
0.9%
3 125
 
0.8%
~ 99
 
0.6%
5 77
 
0.5%
C 73
 
0.5%
Other values (27) 448
 
2.9%
Hangul
ValueCountFrequency (%)
수 5211
 
5.7%
비 4931
 
5.4%
공 2472
 
2.7%
사 2470
 
2.7%
관 2337
 
2.5%
무 2142
 
2.3%
설 2141
 
2.3%
기 1838
 
2.0%
시 1754
 
1.9%
정 1665
 
1.8%
Other values (374) 64977
70.7%
None
ValueCountFrequency (%)
· 223
100.0%
Math Operators
ValueCountFrequency (%)
∼ 17
100.0%

배정예산
Text

Distinct1697
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:25:43.303564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length1
Mean length3.9094
Min length1

Characters and Unicode

Total characters39094
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

Unique1254 ?
Unique (%)12.5%

Sample

1st row815346000
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
5697
57.0%
0 677
 
6.8%
20000000 50
 
0.5%
450000 45
 
0.4%
10000000 41
 
0.4%
6000000 40
 
0.4%
90000000 36
 
0.4%
100000000 36
 
0.4%
3000000 36
 
0.4%
1000000 32
 
0.3%
Other values (1578) 3310
33.1%
2023-12-13T06:25:43.730548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18896
48.3%
- 6129
 
15.7%
4303
 
11.0%
1 1764
 
4.5%
2 1450
 
3.7%
5 1274
 
3.3%
4 1093
 
2.8%
3 1038
 
2.7%
6 938
 
2.4%
8 794
 
2.0%
Other values (2) 1415
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28662
73.3%
Dash Punctuation 6129
 
15.7%
Space Separator 4303
 
11.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18896
65.9%
1 1764
 
6.2%
2 1450
 
5.1%
5 1274
 
4.4%
4 1093
 
3.8%
3 1038
 
3.6%
6 938
 
3.3%
8 794
 
2.8%
7 725
 
2.5%
9 690
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 6129
100.0%
Space Separator
ValueCountFrequency (%)
4303
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39094
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18896
48.3%
- 6129
 
15.7%
4303
 
11.0%
1 1764
 
4.5%
2 1450
 
3.7%
5 1274
 
3.3%
4 1093
 
2.8%
3 1038
 
2.7%
6 938
 
2.4%
8 794
 
2.0%
Other values (2) 1415
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39094
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18896
48.3%
- 6129
 
15.7%
4303
 
11.0%
1 1764
 
4.5%
2 1450
 
3.7%
5 1274
 
3.3%
4 1093
 
2.8%
3 1038
 
2.7%
6 938
 
2.4%
8 794
 
2.0%
Other values (2) 1415
 
3.6%

추경예산
Text

Distinct421
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:25:43.985845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length1
Mean length1.8252
Min length1

Characters and Unicode

Total characters18252
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

Unique361 ?
Unique (%)3.6%

Sample

1st row0
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
5697
57.0%
0 3776
37.8%
20000000 10
 
0.1%
90000000 9
 
0.1%
50000000 7
 
0.1%
300000000 7
 
0.1%
80000000 7
 
0.1%
150000000 7
 
0.1%
200000000 6
 
0.1%
40000000 6
 
0.1%
Other values (389) 468
 
4.7%
2023-12-13T06:25:44.371873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6347
34.8%
- 5998
32.9%
4303
23.6%
1 290
 
1.6%
5 221
 
1.2%
2 206
 
1.1%
3 177
 
1.0%
4 177
 
1.0%
8 145
 
0.8%
9 141
 
0.8%
Other values (2) 247
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7951
43.6%
Dash Punctuation 5998
32.9%
Space Separator 4303
23.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6347
79.8%
1 290
 
3.6%
5 221
 
2.8%
2 206
 
2.6%
3 177
 
2.2%
4 177
 
2.2%
8 145
 
1.8%
9 141
 
1.8%
6 129
 
1.6%
7 118
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 5998
100.0%
Space Separator
ValueCountFrequency (%)
4303
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6347
34.8%
- 5998
32.9%
4303
23.6%
1 290
 
1.6%
5 221
 
1.2%
2 206
 
1.1%
3 177
 
1.0%
4 177
 
1.0%
8 145
 
0.8%
9 141
 
0.8%
Other values (2) 247
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6347
34.8%
- 5998
32.9%
4303
23.6%
1 290
 
1.6%
5 221
 
1.2%
2 206
 
1.1%
3 177
 
1.0%
4 177
 
1.0%
8 145
 
0.8%
9 141
 
0.8%
Other values (2) 247
 
1.4%

전용예산
Text

Distinct293
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:25:44.618614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length1
Mean length1.7099
Min length1

Characters and Unicode

Total characters17099
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

Unique240 ?
Unique (%)2.4%

Sample

1st row0
2nd row-
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
5697
57.0%
0 3897
39.0%
60000 22
 
0.2%
50000000 12
 
0.1%
20000000 10
 
0.1%
7000000 9
 
0.1%
2000000 9
 
0.1%
10000000 9
 
0.1%
3000000 9
 
0.1%
800000 6
 
0.1%
Other values (214) 320
 
3.2%
2023-12-13T06:25:45.028970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 5879
34.4%
0 5828
34.1%
4303
25.2%
1 204
 
1.2%
2 167
 
1.0%
6 134
 
0.8%
5 125
 
0.7%
3 125
 
0.7%
7 94
 
0.5%
4 93
 
0.5%
Other values (2) 147
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6917
40.5%
Dash Punctuation 5879
34.4%
Space Separator 4303
25.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5828
84.3%
1 204
 
2.9%
2 167
 
2.4%
6 134
 
1.9%
5 125
 
1.8%
3 125
 
1.8%
7 94
 
1.4%
4 93
 
1.3%
8 91
 
1.3%
9 56
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 5879
100.0%
Space Separator
ValueCountFrequency (%)
4303
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17099
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 5879
34.4%
0 5828
34.1%
4303
25.2%
1 204
 
1.2%
2 167
 
1.0%
6 134
 
0.8%
5 125
 
0.7%
3 125
 
0.7%
7 94
 
0.5%
4 93
 
0.5%
Other values (2) 147
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17099
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 5879
34.4%
0 5828
34.1%
4303
25.2%
1 204
 
1.2%
2 167
 
1.0%
6 134
 
0.8%
5 125
 
0.7%
3 125
 
0.7%
7 94
 
0.5%
4 93
 
0.5%
Other values (2) 147
 
0.9%

Correlations

2023-12-13T06:25:45.157310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산종류예산년월예산과목명
예산종류1.0000.3500.999
예산년월0.3501.0000.294
예산과목명0.9990.2941.000

Missing values

2023-12-13T06:25:38.711350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:25:38.842762image/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

예산종류예산년월예산코드분류코드예산과목명분류코드명배정예산추경예산전용예산
19512020-01122598122수선유지비슬러지처리비81534600000
907422020-0422152B415시설비덕산정수장 제2정수 침전지 유입밸브 제작 교체---
785012020-12124438076일반재료비가정수돗물 무료점검서비스용 자재---
538212020-08125530870기타복리후생비급량비---
265512020-04125330502월액여비월액여비---
125112020-02125240690공공운영비차량선박비---
170012020-03123240673공공운영비공공요금 및 제세626100000
426112020-071215B8240동력비펌프 효율화사업 투자비 상환금---
490012020-08121240671공공운영비공공요금 및 제세---
816712020-12125591633수선유지비방수비 납부---
예산종류예산년월예산코드분류코드예산과목명분류코드명배정예산추경예산전용예산
650112020-10124530795기타복리후생비직원 건강검진---
24712020-01123030013보수수당47000000000
869622020-0222152B416시설비덕산정수장 중앙관리실 개선사업---
876522020-0222142A703시설비덕산 제3정수장 입상활성탄 여과지 개량공사(3차)000
681512020-10125598200수선유지비급수불편해소---
36912020-01124400534시책업무추진비시책업무추진비285000000
244312020-04124115374무기계약근로자보수실무사무원(현장)---
623212020-10121598702수선유지비취수시설 기계·전기시설물 유지수선38000000038000000
935422020-06221769032자산취득비냉방기 구입(대체)---
796012020-12125125386기간제근로자등보수수도검침(공무직 전환 제외자)---

Duplicate rows

Most frequently occurring

예산종류예산년월예산코드분류코드예산과목명분류코드명배정예산추경예산전용예산# duplicates
93422020-0222152B704시설비블록유량계 교체---14
22012020-04125030015보수수당---12
32212020-05125030015보수수당---12
45012020-07125030015보수수당---12
67712020-10125030015보수수당---12
77812020-11125030015보수수당---12
8812020-02125030015보수수당---11
9312020-02125140335직책급업무수행경비직책급업무수행경비---11
9412020-02125150345직급보조비직급보조비---11
9712020-02125230615사무관리비운영수당---11