Overview

Dataset statistics

Number of variables7
Number of observations3373
Missing cells347
Missing cells (%)1.5%
Duplicate rows475
Duplicate rows (%)14.1%
Total size in memory184.6 KiB
Average record size in memory56.0 B

Variable types

Categorical4
Text1
DateTime2

Dataset

Description경상남도 밀양시의 지방세ARSS 수납현황에 대한 데이터로 세목명고지구분 고지금액 부과일자징수일자수납형태(현금/카드)선택납부 항목이 있습니다.
Author경상남도 밀양시
URLhttps://www.data.go.kr/data/15042697/fileData.do

Alerts

Dataset has 475 (14.1%) duplicate rowsDuplicates
수납형태(현금/카드) is highly imbalanced (90.9%)Imbalance
선택납부 is highly imbalanced (95.0%)Imbalance
징수일자 has 347 (10.3%) missing valuesMissing

Reproduction

Analysis started2023-12-12 14:49:25.271892
Analysis finished2023-12-12 14:49:26.234055
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

세목명
Categorical

Distinct19
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size26.5 KiB
자동차세(자동차)
1495 
재산세(토지)
821 
재산세(주택)
548 
주민세(개인균등)
254 
재산세(건축물)
 
106
Other values (14)
 
149

Length

Max length11
Median length9
Mean length8.168989
Min length5

Unique

Unique6 ?
Unique (%)0.2%

Sample

1st row자동차세(자동차)
2nd row자동차세(자동차)
3rd row자동차세(자동차)
4th row자동차세(자동차)
5th row자동차세(자동차)

Common Values

ValueCountFrequency (%)
자동차세(자동차) 1495
44.3%
재산세(토지) 821
24.3%
재산세(주택) 548
 
16.2%
주민세(개인균등) 254
 
7.5%
재산세(건축물) 106
 
3.1%
등록면허세(면허) 80
 
2.4%
지방소득세(종합소득) 22
 
0.7%
주민세(개인사업) 15
 
0.4%
취득세(부동산) 13
 
0.4%
지방소득세(양도소득) 6
 
0.2%
Other values (9) 13
 
0.4%

Length

2023-12-12T23:49:26.338911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
자동차세(자동차 1495
44.3%
재산세(토지 821
24.3%
재산세(주택 548
 
16.2%
주민세(개인균등 254
 
7.5%
재산세(건축물 106
 
3.1%
등록면허세(면허 80
 
2.4%
지방소득세(종합소득 22
 
0.7%
주민세(개인사업 15
 
0.4%
취득세(부동산 13
 
0.4%
지방소득세(양도소득 6
 
0.2%
Other values (9) 13
 
0.4%

고지구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size26.5 KiB
미납
2173 
체납
854 
자납
346 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미납 2173
64.4%
체납 854
 
25.3%
자납 346
 
10.3%

Length

2023-12-12T23:49:26.502452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:49:26.660939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미납 2173
64.4%
체납 854
 
25.3%
자납 346
 
10.3%

고지금액
Text

Distinct1916
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Memory size26.5 KiB
2023-12-12T23:49:27.056221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length6.7177587
Min length5

Characters and Unicode

Total characters22659
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

Unique1171 ?
Unique (%)34.7%

Sample

1st row291,330
2nd row283,010
3rd row283,010
4th row194,800
5th row390,530
ValueCountFrequency (%)
11,000 99
 
2.9%
11,330 23
 
0.7%
129,870 16
 
0.5%
2,448,560 14
 
0.4%
109,500 12
 
0.4%
625,080 10
 
0.3%
76,770 9
 
0.3%
242,980 9
 
0.3%
3,120,290 9
 
0.3%
233,410 9
 
0.3%
Other values (1906) 3163
93.8%
2023-12-12T23:49:27.789415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4938
21.8%
, 3487
15.4%
1 2390
10.5%
2 1852
 
8.2%
3 1735
 
7.7%
4 1562
 
6.9%
5 1407
 
6.2%
6 1382
 
6.1%
8 1376
 
6.1%
9 1308
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19172
84.6%
Other Punctuation 3487
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4938
25.8%
1 2390
12.5%
2 1852
 
9.7%
3 1735
 
9.0%
4 1562
 
8.1%
5 1407
 
7.3%
6 1382
 
7.2%
8 1376
 
7.2%
9 1308
 
6.8%
7 1222
 
6.4%
Other Punctuation
ValueCountFrequency (%)
, 3487
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22659
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4938
21.8%
, 3487
15.4%
1 2390
10.5%
2 1852
 
8.2%
3 1735
 
7.7%
4 1562
 
6.9%
5 1407
 
6.2%
6 1382
 
6.1%
8 1376
 
6.1%
9 1308
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22659
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4938
21.8%
, 3487
15.4%
1 2390
10.5%
2 1852
 
8.2%
3 1735
 
7.7%
4 1562
 
6.9%
5 1407
 
6.2%
6 1382
 
6.1%
8 1376
 
6.1%
9 1308
 
5.8%

부과일자
Date

Distinct121
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size26.5 KiB
Minimum2004-10-01 00:00:00
Maximum2019-12-06 00:00:00
2023-12-12T23:49:28.024951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:49:28.610842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

징수일자
Date

MISSING 

Distinct82
Distinct (%)2.7%
Missing347
Missing (%)10.3%
Memory size26.5 KiB
Minimum2004-10-01 00:00:00
Maximum2019-12-11 00:00:00
2023-12-12T23:49:28.943356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:49:29.296830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수납형태(현금/카드)
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size26.5 KiB
카드결제
3334 
휴대폰결제
 
39

Length

Max length5
Median length4
Mean length4.0115624
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
카드결제 3334
98.8%
휴대폰결제 39
 
1.2%

Length

2023-12-12T23:49:29.616232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:49:30.007640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
카드결제 3334
98.8%
휴대폰결제 39
 
1.2%

선택납부
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size26.5 KiB
X
3354 
O
 
19

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
X 3354
99.4%
O 19
 
0.6%

Length

2023-12-12T23:49:30.377718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:49:30.639291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 3354
99.4%
o 19
 
0.6%

Correlations

2023-12-12T23:49:30.770540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명고지구분징수일자수납형태(현금/카드)선택납부
세목명1.0000.5090.9840.1030.132
고지구분0.5091.0000.8270.0640.040
징수일자0.9840.8271.0000.2840.292
수납형태(현금/카드)0.1030.0640.2841.0000.000
선택납부0.1320.0400.2920.0001.000
2023-12-12T23:49:31.011573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
선택납부고지구분수납형태(현금/카드)세목명
선택납부1.0000.0670.0000.116
고지구분0.0671.0000.1070.315
수납형태(현금/카드)0.0000.1071.0000.091
세목명0.1160.3150.0911.000
2023-12-12T23:49:31.252359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명고지구분수납형태(현금/카드)선택납부
세목명1.0000.3150.0910.116
고지구분0.3151.0000.1070.067
수납형태(현금/카드)0.0910.1071.0000.000
선택납부0.1160.0670.0001.000

Missing values

2023-12-12T23:49:25.979105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:49:26.160266image/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

세목명고지구분고지금액부과일자징수일자수납형태(현금/카드)선택납부
0자동차세(자동차)미납291,3302019-12-062019-12-06카드결제X
1자동차세(자동차)미납283,0102019-12-062019-12-06카드결제X
2자동차세(자동차)미납283,0102019-12-062019-12-06카드결제X
3자동차세(자동차)미납194,8002019-12-062019-12-06카드결제X
4자동차세(자동차)미납390,5302019-12-062019-12-06카드결제X
5자동차세(자동차)미납390,5302019-12-062019-12-06카드결제X
6자동차세(자동차)미납168,5702019-12-062019-12-06카드결제X
7자동차세(자동차)미납81,5102019-12-062019-12-06카드결제X
8자동차세(자동차)미납194,5002019-12-062019-12-06카드결제X
9자동차세(자동차)미납72,3802019-12-062019-12-06카드결제X
세목명고지구분고지금액부과일자징수일자수납형태(현금/카드)선택납부
3363자동차세(자동차)체납424,3302018-12-072018-12-07카드결제X
3364자동차세(자동차)체납264,9902018-12-072018-12-07카드결제X
3365자동차세(자동차)체납136,9302018-12-072018-12-07카드결제X
3366자동차세(자동차)체납200,7202018-12-072018-12-07카드결제X
3367자동차세(자동차)체납326,6202018-12-072018-12-07카드결제X
3368자동차세(자동차)체납326,6202018-12-072018-12-07카드결제X
3369자동차세(자동차)체납326,6202018-12-072018-12-07카드결제X
3370자동차세(자동차)체납335,0602018-12-072018-12-07카드결제X
3371자동차세(자동차)체납335,0602018-12-072018-12-07카드결제X
3372자동차세(자동차)체납237,7102018-12-072018-12-07카드결제X

Duplicate rows

Most frequently occurring

세목명고지구분고지금액부과일자징수일자수납형태(현금/카드)선택납부# duplicates
462주민세(개인균등)미납11,0002019-08-062019-08-07카드결제X88
466주민세(개인균등)체납11,3302019-08-062019-08-07카드결제X15
8등록면허세(면허)자납109,5002019-01-07<NA>카드결제X12
26자동차세(자동차)미납129,8702019-12-062019-12-06카드결제X9
0등록면허세(면허)미납15,0002019-01-092019-01-09카드결제X7
243자동차세(자동차)자납232,9402019-01-08<NA>카드결제X7
25자동차세(자동차)미납129,8702019-06-052019-06-05카드결제X6
100자동차세(자동차)미납233,4102019-12-062019-12-06카드결제X6
221자동차세(자동차)미납543,8402019-06-052019-06-05카드결제X6
461주민세(개인균등)미납10,8502019-08-062019-08-07카드결제X6