Overview

Dataset statistics

Number of variables10
Number of observations82
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory86.6 B

Variable types

Categorical6
Boolean1
Numeric3

Dataset

Description대구광역시 달서구_지방세 납부 현황_20201231
Author대구광역시 달서구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15079362&dataSetDetailId=150793621a18c1c182341&provdMethod=FILE

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
납부년도 has constant value ""Constant
납부건수 is highly overall correlated with 납부금액 and 1 other fieldsHigh correlation
납부금액 is highly overall correlated with 납부건수 and 1 other fieldsHigh correlation
납부매체비율 is highly overall correlated with 납부건수 and 1 other fieldsHigh correlation
납부매체 is highly overall correlated with 납부매체전자고지여부High correlation
납부매체전자고지여부 is highly overall correlated with 납부매체High correlation
납부금액 has unique valuesUnique
납부매체비율 has 8 (9.8%) zerosZeros

Reproduction

Analysis started2023-12-10 20:09:16.379354
Analysis finished2023-12-10 20:09:21.105402
Duration4.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
대구광역시
82 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 82
100.0%

Length

2023-12-11T05:09:21.288908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:21.459270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 82
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
달서구
82 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
달서구 82
100.0%

Length

2023-12-11T05:09:21.601031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:21.743319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
달서구 82
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
27290
82 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row27290
2nd row27290
3rd row27290
4th row27290
5th row27290

Common Values

ValueCountFrequency (%)
27290 82
100.0%

Length

2023-12-11T05:09:22.289028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:22.465193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
27290 82
100.0%

납부년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
2020
82 

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 82
100.0%

Length

2023-12-11T05:09:22.617012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:22.790564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 82
100.0%

세목명
Categorical

Distinct13
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size788.0 B
등록면허세
10 
자동차세
10 
재산세
10 
주민세
10 
지방소득세
9 
Other values (8)
33 

Length

Max length7
Median length5
Mean length4.0487805
Min length3

Unique

Unique2 ?
Unique (%)2.4%

Sample

1st row등록면허세
2nd row등록세
3rd row면허세
4th row사업소세
5th row자동차세

Common Values

ValueCountFrequency (%)
등록면허세 10
12.2%
자동차세 10
12.2%
재산세 10
12.2%
주민세 10
12.2%
지방소득세 9
11.0%
취득세 9
11.0%
지역자원시설세 6
7.3%
등록세 5
6.1%
면허세 5
6.1%
종합토지세 4
 
4.9%
Other values (3) 4
 
4.9%

Length

2023-12-11T05:09:22.992964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록면허세 10
12.2%
자동차세 10
12.2%
재산세 10
12.2%
주민세 10
12.2%
지방소득세 9
11.0%
취득세 9
11.0%
지역자원시설세 6
7.3%
등록세 5
6.1%
면허세 5
6.1%
종합토지세 4
 
4.9%
Other values (3) 4
 
4.9%

납부매체
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size788.0 B
인터넷지로
13 
가상계좌
11 
기타
11 
자동화기기
11 
은행창구
10 
Other values (4)
26 

Length

Max length5
Median length4
Mean length4.0731707
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인터넷지로 13
15.9%
가상계좌 11
13.4%
기타 11
13.4%
자동화기기 11
13.4%
은행창구 10
12.2%
위택스 9
11.0%
지자체방문 7
8.5%
페이사납부 6
7.3%
자동이체 4
 
4.9%

Length

2023-12-11T05:09:23.255290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:09:23.459554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인터넷지로 13
15.9%
가상계좌 11
13.4%
기타 11
13.4%
자동화기기 11
13.4%
은행창구 10
12.2%
위택스 9
11.0%
지자체방문 7
8.5%
페이사납부 6
7.3%
자동이체 4
 
4.9%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size214.0 B
False
45 
True
37 
ValueCountFrequency (%)
False 45
54.9%
True 37
45.1%
2023-12-11T05:09:23.650896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18303.049
Minimum1
Maximum239441
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-11T05:09:23.854105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q129.5
median1737
Q315872.25
95-th percentile74185.2
Maximum239441
Range239440
Interquartile range (IQR)15842.75

Descriptive statistics

Standard deviation39708.409
Coefficient of variation (CV)2.169497
Kurtosis15.309821
Mean18303.049
Median Absolute Deviation (MAD)1733
Skewness3.6214978
Sum1500850
Variance1.5767578 × 109
MonotonicityNot monotonic
2023-12-11T05:09:24.072104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 4
 
4.9%
12 2
 
2.4%
4 2
 
2.4%
6 2
 
2.4%
27 2
 
2.4%
13 2
 
2.4%
45798 1
 
1.2%
23955 1
 
1.2%
31 1
 
1.2%
44191 1
 
1.2%
Other values (64) 64
78.0%
ValueCountFrequency (%)
1 1
 
1.2%
2 4
4.9%
4 2
2.4%
6 2
2.4%
8 1
 
1.2%
9 1
 
1.2%
10 1
 
1.2%
12 2
2.4%
13 2
2.4%
21 1
 
1.2%
ValueCountFrequency (%)
239441 1
1.2%
189094 1
1.2%
115944 1
1.2%
111654 1
1.2%
74438 1
1.2%
69382 1
1.2%
68171 1
1.2%
63420 1
1.2%
55456 1
1.2%
45798 1
1.2%

납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.7526582 × 109
Minimum37130
Maximum1.4508357 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-11T05:09:24.293007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37130
5-th percentile162684
Q18542127.5
median2.2500489 × 108
Q34.6152206 × 109
95-th percentile3.3681928 × 1010
Maximum1.4508357 × 1011
Range1.4508353 × 1011
Interquartile range (IQR)4.6066785 × 109

Descriptive statistics

Standard deviation2.0962323 × 1010
Coefficient of variation (CV)2.7038885
Kurtosis26.710095
Mean7.7526582 × 109
Median Absolute Deviation (MAD)2.2493199 × 108
Skewness4.8144052
Sum6.3571797 × 1011
Variance4.39419 × 1020
MonotonicityNot monotonic
2023-12-11T05:09:24.469851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1321283390 1
 
1.2%
12074310530 1
 
1.2%
99470 1
 
1.2%
22733570 1
 
1.2%
2699421320 1
 
1.2%
244960300 1
 
1.2%
9621754100 1
 
1.2%
3536544420 1
 
1.2%
57260500 1
 
1.2%
3777654710 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
37130 1
1.2%
46330 1
1.2%
99470 1
1.2%
136020 1
1.2%
161160 1
1.2%
191640 1
1.2%
202670 1
1.2%
234810 1
1.2%
408430 1
1.2%
482190 1
1.2%
ValueCountFrequency (%)
145083570800 1
1.2%
99760778420 1
1.2%
51068135400 1
1.2%
40123521470 1
1.2%
33785459800 1
1.2%
31714827160 1
1.2%
28265577220 1
1.2%
18241538790 1
1.2%
17979766370 1
1.2%
16394122120 1
1.2%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct63
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.975488
Minimum0
Maximum68.62
Zeros8
Zeros (%)9.8%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-11T05:09:24.645856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.03
median4.265
Q316.9225
95-th percentile36.026
Maximum68.62
Range68.62
Interquartile range (IQR)16.8925

Descriptive statistics

Standard deviation14.625506
Coefficient of variation (CV)1.3325609
Kurtosis2.6218559
Mean10.975488
Median Absolute Deviation (MAD)4.265
Skewness1.6328218
Sum899.99
Variance213.90542
MonotonicityNot monotonic
2023-12-11T05:09:24.839175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8
 
9.8%
0.01 6
 
7.3%
0.02 4
 
4.9%
0.03 4
 
4.9%
0.19 2
 
2.4%
19.67 1
 
1.2%
13.59 1
 
1.2%
33.23 1
 
1.2%
22.15 1
 
1.2%
13.15 1
 
1.2%
Other values (53) 53
64.6%
ValueCountFrequency (%)
0.0 8
9.8%
0.01 6
7.3%
0.02 4
4.9%
0.03 4
4.9%
0.04 1
 
1.2%
0.05 1
 
1.2%
0.06 1
 
1.2%
0.09 1
 
1.2%
0.19 2
 
2.4%
0.21 1
 
1.2%
ValueCountFrequency (%)
68.62 1
1.2%
54.72 1
1.2%
46.01 1
1.2%
38.88 1
1.2%
36.04 1
1.2%
35.76 1
1.2%
34.22 1
1.2%
33.38 1
1.2%
33.23 1
1.2%
32.46 1
1.2%

Interactions

2023-12-11T05:09:19.800042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:09:18.544513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:09:19.109434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:09:20.113125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:09:18.780149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:09:19.302380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:09:20.406482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:09:18.940108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:09:19.541315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T05:09:24.940692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
세목명1.0000.0000.0000.0000.0000.374
납부매체0.0001.0000.8730.1380.2680.389
납부매체전자고지여부0.0000.8731.0000.1740.0000.088
납부건수0.0000.1380.1741.0000.7300.647
납부금액0.0000.2680.0000.7301.0000.000
납부매체비율0.3740.3890.0880.6470.0001.000
2023-12-11T05:09:25.056355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부매체세목명납부매체전자고지여부
납부매체1.0000.0000.867
세목명0.0001.0000.000
납부매체전자고지여부0.8670.0001.000
2023-12-11T05:09:25.184730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율세목명납부매체납부매체전자고지여부
납부건수1.0000.8840.8870.0000.0620.178
납부금액0.8841.0000.7750.0000.1330.000
납부매체비율0.8870.7751.0000.1600.1280.077
세목명0.0000.0000.1601.0000.0000.000
납부매체0.0620.1330.1280.0001.0000.867
납부매체전자고지여부0.1780.0000.0770.0000.8671.000

Missing values

2023-12-11T05:09:20.628707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T05:09:20.954600image/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

시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
0대구광역시달서구272902020등록면허세가상계좌Y4579813212833906.89
1대구광역시달서구272902020등록세가상계좌Y1243881200.0
2대구광역시달서구272902020면허세가상계좌Y8718085900.01
3대구광역시달서구272902020사업소세가상계좌Y21360200.0
4대구광역시달서구272902020자동차세가상계좌Y2394414012352147036.04
5대구광역시달서구272902020재산세가상계좌Y1890945106813540028.46
6대구광역시달서구272902020종합토지세가상계좌Y2982827200.0
7대구광역시달서구272902020주민세가상계좌Y115944463071760017.45
8대구광역시달서구272902020지방소득세가상계좌Y693823171482716010.44
9대구광역시달서구272902020지역자원시설세가상계좌Y175301473200.03
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
72대구광역시달서구272902020재산세지자체방문N304058297215031.05
73대구광역시달서구272902020주민세지자체방문N12492342102012.76
74대구광역시달서구272902020지방소득세지자체방문N2761075932302.82
75대구광역시달서구272902020취득세지자체방문N42710853672004.36
76대구광역시달서구272902020등록면허세페이사납부Y414122172702.98
77대구광역시달서구272902020자동차세페이사납부Y539893246059038.88
78대구광역시달서구272902020재산세페이사납부Y475178200230034.22
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