Overview

Dataset statistics

Number of variables10
Number of observations74
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory86.8 B

Variable types

Categorical6
Boolean1
Numeric3

Dataset

Description대구광역시 북구_지방세 납부 현황_20181231
Author대구광역시 북구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15078494&dataSetDetailId=150784941c34037c6525e&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 (10.8%) zerosZeros

Reproduction

Analysis started2024-04-19 06:13:31.472516
Analysis finished2024-04-19 06:13:32.914371
Duration1.44 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size724.0 B
대구광역시
74 

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 74
100.0%

Length

2024-04-19T15:13:33.289260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:13:33.383617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 74
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size724.0 B
북구
74 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
북구 74
100.0%

Length

2024-04-19T15:13:33.496195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:13:33.597026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
북구 74
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size724.0 B
27230
74 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row27230
2nd row27230
3rd row27230
4th row27230
5th row27230

Common Values

ValueCountFrequency (%)
27230 74
100.0%

Length

2024-04-19T15:13:33.714197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:13:33.863605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
27230 74
100.0%

납부년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size724.0 B
2018
74 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 74
100.0%

Length

2024-04-19T15:13:33.968375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:13:34.069206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 74
100.0%

세목명
Categorical

Distinct11
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size724.0 B
등록면허세
9 
자동차세
9 
재산세
9 
주민세
9 
지방소득세
8 
Other values (6)
30 

Length

Max length7
Median length6
Mean length4.0135135
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
등록면허세 9
12.2%
자동차세 9
12.2%
재산세 9
12.2%
주민세 9
12.2%
지방소득세 8
10.8%
취득세 8
10.8%
면허세 6
8.1%
지역자원시설세 6
8.1%
등록세 5
6.8%
종합토지세 3
 
4.1%

Length

2024-04-19T15:13:34.185583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록면허세 9
12.2%
자동차세 9
12.2%
재산세 9
12.2%
주민세 9
12.2%
지방소득세 8
10.8%
취득세 8
10.8%
면허세 6
8.1%
지역자원시설세 6
8.1%
등록세 5
6.8%
종합토지세 3
 
4.1%

납부매체
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size724.0 B
인터넷지로
15 
가상계좌
11 
자동화기기
10 
기타
9 
위택스
9 
Other values (3)
20 

Length

Max length5
Median length4
Mean length4.0675676
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인터넷지로 15
20.3%
가상계좌 11
14.9%
자동화기기 10
13.5%
기타 9
12.2%
위택스 9
12.2%
은행창구 9
12.2%
지자체방문 7
9.5%
자동이체 4
 
5.4%

Length

2024-04-19T15:13:34.327502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:13:34.452209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인터넷지로 15
20.3%
가상계좌 11
14.9%
자동화기기 10
13.5%
기타 9
12.2%
위택스 9
12.2%
은행창구 9
12.2%
지자체방문 7
9.5%
자동이체 4
 
5.4%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size206.0 B
False
41 
True
33 
ValueCountFrequency (%)
False 41
55.4%
True 33
44.6%
2024-04-19T15:13:34.585337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15380.581
Minimum1
Maximum155302
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-19T15:13:34.696798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.65
Q127.5
median1491.5
Q316858.5
95-th percentile80445.95
Maximum155302
Range155301
Interquartile range (IQR)16831

Descriptive statistics

Standard deviation30002.977
Coefficient of variation (CV)1.9507051
Kurtosis10.007757
Mean15380.581
Median Absolute Deviation (MAD)1490.5
Skewness3.0548736
Sum1138163
Variance9.0017865 × 108
MonotonicityNot monotonic
2024-04-19T15:13:34.839977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 4
 
5.4%
2 3
 
4.1%
7 2
 
2.7%
35819 1
 
1.4%
2898 1
 
1.4%
37133 1
 
1.4%
17215 1
 
1.4%
1409 1
 
1.4%
951 1
 
1.4%
17 1
 
1.4%
Other values (58) 58
78.4%
ValueCountFrequency (%)
1 4
5.4%
2 3
4.1%
3 1
 
1.4%
5 1
 
1.4%
7 2
2.7%
14 1
 
1.4%
15 1
 
1.4%
16 1
 
1.4%
17 1
 
1.4%
20 1
 
1.4%
ValueCountFrequency (%)
155302 1
1.4%
135771 1
1.4%
104488 1
1.4%
97435 1
1.4%
71298 1
1.4%
45845 1
1.4%
37445 1
1.4%
37133 1
1.4%
37125 1
1.4%
35819 1
1.4%

납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5795891 × 109
Minimum4840
Maximum5.197196 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-19T15:13:34.994190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4840
5-th percentile61434
Q14175362.5
median2.5537833 × 108
Q33.6053205 × 109
95-th percentile2.2712731 × 1010
Maximum5.197196 × 1010
Range5.1971956 × 1010
Interquartile range (IQR)3.6011451 × 109

Descriptive statistics

Standard deviation9.8189458 × 109
Coefficient of variation (CV)2.144067
Kurtosis12.704719
Mean4.5795891 × 109
Median Absolute Deviation (MAD)2.5537155 × 108
Skewness3.3607047
Sum3.3888959 × 1011
Variance9.6411696 × 1019
MonotonicityNot monotonic
2024-04-19T15:13:35.132767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
930977680 1
 
1.4%
249250600 1
 
1.4%
2455617630 1
 
1.4%
38670700 1
 
1.4%
1900397220 1
 
1.4%
252250 1
 
1.4%
492450 1
 
1.4%
2059045790 1
 
1.4%
215920 1
 
1.4%
546481360 1
 
1.4%
Other values (64) 64
86.5%
ValueCountFrequency (%)
4840 1
1.4%
8720 1
1.4%
28350 1
1.4%
37800 1
1.4%
74160 1
1.4%
130670 1
1.4%
213600 1
1.4%
215920 1
1.4%
245700 1
1.4%
252250 1
1.4%
ValueCountFrequency (%)
51971960490 1
1.4%
50111103200 1
1.4%
26759969910 1
1.4%
23523212420 1
1.4%
22276318210 1
1.4%
17315832110 1
1.4%
16042409900 1
1.4%
15555853590 1
1.4%
12740755280 1
1.4%
10941275770 1
1.4%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct55
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.810676
Minimum0
Maximum86.75
Zeros8
Zeros (%)10.8%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-04-19T15:13:35.266701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0325
median2.925
Q316.905
95-th percentile36.829
Maximum86.75
Range86.75
Interquartile range (IQR)16.8725

Descriptive statistics

Standard deviation15.772898
Coefficient of variation (CV)1.4590113
Kurtosis6.677159
Mean10.810676
Median Absolute Deviation (MAD)2.925
Skewness2.2177427
Sum799.99
Variance248.78431
MonotonicityNot monotonic
2024-04-19T15:13:35.409369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8
 
10.8%
0.01 5
 
6.8%
0.02 3
 
4.1%
0.03 3
 
4.1%
0.04 3
 
4.1%
0.08 2
 
2.7%
15.48 2
 
2.7%
7.84 1
 
1.4%
24.48 1
 
1.4%
2.0 1
 
1.4%
Other values (45) 45
60.8%
ValueCountFrequency (%)
0.0 8
10.8%
0.01 5
6.8%
0.02 3
 
4.1%
0.03 3
 
4.1%
0.04 3
 
4.1%
0.06 1
 
1.4%
0.07 1
 
1.4%
0.08 2
 
2.7%
0.1 1
 
1.4%
0.14 1
 
1.4%
ValueCountFrequency (%)
86.75 1
1.4%
52.81 1
1.4%
46.69 1
1.4%
37.05 1
1.4%
36.71 1
1.4%
35.28 1
1.4%
33.98 1
1.4%
31.4 1
1.4%
31.21 1
1.4%
30.24 1
1.4%

Interactions

2024-04-19T15:13:32.402004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:13:31.727492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:13:32.036193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:13:32.503462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:13:31.851473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:13:32.162464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:13:32.584117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:13:31.946952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:13:32.293165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T15:13:35.508516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
세목명1.0000.0000.0000.0000.2590.475
납부매체0.0001.0000.9830.1810.0000.517
납부매체전자고지여부0.0000.9831.0000.0000.1490.404
납부건수0.0000.1810.0001.0000.9200.651
납부금액0.2590.0000.1490.9201.0000.511
납부매체비율0.4750.5170.4040.6510.5111.000
2024-04-19T15:13:35.607792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부매체전자고지여부세목명납부매체
납부매체전자고지여부1.0000.0000.847
세목명0.0001.0000.000
납부매체0.8470.0001.000
2024-04-19T15:13:35.701936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율세목명납부매체납부매체전자고지여부
납부건수1.0000.9080.9180.0000.0890.000
납부금액0.9081.0000.8420.1290.0000.140
납부매체비율0.9180.8421.0000.2370.1910.289
세목명0.0000.1290.2371.0000.0000.000
납부매체0.0890.0000.1910.0001.0000.847
납부매체전자고지여부0.0000.1400.2890.0000.8471.000

Missing values

2024-04-19T15:13:32.710469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T15:13:32.860144image/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
0대구광역시북구272302018등록면허세가상계좌Y358199309776807.84
1대구광역시북구272302018등록세가상계좌Y2340732800.01
2대구광역시북구272302018면허세가상계좌Y15334797600.03
3대구광역시북구272302018사업소세가상계좌Y148400.0
4대구광역시북구272302018자동차세가상계좌Y1553022352321242033.98
5대구광역시북구272302018재산세가상계좌Y1357712675996991029.71
6대구광역시북구272302018종합토지세가상계좌Y2611297100.01
7대구광역시북구272302018주민세가상계좌Y97435289544483021.32
8대구광역시북구272302018지방소득세가상계좌Y28832160424099006.31
9대구광역시북구272302018지역자원시설세가상계좌Y274229176600.06
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
64대구광역시북구272302018지방소득세자동화기기N1038273985650603.51
65대구광역시북구272302018지역자원시설세자동화기기N251358646400.08
66대구광역시북구272302018취득세자동화기기N315785197196049010.66
67대구광역시북구272302018등록면허세지자체방문N227211520601.82
68대구광역시북구272302018자동차세지자체방문N5812113990213046.69
69대구광역시북구272302018재산세지자체방문N461271830429037.05
70대구광역시북구272302018주민세지자체방문N15742935784012.64
71대구광역시북구272302018지방소득세지자체방문N75672424900.6
72대구광역시북구272302018지역자원시설세지자체방문N187200.01
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