Overview

Dataset statistics

Number of variables10
Number of observations79
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory87.6 B

Variable types

Categorical6
Numeric4

Dataset

Description대구광역시 동구_지방세 체납 현황_20220714
Author대구광역시 동구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15078598&dataSetDetailId=150785981dc3ae63ce982&provdMethod=FILE

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
체납건수 is highly overall correlated with 체납금액 and 2 other fieldsHigh correlation
체납금액 is highly overall correlated with 체납건수 and 2 other fieldsHigh correlation
누적체납건수 is highly overall correlated with 체납건수 and 2 other fieldsHigh correlation
누적체납금액 is highly overall correlated with 체납건수 and 2 other fieldsHigh correlation
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2024-04-21 15:09:44.156729
Analysis finished2024-04-21 15:09:49.663665
Duration5.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size760.0 B
대구광역시
79 

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 79
100.0%

Length

2024-04-22T00:09:49.853498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T00:09:50.152946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 79
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size760.0 B
동구
79 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동구 79
100.0%

Length

2024-04-22T00:09:50.467685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T00:09:50.766814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동구 79
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size760.0 B
27140
79 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row27140
2nd row27140
3rd row27140
4th row27140
5th row27140

Common Values

ValueCountFrequency (%)
27140 79
100.0%

Length

2024-04-22T00:09:51.079204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T00:09:51.379391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
27140 79
100.0%

과세년도
Categorical

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size760.0 B
2021
40 
2020
39 

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 (%)
2021 40
50.6%
2020 39
49.4%

Length

2024-04-22T00:09:51.687462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T00:09:51.996574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 40
50.6%
2020 39
49.4%

세목명
Categorical

Distinct7
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size760.0 B
지방소득세
19 
재산세
17 
취득세
16 
주민세
9 
자동차세
8 
Other values (2)
10 

Length

Max length7
Median length3
Mean length4.0379747
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row등록면허세
2nd row자동차세
3rd row자동차세
4th row자동차세
5th row자동차세

Common Values

ValueCountFrequency (%)
지방소득세 19
24.1%
재산세 17
21.5%
취득세 16
20.3%
주민세 9
11.4%
자동차세 8
10.1%
지역자원시설세 8
10.1%
등록면허세 2
 
2.5%

Length

2024-04-22T00:09:52.369080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T00:09:52.740567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 19
24.1%
재산세 17
21.5%
취득세 16
20.3%
주민세 9
11.4%
자동차세 8
10.1%
지역자원시설세 8
10.1%
등록면허세 2
 
2.5%

체납액구간
Categorical

Distinct11
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size760.0 B
10만원 미만
14 
30만원~50만원미만
12 
50만원~1백만원미만
12 
10만원~30만원미만
11 
1백만원~3백만원미만
8 
Other values (6)
22 

Length

Max length11
Median length11
Mean length10.253165
Min length7

Unique

Unique2 ?
Unique (%)2.5%

Sample

1st row10만원 미만
2nd row10만원 미만
3rd row10만원~30만원미만
4th row30만원~50만원미만
5th row50만원~1백만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 14
17.7%
30만원~50만원미만 12
15.2%
50만원~1백만원미만 12
15.2%
10만원~30만원미만 11
13.9%
1백만원~3백만원미만 8
10.1%
3백만원~5백만원미만 6
7.6%
5백만원~1천만원미만 6
7.6%
1천만원~3천만원미만 5
 
6.3%
3천만원~5천만원미만 3
 
3.8%
1억원~3억원미만 1
 
1.3%

Length

2024-04-22T00:09:53.142620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 14
15.1%
미만 14
15.1%
30만원~50만원미만 12
12.9%
50만원~1백만원미만 12
12.9%
10만원~30만원미만 11
11.8%
1백만원~3백만원미만 8
8.6%
3백만원~5백만원미만 6
6.5%
5백만원~1천만원미만 6
6.5%
1천만원~3천만원미만 5
 
5.4%
3천만원~5천만원미만 3
 
3.2%
Other values (2) 2
 
2.2%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)65.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean883.83544
Minimum1
Maximum15148
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size839.0 B
2024-04-22T00:09:53.379097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median15
Q3166.5
95-th percentile4063
Maximum15148
Range15147
Interquartile range (IQR)162.5

Descriptive statistics

Standard deviation2555.238
Coefficient of variation (CV)2.891079
Kurtosis18.166839
Mean883.83544
Median Absolute Deviation (MAD)14
Skewness4.0840545
Sum69823
Variance6529241.5
MonotonicityNot monotonic
2024-04-22T00:09:53.635559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 13
 
16.5%
6 4
 
5.1%
2 3
 
3.8%
4 3
 
3.8%
3 3
 
3.8%
15 3
 
3.8%
10 3
 
3.8%
17 2
 
2.5%
45 2
 
2.5%
11 1
 
1.3%
Other values (42) 42
53.2%
ValueCountFrequency (%)
1 13
16.5%
2 3
 
3.8%
3 3
 
3.8%
4 3
 
3.8%
5 1
 
1.3%
6 4
 
5.1%
7 1
 
1.3%
8 1
 
1.3%
9 1
 
1.3%
10 3
 
3.8%
ValueCountFrequency (%)
15148 1
1.3%
12891 1
1.3%
7185 1
1.3%
7105 1
1.3%
3725 1
1.3%
3621 1
1.3%
3543 1
1.3%
3486 1
1.3%
2847 1
1.3%
2836 1
1.3%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84371353
Minimum273090
Maximum6.1667283 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size839.0 B
2024-04-22T00:09:53.898719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum273090
5-th percentile492289
Q13704680
median42316760
Q31.0139854 × 108
95-th percentile3.3710554 × 108
Maximum6.1667283 × 108
Range6.1639974 × 108
Interquartile range (IQR)97693855

Descriptive statistics

Standard deviation1.2817089 × 108
Coefficient of variation (CV)1.5191281
Kurtosis7.7058591
Mean84371353
Median Absolute Deviation (MAD)39849360
Skewness2.6859112
Sum6.6653369 × 109
Variance1.6427777 × 1016
MonotonicityNot monotonic
2024-04-22T00:09:54.152377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33744990 1
 
1.3%
164122000 1
 
1.3%
31455310 1
 
1.3%
3485660 1
 
1.3%
2467400 1
 
1.3%
4101220 1
 
1.3%
10460740 1
 
1.3%
232570730 1
 
1.3%
111870980 1
 
1.3%
101437770 1
 
1.3%
Other values (69) 69
87.3%
ValueCountFrequency (%)
273090 1
1.3%
283110 1
1.3%
376350 1
1.3%
462490 1
1.3%
495600 1
1.3%
687000 1
1.3%
797490 1
1.3%
863860 1
1.3%
1046100 1
1.3%
1546540 1
1.3%
ValueCountFrequency (%)
616672830 1
1.3%
604642460 1
1.3%
482585120 1
1.3%
480680050 1
1.3%
321152820 1
1.3%
303204370 1
1.3%
232570730 1
1.3%
175146730 1
1.3%
166826130 1
1.3%
166105600 1
1.3%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct58
Distinct (%)73.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1987.8608
Minimum1
Maximum36052
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size839.0 B
2024-04-22T00:09:54.403342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q18.5
median24
Q3290
95-th percentile10618.6
Maximum36052
Range36051
Interquartile range (IQR)281.5

Descriptive statistics

Standard deviation5974.3347
Coefficient of variation (CV)3.005409
Kurtosis19.173831
Mean1987.8608
Median Absolute Deviation (MAD)23
Skewness4.1873375
Sum157041
Variance35692675
MonotonicityNot monotonic
2024-04-22T00:09:54.657249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 9
 
11.4%
14 3
 
3.8%
3 3
 
3.8%
11 3
 
3.8%
2 3
 
3.8%
16 2
 
2.5%
9 2
 
2.5%
4 2
 
2.5%
26 2
 
2.5%
12 2
 
2.5%
Other values (48) 48
60.8%
ValueCountFrequency (%)
1 9
11.4%
2 3
 
3.8%
3 3
 
3.8%
4 2
 
2.5%
6 1
 
1.3%
7 1
 
1.3%
8 1
 
1.3%
9 2
 
2.5%
10 1
 
1.3%
11 3
 
3.8%
ValueCountFrequency (%)
36052 1
1.3%
30103 1
1.3%
16382 1
1.3%
14233 1
1.3%
10217 1
1.3%
9807 1
1.3%
9725 1
1.3%
8376 1
1.3%
4117 1
1.3%
3726 1
1.3%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4830041 × 108
Minimum315650
Maximum1.6318164 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size839.0 B
2024-04-22T00:09:54.914413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum315650
5-th percentile664549
Q18783735
median71171140
Q31.345283 × 108
95-th percentile5.9232431 × 108
Maximum1.6318164 × 109
Range1.6315008 × 109
Interquartile range (IQR)1.2574457 × 108

Descriptive statistics

Standard deviation2.7513719 × 108
Coefficient of variation (CV)1.8552692
Kurtosis15.665092
Mean1.4830041 × 108
Median Absolute Deviation (MAD)63073860
Skewness3.6722576
Sum1.1715732 × 1010
Variance7.5700471 × 1016
MonotonicityNot monotonic
2024-04-22T00:09:55.180538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69015400 1
 
1.3%
430396800 1
 
1.3%
71171140 1
 
1.3%
5767900 1
 
1.3%
4078590 1
 
1.3%
4101220 1
 
1.3%
18847090 1
 
1.3%
563628230 1
 
1.3%
153065570 1
 
1.3%
157465260 1
 
1.3%
Other values (69) 69
87.3%
ValueCountFrequency (%)
315650 1
1.3%
321520 1
1.3%
376350 1
1.3%
462490 1
1.3%
687000 1
1.3%
1046100 1
1.3%
1620400 1
1.3%
1779370 1
1.3%
1865840 1
1.3%
3026370 1
1.3%
ValueCountFrequency (%)
1631816400 1
1.3%
1426283420 1
1.3%
689447270 1
1.3%
613963730 1
1.3%
589919930 1
1.3%
563628230 1
1.3%
548373640 1
1.3%
462286170 1
1.3%
443429230 1
1.3%
430396800 1
1.3%

Interactions

2024-04-22T00:09:47.651091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:44.564575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:45.594792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:46.616719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:47.911335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:44.819687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:45.849487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:46.873954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:48.170311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:45.071488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:46.095442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:47.128570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:48.434017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:45.329241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:46.351869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T00:09:47.382661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-22T00:09:55.369226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.0000.4960.5070.6420.487
체납액구간0.0000.0001.0000.0000.0000.0000.210
체납건수0.0000.4960.0001.0000.9361.0000.833
체납금액0.0000.5070.0000.9361.0000.9510.862
누적체납건수0.0000.6420.0001.0000.9511.0000.934
누적체납금액0.0000.4870.2100.8330.8620.9341.000
2024-04-22T00:09:55.631275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도체납액구간세목명
과세년도1.0000.0000.000
체납액구간0.0001.0000.000
세목명0.0000.0001.000
2024-04-22T00:09:55.886209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.6220.9870.6920.0000.3190.000
체납금액0.6221.0000.5560.9810.0000.3010.000
누적체납건수0.9870.5561.0000.6450.0000.2690.000
누적체납금액0.6920.9810.6451.0000.0000.1890.071
과세년도0.0000.0000.0000.0001.0000.0000.000
세목명0.3190.3010.2690.1890.0001.0000.000
체납액구간0.0000.0000.0000.0710.0000.0001.000

Missing values

2024-04-22T00:09:49.017295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-22T00:09:49.482051image/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

시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
0대구광역시동구271402020등록면허세10만원 미만97133744990202869015400
1대구광역시동구271402020자동차세10만원 미만37251641220009807430396800
2대구광역시동구271402020자동차세10만원~30만원미만354361667283097251631816400
3대구광역시동구271402020자동차세30만원~50만원미만18464311050349122286020
4대구광역시동구271402020자동차세50만원~1백만원미만634616801710300930
5대구광역시동구271402020재산세10만원 미만718532115282014233548373640
6대구광역시동구271402020재산세10만원~30만원미만28474825851203726613963730
7대구광역시동구271402020재산세1백만원~3백만원미만7612920909082136513680
8대구광역시동구271402020재산세1천만원~3천만원미만71013593007101359300
9대구광역시동구271402020재산세30만원~50만원미만315119891180375142152890
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
69대구광역시동구271402021지역자원시설세30만원~50만원미만13763501376350
70대구광역시동구271402021지역자원시설세50만원~1백만원미만3224580064507730
71대구광역시동구271402021취득세10만원 미만15797490381865840
72대구광역시동구271402021취득세10만원~30만원미만172912160519470190
73대구광역시동구271402021취득세1백만원~3백만원미만10154603501423447140
74대구광역시동구271402021취득세30만원~50만원미만103923700156002950
75대구광역시동구271402021취득세3백만원~5백만원미만27943900311368810
76대구광역시동구271402021취득세3천만원~5천만원미만135449850135449850
77대구광역시동구271402021취득세50만원~1백만원미만859090601813539300
78대구광역시동구271402021취득세5백만원~1천만원미만17521890427876070