Overview

Dataset statistics

Number of variables10
Number of observations115
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.8 KiB
Average record size in memory87.1 B

Variable types

Categorical6
Numeric4

Dataset

Description3년간(2019~2021) 체납액 규모별 체납 건수를 납세자 유형별로 제공하는 데이터로 구간별 체납건수 및 체납금액과 누적 체납액 등을 제공합니다.
Author전라남도 나주시
URLhttps://www.data.go.kr/data/15079575/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
체납건수 is highly overall correlated with 누적체납건수High correlation
체납금액 is highly overall correlated with 누적체납금액High correlation
누적체납건수 is highly overall correlated with 체납건수High correlation
누적체납금액 is highly overall correlated with 체납금액High correlation
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:46:02.175806
Analysis finished2023-12-12 07:46:04.234515
Duration2.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
전라남도
115 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 115
100.0%

Length

2023-12-12T16:46:04.296773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:46:04.472047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 115
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
나주시
115 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
나주시 115
100.0%

Length

2023-12-12T16:46:04.577450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:46:04.682845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
나주시 115
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
46170
115 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46170
2nd row46170
3rd row46170
4th row46170
5th row46170

Common Values

ValueCountFrequency (%)
46170 115
100.0%

Length

2023-12-12T16:46:04.793676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:46:04.906776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46170 115
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2020
41 
2021
40 
2019
34 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2020 41
35.7%
2021 40
34.8%
2019 34
29.6%

Length

2023-12-12T16:46:05.008903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:46:05.114149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 41
35.7%
2021 40
34.8%
2019 34
29.6%

세목명
Categorical

Distinct7
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
지방소득세
28 
취득세
28 
재산세
27 
주민세
14 
자동차세
12 
Other values (2)
6 

Length

Max length7
Median length3
Mean length3.7130435
Min length3

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 28
24.3%
취득세 28
24.3%
재산세 27
23.5%
주민세 14
12.2%
자동차세 12
10.4%
등록면허세 5
 
4.3%
지역자원시설세 1
 
0.9%

Length

2023-12-12T16:46:05.241985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:46:05.362310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 28
24.3%
취득세 28
24.3%
재산세 27
23.5%
주민세 14
12.2%
자동차세 12
10.4%
등록면허세 5
 
4.3%
지역자원시설세 1
 
0.9%

체납액구간
Categorical

Distinct11
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
10만원 미만
19 
10만원~30만원미만
15 
50만원~1백만원미만
15 
30만원~50만원미만
14 
1백만원~3백만원미만
14 
Other values (6)
38 

Length

Max length11
Median length11
Mean length10.269565
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 19
16.5%
10만원~30만원미만 15
13.0%
50만원~1백만원미만 15
13.0%
30만원~50만원미만 14
12.2%
1백만원~3백만원미만 14
12.2%
1천만원~3천만원미만 9
7.8%
3백만원~5백만원미만 9
7.8%
5백만원~1천만원미만 9
7.8%
3천만원~5천만원미만 5
 
4.3%
5천만원~1억원미만 4
 
3.5%

Length

2023-12-12T16:46:05.520792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 19
14.2%
미만 19
14.2%
10만원~30만원미만 15
11.2%
50만원~1백만원미만 15
11.2%
30만원~50만원미만 14
10.4%
1백만원~3백만원미만 14
10.4%
1천만원~3천만원미만 9
6.7%
3백만원~5백만원미만 9
6.7%
5백만원~1천만원미만 9
6.7%
3천만원~5천만원미만 5
 
3.7%
Other values (2) 6
 
4.5%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct66
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean416.28696
Minimum1
Maximum7390
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:46:05.668930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median14
Q3114
95-th percentile1931.3
Maximum7390
Range7389
Interquartile range (IQR)111

Descriptive statistics

Standard deviation1234.2107
Coefficient of variation (CV)2.9648075
Kurtosis19.412131
Mean416.28696
Median Absolute Deviation (MAD)13
Skewness4.2769889
Sum47873
Variance1523276.1
MonotonicityNot monotonic
2023-12-12T16:46:06.165303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 15
 
13.0%
1 10
 
8.7%
3 7
 
6.1%
5 6
 
5.2%
4 4
 
3.5%
6 4
 
3.5%
10 3
 
2.6%
11 2
 
1.7%
17 2
 
1.7%
14 2
 
1.7%
Other values (56) 60
52.2%
ValueCountFrequency (%)
1 10
8.7%
2 15
13.0%
3 7
6.1%
4 4
 
3.5%
5 6
 
5.2%
6 4
 
3.5%
8 1
 
0.9%
9 2
 
1.7%
10 3
 
2.6%
11 2
 
1.7%
ValueCountFrequency (%)
7390 1
0.9%
7267 1
0.9%
5174 1
0.9%
5142 1
0.9%
2959 1
0.9%
2079 1
0.9%
1868 1
0.9%
1827 1
0.9%
1592 1
0.9%
1553 1
0.9%

체납금액
Real number (ℝ)

HIGH CORRELATION 

Distinct114
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60554613
Minimum3640
Maximum2.8011126 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:46:06.334210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3640
5-th percentile751166
Q16389575
median33890350
Q389969500
95-th percentile2.2026282 × 108
Maximum2.8011126 × 108
Range2.8010762 × 108
Interquartile range (IQR)83579925

Descriptive statistics

Standard deviation69882907
Coefficient of variation (CV)1.1540476
Kurtosis1.2702737
Mean60554613
Median Absolute Deviation (MAD)30252620
Skewness1.4135854
Sum6.9637805 × 109
Variance4.8836207 × 1015
MonotonicityNot monotonic
2023-12-12T16:46:06.498274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1042870 2
 
1.7%
5884650 1
 
0.9%
4097890 1
 
0.9%
97465010 1
 
0.9%
88269450 1
 
0.9%
193639700 1
 
0.9%
230687520 1
 
0.9%
130696740 1
 
0.9%
3637730 1
 
0.9%
30818390 1
 
0.9%
Other values (104) 104
90.4%
ValueCountFrequency (%)
3640 1
0.9%
240360 1
0.9%
340340 1
0.9%
525670 1
0.9%
600890 1
0.9%
718700 1
0.9%
765080 1
0.9%
797800 1
0.9%
1042870 2
1.7%
1381200 1
0.9%
ValueCountFrequency (%)
280111260 1
0.9%
274695020 1
0.9%
243384050 1
0.9%
231285320 1
0.9%
230687520 1
0.9%
229785960 1
0.9%
216181480 1
0.9%
210697810 1
0.9%
208208810 1
0.9%
204647730 1
0.9%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct79
Distinct (%)68.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1007.7739
Minimum1
Maximum16385
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:46:06.708102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median28
Q3223.5
95-th percentile6004.7
Maximum16385
Range16384
Interquartile range (IQR)215.5

Descriptive statistics

Standard deviation2892.664
Coefficient of variation (CV)2.8703501
Kurtosis15.122468
Mean1007.7739
Median Absolute Deviation (MAD)25
Skewness3.8087416
Sum115894
Variance8367504.9
MonotonicityNot monotonic
2023-12-12T16:46:06.870668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 7
 
6.1%
5 5
 
4.3%
1 4
 
3.5%
10 4
 
3.5%
2 4
 
3.5%
3 4
 
3.5%
9 3
 
2.6%
12 3
 
2.6%
6 3
 
2.6%
8 3
 
2.6%
Other values (69) 75
65.2%
ValueCountFrequency (%)
1 4
3.5%
2 4
3.5%
3 4
3.5%
4 7
6.1%
5 5
4.3%
6 3
2.6%
7 1
 
0.9%
8 3
2.6%
9 3
2.6%
10 4
3.5%
ValueCountFrequency (%)
16385 1
0.9%
15900 1
0.9%
12151 1
0.9%
11170 1
0.9%
8995 1
0.9%
6977 1
0.9%
5588 1
0.9%
5165 1
0.9%
4892 1
0.9%
4635 1
0.9%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1451878 × 108
Minimum24850
Maximum8.8901293 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:46:07.055363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24850
5-th percentile2688899
Q114704140
median65047050
Q31.5362445 × 108
95-th percentile3.3434056 × 108
Maximum8.8901293 × 108
Range8.8898808 × 108
Interquartile range (IQR)1.3892031 × 108

Descriptive statistics

Standard deviation1.4483004 × 108
Coefficient of variation (CV)1.2646837
Kurtosis10.900476
Mean1.1451878 × 108
Median Absolute Deviation (MAD)58998700
Skewness2.820929
Sum1.316966 × 1010
Variance2.0975739 × 1016
MonotonicityNot monotonic
2023-12-12T16:46:07.223085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13146740 1
 
0.9%
12380590 1
 
0.9%
153263060 1
 
0.9%
139036240 1
 
0.9%
321283470 1
 
0.9%
386175780 1
 
0.9%
255925090 1
 
0.9%
8599330 1
 
0.9%
80825310 1
 
0.9%
797413620 1
 
0.9%
Other values (105) 105
91.3%
ValueCountFrequency (%)
24850 1
0.9%
1042870 1
0.9%
1552790 1
0.9%
1706080 1
0.9%
2085740 1
0.9%
2231750 1
0.9%
2884820 1
0.9%
3517710 1
0.9%
3664750 1
0.9%
3697590 1
0.9%
ValueCountFrequency (%)
889012930 1
0.9%
797413620 1
0.9%
608901670 1
0.9%
386175780 1
0.9%
384108490 1
0.9%
364807120 1
0.9%
321283470 1
0.9%
295556070 1
0.9%
294014490 1
0.9%
286963140 1
0.9%

Interactions

2023-12-12T16:46:03.675464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:02.542930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:02.968466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:03.318877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:03.773242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:02.674905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:03.061993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:03.423251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:03.849237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:02.783043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:03.145345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:03.522251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:03.928866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:02.877062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:03.237679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:03.602887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:46:07.323593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.3770.0000.259
세목명0.0001.0000.0000.5540.4860.4600.427
체납액구간0.0000.0001.0000.0000.4610.0000.197
체납건수0.0000.5540.0001.0000.6750.9780.687
체납금액0.3770.4860.4610.6751.0000.6200.882
누적체납건수0.0000.4600.0000.9780.6201.0000.772
누적체납금액0.2590.4270.1970.6870.8820.7721.000
2023-12-12T16:46:07.463034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간
과세년도1.0000.0000.000
세목명0.0001.0000.000
체납액구간0.0000.0001.000
2023-12-12T16:46:07.585031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.3910.9700.4610.0000.2190.000
체납금액0.3911.0000.2800.9600.2360.2270.214
누적체납건수0.9700.2801.0000.3910.0000.2600.000
누적체납금액0.4610.9600.3911.0000.1590.2080.088
과세년도0.0000.2360.0000.1591.0000.0000.000
세목명0.2190.2270.2600.2080.0001.0000.000
체납액구간0.0000.2140.0000.0880.0000.0001.000

Missing values

2023-12-12T16:46:04.039247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:46:04.179325image/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
0전라남도나주시461702019등록면허세10만원 미만301588465069313146740
1전라남도나주시461702019자동차세10만원 미만976425901503720156450220
2전라남도나주시461702019자동차세10만원~30만원미만13302297859603573608901670
3전라남도나주시461702019자동차세30만원~50만원미만913069417017358391380
4전라남도나주시461702019자동차세50만원~1백만원미만171870063517710
5전라남도나주시461702019재산세10만원 미만2079421284606977139038370
6전라남도나주시461702019재산세10만원~30만원미만31254386460814133521800
7전라남도나주시461702019재산세1백만원~3백만원미만32478866405382315410
8전라남도나주시461702019재산세1천만원~3천만원미만1129096608125468120
9전라남도나주시461702019재산세30만원~50만원미만612465553010943366070
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
105전라남도나주시461702021취득세10만원 미만382441680744031900
106전라남도나주시461702021취득세10만원~30만원미만305077080549812120
107전라남도나주시461702021취득세1백만원~3백만원미만11210500102138938950
108전라남도나주시461702021취득세1억원~3억원미만11484795701148479570
109전라남도나주시461702021취득세1천만원~3천만원미만59289125010173747860
110전라남도나주시461702021취득세30만원~50만원미만276508093664750
111전라남도나주시461702021취득세3백만원~5백만원미만29383730417930080
112전라남도나주시461702021취득세50만원~1백만원미만857406701913588980
113전라남도나주시461702021취득세5백만원~1천만원미만212241560534445880
114전라남도나주시461702021취득세5천만원~1억원미만21226144002122614400