Overview

Dataset statistics

Number of variables10
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory89.6 B

Variable types

Categorical6
Numeric4

Dataset

Description충청남도 논산시 지방세 체납현황에 대한 데이터로 체납액구간,체납건수,체납금액,누적체납건수,누적체납금액 등의 정보를 제공한다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=351&beforeMenuCd=DOM_000000201001001000&publicdatapk=15079392

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
체납건수 is highly overall correlated with 체납금액 and 2 other fieldsHigh correlation
체납금액 is highly overall correlated with 체납건수 and 1 other fieldsHigh correlation
누적체납건수 is highly overall correlated with 체납건수High correlation
누적체납금액 is highly overall correlated with 체납건수 and 1 other fieldsHigh correlation
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:32:48.058900
Analysis finished2024-01-09 21:32:49.621954
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
충청남도
37 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 37
100.0%

Length

2024-01-10T06:32:49.672884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:49.755442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 37
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
논산시
37 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
논산시 37
100.0%

Length

2024-01-10T06:32:49.834841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:49.926204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
논산시 37
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
44230
37 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44230
2nd row44230
3rd row44230
4th row44230
5th row44230

Common Values

ValueCountFrequency (%)
44230 37
100.0%

Length

2024-01-10T06:32:50.004244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:50.079987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44230 37
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
2020
37 

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 37
100.0%

Length

2024-01-10T06:32:50.174001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:50.269806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 37
100.0%

세목명
Categorical

Distinct7
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Memory size428.0 B
지방소득세
9 
재산세
8 
취득세
8 
주민세
5 
자동차세
4 
Other values (2)
3 

Length

Max length7
Median length3
Mean length3.8108108
Min length3

Unique

Unique1 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 9
24.3%
재산세 8
21.6%
취득세 8
21.6%
주민세 5
13.5%
자동차세 4
10.8%
등록면허세 2
 
5.4%
지역자원시설세 1
 
2.7%

Length

2024-01-10T06:32:50.380466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:50.486136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 9
24.3%
재산세 8
21.6%
취득세 8
21.6%
주민세 5
13.5%
자동차세 4
10.8%
등록면허세 2
 
5.4%
지역자원시설세 1
 
2.7%

체납액구간
Categorical

Distinct9
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
10만원 미만
7 
10만원~30만원미만
6 
30만원~50만원미만
5 
50만원~1백만원미만
5 
1백만원~3백만원미만
4 
Other values (4)
10 

Length

Max length11
Median length11
Mean length10.189189
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 7
18.9%
10만원~30만원미만 6
16.2%
30만원~50만원미만 5
13.5%
50만원~1백만원미만 5
13.5%
1백만원~3백만원미만 4
10.8%
1천만원~3천만원미만 3
8.1%
5백만원~1천만원미만 3
8.1%
3백만원~5백만원미만 2
 
5.4%
5천만원~1억원미만 2
 
5.4%

Length

2024-01-10T06:32:50.593006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:50.691700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 7
15.9%
미만 7
15.9%
10만원~30만원미만 6
13.6%
30만원~50만원미만 5
11.4%
50만원~1백만원미만 5
11.4%
1백만원~3백만원미만 4
9.1%
1천만원~3천만원미만 3
6.8%
5백만원~1천만원미만 3
6.8%
3백만원~5백만원미만 2
 
4.5%
5천만원~1억원미만 2
 
4.5%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)70.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean442.43243
Minimum1
Maximum5717
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-01-10T06:32:50.792809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median11
Q396
95-th percentile2461
Maximum5717
Range5716
Interquartile range (IQR)92

Descriptive statistics

Standard deviation1252.4162
Coefficient of variation (CV)2.8307513
Kurtosis12.674568
Mean442.43243
Median Absolute Deviation (MAD)10
Skewness3.5913773
Sum16370
Variance1568546.3
MonotonicityNot monotonic
2024-01-10T06:32:50.879745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 5
 
13.5%
8 3
 
8.1%
2 3
 
8.1%
7 2
 
5.4%
11 2
 
5.4%
4 2
 
5.4%
27 1
 
2.7%
9 1
 
2.7%
47 1
 
2.7%
13 1
 
2.7%
Other values (16) 16
43.2%
ValueCountFrequency (%)
1 5
13.5%
2 3
8.1%
3 1
 
2.7%
4 2
 
5.4%
7 2
 
5.4%
8 3
8.1%
9 1
 
2.7%
11 2
 
5.4%
13 1
 
2.7%
18 1
 
2.7%
ValueCountFrequency (%)
5717 1
2.7%
4957 1
2.7%
1837 1
2.7%
1426 1
2.7%
788 1
2.7%
481 1
2.7%
361 1
2.7%
144 1
2.7%
110 1
2.7%
96 1
2.7%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52633760
Minimum102070
Maximum2.4675069 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-01-10T06:32:50.979252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102070
5-th percentile366490
Q12951240
median33147140
Q377464080
95-th percentile1.7683701 × 108
Maximum2.4675069 × 108
Range2.4664862 × 108
Interquartile range (IQR)74512840

Descriptive statistics

Standard deviation61458925
Coefficient of variation (CV)1.1676712
Kurtosis1.946954
Mean52633760
Median Absolute Deviation (MAD)31546300
Skewness1.4964918
Sum1.9474491 × 109
Variance3.7771995 × 1015
MonotonicityNot monotonic
2024-01-10T06:32:51.079374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
7068700 1
 
2.7%
126770 1
 
2.7%
87339080 1
 
2.7%
194955600 1
 
2.7%
20796710 1
 
2.7%
49875930 1
 
2.7%
33147140 1
 
2.7%
79658860 1
 
2.7%
172307360 1
 
2.7%
102070 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
102070 1
2.7%
126770 1
2.7%
426420 1
2.7%
554760 1
2.7%
964760 1
2.7%
1402550 1
2.7%
1600840 1
2.7%
1979690 1
2.7%
2862170 1
2.7%
2951240 1
2.7%
ValueCountFrequency (%)
246750690 1
2.7%
194955600 1
2.7%
172307360 1
2.7%
144544040 1
2.7%
130229230 1
2.7%
125165180 1
2.7%
93782790 1
2.7%
87339080 1
2.7%
79658860 1
2.7%
77464080 1
2.7%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1299.0811
Minimum1
Maximum14978
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-01-10T06:32:51.176007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.6
Q118
median31
Q3217
95-th percentile8265
Maximum14978
Range14977
Interquartile range (IQR)199

Descriptive statistics

Standard deviation3597.8918
Coefficient of variation (CV)2.7695667
Kurtosis10.367474
Mean1299.0811
Median Absolute Deviation (MAD)28
Skewness3.2910743
Sum48066
Variance12944825
MonotonicityNot monotonic
2024-01-10T06:32:51.493669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
19 3
 
8.1%
1 2
 
5.4%
21 2
 
5.4%
11 2
 
5.4%
1221 1
 
2.7%
133 1
 
2.7%
344 1
 
2.7%
125 1
 
2.7%
101 1
 
2.7%
27 1
 
2.7%
Other values (22) 22
59.5%
ValueCountFrequency (%)
1 2
5.4%
3 1
 
2.7%
4 1
 
2.7%
8 1
 
2.7%
10 1
 
2.7%
11 2
5.4%
12 1
 
2.7%
18 1
 
2.7%
19 3
8.1%
20 1
 
2.7%
ValueCountFrequency (%)
14978 1
2.7%
14801 1
2.7%
6631 1
2.7%
6005 1
2.7%
1562 1
2.7%
1221 1
2.7%
842 1
2.7%
344 1
2.7%
279 1
2.7%
217 1
2.7%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3373099 × 108
Minimum189280
Maximum1.0189869 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-01-10T06:32:51.596503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189280
5-th percentile925502
Q113942520
median86584330
Q32.1949271 × 108
95-th percentile3.2030189 × 108
Maximum1.0189869 × 109
Range1.0187977 × 109
Interquartile range (IQR)2.0555019 × 108

Descriptive statistics

Standard deviation1.8512511 × 108
Coefficient of variation (CV)1.3843097
Kurtosis14.15477
Mean1.3373099 × 108
Median Absolute Deviation (MAD)73656580
Skewness3.2269217
Sum4.9480466 × 109
Variance3.4271306 × 1016
MonotonicityNot monotonic
2024-01-10T06:32:51.699539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
17578110 1
 
2.7%
189280 1
 
2.7%
219492710 1
 
2.7%
308468960 1
 
2.7%
40560330 1
 
2.7%
109323520 1
 
2.7%
95011250 1
 
2.7%
137567170 1
 
2.7%
236456960 1
 
2.7%
941680 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
189280 1
2.7%
860790 1
2.7%
941680 1
2.7%
4334680 1
2.7%
4336930 1
2.7%
5998830 1
2.7%
7203120 1
2.7%
12927750 1
2.7%
13168730 1
2.7%
13942520 1
2.7%
ValueCountFrequency (%)
1018986940 1
2.7%
347276390 1
2.7%
313558270 1
2.7%
308468960 1
2.7%
294899580 1
2.7%
287256840 1
2.7%
252137480 1
2.7%
236456960 1
2.7%
230241930 1
2.7%
219492710 1
2.7%

Interactions

2024-01-10T06:32:49.162234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:48.293246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:48.550684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:48.808748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:49.245804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:48.356769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:48.615360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:48.896622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:49.306414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:48.419438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:48.675712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:48.985103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:49.371819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:48.488446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:48.743052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:49.076655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:32:51.767551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.1560.3270.3940.275
체납액구간0.0001.0000.0000.4550.0000.490
체납건수0.1560.0001.0000.7411.0000.724
체납금액0.3270.4550.7411.0000.8330.870
누적체납건수0.3940.0001.0000.8331.0000.546
누적체납금액0.2750.4900.7240.8700.5461.000
2024-01-10T06:32:51.845808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명
체납액구간1.0000.000
세목명0.0001.000
2024-01-10T06:32:51.911751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.5230.9220.5400.0560.000
체납금액0.5231.0000.3810.9430.1820.231
누적체납건수0.9220.3811.0000.4800.2590.000
누적체납금액0.5400.9430.4801.0000.0870.280
세목명0.0560.1820.2590.0871.0000.000
체납액구간0.0000.2310.0000.2800.0001.000

Missing values

2024-01-10T06:32:49.459276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:32:49.577838image/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
0충청남도논산시442302020등록면허세10만원 미만4817068700122117578110
1충청남도논산시442302020등록면허세10만원~30만원미만24264204860790
2충청남도논산시442302020자동차세10만원 미만1837774640806631287256840
3충청남도논산시442302020자동차세10만원~30만원미만142624675069060051018986940
4충청남도논산시442302020자동차세30만원~50만원미만672350663027995787420
5충청남도논산시442302020자동차세50만원~1백만원미만15547602112927750
6충청남도논산시442302020재산세10만원 미만495712516518014978347276390
7충청남도논산시442302020재산세10만원~30만원미만7881302292301562252137480
8충청남도논산시442302020재산세1백만원~3백만원미만89144544040187294899580
9충청남도논산시442302020재산세1천만원~3천만원미만44955310011132021540
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
27충청남도논산시442302020지방소득세5천만원~1억원미만21723073603236456960
28충청남도논산시442302020지역자원시설세10만원 미만912677018189280
29충청남도논산시442302020취득세10만원 미만410207024941680
30충청남도논산시442302020취득세10만원~30만원미만71600840315998830
31충청남도논산시442302020취득세1백만원~3백만원미만8138748202136821290
32충청남도논산시442302020취득세1천만원~3천만원미만2386620608134423220
33충청남도논산시442302020취득세30만원~50만원미만72862170114334680
34충청남도논산시442302020취득세50만원~1백만원미만19647601913168730
35충청남도논산시442302020취득세5백만원~1천만원미만1720312017203120
36충청남도논산시442302020취득세5천만원~1억원미만161190190161190190