Overview

Dataset statistics

Number of variables10
Number of observations75
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 KiB
Average record size in memory87.8 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
체납건수 is highly overall correlated with 누적체납건수 and 1 other fieldsHigh correlation
체납금액 is highly overall correlated with 누적체납금액High 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 21:32:52.481251
Analysis finished2024-01-09 21:32:53.974795
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
충청남도
75 

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 75
100.0%

Length

2024-01-10T06:32:54.024960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:54.110248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 75
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
논산시
75 

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 75
100.0%

Length

2024-01-10T06:32:54.189516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:54.262195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
논산시 75
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
44230
75 

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 75
100.0%

Length

2024-01-10T06:32:54.338769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:54.412861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44230 75
100.0%

과세년도
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
2021
38 
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 (%)
2021 38
50.7%
2020 37
49.3%

Length

2024-01-10T06:32:54.489316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:54.566540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 38
50.7%
2020 37
49.3%

세목명
Categorical

Distinct7
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
취득세
18 
지방소득세
17 
재산세
16 
주민세
10 
자동차세
7 
Other values (2)
7 

Length

Max length7
Median length3
Mean length3.7866667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 18
24.0%
지방소득세 17
22.7%
재산세 16
21.3%
주민세 10
13.3%
자동차세 7
 
9.3%
등록면허세 5
 
6.7%
지역자원시설세 2
 
2.7%

Length

2024-01-10T06:32:54.652813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:32:54.753396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취득세 18
24.0%
지방소득세 17
22.7%
재산세 16
21.3%
주민세 10
13.3%
자동차세 7
 
9.3%
등록면허세 5
 
6.7%
지역자원시설세 2
 
2.7%

체납액구간
Categorical

Distinct11
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
10만원 미만
14 
10만원~30만원미만
12 
30만원~50만원미만
10 
50만원~1백만원미만
9 
1백만원~3백만원미만
8 
Other values (6)
22 

Length

Max length11
Median length11
Mean length10.186667
Min length7

Unique

Unique2 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 14
18.7%
10만원~30만원미만 12
16.0%
30만원~50만원미만 10
13.3%
50만원~1백만원미만 9
12.0%
1백만원~3백만원미만 8
10.7%
3백만원~5백만원미만 6
8.0%
5백만원~1천만원미만 6
8.0%
1천만원~3천만원미만 5
 
6.7%
5천만원~1억원미만 3
 
4.0%
1억원~3억원미만 1
 
1.3%

Length

2024-01-10T06:32:54.860055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 14
15.7%
미만 14
15.7%
10만원~30만원미만 12
13.5%
30만원~50만원미만 10
11.2%
50만원~1백만원미만 9
10.1%
1백만원~3백만원미만 8
9.0%
3백만원~5백만원미만 6
6.7%
5백만원~1천만원미만 6
6.7%
1천만원~3천만원미만 5
 
5.6%
5천만원~1억원미만 3
 
3.4%
Other values (2) 2
 
2.2%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)62.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean365.37333
Minimum1
Maximum5717
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-01-10T06:32:54.961428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median11
Q392.5
95-th percentile1853.5
Maximum5717
Range5716
Interquartile range (IQR)89.5

Descriptive statistics

Standard deviation1072.9054
Coefficient of variation (CV)2.9364634
Kurtosis15.805189
Mean365.37333
Median Absolute Deviation (MAD)10
Skewness3.959369
Sum27403
Variance1151126
MonotonicityNot monotonic
2024-01-10T06:32:55.064087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
1 11
 
14.7%
3 5
 
6.7%
10 5
 
6.7%
2 4
 
5.3%
8 3
 
4.0%
7 3
 
4.0%
4 3
 
4.0%
11 2
 
2.7%
88 1
 
1.3%
4926 1
 
1.3%
Other values (37) 37
49.3%
ValueCountFrequency (%)
1 11
14.7%
2 4
 
5.3%
3 5
6.7%
4 3
 
4.0%
5 1
 
1.3%
6 1
 
1.3%
7 3
 
4.0%
8 3
 
4.0%
9 1
 
1.3%
10 5
6.7%
ValueCountFrequency (%)
5717 1
1.3%
4957 1
1.3%
4926 1
1.3%
1892 1
1.3%
1837 1
1.3%
1559 1
1.3%
1426 1
1.3%
788 1
1.3%
731 1
1.3%
591 1
1.3%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49777137
Minimum102070
Maximum2.6970356 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-01-10T06:32:55.171349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102070
5-th percentile324458
Q13151445
median26987390
Q373237350
95-th percentile1.6648527 × 108
Maximum2.6970356 × 108
Range2.6960149 × 108
Interquartile range (IQR)70085905

Descriptive statistics

Standard deviation59762231
Coefficient of variation (CV)1.200596
Kurtosis2.8220896
Mean49777137
Median Absolute Deviation (MAD)25386550
Skewness1.6592518
Sum3.7332853 × 109
Variance3.5715243 × 1015
MonotonicityNot monotonic
2024-01-10T06:32:55.281848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7068700 1
 
1.3%
59832770 1
 
1.3%
1813530 1
 
1.3%
2735060 1
 
1.3%
4499420 1
 
1.3%
5656740 1
 
1.3%
364190 1
 
1.3%
64053960 1
 
1.3%
60524810 1
 
1.3%
47374360 1
 
1.3%
Other values (65) 65
86.7%
ValueCountFrequency (%)
102070 1
1.3%
126770 1
1.3%
221540 1
1.3%
231750 1
1.3%
364190 1
1.3%
426420 1
1.3%
554760 1
1.3%
683580 1
1.3%
964760 1
1.3%
1402550 1
1.3%
ValueCountFrequency (%)
269703560 1
1.3%
246750690 1
1.3%
194955600 1
1.3%
172307360 1
1.3%
163990090 1
1.3%
151549490 1
1.3%
144544040 1
1.3%
130229230 1
1.3%
128069890 1
1.3%
125165180 1
1.3%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)78.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1208.72
Minimum1
Maximum14978
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-01-10T06:32:55.389346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.7
Q112
median31
Q3214
95-th percentile7417
Maximum14978
Range14977
Interquartile range (IQR)202

Descriptive statistics

Standard deviation3303.0261
Coefficient of variation (CV)2.7326644
Kurtosis10.503907
Mean1208.72
Median Absolute Deviation (MAD)29
Skewness3.3005712
Sum90654
Variance10909981
MonotonicityNot monotonic
2024-01-10T06:32:55.497677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 4
 
5.3%
12 3
 
4.0%
19 3
 
4.0%
11 3
 
4.0%
21 2
 
2.7%
31 2
 
2.7%
29 2
 
2.7%
15 2
 
2.7%
3 2
 
2.7%
27 2
 
2.7%
Other values (49) 50
66.7%
ValueCountFrequency (%)
1 4
5.3%
2 2
2.7%
3 2
2.7%
4 1
 
1.3%
5 1
 
1.3%
6 1
 
1.3%
7 1
 
1.3%
8 1
 
1.3%
10 1
 
1.3%
11 3
4.0%
ValueCountFrequency (%)
14978 1
1.3%
14801 1
1.3%
14744 1
1.3%
9251 1
1.3%
6631 1
1.3%
6458 1
1.3%
6184 1
1.3%
6005 1
1.3%
1562 1
1.3%
1530 1
1.3%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2985954 × 108
Minimum189280
Maximum1.047893 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-01-10T06:32:55.612921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189280
5-th percentile1166303
Q113124680
median86584330
Q31.9880191 × 108
95-th percentile3.3045412 × 108
Maximum1.047893 × 109
Range1.0477037 × 109
Interquartile range (IQR)1.8567723 × 108

Descriptive statistics

Standard deviation1.831605 × 108
Coefficient of variation (CV)1.4104509
Kurtosis14.490211
Mean1.2985954 × 108
Median Absolute Deviation (MAD)74400270
Skewness3.351215
Sum9.7394653 × 109
Variance3.3547767 × 1016
MonotonicityNot monotonic
2024-01-10T06:32:55.722835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17578110 1
 
1.3%
150856300 1
 
1.3%
12184060 1
 
1.3%
4589620 1
 
1.3%
10566590 1
 
1.3%
14742840 1
 
1.3%
143399950 1
 
1.3%
210451620 1
 
1.3%
132656860 1
 
1.3%
84107230 1
 
1.3%
Other values (65) 65
86.7%
ValueCountFrequency (%)
189280 1
1.3%
371760 1
1.3%
860790 1
1.3%
941680 1
1.3%
1262570 1
1.3%
1406410 1
1.3%
3351650 1
1.3%
4334680 1
1.3%
4336930 1
1.3%
4374620 1
1.3%
ValueCountFrequency (%)
1047892960 1
1.3%
1018986940 1
1.3%
349724850 1
1.3%
347276390 1
1.3%
323244570 1
1.3%
313558270 1
1.3%
308468960 1
1.3%
294899580 1
1.3%
287256840 1
1.3%
279413670 1
1.3%

Interactions

2024-01-10T06:32:53.528087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:52.728184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:52.986350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:53.247251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:53.595700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:52.792114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:53.050428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:53.312867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:53.662600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:52.854416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:53.113928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:53.382024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:53.731772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:52.920746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:53.182128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:32:53.452366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:32:55.796251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.0000.4820.4550.5200.498
체납액구간0.0000.0001.0000.0000.5440.0000.483
체납건수0.0000.4820.0001.0000.8500.8750.781
체납금액0.0000.4550.5440.8501.0000.7390.880
누적체납건수0.0000.5200.0000.8750.7391.0000.862
누적체납금액0.0000.4980.4830.7810.8800.8621.000
2024-01-10T06:32:56.157279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도체납액구간세목명
과세년도1.0000.0000.000
체납액구간0.0001.0000.000
세목명0.0000.0001.000
2024-01-10T06:32:56.233191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.4880.9210.5050.0000.3080.000
체납금액0.4881.0000.3520.9180.0000.2570.278
누적체납건수0.9210.3521.0000.5000.0000.3600.000
누적체납금액0.5050.9180.5001.0000.0000.3460.274
과세년도0.0000.0000.0000.0001.0000.0000.000
세목명0.3080.2570.3600.3460.0001.0000.000
체납액구간0.0000.2780.0000.2740.0000.0001.000

Missing values

2024-01-10T06:32:53.821074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:32:53.929282image/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
65충청남도논산시442302021취득세10만원 미만14683580331406410
66충청남도논산시442302021취득세10만원~30만원미만102001720275017160
67충청남도논산시442302021취득세1백만원~3백만원미만353243701222761550
68충청남도논산시442302021취득세1억원~3억원미만11024329001102432900
69충청남도논산시442302021취득세30만원~50만원미만52023140114374620
70충청남도논산시442302021취득세3백만원~5백만원미만27281950518168340
71충청남도논산시442302021취득세3천만원~5천만원미만1354917403110891770
72충청남도논산시442302021취득세50만원~1백만원미만31923120159745670
73충청남도논산시442302021취득세5백만원~1천만원미만15308350213080630
74충청남도논산시442302021취득세5천만원~1억원미만1688802502135302680