Overview

Dataset statistics

Number of variables10
Number of observations121
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.3 KiB
Average record size in memory87.1 B

Variable types

Categorical6
Numeric4

Dataset

Description2017년부터 2022년까지 서천군 지방세 세목별 체납액에 대한 과세자료를 제공합니다.(세목별, 체납액구간 별, 체납건수, 체납금액 포함)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=347&beforeMenuCd=DOM_000000201001001000&publicdatapk=15080480

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
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:36:04.115743
Analysis finished2024-01-09 22:36:05.908662
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
충청남도
121 

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 121
100.0%

Length

2024-01-10T07:36:05.976809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:36:06.057541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 121
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
서천군
121 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서천군 121
100.0%

Length

2024-01-10T07:36:06.139621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:36:06.221462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서천군 121
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
44770
121 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44770
2nd row44770
3rd row44770
4th row44770
5th row44770

Common Values

ValueCountFrequency (%)
44770 121
100.0%

Length

2024-01-10T07:36:06.303365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:36:06.380253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44770 121
100.0%

과세년도
Categorical

Distinct5
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2020
30 
2021
28 
2019
25 
2018
20 
2017
18 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2020 30
24.8%
2021 28
23.1%
2019 25
20.7%
2018 20
16.5%
2017 18
14.9%

Length

2024-01-10T07:36:06.701098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:36:06.794800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 30
24.8%
2021 28
23.1%
2019 25
20.7%
2018 20
16.5%
2017 18
14.9%

세목명
Categorical

Distinct6
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
지방소득세
38 
재산세
33 
취득세
19 
자동차세
15 
주민세
10 

Length

Max length5
Median length3
Mean length3.8512397
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 38
31.4%
재산세 33
27.3%
취득세 19
15.7%
자동차세 15
 
12.4%
주민세 10
 
8.3%
등록면허세 6
 
5.0%

Length

2024-01-10T07:36:06.929981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:36:07.052011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 38
31.4%
재산세 33
27.3%
취득세 19
15.7%
자동차세 15
 
12.4%
주민세 10
 
8.3%
등록면허세 6
 
5.0%

체납액구간
Categorical

Distinct10
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
10만원 미만
27 
10만원~30만원미만
20 
30만원~50만원미만
18 
1백만원~3백만원미만
14 
3백만원~5백만원미만
12 
Other values (5)
30 

Length

Max length11
Median length11
Mean length10.082645
Min length7

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 27
22.3%
10만원~30만원미만 20
16.5%
30만원~50만원미만 18
14.9%
1백만원~3백만원미만 14
11.6%
3백만원~5백만원미만 12
9.9%
50만원~1백만원미만 12
9.9%
5백만원~1천만원미만 8
 
6.6%
1천만원~3천만원미만 6
 
5.0%
5천만원~1억원미만 3
 
2.5%
3천만원~5천만원미만 1
 
0.8%

Length

2024-01-10T07:36:07.175043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:36:07.291155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 27
18.2%
미만 27
18.2%
10만원~30만원미만 20
13.5%
30만원~50만원미만 18
12.2%
1백만원~3백만원미만 14
9.5%
3백만원~5백만원미만 12
8.1%
50만원~1백만원미만 12
8.1%
5백만원~1천만원미만 8
 
5.4%
1천만원~3천만원미만 6
 
4.1%
5천만원~1억원미만 3
 
2.0%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)46.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean142.70248
Minimum1
Maximum2960
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-10T07:36:07.432242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median8
Q348
95-th percentile491
Maximum2960
Range2959
Interquartile range (IQR)46

Descriptive statistics

Standard deviation433.43019
Coefficient of variation (CV)3.0372996
Kurtosis25.301392
Mean142.70248
Median Absolute Deviation (MAD)7
Skewness4.8704664
Sum17267
Variance187861.73
MonotonicityNot monotonic
2024-01-10T07:36:07.548718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 26
21.5%
2 13
 
10.7%
4 8
 
6.6%
8 6
 
5.0%
5 4
 
3.3%
3 4
 
3.3%
24 3
 
2.5%
21 3
 
2.5%
18 2
 
1.7%
15 2
 
1.7%
Other values (46) 50
41.3%
ValueCountFrequency (%)
1 26
21.5%
2 13
10.7%
3 4
 
3.3%
4 8
 
6.6%
5 4
 
3.3%
6 2
 
1.7%
7 1
 
0.8%
8 6
 
5.0%
9 2
 
1.7%
10 1
 
0.8%
ValueCountFrequency (%)
2960 1
0.8%
2459 1
0.8%
2204 1
0.8%
1569 1
0.8%
835 1
0.8%
576 1
0.8%
491 1
0.8%
477 1
0.8%
434 1
0.8%
433 1
0.8%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15136138
Minimum83790
Maximum1.1991882 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-10T07:36:07.672464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum83790
5-th percentile425750
Q12678920
median6404030
Q318252080
95-th percentile61019550
Maximum1.1991882 × 108
Range1.1983503 × 108
Interquartile range (IQR)15573160

Descriptive statistics

Standard deviation21464520
Coefficient of variation (CV)1.4180975
Kurtosis6.7870803
Mean15136138
Median Absolute Deviation (MAD)5349670
Skewness2.4621576
Sum1.8314728 × 109
Variance4.6072562 × 1014
MonotonicityNot monotonic
2024-01-10T07:36:07.800871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
776180 1
 
0.8%
695430 1
 
0.8%
438310 1
 
0.8%
12557800 1
 
0.8%
8488060 1
 
0.8%
83790 1
 
0.8%
62385940 1
 
0.8%
34417390 1
 
0.8%
17392900 1
 
0.8%
17129190 1
 
0.8%
Other values (111) 111
91.7%
ValueCountFrequency (%)
83790 1
0.8%
98840 1
0.8%
111350 1
0.8%
334300 1
0.8%
370760 1
0.8%
416440 1
0.8%
425750 1
0.8%
438310 1
0.8%
539860 1
0.8%
616300 1
0.8%
ValueCountFrequency (%)
119918820 1
0.8%
94744930 1
0.8%
88793280 1
0.8%
82617600 1
0.8%
62385940 1
0.8%
61610510 1
0.8%
61019550 1
0.8%
59780380 1
0.8%
56298880 1
0.8%
53810810 1
0.8%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean363.67769
Minimum1
Maximum5676
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-10T07:36:07.946440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median19
Q396
95-th percentile1806
Maximum5676
Range5675
Interquartile range (IQR)92

Descriptive statistics

Standard deviation937.91058
Coefficient of variation (CV)2.578961
Kurtosis17.155032
Mean363.67769
Median Absolute Deviation (MAD)17
Skewness3.9080942
Sum44005
Variance879676.25
MonotonicityNot monotonic
2024-01-10T07:36:08.060766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 10
 
8.3%
2 10
 
8.3%
3 8
 
6.6%
5 5
 
4.1%
11 5
 
4.1%
9 4
 
3.3%
6 3
 
2.5%
17 3
 
2.5%
4 3
 
2.5%
37 3
 
2.5%
Other values (58) 67
55.4%
ValueCountFrequency (%)
1 10
8.3%
2 10
8.3%
3 8
6.6%
4 3
 
2.5%
5 5
4.1%
6 3
 
2.5%
7 2
 
1.7%
8 1
 
0.8%
9 4
 
3.3%
10 2
 
1.7%
ValueCountFrequency (%)
5676 1
0.8%
5596 1
0.8%
3452 1
0.8%
3217 1
0.8%
3080 1
0.8%
2382 1
0.8%
1806 1
0.8%
1557 1
0.8%
1511 1
0.8%
1442 1
0.8%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31449728
Minimum223860
Maximum2.4546259 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-10T07:36:08.198076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum223860
5-th percentile1237690
Q15966970
median14525980
Q344566110
95-th percentile99468230
Maximum2.4546259 × 108
Range2.4523873 × 108
Interquartile range (IQR)38599140

Descriptive statistics

Standard deviation42093003
Coefficient of variation (CV)1.3384218
Kurtosis8.0856039
Mean31449728
Median Absolute Deviation (MAD)12354550
Skewness2.5890694
Sum3.8054171 × 109
Variance1.7718209 × 1015
MonotonicityNot monotonic
2024-01-10T07:36:08.324015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1923090 1
 
0.8%
2138230 1
 
0.8%
1100520 1
 
0.8%
61835360 1
 
0.8%
10758910 1
 
0.8%
377470 1
 
0.8%
157130870 1
 
0.8%
50045650 1
 
0.8%
44566110 1
 
0.8%
29946900 1
 
0.8%
Other values (111) 111
91.7%
ValueCountFrequency (%)
223860 1
0.8%
377470 1
0.8%
662210 1
0.8%
726700 1
0.8%
1100520 1
0.8%
1236060 1
0.8%
1237690 1
0.8%
1442800 1
0.8%
1555130 1
0.8%
1684320 1
0.8%
ValueCountFrequency (%)
245462590 1
0.8%
196352360 1
0.8%
183852080 1
0.8%
157130870 1
0.8%
143283390 1
0.8%
127553200 1
0.8%
99468230 1
0.8%
98877010 1
0.8%
94744930 1
0.8%
89057960 1
0.8%

Interactions

2024-01-10T07:36:05.347511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:04.386776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:04.675865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:05.018497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:05.441745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:04.457553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:04.756876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:05.109956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:05.530926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:04.531403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:04.838965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:05.188267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:05.605737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:04.599440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:04.925861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:05.269917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:36:08.404889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.3440.0000.078
세목명0.0001.0000.2720.3140.0000.4800.261
체납액구간0.0000.2721.0000.0000.7480.0000.609
체납건수0.0000.3140.0001.0000.5050.9070.659
체납금액0.3440.0000.7480.5051.0000.3550.945
누적체납건수0.0000.4800.0000.9070.3551.0000.691
누적체납금액0.0780.2610.6090.6590.9450.6911.000
2024-01-10T07:36:08.500190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도체납액구간세목명
과세년도1.0000.0000.000
체납액구간0.0001.0000.142
세목명0.0000.1421.000
2024-01-10T07:36:08.578051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.3240.9700.3920.0000.1910.000
체납금액0.3241.0000.2150.9370.1970.0000.462
누적체납건수0.9700.2151.0000.3500.0000.2880.000
누적체납금액0.3920.9370.3501.0000.0180.1320.329
과세년도0.0000.1970.0000.0181.0000.0000.000
세목명0.1910.0000.2880.1320.0001.0000.142
체납액구간0.0000.4620.0000.3290.0000.1421.000

Missing values

2024-01-10T07:36:05.708493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:36:05.847486image/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
0충청남도서천군447702017등록면허세10만원 미만717761801911923090
1충청남도서천군447702017자동차세10만원 미만138616996072430128020
2충청남도서천군447702017자동차세10만원~30만원미만1572594555053689057960
3충청남도서천군447702017자동차세30만원~50만원미만51845880176160870
4충청남도서천군447702017재산세10만원 미만4336404030180626279430
5충청남도서천군447702017재산세10만원~30만원미만102031470336104770
6충청남도서천군447702017재산세1백만원~3백만원미만238182101018629970
7충청남도서천군447702017재산세30만원~50만원미만266422051684320
8충청남도서천군447702017재산세3백만원~5백만원미만13989870415258770
9충청남도서천군447702017재산세50만원~1백만원미만43090990118391870
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
111충청남도서천군447702021지방소득세30만원~50만원미만2178125902810461570
112충청남도서천군447702021지방소득세3백만원~5백만원미만519667050624464570
113충청남도서천군447702021지방소득세3천만원~5천만원미만282617600282617600
114충청남도서천군447702021지방소득세50만원~1백만원미만28207921206246150370
115충청남도서천군447702021지방소득세5백만원~1천만원미만8538108101172355600
116충청남도서천군447702021취득세10만원 미만2988405223860
117충청남도서천군447702021취득세10만원~30만원미만111135091236060
118충청남도서천군447702021취득세1백만원~3백만원미만1170429011704290
119충청남도서천군447702021취득세1천만원~3천만원미만110020580469840950
120충청남도서천군447702021취득세3백만원~5백만원미만28215720311275810