Overview

Dataset statistics

Number of variables10
Number of observations63
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory88.1 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 22:35:59.189528
Analysis finished2024-01-09 22:36:01.060995
Duration1.87 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
충청남도
63 

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 63
100.0%

Length

2024-01-10T07:36:01.123869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:36:01.221128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 63
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
서천군
63 

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 63
100.0%

Length

2024-01-10T07:36:01.319239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:36:01.414059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서천군 63
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
44770
63 

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 63
100.0%

Length

2024-01-10T07:36:01.502794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:36:01.586310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44770 63
100.0%

과세년도
Categorical

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
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 (%)
2019 25
39.7%
2018 20
31.7%
2017 18
28.6%

Length

2024-01-10T07:36:01.671453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:36:01.764261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 25
39.7%
2018 20
31.7%
2017 18
28.6%

세목명
Categorical

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
지방소득세
20 
재산세
19 
자동차세
9 
취득세
8 
주민세
4 

Length

Max length5
Median length4
Mean length3.8730159
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 20
31.7%
재산세 19
30.2%
자동차세 9
14.3%
취득세 8
 
12.7%
주민세 4
 
6.3%
등록면허세 3
 
4.8%

Length

2024-01-10T07:36:01.882220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:36:01.986320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 20
31.7%
재산세 19
30.2%
자동차세 9
14.3%
취득세 8
 
12.7%
주민세 4
 
6.3%
등록면허세 3
 
4.8%

체납액구간
Categorical

Distinct9
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size636.0 B
10만원 미만
15 
10만원~30만원미만
11 
30만원~50만원미만
10 
1백만원~3백만원미만
7 
50만원~1백만원미만
7 
Other values (4)
13 

Length

Max length11
Median length11
Mean length10.015873
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 15
23.8%
10만원~30만원미만 11
17.5%
30만원~50만원미만 10
15.9%
1백만원~3백만원미만 7
11.1%
50만원~1백만원미만 7
11.1%
3백만원~5백만원미만 5
 
7.9%
5백만원~1천만원미만 4
 
6.3%
5천만원~1억원미만 2
 
3.2%
1천만원~3천만원미만 2
 
3.2%

Length

2024-01-10T07:36:02.105559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:36:02.225255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 15
19.2%
미만 15
19.2%
10만원~30만원미만 11
14.1%
30만원~50만원미만 10
12.8%
1백만원~3백만원미만 7
9.0%
50만원~1백만원미만 7
9.0%
3백만원~5백만원미만 5
 
6.4%
5백만원~1천만원미만 4
 
5.1%
5천만원~1억원미만 2
 
2.6%
1천만원~3천만원미만 2
 
2.6%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.079365
Minimum1
Maximum835
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-01-10T07:36:02.343166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median6
Q338
95-th percentile422.1
Maximum835
Range834
Interquartile range (IQR)36

Descriptive statistics

Standard deviation159.42106
Coefficient of variation (CV)2.1233672
Kurtosis9.3220394
Mean75.079365
Median Absolute Deviation (MAD)5
Skewness2.9199615
Sum4730
Variance25415.074
MonotonicityNot monotonic
2024-01-10T07:36:02.450573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 15
23.8%
2 8
 
12.7%
4 5
 
7.9%
8 5
 
7.9%
5 2
 
3.2%
71 1
 
1.6%
9 1
 
1.6%
219 1
 
1.6%
324 1
 
1.6%
12 1
 
1.6%
Other values (23) 23
36.5%
ValueCountFrequency (%)
1 15
23.8%
2 8
12.7%
3 1
 
1.6%
4 5
 
7.9%
5 2
 
3.2%
6 1
 
1.6%
8 5
 
7.9%
9 1
 
1.6%
10 1
 
1.6%
12 1
 
1.6%
ValueCountFrequency (%)
835 1
1.6%
576 1
1.6%
491 1
1.6%
433 1
1.6%
324 1
1.6%
321 1
1.6%
243 1
1.6%
232 1
1.6%
219 1
1.6%
180 1
1.6%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9368271.4
Minimum334300
Maximum94744930
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-01-10T07:36:02.580533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum334300
5-th percentile437161
Q11613395
median3838540
Q38066090
95-th percentile37240271
Maximum94744930
Range94410630
Interquartile range (IQR)6452695

Descriptive statistics

Standard deviation17590417
Coefficient of variation (CV)1.8776588
Kurtosis15.169968
Mean9368271.4
Median Absolute Deviation (MAD)2820410
Skewness3.8058026
Sum5.902011 × 108
Variance3.0942279 × 1014
MonotonicityNot monotonic
2024-01-10T07:36:02.723343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
776180 1
 
1.6%
6169960 1
 
1.6%
5668690 1
 
1.6%
416440 1
 
1.6%
2270850 1
 
1.6%
4457760 1
 
1.6%
1140180 1
 
1.6%
8933880 1
 
1.6%
56298880 1
 
1.6%
3838540 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
334300 1
1.6%
370760 1
1.6%
416440 1
1.6%
425750 1
1.6%
539860 1
1.6%
664220 1
1.6%
714180 1
1.6%
776180 1
1.6%
814100 1
1.6%
829460 1
1.6%
ValueCountFrequency (%)
94744930 1
1.6%
88793280 1
1.6%
56298880 1
1.6%
38495240 1
1.6%
25945550 1
1.6%
22206410 1
1.6%
15008170 1
1.6%
14149030 1
1.6%
13747610 1
1.6%
12455050 1
1.6%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)65.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean277.90476
Minimum1
Maximum3217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-01-10T07:36:02.847427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14.5
median17
Q3101.5
95-th percentile1472.2
Maximum3217
Range3216
Interquartile range (IQR)97

Descriptive statistics

Standard deviation611.63962
Coefficient of variation (CV)2.2008965
Kurtosis10.021325
Mean277.90476
Median Absolute Deviation (MAD)16
Skewness3.012965
Sum17508
Variance374103.02
MonotonicityNot monotonic
2024-01-10T07:36:02.955455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1 8
 
12.7%
2 5
 
7.9%
17 3
 
4.8%
5 3
 
4.8%
24 2
 
3.2%
9 2
 
3.2%
14 2
 
3.2%
6 2
 
3.2%
4 2
 
3.2%
11 2
 
3.2%
Other values (31) 32
50.8%
ValueCountFrequency (%)
1 8
12.7%
2 5
7.9%
3 1
 
1.6%
4 2
 
3.2%
5 3
 
4.8%
6 2
 
3.2%
8 1
 
1.6%
9 2
 
3.2%
10 1
 
1.6%
11 2
 
3.2%
ValueCountFrequency (%)
3217 1
1.6%
2382 1
1.6%
1806 1
1.6%
1511 1
1.6%
1123 1
1.6%
1092 1
1.6%
1020 1
1.6%
904 1
1.6%
768 1
1.6%
724 1
1.6%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21830283
Minimum662210
Maximum1.8385208 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-01-10T07:36:03.091027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum662210
5-th percentile1568049
Q13809470
median10775930
Q325621725
95-th percentile89031492
Maximum1.8385208 × 108
Range1.8318987 × 108
Interquartile range (IQR)21812255

Descriptive statistics

Standard deviation32421042
Coefficient of variation (CV)1.4851407
Kurtosis11.127741
Mean21830283
Median Absolute Deviation (MAD)8023380
Skewness3.0873047
Sum1.3753079 × 109
Variance1.051124 × 1015
MonotonicityNot monotonic
2024-01-10T07:36:03.235382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1923090 1
 
1.6%
30128020 1
 
1.6%
5668690 1
 
1.6%
1775350 1
 
1.6%
2270850 1
 
1.6%
4457760 1
 
1.6%
3892730 1
 
1.6%
46678980 1
 
1.6%
183852080 1
 
1.6%
12678330 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
662210 1
1.6%
726700 1
1.6%
1442800 1
1.6%
1555130 1
1.6%
1684320 1
1.6%
1775350 1
1.6%
1923090 1
1.6%
2020860 1
1.6%
2168220 1
1.6%
2270850 1
1.6%
ValueCountFrequency (%)
183852080 1
1.6%
127553200 1
1.6%
94744930 1
1.6%
89057960 1
1.6%
88793280 1
1.6%
49277560 1
1.6%
49133130 1
1.6%
46678980 1
1.6%
40409280 1
1.6%
37745100 1
1.6%

Interactions

2024-01-10T07:36:00.318328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:35:59.446407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:35:59.748957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:00.025195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:00.388117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:35:59.523893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:35:59.810321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:00.102556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:00.457258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:35:59.596723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:35:59.874370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:00.170120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:00.533256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:35:59.668196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:35:59.943459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:36:00.241693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:36:03.323412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.5120.0000.084
세목명0.0001.0000.0000.4690.1470.5380.161
체납액구간0.0000.0001.0000.0000.7320.0000.507
체납건수0.0000.4690.0001.0000.5330.9630.800
체납금액0.5120.1470.7320.5331.0000.4920.892
누적체납건수0.0000.5380.0000.9630.4921.0000.570
누적체납금액0.0840.1610.5070.8000.8920.5701.000
2024-01-10T07:36:03.413412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도체납액구간세목명
과세년도1.0000.0000.000
체납액구간0.0001.0000.000
세목명0.0000.0001.000
2024-01-10T07:36:03.495595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.1380.9760.2950.0000.2970.000
체납금액0.1381.0000.0890.9010.2250.0000.459
누적체납건수0.9760.0891.0000.3150.0000.3270.000
누적체납금액0.2950.9010.3151.0000.0000.0850.294
과세년도0.0000.2250.0000.0001.0000.0000.000
세목명0.2970.0000.3270.0850.0001.0000.000
체납액구간0.0000.4590.0000.2940.0000.0001.000

Missing values

2024-01-10T07:36:00.884399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:36:01.011066image/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
53충청남도서천군447702019지방소득세1백만원~3백만원미만8150081701425708390
54충청남도서천군447702019지방소득세1천만원~3천만원미만111052700111052700
55충청남도서천군447702019지방소득세30만원~50만원미만4148472093505580
56충청남도서천군447702019지방소득세3백만원~5백만원미만28131240312817710
57충청남도서천군447702019지방소득세50만원~1백만원미만1389135803727173210
58충청남도서천군447702019지방소득세5백만원~1천만원미만19959570215628260
59충청남도서천군447702019취득세1천만원~3천만원미만122206410249277560
60충청남도서천군447702019취득세30만원~50만원미만13343002662210
61충청남도서천군447702019취득세5백만원~1천만원미만1726587017265870
62충청남도서천군447702019취득세5천만원~1억원미만188793280188793280