Overview

Dataset statistics

Number of variables10
Number of observations73
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory87.8 B

Variable types

Categorical6
Numeric4

Dataset

Description제공범위 : 지방세 체납현황을 체납액 규모별로 제공. 관련 법령 : 지방세법. 소관기관 : 지방자치단체. 제공기관 : 시군구. 표준데이터 셋 제공시스템 : 표준지방세시스템. 자료기준일 : 매년 12월 31일.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=353&beforeMenuCd=DOM_000000201001001000&publicdatapk=15078703

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 21:44:48.110156
Analysis finished2024-01-09 21:44:49.688887
Duration1.58 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
충청남도
73 

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 73
100.0%

Length

2024-01-10T06:44:49.752931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:44:49.847431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 73
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
홍성군
73 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
홍성군 73
100.0%

Length

2024-01-10T06:44:49.948541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:44:50.043543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
홍성군 73
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
44800
73 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44800
2nd row44800
3rd row44800
4th row44800
5th row44800

Common Values

ValueCountFrequency (%)
44800 73
100.0%

Length

2024-01-10T06:44:50.144658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:44:50.230033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44800 73
100.0%

과세년도
Categorical

Distinct3
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size716.0 B
2019
26 
2017
24 
2018
23 

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 26
35.6%
2017 24
32.9%
2018 23
31.5%

Length

2024-01-10T06:44:50.306000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:44:50.384089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 26
35.6%
2017 24
32.9%
2018 23
31.5%

세목명
Categorical

Distinct6
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size716.0 B
지방소득세
23 
재산세
21 
주민세
10 
자동차세
9 
취득세
6 

Length

Max length5
Median length3
Mean length3.8630137
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 23
31.5%
재산세 21
28.8%
주민세 10
13.7%
자동차세 9
 
12.3%
취득세 6
 
8.2%
등록면허세 4
 
5.5%

Length

2024-01-10T06:44:50.476389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:44:50.593422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 23
31.5%
재산세 21
28.8%
주민세 10
13.7%
자동차세 9
 
12.3%
취득세 6
 
8.2%
등록면허세 4
 
5.5%

체납액구간
Categorical

Distinct9
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size716.0 B
10만원 미만
16 
10만원~30만원미만
14 
30만원~50만원미만
9 
50만원~1백만원미만
9 
1백만원~3백만원미만
8 
Other values (4)
17 

Length

Max length11
Median length11
Mean length10.109589
Min length7

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row10만원 미만
2nd row5백만원~1천만원미만
3rd row10만원 미만
4th row10만원~30만원미만
5th row30만원~50만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 16
21.9%
10만원~30만원미만 14
19.2%
30만원~50만원미만 9
12.3%
50만원~1백만원미만 9
12.3%
1백만원~3백만원미만 8
11.0%
5백만원~1천만원미만 6
 
8.2%
3백만원~5백만원미만 6
 
8.2%
1천만원~3천만원미만 4
 
5.5%
5천만원~1억원미만 1
 
1.4%

Length

2024-01-10T06:44:50.730438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:44:50.863641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 16
18.0%
미만 16
18.0%
10만원~30만원미만 14
15.7%
30만원~50만원미만 9
10.1%
50만원~1백만원미만 9
10.1%
1백만원~3백만원미만 8
9.0%
5백만원~1천만원미만 6
 
6.7%
3백만원~5백만원미만 6
 
6.7%
1천만원~3천만원미만 4
 
4.5%
5천만원~1억원미만 1
 
1.1%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)47.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.109589
Minimum1
Maximum1371
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2024-01-10T06:44:50.999324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median6
Q340
95-th percentile584.6
Maximum1371
Range1370
Interquartile range (IQR)38

Descriptive statistics

Standard deviation227.34956
Coefficient of variation (CV)2.3903957
Kurtosis15.263014
Mean95.109589
Median Absolute Deviation (MAD)5
Skewness3.6378454
Sum6943
Variance51687.821
MonotonicityNot monotonic
2024-01-10T06:44:51.124424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 13
17.8%
2 6
 
8.2%
3 6
 
8.2%
5 4
 
5.5%
4 4
 
5.5%
6 4
 
5.5%
23 3
 
4.1%
20 2
 
2.7%
104 2
 
2.7%
14 2
 
2.7%
Other values (25) 27
37.0%
ValueCountFrequency (%)
1 13
17.8%
2 6
8.2%
3 6
8.2%
4 4
 
5.5%
5 4
 
5.5%
6 4
 
5.5%
8 1
 
1.4%
11 1
 
1.4%
13 2
 
2.7%
14 2
 
2.7%
ValueCountFrequency (%)
1371 1
1.4%
876 1
1.4%
639 1
1.4%
620 1
1.4%
561 1
1.4%
409 1
1.4%
380 1
1.4%
298 1
1.4%
271 1
1.4%
224 1
1.4%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14955522
Minimum68790
Maximum1.3233919 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2024-01-10T06:44:51.477857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum68790
5-th percentile212092
Q12189880
median8027840
Q317003540
95-th percentile44910168
Maximum1.3233919 × 108
Range1.322704 × 108
Interquartile range (IQR)14813660

Descriptive statistics

Standard deviation23155065
Coefficient of variation (CV)1.548262
Kurtosis12.443817
Mean14955522
Median Absolute Deviation (MAD)6364920
Skewness3.2941625
Sum1.0917531 × 109
Variance5.3615706 × 1014
MonotonicityNot monotonic
2024-01-10T06:44:51.598072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
288900 1
 
1.4%
31363750 1
 
1.4%
31688580 1
 
1.4%
18777860 1
 
1.4%
30784810 1
 
1.4%
11940430 1
 
1.4%
95990780 1
 
1.4%
18745070 1
 
1.4%
1244400 1
 
1.4%
2777700 1
 
1.4%
Other values (63) 63
86.3%
ValueCountFrequency (%)
68790 1
1.4%
114230 1
1.4%
193960 1
1.4%
194200 1
1.4%
224020 1
1.4%
288900 1
1.4%
356030 1
1.4%
464010 1
1.4%
524220 1
1.4%
637190 1
1.4%
ValueCountFrequency (%)
132339190 1
1.4%
102813750 1
1.4%
95990780 1
1.4%
50042790 1
1.4%
41488420 1
1.4%
37941850 1
1.4%
36795800 1
1.4%
35950200 1
1.4%
31688580 1
1.4%
31363750 1
1.4%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct49
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean256.21918
Minimum1
Maximum4068
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2024-01-10T06:44:51.710386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median19
Q3101
95-th percentile1426
Maximum4068
Range4067
Interquartile range (IQR)95

Descriptive statistics

Standard deviation654.13966
Coefficient of variation (CV)2.5530472
Kurtosis18.146363
Mean256.21918
Median Absolute Deviation (MAD)16
Skewness3.9671467
Sum18704
Variance427898.7
MonotonicityNot monotonic
2024-01-10T06:44:51.826319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
2 5
 
6.8%
10 5
 
6.8%
5 4
 
5.5%
1 3
 
4.1%
6 3
 
4.1%
3 3
 
4.1%
8 3
 
4.1%
7 3
 
4.1%
14 2
 
2.7%
34 2
 
2.7%
Other values (39) 40
54.8%
ValueCountFrequency (%)
1 3
4.1%
2 5
6.8%
3 3
4.1%
4 2
 
2.7%
5 4
5.5%
6 3
4.1%
7 3
4.1%
8 3
4.1%
10 5
6.8%
12 1
 
1.4%
ValueCountFrequency (%)
4068 1
1.4%
2697 1
1.4%
1821 1
1.4%
1588 1
1.4%
1318 1
1.4%
1090 1
1.4%
968 1
1.4%
757 1
1.4%
681 1
1.4%
588 1
1.4%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29616770
Minimum121710
Maximum2.252032 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2024-01-10T06:44:51.940878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum121710
5-th percentile870974
Q15522230
median18340300
Q338186220
95-th percentile1.0303194 × 108
Maximum2.252032 × 108
Range2.2508149 × 108
Interquartile range (IQR)32663990

Descriptive statistics

Standard deviation38006662
Coefficient of variation (CV)1.2832818
Kurtosis9.7461413
Mean29616770
Median Absolute Deviation (MAD)15686050
Skewness2.7059921
Sum2.1620242 × 109
Variance1.4445063 × 1015
MonotonicityNot monotonic
2024-01-10T06:44:52.043681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
638410 1
 
1.4%
67474840 1
 
1.4%
62200730 1
 
1.4%
43631720 1
 
1.4%
94457610 1
 
1.4%
19635350 1
 
1.4%
225203200 1
 
1.4%
49586900 1
 
1.4%
2522280 1
 
1.4%
7184670 1
 
1.4%
Other values (63) 63
86.3%
ValueCountFrequency (%)
121710 1
1.4%
356030 1
1.4%
638410 1
1.4%
783980 1
1.4%
928970 1
1.4%
1008000 1
1.4%
1123170 1
1.4%
1277880 1
1.4%
1280000 1
1.4%
1341380 1
1.4%
ValueCountFrequency (%)
225203200 1
1.4%
132339190 1
1.4%
129212420 1
1.4%
115893430 1
1.4%
94457610 1
1.4%
79674640 1
1.4%
79169630 1
1.4%
67474840 1
1.4%
65912040 1
1.4%
63672800 1
1.4%

Interactions

2024-01-10T06:44:49.179967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:48.358904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:48.640474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:48.906518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:49.261472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:48.430846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:48.707547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:48.975081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:49.332289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:48.507175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:48.773936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:49.044704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:49.401074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:48.579250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:48.843262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:49.115101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:44:52.111750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0480.5180.1640.325
세목명0.0001.0000.0000.3660.0000.3450.212
체납액구간0.0000.0001.0000.0000.7420.0000.448
체납건수0.0480.3660.0001.0000.5470.9590.724
체납금액0.5180.0000.7420.5471.0000.3660.800
누적체납건수0.1640.3450.0000.9590.3661.0000.878
누적체납금액0.3250.2120.4480.7240.8000.8781.000
2024-01-10T06:44:52.194983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도체납액구간세목명
과세년도1.0000.0000.000
체납액구간0.0001.0000.000
세목명0.0000.0001.000
2024-01-10T06:44:52.265143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.3280.9660.3740.0000.1360.000
체납금액0.3281.0000.2010.9530.2470.0000.470
누적체납건수0.9660.2011.0000.3000.1020.2090.000
누적체납금액0.3740.9530.3001.0000.2300.1310.251
과세년도0.0000.2470.1020.2301.0000.0000.000
세목명0.1360.0000.2090.1310.0001.0000.000
체납액구간0.0000.4700.0000.2510.0000.0001.000

Missing values

2024-01-10T06:44:49.488291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:44:49.634267image/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
0충청남도홍성군448002017등록면허세10만원 미만2228890059638410
1충청남도홍성군448002017등록면허세5백만원~1천만원미만217128510217128510
2충청남도홍성군448002017자동차세10만원 미만136613681045719968970
3충청남도홍성군448002017자동차세10만원~30만원미만1743046817045979169630
4충청남도홍성군448002017자동차세30만원~50만원미만51662920103265620
5충청남도홍성군448002017재산세10만원 미만63913959360182142756350
6충청남도홍성군448002017재산세10만원~30만원미만34565476010116224170
7충청남도홍성군448002017재산세1백만원~3백만원미만480278401422104490
8충청남도홍성군448002017재산세1천만원~3천만원미만110033890220973500
9충청남도홍성군448002017재산세30만원~50만원미만62276570207722180
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
63충청남도홍성군448002019지방소득세10만원~30만원미만3160060508315165040
64충청남도홍성군448002019지방소득세1백만원~3백만원미만23367958003555136100
65충청남도홍성군448002019지방소득세1천만원~3천만원미만61028137507115893430
66충청남도홍성군448002019지방소득세30만원~50만원미만2392756302911929880
67충청남도홍성군448002019지방소득세3백만원~5백만원미만4142609201452905480
68충청남도홍성군448002019지방소득세50만원~1백만원미만27190395904632612150
69충청남도홍성군448002019지방소득세5백만원~1천만원미만5414884201079674640
70충청남도홍성군448002019지방소득세5천만원~1억원미만21323391902132339190
71충청남도홍성군448002019취득세10만원~30만원미만122402061008000
72충청남도홍성군448002019취득세1천만원~3천만원미만235950200235950200