Overview

Dataset statistics

Number of variables10
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory89.7 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
과세년도 has constant value ""Constant
체납건수 is highly overall correlated with 누적체납건수High correlation
체납금액 is highly overall correlated with 누적체납금액 and 1 other fieldsHigh correlation
누적체납건수 is highly overall correlated with 체납건수High correlation
누적체납금액 is highly overall correlated with 체납금액High correlation
체납액구간 is highly overall correlated with 체납금액High correlation
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:44:44.059126
Analysis finished2024-01-09 21:44:45.440798
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
충청남도
36 

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 36
100.0%

Length

2024-01-10T06:44:45.490446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:44:45.562802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 36
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
홍성군
36 

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 36
100.0%

Length

2024-01-10T06:44:45.637862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:44:45.709693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
홍성군 36
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
44800
36 

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 36
100.0%

Length

2024-01-10T06:44:45.782872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:44:45.859090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44800 36
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2021
36 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 36
100.0%

Length

2024-01-10T06:44:45.934771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:44:46.007005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 36
100.0%

세목명
Categorical

Distinct7
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
지방소득세
11 
재산세
8 
취득세
6 
자동차세
4 
주민세
4 
Other values (2)
3 

Length

Max length7
Median length6
Mean length3.9444444
Min length3

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 11
30.6%
재산세 8
22.2%
취득세 6
16.7%
자동차세 4
 
11.1%
주민세 4
 
11.1%
등록면허세 2
 
5.6%
지역자원시설세 1
 
2.8%

Length

2024-01-10T06:44:46.097045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:44:46.210684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 11
30.6%
재산세 8
22.2%
취득세 6
16.7%
자동차세 4
 
11.1%
주민세 4
 
11.1%
등록면허세 2
 
5.6%
지역자원시설세 1
 
2.8%

체납액구간
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
10만원 미만
6 
50만원~1백만원미만
6 
10만원~30만원미만
6 
30만원~50만원미만
4 
1백만원~3백만원미만
4 
Other values (6)
10 

Length

Max length11
Median length11
Mean length10.25
Min length7

Unique

Unique3 ?
Unique (%)8.3%

Sample

1st row10만원 미만
2nd row50만원~1백만원미만
3rd row10만원 미만
4th row10만원~30만원미만
5th row30만원~50만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 6
16.7%
50만원~1백만원미만 6
16.7%
10만원~30만원미만 6
16.7%
30만원~50만원미만 4
11.1%
1백만원~3백만원미만 4
11.1%
5백만원~1천만원미만 3
8.3%
1천만원~3천만원미만 2
 
5.6%
3백만원~5백만원미만 2
 
5.6%
1억원~3억원미만 1
 
2.8%
3천만원~5천만원미만 1
 
2.8%

Length

2024-01-10T06:44:46.564130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 6
14.3%
미만 6
14.3%
50만원~1백만원미만 6
14.3%
10만원~30만원미만 6
14.3%
30만원~50만원미만 4
9.5%
1백만원~3백만원미만 4
9.5%
5백만원~1천만원미만 3
7.1%
1천만원~3천만원미만 2
 
4.8%
3백만원~5백만원미만 2
 
4.8%
1억원~3억원미만 1
 
2.4%
Other values (2) 2
 
4.8%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean177.02778
Minimum1
Maximum2332
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-01-10T06:44:46.655291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.75
median12.5
Q352.25
95-th percentile878.75
Maximum2332
Range2331
Interquartile range (IQR)48.5

Descriptive statistics

Standard deviation470.81337
Coefficient of variation (CV)2.6595452
Kurtosis14.412645
Mean177.02778
Median Absolute Deviation (MAD)11.5
Skewness3.7236378
Sum6373
Variance221665.23
MonotonicityNot monotonic
2024-01-10T06:44:46.740427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 6
 
16.7%
5 3
 
8.3%
3 2
 
5.6%
18 2
 
5.6%
6 2
 
5.6%
242 1
 
2.8%
13 1
 
2.8%
47 1
 
2.8%
2 1
 
2.8%
44 1
 
2.8%
Other values (16) 16
44.4%
ValueCountFrequency (%)
1 6
16.7%
2 1
 
2.8%
3 2
 
5.6%
4 1
 
2.8%
5 3
8.3%
6 2
 
5.6%
8 1
 
2.8%
10 1
 
2.8%
12 1
 
2.8%
13 1
 
2.8%
ValueCountFrequency (%)
2332 1
2.8%
1589 1
2.8%
642 1
2.8%
524 1
2.8%
341 1
2.8%
242 1
2.8%
202 1
2.8%
80 1
2.8%
53 1
2.8%
52 1
2.8%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41694563
Minimum161770
Maximum2.4942237 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-01-10T06:44:46.840249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum161770
5-th percentile563820
Q14050115
median23088660
Q363788245
95-th percentile1.2960919 × 108
Maximum2.4942237 × 108
Range2.492606 × 108
Interquartile range (IQR)59738130

Descriptive statistics

Standard deviation52269180
Coefficient of variation (CV)1.253621
Kurtosis6.2826155
Mean41694563
Median Absolute Deviation (MAD)22255035
Skewness2.1835263
Sum1.5010043 × 109
Variance2.7320672 × 1015
MonotonicityNot monotonic
2024-01-10T06:44:46.943143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
2826390 1
 
2.8%
15105560 1
 
2.8%
249422370 1
 
2.8%
152596860 1
 
2.8%
17048120 1
 
2.8%
72113580 1
 
2.8%
77018770 1
 
2.8%
32056390 1
 
2.8%
121946630 1
 
2.8%
89289890 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
161770 1
2.8%
259770 1
2.8%
665170 1
2.8%
709160 1
2.8%
958090 1
2.8%
1087490 1
2.8%
2310270 1
2.8%
2826390 1
2.8%
3919360 1
2.8%
4093700 1
2.8%
ValueCountFrequency (%)
249422370 1
2.8%
152596860 1
2.8%
121946630 1
2.8%
90008580 1
2.8%
89289890 1
2.8%
77018770 1
2.8%
72113580 1
2.8%
71182070 1
2.8%
69401920 1
2.8%
61917020 1
2.8%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean438.75
Minimum1
Maximum6543
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-01-10T06:44:47.037363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17.75
median27.5
Q3109.25
95-th percentile2140.25
Maximum6543
Range6542
Interquartile range (IQR)101.5

Descriptive statistics

Standard deviation1225.5589
Coefficient of variation (CV)2.7932967
Kurtosis18.4469
Mean438.75
Median Absolute Deviation (MAD)26
Skewness4.0883683
Sum15795
Variance1501994.6
MonotonicityNot monotonic
2024-01-10T06:44:47.128911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4 3
 
8.3%
1 3
 
8.3%
8 2
 
5.6%
12 2
 
5.6%
2 1
 
2.8%
10 1
 
2.8%
11 1
 
2.8%
29 1
 
2.8%
96 1
 
2.8%
3 1
 
2.8%
Other values (20) 20
55.6%
ValueCountFrequency (%)
1 3
8.3%
2 1
 
2.8%
3 1
 
2.8%
4 3
8.3%
7 1
 
2.8%
8 2
5.6%
10 1
 
2.8%
11 1
 
2.8%
12 2
5.6%
13 1
 
2.8%
ValueCountFrequency (%)
6543 1
2.8%
3089 1
2.8%
1824 1
2.8%
1696 1
2.8%
614 1
2.8%
507 1
2.8%
462 1
2.8%
177 1
2.8%
119 1
2.8%
106 1
2.8%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86540479
Minimum337540
Maximum4.4378911 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-01-10T06:44:47.234573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum337540
5-th percentile698162.5
Q17910390
median45323990
Q31.2689114 × 108
95-th percentile2.9065166 × 108
Maximum4.4378911 × 108
Range4.4345157 × 108
Interquartile range (IQR)1.1898075 × 108

Descriptive statistics

Standard deviation1.0427389 × 108
Coefficient of variation (CV)1.2049146
Kurtosis3.0444751
Mean86540479
Median Absolute Deviation (MAD)44040405
Skewness1.7048456
Sum3.1154572 × 109
Variance1.0873043 × 1016
MonotonicityNot monotonic
2024-01-10T06:44:47.339341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
6102930 1
 
2.8%
32816780 1
 
2.8%
249422370 1
 
2.8%
443789110 1
 
2.8%
27818110 1
 
2.8%
153535310 1
 
2.8%
109428160 1
 
2.8%
66340400 1
 
2.8%
207038460 1
 
2.8%
283190100 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
337540 1
2.8%
665170 1
2.8%
709160 1
2.8%
1038920 1
2.8%
1437520 1
2.8%
2200370 1
2.8%
3678090 1
2.8%
6102930 1
2.8%
7316090 1
2.8%
8108490 1
2.8%
ValueCountFrequency (%)
443789110 1
2.8%
313036340 1
2.8%
283190100 1
2.8%
249422370 1
2.8%
207038460 1
2.8%
153535310 1
2.8%
152779960 1
2.8%
151611790 1
2.8%
129262110 1
2.8%
126100820 1
2.8%

Interactions

2024-01-10T06:44:44.996837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:44.263685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:44.503702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:44.744844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:45.067366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:44.322446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:44.561515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:44.802029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:45.138438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:44.384750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:44.621084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:44.867628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:45.208671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:44.446131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:44.682862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:44:44.931602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:44:47.404212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.4940.0000.4710.000
체납액구간0.0001.0000.0000.7900.0000.791
체납건수0.4940.0001.0000.0001.0000.485
체납금액0.0000.7900.0001.0000.0790.966
누적체납건수0.4710.0001.0000.0791.0000.620
누적체납금액0.0000.7910.4850.9660.6201.000
2024-01-10T06:44:47.494051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명
체납액구간1.0000.000
세목명0.0001.000
2024-01-10T06:44:47.561018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.2400.9880.3010.3260.000
체납금액0.2401.0000.2350.9800.0000.504
누적체납건수0.9880.2351.0000.3170.3190.000
누적체납금액0.3010.9800.3171.0000.0000.491
세목명0.3260.0000.3190.0001.0000.000
체납액구간0.0000.5040.0000.4910.0001.000

Missing values

2024-01-10T06:44:45.292737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:44:45.399113image/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
0충청남도홍성군448002021등록면허세10만원 미만24228263905076102930
1충청남도홍성군448002021등록면허세50만원~1백만원미만16651701665170
2충청남도홍성군448002021자동차세10만원 미만64225930400169674986220
3충청남도홍성군448002021자동차세10만원~30만원미만524900085801824313036340
4충청남도홍성군448002021자동차세30만원~50만원미만2383535008128812460
5충청남도홍성군448002021자동차세50만원~1백만원미만17091601709160
6충청남도홍성군448002021재산세10만원 미만2332545642906543151611790
7충청남도홍성군448002021재산세10만원~30만원미만34156033440614100326180
8충청남도홍성군448002021재산세1백만원~3백만원미만386191702080129262110
9충청남도홍성군448002021재산세1천만원~3천만원미만4694019207110255150
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
26충청남도홍성군448002021지방소득세50만원~1백만원미만47320563909666340400
27충청남도홍성군448002021지방소득세5백만원~1천만원미만1812194663029207038460
28충청남도홍성군448002021지방소득세5천만원~1억원미만1892898904283190100
29충청남도홍성군448002021지역자원시설세10만원~30만원미만125977041038920
30충청남도홍성군448002021취득세10만원 미만31617708337540
31충청남도홍성군448002021취득세10만원~30만원미만5958090122200370
32충청남도홍성군448002021취득세1백만원~3백만원미만568067901115079980
33충청남도홍성군448002021취득세30만원~50만원미만3108749041437520
34충청남도홍성군448002021취득세50만원~1백만원미만53919360107316090
35충청남도홍성군448002021취득세5백만원~1천만원미만17155240216731990