Overview

Dataset statistics

Number of variables10
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory89.9 B

Variable types

Categorical6
Numeric4

Dataset

Description충청북도 옥천군의 체납액 규모별 체납 건수를 납세자 유형별(세목명, 체납액구간, 체납건수, 체납금액 등)로 제공합니다.
Author충청북도 옥천군
URLhttps://www.data.go.kr/data/15078508/fileData.do

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 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 started2023-12-12 16:12:13.673966
Analysis finished2023-12-12 16:12:15.878389
Duration2.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
충청북도
34 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청북도 34
100.0%

Length

2023-12-13T01:12:15.956328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:12:16.090337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청북도 34
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
옥천군
34 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
옥천군 34
100.0%

Length

2023-12-13T01:12:16.239459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:12:16.367305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
옥천군 34
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
43730
34 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row43730
2nd row43730
3rd row43730
4th row43730
5th row43730

Common Values

ValueCountFrequency (%)
43730 34
100.0%

Length

2023-12-13T01:12:16.522669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:12:16.649377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
43730 34
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
2021
34 

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 34
100.0%

Length

2023-12-13T01:12:16.782755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:12:16.928967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 34
100.0%

세목명
Categorical

Distinct7
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size404.0 B
지방소득세
10 
재산세
8 
취득세
6 
주민세
5 
자동차세
3 
Other values (2)
2 

Length

Max length7
Median length3
Mean length3.8529412
Min length3

Unique

Unique2 ?
Unique (%)5.9%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 10
29.4%
재산세 8
23.5%
취득세 6
17.6%
주민세 5
14.7%
자동차세 3
 
8.8%
등록면허세 1
 
2.9%
지역자원시설세 1
 
2.9%

Length

2023-12-13T01:12:17.094255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:12:17.247578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 10
29.4%
재산세 8
23.5%
취득세 6
17.6%
주민세 5
14.7%
자동차세 3
 
8.8%
등록면허세 1
 
2.9%
지역자원시설세 1
 
2.9%

체납액구간
Categorical

Distinct10
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Memory size404.0 B
10만원 미만
7 
10만원~30만원미만
5 
30만원~50만원미만
4 
1백만원~3백만원미만
4 
50만원~1백만원미만
4 
Other values (5)
10 

Length

Max length11
Median length11
Mean length10.147059
Min length7

Unique

Unique2 ?
Unique (%)5.9%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 7
20.6%
10만원~30만원미만 5
14.7%
30만원~50만원미만 4
11.8%
1백만원~3백만원미만 4
11.8%
50만원~1백만원미만 4
11.8%
5백만원~1천만원미만 4
11.8%
1천만원~3천만원미만 2
 
5.9%
3백만원~5백만원미만 2
 
5.9%
3천만원~5천만원미만 1
 
2.9%
5천만원~1억원미만 1
 
2.9%

Length

2023-12-13T01:12:17.406947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:12:17.594521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 7
17.1%
미만 7
17.1%
10만원~30만원미만 5
12.2%
30만원~50만원미만 4
9.8%
1백만원~3백만원미만 4
9.8%
50만원~1백만원미만 4
9.8%
5백만원~1천만원미만 4
9.8%
1천만원~3천만원미만 2
 
4.9%
3백만원~5백만원미만 2
 
4.9%
3천만원~5천만원미만 1
 
2.4%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)67.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117.94118
Minimum1
Maximum2257
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T01:12:17.760349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12.25
median7.5
Q320.75
95-th percentile472.35
Maximum2257
Range2256
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation404.99472
Coefficient of variation (CV)3.4338704
Kurtosis25.291561
Mean117.94118
Median Absolute Deviation (MAD)6.5
Skewness4.8812436
Sum4010
Variance164020.72
MonotonicityNot monotonic
2023-12-13T01:12:17.889655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 7
20.6%
3 4
 
11.8%
2 2
 
5.9%
4 2
 
5.9%
58 1
 
2.9%
7 1
 
2.9%
8 1
 
2.9%
5 1
 
2.9%
17 1
 
2.9%
22 1
 
2.9%
Other values (13) 13
38.2%
ValueCountFrequency (%)
1 7
20.6%
2 2
 
5.9%
3 4
11.8%
4 2
 
5.9%
5 1
 
2.9%
7 1
 
2.9%
8 1
 
2.9%
9 1
 
2.9%
10 1
 
2.9%
11 1
 
2.9%
ValueCountFrequency (%)
2257 1
2.9%
798 1
2.9%
297 1
2.9%
196 1
2.9%
105 1
2.9%
104 1
2.9%
58 1
2.9%
32 1
2.9%
22 1
2.9%
17 1
2.9%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14583353
Minimum27430
Maximum52556870
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T01:12:18.036951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27430
5-th percentile607546
Q13801742.5
median10511925
Q320519278
95-th percentile43886713
Maximum52556870
Range52529440
Interquartile range (IQR)16717535

Descriptive statistics

Standard deviation14733782
Coefficient of variation (CV)1.0103152
Kurtosis0.35283227
Mean14583353
Median Absolute Deviation (MAD)8052250
Skewness1.1459609
Sum4.9583399 × 108
Variance2.1708435 × 1014
MonotonicityNot monotonic
2023-12-13T01:12:18.209099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
948450 1
 
2.9%
52556870 1
 
2.9%
44902130 1
 
2.9%
8166580 1
 
2.9%
16548830 1
 
2.9%
43339950 1
 
2.9%
11808660 1
 
2.9%
41050250 1
 
2.9%
27430 1
 
2.9%
6031960 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
27430 1
2.9%
587760 1
2.9%
618200 1
2.9%
948450 1
2.9%
1040650 1
2.9%
1115740 1
2.9%
1260260 1
2.9%
1671870 1
2.9%
3644870 1
2.9%
4272360 1
2.9%
ValueCountFrequency (%)
52556870 1
2.9%
44902130 1
2.9%
43339950 1
2.9%
41050250 1
2.9%
33801820 1
2.9%
32577740 1
2.9%
26880160 1
2.9%
25265710 1
2.9%
21433580 1
2.9%
17776370 1
2.9%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean394.64706
Minimum1
Maximum7420
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T01:12:18.361791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q18.5
median26.5
Q359.5
95-th percentile1681.8
Maximum7420
Range7419
Interquartile range (IQR)51

Descriptive statistics

Standard deviation1321.0017
Coefficient of variation (CV)3.3472991
Kurtosis25.890294
Mean394.64706
Median Absolute Deviation (MAD)22
Skewness4.9051225
Sum13418
Variance1745045.6
MonotonicityNot monotonic
2023-12-13T01:12:18.507803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 3
 
8.8%
3 2
 
5.9%
29 2
 
5.9%
4 1
 
2.9%
10 1
 
2.9%
26 1
 
2.9%
2 1
 
2.9%
11 1
 
2.9%
314 1
 
2.9%
18 1
 
2.9%
Other values (20) 20
58.8%
ValueCountFrequency (%)
1 3
8.8%
2 1
 
2.9%
3 2
5.9%
4 1
 
2.9%
5 1
 
2.9%
8 1
 
2.9%
10 1
 
2.9%
11 1
 
2.9%
13 1
 
2.9%
18 1
 
2.9%
ValueCountFrequency (%)
7420 1
2.9%
1973 1
2.9%
1525 1
2.9%
1186 1
2.9%
314 1
2.9%
217 1
2.9%
169 1
2.9%
91 1
2.9%
60 1
2.9%
58 1
2.9%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45302414
Minimum60550
Maximum2.1988259 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T01:12:19.036469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60550
5-th percentile1571058
Q110241090
median23003100
Q351706475
95-th percentile1.5515793 × 108
Maximum2.1988259 × 108
Range2.1982204 × 108
Interquartile range (IQR)41465385

Descriptive statistics

Standard deviation54002931
Coefficient of variation (CV)1.1920541
Kurtosis3.807508
Mean45302414
Median Absolute Deviation (MAD)18030765
Skewness1.9667499
Sum1.5402821 × 109
Variance2.9163165 × 1015
MonotonicityNot monotonic
2023-12-13T01:12:19.218569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
2620270 1
 
2.9%
52556870 1
 
2.9%
219882590 1
 
2.9%
14161760 1
 
2.9%
108930120 1
 
2.9%
43339950 1
 
2.9%
40392260 1
 
2.9%
129584830 1
 
2.9%
60550 1
 
2.9%
16199810 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
60550 1
2.9%
1405230 1
2.9%
1660350 1
2.9%
2620270 1
2.9%
4330730 1
2.9%
5691010 1
2.9%
6720020 1
2.9%
9115410 1
2.9%
9716430 1
2.9%
11815070 1
2.9%
ValueCountFrequency (%)
219882590 1
2.9%
202650820 1
2.9%
129584830 1
2.9%
108930120 1
2.9%
106243300 1
2.9%
95389220 1
2.9%
70830000 1
2.9%
66102080 1
2.9%
52556870 1
2.9%
49155290 1
2.9%

Interactions

2023-12-13T01:12:15.117345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:13.961533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:14.329419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:14.693159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:15.236576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:14.047404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:14.413156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:14.776154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:15.348368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:14.139096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:14.498919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:14.860471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:15.456521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:14.233748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:14.597787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:15.011723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:12:19.332973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.2120.0000.3110.000
체납액구간0.0001.0000.0000.8200.0000.251
체납건수0.2120.0001.0000.1780.9780.534
체납금액0.0000.8200.1781.0000.6960.851
누적체납건수0.3110.0000.9780.6961.0000.608
누적체납금액0.0000.2510.5340.8510.6081.000
2023-12-13T01:12:19.462153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명
체납액구간1.0000.000
세목명0.0001.000
2023-12-13T01:12:19.555711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.1060.9440.1190.1170.000
체납금액0.1061.0000.0240.8790.0000.383
누적체납건수0.9440.0241.0000.1580.1930.000
누적체납금액0.1190.8790.1581.0000.0000.107
세목명0.1170.0000.1930.0001.0000.000
체납액구간0.0000.3830.0000.1070.0001.000

Missing values

2023-12-13T01:12:15.619132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:12:15.818990image/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
0충청북도옥천군437302021등록면허세10만원 미만589484501692620270
1충청북도옥천군437302021자동차세10만원 미만29712671070152566102080
2충청북도옥천군437302021자동차세10만원~30만원미만196325777401186202650820
3충청북도옥천군437302021자동차세30만원~50만원미만1245601604215249010
4충청북도옥천군437302021재산세10만원 미만225733801820742095389220
5충청북도옥천군437302021재산세10만원~30만원미만1041777637021736225130
6충청북도옥천군437302021재산세1백만원~3백만원미만10170066704070830000
7충청북도옥천군437302021재산세1천만원~3천만원미만121433580349155290
8충청북도옥천군437302021재산세30만원~50만원미만1145493502911815070
9충청북도옥천군437302021재산세3백만원~5백만원미만312984990521946030
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
24충청북도옥천군437302021지방소득세50만원~1백만원미만17118086605840392260
25충청북도옥천군437302021지방소득세5백만원~1천만원미만54105025018129584830
26충청북도옥천군437302021지방소득세5천만원~1억원미만152556870152556870
27충청북도옥천군437302021지역자원시설세10만원 미만127430260550
28충청북도옥천군437302021취득세10만원 미만8587760261405230
29충청북도옥천군437302021취득세10만원~30만원미만3618200295691010
30충청북도옥천군437302021취득세1백만원~3백만원미만242723601017419410
31충청북도옥천군437302021취득세30만원~50만원미만3126026041660350
32충청북도옥천군437302021취득세50만원~1백만원미만21115740116720020
33충청북도옥천군437302021취득세5백만원~1천만원미만15657880324060170