Overview

Dataset statistics

Number of variables11
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory97.0 B

Variable types

Categorical7
Numeric4

Dataset

Description경상남도 사천시 지방세 체납 현황(2018 ~ 2020년)에 대한 데이터로 체납액 규모별 체납 건수를 납세자 유형별로 제공합니다.
URLhttps://www.data.go.kr/data/15079596/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
데이터기준일자 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 23:40:08.014180
Analysis finished2023-12-12 23:40:09.780288
Duration1.77 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
경상남도
44 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 44
100.0%

Length

2023-12-13T08:40:09.852605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:40:09.943964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 44
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
사천시
44 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사천시 44
100.0%

Length

2023-12-13T08:40:10.034880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:40:10.149858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사천시 44
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
48240
44 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48240
2nd row48240
3rd row48240
4th row48240
5th row48240

Common Values

ValueCountFrequency (%)
48240 44
100.0%

Length

2023-12-13T08:40:10.244892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:40:10.342984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48240 44
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
2021
44 

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 44
100.0%

Length

2023-12-13T08:40:10.449791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:40:10.545579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 44
100.0%

세목명
Categorical

Distinct7
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size484.0 B
지방소득세
11 
재산세
10 
취득세
8 
주민세
6 
등록면허세
3 
Other values (2)
6 

Length

Max length7
Median length3
Mean length3.9772727
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 11
25.0%
재산세 10
22.7%
취득세 8
18.2%
주민세 6
13.6%
등록면허세 3
 
6.8%
자동차세 3
 
6.8%
지역자원시설세 3
 
6.8%

Length

2023-12-13T08:40:10.922299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:40:11.056999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 11
25.0%
재산세 10
22.7%
취득세 8
18.2%
주민세 6
13.6%
등록면허세 3
 
6.8%
자동차세 3
 
6.8%
지역자원시설세 3
 
6.8%

체납액구간
Categorical

Distinct11
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
10만원 미만
7 
10만원~30만원미만
7 
30만원~50만원미만
6 
3천만원~5천만원미만
4 
1백만원~3백만원미만
4 
Other values (6)
16 

Length

Max length11
Median length11
Mean length10.25
Min length7

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row10만원 미만
2nd row10만원~30만원미만
3rd row3천만원~5천만원미만
4th row10만원 미만
5th row10만원~30만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 7
15.9%
10만원~30만원미만 7
15.9%
30만원~50만원미만 6
13.6%
3천만원~5천만원미만 4
9.1%
1백만원~3백만원미만 4
9.1%
3백만원~5백만원미만 4
9.1%
50만원~1백만원미만 4
9.1%
5백만원~1천만원미만 3
6.8%
1억원~3억원미만 2
 
4.5%
1천만원~3천만원미만 2
 
4.5%

Length

2023-12-13T08:40:11.216238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 7
13.7%
미만 7
13.7%
10만원~30만원미만 7
13.7%
30만원~50만원미만 6
11.8%
3천만원~5천만원미만 4
7.8%
1백만원~3백만원미만 4
7.8%
3백만원~5백만원미만 4
7.8%
50만원~1백만원미만 4
7.8%
5백만원~1천만원미만 3
5.9%
1억원~3억원미만 2
 
3.9%
Other values (2) 3
5.9%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)61.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean263.40909
Minimum1
Maximum3723
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-13T08:40:11.332588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12.75
median9.5
Q376.25
95-th percentile1135.65
Maximum3723
Range3722
Interquartile range (IQR)73.5

Descriptive statistics

Standard deviation745.43389
Coefficient of variation (CV)2.8299475
Kurtosis14.362457
Mean263.40909
Median Absolute Deviation (MAD)8.5
Skewness3.7430071
Sum11590
Variance555671.69
MonotonicityNot monotonic
2023-12-13T08:40:11.440509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 8
18.2%
5 3
 
6.8%
8 3
 
6.8%
2 3
 
6.8%
6 3
 
6.8%
10 2
 
4.5%
37 2
 
4.5%
458 1
 
2.3%
3 1
 
2.3%
13 1
 
2.3%
Other values (17) 17
38.6%
ValueCountFrequency (%)
1 8
18.2%
2 3
 
6.8%
3 1
 
2.3%
5 3
 
6.8%
6 3
 
6.8%
8 3
 
6.8%
9 1
 
2.3%
10 2
 
4.5%
13 1
 
2.3%
17 1
 
2.3%
ValueCountFrequency (%)
3723 1
2.3%
3026 1
2.3%
1143 1
2.3%
1094 1
2.3%
1021 1
2.3%
458 1
2.3%
355 1
2.3%
109 1
2.3%
89 1
2.3%
88 1
2.3%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48214888
Minimum233310
Maximum1.863323 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-13T08:40:11.595892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum233310
5-th percentile353895
Q13731872.5
median32477310
Q370603005
95-th percentile1.349626 × 108
Maximum1.863323 × 108
Range1.8609899 × 108
Interquartile range (IQR)66871132

Descriptive statistics

Standard deviation50841530
Coefficient of variation (CV)1.0544778
Kurtosis0.44488924
Mean48214888
Median Absolute Deviation (MAD)29329840
Skewness1.1302015
Sum2.1214551 × 109
Variance2.5848612 × 1015
MonotonicityNot monotonic
2023-12-13T08:40:11.757979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
7275510 1
 
2.3%
20374020 1
 
2.3%
120089220 1
 
2.3%
105978350 1
 
2.3%
14700390 1
 
2.3%
37019780 1
 
2.3%
30464220 1
 
2.3%
35932650 1
 
2.3%
53746760 1
 
2.3%
51700920 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
233310 1
2.3%
241020 1
2.3%
335730 1
2.3%
456830 1
2.3%
894040 1
2.3%
1336850 1
2.3%
2144260 1
2.3%
2797890 1
2.3%
3497050 1
2.3%
3517030 1
2.3%
ValueCountFrequency (%)
186332300 1
2.3%
175592130 1
2.3%
135205500 1
2.3%
133586140 1
2.3%
127174500 1
2.3%
121897260 1
2.3%
120089220 1
2.3%
105978350 1
2.3%
88930340 1
2.3%
87400780 1
2.3%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean853.79545
Minimum1
Maximum11113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-13T08:40:11.911296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15.75
median31.5
Q3178.5
95-th percentile5853.65
Maximum11113
Range11112
Interquartile range (IQR)172.75

Descriptive statistics

Standard deviation2344.2084
Coefficient of variation (CV)2.7456323
Kurtosis10.762884
Mean853.79545
Median Absolute Deviation (MAD)29.5
Skewness3.3078921
Sum37567
Variance5495312.9
MonotonicityNot monotonic
2023-12-13T08:40:12.047442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 6
 
13.6%
2 4
 
9.1%
27 2
 
4.5%
13 2
 
4.5%
10 2
 
4.5%
24 1
 
2.3%
39 1
 
2.3%
5 1
 
2.3%
43 1
 
2.3%
922 1
 
2.3%
Other values (23) 23
52.3%
ValueCountFrequency (%)
1 6
13.6%
2 4
9.1%
5 1
 
2.3%
6 1
 
2.3%
10 2
 
4.5%
12 1
 
2.3%
13 2
 
4.5%
17 1
 
2.3%
18 1
 
2.3%
24 1
 
2.3%
ValueCountFrequency (%)
11113 1
2.3%
8629 1
2.3%
5969 1
2.3%
5200 1
2.3%
2181 1
2.3%
1297 1
2.3%
922 1
2.3%
374 1
2.3%
346 1
2.3%
209 1
2.3%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2197587 × 108
Minimum335730
Maximum1.0046955 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-13T08:40:12.199713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum335730
5-th percentile943484.5
Q112001795
median63947465
Q31.6647932 × 108
95-th percentile3.1325583 × 108
Maximum1.0046955 × 109
Range1.0043597 × 109
Interquartile range (IQR)1.5447753 × 108

Descriptive statistics

Standard deviation1.711814 × 108
Coefficient of variation (CV)1.4034038
Kurtosis16.020505
Mean1.2197587 × 108
Median Absolute Deviation (MAD)59626890
Skewness3.4126475
Sum5.3669385 × 109
Variance2.9303072 × 1016
MonotonicityNot monotonic
2023-12-13T08:40:12.319143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
20309130 1
 
2.3%
69657970 1
 
2.3%
120089220 1
 
2.3%
269160810 1
 
2.3%
40353520 1
 
2.3%
182628760 1
 
2.3%
79431960 1
 
2.3%
151183430 1
 
2.3%
255687490 1
 
2.3%
51700920 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
335730 1
2.3%
395520 1
2.3%
798490 1
2.3%
1765120 1
2.3%
2003230 1
2.3%
3517030 1
2.3%
4036890 1
2.3%
4604260 1
2.3%
5513560 1
2.3%
7920040 1
2.3%
ValueCountFrequency (%)
1004695470 1
2.3%
370738690 1
2.3%
316962870 1
2.3%
292249280 1
2.3%
270088990 1
2.3%
269160810 1
2.3%
255687490 1
2.3%
245284750 1
2.3%
234530000 1
2.3%
213698680 1
2.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-06-01
44 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-01
2nd row2023-06-01
3rd row2023-06-01
4th row2023-06-01
5th row2023-06-01

Common Values

ValueCountFrequency (%)
2023-06-01 44
100.0%

Length

2023-12-13T08:40:12.444552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:40:12.564684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-01 44
100.0%

Interactions

2023-12-13T08:40:09.211952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:08.253783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:08.576968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:08.908884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:09.301314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:08.334981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:08.657970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:08.984578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:09.386765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:08.423291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:08.752955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:09.059196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:09.459893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:08.497729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:08.827487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:40:09.122279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:40:12.624094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.4560.3570.4560.413
체납액구간0.0001.0000.0000.6800.0000.182
체납건수0.4560.0001.0000.7300.9970.562
체납금액0.3570.6800.7301.0000.6470.809
누적체납건수0.4560.0000.9970.6471.0000.697
누적체납금액0.4130.1820.5620.8090.6971.000
2023-12-13T08:40:12.728993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명
체납액구간1.0000.000
세목명0.0001.000
2023-12-13T08:40:12.822742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.2700.9680.4630.2830.000
체납금액0.2701.0000.2170.9190.1890.377
누적체납건수0.9680.2171.0000.4630.2830.000
누적체납금액0.4630.9190.4631.0000.2770.102
세목명0.2830.1890.2830.2771.0000.000
체납액구간0.0000.3770.0000.1020.0001.000

Missing values

2023-12-13T08:40:09.561075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:40:09.698758image/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

시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액데이터기준일자
0경상남도사천시482402021등록면허세10만원 미만45872755101297203091302023-06-01
1경상남도사천시482402021등록면허세10만원~30만원미만124102023955202023-06-01
2경상남도사천시482402021등록면허세3천만원~5천만원미만1366129201366129202023-06-01
3경상남도사천시482402021자동차세10만원 미만11435089793052002345300002023-06-01
4경상남도사천시482402021자동차세10만원~30만원미만1094186332300596910046954702023-06-01
5경상남도사천시482402021자동차세30만원~50만원미만75273172903461225304102023-06-01
6경상남도사천시482402021재산세10만원 미만30268740078086292136986802023-06-01
7경상남도사천시482402021재산세10만원~30만원미만102117559213021813707386902023-06-01
8경상남도사천시482402021재산세1백만원~3백만원미만801352055001742922492802023-06-01
9경상남도사천시482402021재산세1억원~3억원미만112189726011218972602023-06-01
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액데이터기준일자
34경상남도사천시482402021지역자원시설세10만원~30만원미만813368501320032302023-06-01
35경상남도사천시482402021지역자원시설세30만원~50만원미만133573013357302023-06-01
36경상남도사천시482402021취득세10만원 미만52333103917651202023-06-01
37경상남도사천시482402021취득세10만원~30만원미만58940402755135602023-06-01
38경상남도사천시482402021취득세1백만원~3백만원미만101846071024446013702023-06-01
39경상남도사천시482402021취득세30만원~50만원미만521442601040368902023-06-01
40경상남도사천시482402021취득세3백만원~5백만원미만62400144013510503802023-06-01
41경상남도사천시482402021취득세3천만원~5천만원미만2641558402641558402023-06-01
42경상남도사천시482402021취득세50만원~1백만원미만13962568027191736102023-06-01
43경상남도사천시482402021취득세5백만원~1천만원미만3207946705327353302023-06-01