Overview

Dataset statistics

Number of variables10
Number of observations45
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory88.9 B

Variable types

Categorical4
Numeric5
DateTime1

Dataset

Description○ 과세액 중 비과세액과 감면액이 차지하는 비율 현황 제공(세목명, 과세년도, 비과세금액, 감면금액, 부과금액, 비과세감면율)- 국민 조세 혜택 규모를 파악하는데 사용
Author세종특별자치시
URLhttps://www.data.go.kr/data/15080354/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
비과세금액 is highly overall correlated with 감면금액 and 2 other fieldsHigh correlation
감면금액 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 비과세금액 and 1 other fieldsHigh correlation
세목명 is highly overall correlated with 부과금액High correlation
감면금액 has unique valuesUnique
비과세금액 has 9 (20.0%) zerosZeros
부과금액 has 3 (6.7%) zerosZeros
비과세감면율 has 8 (17.8%) zerosZeros

Reproduction

Analysis started2023-12-12 20:08:41.965388
Analysis finished2023-12-12 20:08:45.506064
Duration3.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
세종특별자치시
45 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세종특별자치시 45
100.0%

Length

2023-12-13T05:08:45.569498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:08:45.675162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세종특별자치시 45
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
세종특별자치시
45 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세종특별자치시 45
100.0%

Length

2023-12-13T05:08:45.796153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:08:45.913209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세종특별자치시 45
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
36110
45 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row36110
2nd row36110
3rd row36110
4th row36110
5th row36110

Common Values

ValueCountFrequency (%)
36110 45
100.0%

Length

2023-12-13T05:08:46.028734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:08:46.164448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
36110 45
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size492.0 B
재산세
6 
주민세
6 
취득세
6 
자동차세
6 
등록면허세
6 
Other values (3)
15 

Length

Max length7
Median length3
Mean length3.9333333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row등록세
2nd row재산세
3rd row주민세
4th row취득세
5th row자동차세

Common Values

ValueCountFrequency (%)
재산세 6
13.3%
주민세 6
13.3%
취득세 6
13.3%
자동차세 6
13.3%
등록면허세 6
13.3%
지역자원시설세 6
13.3%
교육세 5
11.1%
등록세 4
8.9%

Length

2023-12-13T05:08:46.281742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:08:46.419042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 6
13.3%
주민세 6
13.3%
취득세 6
13.3%
자동차세 6
13.3%
등록면허세 6
13.3%
지역자원시설세 6
13.3%
교육세 5
11.1%
등록세 4
8.9%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.5333
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-13T05:08:46.578357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2020
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7267942
Coefficient of variation (CV)0.00085504615
Kurtosis-1.2763115
Mean2019.5333
Median Absolute Deviation (MAD)2
Skewness-0.0034490255
Sum90879
Variance2.9818182
MonotonicityIncreasing
2023-12-13T05:08:46.691445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2018 8
17.8%
2020 8
17.8%
2022 8
17.8%
2017 7
15.6%
2019 7
15.6%
2021 7
15.6%
ValueCountFrequency (%)
2017 7
15.6%
2018 8
17.8%
2019 7
15.6%
2020 8
17.8%
2021 7
15.6%
2022 8
17.8%
ValueCountFrequency (%)
2022 8
17.8%
2021 7
15.6%
2020 8
17.8%
2019 7
15.6%
2018 8
17.8%
2017 7
15.6%

비과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.5863565 × 109
Minimum0
Maximum5.5427424 × 1010
Zeros9
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-13T05:08:46.810319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q134737000
median1.55974 × 108
Q31.4300792 × 1010
95-th percentile4.1002497 × 1010
Maximum5.5427424 × 1010
Range5.5427424 × 1010
Interquartile range (IQR)1.4266055 × 1010

Descriptive statistics

Standard deviation1.5177272 × 1010
Coefficient of variation (CV)1.7676033
Kurtosis1.5342464
Mean8.5863565 × 109
Median Absolute Deviation (MAD)1.55974 × 108
Skewness1.6605897
Sum3.8638604 × 1011
Variance2.3034958 × 1020
MonotonicityNot monotonic
2023-12-13T05:08:46.954114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 9
 
20.0%
157541000 1
 
2.2%
28447223000 1
 
2.2%
130518000 1
 
2.2%
1132986000 1
 
2.2%
1446651000 1
 
2.2%
41579845000 1
 
2.2%
259869000 1
 
2.2%
16853457000 1
 
2.2%
28803000 1
 
2.2%
Other values (27) 27
60.0%
ValueCountFrequency (%)
0 9
20.0%
28803000 1
 
2.2%
31321000 1
 
2.2%
34737000 1
 
2.2%
40516000 1
 
2.2%
42010000 1
 
2.2%
60983000 1
 
2.2%
68954000 1
 
2.2%
95916000 1
 
2.2%
108356000 1
 
2.2%
ValueCountFrequency (%)
55427424000 1
2.2%
42287705000 1
2.2%
41579845000 1
2.2%
38693107000 1
2.2%
36284164000 1
2.2%
33436611000 1
2.2%
31241312000 1
2.2%
28447223000 1
2.2%
18447723000 1
2.2%
17386664000 1
2.2%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.991358 × 109
Minimum1000
Maximum3.4467712 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-13T05:08:47.100927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile8400
Q12.19595 × 108
median4.77036 × 108
Q32.1313583 × 1010
95-th percentile2.8204518 × 1010
Maximum3.4467712 × 1010
Range3.4467711 × 1010
Interquartile range (IQR)2.1093988 × 1010

Descriptive statistics

Standard deviation1.1293793 × 1010
Coefficient of variation (CV)1.6153933
Kurtosis-0.3306114
Mean6.991358 × 109
Median Absolute Deviation (MAD)4.45222 × 108
Skewness1.211375
Sum3.1461111 × 1011
Variance1.2754976 × 1020
MonotonicityNot monotonic
2023-12-13T05:08:47.248096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
5685000 1
 
2.2%
919777000 1
 
2.2%
343598000 1
 
2.2%
29444165000 1
 
2.2%
922258000 1
 
2.2%
477036000 1
 
2.2%
233940000 1
 
2.2%
6000 1
 
2.2%
26221729000 1
 
2.2%
339101000 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
1000 1
2.2%
5000 1
2.2%
6000 1
2.2%
18000 1
2.2%
168000 1
2.2%
2282000 1
2.2%
2641000 1
2.2%
5685000 1
2.2%
96328000 1
2.2%
182562000 1
2.2%
ValueCountFrequency (%)
34467712000 1
2.2%
29444165000 1
2.2%
28666771000 1
2.2%
26355508000 1
2.2%
26221729000 1
2.2%
24355486000 1
2.2%
24023064000 1
2.2%
22081343000 1
2.2%
21898157000 1
2.2%
21884768000 1
2.2%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct43
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.8904088 × 1010
Minimum0
Maximum3.36 × 1011
Zeros3
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-13T05:08:47.402568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile36627400
Q11.1988939 × 1010
median3.8681962 × 1010
Q36.7251851 × 1010
95-th percentile2.943906 × 1011
Maximum3.36 × 1011
Range3.36 × 1011
Interquartile range (IQR)5.5262912 × 1010

Descriptive statistics

Standard deviation9.3883666 × 1010
Coefficient of variation (CV)1.3625268
Kurtosis2.520297
Mean6.8904088 × 1010
Median Absolute Deviation (MAD)2.6843619 × 1010
Skewness1.8950817
Sum3.100684 × 1012
Variance8.8141427 × 1021
MonotonicityNot monotonic
2023-12-13T05:08:47.557044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0 3
 
6.7%
67251851000 1
 
2.2%
10347801000 1
 
2.2%
287953000000 1
 
2.2%
60062089000 1
 
2.2%
15617666000 1
 
2.2%
13319426000 1
 
2.2%
59464297000 1
 
2.2%
109111000000 1
 
2.2%
11988939000 1
 
2.2%
Other values (33) 33
73.3%
ValueCountFrequency (%)
0 3
6.7%
183137000 1
 
2.2%
7760161000 1
 
2.2%
8377157000 1
 
2.2%
8749103000 1
 
2.2%
9377573000 1
 
2.2%
10347801000 1
 
2.2%
10833784000 1
 
2.2%
11838343000 1
 
2.2%
11988939000 1
 
2.2%
ValueCountFrequency (%)
336000000000 1
2.2%
334228000000 1
2.2%
296000000000 1
2.2%
287953000000 1
2.2%
253000000000 1
2.2%
229000000000 1
2.2%
128000000000 1
2.2%
109111000000 1
2.2%
98333133000 1
2.2%
90648275000 1
2.2%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.177778
Minimum0
Maximum83
Zeros8
Zeros (%)17.8%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-13T05:08:47.692052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q317
95-th percentile66.6
Maximum83
Range83
Interquartile range (IQR)15

Descriptive statistics

Standard deviation23.091014
Coefficient of variation (CV)1.4273292
Kurtosis1.7803604
Mean16.177778
Median Absolute Deviation (MAD)5
Skewness1.7483791
Sum728
Variance533.19495
MonotonicityNot monotonic
2023-12-13T05:08:47.809182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 8
17.8%
2 6
13.3%
4 5
11.1%
5 3
 
6.7%
14 3
 
6.7%
3 3
 
6.7%
12 2
 
4.4%
20 2
 
4.4%
15 1
 
2.2%
19 1
 
2.2%
Other values (11) 11
24.4%
ValueCountFrequency (%)
0 8
17.8%
2 6
13.3%
3 3
 
6.7%
4 5
11.1%
5 3
 
6.7%
10 1
 
2.2%
12 2
 
4.4%
13 1
 
2.2%
14 3
 
6.7%
15 1
 
2.2%
ValueCountFrequency (%)
83 1
2.2%
72 1
2.2%
67 1
2.2%
65 1
2.2%
64 1
2.2%
62 1
2.2%
53 1
2.2%
26 1
2.2%
20 2
4.4%
19 1
2.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-13T05:08:47.913820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:48.007376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T05:08:44.403644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:42.290814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:42.852969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:43.353188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:43.843318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:44.493255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:42.414579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:42.938278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:43.442044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:43.943522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:44.573184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:42.531869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:43.038928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:43.531329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:44.047683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:44.674776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:42.653192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:43.155696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:43.627339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:44.157838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:44.793167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:42.765087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:43.263118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:43.730251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:08:44.275174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:08:48.093660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.6880.6320.9210.846
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.6880.0001.0000.8250.9010.822
감면금액0.6320.0000.8251.0000.9270.816
부과금액0.9210.0000.9010.9271.0000.934
비과세감면율0.8460.0000.8220.8160.9341.000
2023-12-13T05:08:48.209899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도비과세금액감면금액부과금액비과세감면율세목명
과세년도1.0000.1040.0330.1840.0210.000
비과세금액0.1041.0000.8060.5930.8480.449
감면금액0.0330.8061.0000.6990.6350.438
부과금액0.1840.5930.6991.0000.3360.566
비과세감면율0.0210.8480.6350.3361.0000.435
세목명0.0000.4490.4380.5660.4351.000

Missing values

2023-12-13T05:08:45.235605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:08:45.445088image/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

시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율데이터기준일
0세종특별자치시세종특별자치시36110등록세201705685000002022-12-31
1세종특별자치시세종특별자치시36110재산세2017334366110002208134300067251851000832022-12-31
2세종특별자치시세종특별자치시36110주민세201742010000182562000776016100032022-12-31
3세종특별자치시세종특별자치시36110취득세20171738666400024355486000336000000000122022-12-31
4세종특별자치시세종특별자치시36110자동차세2017959160008047220003868196200022022-12-31
5세종특별자치시세종특별자치시36110등록면허세2017689540005237240001350945200042022-12-31
6세종특별자치시세종특별자치시36110지역자원시설세201712857660004582040008749103000202022-12-31
7세종특별자치시세종특별자치시36110교육세2018010005082055300002022-12-31
8세종특별자치시세종특별자치시36110등록세201802282000002022-12-31
9세종특별자치시세종특별자치시36110재산세2018362841640002131358300079517055000722022-12-31
시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율데이터기준일
35세종특별자치시세종특별자치시36110등록면허세2021288030006042940001703536200042022-12-31
36세종특별자치시세종특별자치시36110지역자원시설세2021169123900026256500014447428000142022-12-31
37세종특별자치시세종특별자치시36110교육세202201680005349535100002022-12-31
38세종특별자치시세종특별자치시36110등록세202202641000002022-12-31
39세종특별자치시세종특별자치시36110재산세20225542742400026355508000128000000000642022-12-31
40세종특별자치시세종특별자치시36110주민세20221559740005194580001315351400052022-12-31
41세종특별자치시세종특별자치시36110취득세20221844772300024023064000229000000000192022-12-31
42세종특별자치시세종특별자치시36110자동차세20221673830009292890005544277900022022-12-31
43세종특별자치시세종특별자치시36110등록면허세20221395860003778610001402241700042022-12-31
44세종특별자치시세종특별자치시36110지역자원시설세2022192225900026931900014813626000152022-12-31