Overview

Dataset statistics

Number of variables9
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory83.5 B

Variable types

Categorical5
Numeric4

Dataset

Description상기 데이터는 연도별 과세액 중 비과세액과 감면액이 차지하는 비율 현황을 제공하여 국민 조세 혜택 규모를 파악하는데 사용
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=349&beforeMenuCd=DOM_000000201001001000&publicdatapk=15080020

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
비과세금액 is highly overall correlated with 감면금액 and 2 other fieldsHigh correlation
감면금액 is highly overall correlated with 비과세금액 and 3 other fieldsHigh correlation
부과금액 is highly overall correlated with 비과세금액 and 1 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 감면금액 and 1 other fieldsHigh correlation
비과세금액 has 6 (25.0%) zerosZeros
부과금액 has 3 (12.5%) zerosZeros
비과세감면율 has 6 (25.0%) zerosZeros

Reproduction

Analysis started2024-01-09 20:57:40.870994
Analysis finished2024-01-09 20:57:42.773758
Duration1.9 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
충청남도
24 

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 24
100.0%

Length

2024-01-10T05:57:42.848264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:57:42.943547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 24
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
부여군
24 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부여군 24
100.0%

Length

2024-01-10T05:57:43.039819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:57:43.134041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부여군 24
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
44760
24 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44760
2nd row44760
3rd row44760
4th row44760
5th row44760

Common Values

ValueCountFrequency (%)
44760 24
100.0%

Length

2024-01-10T05:57:43.235417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:57:43.341210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44760 24
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
교육세
3 
등록세
3 
재산세
3 
주민세
3 
취득세
3 
Other values (3)
9 

Length

Max length7
Median length3
Mean length3.875
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교육세 3
12.5%
등록세 3
12.5%
재산세 3
12.5%
주민세 3
12.5%
취득세 3
12.5%
자동차세 3
12.5%
등록면허세 3
12.5%
지역자원시설세 3
12.5%

Length

2024-01-10T05:57:43.464617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:57:43.599620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교육세 3
12.5%
등록세 3
12.5%
재산세 3
12.5%
주민세 3
12.5%
취득세 3
12.5%
자동차세 3
12.5%
등록면허세 3
12.5%
지역자원시설세 3
12.5%

과세년도
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
2017
8 
2018
8 
2019
8 

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 (%)
2017 8
33.3%
2018 8
33.3%
2019 8
33.3%

Length

2024-01-10T05:57:43.752808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:57:43.858413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 8
33.3%
2018 8
33.3%
2019 8
33.3%

비과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.4112171 × 108
Minimum0
Maximum5.013899 × 109
Zeros6
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-01-10T05:57:43.969033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13090750
median34026500
Q34.165095 × 108
95-th percentile4.7533248 × 109
Maximum5.013899 × 109
Range5.013899 × 109
Interquartile range (IQR)4.1341875 × 108

Descriptive statistics

Standard deviation1.6348282 × 109
Coefficient of variation (CV)1.9436286
Kurtosis2.5464664
Mean8.4112171 × 108
Median Absolute Deviation (MAD)34026500
Skewness1.9614409
Sum2.0186921 × 1010
Variance2.6726633 × 1018
MonotonicityNot monotonic
2024-01-10T05:57:44.099030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 6
25.0%
4612796000 1
 
4.2%
143825000 1
 
4.2%
11086000 1
 
4.2%
44600000 1
 
4.2%
1846824000 1
 
4.2%
28140000 1
 
4.2%
5013899000 1
 
4.2%
140446000 1
 
4.2%
11763000 1
 
4.2%
Other values (9) 9
37.5%
ValueCountFrequency (%)
0 6
25.0%
4121000 1
 
4.2%
11086000 1
 
4.2%
11763000 1
 
4.2%
19880000 1
 
4.2%
25350000 1
 
4.2%
28140000 1
 
4.2%
39913000 1
 
4.2%
44600000 1
 
4.2%
46049000 1
 
4.2%
ValueCountFrequency (%)
5013899000 1
4.2%
4778124000 1
4.2%
4612796000 1
4.2%
2049837000 1
4.2%
1846824000 1
4.2%
1234563000 1
4.2%
143825000 1
4.2%
140446000 1
4.2%
135705000 1
4.2%
46049000 1
4.2%

감면금액
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.62292 × 108
Minimum5000
Maximum4.606278 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-01-10T05:57:44.206017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5000
5-th percentile5000
Q114135000
median79302500
Q34.810415 × 108
95-th percentile2.4774408 × 109
Maximum4.606278 × 109
Range4.606273 × 109
Interquartile range (IQR)4.669065 × 108

Descriptive statistics

Standard deviation1.0968565 × 109
Coefficient of variation (CV)1.9506884
Kurtosis7.991955
Mean5.62292 × 108
Median Absolute Deviation (MAD)73882000
Skewness2.7651236
Sum1.3495008 × 1010
Variance1.2030941 × 1018
MonotonicityNot monotonic
2024-01-10T05:57:44.307617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
5000 3
 
12.5%
10836000 2
 
8.3%
382019000 1
 
4.2%
35823000 1
 
4.2%
135131000 1
 
4.2%
371301000 1
 
4.2%
2349135000 1
 
4.2%
788433000 1
 
4.2%
18518000 1
 
4.2%
43717000 1
 
4.2%
Other values (11) 11
45.8%
ValueCountFrequency (%)
5000 3
12.5%
10836000 2
8.3%
12266000 1
 
4.2%
14758000 1
 
4.2%
18518000 1
 
4.2%
27684000 1
 
4.2%
35823000 1
 
4.2%
43138000 1
 
4.2%
43717000 1
 
4.2%
114888000 1
 
4.2%
ValueCountFrequency (%)
4606278000 1
4.2%
2500083000 1
4.2%
2349135000 1
4.2%
788433000 1
4.2%
764206000 1
4.2%
762617000 1
4.2%
387183000 1
4.2%
382019000 1
4.2%
371301000 1
4.2%
135131000 1
4.2%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4839532 × 109
Minimum0
Maximum2.0189357 × 1010
Zeros3
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-01-10T05:57:44.414627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.909155 × 108
median3.265083 × 109
Q37.4589808 × 109
95-th percentile1.4594008 × 1010
Maximum2.0189357 × 1010
Range2.0189357 × 1010
Interquartile range (IQR)6.4680652 × 109

Descriptive statistics

Standard deviation5.8888084 × 109
Coefficient of variation (CV)1.0738254
Kurtosis0.093798522
Mean5.4839532 × 109
Median Absolute Deviation (MAD)2.563694 × 109
Skewness1.0608324
Sum1.3161488 × 1011
Variance3.4678065 × 1019
MonotonicityNot monotonic
2024-01-10T05:57:44.571232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 3
 
12.5%
5198638000 1
 
4.2%
10220831000 1
 
4.2%
888302000 1
 
4.2%
1276339000 1
 
4.2%
13646749000 1
 
4.2%
14255971000 1
 
4.2%
1278091000 1
 
4.2%
6538364000 1
 
4.2%
5357451000 1
 
4.2%
Other values (12) 12
50.0%
ValueCountFrequency (%)
0 3
12.5%
762890000 1
 
4.2%
888302000 1
 
4.2%
913517000 1
 
4.2%
1016715000 1
 
4.2%
1268721000 1
 
4.2%
1268876000 1
 
4.2%
1276339000 1
 
4.2%
1278091000 1
 
4.2%
1331528000 1
 
4.2%
ValueCountFrequency (%)
20189357000 1
4.2%
14653661000 1
4.2%
14255971000 1
4.2%
13646749000 1
4.2%
13633251000 1
4.2%
10220831000 1
4.2%
6538364000 1
4.2%
6369957000 1
4.2%
5890278000 1
4.2%
5655390000 1
4.2%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.798333
Minimum0
Maximum91.29
Zeros6
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-01-10T05:57:44.751949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.1375
median6.85
Q324.8125
95-th percentile88.476
Maximum91.29
Range91.29
Interquartile range (IQR)22.675

Descriptive statistics

Standard deviation28.724073
Coefficient of variation (CV)1.4508329
Kurtosis2.4145239
Mean19.798333
Median Absolute Deviation (MAD)6.85
Skewness1.850726
Sum475.16
Variance825.0724
MonotonicityNot monotonic
2024-01-10T05:57:44.887403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 6
25.0%
3.05 2
 
8.3%
4.19 1
 
4.2%
20.22 1
 
4.2%
11.46 1
 
4.2%
29.43 1
 
4.2%
88.74 1
 
4.2%
20.16 1
 
4.2%
9.51 1
 
4.2%
28.93 1
 
4.2%
Other values (8) 8
33.3%
ValueCountFrequency (%)
0.0 6
25.0%
2.85 1
 
4.2%
2.91 1
 
4.2%
3.05 2
 
8.3%
3.75 1
 
4.2%
4.19 1
 
4.2%
9.51 1
 
4.2%
11.46 1
 
4.2%
11.83 1
 
4.2%
20.16 1
 
4.2%
ValueCountFrequency (%)
91.29 1
4.2%
88.74 1
4.2%
86.98 1
4.2%
33.37 1
4.2%
29.43 1
4.2%
28.93 1
4.2%
23.44 1
4.2%
20.22 1
4.2%
20.16 1
4.2%
11.83 1
4.2%

Interactions

2024-01-10T05:57:42.180377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:41.085759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:41.428514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:41.783943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:42.267600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:41.170415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:41.512137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:41.882154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:42.340698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:41.250750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:41.592083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:41.977944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:42.450280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:41.346541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:41.696496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:57:42.086190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:57:44.974418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.7120.8220.7301.000
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.7120.0001.0001.0000.8400.930
감면금액0.8220.0001.0001.0000.9000.806
부과금액0.7300.0000.8400.9001.0000.575
비과세감면율1.0000.0000.9300.8060.5751.000
2024-01-10T05:57:45.082074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2024-01-10T05:57:45.181315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율세목명과세년도
비과세금액1.0000.7950.5170.9090.4870.000
감면금액0.7951.0000.6330.8130.6450.000
부과금액0.5170.6331.0000.3780.4770.000
비과세감면율0.9090.8130.3781.0000.9180.000
세목명0.4870.6450.4770.9181.0000.000
과세년도0.0000.0000.0000.0000.0001.000

Missing values

2024-01-10T05:57:42.567560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:57:42.717473image/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

시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
0충청남도부여군44760교육세20170500051986380000.0
1충청남도부여군44760등록세201701475800000.0
2충청남도부여군44760재산세20174612796000764206000589027800091.29
3충청남도부여군44760주민세2017198800002768400012688760003.75
4충청남도부여군44760취득세2017204983700025000830001363325100033.37
5충청남도부여군44760자동차세201739913000387183000146536610002.91
6충청남도부여군44760등록면허세20174121000116143000101671500011.83
7충청남도부여군44760지역자원시설세20171357050004313800076289000023.44
8충청남도부여군44760교육세20180500056553900000.0
9충청남도부여군44760등록세201801226600000.0
시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
14충청남도부여군44760등록면허세20181176300011488800013315280009.51
15충청남도부여군44760지역자원시설세20181404460004371700091351700020.16
16충청남도부여군44760교육세20190500053574510000.0
17충청남도부여군44760등록세201901851800000.0
18충청남도부여군44760재산세20195013899000788433000653836400088.74
19충청남도부여군44760주민세2019281400001083600012780910003.05
20충청남도부여군44760취득세2019184682400023491350001425597100029.43
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