Overview

Dataset statistics

Number of variables8
Number of observations141
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory68.9 B

Variable types

Categorical6
Numeric2

Dataset

Description2017~2021년도 충청남도 보령시 지방세 세원이 되는 과세물건에 대한 데이터로 건축물, 항공기 등의 유형별로 부과된 현황을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=353&beforeMenuCd=DOM_000000201001001000&publicdatapk=15078789

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
부과건수 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
세목명 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
세원 유형명 is highly overall correlated with 부과건수 and 2 other fieldsHigh correlation
부과건수 has 36 (25.5%) zerosZeros
부과금액 has 36 (25.5%) zerosZeros

Reproduction

Analysis started2024-01-09 21:18:31.001660
Analysis finished2024-01-09 21:18:31.612069
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
충청남도
141 

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 141
100.0%

Length

2024-01-10T06:18:31.667914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:18:31.744260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 141
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
보령시
141 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보령시 141
100.0%

Length

2024-01-10T06:18:31.839976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:18:31.935064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보령시 141
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
44180
141 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44180
2nd row44180
3rd row44180
4th row44180
5th row44180

Common Values

ValueCountFrequency (%)
44180 141
100.0%

Length

2024-01-10T06:18:32.013324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:18:32.098306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44180 141
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2017
47 
2018
47 
2019
47 

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 47
33.3%
2018 47
33.3%
2019 47
33.3%

Length

2024-01-10T06:18:32.177743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:18:32.256221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 47
33.3%
2018 47
33.3%
2019 47
33.3%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
취득세
27 
주민세
27 
자동차세
21 
재산세
15 
레저세
12 
Other values (8)
39 

Length

Max length7
Median length3
Mean length3.6808511
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row담배소비세
2nd row교육세
3rd row도시계획세
4th row취득세
5th row취득세

Common Values

ValueCountFrequency (%)
취득세 27
19.1%
주민세 27
19.1%
자동차세 21
14.9%
재산세 15
10.6%
레저세 12
8.5%
지방소득세 12
8.5%
등록면허세 6
 
4.3%
지역자원시설세 6
 
4.3%
담배소비세 3
 
2.1%
교육세 3
 
2.1%
Other values (3) 9
 
6.4%

Length

2024-01-10T06:18:32.341956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 27
19.1%
주민세 27
19.1%
자동차세 21
14.9%
재산세 15
10.6%
레저세 12
8.5%
지방소득세 12
8.5%
등록면허세 6
 
4.3%
지역자원시설세 6
 
4.3%
담배소비세 3
 
2.1%
교육세 3
 
2.1%
Other values (3) 9
 
6.4%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
담배소비세
 
3
소싸움
 
3
도시계획세
 
3
건축물
 
3
주택(개별)
 
3
Other values (42)
126 

Length

Max length11
Median length8
Mean length6.0425532
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row담배소비세
2nd row교육세
3rd row도시계획세
4th row건축물
5th row주택(개별)

Common Values

ValueCountFrequency (%)
담배소비세 3
 
2.1%
소싸움 3
 
2.1%
도시계획세 3
 
2.1%
건축물 3
 
2.1%
주택(개별) 3
 
2.1%
주택(단독) 3
 
2.1%
기타 3
 
2.1%
항공기 3
 
2.1%
기계장비 3
 
2.1%
차량 3
 
2.1%
Other values (37) 111
78.7%

Length

2024-01-10T06:18:32.434566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
담배소비세 3
 
2.1%
화물 3
 
2.1%
기타승용 3
 
2.1%
승용 3
 
2.1%
지방소비세 3
 
2.1%
등록면허세(면허 3
 
2.1%
등록면허세(등록 3
 
2.1%
지역자원시설세(소방 3
 
2.1%
지역자원시설세(특자 3
 
2.1%
지방소득세(특별징수 3
 
2.1%
Other values (37) 111
78.7%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct105
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15279.511
Minimum0
Maximum237516
Zeros36
Zeros (%)25.5%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-01-10T06:18:32.530457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median841
Q38843
95-th percentile71062
Maximum237516
Range237516
Interquartile range (IQR)8843

Descriptive statistics

Standard deviation39098.244
Coefficient of variation (CV)2.5588675
Kurtosis20.598239
Mean15279.511
Median Absolute Deviation (MAD)841
Skewness4.2753213
Sum2154411
Variance1.5286727 × 109
MonotonicityNot monotonic
2024-01-10T06:18:32.634154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36
 
25.5%
12 2
 
1.4%
109 1
 
0.7%
1705 1
 
0.7%
321 1
 
0.7%
181 1
 
0.7%
1377 1
 
0.7%
1375 1
 
0.7%
1298 1
 
0.7%
235123 1
 
0.7%
Other values (95) 95
67.4%
ValueCountFrequency (%)
0 36
25.5%
12 2
 
1.4%
13 1
 
0.7%
16 1
 
0.7%
39 1
 
0.7%
40 1
 
0.7%
41 1
 
0.7%
52 1
 
0.7%
70 1
 
0.7%
74 1
 
0.7%
ValueCountFrequency (%)
237516 1
0.7%
236173 1
0.7%
235123 1
0.7%
117229 1
0.7%
106270 1
0.7%
91448 1
0.7%
72132 1
0.7%
71062 1
0.7%
70183 1
0.7%
63041 1
0.7%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct106
Distinct (%)75.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8463597 × 109
Minimum0
Maximum1.3210457 × 1010
Zeros36
Zeros (%)25.5%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-01-10T06:18:32.742861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.96882 × 108
Q35.595495 × 109
95-th percentile1.1088195 × 1010
Maximum1.3210457 × 1010
Range1.3210457 × 1010
Interquartile range (IQR)5.595495 × 109

Descriptive statistics

Standard deviation3.8218115 × 109
Coefficient of variation (CV)1.3427016
Kurtosis0.1810995
Mean2.8463597 × 109
Median Absolute Deviation (MAD)4.96882 × 108
Skewness1.2092898
Sum4.0133671 × 1011
Variance1.4606243 × 1019
MonotonicityNot monotonic
2024-01-10T06:18:32.862704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36
 
25.5%
8657779000 1
 
0.7%
113874000 1
 
0.7%
7390000000 1
 
0.7%
2236820000 1
 
0.7%
580195000 1
 
0.7%
6586891000 1
 
0.7%
1911997000 1
 
0.7%
6654431000 1
 
0.7%
11088195000 1
 
0.7%
Other values (96) 96
68.1%
ValueCountFrequency (%)
0 36
25.5%
736000 1
 
0.7%
2938000 1
 
0.7%
3212000 1
 
0.7%
3341000 1
 
0.7%
3927000 1
 
0.7%
7480000 1
 
0.7%
20180000 1
 
0.7%
21760000 1
 
0.7%
22140000 1
 
0.7%
ValueCountFrequency (%)
13210457000 1
0.7%
13126562000 1
0.7%
12659356000 1
0.7%
12378570000 1
0.7%
11423110000 1
0.7%
11352558000 1
0.7%
11244463000 1
0.7%
11088195000 1
0.7%
10994086000 1
0.7%
10969346000 1
0.7%

Interactions

2024-01-10T06:18:31.328129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:18:31.210020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:18:31.391176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:18:31.265524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:18:33.156249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0001.0000.8600.711
세원 유형명0.0001.0001.0000.9610.930
부과건수0.0000.8600.9611.0000.691
부과금액0.0000.7110.9300.6911.000
2024-01-10T06:18:33.233147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명
과세년도1.0000.0000.000
세목명0.0001.0000.857
세원 유형명0.0000.8571.000
2024-01-10T06:18:33.306391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액과세년도세목명세원 유형명
부과건수1.0000.7080.0000.6360.671
부과금액0.7081.0000.0000.3870.558
과세년도0.0000.0001.0000.0000.000
세목명0.6360.3870.0001.0000.857
세원 유형명0.6710.5580.0000.8571.000

Missing values

2024-01-10T06:18:31.480383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:18:31.573555image/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

시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
0충청남도보령시441802017담배소비세담배소비세1098657779000
1충청남도보령시441802017교육세교육세23751611244463000
2충청남도보령시441802017도시계획세도시계획세00
3충청남도보령시441802017취득세건축물110210969346000
4충청남도보령시441802017취득세주택(개별)15672262291000
5충청남도보령시441802017취득세주택(단독)21849745162000
6충청남도보령시441802017취득세기타383333409000
7충청남도보령시441802017취득세항공기00
8충청남도보령시441802017취득세기계장비390494132000
9충청남도보령시441802017취득세차량83237159463000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
131충청남도보령시441802019주민세주민세(재산분)951593007000
132충청남도보령시441802019주민세주민세(종업원분)8412229815000
133충청남도보령시441802019주민세주민세(특별징수)00
134충청남도보령시441802019주민세주민세(법인세분)00
135충청남도보령시441802019주민세주민세(양도소득)00
136충청남도보령시441802019주민세주민세(종합소득)00
137충청남도보령시441802019주민세주민세(법인균등)1851122189000
138충청남도보령시441802019주민세주민세(개인사업)3901196068000
139충청남도보령시441802019주민세주민세(개인균등)42749328490000
140충청남도보령시441802019체납체납914485873687000