Overview

Dataset statistics

Number of variables10
Number of observations274
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.6 KiB
Average record size in memory84.5 B

Variable types

Numeric3
Categorical5
Text1
DateTime1

Dataset

Description전라남도 신안군 지방세 과세를 위해 세원이 되는 과세 대상 유형별 부과된 현황을 제공하는 데이터로 과세년도, 세목명, 세원유형, 부과건수, 부과금액등의 자료를 제공합니다. (2017년~2022년)
Author전라남도 신안군
URLhttps://www.data.go.kr/data/15079929/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터 기준일자 has constant value ""Constant
세목명 is highly overall correlated with 세원 유형명High correlation
세원 유형명 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
순번 is highly overall correlated with 과세연도High correlation
과세연도 is highly overall correlated with 순번High correlation
부과건수 is highly overall correlated with 세원 유형명High correlation
순번 has unique valuesUnique
부과건수 has 68 (24.8%) zerosZeros

Reproduction

Analysis started2023-12-12 12:51:24.532858
Analysis finished2023-12-12 12:51:26.050694
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct274
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean137.5
Minimum1
Maximum274
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T21:51:26.118209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.65
Q169.25
median137.5
Q3205.75
95-th percentile260.35
Maximum274
Range273
Interquartile range (IQR)136.5

Descriptive statistics

Standard deviation79.241193
Coefficient of variation (CV)0.57629959
Kurtosis-1.2
Mean137.5
Median Absolute Deviation (MAD)68.5
Skewness0
Sum37675
Variance6279.1667
MonotonicityStrictly increasing
2023-12-12T21:51:26.282397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
182 1
 
0.4%
188 1
 
0.4%
187 1
 
0.4%
186 1
 
0.4%
185 1
 
0.4%
184 1
 
0.4%
183 1
 
0.4%
181 1
 
0.4%
207 1
 
0.4%
Other values (264) 264
96.4%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
274 1
0.4%
273 1
0.4%
272 1
0.4%
271 1
0.4%
270 1
0.4%
269 1
0.4%
268 1
0.4%
267 1
0.4%
266 1
0.4%
265 1
0.4%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
전라남도
274 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 274
100.0%

Length

2023-12-12T21:51:26.415800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:51:26.505962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 274
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
신안군
274 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신안군 274
100.0%

Length

2023-12-12T21:51:26.618307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:51:26.718610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신안군 274
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
46910
274 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46910
2nd row46910
3rd row46910
4th row46910
5th row46910

Common Values

ValueCountFrequency (%)
46910 274
100.0%

Length

2023-12-12T21:51:26.811507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:51:26.921149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46910 274
100.0%

과세연도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.5182
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T21:51:27.021782image/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 deviation1.7122792
Coefficient of variation (CV)0.0008478652
Kurtosis-1.2557429
Mean2019.5182
Median Absolute Deviation (MAD)1
Skewness-0.031289271
Sum553348
Variance2.9319002
MonotonicityIncreasing
2023-12-12T21:51:27.146892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2017 47
17.2%
2019 47
17.2%
2020 47
17.2%
2021 46
16.8%
2022 46
16.8%
2018 41
15.0%
ValueCountFrequency (%)
2017 47
17.2%
2018 41
15.0%
2019 47
17.2%
2020 47
17.2%
2021 46
16.8%
2022 46
16.8%
ValueCountFrequency (%)
2022 46
16.8%
2021 46
16.8%
2020 47
17.2%
2019 47
17.2%
2018 41
15.0%
2017 47
17.2%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
취득세
54 
주민세
50 
자동차세
42 
재산세
30 
지방소득세
24 
Other values (8)
74 

Length

Max length7
Median length3
Mean length3.7153285
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지방소득세
2nd row지방소득세
3rd row지방소득세
4th row지방소득세
5th row지방소비세

Common Values

ValueCountFrequency (%)
취득세 54
19.7%
주민세 50
18.2%
자동차세 42
15.3%
재산세 30
10.9%
지방소득세 24
8.8%
레저세 20
 
7.3%
지역자원시설세 14
 
5.1%
등록면허세 12
 
4.4%
교육세 6
 
2.2%
담배소비세 6
 
2.2%
Other values (3) 16
 
5.8%

Length

2023-12-12T21:51:27.290245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 54
19.7%
주민세 50
18.2%
자동차세 42
15.3%
재산세 30
10.9%
지방소득세 24
8.8%
레저세 20
 
7.3%
지역자원시설세 14
 
5.1%
등록면허세 12
 
4.4%
교육세 6
 
2.2%
담배소비세 6
 
2.2%
Other values (3) 16
 
5.8%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
지방소득세(특별징수)
 
6
건축물
 
6
재산세(선박)
 
6
자동차세(주행)
 
6
재산세(토지)
 
6
Other values (45)
244 

Length

Max length11
Median length8
Mean length6.0985401
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지방소득세(특별징수)
2nd row지방소득세(법인소득)
3rd row지방소득세(양도소득)
4th row지방소득세(종합소득)
5th row지방소비세

Common Values

ValueCountFrequency (%)
지방소득세(특별징수) 6
 
2.2%
건축물 6
 
2.2%
재산세(선박) 6
 
2.2%
자동차세(주행) 6
 
2.2%
재산세(토지) 6
 
2.2%
기계장비 6
 
2.2%
재산세(항공기) 6
 
2.2%
지방소득세(종합소득) 6
 
2.2%
교육세 6
 
2.2%
주택(개별) 6
 
2.2%
Other values (40) 214
78.1%

Length

2023-12-12T21:51:27.439441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지방소득세(특별징수 6
 
2.2%
기타승용 6
 
2.2%
승용 6
 
2.2%
재산세(건축물 6
 
2.2%
등록면허세(등록 6
 
2.2%
3륜이하 6
 
2.2%
건축물 6
 
2.2%
화물 6
 
2.2%
승합 6
 
2.2%
지방소득세(법인소득 6
 
2.2%
Other values (40) 214
78.1%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct191
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9495.8832
Minimum0
Maximum130076
Zeros68
Zeros (%)24.8%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T21:51:27.610012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.25
median273
Q35037.75
95-th percentile68423
Maximum130076
Range130076
Interquartile range (IQR)5036.5

Descriptive statistics

Standard deviation23931.855
Coefficient of variation (CV)2.5202348
Kurtosis11.375162
Mean9495.8832
Median Absolute Deviation (MAD)273
Skewness3.368587
Sum2601872
Variance5.7273368 × 108
MonotonicityNot monotonic
2023-12-12T21:51:27.784474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 68
 
24.8%
12 5
 
1.8%
15 3
 
1.1%
11 3
 
1.1%
10 3
 
1.1%
77 2
 
0.7%
95 2
 
0.7%
58 2
 
0.7%
6 2
 
0.7%
13 2
 
0.7%
Other values (181) 182
66.4%
ValueCountFrequency (%)
0 68
24.8%
1 1
 
0.4%
2 1
 
0.4%
6 2
 
0.7%
7 1
 
0.4%
9 1
 
0.4%
10 3
 
1.1%
11 3
 
1.1%
12 5
 
1.8%
13 2
 
0.7%
ValueCountFrequency (%)
130076 1
0.4%
125477 1
0.4%
123730 1
0.4%
119170 1
0.4%
115987 1
0.4%
115177 1
0.4%
111757 1
0.4%
92617 1
0.4%
75309 1
0.4%
73272 1
0.4%

부과금액
Text

Distinct208
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-12T21:51:28.074256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10.5
Mean length7.959854
Min length2

Characters and Unicode

Total characters2181
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique207 ?
Unique (%)75.5%

Sample

1st row861526000
2nd row1144294000
3rd row370770000
4th row367281000
5th row0
ValueCountFrequency (%)
0 67
 
24.5%
861526000 1
 
0.4%
9921687000 1
 
0.4%
3716324000 1
 
0.4%
2924029000 1
 
0.4%
332894000 1
 
0.4%
11317733000 1
 
0.4%
272304000 1
 
0.4%
2017853000 1
 
0.4%
1451103000 1
 
0.4%
Other values (198) 198
72.3%
2023-12-12T21:51:28.520035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 797
36.5%
275
 
12.6%
1 156
 
7.2%
2 148
 
6.8%
4 128
 
5.9%
9 125
 
5.7%
3 124
 
5.7%
8 123
 
5.6%
5 112
 
5.1%
7 103
 
4.7%
Other values (2) 90
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1905
87.3%
Space Separator 275
 
12.6%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 797
41.8%
1 156
 
8.2%
2 148
 
7.8%
4 128
 
6.7%
9 125
 
6.6%
3 124
 
6.5%
8 123
 
6.5%
5 112
 
5.9%
7 103
 
5.4%
6 89
 
4.7%
Space Separator
ValueCountFrequency (%)
275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2181
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 797
36.5%
275
 
12.6%
1 156
 
7.2%
2 148
 
6.8%
4 128
 
5.9%
9 125
 
5.7%
3 124
 
5.7%
8 123
 
5.6%
5 112
 
5.1%
7 103
 
4.7%
Other values (2) 90
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2181
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 797
36.5%
275
 
12.6%
1 156
 
7.2%
2 148
 
6.8%
4 128
 
5.9%
9 125
 
5.7%
3 124
 
5.7%
8 123
 
5.6%
5 112
 
5.1%
7 103
 
4.7%
Other values (2) 90
 
4.1%

데이터 기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum2023-11-30 00:00:00
Maximum2023-11-30 00:00:00
2023-12-12T21:51:28.680058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:51:28.782228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T21:51:25.451634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:51:24.900497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:51:25.194729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:51:25.541349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:51:24.996713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:51:25.280046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:51:25.648084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:51:25.096221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:51:25.364919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:51:28.850547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번과세연도세목명세원 유형명부과건수
순번1.0000.9440.3730.0000.000
과세연도0.9441.0000.0000.0000.000
세목명0.3730.0001.0001.0000.794
세원 유형명0.0000.0001.0001.0000.910
부과건수0.0000.0000.7940.9101.000
2023-12-12T21:51:28.964005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명세원 유형명
세목명1.0000.926
세원 유형명0.9261.000
2023-12-12T21:51:29.070402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번과세연도부과건수세목명세원 유형명
순번1.0000.9860.0430.1630.000
과세연도0.9861.0000.0380.0000.000
부과건수0.0430.0381.0000.4960.572
세목명0.1630.0000.4961.0000.926
세원 유형명0.0000.0000.5720.9261.000

Missing values

2023-12-12T21:51:25.779149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:51:25.980948image/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

순번시도명시군구명자치단체코드과세연도세목명세원 유형명부과건수부과금액데이터 기준일자
01전라남도신안군469102017지방소득세지방소득세(특별징수)28758615260002023-11-30
12전라남도신안군469102017지방소득세지방소득세(법인소득)51311442940002023-11-30
23전라남도신안군469102017지방소득세지방소득세(양도소득)5853707700002023-11-30
34전라남도신안군469102017지방소득세지방소득세(종합소득)18493672810002023-11-30
45전라남도신안군469102017지방소비세지방소비세002023-11-30
56전라남도신안군469102017교육세교육세11175730389290002023-11-30
67전라남도신안군469102017도시계획세도시계획세002023-11-30
78전라남도신안군469102017취득세건축물5197981200002023-11-30
89전라남도신안군469102017취득세주택(개별)8304484120002023-11-30
910전라남도신안군469102017취득세주택(단독)1592720002023-11-30
순번시도명시군구명자치단체코드과세연도세목명세원 유형명부과건수부과금액데이터 기준일자
264265전라남도신안군469102022주민세주민세(법인세분)002023-11-30
265266전라남도신안군469102022주민세주민세(양도소득)002023-11-30
266267전라남도신안군469102022주민세주민세(종합소득)002023-11-30
267268전라남도신안군469102022담배소비세담배소비세63628556480002023-11-30
268269전라남도신안군469102022등록면허세등록면허세(면허)226203293500002023-11-30
269270전라남도신안군469102022등록면허세등록면허세(등록)2121156694420002023-11-30
270271전라남도신안군469102022지역자원시설세지역자원시설세(소방)62643524610002023-11-30
271272전라남도신안군469102022지역자원시설세지역자원시설세(시설)002023-11-30
272273전라남도신안군469102022지역자원시설세지역자원시설세(특자)68170002023-11-30
273274전라남도신안군469102022체납체납5795925963100002023-11-30