Overview

Dataset statistics

Number of variables8
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory70.9 B

Variable types

Categorical5
Text1
Numeric2

Dataset

Description지방세 과세를 위해 세원이 되는 과세 대상 유형별 부과된 현황을 제공하는 데이터로 물건 유형에 따른 세부담 수준의 형평성 검토 및 부동산 등 관련분야 규제정책 대상 확인 시 기초자료 활용 가능 합니다.
Author경기도 양평군
URLhttps://www.data.go.kr/data/15080424/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
부과건수 is highly overall correlated with 부과금액 and 1 other fieldsHigh correlation
부과금액 is highly overall correlated with 부과건수High correlation
세목명 is highly overall correlated with 부과건수High correlation
세원 유형명 has unique valuesUnique
부과건수 has 10 (21.7%) zerosZeros
부과금액 has 10 (21.7%) zerosZeros

Reproduction

Analysis started2023-12-12 15:25:52.578051
Analysis finished2023-12-12 15:25:53.984623
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
경기도
46 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 46
100.0%

Length

2023-12-13T00:25:54.054914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:25:54.179386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 46
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
양평군
46 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
양평군 46
100.0%

Length

2023-12-13T00:25:54.297565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:25:54.394029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양평군 46
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
41830
46 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41830
2nd row41830
3rd row41830
4th row41830
5th row41830

Common Values

ValueCountFrequency (%)
41830 46
100.0%

Length

2023-12-13T00:25:54.504955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:25:54.596169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41830 46
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
2022
46 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 46
100.0%

Length

2023-12-13T00:25:54.711418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:25:54.809296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 46
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
취득세
9 
자동차세
7 
주민세
7 
재산세
5 
레저세
4 
Other values (8)
14 

Length

Max length7
Median length3
Mean length3.7826087
Min length2

Unique

Unique5 ?
Unique (%)10.9%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 9
19.6%
자동차세 7
15.2%
주민세 7
15.2%
재산세 5
10.9%
레저세 4
8.7%
지방소득세 4
8.7%
지역자원시설세 3
 
6.5%
등록면허세 2
 
4.3%
담배소비세 1
 
2.2%
교육세 1
 
2.2%
Other values (3) 3
 
6.5%

Length

2023-12-13T00:25:54.922431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 9
19.6%
자동차세 7
15.2%
주민세 7
15.2%
재산세 5
10.9%
레저세 4
8.7%
지방소득세 4
8.7%
지역자원시설세 3
 
6.5%
등록면허세 2
 
4.3%
담배소비세 1
 
2.2%
교육세 1
 
2.2%
Other values (3) 3
 
6.5%

세원 유형명
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-13T00:25:55.209434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length6.0217391
Min length2

Characters and Unicode

Total characters277
Distinct characters73
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row담배소비세
2nd row교육세
3rd row도시계획세
4th row건축물
5th row주택(개별)
ValueCountFrequency (%)
담배소비세 1
 
2.2%
지역자원시설세(소방 1
 
2.2%
지방소득세(종합소득 1
 
2.2%
주민세(종업원분 1
 
2.2%
주민세(특별징수 1
 
2.2%
주민세(법인세분 1
 
2.2%
주민세(양도소득 1
 
2.2%
주민세(종합소득 1
 
2.2%
지방소비세 1
 
2.2%
등록면허세(면허 1
 
2.2%
Other values (36) 36
78.3%
2023-12-13T00:25:55.797289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 27
 
9.7%
( 24
 
8.7%
) 24
 
8.7%
소 14
 
5.1%
주 11
 
4.0%
지 10
 
3.6%
득 9
 
3.2%
민 7
 
2.5%
방 6
 
2.2%
기 5
 
1.8%
Other values (63) 140
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 228
82.3%
Open Punctuation 24
 
8.7%
Close Punctuation 24
 
8.7%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 27
 
11.8%
소 14
 
6.1%
주 11
 
4.8%
지 10
 
4.4%
득 9
 
3.9%
민 7
 
3.1%
방 6
 
2.6%
기 5
 
2.2%
자 5
 
2.2%
시 5
 
2.2%
Other values (60) 129
56.6%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 228
82.3%
Common 49
 
17.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 27
 
11.8%
소 14
 
6.1%
주 11
 
4.8%
지 10
 
4.4%
득 9
 
3.9%
민 7
 
3.1%
방 6
 
2.6%
기 5
 
2.2%
자 5
 
2.2%
시 5
 
2.2%
Other values (60) 129
56.6%
Common
ValueCountFrequency (%)
( 24
49.0%
) 24
49.0%
3 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 228
82.3%
ASCII 49
 
17.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 27
 
11.8%
소 14
 
6.1%
주 11
 
4.8%
지 10
 
4.4%
득 9
 
3.9%
민 7
 
3.1%
방 6
 
2.6%
기 5
 
2.2%
자 5
 
2.2%
시 5
 
2.2%
Other values (60) 129
56.6%
ASCII
ValueCountFrequency (%)
( 24
49.0%
) 24
49.0%
3 1
 
2.0%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22969.587
Minimum0
Maximum357384
Zeros10
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T00:25:55.959330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111.25
median783
Q317836
95-th percentile111135.25
Maximum357384
Range357384
Interquartile range (IQR)17824.75

Descriptive statistics

Standard deviation58770.089
Coefficient of variation (CV)2.5586045
Kurtosis24.000795
Mean22969.587
Median Absolute Deviation (MAD)783
Skewness4.5417752
Sum1056601
Variance3.4539234 × 109
MonotonicityNot monotonic
2023-12-13T00:25:56.159129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 10
 
21.7%
638 1
 
2.2%
133960 1
 
2.2%
465 1
 
2.2%
9 1
 
2.2%
38653 1
 
2.2%
39832 1
 
2.2%
54684 1
 
2.2%
216 1
 
2.2%
48094 1
 
2.2%
Other values (27) 27
58.7%
ValueCountFrequency (%)
0 10
21.7%
9 1
 
2.2%
11 1
 
2.2%
12 1
 
2.2%
34 1
 
2.2%
42 1
 
2.2%
108 1
 
2.2%
109 1
 
2.2%
216 1
 
2.2%
285 1
 
2.2%
ValueCountFrequency (%)
357384 1
2.2%
133960 1
2.2%
125680 1
2.2%
67501 1
2.2%
54684 1
2.2%
54500 1
2.2%
48094 1
2.2%
39832 1
2.2%
38653 1
2.2%
27716 1
2.2%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5562707 × 109
Minimum0
Maximum5.260218 × 1010
Zeros10
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T00:25:56.364757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18945000
median5.64146 × 108
Q38.2901718 × 109
95-th percentile2.032906 × 1010
Maximum5.260218 × 1010
Range5.260218 × 1010
Interquartile range (IQR)8.2812268 × 109

Descriptive statistics

Standard deviation9.6080425 × 109
Coefficient of variation (CV)1.7292251
Kurtosis12.170497
Mean5.5562707 × 109
Median Absolute Deviation (MAD)5.64146 × 108
Skewness3.0343569
Sum2.5558845 × 1011
Variance9.2314482 × 1019
MonotonicityNot monotonic
2023-12-13T00:25:56.620835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 10
 
21.7%
8923200000 1
 
2.2%
24259490000 1
 
2.2%
664636000 1
 
2.2%
17578560000 1
 
2.2%
466684000 1
 
2.2%
5464403000 1
 
2.2%
2136869000 1
 
2.2%
11345000 1
 
2.2%
6071079000 1
 
2.2%
Other values (27) 27
58.7%
ValueCountFrequency (%)
0 10
21.7%
1419000 1
 
2.2%
8145000 1
 
2.2%
11345000 1
 
2.2%
13481000 1
 
2.2%
14773000 1
 
2.2%
19172000 1
 
2.2%
48345000 1
 
2.2%
60076000 1
 
2.2%
135006000 1
 
2.2%
ValueCountFrequency (%)
52602180000 1
2.2%
24259490000 1
2.2%
21245893000 1
2.2%
17578560000 1
2.2%
16731834000 1
2.2%
16319811000 1
2.2%
14030071000 1
2.2%
11336551000 1
2.2%
11124701000 1
2.2%
9587249000 1
2.2%

Interactions

2023-12-13T00:25:53.143217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:25:52.899298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:25:53.273302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:25:53.016695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:25:56.784381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명세원 유형명부과건수부과금액
세목명1.0001.0000.8750.640
세원 유형명1.0001.0001.0001.000
부과건수0.8751.0001.0000.661
부과금액0.6401.0000.6611.000
2023-12-13T00:25:56.944441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액세목명
부과건수1.0000.7650.647
부과금액0.7651.0000.340
세목명0.6470.3401.000

Missing values

2023-12-13T00:25:53.434082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:25:53.925977image/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
0경기도양평군418302022담배소비세담배소비세6388923200000
1경기도양평군418302022교육세교육세35738421245893000
2경기도양평군418302022도시계획세도시계획세00
3경기도양평군418302022취득세건축물32458446603000
4경기도양평군418302022취득세주택(개별)337216319811000
5경기도양평군418302022취득세주택(단독)14269587249000
6경기도양평군418302022취득세기타108580934000
7경기도양평군418302022취득세항공기00
8경기도양평군418302022취득세기계장비285455020000
9경기도양평군418302022취득세차량913811336551000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
36경기도양평군418302022재산세재산세(주택)480946071079000
37경기도양평군418302022재산세재산세(토지)13396024259490000
38경기도양평군418302022재산세재산세(항공기)00
39경기도양평군418302022재산세재산세(선박)1091419000
40경기도양평군418302022재산세재산세(건축물)190303124103000
41경기도양평군418302022지방소득세지방소득세(특별징수)245756323077000
42경기도양평군418302022지방소득세지방소득세(법인소득)18134232620000
43경기도양평군418302022지방소득세지방소득세(양도소득)380514030071000
44경기도양평군418302022지방소득세지방소득세(종합소득)277167820878000
45경기도양평군418302022체납체납12568016731834000