Overview

Dataset statistics

Number of variables8
Number of observations45
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory69.9 B

Variable types

Categorical4
Text1
Numeric2
DateTime1

Dataset

Description지방세 과세를 위해 세원이 되는 과세 대상 유형별 부과된 현황(과세년도, 세목명, 세원 유형명, 부과건수, 부과금액)에 대하여 제공
Author전라북도 장수군
URLhttps://www.data.go.kr/data/15079442/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
과세년도 has constant value ""Constant
기준일자 has constant value ""Constant
부과건수 is highly overall correlated with 부과금액 and 1 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 has unique valuesUnique
부과건수 has 12 (26.7%) zerosZeros
부과금액 has 12 (26.7%) zerosZeros

Reproduction

Analysis started2023-12-11 23:47:28.809928
Analysis finished2023-12-11 23:47:29.744421
Duration0.93 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
전라북도
45 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 45
100.0%

Length

2023-12-12T08:47:29.811133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:47:29.895344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 45
100.0%

시군구명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장수군 45
100.0%

Length

2023-12-12T08:47:29.982490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:47:30.064573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장수군 45
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
2021
45 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 45
100.0%

Length

2023-12-12T08:47:30.147646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:47:30.243977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 45
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size492.0 B
취득세
9 
자동차세
7 
주민세
7 
재산세
5 
레저세
4 
Other values (7)
13 

Length

Max length7
Median length3
Mean length3.7555556
Min length2

Unique

Unique4 ?
Unique (%)8.9%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 9
20.0%
자동차세 7
15.6%
주민세 7
15.6%
재산세 5
11.1%
레저세 4
8.9%
지방소득세 4
8.9%
지역자원시설세 3
 
6.7%
등록면허세 2
 
4.4%
담배소비세 1
 
2.2%
교육세 1
 
2.2%
Other values (2) 2
 
4.4%

Length

2023-12-12T08:47:30.360617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 9
20.0%
자동차세 7
15.6%
주민세 7
15.6%
재산세 5
11.1%
레저세 4
8.9%
지방소득세 4
8.9%
지역자원시설세 3
 
6.7%
등록면허세 2
 
4.4%
담배소비세 1
 
2.2%
교육세 1
 
2.2%
Other values (2) 2
 
4.4%

세원 유형명
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T08:47:30.568830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length6.0444444
Min length2

Characters and Unicode

Total characters272
Distinct characters72
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

Unique45 ?
Unique (%)100.0%

Sample

1st row담배소비세
2nd row교육세
3rd row건축물
4th row주택(개별)
5th row주택(단독)
ValueCountFrequency (%)
담배소비세 1
 
2.2%
화물 1
 
2.2%
기타승용 1
 
2.2%
승용 1
 
2.2%
지방소비세 1
 
2.2%
주민세(사업소분 1
 
2.2%
주민세(개인분 1
 
2.2%
주민세(종업원분 1
 
2.2%
주민세(특별징수 1
 
2.2%
주민세(법인세분 1
 
2.2%
Other values (35) 35
77.8%
2023-12-12T08:47:30.907571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 26
 
9.6%
( 24
 
8.8%
) 24
 
8.8%
소 14
 
5.1%
주 11
 
4.0%
지 10
 
3.7%
득 9
 
3.3%
민 7
 
2.6%
방 6
 
2.2%
자 5
 
1.8%
Other values (62) 136
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 223
82.0%
Open Punctuation 24
 
8.8%
Close Punctuation 24
 
8.8%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 26
 
11.7%
소 14
 
6.3%
주 11
 
4.9%
지 10
 
4.5%
득 9
 
4.0%
민 7
 
3.1%
방 6
 
2.7%
자 5
 
2.2%
산 5
 
2.2%
기 5
 
2.2%
Other values (59) 125
56.1%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 223
82.0%
Common 49
 
18.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 26
 
11.7%
소 14
 
6.3%
주 11
 
4.9%
지 10
 
4.5%
득 9
 
4.0%
민 7
 
3.1%
방 6
 
2.7%
자 5
 
2.2%
산 5
 
2.2%
기 5
 
2.2%
Other values (59) 125
56.1%
Common
ValueCountFrequency (%)
( 24
49.0%
) 24
49.0%
3 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 223
82.0%
ASCII 49
 
18.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 26
 
11.7%
소 14
 
6.3%
주 11
 
4.9%
지 10
 
4.5%
득 9
 
4.0%
민 7
 
3.1%
방 6
 
2.7%
자 5
 
2.2%
산 5
 
2.2%
기 5
 
2.2%
Other values (59) 125
56.1%
ASCII
ValueCountFrequency (%)
( 24
49.0%
) 24
49.0%
3 1
 
2.0%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3839.2667
Minimum0
Maximum64308
Zeros12
Zeros (%)26.7%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:47:31.013415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median127
Q33513
95-th percentile11144.6
Maximum64308
Range64308
Interquartile range (IQR)3513

Descriptive statistics

Standard deviation10653.835
Coefficient of variation (CV)2.7749661
Kurtosis25.098637
Mean3839.2667
Median Absolute Deviation (MAD)127
Skewness4.7691327
Sum172767
Variance1.135042 × 108
MonotonicityNot monotonic
2023-12-12T08:47:31.125422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 12
26.7%
474 1
 
2.2%
6293 1
 
2.2%
11529 1
 
2.2%
7 1
 
2.2%
956 1
 
2.2%
9607 1
 
2.2%
83 1
 
2.2%
5581 1
 
2.2%
5976 1
 
2.2%
Other values (24) 24
53.3%
ValueCountFrequency (%)
0 12
26.7%
1 1
 
2.2%
7 1
 
2.2%
8 1
 
2.2%
12 1
 
2.2%
13 1
 
2.2%
51 1
 
2.2%
66 1
 
2.2%
67 1
 
2.2%
82 1
 
2.2%
ValueCountFrequency (%)
64308 1
2.2%
31934 1
2.2%
11529 1
2.2%
9607 1
2.2%
7349 1
2.2%
6753 1
2.2%
6293 1
2.2%
5976 1
2.2%
5581 1
2.2%
4960 1
2.2%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2897478 × 108
Minimum0
Maximum1.0133316 × 1010
Zeros12
Zeros (%)26.7%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:47:31.254949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.15312 × 108
Q36.30717 × 108
95-th percentile1.730484 × 109
Maximum1.0133316 × 1010
Range1.0133316 × 1010
Interquartile range (IQR)6.30717 × 108

Descriptive statistics

Standard deviation1.5621797 × 109
Coefficient of variation (CV)2.4836922
Kurtosis32.533183
Mean6.2897478 × 108
Median Absolute Deviation (MAD)1.15312 × 108
Skewness5.3715252
Sum2.8303865 × 1010
Variance2.4404055 × 1018
MonotonicityNot monotonic
2023-12-12T08:47:31.419393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 12
26.7%
1392085000 1
 
2.2%
396225000 1
 
2.2%
1709196000 1
 
2.2%
10133316000 1
 
2.2%
127381000 1
 
2.2%
96029000 1
 
2.2%
87522000 1
 
2.2%
104490000 1
 
2.2%
238353000 1
 
2.2%
Other values (24) 24
53.3%
ValueCountFrequency (%)
0 12
26.7%
364000 1
 
2.2%
1060000 1
 
2.2%
2580000 1
 
2.2%
2760000 1
 
2.2%
4753000 1
 
2.2%
23866000 1
 
2.2%
72114000 1
 
2.2%
87522000 1
 
2.2%
96029000 1
 
2.2%
ValueCountFrequency (%)
10133316000 1
2.2%
2134963000 1
2.2%
1735806000 1
2.2%
1709196000 1
2.2%
1629794000 1
2.2%
1392085000 1
2.2%
1382938000 1
2.2%
1111203000 1
2.2%
1085490000 1
2.2%
914374000 1
2.2%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
Minimum2021-12-31 00:00:00
Maximum2021-12-31 00:00:00
2023-12-12T08:47:31.537451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:47:31.680723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T08:47:29.148178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:47:28.987843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:47:29.225708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:47:29.072810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:47:31.772887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명세원 유형명부과건수부과금액
세목명1.0001.0000.8730.863
세원 유형명1.0001.0001.0001.000
부과건수0.8731.0001.0000.000
부과금액0.8631.0000.0001.000
2023-12-12T08:47:31.873713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액세목명
부과건수1.0000.7320.517
부과금액0.7321.0000.505
세목명0.5170.5051.000

Missing values

2023-12-12T08:47:29.327608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:47:29.450326image/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

시도명시군구명과세년도세목명세원 유형명부과건수부과금액기준일자
0전라북도장수군2021담배소비세담배소비세47413920850002021-12-31
1전라북도장수군2021교육세교육세6430817358060002021-12-31
2전라북도장수군2021취득세건축물5216307170002021-12-31
3전라북도장수군2021취득세주택(개별)5944841180002021-12-31
4전라북도장수군2021취득세주택(단독)51721140002021-12-31
5전라북도장수군2021취득세기타813829380002021-12-31
6전라북도장수군2021취득세항공기002021-12-31
7전라북도장수군2021취득세기계장비1271153120002021-12-31
8전라북도장수군2021취득세차량176516297940002021-12-31
9전라북도장수군2021취득세선박13640002021-12-31
시도명시군구명과세년도세목명세원 유형명부과건수부과금액기준일자
35전라북도장수군2021등록면허세등록면허세(면허)55811044900002021-12-31
36전라북도장수군2021등록면허세등록면허세(등록)62933962250002021-12-31
37전라북도장수군2021지역자원시설세지역자원시설세(소방)59762383530002021-12-31
38전라북도장수군2021지역자원시설세지역자원시설세(시설)002021-12-31
39전라북도장수군2021지역자원시설세지역자원시설세(특자)1327600002021-12-31
40전라북도장수군2021지방소득세지방소득세(특별징수)342010854900002021-12-31
41전라북도장수군2021지방소득세지방소득세(법인소득)4715266300002021-12-31
42전라북도장수군2021지방소득세지방소득세(양도소득)4494324600002021-12-31
43전라북도장수군2021지방소득세지방소득세(종합소득)15921569150002021-12-31
44전라북도장수군2021체납체납67537761890002021-12-31