Overview

Dataset statistics

Number of variables9
Number of observations188
Missing cells84
Missing cells (%)5.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.1 KiB
Average record size in memory76.7 B

Variable types

Categorical7
Numeric2

Dataset

Description이 데이터는 2017년 ~ 2020년 남원시 세원 유형별 과세 현황에 대하여 세목명, 세원 유형명, 부과건수, 부과금액 등에 대한 데이터 입니다.
URLhttps://www.data.go.kr/data/15079837/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터 기준일자 has constant value ""Constant
부과건수 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 부과건수 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 부과건수 and 2 other fieldsHigh correlation
세원 유형명 is highly overall correlated with 부과건수 and 2 other fieldsHigh correlation
부과건수 has 42 (22.3%) missing valuesMissing
부과금액 has 42 (22.3%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:17:08.574888
Analysis finished2023-12-12 18:17:09.952207
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
전라북도
188 

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 188
100.0%

Length

2023-12-13T03:17:10.025869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:17:10.127325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 188
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
남원시
188 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남원시 188
100.0%

Length

2023-12-13T03:17:10.285727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:17:10.400627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남원시 188
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
45190
188 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row45190
2nd row45190
3rd row45190
4th row45190
5th row45190

Common Values

ValueCountFrequency (%)
45190 188
100.0%

Length

2023-12-13T03:17:10.520459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:17:10.613615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
45190 188
100.0%

과세년도
Categorical

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2017
47 
2018
47 
2019
47 
2020
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
25.0%
2018 47
25.0%
2019 47
25.0%
2020 47
25.0%

Length

2023-12-13T03:17:10.718460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:17:10.835768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 47
25.0%
2018 47
25.0%
2019 47
25.0%
2020 47
25.0%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
취득세
36 
주민세
36 
자동차세
28 
재산세
20 
레저세
16 
Other values (8)
52 

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 36
19.1%
주민세 36
19.1%
자동차세 28
14.9%
재산세 20
10.6%
레저세 16
8.5%
지방소득세 16
8.5%
등록면허세 8
 
4.3%
지역자원시설세 8
 
4.3%
담배소비세 4
 
2.1%
교육세 4
 
2.1%
Other values (3) 12
 
6.4%

Length

2023-12-13T03:17:10.964050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 36
19.1%
주민세 36
19.1%
자동차세 28
14.9%
재산세 20
10.6%
레저세 16
8.5%
지방소득세 16
8.5%
등록면허세 8
 
4.3%
지역자원시설세 8
 
4.3%
담배소비세 4
 
2.1%
교육세 4
 
2.1%
Other values (3) 12
 
6.4%

세원 유형명
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
담배소비세
 
4
소싸움
 
4
도시계획세
 
4
건축물
 
4
주택(개별)
 
4
Other values (42)
168 

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 4
 
2.1%
소싸움 4
 
2.1%
도시계획세 4
 
2.1%
건축물 4
 
2.1%
주택(개별) 4
 
2.1%
주택(단독) 4
 
2.1%
기타 4
 
2.1%
항공기 4
 
2.1%
기계장비 4
 
2.1%
차량 4
 
2.1%
Other values (37) 148
78.7%

Length

2023-12-13T03:17:11.102547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
담배소비세 4
 
2.1%
화물 4
 
2.1%
기타승용 4
 
2.1%
승용 4
 
2.1%
지방소비세 4
 
2.1%
주민세(재산분 4
 
2.1%
주민세(종업원분 4
 
2.1%
주민세(특별징수 4
 
2.1%
주민세(법인세분 4
 
2.1%
주민세(양도소득 4
 
2.1%
Other values (37) 148
78.7%

부과건수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct131
Distinct (%)89.7%
Missing42
Missing (%)22.3%
Infinite0
Infinite (%)0.0%
Mean14949.479
Minimum1
Maximum198692
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-13T03:17:11.238701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.5
Q1265.75
median1491.5
Q314356.5
95-th percentile62545.5
Maximum198692
Range198691
Interquartile range (IQR)14090.75

Descriptive statistics

Standard deviation33976.378
Coefficient of variation (CV)2.2727465
Kurtosis18.803123
Mean14949.479
Median Absolute Deviation (MAD)1483.5
Skewness4.1304269
Sum2182624
Variance1.1543942 × 109
MonotonicityNot monotonic
2023-12-13T03:17:11.401064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 5
 
2.7%
2 4
 
2.1%
6 4
 
2.1%
4 2
 
1.1%
6654 2
 
1.1%
1279 2
 
1.1%
265 2
 
1.1%
880 2
 
1.1%
1379 1
 
0.5%
96 1
 
0.5%
Other values (121) 121
64.4%
(Missing) 42
 
22.3%
ValueCountFrequency (%)
1 1
 
0.5%
2 4
2.1%
3 1
 
0.5%
4 2
 
1.1%
6 4
2.1%
7 1
 
0.5%
9 1
 
0.5%
11 1
 
0.5%
12 5
2.7%
21 1
 
0.5%
ValueCountFrequency (%)
198692 1
0.5%
192753 1
0.5%
190181 1
0.5%
189345 1
0.5%
70585 1
0.5%
69635 1
0.5%
69488 1
0.5%
67209 1
0.5%
48555 1
0.5%
47614 1
0.5%

부과금액
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct146
Distinct (%)100.0%
Missing42
Missing (%)22.3%
Infinite0
Infinite (%)0.0%
Mean1.8694822 × 109
Minimum22000
Maximum1.15337 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-13T03:17:11.567068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22000
5-th percentile286250
Q11.0136875 × 108
median9.63611 × 108
Q33.2630108 × 109
95-th percentile6.2781285 × 109
Maximum1.15337 × 1010
Range1.1533678 × 1010
Interquartile range (IQR)3.161642 × 109

Descriptive statistics

Standard deviation2.2753812 × 109
Coefficient of variation (CV)1.2171184
Kurtosis1.3516787
Mean1.8694822 × 109
Median Absolute Deviation (MAD)9.531235 × 108
Skewness1.3450048
Sum2.729444 × 1011
Variance5.1773597 × 1018
MonotonicityNot monotonic
2023-12-13T03:17:11.696528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3286433000 1
 
0.5%
455187000 1
 
0.5%
106675000 1
 
0.5%
138806000 1
 
0.5%
339903000 1
 
0.5%
3426195000 1
 
0.5%
4676698000 1
 
0.5%
1120700000 1
 
0.5%
1122090000 1
 
0.5%
418002000 1
 
0.5%
Other values (136) 136
72.3%
(Missing) 42
 
22.3%
ValueCountFrequency (%)
22000 1
0.5%
24000 1
0.5%
25000 1
0.5%
37000 1
0.5%
162000 1
0.5%
202000 1
0.5%
234000 1
0.5%
255000 1
0.5%
380000 1
0.5%
470000 1
0.5%
ValueCountFrequency (%)
11533700000 1
0.5%
6935548000 1
0.5%
6843413000 1
0.5%
6630454000 1
0.5%
6535039000 1
0.5%
6373661000 1
0.5%
6316558000 1
0.5%
6280773000 1
0.5%
6270195000 1
0.5%
6183713000 1
0.5%

데이터 기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2020-12-31
188 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-31
2nd row2020-12-31
3rd row2020-12-31
4th row2020-12-31
5th row2020-12-31

Common Values

ValueCountFrequency (%)
2020-12-31 188
100.0%

Length

2023-12-13T03:17:11.832497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:17:11.941407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-31 188
100.0%

Interactions

2023-12-13T03:17:09.097277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:17:08.870394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:17:09.192313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:17:09.000996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:17:12.016560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0001.0000.8470.803
세원 유형명0.0001.0001.0000.9960.955
부과건수0.0000.8470.9961.0000.620
부과금액0.0000.8030.9550.6201.000
2023-12-13T03:17:12.117276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도세원 유형명
세목명1.0000.0000.898
과세년도0.0001.0000.000
세원 유형명0.8980.0001.000
2023-12-13T03:17:12.214968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액과세년도세목명세원 유형명
부과건수1.0000.5380.0000.6590.857
부과금액0.5381.0000.0000.5430.685
과세년도0.0000.0001.0000.0000.000
세목명0.6590.5430.0001.0000.898
세원 유형명0.8570.6850.0000.8981.000

Missing values

2023-12-13T03:17:09.596820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:17:09.741699image/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.
2023-12-13T03:17:09.880397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액데이터 기준일자
0전라북도남원시451902017담배소비세담배소비세10854543680002020-12-31
1전라북도남원시451902017교육세교육세18934561837130002020-12-31
2전라북도남원시451902017도시계획세도시계획세<NA><NA>2020-12-31
3전라북도남원시451902017취득세건축물71816991140002020-12-31
4전라북도남원시451902017취득세주택(개별)137217228950002020-12-31
5전라북도남원시451902017취득세주택(단독)62110035830002020-12-31
6전라북도남원시451902017취득세기타12609570002020-12-31
7전라북도남원시451902017취득세항공기<NA><NA>2020-12-31
8전라북도남원시451902017취득세기계장비3844492050002020-12-31
9전라북도남원시451902017취득세차량643151910250002020-12-31
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액데이터 기준일자
178전라북도남원시451902020주민세주민세(개인균등)344093447520002020-12-31
179전라북도남원시451902020지방소득세지방소득세(특별징수)991138698540002020-12-31
180전라북도남원시451902020지방소득세지방소득세(법인소득)137936564230002020-12-31
181전라북도남원시451902020지방소득세지방소득세(양도소득)12798885350002020-12-31
182전라북도남원시451902020지방소득세지방소득세(종합소득)665410565630002020-12-31
183전라북도남원시451902020등록면허세등록면허세(면허)194954224220002020-12-31
184전라북도남원시451902020등록면허세등록면허세(등록)2038116748660002020-12-31
185전라북도남원시451902020지역자원시설세지역자원시설세(소방)2493012210790002020-12-31
186전라북도남원시451902020지역자원시설세지역자원시설세(특자)26877370002020-12-31
187전라북도남원시451902020체납체납4761425537930002020-12-31