Overview

Dataset statistics

Number of variables8
Number of observations38
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory70.4 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description세목별 납세 인원 현황을 제공합니다.(과세연도별 ,세목별, 납세자 유형 및 납세자 수, 주소가 관내 관외 등 제공합니다.)
Author전북특별자치도 익산시
URLhttps://www.data.go.kr/data/15079922/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant

Reproduction

Analysis started2024-03-14 17:30:51.173133
Analysis finished2024-03-14 17:30:52.162480
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size432.0 B
전북특별자치도
38 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전북특별자치도 38
100.0%

Length

2024-03-15T02:30:52.314853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:30:52.590592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북특별자치도 38
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size432.0 B
익산시
38 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
익산시 38
100.0%

Length

2024-03-15T02:30:52.788350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:30:52.960564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
익산시 38
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size432.0 B
45140
38 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row45140
2nd row45140
3rd row45140
4th row45140
5th row45140

Common Values

ValueCountFrequency (%)
45140 38
100.0%

Length

2024-03-15T02:30:53.140890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:30:53.334094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
45140 38
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size432.0 B
2021
38 

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 38
100.0%

Length

2024-03-15T02:30:53.529424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:30:53.874596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 38
100.0%

세목명
Categorical

Distinct11
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Memory size432.0 B
등록세
4 
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
Other values (6)
18 

Length

Max length7
Median length5
Mean length4.2631579
Min length3

Unique

Unique1 ?
Unique (%)2.6%

Sample

1st row등록세
2nd row등록세
3rd row등록세
4th row등록세
5th row재산세

Common Values

ValueCountFrequency (%)
등록세 4
10.5%
재산세 4
10.5%
주민세 4
10.5%
취득세 4
10.5%
자동차세 4
10.5%
등록면허세 4
10.5%
지방소득세 4
10.5%
지역자원시설세 4
10.5%
담배소비세 3
7.9%
종합토지세 2
5.3%

Length

2024-03-15T02:30:54.095347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록세 4
10.5%
재산세 4
10.5%
주민세 4
10.5%
취득세 4
10.5%
자동차세 4
10.5%
등록면허세 4
10.5%
지방소득세 4
10.5%
지역자원시설세 4
10.5%
담배소비세 3
7.9%
종합토지세 2
5.3%

납세자유형
Categorical

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size432.0 B
개인
19 
법인
19 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인
2nd row개인
3rd row법인
4th row법인
5th row개인

Common Values

ValueCountFrequency (%)
개인 19
50.0%
법인 19
50.0%

Length

2024-03-15T02:30:54.343003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:30:54.520563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 19
50.0%
법인 19
50.0%

관내_관외
Boolean

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size166.0 B
False
19 
True
19 
ValueCountFrequency (%)
False 19
50.0%
True 19
50.0%
2024-03-15T02:30:54.695548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

Distinct36
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13588.132
Minimum1
Maximum106629
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size470.0 B
2024-03-15T02:30:54.978043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q142.25
median1175.5
Q36886.75
95-th percentile92588.05
Maximum106629
Range106628
Interquartile range (IQR)6844.5

Descriptive statistics

Standard deviation28227.794
Coefficient of variation (CV)2.077386
Kurtosis5.2279348
Mean13588.132
Median Absolute Deviation (MAD)1174.5
Skewness2.4737903
Sum516349
Variance7.9680836 × 108
MonotonicityNot monotonic
2024-03-15T02:30:55.209931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 3
 
7.9%
186 1
 
2.6%
3144 1
 
2.6%
8 1
 
2.6%
8576 1
 
2.6%
34854 1
 
2.6%
1906 1
 
2.6%
3570 1
 
2.6%
2 1
 
2.6%
5209 1
 
2.6%
Other values (26) 26
68.4%
ValueCountFrequency (%)
1 3
7.9%
2 1
 
2.6%
4 1
 
2.6%
8 1
 
2.6%
9 1
 
2.6%
15 1
 
2.6%
28 1
 
2.6%
35 1
 
2.6%
64 1
 
2.6%
153 1
 
2.6%
ValueCountFrequency (%)
106629 1
2.6%
98969 1
2.6%
91462 1
2.6%
56459 1
2.6%
37307 1
2.6%
34854 1
2.6%
28925 1
2.6%
8576 1
2.6%
8470 1
2.6%
7347 1
2.6%

Interactions

2024-03-15T02:30:51.446830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:30:55.379423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납세자유형관내_관외납세자수
세목명1.0000.0000.0000.000
납세자유형0.0001.0000.0000.457
관내_관외0.0000.0001.0000.405
납세자수0.0000.4570.4051.000
2024-03-15T02:30:55.539855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관내_관외납세자유형세목명
관내_관외1.0000.0000.000
납세자유형0.0001.0000.000
세목명0.0000.0001.000
2024-03-15T02:30:55.700557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수세목명납세자유형관내_관외
납세자수1.0000.0000.3050.269
세목명0.0001.0000.0000.000
납세자유형0.3050.0001.0000.000
관내_관외0.2690.0000.0001.000

Missing values

2024-03-15T02:30:51.839191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:30:52.075824image/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

시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
0전북특별자치도익산시451402021등록세개인N186
1전북특별자치도익산시451402021등록세개인Y396
2전북특별자치도익산시451402021등록세법인N4
3전북특별자치도익산시451402021등록세법인Y9
4전북특별자치도익산시451402021재산세개인N56459
5전북특별자치도익산시451402021재산세개인Y98969
6전북특별자치도익산시451402021재산세법인N1238
7전북특별자치도익산시451402021재산세법인Y3940
8전북특별자치도익산시451402021주민세개인N7347
9전북특별자치도익산시451402021주민세개인Y106629
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
28전북특별자치도익산시451402021종합토지세개인Y1
29전북특별자치도익산시451402021지방소득세개인N5209
30전북특별자치도익산시451402021지방소득세개인Y37307
31전북특별자치도익산시451402021지방소득세법인N1067
32전북특별자치도익산시451402021지방소득세법인Y3577
33전북특별자치도익산시451402021지방소비세법인Y1
34전북특별자치도익산시451402021지역자원시설세개인N35
35전북특별자치도익산시451402021지역자원시설세개인Y153
36전북특별자치도익산시451402021지역자원시설세법인N15
37전북특별자치도익산시451402021지역자원시설세법인Y64