Overview

Dataset statistics

Number of variables8
Number of observations92
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory68.4 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description세목별 납세 인원 현황을 표준지방세시스템의 데이터를 활용하여 과세년도, 세목명, 납세자 유형, 관내/관외, 납세자 수를 조회 및 열람할 수 있음
Author전라남도 고흥군
URLhttps://www.data.go.kr/data/15079105/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 11:51:42.003575
Analysis finished2023-12-12 11:51:42.989051
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size868.0 B
전라남도
92 

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 92
100.0%

Length

2023-12-12T20:51:43.063672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:51:43.184060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 92
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size868.0 B
고흥군
92 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고흥군 92
100.0%

Length

2023-12-12T20:51:43.300777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:51:43.413170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고흥군 92
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size868.0 B
46770
92 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46770
2nd row46770
3rd row46770
4th row46770
5th row46770

Common Values

ValueCountFrequency (%)
46770 92
100.0%

Length

2023-12-12T20:51:43.559028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:51:43.690955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46770 92
100.0%

과세년도
Categorical

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size868.0 B
2019
32 
2017
30 
2018
30 

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 (%)
2019 32
34.8%
2017 30
32.6%
2018 30
32.6%

Length

2023-12-12T20:51:43.807200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:51:43.945704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 32
34.8%
2017 30
32.6%
2018 30
32.6%

세목명
Categorical

Distinct9
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size868.0 B
재산세
12 
주민세
12 
취득세
12 
자동차세
12 
등록면허세
12 
Other values (4)
32 

Length

Max length7
Median length3
Mean length3.9347826
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 12
13.0%
주민세 12
13.0%
취득세 12
13.0%
자동차세 12
13.0%
등록면허세 12
13.0%
지방소득세 12
13.0%
등록세 11
12.0%
담배소비세 5
5.4%
지역자원시설세 4
 
4.3%

Length

2023-12-12T20:51:44.083605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:51:44.284626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 12
13.0%
주민세 12
13.0%
취득세 12
13.0%
자동차세 12
13.0%
등록면허세 12
13.0%
지방소득세 12
13.0%
등록세 11
12.0%
담배소비세 5
5.4%
지역자원시설세 4
 
4.3%

납세자유형
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size868.0 B
법인
47 
개인
45 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
법인 47
51.1%
개인 45
48.9%

Length

2023-12-12T20:51:44.467236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:51:44.578024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 47
51.1%
개인 45
48.9%

관내/관외
Boolean

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size224.0 B
False
46 
True
46 
ValueCountFrequency (%)
False 46
50.0%
True 46
50.0%
2023-12-12T20:51:44.682058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

Distinct85
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5752.1848
Minimum1
Maximum47687
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size960.0 B
2023-12-12T20:51:44.832526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.65
Q1225
median818.5
Q33628.5
95-th percentile34105.5
Maximum47687
Range47686
Interquartile range (IQR)3403.5

Descriptive statistics

Standard deviation11368.673
Coefficient of variation (CV)1.9764095
Kurtosis5.1236311
Mean5752.1848
Median Absolute Deviation (MAD)808.5
Skewness2.4711588
Sum529201
Variance1.2924672 × 108
MonotonicityNot monotonic
2023-12-12T20:51:45.065651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 5
 
5.4%
4 3
 
3.3%
11 2
 
2.2%
249 1
 
1.1%
250 1
 
1.1%
3385 1
 
1.1%
604 1
 
1.1%
34417 1
 
1.1%
47687 1
 
1.1%
291 1
 
1.1%
Other values (75) 75
81.5%
ValueCountFrequency (%)
1 5
5.4%
4 3
3.3%
6 1
 
1.1%
9 1
 
1.1%
11 2
 
2.2%
12 1
 
1.1%
14 1
 
1.1%
52 1
 
1.1%
53 1
 
1.1%
61 1
 
1.1%
ValueCountFrequency (%)
47687 1
1.1%
45932 1
1.1%
44800 1
1.1%
34417 1
1.1%
34155 1
1.1%
34065 1
1.1%
33851 1
1.1%
32419 1
1.1%
31821 1
1.1%
19005 1
1.1%

Interactions

2023-12-12T20:51:42.278485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:51:45.220917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명납세자유형관내/관외납세자수
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0000.0000.1140.523
납세자유형0.0000.0001.0000.0000.458
관내/관외0.0000.1140.0001.0000.412
납세자수0.0000.5230.4580.4121.000
2023-12-12T20:51:45.384563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자유형관내/관외과세년도세목명
납세자유형1.0000.0000.0000.000
관내/관외0.0001.0000.0000.105
과세년도0.0000.0001.0000.000
세목명0.0000.1050.0001.000
2023-12-12T20:51:45.530933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수과세년도세목명납세자유형관내/관외
납세자수1.0000.0000.3040.4760.428
과세년도0.0001.0000.0000.0000.000
세목명0.3040.0001.0000.0000.105
납세자유형0.4760.0000.0001.0000.000
관내/관외0.4280.0000.1050.0001.000

Missing values

2023-12-12T20:51:42.753988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:51:42.923880image/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
0전라남도고흥군467702017등록세개인N249
1전라남도고흥군467702017등록세개인Y157
2전라남도고흥군467702017등록세법인Y4
3전라남도고흥군467702017재산세개인N44800
4전라남도고흥군467702017재산세개인Y34065
5전라남도고흥군467702017재산세법인N526
6전라남도고흥군467702017재산세법인Y3361
7전라남도고흥군467702017주민세개인N3011
8전라남도고흥군467702017주민세개인Y31821
9전라남도고흥군467702017주민세법인N198
시도명시군구명자치단체코드과세년도세목명납세자유형관내/관외납세자수
82전라남도고흥군467702019등록면허세개인N3621
83전라남도고흥군467702019등록면허세개인Y10752
84전라남도고흥군467702019등록면허세법인N778
85전라남도고흥군467702019등록면허세법인Y1195
86전라남도고흥군467702019지방소득세개인N738
87전라남도고흥군467702019지방소득세개인Y5404
88전라남도고흥군467702019지방소득세법인N290
89전라남도고흥군467702019지방소득세법인Y991
90전라남도고흥군467702019지역자원시설세개인Y6
91전라남도고흥군467702019지역자원시설세법인Y1