Overview

Dataset statistics

Number of variables8
Number of observations107
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 KiB
Average record size in memory68.2 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description3년간(2020~2022) 연도별 세목별 납세자 유형별로 관내/관외 납세자를 구분한 납세 인원 현황을 제공합니다.
Author전라남도 나주시
URLhttps://www.data.go.kr/data/15126705/fileData.do

Alerts

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

Reproduction

Analysis started2024-03-14 22:51:40.315310
Analysis finished2024-03-14 22:51:41.720107
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size984.0 B
전라남도
107 

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 107
100.0%

Length

2024-03-15T07:51:41.831519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T07:51:42.098163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 107
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size984.0 B
나주시
107 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
나주시 107
100.0%

Length

2024-03-15T07:51:42.401755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T07:51:42.721035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
나주시 107
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size984.0 B
46170
107 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46170
2nd row46170
3rd row46170
4th row46170
5th row46170

Common Values

ValueCountFrequency (%)
46170 107
100.0%

Length

2024-03-15T07:51:43.077570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T07:51:43.371826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46170 107
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size984.0 B
2022
38 
2021
35 
2020
34 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2022 38
35.5%
2021 35
32.7%
2020 34
31.8%

Length

2024-03-15T07:51:43.581199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T07:51:43.778767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 38
35.5%
2021 35
32.7%
2020 34
31.8%

세목명
Categorical

Distinct11
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size984.0 B
재산세
12 
주민세
12 
취득세
12 
자동차세
12 
등록면허세
12 
Other values (6)
47 

Length

Max length7
Median length5
Mean length4.1962617
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 12
11.2%
주민세 12
11.2%
취득세 12
11.2%
자동차세 12
11.2%
등록면허세 12
11.2%
지방소득세 12
11.2%
지역자원시설세 12
11.2%
등록세 11
10.3%
담배소비세 7
6.5%
지방소비세 3
 
2.8%

Length

2024-03-15T07:51:44.048155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재산세 12
11.2%
주민세 12
11.2%
취득세 12
11.2%
자동차세 12
11.2%
등록면허세 12
11.2%
지방소득세 12
11.2%
지역자원시설세 12
11.2%
등록세 11
10.3%
담배소비세 7
6.5%
지방소비세 3
 
2.8%

납세자유형
Categorical

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size984.0 B
개인
56 
법인
51 

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 (%)
개인 56
52.3%
법인 51
47.7%

Length

2024-03-15T07:51:44.536210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T07:51:44.715761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 56
52.3%
법인 51
47.7%

관내_관외
Boolean

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size235.0 B
False
55 
True
52 
ValueCountFrequency (%)
False 55
51.4%
True 52
48.6%
2024-03-15T07:51:44.864130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

Distinct95
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8152.5234
Minimum1
Maximum60266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-15T07:51:45.145475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.6
Q133.5
median2066
Q35587.5
95-th percentile47003.3
Maximum60266
Range60265
Interquartile range (IQR)5554

Descriptive statistics

Standard deviation15243.726
Coefficient of variation (CV)1.8698169
Kurtosis4.2021014
Mean8152.5234
Median Absolute Deviation (MAD)2058
Skewness2.3193386
Sum872320
Variance2.3237117 × 108
MonotonicityNot monotonic
2024-03-15T07:51:45.474665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 6
 
5.6%
4 3
 
2.8%
6 3
 
2.8%
5 2
 
1.9%
3 2
 
1.9%
13 2
 
1.9%
332 1
 
0.9%
44673 1
 
0.9%
60266 1
 
0.9%
543 1
 
0.9%
Other values (85) 85
79.4%
ValueCountFrequency (%)
1 6
5.6%
3 2
 
1.9%
4 3
2.8%
5 2
 
1.9%
6 3
2.8%
7 1
 
0.9%
8 1
 
0.9%
10 1
 
0.9%
13 2
 
1.9%
14 1
 
0.9%
ValueCountFrequency (%)
60266 1
0.9%
59693 1
0.9%
59112 1
0.9%
52072 1
0.9%
51746 1
0.9%
48002 1
0.9%
44673 1
0.9%
43841 1
0.9%
42486 1
0.9%
41808 1
0.9%

Interactions

2024-03-15T07:51:40.818252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T07:51:45.678123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명납세자유형관내_관외납세자수
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0000.0000.0000.432
납세자유형0.0000.0001.0000.0000.629
관내_관외0.0000.0000.0001.0000.548
납세자수0.0000.4320.6290.5481.000
2024-03-15T07:51:45.849712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관내_관외세목명납세자유형과세년도
관내_관외1.0000.0000.0000.000
세목명0.0001.0000.0000.000
납세자유형0.0000.0001.0000.000
과세년도0.0000.0000.0001.000
2024-03-15T07:51:46.012747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수과세년도세목명납세자유형관내_관외
납세자수1.0000.0000.2150.4620.401
과세년도0.0001.0000.0000.0000.000
세목명0.2150.0001.0000.0000.000
납세자유형0.4620.0000.0001.0000.000
관내_관외0.4010.0000.0000.0001.000

Missing values

2024-03-15T07:51:41.182077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T07:51:41.631968image/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
0전라남도나주시461702020등록세개인N332
1전라남도나주시461702020등록세개인Y275
2전라남도나주시461702020등록세법인Y3
3전라남도나주시461702020재산세개인N59112
4전라남도나주시461702020재산세개인Y41808
5전라남도나주시461702020재산세법인N2066
6전라남도나주시461702020재산세법인Y4151
7전라남도나주시461702020주민세개인N5831
8전라남도나주시461702020주민세개인Y48002
9전라남도나주시461702020주민세법인N1054
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
97전라남도나주시461702022등록면허세법인Y2758
98전라남도나주시461702022지방소득세개인N5415
99전라남도나주시461702022지방소득세개인Y20922
100전라남도나주시461702022지방소득세법인N1230
101전라남도나주시461702022지방소득세법인Y2923
102전라남도나주시461702022지방소비세개인Y1
103전라남도나주시461702022지역자원시설세개인N6
104전라남도나주시461702022지역자원시설세개인Y13
105전라남도나주시461702022지역자원시설세법인N7
106전라남도나주시461702022지역자원시설세법인Y26