Overview

Dataset statistics

Number of variables8
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory70.8 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description관외 납세자에 대한 부과징수 정책 수립시 기초자료 등으로 활용하기 위해 지방세 세목별 납세 인원 현황(납세자 수 등)을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=352&beforeMenuCd=DOM_000000201001001000&publicdatapk=15078642

Alerts

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

Reproduction

Analysis started2024-01-09 20:57:32.669367
Analysis finished2024-01-09 20:57:33.389959
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
충청남도
35 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 35
100.0%

Length

2024-01-10T05:57:33.445690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:57:33.543922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 35
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
예산군
35 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
예산군 35
100.0%

Length

2024-01-10T05:57:33.627599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:57:33.706452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
예산군 35
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
44810
35 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44810
2nd row44810
3rd row44810
4th row44810
5th row44810

Common Values

ValueCountFrequency (%)
44810 35
100.0%

Length

2024-01-10T05:57:33.792049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:57:33.877353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44810 35
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
2021
35 

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 35
100.0%

Length

2024-01-10T05:57:33.962486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:57:34.062998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 35
100.0%

세목명
Categorical

Distinct10
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
등록세
4 
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
Other values (5)
15 

Length

Max length7
Median length5
Mean length4.2
Min length3

Unique

Unique1 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
등록세 4
11.4%
재산세 4
11.4%
주민세 4
11.4%
취득세 4
11.4%
자동차세 4
11.4%
등록면허세 4
11.4%
지방소득세 4
11.4%
지역자원시설세 4
11.4%
담배소비세 2
5.7%
지방소비세 1
 
2.9%

Length

2024-01-10T05:57:34.167447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:57:34.283255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등록세 4
11.4%
재산세 4
11.4%
주민세 4
11.4%
취득세 4
11.4%
자동차세 4
11.4%
등록면허세 4
11.4%
지방소득세 4
11.4%
지역자원시설세 4
11.4%
담배소비세 2
5.7%
지방소비세 1
 
2.9%

납세자유형
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
법인
18 
개인
17 

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 (%)
법인 18
51.4%
개인 17
48.6%

Length

2024-01-10T05:57:34.406015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:57:34.497125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 18
51.4%
개인 17
48.6%

관내_관외
Boolean

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size167.0 B
False
18 
True
17 
ValueCountFrequency (%)
False 18
51.4%
True 17
48.6%
2024-01-10T05:57:34.577873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

Distinct33
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5701.6857
Minimum1
Maximum43676
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-01-10T05:57:34.669338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.7
Q182
median1101
Q33209
95-th percentile33810.5
Maximum43676
Range43675
Interquartile range (IQR)3127

Descriptive statistics

Standard deviation11282.41
Coefficient of variation (CV)1.9787849
Kurtosis4.694772
Mean5701.6857
Median Absolute Deviation (MAD)1094
Skewness2.3799009
Sum199559
Variance1.2729276 × 108
MonotonicityNot monotonic
2024-01-10T05:57:34.777639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
6 2
 
5.7%
1 2
 
5.7%
281 1
 
2.9%
1262 1
 
2.9%
50 1
 
2.9%
7 1
 
2.9%
4583 1
 
2.9%
11720 1
 
2.9%
1207 1
 
2.9%
11873 1
 
2.9%
Other values (23) 23
65.7%
ValueCountFrequency (%)
1 2
5.7%
2 1
2.9%
5 1
2.9%
6 2
5.7%
7 1
2.9%
9 1
2.9%
50 1
2.9%
114 1
2.9%
221 1
2.9%
281 1
2.9%
ValueCountFrequency (%)
43676 1
2.9%
35158 1
2.9%
33233 1
2.9%
28192 1
2.9%
11873 1
2.9%
11720 1
2.9%
8905 1
2.9%
4583 1
2.9%
4043 1
2.9%
2375 1
2.9%

Interactions

2024-01-10T05:57:33.158555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:57:34.852358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납세자유형관내_관외납세자수
세목명1.0000.0000.0000.000
납세자유형0.0001.0000.0000.387
관내_관외0.0000.0001.0000.296
납세자수0.0000.3870.2961.000
2024-01-10T05:57:34.934304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관내_관외세목명납세자유형
관내_관외1.0000.0000.000
세목명0.0001.0000.000
납세자유형0.0000.0001.000
2024-01-10T05:57:35.015769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수세목명납세자유형관내_관외
납세자수1.0000.0000.3760.283
세목명0.0001.0000.0000.000
납세자유형0.3760.0001.0000.000
관내_관외0.2830.0000.0001.000

Missing values

2024-01-10T05:57:33.245080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:57:33.346600image/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
0충청남도예산군448102021등록세개인N281
1충청남도예산군448102021등록세개인Y314
2충청남도예산군448102021등록세법인N6
3충청남도예산군448102021등록세법인Y9
4충청남도예산군448102021재산세개인N43676
5충청남도예산군448102021재산세개인Y33233
6충청남도예산군448102021재산세법인N1101
7충청남도예산군448102021재산세법인Y1762
8충청남도예산군448102021주민세개인N1965
9충청남도예산군448102021주민세개인Y35158
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
25충청남도예산군448102021등록면허세법인Y1262
26충청남도예산군448102021지방소득세개인N2240
27충청남도예산군448102021지방소득세개인Y11873
28충청남도예산군448102021지방소득세법인N535
29충청남도예산군448102021지방소득세법인Y1381
30충청남도예산군448102021지방소비세법인Y1
31충청남도예산군448102021지역자원시설세개인N6
32충청남도예산군448102021지역자원시설세개인Y2
33충청남도예산군448102021지역자원시설세법인N1
34충청남도예산군448102021지역자원시설세법인Y5