Overview

Dataset statistics

Number of variables8
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory70.7 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description충청북도 옥천군의 세목별 납세 인원 현황에 대하여 과세년도, 세목명, 납세자유형, 관내/관외 여부, 납세자수를 제공합니다.
Author충청북도 옥천군
URLhttps://www.data.go.kr/data/15078520/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 started2023-12-12 07:09:41.306057
Analysis finished2023-12-12 07:09:41.773902
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
충청북도
36 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청북도 36
100.0%

Length

2023-12-12T16:09:41.841849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:09:41.933890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청북도 36
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
옥천군
36 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
옥천군 36
100.0%

Length

2023-12-12T16:09:42.047194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:09:42.146375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
옥천군 36
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
43730
36 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row43730
2nd row43730
3rd row43730
4th row43730
5th row43730

Common Values

ValueCountFrequency (%)
43730 36
100.0%

Length

2023-12-12T16:09:42.269674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:09:42.720181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
43730 36
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2021
36 

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 36
100.0%

Length

2023-12-12T16:09:42.881718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:09:42.989738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 36
100.0%

세목명
Categorical

Distinct10
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
등록세
4 
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
Other values (5)
16 

Length

Max length7
Median length5
Mean length4.2222222
Min length3

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
등록세 4
11.1%
재산세 4
11.1%
주민세 4
11.1%
취득세 4
11.1%
자동차세 4
11.1%
등록면허세 4
11.1%
지방소득세 4
11.1%
지역자원시설세 4
11.1%
담배소비세 3
8.3%
지방소비세 1
 
2.8%

Length

2023-12-12T16:09:43.109886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:09:43.291345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등록세 4
11.1%
재산세 4
11.1%
주민세 4
11.1%
취득세 4
11.1%
자동차세 4
11.1%
등록면허세 4
11.1%
지방소득세 4
11.1%
지역자원시설세 4
11.1%
담배소비세 3
8.3%
지방소비세 1
 
2.8%

납세자유형
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
법인
19 
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 19
52.8%
개인 17
47.2%

Length

2023-12-12T16:09:43.438135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:09:43.548096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 19
52.8%
개인 17
47.2%

관내_관외
Boolean

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size168.0 B
False
18 
True
18 
ValueCountFrequency (%)
False 18
50.0%
True 18
50.0%
2023-12-12T16:09:43.632503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

Distinct33
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3860.3889
Minimum1
Maximum34053
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T16:09:43.736651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q143.5
median733
Q32087
95-th percentile22832.75
Maximum34053
Range34052
Interquartile range (IQR)2043.5

Descriptive statistics

Standard deviation7984.2322
Coefficient of variation (CV)2.0682456
Kurtosis6.5657145
Mean3860.3889
Median Absolute Deviation (MAD)715.5
Skewness2.6504581
Sum138974
Variance63747963
MonotonicityNot monotonic
2023-12-12T16:09:43.865196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 3
 
8.3%
4 2
 
5.6%
293 1
 
2.8%
1285 1
 
2.8%
51 1
 
2.8%
3125 1
 
2.8%
7465 1
 
2.8%
785 1
 
2.8%
987 1
 
2.8%
7320 1
 
2.8%
Other values (23) 23
63.9%
ValueCountFrequency (%)
1 3
8.3%
3 1
 
2.8%
4 2
5.6%
9 1
 
2.8%
14 1
 
2.8%
21 1
 
2.8%
51 1
 
2.8%
119 1
 
2.8%
166 1
 
2.8%
230 1
 
2.8%
ValueCountFrequency (%)
34053 1
2.8%
24815 1
2.8%
22172 1
2.8%
17863 1
2.8%
7465 1
2.8%
7320 1
2.8%
6318 1
2.8%
3125 1
2.8%
3014 1
2.8%
1778 1
2.8%

Interactions

2023-12-12T16:09:41.485972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:09:43.955774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납세자유형관내_관외납세자수
세목명1.0000.0000.0000.000
납세자유형0.0001.0000.0000.329
관내_관외0.0000.0001.0000.233
납세자수0.0000.3290.2331.000
2023-12-12T16:09:44.063219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명관내_관외납세자유형
세목명1.0000.0000.000
관내_관외0.0001.0000.000
납세자유형0.0000.0001.000
2023-12-12T16:09:44.171819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수세목명납세자유형관내_관외
납세자수1.0000.0000.3180.220
세목명0.0001.0000.0000.000
납세자유형0.3180.0001.0000.000
관내_관외0.2200.0000.0001.000

Missing values

2023-12-12T16:09:41.602340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:09:41.722089image/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
0충청북도옥천군437302021등록세개인N293
1충청북도옥천군437302021등록세개인Y259
2충청북도옥천군437302021등록세법인N1
3충청북도옥천군437302021등록세법인Y14
4충청북도옥천군437302021재산세개인N34053
5충청북도옥천군437302021재산세개인Y24815
6충청북도옥천군437302021재산세법인N765
7충청북도옥천군437302021재산세법인Y1778
8충청북도옥천군437302021주민세개인N1234
9충청북도옥천군437302021주민세개인Y22172
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
26충청북도옥천군437302021등록면허세법인Y987
27충청북도옥천군437302021지방소득세개인N1285
28충청북도옥천군437302021지방소득세개인Y7320
29충청북도옥천군437302021지방소득세법인N344
30충청북도옥천군437302021지방소득세법인Y916
31충청북도옥천군437302021지방소비세법인Y1
32충청북도옥천군437302021지역자원시설세개인N9
33충청북도옥천군437302021지역자원시설세개인Y21
34충청북도옥천군437302021지역자원시설세법인N3
35충청북도옥천군437302021지역자원시설세법인Y4