Overview

Dataset statistics

Number of variables8
Number of observations134
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory68.0 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description최근 3년간 지방세 부과 징수 자료에 따른 지방세 세목별 통계자료를 근거로 연도별 지방세 세원유형별 과세 현황을 추출한 자료에 해당됩니다
Author충청북도 진천군
URLhttps://www.data.go.kr/data/15079482/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
납세자수 is highly overall correlated with 납세자유형High correlation
납세자유형 is highly overall correlated with 납세자수High correlation

Reproduction

Analysis started2024-03-30 09:20:02.666117
Analysis finished2024-03-30 09:20:04.512367
Duration1.85 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
충청북도
134 

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 134
100.0%

Length

2024-03-30T09:20:04.795549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-30T09:20:05.249033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청북도 134
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
진천군
134 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진천군 134
100.0%

Length

2024-03-30T09:20:05.756559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-30T09:20:06.285768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진천군 134
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
43750
134 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row43750
2nd row43750
3rd row43750
4th row43750
5th row43750

Common Values

ValueCountFrequency (%)
43750 134
100.0%

Length

2024-03-30T09:20:06.743071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-30T09:20:07.207703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
43750 134
100.0%

과세년도
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2022
35 
2020
34 
2021
33 
2019
32 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2022 35
26.1%
2020 34
25.4%
2021 33
24.6%
2019 32
23.9%

Length

2024-03-30T09:20:07.572965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-30T09:20:07.943315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 35
26.1%
2020 34
25.4%
2021 33
24.6%
2019 32
23.9%

세목명
Categorical

Distinct11
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
등록세
16 
재산세
16 
주민세
16 
취득세
16 
자동차세
16 
Other values (6)
54 

Length

Max length7
Median length5
Mean length4.0149254
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
등록세 16
11.9%
재산세 16
11.9%
주민세 16
11.9%
취득세 16
11.9%
자동차세 16
11.9%
등록면허세 16
11.9%
지방소득세 16
11.9%
담배소비세 9
6.7%
지역자원시설세 8
6.0%
지방소비세 3
 
2.2%

Length

2024-03-30T09:20:08.628240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록세 16
11.9%
재산세 16
11.9%
주민세 16
11.9%
취득세 16
11.9%
자동차세 16
11.9%
등록면허세 16
11.9%
지방소득세 16
11.9%
담배소비세 9
6.7%
지역자원시설세 8
6.0%
지방소비세 3
 
2.2%

납세자유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
법인
74 
개인
60 

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 74
55.2%
개인 60
44.8%

Length

2024-03-30T09:20:09.299861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-30T09:20:10.008412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 74
55.2%
개인 60
44.8%

관내_관외
Boolean

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size266.0 B
False
69 
True
65 
ValueCountFrequency (%)
False 69
51.5%
True 65
48.5%
2024-03-30T09:20:10.722118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

HIGH CORRELATION 

Distinct116
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5526.3433
Minimum1
Maximum35654
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T09:20:11.660064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q1115.75
median1566
Q34723
95-th percentile29173.65
Maximum35654
Range35653
Interquartile range (IQR)4607.25

Descriptive statistics

Standard deviation9525.6668
Coefficient of variation (CV)1.7236835
Kurtosis2.8607036
Mean5526.3433
Median Absolute Deviation (MAD)1560.5
Skewness2.0488482
Sum740530
Variance90738327
MonotonicityNot monotonic
2024-03-30T09:20:12.490227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 6
 
4.5%
2 4
 
3.0%
5 4
 
3.0%
3 4
 
3.0%
6 3
 
2.2%
4 3
 
2.2%
1633 1
 
0.7%
4799 1
 
0.7%
10487 1
 
0.7%
3523 1
 
0.7%
Other values (106) 106
79.1%
ValueCountFrequency (%)
1 6
4.5%
2 4
3.0%
3 4
3.0%
4 3
2.2%
5 4
3.0%
6 3
2.2%
7 1
 
0.7%
10 1
 
0.7%
11 1
 
0.7%
29 1
 
0.7%
ValueCountFrequency (%)
35654 1
0.7%
34744 1
0.7%
34575 1
0.7%
33287 1
0.7%
31463 1
0.7%
31280 1
0.7%
30499 1
0.7%
28460 1
0.7%
27804 1
0.7%
27782 1
0.7%

Interactions

2024-03-30T09:20:03.234932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T09:20:13.456581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명납세자유형관내_관외납세자수
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0000.0760.0000.534
납세자유형0.0000.0761.0000.0000.882
관내_관외0.0000.0000.0001.0000.593
납세자수0.0000.5340.8820.5931.000
2024-03-30T09:20:15.151121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도관내_관외세목명납세자유형
과세년도1.0000.0000.0000.000
관내_관외0.0001.0000.0000.000
세목명0.0000.0001.0000.066
납세자유형0.0000.0000.0661.000
2024-03-30T09:20:15.521214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수과세년도세목명납세자유형관내_관외
납세자수1.0000.0000.2820.6900.438
과세년도0.0001.0000.0000.0000.000
세목명0.2820.0001.0000.0660.000
납세자유형0.6900.0000.0661.0000.000
관내_관외0.4380.0000.0000.0001.000

Missing values

2024-03-30T09:20:03.812781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T09:20:04.319015image/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
0충청북도진천군437502019등록세개인N92
1충청북도진천군437502019등록세개인Y104
2충청북도진천군437502019등록세법인N2
3충청북도진천군437502019등록세법인Y5
4충청북도진천군437502019재산세개인N27502
5충청북도진천군437502019재산세개인Y25584
6충청북도진천군437502019재산세법인N899
7충청북도진천군437502019재산세법인Y1668
8충청북도진천군437502019주민세개인N4090
9충청북도진천군437502019주민세개인Y31280
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
124충청북도진천군437502022등록면허세개인Y10590
125충청북도진천군437502022등록면허세법인N1571
126충청북도진천군437502022등록면허세법인Y1717
127충청북도진천군437502022지방소득세개인N5205
128충청북도진천군437502022지방소득세개인Y17281
129충청북도진천군437502022지방소득세법인N989
130충청북도진천군437502022지방소득세법인Y1781
131충청북도진천군437502022지방소비세법인Y1
132충청북도진천군437502022지역자원시설세법인N3
133충청북도진천군437502022지역자원시설세법인Y7