Overview

Dataset statistics

Number of variables8
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory70.9 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description부산광역시 연제구 지방세 납세자 현황에 대한 데이터로 세목별, 유형별 항목 등에 따른 납세자수 현황 데이터를 제공합니다.
Author부산광역시 연제구
URLhttps://www.data.go.kr/data/15079343/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
납세자수 has unique valuesUnique

Reproduction

Analysis started2024-03-14 20:48:22.059562
Analysis finished2024-03-14 20:48:23.369815
Duration1.31 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size392.0 B
부산광역시
33 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 33
100.0%

Length

2024-03-15T05:48:23.612556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:48:23.952365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 33
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size392.0 B
연제구
33 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연제구 33
100.0%

Length

2024-03-15T05:48:24.304239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:48:24.638267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
연제구 33
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size392.0 B
26470
33 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26470
2nd row26470
3rd row26470
4th row26470
5th row26470

Common Values

ValueCountFrequency (%)
26470 33
100.0%

Length

2024-03-15T05:48:25.122549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:48:25.504496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26470 33
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size392.0 B
2022
33 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 33
100.0%

Length

2024-03-15T05:48:25.891809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:48:26.209984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 33
100.0%

세목명
Categorical

Distinct10
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Memory size392.0 B
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
등록면허세
4 
Other values (5)
13 

Length

Max length7
Median length5
Mean length4.1515152
Min length3

Unique

Unique1 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 4
12.1%
주민세 4
12.1%
취득세 4
12.1%
자동차세 4
12.1%
등록면허세 4
12.1%
지방소득세 4
12.1%
지역자원시설세 4
12.1%
등록세 2
6.1%
레저세 2
6.1%
지방소비세 1
 
3.0%

Length

2024-03-15T05:48:26.583749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:48:27.188254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 4
12.1%
주민세 4
12.1%
취득세 4
12.1%
자동차세 4
12.1%
등록면허세 4
12.1%
지방소득세 4
12.1%
지역자원시설세 4
12.1%
등록세 2
6.1%
레저세 2
6.1%
지방소비세 1
 
3.0%

납세자유형
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size392.0 B
개인
17 
법인
16 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 17
51.5%
법인 16
48.5%

Length

2024-03-15T05:48:27.505361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:48:27.690706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 17
51.5%
법인 16
48.5%

관내_관외
Boolean

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size161.0 B
False
17 
True
16 
ValueCountFrequency (%)
False 17
51.5%
True 16
48.5%
2024-03-15T05:48:27.846818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10318.515
Minimum1
Maximum76747
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size425.0 B
2024-03-15T05:48:28.030274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.6
Q152
median1711
Q39144
95-th percentile57375.8
Maximum76747
Range76746
Interquartile range (IQR)9092

Descriptive statistics

Standard deviation19699.494
Coefficient of variation (CV)1.9091404
Kurtosis4.536133
Mean10318.515
Median Absolute Deviation (MAD)1690
Skewness2.3067044
Sum340511
Variance3.8807007 × 108
MonotonicityNot monotonic
2024-03-15T05:48:28.289589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
21 1
 
3.0%
42045 1
 
3.0%
1711 1
 
3.0%
12333 1
 
3.0%
16004 1
 
3.0%
1768 1
 
3.0%
2317 1
 
3.0%
11554 1
 
3.0%
1126 1
 
3.0%
9 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
1 1
3.0%
2 1
3.0%
3 1
3.0%
9 1
3.0%
10 1
3.0%
21 1
3.0%
22 1
3.0%
27 1
3.0%
52 1
3.0%
157 1
3.0%
ValueCountFrequency (%)
76747 1
3.0%
60830 1
3.0%
55073 1
3.0%
42045 1
3.0%
28662 1
3.0%
16004 1
3.0%
12333 1
3.0%
11554 1
3.0%
9144 1
3.0%
6684 1
3.0%

Interactions

2024-03-15T05:48:22.340240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:48:28.535712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납세자유형관내_관외납세자수
세목명1.0000.0000.0000.000
납세자유형0.0001.0000.0000.427
관내_관외0.0000.0001.0000.319
납세자수0.0000.4270.3191.000
2024-03-15T05:48:28.709728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관내_관외납세자유형세목명
관내_관외1.0000.0000.000
납세자유형0.0001.0000.000
세목명0.0000.0001.000
2024-03-15T05:48:28.879846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수세목명납세자유형관내_관외
납세자수1.0000.0000.4130.304
세목명0.0001.0000.0000.000
납세자유형0.4130.0001.0000.000
관내_관외0.3040.0000.0001.000

Missing values

2024-03-15T05:48:22.758086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:48:23.203729image/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
0부산광역시연제구264702022등록세개인N21
1부산광역시연제구264702022등록세개인Y9
2부산광역시연제구264702022레저세개인N3
3부산광역시연제구264702022레저세법인N2
4부산광역시연제구264702022재산세개인N28662
5부산광역시연제구264702022재산세개인Y60830
6부산광역시연제구264702022재산세법인N697
7부산광역시연제구264702022재산세법인Y615
8부산광역시연제구264702022주민세개인N9144
9부산광역시연제구264702022주민세개인Y76747
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
23부산광역시연제구264702022등록면허세법인Y2317
24부산광역시연제구264702022지방소득세개인N11554
25부산광역시연제구264702022지방소득세개인Y42045
26부산광역시연제구264702022지방소득세법인N1126
27부산광역시연제구264702022지방소득세법인Y2482
28부산광역시연제구264702022지방소비세법인Y1
29부산광역시연제구264702022지역자원시설세개인N27
30부산광역시연제구264702022지역자원시설세개인Y52
31부산광역시연제구264702022지역자원시설세법인N10
32부산광역시연제구264702022지역자원시설세법인Y22