Overview

Dataset statistics

Number of variables8
Number of observations162
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.7 KiB
Average record size in memory67.8 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description지방세가 과세된 세목별 납세 인원 현황을 제공 (시도명 시군구명 자치단체코드 과세년도 세목명 납세자유형 관내/관외납세자수)
URLhttps://www.data.go.kr/data/15078328/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 13:59:34.512140
Analysis finished2023-12-12 13:59:35.148369
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
경상북도
162 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 162
100.0%

Length

2023-12-12T22:59:35.230930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:59:35.360933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 162
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
봉화군
162 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
봉화군 162
100.0%

Length

2023-12-12T22:59:35.458791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:59:35.573973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
봉화군 162
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
47920
162 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47920
2nd row47920
3rd row47920
4th row47920
5th row47920

Common Values

ValueCountFrequency (%)
47920 162
100.0%

Length

2023-12-12T22:59:35.706606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:59:35.815118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47920 162
100.0%

과세년도
Categorical

Distinct5
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2020
33 
2021
33 
2017
32 
2018
32 
2019
32 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2020 33
20.4%
2021 33
20.4%
2017 32
19.8%
2018 32
19.8%
2019 32
19.8%

Length

2023-12-12T22:59:35.940944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:59:36.078802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 33
20.4%
2021 33
20.4%
2017 32
19.8%
2018 32
19.8%
2019 32
19.8%

세목명
Categorical

Distinct10
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
재산세
20 
주민세
20 
취득세
20 
자동차세
20 
등록면허세
20 
Other values (5)
62 

Length

Max length7
Median length5
Mean length4.0246914
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 20
12.3%
주민세 20
12.3%
취득세 20
12.3%
자동차세 20
12.3%
등록면허세 20
12.3%
지방소득세 20
12.3%
등록세 19
11.7%
담배소비세 11
6.8%
지역자원시설세 10
6.2%
지방소비세 2
 
1.2%

Length

2023-12-12T22:59:36.245164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:59:36.387569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 20
12.3%
주민세 20
12.3%
취득세 20
12.3%
자동차세 20
12.3%
등록면허세 20
12.3%
지방소득세 20
12.3%
등록세 19
11.7%
담배소비세 11
6.8%
지역자원시설세 10
6.2%
지방소비세 2
 
1.2%

납세자유형
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
개인
82 
법인
80 

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 (%)
개인 82
50.6%
법인 80
49.4%

Length

2023-12-12T22:59:36.556097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:59:36.681353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 82
50.6%
법인 80
49.4%

관내/관외
Boolean

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size294.0 B
False
81 
True
81 
ValueCountFrequency (%)
False 81
50.0%
True 81
50.0%
2023-12-12T22:59:36.811614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

Distinct136
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2792.3333
Minimum1
Maximum23573
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T22:59:36.942900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q171
median478
Q31593.75
95-th percentile19747.65
Maximum23573
Range23572
Interquartile range (IQR)1522.75

Descriptive statistics

Standard deviation5704.079
Coefficient of variation (CV)2.0427644
Kurtosis5.1630458
Mean2792.3333
Median Absolute Deviation (MAD)474
Skewness2.5044742
Sum452358
Variance32536517
MonotonicityNot monotonic
2023-12-12T22:59:37.080770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 12
 
7.4%
1 11
 
6.8%
137 2
 
1.2%
494 2
 
1.2%
140 2
 
1.2%
3 2
 
1.2%
4 2
 
1.2%
658 1
 
0.6%
642 1
 
0.6%
4770 1
 
0.6%
Other values (126) 126
77.8%
ValueCountFrequency (%)
1 11
6.8%
2 12
7.4%
3 2
 
1.2%
4 2
 
1.2%
5 1
 
0.6%
6 1
 
0.6%
7 1
 
0.6%
28 1
 
0.6%
30 1
 
0.6%
31 1
 
0.6%
ValueCountFrequency (%)
23573 1
0.6%
23191 1
0.6%
22786 1
0.6%
22410 1
0.6%
21985 1
0.6%
19870 1
0.6%
19861 1
0.6%
19778 1
0.6%
19752 1
0.6%
19665 1
0.6%

Interactions

2023-12-12T22:59:34.799162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:59:37.185102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명납세자유형관내/관외납세자수
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0000.2880.0000.649
납세자유형0.0000.2881.0000.0000.458
관내/관외0.0000.0000.0001.0000.435
납세자수0.0000.6490.4580.4351.000
2023-12-12T22:59:37.616016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자유형관내/관외세목명과세년도
납세자유형1.0000.0000.2150.000
관내/관외0.0001.0000.0000.000
세목명0.2150.0001.0000.000
과세년도0.0000.0000.0001.000
2023-12-12T22:59:37.706541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수과세년도세목명납세자유형관내/관외
납세자수1.0000.0000.3970.4830.459
과세년도0.0001.0000.0000.0000.000
세목명0.3970.0001.0000.2150.000
납세자유형0.4830.0000.2151.0000.000
관내/관외0.4590.0000.0000.0001.000

Missing values

2023-12-12T22:59:34.923646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:59:35.087798image/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
0경상북도봉화군479202017등록세개인N137
1경상북도봉화군479202017등록세개인Y132
2경상북도봉화군479202017등록세법인N2
3경상북도봉화군479202017등록세법인Y6
4경상북도봉화군479202017재산세개인N21985
5경상북도봉화군479202017재산세개인Y19665
6경상북도봉화군479202017재산세법인N339
7경상북도봉화군479202017재산세법인Y898
8경상북도봉화군479202017주민세개인N1586
9경상북도봉화군479202017주민세개인Y14363
시도명시군구명자치단체코드과세년도세목명납세자유형관내/관외납세자수
152경상북도봉화군479202021등록면허세개인Y4983
153경상북도봉화군479202021등록면허세법인N642
154경상북도봉화군479202021등록면허세법인Y658
155경상북도봉화군479202021지방소득세개인N598
156경상북도봉화군479202021지방소득세개인Y3478
157경상북도봉화군479202021지방소득세법인N175
158경상북도봉화군479202021지방소득세법인Y541
159경상북도봉화군479202021지방소비세법인Y1
160경상북도봉화군479202021지역자원시설세개인N1
161경상북도봉화군479202021지역자원시설세개인Y2