Overview

Dataset statistics

Number of variables8
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory69.6 B

Variable types

Categorical6
Boolean1
Numeric1

Dataset

Description대구광역시_지방세납세자현황_20201231
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15079143&dataSetDetailId=150791431a07f55bb61e9&provdMethod=FILE

Alerts

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

Reproduction

Analysis started2023-12-10 19:23:47.605510
Analysis finished2023-12-10 19:23:48.430589
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
대구광역시
51 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 51
100.0%

Length

2023-12-11T04:23:48.534227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:48.676731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 51
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
대구광역시
51 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 51
100.0%

Length

2023-12-11T04:23:48.820452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:48.959321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 51
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
27000
51 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row27000
2nd row27000
3rd row27000
4th row27000
5th row27000

Common Values

ValueCountFrequency (%)
27000 51
100.0%

Length

2023-12-11T04:23:49.117298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:49.257522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
27000 51
100.0%

과세년도
Categorical

Distinct4
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size540.0 B
2017
14 
2018
13 
2019
12 
2020
12 

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 (%)
2017 14
27.5%
2018 13
25.5%
2019 12
23.5%
2020 12
23.5%

Length

2023-12-11T04:23:49.587873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:49.893956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 14
27.5%
2018 13
25.5%
2019 12
23.5%
2020 12
23.5%

세목명
Categorical

Distinct6
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size540.0 B
담배소비세
16 
지방소득세
15 
취득세
10 
자동차세
5 
지방소비세
4 

Length

Max length5
Median length5
Mean length4.5098039
Min length3

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row취득세
2nd row취득세
3rd row취득세
4th row취득세
5th row자동차세

Common Values

ValueCountFrequency (%)
담배소비세 16
31.4%
지방소득세 15
29.4%
취득세 10
19.6%
자동차세 5
 
9.8%
지방소비세 4
 
7.8%
등록면허세 1
 
2.0%

Length

2023-12-11T04:23:50.210442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:50.427591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
담배소비세 16
31.4%
지방소득세 15
29.4%
취득세 10
19.6%
자동차세 5
 
9.8%
지방소비세 4
 
7.8%
등록면허세 1
 
2.0%

납세자유형
Categorical

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
개인
30 
법인
21 

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 30
58.8%
법인 21
41.2%

Length

2023-12-11T04:23:50.677215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:23:50.822345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 30
58.8%
법인 21
41.2%

관내_관외
Boolean

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size183.0 B
True
32 
False
19 
ValueCountFrequency (%)
True 32
62.7%
False 19
37.3%
2023-12-11T04:23:50.984080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

Distinct15
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6470588
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-11T04:23:51.147634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q36.5
95-th percentile13.5
Maximum27
Range26
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation5.0549917
Coefficient of variation (CV)1.087783
Kurtosis6.7952286
Mean4.6470588
Median Absolute Deviation (MAD)2
Skewness2.2817955
Sum237
Variance25.552941
MonotonicityNot monotonic
2023-12-11T04:23:51.338515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 17
33.3%
3 7
13.7%
2 7
13.7%
5 3
 
5.9%
7 3
 
5.9%
8 2
 
3.9%
6 2
 
3.9%
11 2
 
3.9%
4 2
 
3.9%
12 1
 
2.0%
Other values (5) 5
 
9.8%
ValueCountFrequency (%)
1 17
33.3%
2 7
13.7%
3 7
13.7%
4 2
 
3.9%
5 3
 
5.9%
6 2
 
3.9%
7 3
 
5.9%
8 2
 
3.9%
9 1
 
2.0%
11 2
 
3.9%
ValueCountFrequency (%)
27 1
 
2.0%
16 1
 
2.0%
14 1
 
2.0%
13 1
 
2.0%
12 1
 
2.0%
11 2
3.9%
9 1
 
2.0%
8 2
3.9%
7 3
5.9%
6 2
3.9%

Interactions

2023-12-11T04:23:47.947742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T04:23:51.487245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명납세자유형관내_관외납세자수
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0000.1370.3340.217
납세자유형0.0000.1371.0000.0000.322
관내_관외0.0000.3340.0001.0000.142
납세자수0.0000.2170.3220.1421.000
2023-12-11T04:23:51.642928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도관내_관외납세자유형세목명
과세년도1.0000.0000.0000.000
관내_관외0.0001.0000.0000.226
납세자유형0.0000.0001.0000.083
세목명0.0000.2260.0831.000
2023-12-11T04:23:51.789792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수과세년도세목명납세자유형관내_관외
납세자수1.0000.0000.0970.3230.135
과세년도0.0001.0000.0000.0000.000
세목명0.0970.0001.0000.0830.226
납세자유형0.3230.0000.0831.0000.000
관내_관외0.1350.0000.2260.0001.000

Missing values

2023-12-11T04:23:48.160124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T04:23:48.349506image/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
0대구광역시대구광역시270002017취득세개인N1
1대구광역시대구광역시270002017취득세개인Y3
2대구광역시대구광역시270002017취득세법인N2
3대구광역시대구광역시270002017취득세법인Y2
4대구광역시대구광역시270002017자동차세개인Y1
5대구광역시대구광역시270002017자동차세법인Y1
6대구광역시대구광역시270002017담배소비세개인N8
7대구광역시대구광역시270002017담배소비세개인Y5
8대구광역시대구광역시270002017담배소비세법인N6
9대구광역시대구광역시270002017담배소비세법인Y3
시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
41대구광역시대구광역시270002020담배소비세개인N27
42대구광역시대구광역시270002020담배소비세개인Y7
43대구광역시대구광역시270002020담배소비세법인N5
44대구광역시대구광역시270002020담배소비세법인Y4
45대구광역시대구광역시270002020등록면허세개인Y1
46대구광역시대구광역시270002020지방소득세개인N3
47대구광역시대구광역시270002020지방소득세개인Y16
48대구광역시대구광역시270002020지방소득세법인N2
49대구광역시대구광역시270002020지방소득세법인Y4
50대구광역시대구광역시270002020지방소비세개인Y1