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

Description대구광역시 북구_지방세 납세자 현황_20201231
Author대구광역시 북구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15078492&dataSetDetailId=150784921b8cce01d5ed4&provdMethod=FILE

Alerts

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

Reproduction

Analysis started2024-04-20 21:07:22.801898
Analysis finished2024-04-20 21:07:23.595812
Duration0.79 seconds
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
대구광역시
33 

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 33
100.0%

Length

2024-04-21T06:07:23.707408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T06:07:23.939467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 33
100.0%

시군구명
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
북구 33
100.0%

Length

2024-04-21T06:07:24.179469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T06:07:24.487014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
북구 33
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size392.0 B
27230
33 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row27230
2nd row27230
3rd row27230
4th row27230
5th row27230

Common Values

ValueCountFrequency (%)
27230 33
100.0%

Length

2024-04-21T06:07:24.797764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T06:07:25.098807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
27230 33
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size392.0 B
2020
33 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 33
100.0%

Length

2024-04-21T06:07:25.416552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T06:07:25.723300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 33
100.0%

세목명
Categorical

Distinct9
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Memory size392.0 B
등록세
4 
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
Other values (4)
13 

Length

Max length7
Median length5
Mean length4.1515152
Min length3

Unique

Unique1 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
등록세 4
12.1%
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%
지방소비세 1
 
3.0%

Length

2024-04-21T06:07:26.078130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T06:07:26.422069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등록세 4
12.1%
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%
지방소비세 1
 
3.0%

납세자유형
Categorical

HIGH CORRELATION 

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

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 17
51.5%
개인 16
48.5%

Length

2024-04-21T06:07:26.666981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T06:07:26.838753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 17
51.5%
개인 16
48.5%

관내관외
Boolean

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size161.0 B
True
17 
False
16 
ValueCountFrequency (%)
True 17
51.5%
False 16
48.5%
2024-04-21T06:07:27.009819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21217.758
Minimum1
Maximum151340
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size425.0 B
2024-04-21T06:07:27.194761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q1127
median2672
Q319862
95-th percentile122083.8
Maximum151340
Range151339
Interquartile range (IQR)19735

Descriptive statistics

Standard deviation39500.683
Coefficient of variation (CV)1.8616804
Kurtosis4.9103128
Mean21217.758
Median Absolute Deviation (MAD)2626
Skewness2.3579372
Sum700186
Variance1.560304 × 109
MonotonicityNot monotonic
2024-04-21T06:07:27.411110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 3
 
9.1%
90 1
 
3.0%
532 1
 
3.0%
51 1
 
3.0%
26 1
 
3.0%
127 1
 
3.0%
105 1
 
3.0%
3976 1
 
3.0%
1747 1
 
3.0%
62010 1
 
3.0%
Other values (21) 21
63.6%
ValueCountFrequency (%)
1 3
9.1%
26 1
 
3.0%
46 1
 
3.0%
51 1
 
3.0%
90 1
 
3.0%
105 1
 
3.0%
127 1
 
3.0%
462 1
 
3.0%
532 1
 
3.0%
881 1
 
3.0%
ValueCountFrequency (%)
151340 1
3.0%
134130 1
3.0%
114053 1
3.0%
62010 1
3.0%
44525 1
3.0%
44246 1
3.0%
37877 1
3.0%
23529 1
3.0%
19862 1
3.0%
18808 1
3.0%

Interactions

2024-04-21T06:07:23.076275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T06:07:27.605231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납세자유형관내관외납세자수
세목명1.0000.0000.0000.000
납세자유형0.0001.0000.0000.545
관내관외0.0000.0001.0000.209
납세자수0.0000.5450.2091.000
2024-04-21T06:07:27.761515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자유형관내관외세목명
납세자유형1.0000.0000.000
관내관외0.0001.0000.000
세목명0.0000.0001.000
2024-04-21T06:07:27.907661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자수세목명납세자유형관내관외
납세자수1.0000.0000.5320.191
세목명0.0001.0000.0000.000
납세자유형0.5320.0001.0000.000
관내관외0.1910.0000.0001.000

Missing values

2024-04-21T06:07:23.295863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T06:07:23.512857image/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

시도명시군구명자치단체코드과세년도세목명납세자유형관내관외납세자수
0대구광역시북구272302020등록세개인N90
1대구광역시북구272302020등록세개인Y46
2대구광역시북구272302020등록세법인N1
3대구광역시북구272302020등록세법인Y1
4대구광역시북구272302020재산세개인N44246
5대구광역시북구272302020재산세개인Y114053
6대구광역시북구272302020재산세법인N881
7대구광역시북구272302020재산세법인Y1305
8대구광역시북구272302020주민세개인N23529
9대구광역시북구272302020주민세개인Y151340
시도명시군구명자치단체코드과세년도세목명납세자유형관내관외납세자수
23대구광역시북구272302020등록면허세법인Y3772
24대구광역시북구272302020지방소득세개인N14227
25대구광역시북구272302020지방소득세개인Y62010
26대구광역시북구272302020지방소득세법인N1747
27대구광역시북구272302020지방소득세법인Y3976
28대구광역시북구272302020지방소비세법인Y1
29대구광역시북구272302020지역자원시설세개인N105
30대구광역시북구272302020지역자원시설세개인Y127
31대구광역시북구272302020지역자원시설세법인N26
32대구광역시북구272302020지역자원시설세법인Y51