Overview

Dataset statistics

Number of variables8
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory70.9 B

Variable types

Categorical5
Text1
Numeric2

Dataset

Description울산광역시 중구 세원유형별과세현황 데이터로 과세년도, 세목명, 세원 유형명, 부과건수, 부과금액 등으로 구성되어 있습니다.
URLhttps://www.data.go.kr/data/15078656/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
부과건수 is highly overall correlated with 부과금액High correlation
부과금액 is highly overall correlated with 부과건수High correlation
세원 유형명 has unique valuesUnique
부과건수 has 14 (30.4%) zerosZeros
부과금액 has 14 (30.4%) zerosZeros

Reproduction

Analysis started2023-12-12 14:24:05.793701
Analysis finished2023-12-12 14:24:06.648655
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
울산광역시
46 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
울산광역시 46
100.0%

Length

2023-12-12T23:24:06.732143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:24:06.832509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울산광역시 46
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
중구
46 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 46
100.0%

Length

2023-12-12T23:24:06.956544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:24:07.073128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 46
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
31110
46 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row31110
2nd row31110
3rd row31110
4th row31110
5th row31110

Common Values

ValueCountFrequency (%)
31110 46
100.0%

Length

2023-12-12T23:24:07.190805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:24:07.306038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
31110 46
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
2021
46 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 46
100.0%

Length

2023-12-12T23:24:07.425626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:24:07.524187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 46
100.0%

세목명
Categorical

Distinct13
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
취득세
9 
자동차세
7 
주민세
7 
재산세
5 
레저세
4 
Other values (8)
14 

Length

Max length7
Median length3
Mean length3.7826087
Min length2

Unique

Unique5 ?
Unique (%)10.9%

Sample

1st row담배소비세
2nd row교육세
3rd row도시계획세
4th row취득세
5th row취득세

Common Values

ValueCountFrequency (%)
취득세 9
19.6%
자동차세 7
15.2%
주민세 7
15.2%
재산세 5
10.9%
레저세 4
8.7%
지방소득세 4
8.7%
지역자원시설세 3
 
6.5%
등록면허세 2
 
4.3%
담배소비세 1
 
2.2%
교육세 1
 
2.2%
Other values (3) 3
 
6.5%

Length

2023-12-12T23:24:07.640751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 9
19.6%
자동차세 7
15.2%
주민세 7
15.2%
재산세 5
10.9%
레저세 4
8.7%
지방소득세 4
8.7%
지역자원시설세 3
 
6.5%
등록면허세 2
 
4.3%
담배소비세 1
 
2.2%
교육세 1
 
2.2%
Other values (3) 3
 
6.5%

세원 유형명
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-12T23:24:07.925505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length6.0217391
Min length2

Characters and Unicode

Total characters277
Distinct characters73
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row담배소비세
2nd row교육세
3rd row도시계획세
4th row건축물
5th row주택(개별)
ValueCountFrequency (%)
담배소비세 1
 
2.2%
주민세(사업소분 1
 
2.2%
지역자원시설세(특자 1
 
2.2%
승합 1
 
2.2%
기타승용 1
 
2.2%
승용 1
 
2.2%
지방소비세 1
 
2.2%
지방소득세(특별징수 1
 
2.2%
지방소득세(법인소득 1
 
2.2%
지방소득세(양도소득 1
 
2.2%
Other values (36) 36
78.3%
2023-12-12T23:24:08.370043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 27
 
9.7%
) 24
 
8.7%
( 24
 
8.7%
소 14
 
5.1%
주 11
 
4.0%
지 10
 
3.6%
득 9
 
3.2%
민 7
 
2.5%
방 6
 
2.2%
재 5
 
1.8%
Other values (63) 140
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 228
82.3%
Close Punctuation 24
 
8.7%
Open Punctuation 24
 
8.7%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 27
 
11.8%
소 14
 
6.1%
주 11
 
4.8%
지 10
 
4.4%
득 9
 
3.9%
민 7
 
3.1%
방 6
 
2.6%
재 5
 
2.2%
산 5
 
2.2%
시 5
 
2.2%
Other values (60) 129
56.6%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 228
82.3%
Common 49
 
17.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 27
 
11.8%
소 14
 
6.1%
주 11
 
4.8%
지 10
 
4.4%
득 9
 
3.9%
민 7
 
3.1%
방 6
 
2.6%
재 5
 
2.2%
산 5
 
2.2%
시 5
 
2.2%
Other values (60) 129
56.6%
Common
ValueCountFrequency (%)
) 24
49.0%
( 24
49.0%
3 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 228
82.3%
ASCII 49
 
17.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 27
 
11.8%
소 14
 
6.1%
주 11
 
4.8%
지 10
 
4.4%
득 9
 
3.9%
민 7
 
3.1%
방 6
 
2.6%
재 5
 
2.2%
산 5
 
2.2%
시 5
 
2.2%
Other values (60) 129
56.6%
ASCII
ValueCountFrequency (%)
) 24
49.0%
( 24
49.0%
3 1
 
2.0%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24631.565
Minimum0
Maximum406548
Zeros14
Zeros (%)30.4%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T23:24:08.497234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median802.5
Q316504.25
95-th percentile116291.5
Maximum406548
Range406548
Interquartile range (IQR)16504.25

Descriptive statistics

Standard deviation66788.076
Coefficient of variation (CV)2.7114832
Kurtosis24.376721
Mean24631.565
Median Absolute Deviation (MAD)802.5
Skewness4.5710753
Sum1133052
Variance4.4606471 × 109
MonotonicityNot monotonic
2023-12-12T23:24:08.660167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 14
30.4%
8888 1
 
2.2%
140785 1
 
2.2%
7 1
 
2.2%
27057 1
 
2.2%
1499 1
 
2.2%
4169 1
 
2.2%
31912 1
 
2.2%
84295 1
 
2.2%
406548 1
 
2.2%
Other values (23) 23
50.0%
ValueCountFrequency (%)
0 14
30.4%
7 1
 
2.2%
16 1
 
2.2%
30 1
 
2.2%
38 1
 
2.2%
63 1
 
2.2%
464 1
 
2.2%
656 1
 
2.2%
742 1
 
2.2%
784 1
 
2.2%
ValueCountFrequency (%)
406548 1
2.2%
140785 1
2.2%
119327 1
2.2%
107185 1
2.2%
84295 1
2.2%
79615 1
2.2%
33901 1
2.2%
31912 1
2.2%
27057 1
2.2%
22543 1
2.2%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0276065 × 109
Minimum0
Maximum2.0942 × 1010
Zeros14
Zeros (%)30.4%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T23:24:08.834434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.195255 × 108
Q35.770522 × 109
95-th percentile1.5822392 × 1010
Maximum2.0942 × 1010
Range2.0942 × 1010
Interquartile range (IQR)5.770522 × 109

Descriptive statistics

Standard deviation6.0022319 × 109
Coefficient of variation (CV)1.4902727
Kurtosis0.55637207
Mean4.0276065 × 109
Median Absolute Deviation (MAD)2.195255 × 108
Skewness1.3621167
Sum1.852699 × 1011
Variance3.6026788 × 1019
MonotonicityNot monotonic
2023-12-12T23:24:08.989825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 14
30.4%
735365000 1
 
2.2%
20942000000 1
 
2.2%
5454250000 1
 
2.2%
12227659000 1
 
2.2%
4186443000 1
 
2.2%
10847908000 1
 
2.2%
5875946000 1
 
2.2%
848291000 1
 
2.2%
15837227000 1
 
2.2%
Other values (23) 23
50.0%
ValueCountFrequency (%)
0 14
30.4%
1404000 1
 
2.2%
6465000 1
 
2.2%
12345000 1
 
2.2%
13611000 1
 
2.2%
18627000 1
 
2.2%
19020000 1
 
2.2%
59664000 1
 
2.2%
100937000 1
 
2.2%
141596000 1
 
2.2%
ValueCountFrequency (%)
20942000000 1
2.2%
16093830000 1
2.2%
15837227000 1
2.2%
15777885000 1
2.2%
15354813000 1
2.2%
14625271000 1
2.2%
13391463000 1
2.2%
12227659000 1
2.2%
10847908000 1
2.2%
9393634000 1
2.2%

Interactions

2023-12-12T23:24:06.236245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:06.008588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:06.340936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:24:06.130142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:24:09.090587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명세원 유형명부과건수부과금액
세목명1.0001.0000.7140.691
세원 유형명1.0001.0001.0001.000
부과건수0.7141.0001.0000.761
부과금액0.6911.0000.7611.000
2023-12-12T23:24:09.193988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액세목명
부과건수1.0000.8640.435
부과금액0.8641.0000.367
세목명0.4350.3671.000

Missing values

2023-12-12T23:24:06.461089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:24:06.591769image/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

시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
0울산광역시중구311102021담배소비세담배소비세00
1울산광역시중구311102021교육세교육세40654815837227000
2울산광역시중구311102021도시계획세도시계획세00
3울산광역시중구311102021취득세건축물7426083075000
4울산광역시중구311102021취득세주택(개별)142815777885000
5울산광역시중구311102021취득세주택(단독)375215354813000
6울산광역시중구311102021취득세기타16100937000
7울산광역시중구311102021취득세항공기00
8울산광역시중구311102021취득세기계장비3812345000
9울산광역시중구311102021취득세차량2071297455000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
36울산광역시중구311102021주민세주민세(특별징수)00
37울산광역시중구311102021주민세주민세(법인세분)00
38울산광역시중구311102021주민세주민세(양도소득)00
39울산광역시중구311102021주민세주민세(종합소득)00
40울산광역시중구311102021등록면허세등록면허세(면허)18781751302000
41울산광역시중구311102021등록면허세등록면허세(등록)339014103997000
42울산광역시중구311102021지역자원시설세지역자원시설세(소방)1071854283320000
43울산광역시중구311102021지역자원시설세지역자원시설세(시설)00
44울산광역시중구311102021지역자원시설세지역자원시설세(특자)46418627000
45울산광역시중구311102021체납체납1193279393634000