Overview

Dataset statistics

Number of variables8
Number of observations93
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory69.4 B

Variable types

Categorical5
Text1
Numeric2

Dataset

Description지방세 과세를 위해 세원이 되는 과세 대상 유형별 부과된 현황을 제공하는 데이터로, 물건 유형에 따른 세부담 수준의 형평성 검토 및 부동산 등 관련분야 규제정책 대상 확인 시 기초자료로 활용됩니다.
Author인천광역시 연수구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15079016&srcSe=7661IVAWM27C61E190

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
부과건수 is highly overall correlated with 부과금액(만원) and 1 other fieldsHigh correlation
부과금액(만원) is highly overall correlated with 부과건수High correlation
세목명 is highly overall correlated with 부과건수High correlation
부과건수 has 22 (23.7%) zerosZeros
부과금액(만원) has 22 (23.7%) zerosZeros

Reproduction

Analysis started2024-01-28 12:51:58.201590
Analysis finished2024-01-28 12:51:58.868786
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
인천광역시
93 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 93
100.0%

Length

2024-01-28T21:51:58.916984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:51:58.985375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 93
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
연수구
93 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연수구 93
100.0%

Length

2024-01-28T21:51:59.054507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:51:59.118732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
연수구 93
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
28185
93 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28185
2nd row28185
3rd row28185
4th row28185
5th row28185

Common Values

ValueCountFrequency (%)
28185 93
100.0%

Length

2024-01-28T21:51:59.184644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:51:59.263451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28185 93
100.0%

과세년도
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
2020
47 
2021
46 

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 47
50.5%
2021 46
49.5%

Length

2024-01-28T21:51:59.338158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:51:59.404871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 47
50.5%
2021 46
49.5%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size876.0 B
취득세
18 
주민세
16 
자동차세
14 
재산세
10 
레저세
8 
Other values (8)
27 

Length

Max length7
Median length3
Mean length3.7311828
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 18
19.4%
주민세 16
17.2%
자동차세 14
15.1%
재산세 10
10.8%
레저세 8
8.6%
지방소득세 8
8.6%
지역자원시설세 5
 
5.4%
등록면허세 4
 
4.3%
담배소비세 2
 
2.2%
교육세 2
 
2.2%
Other values (3) 6
 
6.5%

Length

2024-01-28T21:51:59.497618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 18
19.4%
주민세 16
17.2%
자동차세 14
15.1%
재산세 10
10.8%
레저세 8
8.6%
지방소득세 8
8.6%
지역자원시설세 5
 
5.4%
등록면허세 4
 
4.3%
담배소비세 2
 
2.2%
교육세 2
 
2.2%
Other values (3) 6
 
6.5%

세원 유형명
Text

Distinct50
Distinct (%)53.8%
Missing0
Missing (%)0.0%
Memory size876.0 B
2024-01-28T21:51:59.690285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length6.0322581
Min length2

Characters and Unicode

Total characters561
Distinct characters74
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

Unique7 ?
Unique (%)7.5%

Sample

1st row담배소비세
2nd row교육세
3rd row도시계획세
4th row건축물
5th row주택(개별)
ValueCountFrequency (%)
담배소비세 2
 
2.2%
도시계획세 2
 
2.2%
지방소득세(종합소득 2
 
2.2%
승합 2
 
2.2%
교육세 2
 
2.2%
기타승용 2
 
2.2%
승용 2
 
2.2%
지방소비세 2
 
2.2%
지방소득세(특별징수 2
 
2.2%
체납 2
 
2.2%
Other values (40) 73
78.5%
2024-01-28T21:51:59.981353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 55
 
9.8%
) 49
 
8.7%
( 49
 
8.7%
소 27
 
4.8%
주 24
 
4.3%
지 19
 
3.4%
득 18
 
3.2%
민 16
 
2.9%
방 12
 
2.1%
산 11
 
2.0%
Other values (64) 281
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 461
82.2%
Close Punctuation 49
 
8.7%
Open Punctuation 49
 
8.7%
Decimal Number 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 55
 
11.9%
소 27
 
5.9%
주 24
 
5.2%
지 19
 
4.1%
득 18
 
3.9%
민 16
 
3.5%
방 12
 
2.6%
산 11
 
2.4%
재 11
 
2.4%
기 10
 
2.2%
Other values (61) 258
56.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Decimal Number
ValueCountFrequency (%)
3 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 461
82.2%
Common 100
 
17.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 55
 
11.9%
소 27
 
5.9%
주 24
 
5.2%
지 19
 
4.1%
득 18
 
3.9%
민 16
 
3.5%
방 12
 
2.6%
산 11
 
2.4%
재 11
 
2.4%
기 10
 
2.2%
Other values (61) 258
56.0%
Common
ValueCountFrequency (%)
) 49
49.0%
( 49
49.0%
3 2
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 461
82.2%
ASCII 100
 
17.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 55
 
11.9%
소 27
 
5.9%
주 24
 
5.2%
지 19
 
4.1%
득 18
 
3.9%
민 16
 
3.5%
방 12
 
2.6%
산 11
 
2.4%
재 11
 
2.4%
기 10
 
2.2%
Other values (61) 258
56.0%
ASCII
ValueCountFrequency (%)
) 49
49.0%
( 49
49.0%
3 2
 
2.0%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct70
Distinct (%)75.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51317.914
Minimum0
Maximum890481
Zeros22
Zeros (%)23.7%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-01-28T21:52:00.098019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2198
Q326296
95-th percentile285912.8
Maximum890481
Range890481
Interquartile range (IQR)26295

Descriptive statistics

Standard deviation140491.07
Coefficient of variation (CV)2.7376614
Kurtosis23.818545
Mean51317.914
Median Absolute Deviation (MAD)2198
Skewness4.6009636
Sum4772566
Variance1.9737742 × 1010
MonotonicityNot monotonic
2024-01-28T21:52:00.202858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22
 
23.7%
1 3
 
3.2%
4908 1
 
1.1%
1800 1
 
1.1%
1264 1
 
1.1%
34190 1
 
1.1%
59 1
 
1.1%
26296 1
 
1.1%
150619 1
 
1.1%
8357 1
 
1.1%
Other values (60) 60
64.5%
ValueCountFrequency (%)
0 22
23.7%
1 3
 
3.2%
4 1
 
1.1%
5 1
 
1.1%
7 1
 
1.1%
12 1
 
1.1%
23 1
 
1.1%
43 1
 
1.1%
53 1
 
1.1%
57 1
 
1.1%
ValueCountFrequency (%)
890481 1
1.1%
841900 1
1.1%
322412 1
1.1%
301961 1
1.1%
295742 1
1.1%
279360 1
1.1%
230029 1
1.1%
150619 1
1.1%
142877 1
1.1%
141393 1
1.1%

부과금액(만원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct71
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1922704.9
Minimum0
Maximum15671600
Zeros22
Zeros (%)23.7%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-01-28T21:52:00.307974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median91913
Q32151825
95-th percentile9116890
Maximum15671600
Range15671600
Interquartile range (IQR)2151824

Descriptive statistics

Standard deviation3292924.2
Coefficient of variation (CV)1.7126519
Kurtosis4.2104096
Mean1922704.9
Median Absolute Deviation (MAD)91913
Skewness2.0728206
Sum1.7881156 × 108
Variance1.084335 × 1013
MonotonicityNot monotonic
2024-01-28T21:52:00.419485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22
 
23.7%
1 2
 
2.2%
24378 1
 
1.1%
5961 1
 
1.1%
1429 1
 
1.1%
2151825 1
 
1.1%
136 1
 
1.1%
5319833 1
 
1.1%
5732710 1
 
1.1%
22094 1
 
1.1%
Other values (61) 61
65.6%
ValueCountFrequency (%)
0 22
23.7%
1 2
 
2.2%
136 1
 
1.1%
153 1
 
1.1%
313 1
 
1.1%
539 1
 
1.1%
1228 1
 
1.1%
1429 1
 
1.1%
4646 1
 
1.1%
5961 1
 
1.1%
ValueCountFrequency (%)
15671600 1
1.1%
12500000 1
1.1%
11500000 1
1.1%
11330800 1
1.1%
9267181 1
1.1%
9016696 1
1.1%
6939235 1
1.1%
6921028 1
1.1%
6485957 1
1.1%
6457898 1
1.1%

Interactions

2024-01-28T21:51:58.527614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:51:58.403494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:51:58.606055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:51:58.457538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T21:52:00.504521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명세원 유형명부과건수부과금액(만원)
과세년도1.0000.0000.0000.0000.000
세목명0.0001.0001.0000.8240.644
세원 유형명0.0001.0001.0000.9700.863
부과건수0.0000.8240.9701.0000.535
부과금액(만원)0.0000.6440.8630.5351.000
2024-01-28T21:52:00.583526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도
세목명1.0000.000
과세년도0.0001.000
2024-01-28T21:52:00.650153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액(만원)과세년도세목명
부과건수1.0000.8450.0000.604
부과금액(만원)0.8451.0000.0000.346
과세년도0.0000.0001.0000.000
세목명0.6040.3460.0001.000

Missing values

2024-01-28T21:51:58.728759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T21:51:58.829318image/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(만원)
0인천광역시연수구281852020담배소비세담배소비세00
1인천광역시연수구281852020교육세교육세8419006321100
2인천광역시연수구281852020도시계획세도시계획세00
3인천광역시연수구281852020취득세건축물647811330800
4인천광역시연수구281852020취득세주택(개별)215250225
5인천광역시연수구281852020취득세주택(단독)2039615671600
6인천광역시연수구281852020취득세기타57120730
7인천광역시연수구281852020취득세항공기00
8인천광역시연수구281852020취득세기계장비9052022
9인천광역시연수구281852020취득세차량358626939235
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액(만원)
83인천광역시연수구281852021주민세주민세(특별징수)00
84인천광역시연수구281852021주민세주민세(법인세분)00
85인천광역시연수구281852021주민세주민세(양도소득)00
86인천광역시연수구281852021주민세주민세(종합소득)00
87인천광역시연수구281852021등록면허세등록면허세(면허)37723154052
88인천광역시연수구281852021등록면허세등록면허세(등록)869971428871
89인천광역시연수구281852021지역자원시설세지역자원시설세(소방)3224121905694
90인천광역시연수구281852021지역자원시설세지역자원시설세(시설)1224133
91인천광역시연수구281852021지역자원시설세지역자원시설세(특자)231313
92인천광역시연수구281852021체납체납2300292003507