Overview

Dataset statistics

Number of variables10
Number of observations35
Missing cells4
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory89.8 B

Variable types

Categorical6
Numeric4

Dataset

Description해당자료는 경기도 구리시의 지방세 비과감면율 2019년기준 2018년기준 2017년 기 준 현황 자료(시군구명, 자치단체코드, 세목명, 감면금액, 부과금액 등)에 대한 제공 입니다.
URLhttps://www.data.go.kr/data/15080567/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일자 has constant value ""Constant
비과세금액 is highly overall correlated with 감면금액 and 2 other fieldsHigh correlation
감면금액 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 비과세금액 and 3 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 비과세금액 and 3 other fieldsHigh correlation
세목명 is highly overall correlated with 부과금액 and 1 other fieldsHigh correlation
비과세금액 has 4 (11.4%) missing valuesMissing
감면금액 has unique valuesUnique
비과세금액 has 1 (2.9%) zerosZeros
부과금액 has 4 (11.4%) zerosZeros
비과세감면율 has 5 (14.3%) zerosZeros

Reproduction

Analysis started2023-12-12 16:04:17.521266
Analysis finished2023-12-12 16:04:19.685393
Duration2.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
경기도
35 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 35
100.0%

Length

2023-12-13T01:04:19.748155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:04:19.837004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 35
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
구리시
35 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구리시 35
100.0%

Length

2023-12-13T01:04:19.939425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:04:20.036051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구리시 35
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
41310
35 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41310
2nd row41310
3rd row41310
4th row41310
5th row41310

Common Values

ValueCountFrequency (%)
41310 35
100.0%

Length

2023-12-13T01:04:20.142046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:04:20.243385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41310 35
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
재산세
5 
주민세
5 
취득세
5 
자동차세
5 
등록면허세
5 
Other values (3)
10 

Length

Max length7
Median length3
Mean length4
Min length3

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row등록세
2nd row재산세
3rd row주민세
4th row취득세
5th row자동차세

Common Values

ValueCountFrequency (%)
재산세 5
14.3%
주민세 5
14.3%
취득세 5
14.3%
자동차세 5
14.3%
등록면허세 5
14.3%
지역자원시설세 5
14.3%
등록세 4
11.4%
교육세 1
 
2.9%

Length

2023-12-13T01:04:20.356751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:04:20.531427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 5
14.3%
주민세 5
14.3%
취득세 5
14.3%
자동차세 5
14.3%
등록면허세 5
14.3%
지역자원시설세 5
14.3%
등록세 4
11.4%
교육세 1
 
2.9%

과세년도
Categorical

Distinct5
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2017
7 
2018
7 
2019
7 
2020
7 
2021
7 

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 7
20.0%
2018 7
20.0%
2019 7
20.0%
2020 7
20.0%
2021 7
20.0%

Length

2023-12-13T01:04:20.688152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:04:20.817983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 7
20.0%
2018 7
20.0%
2019 7
20.0%
2020 7
20.0%
2021 7
20.0%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct31
Distinct (%)100.0%
Missing4
Missing (%)11.4%
Infinite0
Infinite (%)0.0%
Mean3.7031284 × 109
Minimum0
Maximum2.0992815 × 1010
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:04:20.972852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3354000
Q132245000
median2.1515 × 108
Q33.679233 × 109
95-th percentile1.8133026 × 1010
Maximum2.0992815 × 1010
Range2.0992815 × 1010
Interquartile range (IQR)3.646988 × 109

Descriptive statistics

Standard deviation6.6809595 × 109
Coefficient of variation (CV)1.8041393
Kurtosis1.4595568
Mean3.7031284 × 109
Median Absolute Deviation (MAD)1.96278 × 108
Skewness1.7251557
Sum1.1479698 × 1011
Variance4.463522 × 1019
MonotonicityNot monotonic
2023-12-13T01:04:21.111812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
31490000 1
 
2.9%
244196000 1
 
2.9%
7763000 1
 
2.9%
175341000 1
 
2.9%
7972161000 1
 
2.9%
3750000 1
 
2.9%
20992815000 1
 
2.9%
239535000 1
 
2.9%
2958000 1
 
2.9%
172902000 1
 
2.9%
Other values (21) 21
60.0%
(Missing) 4
 
11.4%
ValueCountFrequency (%)
0 1
2.9%
2958000 1
2.9%
3750000 1
2.9%
3950000 1
2.9%
7763000 1
2.9%
18872000 1
2.9%
22735000 1
2.9%
31490000 1
2.9%
33000000 1
2.9%
37922000 1
2.9%
ValueCountFrequency (%)
20992815000 1
2.9%
19119441000 1
2.9%
17146610000 1
2.9%
16519577000 1
2.9%
16242233000 1
2.9%
7972161000 1
2.9%
5277629000 1
2.9%
5238296000 1
2.9%
2120170000 1
2.9%
1842242000 1
2.9%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4358272 × 109
Minimum1000
Maximum1.4065966 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:04:21.248027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1808300
Q121110500
median2.21533 × 108
Q33.4404945 × 109
95-th percentile1.3149779 × 1010
Maximum1.4065966 × 1010
Range1.4065965 × 1010
Interquartile range (IQR)3.419384 × 109

Descriptive statistics

Standard deviation4.2666408 × 109
Coefficient of variation (CV)1.7516188
Kurtosis2.3118281
Mean2.4358272 × 109
Median Absolute Deviation (MAD)2.20732 × 108
Skewness1.8739841
Sum8.5253951 × 1010
Variance1.8204223 × 1019
MonotonicityNot monotonic
2023-12-13T01:04:21.400603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
14382000 1
 
2.9%
3313793000 1
 
2.9%
108764000 1
 
2.9%
1000 1
 
2.9%
4670219000 1
 
2.9%
19234000 1
 
2.9%
14065966000 1
 
2.9%
583987000 1
 
2.9%
76055000 1
 
2.9%
115897000 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
1000 1
2.9%
801000 1
2.9%
2240000 1
2.9%
9140000 1
2.9%
14382000 1
2.9%
16233000 1
2.9%
18010000 1
2.9%
19234000 1
2.9%
19317000 1
2.9%
22904000 1
2.9%
ValueCountFrequency (%)
14065966000 1
2.9%
13245520000 1
2.9%
13108747000 1
2.9%
11363437000 1
2.9%
7738204000 1
2.9%
5404042000 1
2.9%
4670219000 1
2.9%
3961886000 1
2.9%
3567196000 1
2.9%
3313793000 1
2.9%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5631515 × 1010
Minimum0
Maximum1.1812 × 1011
Zeros4
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:04:21.530992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.58216 × 109
median6.015612 × 109
Q33.6960142 × 1010
95-th percentile9.7169857 × 1010
Maximum1.1812 × 1011
Range1.1812 × 1011
Interquartile range (IQR)3.3377982 × 1010

Descriptive statistics

Standard deviation3.2829543 × 1010
Coefficient of variation (CV)1.2808272
Kurtosis2.0184251
Mean2.5631515 × 1010
Median Absolute Deviation (MAD)6.015612 × 109
Skewness1.637705
Sum8.9710304 × 1011
Variance1.0777789 × 1021
MonotonicityNot monotonic
2023-12-13T01:04:21.702020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 4
 
11.4%
6281042000 1
 
2.9%
4019065000 1
 
2.9%
5739792000 1
 
2.9%
25346930000 1
 
2.9%
118120000000 1
 
2.9%
3634470000 1
 
2.9%
46834674000 1
 
2.9%
3999717000 1
 
2.9%
5830584000 1
 
2.9%
Other values (22) 22
62.9%
ValueCountFrequency (%)
0 4
11.4%
3009987000 1
 
2.9%
3115917000 1
 
2.9%
3234779000 1
 
2.9%
3439046000 1
 
2.9%
3529850000 1
 
2.9%
3634470000 1
 
2.9%
3686239000 1
 
2.9%
3870362000 1
 
2.9%
3999717000 1
 
2.9%
ValueCountFrequency (%)
118120000000 1
2.9%
116480000000 1
2.9%
88894081000 1
2.9%
79469290000 1
2.9%
71707889000 1
2.9%
46834674000 1
2.9%
44296294000 1
2.9%
41725172000 1
2.9%
38570798000 1
2.9%
35349486000 1
2.9%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.82
Minimum0
Maximum56.36
Zeros5
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:04:21.812544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.585
median4.38
Q315.605
95-th percentile54.43
Maximum56.36
Range56.36
Interquartile range (IQR)14.02

Descriptive statistics

Standard deviation17.890134
Coefficient of variation (CV)1.3954862
Kurtosis1.6682584
Mean12.82
Median Absolute Deviation (MAD)4.38
Skewness1.7260436
Sum448.7
Variance320.05688
MonotonicityNot monotonic
2023-12-13T01:04:21.928804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.0 5
 
14.3%
56.11 1
 
2.9%
8.92 1
 
2.9%
2.63 1
 
2.9%
2.88 1
 
2.9%
17.96 1
 
2.9%
0.73 1
 
2.9%
56.36 1
 
2.9%
8.89 1
 
2.9%
1.36 1
 
2.9%
Other values (21) 21
60.0%
ValueCountFrequency (%)
0.0 5
14.3%
0.66 1
 
2.9%
0.73 1
 
2.9%
1.36 1
 
2.9%
1.58 1
 
2.9%
1.59 1
 
2.9%
1.79 1
 
2.9%
2.62 1
 
2.9%
2.63 1
 
2.9%
2.88 1
 
2.9%
ValueCountFrequency (%)
56.36 1
2.9%
56.11 1
2.9%
53.71 1
2.9%
51.36 1
2.9%
50.59 1
2.9%
18.81 1
2.9%
18.8 1
2.9%
17.96 1
2.9%
16.61 1
2.9%
14.6 1
2.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-06-21
35 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-21
2nd row2023-06-21
3rd row2023-06-21
4th row2023-06-21
5th row2023-06-21

Common Values

ValueCountFrequency (%)
2023-06-21 35
100.0%

Length

2023-12-13T01:04:22.066155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:04:22.167171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-21 35
100.0%

Interactions

2023-12-13T01:04:19.130909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:17.798118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:18.162153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:18.762887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:19.211252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:17.882533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:18.519287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:18.845470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:19.298379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:17.976095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:18.594442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:18.936294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:19.388660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:18.090746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:18.674149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:04:19.050245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:04:22.232427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.7540.7080.7890.796
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.7540.0001.0000.9320.9100.860
감면금액0.7080.0000.9321.0000.8760.920
부과금액0.7890.0000.9100.8761.0000.727
비과세감면율0.7960.0000.8600.9200.7271.000
2023-12-13T01:04:22.347506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도
세목명1.0000.000
과세년도0.0001.000
2023-12-13T01:04:22.430981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율세목명과세년도
비과세금액1.0000.7650.6340.9250.3430.000
감면금액0.7651.0000.9020.8470.4770.000
부과금액0.6340.9021.0000.7230.5630.000
비과세감면율0.9250.8470.7231.0000.5790.000
세목명0.3430.4770.5630.5791.0000.000
과세년도0.0000.0000.0000.0000.0001.000

Missing values

2023-12-13T01:04:19.499841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:04:19.632590image/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

시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율데이터기준일자
0경기도구리시41310등록세2017<NA>1438200000.02023-06-21
1경기도구리시41310재산세20171651957700033137930003534948600056.112023-06-21
2경기도구리시41310주민세2017314900001623300030099870001.592023-06-21
3경기도구리시41310취득세2017523829600077382040008889408100014.62023-06-21
4경기도구리시41310자동차세2017216306000533583000225235500003.332023-06-21
5경기도구리시41310등록면허세20172273500026121700060156120004.722023-06-21
6경기도구리시41310지역자원시설세2017215150000187886000311591700012.932023-06-21
7경기도구리시41310등록세2018<NA>224000000.02023-06-21
8경기도구리시41310재산세20181624223300035671960003857079800051.362023-06-21
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시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율데이터기준일자
25경기도구리시41310자동차세2020172902000583987000288760030002.622023-06-21
26경기도구리시41310등록면허세202029580007605500058305840001.362023-06-21
27경기도구리시41310지역자원시설세202023953500011589700039997170008.892023-06-21
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30경기도구리시41310주민세202137500002290400036344700000.732023-06-21
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32경기도구리시41310자동차세2021175341000554148000253469300002.882023-06-21
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