Overview

Dataset statistics

Number of variables9
Number of observations42
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory81.1 B

Variable types

Categorical4
Numeric5

Dataset

Description과세액 중 비과세액과 감면액이 차지하는 비율 현황을 제공함으로써 국민 조세 혜택의 규모를 파악하는데 사용하고자 합니다.
Author부산광역시 해운대구
URLhttps://www.data.go.kr/data/15078931/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 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 1 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 비과세감면율High correlation
비과세금액 has 1 (2.4%) missing valuesMissing
감면금액 has unique valuesUnique
비과세금액 has 5 (11.9%) zerosZeros
부과금액 has 3 (7.1%) zerosZeros
비과세감면율 has 5 (11.9%) zerosZeros

Reproduction

Analysis started2024-04-21 01:49:47.662061
Analysis finished2024-04-21 01:49:51.917789
Duration4.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
부산광역시
42 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 42
100.0%

Length

2024-04-21T10:49:51.975977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:49:52.073493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 42
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
해운대구
42 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
해운대구 42
100.0%

Length

2024-04-21T10:49:52.163137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:49:52.248653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해운대구 42
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
26350
42 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26350
2nd row26350
3rd row26350
4th row26350
5th row26350

Common Values

ValueCountFrequency (%)
26350 42
100.0%

Length

2024-04-21T10:49:52.341268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:49:52.440723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26350 42
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
재산세
6 
주민세
6 
취득세
6 
자동차세
6 
등록면허세
6 
Other values (3)
12 

Length

Max length7
Median length3
Mean length4
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 6
14.3%
주민세 6
14.3%
취득세 6
14.3%
자동차세 6
14.3%
등록면허세 6
14.3%
지역자원시설세 6
14.3%
등록세 4
9.5%
교육세 2
 
4.8%

Length

2024-04-21T10:49:52.564957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:49:52.729910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 6
14.3%
주민세 6
14.3%
취득세 6
14.3%
자동차세 6
14.3%
등록면허세 6
14.3%
지역자원시설세 6
14.3%
등록세 4
9.5%
교육세 2
 
4.8%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.619
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-04-21T10:49:52.847774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2020
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7243221
Coefficient of variation (CV)0.00085378584
Kurtosis-1.2711404
Mean2019.619
Median Absolute Deviation (MAD)1.5
Skewness-0.061731685
Sum84824
Variance2.9732869
MonotonicityIncreasing
2024-04-21T10:49:52.947415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2022 8
19.0%
2018 7
16.7%
2019 7
16.7%
2020 7
16.7%
2021 7
16.7%
2017 6
14.3%
ValueCountFrequency (%)
2017 6
14.3%
2018 7
16.7%
2019 7
16.7%
2020 7
16.7%
2021 7
16.7%
2022 8
19.0%
ValueCountFrequency (%)
2022 8
19.0%
2021 7
16.7%
2020 7
16.7%
2019 7
16.7%
2018 7
16.7%
2017 6
14.3%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct37
Distinct (%)90.2%
Missing1
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean7.2538268 × 109
Minimum0
Maximum5.4804611 × 1010
Zeros5
Zeros (%)11.9%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-04-21T10:49:53.054921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.70434 × 108
median5.94046 × 108
Q33.5824722 × 109
95-th percentile4.3530476 × 1010
Maximum5.4804611 × 1010
Range5.4804611 × 1010
Interquartile range (IQR)3.4120382 × 109

Descriptive statistics

Standard deviation1.5009668 × 1010
Coefficient of variation (CV)2.0692068
Kurtosis3.4827373
Mean7.2538268 × 109
Median Absolute Deviation (MAD)4.83322 × 108
Skewness2.1961594
Sum2.974069 × 1011
Variance2.2529013 × 1020
MonotonicityNot monotonic
2024-04-21T10:49:53.172688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 5
 
11.9%
30820057000 1
 
2.4%
170434000 1
 
2.4%
231980670 1
 
2.4%
127275500 1
 
2.4%
860360 1
 
2.4%
48673632000 1
 
2.4%
564901000 1
 
2.4%
4775493000 1
 
2.4%
509398000 1
 
2.4%
Other values (27) 27
64.3%
ValueCountFrequency (%)
0 5
11.9%
860360 1
 
2.4%
89895000 1
 
2.4%
97607000 1
 
2.4%
110724000 1
 
2.4%
127275500 1
 
2.4%
170434000 1
 
2.4%
180181000 1
 
2.4%
228082000 1
 
2.4%
231980670 1
 
2.4%
ValueCountFrequency (%)
54804611000 1
2.4%
48673632000 1
2.4%
43530476240 1
2.4%
38946532000 1
2.4%
34781002000 1
2.4%
30820057000 1
2.4%
7739106000 1
2.4%
7564455000 1
2.4%
7324096000 1
2.4%
4775493000 1
2.4%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7073131 × 109
Minimum1000
Maximum2.527997 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-04-21T10:49:53.440822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile234600
Q12.1936175 × 108
median5.03589 × 108
Q35.3281512 × 109
95-th percentile1.5916743 × 1010
Maximum2.527997 × 1010
Range2.5279969 × 1010
Interquartile range (IQR)5.1087895 × 109

Descriptive statistics

Standard deviation6.0881034 × 109
Coefficient of variation (CV)1.6421875
Kurtosis3.7156292
Mean3.7073131 × 109
Median Absolute Deviation (MAD)5.034815 × 108
Skewness2.0682738
Sum1.5570715 × 1011
Variance3.7065003 × 1019
MonotonicityNot monotonic
2024-04-21T10:49:53.591351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
4843943000 1
 
2.4%
229960000 1
 
2.4%
1694908080 1
 
2.4%
173753050 1
 
2.4%
894440 1
 
2.4%
683000 1
 
2.4%
5507831000 1
 
2.4%
425248000 1
 
2.4%
14919974000 1
 
2.4%
1607356000 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
1000 1
2.4%
4000 1
2.4%
211000 1
2.4%
683000 1
2.4%
894440 1
2.4%
14273000 1
2.4%
162293000 1
2.4%
173753050 1
2.4%
200366000 1
2.4%
214049000 1
2.4%
ValueCountFrequency (%)
25279970000 1
2.4%
19024187000 1
2.4%
15968644000 1
2.4%
14930617000 1
2.4%
14919974000 1
2.4%
13336779890 1
2.4%
6320010000 1
2.4%
5740960000 1
2.4%
5699090780 1
2.4%
5507831000 1
2.4%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1305635 × 1010
Minimum0
Maximum4.46342 × 1011
Zeros3
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-04-21T10:49:53.745234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3504966
Q11.190417 × 1010
median2.5528242 × 1010
Q39.2451022 × 1010
95-th percentile1.8586426 × 1011
Maximum4.46342 × 1011
Range4.46342 × 1011
Interquartile range (IQR)8.0546852 × 1010

Descriptive statistics

Standard deviation8.6429437 × 1010
Coefficient of variation (CV)1.4098123
Kurtosis9.1357704
Mean6.1305635 × 1010
Median Absolute Deviation (MAD)1.5509535 × 1010
Skewness2.6953507
Sum2.5748367 × 1012
Variance7.4700475 × 1021
MonotonicityNot monotonic
2024-04-21T10:49:53.888713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 3
 
7.1%
85642850000 1
 
2.4%
18297083000 1
 
2.4%
446342000000 1
 
2.4%
43899714980 1
 
2.4%
28039494740 1
 
2.4%
70099320 1
 
2.4%
130688000000 1
 
2.4%
10672476000 1
 
2.4%
267823000000 1
 
2.4%
Other values (30) 30
71.4%
ValueCountFrequency (%)
0 3
7.1%
70099320 1
 
2.4%
3760258990 1
 
2.4%
8975520000 1
 
2.4%
9573594000 1
 
2.4%
10463821000 1
 
2.4%
10672476000 1
 
2.4%
11137129760 1
 
2.4%
11464385000 1
 
2.4%
13223527000 1
 
2.4%
ValueCountFrequency (%)
446342000000 1
2.4%
267823000000 1
2.4%
187763547000 1
2.4%
149777842000 1
2.4%
149490000000 1
2.4%
144652000000 1
2.4%
130688000000 1
2.4%
128547000000 1
2.4%
126878000000 1
2.4%
102612000000 1
2.4%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.330714
Minimum0
Maximum82.22
Zeros5
Zeros (%)11.9%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-04-21T10:49:54.011203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.8225
median6.375
Q315.2875
95-th percentile42.476
Maximum82.22
Range82.22
Interquartile range (IQR)12.465

Descriptive statistics

Standard deviation17.035421
Coefficient of variation (CV)1.2779076
Kurtosis5.6142915
Mean13.330714
Median Absolute Deviation (MAD)4.74
Skewness2.207435
Sum559.89
Variance290.20555
MonotonicityNot monotonic
2024-04-21T10:49:54.122442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0.0 5
 
11.9%
6.46 2
 
4.8%
41.64 1
 
2.4%
7.35 1
 
2.4%
3.79 1
 
2.4%
4.39 1
 
2.4%
1.07 1
 
2.4%
2.5 1
 
2.4%
41.46 1
 
2.4%
9.28 1
 
2.4%
Other values (27) 27
64.3%
ValueCountFrequency (%)
0.0 5
11.9%
1.07 1
 
2.4%
1.29 1
 
2.4%
1.98 1
 
2.4%
2.19 1
 
2.4%
2.3 1
 
2.4%
2.5 1
 
2.4%
3.79 1
 
2.4%
4.39 1
 
2.4%
4.54 1
 
2.4%
ValueCountFrequency (%)
82.22 1
2.4%
43.55 1
2.4%
42.52 1
2.4%
41.64 1
2.4%
41.46 1
2.4%
40.81 1
2.4%
32.93 1
2.4%
22.23 1
2.4%
18.55 1
2.4%
15.93 1
2.4%

Interactions

2024-04-21T10:49:51.240035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:49.327034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:49.971259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:50.391471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:50.820729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:51.337855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:49.471364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:50.055444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:50.466832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:50.916638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:51.450495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:49.721964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:50.132965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:50.549619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:50.994537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:51.542440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:49.809994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:50.207386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:50.637821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:51.078501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:51.625434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:49.891070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:50.298054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:50.724142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:49:51.154243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:49:54.201766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.4960.6760.5380.793
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.4960.0001.0000.8860.8530.709
감면금액0.6760.0000.8861.0000.9460.816
부과금액0.5380.0000.8530.9461.0000.685
비과세감면율0.7930.0000.7090.8160.6851.000
2024-04-21T10:49:54.302829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도비과세금액감면금액부과금액비과세감면율세목명
과세년도1.000-0.052-0.0710.064-0.1850.000
비과세금액-0.0521.0000.7590.6030.7680.281
감면금액-0.0710.7591.0000.6940.7890.440
부과금액0.0640.6030.6941.0000.3510.313
비과세감면율-0.1850.7680.7890.3511.0000.581
세목명0.0000.2810.4400.3130.5811.000

Missing values

2024-04-21T10:49:51.736386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:49:51.867845image/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

시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
0부산광역시해운대구26350재산세20173082005700048439430008564285000041.64
1부산광역시해운대구26350주민세2017908237000521310000897552000015.93
2부산광역시해운대구26350취득세201773240960001493061700014465200000015.39
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