Overview

Dataset statistics

Number of variables9
Number of observations21
Missing cells2
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory84.3 B

Variable types

Categorical5
Numeric4

Dataset

Description지방세 금액 중 비과세·감면액이 차지하는 비율에 대하여 과세연도, 세목명, 비과세금액, 감면금액, 부과금액, 비과세감면율 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15079779/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
비과세금액 is highly overall correlated with 감면금액High correlation
감면금액 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 감면금액High correlation
비과세감면율 is highly overall correlated with 감면금액 and 1 other fieldsHigh correlation
세목명 is highly overall correlated with 비과세감면율High correlation
비과세금액 has 2 (9.5%) missing valuesMissing
감면금액 has unique valuesUnique
부과금액 has unique valuesUnique
비과세금액 has 2 (9.5%) zerosZeros
비과세감면율 has 3 (14.3%) zerosZeros

Reproduction

Analysis started2023-12-12 23:36:00.175859
Analysis finished2023-12-12 23:36:02.269337
Duration2.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
경상북도
21 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 21
100.0%

Length

2023-12-13T08:36:02.323515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:36:02.404129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 21
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
청도군
21 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청도군 21
100.0%

Length

2023-12-13T08:36:02.489756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:36:02.569988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청도군 21
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
47820
21 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47820
2nd row47820
3rd row47820
4th row47820
5th row47820

Common Values

ValueCountFrequency (%)
47820 21
100.0%

Length

2023-12-13T08:36:02.651089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:36:02.732109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47820 21
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
취득세
3 
등록면허세
3 
주민세
3 
재산세
3 
자동차세
3 
Other values (2)
6 

Length

Max length7
Median length5
Mean length4.2857143
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 3
14.3%
등록면허세 3
14.3%
주민세 3
14.3%
재산세 3
14.3%
자동차세 3
14.3%
지역자원시설세 3
14.3%
지방교육세 3
14.3%

Length

2023-12-13T08:36:02.826469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:36:02.932159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취득세 3
14.3%
등록면허세 3
14.3%
주민세 3
14.3%
재산세 3
14.3%
자동차세 3
14.3%
지역자원시설세 3
14.3%
지방교육세 3
14.3%

과세년도
Categorical

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
2020
7 
2021
7 
2022
7 

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 7
33.3%
2021 7
33.3%
2022 7
33.3%

Length

2023-12-13T08:36:03.042834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:36:03.129431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 7
33.3%
2021 7
33.3%
2022 7
33.3%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct18
Distinct (%)94.7%
Missing2
Missing (%)9.5%
Infinite0
Infinite (%)0.0%
Mean5.8503075 × 108
Minimum0
Maximum2.7530125 × 109
Zeros2
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T08:36:03.220424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13987500
median72581590
Q39.8452774 × 108
95-th percentile2.649934 × 109
Maximum2.7530125 × 109
Range2.7530125 × 109
Interquartile range (IQR)9.8054024 × 108

Descriptive statistics

Standard deviation9.2598293 × 108
Coefficient of variation (CV)1.5827936
Kurtosis1.0487522
Mean5.8503075 × 108
Median Absolute Deviation (MAD)69126570
Skewness1.5123357
Sum1.1115584 × 1010
Variance8.5744438 × 1017
MonotonicityNot monotonic
2023-12-13T08:36:03.334098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 2
 
9.5%
68043140 1
 
4.8%
101814460 1
 
4.8%
72581590 1
 
4.8%
2753012460 1
 
4.8%
200000 1
 
4.8%
3475000 1
 
4.8%
706913080 1
 
4.8%
97378610 1
 
4.8%
1470918050 1
 
4.8%
Other values (8) 8
38.1%
(Missing) 2
 
9.5%
ValueCountFrequency (%)
0 2
9.5%
200000 1
4.8%
3455020 1
4.8%
3475000 1
4.8%
4500000 1
4.8%
7286000 1
4.8%
68043140 1
4.8%
69426070 1
4.8%
72581590 1
4.8%
96409190 1
4.8%
ValueCountFrequency (%)
2753012460 1
4.8%
2638480820 1
4.8%
1759548420 1
4.8%
1470918050 1
4.8%
1262142410 1
4.8%
706913080 1
4.8%
101814460 1
4.8%
97378610 1
4.8%
96409190 1
4.8%
72581590 1
4.8%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0988832 × 108
Minimum3410
Maximum3.4140573 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T08:36:03.733352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410
5-th percentile5770
Q140659840
median1.5868953 × 108
Q35.0976504 × 108
95-th percentile1.7635842 × 109
Maximum3.4140573 × 109
Range3.4140538 × 109
Interquartile range (IQR)4.691052 × 108

Descriptive statistics

Standard deviation8.3575116 × 108
Coefficient of variation (CV)1.6390867
Kurtosis7.0346544
Mean5.0988832 × 108
Median Absolute Deviation (MAD)1.5868254 × 108
Skewness2.5672001
Sum1.0707655 × 1010
Variance6.9848001 × 1017
MonotonicityNot monotonic
2023-12-13T08:36:03.887037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1763584150 1
 
4.8%
158689530 1
 
4.8%
5770 1
 
4.8%
40659840 1
 
4.8%
155521810 1
 
4.8%
517839330 1
 
4.8%
2920580 1
 
4.8%
85396410 1
 
4.8%
1705172720 1
 
4.8%
6990 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
3410 1
4.8%
5770 1
4.8%
6990 1
4.8%
2920580 1
4.8%
39574860 1
4.8%
40659840 1
4.8%
85396410 1
4.8%
94896790 1
4.8%
145558970 1
4.8%
155521810 1
4.8%
ValueCountFrequency (%)
3414057260 1
4.8%
1763584150 1
4.8%
1705172720 1
4.8%
828743910 1
4.8%
517839330 1
4.8%
509765040 1
4.8%
474666880 1
4.8%
392256780 1
4.8%
192233000 1
4.8%
186100620 1
4.8%

부과금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1233134 × 109
Minimum2.0604289 × 108
Maximum1.6576671 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T08:36:04.030936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0604289 × 108
5-th percentile2.7775419 × 108
Q17.5495624 × 108
median5.4942182 × 109
Q36.6523573 × 109
95-th percentile1.41596 × 1010
Maximum1.6576671 × 1010
Range1.6370628 × 1010
Interquartile range (IQR)5.8974011 × 109

Descriptive statistics

Standard deviation4.9331361 × 109
Coefficient of variation (CV)0.96288003
Kurtosis0.25016777
Mean5.1233134 × 109
Median Absolute Deviation (MAD)4.2659034 × 109
Skewness0.98869517
Sum1.0758958 × 1011
Variance2.4335832 × 1019
MonotonicityNot monotonic
2023-12-13T08:36:04.138455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
13661916350 1
 
4.8%
1286629460 1
 
4.8%
5763695170 1
 
4.8%
573904820 1
 
4.8%
6652357320 1
 
4.8%
6018690940 1
 
4.8%
754956240 1
 
4.8%
1122241580 1
 
4.8%
14159600260 1
 
4.8%
5494218180 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
206042890 1
4.8%
277754190 1
4.8%
461215150 1
4.8%
558094050 1
4.8%
573904820 1
4.8%
754956240 1
4.8%
1122241580 1
4.8%
1228314730 1
4.8%
1286629460 1
4.8%
4611900800 1
4.8%
ValueCountFrequency (%)
16576670970 1
4.8%
14159600260 1
4.8%
13661916350 1
4.8%
8777923560 1
4.8%
7698147490 1
4.8%
6652357320 1
4.8%
6028079130 1
4.8%
6018690940 1
4.8%
5763695170 1
4.8%
5677227150 1
4.8%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.24
Minimum0
Maximum192.56
Zeros3
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T08:36:04.273748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.38
median17.03
Q341.48
95-th percentile170.89
Maximum192.56
Range192.56
Interquartile range (IQR)38.1

Descriptive statistics

Standard deviation52.215018
Coefficient of variation (CV)1.5249713
Kurtosis5.455912
Mean34.24
Median Absolute Deviation (MAD)14.12
Skewness2.4235849
Sum719.04
Variance2726.4081
MonotonicityNot monotonic
2023-12-13T08:36:04.386901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 3
 
14.3%
23.68 1
 
4.8%
3.38 1
 
4.8%
24.83 1
 
4.8%
3.43 1
 
4.8%
54.34 1
 
4.8%
0.41 1
 
4.8%
7.92 1
 
4.8%
17.03 1
 
4.8%
24.54 1
 
4.8%
Other values (9) 9
42.9%
ValueCountFrequency (%)
0.0 3
14.3%
0.41 1
 
4.8%
2.91 1
 
4.8%
3.38 1
 
4.8%
3.43 1
 
4.8%
7.92 1
 
4.8%
12.44 1
 
4.8%
12.6 1
 
4.8%
17.03 1
 
4.8%
23.68 1
 
4.8%
ValueCountFrequency (%)
192.56 1
4.8%
170.89 1
4.8%
55.45 1
4.8%
54.34 1
4.8%
42.94 1
4.8%
41.48 1
4.8%
28.21 1
4.8%
24.83 1
4.8%
24.54 1
4.8%
23.68 1
4.8%

Interactions

2023-12-13T08:36:01.618564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:00.450488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:00.798264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:01.219184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:01.706516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:00.535837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:00.887495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:01.322284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:01.814163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:00.619016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:00.992056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:01.453265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:01.922759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:00.706766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:01.092563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:36:01.536172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:36:04.473912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.5300.5370.8680.711
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.5300.0001.0000.9970.7360.274
감면금액0.5370.0000.9971.0000.8690.486
부과금액0.8680.0000.7360.8691.0000.000
비과세감면율0.7110.0000.2740.4860.0001.000
2023-12-13T08:36:04.578440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도
세목명1.0000.000
과세년도0.0001.000
2023-12-13T08:36:04.674776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율세목명과세년도
비과세금액1.0000.5990.4830.4500.3040.000
감면금액0.5991.0000.5040.6410.3460.000
부과금액0.4830.5041.000-0.2570.4820.000
비과세감면율0.4500.641-0.2571.0000.5140.000
세목명0.3040.3460.4820.5141.0000.000
과세년도0.0000.0000.0000.0000.0001.000

Missing values

2023-12-13T08:36:02.084967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:36:02.222564image/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
0경상북도청도군47820취득세2020147091805017635841501366191635023.68
1경상북도청도군47820등록면허세20203455020158689530128662946012.6
2경상북도청도군47820주민세20204500000392256780206042890192.56
3경상북도청도군47820재산세20201759548420828743910602807913042.94
4경상북도청도군47820자동차세20206942607018610062087779235602.91
5경상북도청도군47820지역자원시설세2020964091909489679046121515041.48
6경상북도청도군47820지방교육세20200341046119008000.0
7경상북도청도군47820취득세2021126214241034140572601657667097028.21
8경상북도청도군47820등록면허세20217286000145558970122831473012.44
9경상북도청도군47820주민세20210474666880277754190170.89
시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
11경상북도청도군47820자동차세20216804314019223300076981474903.38
12경상북도청도군47820지역자원시설세2021973786103957486055809405024.54
13경상북도청도군47820지방교육세2021<NA>699054942181800.0
14경상북도청도군47820취득세202270691308017051727201415960026017.03
15경상북도청도군47820등록면허세202234750008539641011222415807.92
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