Overview

Dataset statistics

Number of variables9
Number of observations34
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory81.9 B

Variable types

Categorical5
Numeric4

Dataset

Description지방세 각 세목에 해당하는 비과세 금액과 부과금액을 확인할 수 있으며, 이에 따른 비과세감면율의 현황도 비교할 수 있습니다.
URLhttps://www.data.go.kr/data/15078553/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 3 other fieldsHigh correlation
감면금액 is highly overall correlated with 비과세금액 and 3 other fieldsHigh correlation
부과금액 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 비과세금액 and 3 other fieldsHigh correlation
세목명 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
비과세금액 has 1 (2.9%) missing valuesMissing
부과금액 has unique valuesUnique
비과세감면율 has unique valuesUnique
비과세금액 has 3 (8.8%) zerosZeros
감면금액 has 2 (5.9%) zerosZeros
부과금액 has 1 (2.9%) zerosZeros
비과세감면율 has 1 (2.9%) zerosZeros

Reproduction

Analysis started2023-12-12 06:06:50.473568
Analysis finished2023-12-12 06:06:52.361413
Duration1.89 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
대전광역시
34 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전광역시 34
100.0%

Length

2023-12-12T15:06:52.433132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:52.591659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 34
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
중구
34 

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 34
100.0%

Length

2023-12-12T15:06:52.697783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:52.798963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 34
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
30140
34 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30140
2nd row30140
3rd row30140
4th row30140
5th row30140

Common Values

ValueCountFrequency (%)
30140 34
100.0%

Length

2023-12-12T15:06:52.950997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:53.083020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30140 34
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size404.0 B
재산세
5 
주민세
5 
취득세
5 
자동차세
5 
등록면허세
5 
Other values (2)
9 

Length

Max length7
Median length3
Mean length4.0294118
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 5
14.7%
주민세 5
14.7%
취득세 5
14.7%
자동차세 5
14.7%
등록면허세 5
14.7%
지역자원시설세 5
14.7%
등록세 4
11.8%

Length

2023-12-12T15:06:53.248312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:53.420248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 5
14.7%
주민세 5
14.7%
취득세 5
14.7%
자동차세 5
14.7%
등록면허세 5
14.7%
지역자원시설세 5
14.7%
등록세 4
11.8%

과세연도
Categorical

Distinct5
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size404.0 B
2017
7 
2018
7 
2020
7 
2021
7 
2019
6 

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
20.6%
2018 7
20.6%
2020 7
20.6%
2021 7
20.6%
2019 6
17.6%

Length

2023-12-12T15:06:53.917615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:54.045127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 7
20.6%
2018 7
20.6%
2020 7
20.6%
2021 7
20.6%
2019 6
17.6%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct31
Distinct (%)93.9%
Missing1
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean3.220476 × 109
Minimum0
Maximum1.9566448 × 1010
Zeros3
Zeros (%)8.8%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:06:54.192473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110984820
median3.5422991 × 108
Q31.8664642 × 109
95-th percentile1.7697359 × 1010
Maximum1.9566448 × 1010
Range1.9566448 × 1010
Interquartile range (IQR)1.8554794 × 109

Descriptive statistics

Standard deviation6.2057059 × 109
Coefficient of variation (CV)1.926953
Kurtosis2.3077576
Mean3.220476 × 109
Median Absolute Deviation (MAD)3.5422991 × 108
Skewness1.9966156
Sum1.0627571 × 1011
Variance3.8510786 × 1019
MonotonicityNot monotonic
2023-12-12T15:06:54.350361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 3
 
8.8%
15782841280 1
 
2.9%
367295000 1
 
2.9%
14682000 1
 
2.9%
352144000 1
 
2.9%
3336045000 1
 
2.9%
1069192000 1
 
2.9%
19566448000 1
 
2.9%
1197740 1
 
2.9%
12751130 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
0 3
8.8%
36820 1
 
2.9%
822580 1
 
2.9%
1197740 1
 
2.9%
1379480 1
 
2.9%
10855500 1
 
2.9%
10984820 1
 
2.9%
12600760 1
 
2.9%
12751130 1
 
2.9%
14682000 1
 
2.9%
ValueCountFrequency (%)
19566448000 1
2.9%
18233981350 1
2.9%
17339611080 1
2.9%
16601824840 1
2.9%
15782841280 1
2.9%
3336045000 1
2.9%
2570136930 1
2.9%
2030510870 1
2.9%
1866464210 1
2.9%
1352462790 1
2.9%

감면금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4110104 × 109
Minimum0
Maximum5.5386954 × 109
Zeros2
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:06:54.519652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4992
Q144435672
median5.7357006 × 108
Q33.386237 × 109
95-th percentile4.5136475 × 109
Maximum5.5386954 × 109
Range5.5386954 × 109
Interquartile range (IQR)3.3418013 × 109

Descriptive statistics

Standard deviation1.7989729 × 109
Coefficient of variation (CV)1.2749537
Kurtosis-0.4132881
Mean1.4110104 × 109
Median Absolute Deviation (MAD)5.7267258 × 108
Skewness1.0523017
Sum4.7974353 × 1010
Variance3.2363035 × 1018
MonotonicityNot monotonic
2023-12-12T15:06:54.654560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 2
 
5.9%
808980 1
 
2.9%
986000 1
 
2.9%
3637062420 1
 
2.9%
495372400 1
 
2.9%
5538695390 1
 
2.9%
869793300 1
 
2.9%
58813690 1
 
2.9%
9180 1
 
2.9%
3760853000 1
 
2.9%
Other values (23) 23
67.6%
ValueCountFrequency (%)
0 2
5.9%
7680 1
2.9%
9180 1
2.9%
31240 1
2.9%
350430 1
2.9%
808980 1
2.9%
986000 1
2.9%
39643000 1
2.9%
58813690 1
2.9%
61533390 1
2.9%
ValueCountFrequency (%)
5538695390 1
2.9%
5423632000 1
2.9%
4023655860 1
2.9%
3895106130 1
2.9%
3876640310 1
2.9%
3760853000 1
2.9%
3637062420 1
2.9%
3496941070 1
2.9%
3391808560 1
2.9%
3369522180 1
2.9%

부과금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8615129 × 1010
Minimum0
Maximum7.7150644 × 1010
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:06:54.809468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17702976
Q14.3458565 × 109
median7.2359199 × 109
Q33.5663758 × 1010
95-th percentile5.2304744 × 1010
Maximum7.7150644 × 1010
Range7.7150644 × 1010
Interquartile range (IQR)3.1317901 × 1010

Descriptive statistics

Standard deviation2.0125716 × 1010
Coefficient of variation (CV)1.0811484
Kurtosis0.73650865
Mean1.8615129 × 1010
Median Absolute Deviation (MAD)7.2186125 × 109
Skewness1.1235071
Sum6.3291439 × 1011
Variance4.0504445 × 1020
MonotonicityNot monotonic
2023-12-12T15:06:54.976876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
82078710 1
 
2.9%
15988900 1
 
2.9%
56435780 1
 
2.9%
40686158690 1
 
2.9%
7297582860 1
 
2.9%
61748401880 1
 
2.9%
24062180820 1
 
2.9%
5953664970 1
 
2.9%
0 1
 
2.9%
6095188240 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
0 1
2.9%
15988900 1
2.9%
18625940 1
2.9%
19317620 1
2.9%
21210150 1
2.9%
34596820 1
2.9%
56435780 1
2.9%
82078710 1
2.9%
4188084000 1
2.9%
4819173830 1
2.9%
ValueCountFrequency (%)
77150644000 1
2.9%
61748401880 1
2.9%
47219697830 1
2.9%
41743445270 1
2.9%
40686158690 1
2.9%
39143929930 1
2.9%
37501969720 1
2.9%
36488512300 1
2.9%
36482866520 1
2.9%
33206432000 1
2.9%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.619412
Minimum0
Maximum70.25
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:06:55.113010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1175
Q12.215
median7.56
Q321.75
95-th percentile53.4675
Maximum70.25
Range70.25
Interquartile range (IQR)19.535

Descriptive statistics

Standard deviation18.95778
Coefficient of variation (CV)1.213732
Kurtosis1.6170165
Mean15.619412
Median Absolute Deviation (MAD)6.455
Skewness1.597612
Sum531.06
Variance359.39743
MonotonicityNot monotonic
2023-12-12T15:06:55.240843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0.99 1
 
2.9%
7.55 1
 
2.9%
0.62 1
 
2.9%
53.76 1
 
2.9%
22.98 1
 
2.9%
12.26 1
 
2.9%
5.09 1
 
2.9%
1.2 1
 
2.9%
0.0 1
 
2.9%
2.07 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
0.0 1
2.9%
0.02 1
2.9%
0.17 1
2.9%
0.62 1
2.9%
0.99 1
2.9%
1.01 1
2.9%
1.2 1
2.9%
1.5 1
2.9%
2.07 1
2.9%
2.65 1
2.9%
ValueCountFrequency (%)
70.25 1
2.9%
53.76 1
2.9%
53.31 1
2.9%
53.23 1
2.9%
52.49 1
2.9%
24.6 1
2.9%
23.28 1
2.9%
23.04 1
2.9%
22.98 1
2.9%
18.06 1
2.9%

Interactions

2023-12-12T15:06:51.704503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:50.689157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:50.999204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:51.346298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:51.811535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:50.765527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:51.096694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:51.440935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:51.901066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:50.836295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:51.177835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:51.524400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:52.000558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:50.919321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:51.264668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:51.617809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:06:55.342842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세연도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.7580.8290.7270.813
과세연도0.0001.0000.0000.0000.0000.000
비과세금액0.7580.0001.0000.7440.8940.829
감면금액0.8290.0000.7441.0000.8540.667
부과금액0.7270.0000.8940.8541.0000.525
비과세감면율0.8130.0000.8290.6670.5251.000
2023-12-12T15:06:55.471617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세연도
세목명1.0000.000
과세연도0.0001.000
2023-12-12T15:06:55.591196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율세목명과세연도
비과세금액1.0000.8760.8680.8810.6030.000
감면금액0.8761.0000.9640.6680.6980.000
부과금액0.8680.9641.0000.6350.4860.000
비과세감면율0.8810.6680.6351.0000.6390.000
세목명0.6030.6980.4860.6391.0000.000
과세연도0.0000.0000.0000.0000.0001.000

Missing values

2023-12-12T15:06:52.124288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:06:52.287024image/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

시도명시군구명자치단체코드세목명과세연도비과세금액감면금액부과금액비과세감면율
0대전광역시중구30140등록세20170808980820787100.99
1대전광역시중구30140재산세20171578284128033695221803648851230052.49
2대전광역시중구30140주민세20171066366870562082440662067154024.6
3대전광역시중구30140취득세2017135246279040236558604174344527012.88
4대전광역시중구30140자동차세2017266651170972923290236657640705.24
5대전광역시중구30140등록면허세20171085550012844322052531111802.65
6대전광역시중구30140지역자원시설세2017368200212101500.17
7대전광역시중구30140등록세201807680345968200.02
8대전광역시중구30140재산세20181660182484033918085603750196972053.31
9대전광역시중구30140주민세20181085611440585057690717705176023.28
시도명시군구명자치단체코드세목명과세연도비과세금액감면금액부과금액비과세감면율
24대전광역시중구30140자동차세2020353800570869793300240621808205.09
25대전광역시중구30140등록면허세2020127511305881369059536649701.2
26대전광역시중구30140지역자원시설세202011977409180159889007.55
27대전광역시중구30140등록세2021<NA>98600000.0
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30대전광역시중구30140취득세2021333604500054236320007715064400011.35
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32대전광역시중구30140등록면허세2021146820003964300053747430001.01
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