Overview

Dataset statistics

Number of variables9
Number of observations34
Missing cells0
Missing cells (%)0.0%
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 과세액 중 비과세액과 감면액이 차지하는 비율 현황 데이터를 제공하여 국민 조세 혜택 규모를 파악하는데 사용하고자 합니다.
URLhttps://www.data.go.kr/data/15078718/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 2 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 비과세금액 and 1 other fieldsHigh correlation
세목명 is highly overall correlated with 부과금액 High correlation
감면금액 has unique valuesUnique
부과금액 has unique valuesUnique
비과세금액 has 6 (17.6%) zerosZeros
감면금액 has 1 (2.9%) zerosZeros
부과금액 has 1 (2.9%) zerosZeros
비과세감면율 has 3 (8.8%) zerosZeros

Reproduction

Analysis started2023-12-12 22:49:23.084464
Analysis finished2023-12-12 22:49:25.298797
Duration2.21 seconds
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
전라남도
34 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 34
100.0%

Length

2023-12-13T07:49:25.365835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:49:25.469498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 34
100.0%

시군구명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
무안군 34
100.0%

Length

2023-12-13T07:49:25.578822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:49:25.672348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무안군 34
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
46840
34 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46840
2nd row46840
3rd row46840
4th row46840
5th row46840

Common Values

ValueCountFrequency (%)
46840 34
100.0%

Length

2023-12-13T07:49:25.784374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:49:25.889218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46840 34
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Memory size404.0 B
재산세
5 
주민세
5 
취득세
5 
자동차세
5 
등록면허세
5 
Other values (3)
9 

Length

Max length7
Median length3
Mean length3.7941176
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%
등록세 4
11.8%
지역자원시설세 3
8.8%
교육세 2
 
5.9%

Length

2023-12-13T07:49:25.986917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:49:26.132478image/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%
등록세 4
11.8%
지역자원시설세 3
8.8%
교육세 2
 
5.9%

과세년도
Categorical

Distinct5
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size404.0 B
2020
8 
2021
8 
2017
7 
2018
6 
2019
5 

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 (%)
2020 8
23.5%
2021 8
23.5%
2017 7
20.6%
2018 6
17.6%
2019 5
14.7%

Length

2023-12-13T07:49:26.294927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:49:26.394196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 8
23.5%
2021 8
23.5%
2017 7
20.6%
2018 6
17.6%
2019 5
14.7%

비과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5318712 × 109
Minimum0
Maximum8.169376 × 109
Zeros6
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T07:49:26.524641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111073055
median86715315
Q32.9206216 × 109
95-th percentile6.8293641 × 109
Maximum8.169376 × 109
Range8.169376 × 109
Interquartile range (IQR)2.9095486 × 109

Descriptive statistics

Standard deviation2.5290099 × 109
Coefficient of variation (CV)1.6509286
Kurtosis0.88653076
Mean1.5318712 × 109
Median Absolute Deviation (MAD)86715315
Skewness1.4925614
Sum5.208362 × 1010
Variance6.3958913 × 1018
MonotonicityNot monotonic
2023-12-13T07:49:26.684217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 6
 
17.6%
3224485480 1
 
2.9%
297928000 1
 
2.9%
13355000 1
 
2.9%
90236000 1
 
2.9%
2009030000 1
 
2.9%
119921000 1
 
2.9%
7430269000 1
 
2.9%
286867000 1
 
2.9%
7705000 1
 
2.9%
Other values (19) 19
55.9%
ValueCountFrequency (%)
0 6
17.6%
346980 1
 
2.9%
7705000 1
 
2.9%
10780470 1
 
2.9%
11950810 1
 
2.9%
13355000 1
 
2.9%
22860000 1
 
2.9%
23105790 1
 
2.9%
80853430 1
 
2.9%
81127000 1
 
2.9%
ValueCountFrequency (%)
8169376000 1
2.9%
7430269000 1
2.9%
6505800000 1
2.9%
6410664470 1
2.9%
5105496280 1
2.9%
4081359710 1
2.9%
3818591940 1
2.9%
3667676290 1
2.9%
3224485480 1
2.9%
2009030000 1
2.9%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9833066 × 108
Minimum0
Maximum6.066965 × 109
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T07:49:26.844049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile37150
Q11.3827084 × 108
median1.9954 × 108
Q31.4653071 × 109
95-th percentile4.7334909 × 109
Maximum6.066965 × 109
Range6.066965 × 109
Interquartile range (IQR)1.3270362 × 109

Descriptive statistics

Standard deviation1.5653724 × 109
Coefficient of variation (CV)1.5679899
Kurtosis3.4202591
Mean9.9833066 × 108
Median Absolute Deviation (MAD)1.979965 × 108
Skewness2.0191502
Sum3.3943242 × 1010
Variance2.4503906 × 1018
MonotonicityNot monotonic
2023-12-13T07:49:26.992339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
3381110 1
 
2.9%
55000 1
 
2.9%
1585859000 1
 
2.9%
135910000 1
 
2.9%
4692803000 1
 
2.9%
388768000 1
 
2.9%
201997000 1
 
2.9%
154653000 1
 
2.9%
3527000 1
 
2.9%
4000 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
0 1
2.9%
4000 1
2.9%
55000 1
2.9%
3032000 1
2.9%
3381110 1
2.9%
3527000 1
2.9%
11789440 1
2.9%
15500950 1
2.9%
135910000 1
2.9%
145353350 1
2.9%
ValueCountFrequency (%)
6066965000 1
2.9%
4809054170 1
2.9%
4692803000 1
2.9%
3170762450 1
2.9%
2982648980 1
2.9%
1702989490 1
2.9%
1673880000 1
2.9%
1650958180 1
2.9%
1585859000 1
2.9%
1103651220 1
2.9%

부과금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2057719 × 1010
Minimum0
Maximum6.3681465 × 1010
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T07:49:27.131727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18950727
Q11.4529072 × 109
median7.2599565 × 109
Q31.4945588 × 1010
95-th percentile4.1677044 × 1010
Maximum6.3681465 × 1010
Range6.3681465 × 1010
Interquartile range (IQR)1.349268 × 1010

Descriptive statistics

Standard deviation1.5006521 × 1010
Coefficient of variation (CV)1.2445571
Kurtosis3.8427884
Mean1.2057719 × 1010
Median Absolute Deviation (MAD)6.638488 × 109
Skewness1.9004516
Sum4.0996246 × 1011
Variance2.2519566 × 1020
MonotonicityNot monotonic
2023-12-13T07:49:27.260506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
55282920 1
 
2.9%
10763932000 1
 
2.9%
12283683000 1
 
2.9%
1414937000 1
 
2.9%
63681465000 1
 
2.9%
13854677000 1
 
2.9%
3755981000 1
 
2.9%
2164337000 1
 
2.9%
0 1
 
2.9%
11443686000 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
0 1
2.9%
2557220 1
2.9%
27778000 1
2.9%
55282920 1
2.9%
81257560 1
2.9%
577701000 1
2.9%
1295458650 1
2.9%
1353093630 1
2.9%
1414937000 1
2.9%
1566817650 1
2.9%
ValueCountFrequency (%)
63681465000 1
2.9%
49497512000 1
2.9%
37466022650 1
2.9%
31926804620 1
2.9%
29256766690 1
2.9%
18661750770 1
2.9%
17897353280 1
2.9%
16424391000 1
2.9%
15143719170 1
2.9%
14351192980 1
2.9%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.043529
Minimum0
Maximum150.58
Zeros3
Zeros (%)8.8%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T07:49:27.401530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.065
median14.04
Q321.2775
95-th percentile66.451
Maximum150.58
Range150.58
Interquartile range (IQR)17.2125

Descriptive statistics

Standard deviation28.805415
Coefficient of variation (CV)1.368849
Kurtosis12.17796
Mean21.043529
Median Absolute Deviation (MAD)8.37
Skewness3.1303675
Sum715.48
Variance829.75192
MonotonicityNot monotonic
2023-12-13T07:49:27.562688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.0 3
 
8.8%
6.12 1
 
2.9%
7.1 1
 
2.9%
18.63 1
 
2.9%
6.2 1
 
2.9%
2.9 1
 
2.9%
16.32 1
 
2.9%
150.58 1
 
2.9%
67.53 1
 
2.9%
20.4 1
 
2.9%
Other values (22) 22
64.7%
ValueCountFrequency (%)
0.0 3
8.8%
2.71 1
 
2.9%
2.76 1
 
2.9%
2.9 1
 
2.9%
2.96 1
 
2.9%
3.39 1
 
2.9%
3.56 1
 
2.9%
5.58 1
 
2.9%
5.76 1
 
2.9%
6.12 1
 
2.9%
ValueCountFrequency (%)
150.58 1
2.9%
67.53 1
2.9%
65.87 1
2.9%
53.58 1
2.9%
38.11 1
2.9%
33.89 1
2.9%
32.59 1
2.9%
22.13 1
2.9%
21.53 1
2.9%
20.52 1
2.9%

Interactions

2023-12-13T07:49:24.686173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:23.306887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:23.965721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:24.340284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:24.812813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:23.394271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:24.091717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:24.423268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:24.912354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:23.767220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:24.176115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:24.508025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:24.997459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:23.849155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:24.257721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:24.599517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:49:27.656963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.4350.6180.7630.644
과세년도0.0001.0000.1470.0000.0000.000
비과세금액0.4350.1471.0000.9670.9620.708
감면금액0.6180.0000.9671.0000.9520.699
부과금액0.7630.0000.9620.9521.0000.373
비과세감면율0.6440.0000.7080.6990.3731.000
2023-12-13T07:49:27.768300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도
세목명1.0000.000
과세년도0.0001.000
2023-12-13T07:49:27.885230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율세목명과세년도
비과세금액1.0000.8190.6200.7560.2300.047
감면금액0.8191.0000.8190.5100.3760.000
부과금액0.6200.8191.0000.1020.5290.000
비과세감면율0.7560.5100.1021.0000.4050.000
세목명0.2300.3760.5290.4051.0000.000
과세년도0.0470.0000.0000.0000.0001.000

Missing values

2023-12-13T07:49:25.105445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:49:25.247174image/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
0전라남도무안군46840등록세201703381110552829206.12
1전라남도무안군46840재산세2017322448548011036512201328171165032.59
2전라남도무안군46840주민세2017228600001550095012954586502.96
3전라남도무안군46840취득세2017366767629031707624503746602265018.25
4전라남도무안군46840자동차세201783194630432715560186617507702.76
5전라남도무안군46840등록면허세20171195081019612514024310792308.56
6전라남도무안군46840지역자원시설세20173469800255722013.57
7전라남도무안군46840등록세20180117894408125756014.51
8전라남도무안군46840재산세2018381859194016509581801435119298038.11
9전라남도무안군46840주민세2018132252750145353350135309363020.52
시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
24전라남도무안군46840등록면허세2020770500020199700037559810005.58
25전라남도무안군46840지역자원시설세2020286867000154653000216433700020.4
26전라남도무안군46840교육세2021055000107639320000.0
27전라남도무안군46840등록세20210352700000.0
28전라남도무안군46840재산세2021743026900016738800001348212200067.53
29전라남도무안군46840주민세2021119921000750007000577701000150.58
30전라남도무안군46840취득세2021200903000060669650004949751200016.32
31전라남도무안군46840자동차세202190236000386707000164243910002.9
32전라남도무안군46840등록면허세20211335500019708300033921850006.2
33전라남도무안군46840지역자원시설세2021297928000167792000249963900018.63