Overview

Dataset statistics

Number of variables9
Number of observations23
Missing cells2
Missing cells (%)1.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory83.7 B

Variable types

Categorical5
Numeric4

Dataset

Description경기도 파주시의 2017년부터 2019년까지의 과세액 중 비과세액과 감면액이 차지하는 비율 현황으로서 국민 조세 혜택 규모를 파악하는 기초자료로 활용됨
Author경기도 파주시
URLhttps://www.data.go.kr/data/15078363/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 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 비과세금액 and 2 other fieldsHigh correlation
비과세금액 has 2 (8.7%) missing valuesMissing
감면금액 has unique valuesUnique
비과세금액 has 3 (13.0%) zerosZeros
부과금액 has 2 (8.7%) zerosZeros
비과세감면율 has 5 (21.7%) zerosZeros

Reproduction

Analysis started2023-12-11 23:49:59.056121
Analysis finished2023-12-11 23:50:01.320751
Duration2.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
경기도
23 

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 23
100.0%

Length

2023-12-12T08:50:01.396321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:50:01.487535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 23
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
파주시
23 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
파주시 23
100.0%

Length

2023-12-12T08:50:01.595747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:50:01.705792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
파주시 23
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
41480
23 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41480
2nd row41480
3rd row41480
4th row41480
5th row41480

Common Values

ValueCountFrequency (%)
41480 23
100.0%

Length

2023-12-12T08:50:01.812979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:50:01.915639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41480 23
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size316.0 B
교육세
3 
재산세
3 
주민세
3 
취득세
3 
자동차세
3 
Other values (3)
8 

Length

Max length7
Median length3
Mean length3.9130435
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교육세 3
13.0%
재산세 3
13.0%
주민세 3
13.0%
취득세 3
13.0%
자동차세 3
13.0%
등록면허세 3
13.0%
지역자원시설세 3
13.0%
등록세 2
8.7%

Length

2023-12-12T08:50:02.019524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:50:02.153507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교육세 3
13.0%
재산세 3
13.0%
주민세 3
13.0%
취득세 3
13.0%
자동차세 3
13.0%
등록면허세 3
13.0%
지역자원시설세 3
13.0%
등록세 2
8.7%

과세년도
Categorical

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2017
8 
2018
8 
2019
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 8
34.8%
2018 8
34.8%
2019 7
30.4%

Length

2023-12-12T08:50:02.275933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:50:02.363941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 8
34.8%
2018 8
34.8%
2019 7
30.4%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct19
Distinct (%)90.5%
Missing2
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean7.7830596 × 109
Minimum0
Maximum4.8985107 × 1010
Zeros3
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T08:50:02.472995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q122503000
median6.98546 × 108
Q35.106538 × 109
95-th percentile4.1419047 × 1010
Maximum4.8985107 × 1010
Range4.8985107 × 1010
Interquartile range (IQR)5.084035 × 109

Descriptive statistics

Standard deviation1.5446648 × 1010
Coefficient of variation (CV)1.9846499
Kurtosis2.8611691
Mean7.7830596 × 109
Median Absolute Deviation (MAD)6.84604 × 108
Skewness2.0566164
Sum1.6344425 × 1011
Variance2.3859894 × 1020
MonotonicityNot monotonic
2023-12-12T08:50:02.600816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 3
 
13.0%
214725000 1
 
4.3%
5106538000 1
 
4.3%
747777000 1
 
4.3%
13942000 1
 
4.3%
741225000 1
 
4.3%
10711530000 1
 
4.3%
85990000 1
 
4.3%
48985107000 1
 
4.3%
698546000 1
 
4.3%
Other values (9) 9
39.1%
(Missing) 2
 
8.7%
ValueCountFrequency (%)
0 3
13.0%
12660000 1
 
4.3%
13942000 1
 
4.3%
22503000 1
 
4.3%
85990000 1
 
4.3%
214725000 1
 
4.3%
215505000 1
 
4.3%
640578000 1
 
4.3%
698546000 1
 
4.3%
741225000 1
 
4.3%
ValueCountFrequency (%)
48985107000 1
4.3%
41419047000 1
4.3%
40599864000 1
4.3%
11684781000 1
4.3%
10711530000 1
4.3%
5106538000 1
4.3%
791127000 1
4.3%
752806000 1
4.3%
747777000 1
4.3%
741225000 1
4.3%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4557182 × 109
Minimum4000
Maximum4.3008869 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T08:50:02.708766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4000
5-th percentile5200
Q12.430515 × 108
median6.71061 × 108
Q37.1466915 × 109
95-th percentile3.3870384 × 1010
Maximum4.3008869 × 1010
Range4.3008865 × 1010
Interquartile range (IQR)6.90364 × 109

Descriptive statistics

Standard deviation1.29588 × 1010
Coefficient of variation (CV)1.7381022
Kurtosis2.0180278
Mean7.4557182 × 109
Median Absolute Deviation (MAD)6.71056 × 108
Skewness1.7794071
Sum1.7148152 × 1011
Variance1.679305 × 1020
MonotonicityNot monotonic
2023-12-12T08:50:02.820863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
4000 1
 
4.3%
1288389000 1
 
4.3%
671061000 1
 
4.3%
421957000 1
 
4.3%
1540556000 1
 
4.3%
43008869000 1
 
4.3%
12905000 1
 
4.3%
12166048000 1
 
4.3%
7000 1
 
4.3%
663488000 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
4000 1
4.3%
5000 1
4.3%
7000 1
4.3%
12905000 1
4.3%
63226000 1
4.3%
64146000 1
4.3%
421957000 1
4.3%
459055000 1
4.3%
586534000 1
4.3%
611624000 1
4.3%
ValueCountFrequency (%)
43008869000 1
4.3%
33981435000 1
4.3%
32870922000 1
4.3%
19166699000 1
4.3%
18920074000 1
4.3%
12166048000 1
4.3%
2127335000 1
4.3%
1540556000 1
4.3%
1433473000 1
4.3%
1423707000 1
4.3%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9290472 × 1010
Minimum0
Maximum2.7098369 × 1011
Zeros2
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T08:50:02.926183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.4512269 × 109
Q11.8947582 × 1010
median5.9787684 × 1010
Q38.7867912 × 1010
95-th percentile2.1654158 × 1011
Maximum2.7098369 × 1011
Range2.7098369 × 1011
Interquartile range (IQR)6.892033 × 1010

Descriptive statistics

Standard deviation7.415816 × 1010
Coefficient of variation (CV)1.0702505
Kurtosis1.7663606
Mean6.9290472 × 1010
Median Absolute Deviation (MAD)4.1183157 × 1010
Skewness1.5436333
Sum1.5936808 × 1012
Variance5.4994326 × 1021
MonotonicityNot monotonic
2023-12-12T08:50:03.034309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 2
 
8.7%
59787684000 1
 
4.3%
67928810000 1
 
4.3%
20827846000 1
 
4.3%
16891722000 1
 
4.3%
70142469000 1
 
4.3%
217258735000 1
 
4.3%
20360344000 1
 
4.3%
113738333000 1
 
4.3%
60338525000 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
0 2
8.7%
14512269000 1
4.3%
16698342000 1
4.3%
16891722000 1
4.3%
18604527000 1
4.3%
19290637000 1
4.3%
19538931000 1
4.3%
20360344000 1
4.3%
20827846000 1
4.3%
21142953000 1
4.3%
ValueCountFrequency (%)
270983690000 1
4.3%
217258735000 1
4.3%
210087185000 1
4.3%
118030194000 1
4.3%
113738333000 1
4.3%
105593355000 1
4.3%
70142469000 1
4.3%
67928810000 1
4.3%
67545047000 1
4.3%
64379252000 1
4.3%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.521304
Minimum0
Maximum57.14
Zeros5
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T08:50:03.131912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.905
median3.25
Q311.97
95-th percentile53.448
Maximum57.14
Range57.14
Interquartile range (IQR)11.065

Descriptive statistics

Standard deviation17.981783
Coefficient of variation (CV)1.5607419
Kurtosis2.282098
Mean11.521304
Median Absolute Deviation (MAD)3.25
Skewness1.8671399
Sum264.99
Variance323.34451
MonotonicityNot monotonic
2023-12-12T08:50:03.234060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 5
21.7%
50.64 1
 
4.3%
6.81 1
 
4.3%
2.58 1
 
4.3%
3.25 1
 
4.3%
24.73 1
 
4.3%
0.49 1
 
4.3%
53.76 1
 
4.3%
7.06 1
 
4.3%
2.54 1
 
4.3%
Other values (9) 9
39.1%
ValueCountFrequency (%)
0.0 5
21.7%
0.49 1
 
4.3%
1.32 1
 
4.3%
1.42 1
 
4.3%
2.54 1
 
4.3%
2.58 1
 
4.3%
3.24 1
 
4.3%
3.25 1
 
4.3%
3.26 1
 
4.3%
4.2 1
 
4.3%
ValueCountFrequency (%)
57.14 1
4.3%
53.76 1
4.3%
50.64 1
4.3%
24.73 1
4.3%
18.61 1
4.3%
16.44 1
4.3%
7.5 1
4.3%
7.06 1
4.3%
6.81 1
4.3%
4.2 1
4.3%

Interactions

2023-12-12T08:50:00.403677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:49:59.321712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:49:59.678034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:50:00.031431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:50:00.500278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:49:59.417895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:49:59.766387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:50:00.133681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:50:00.619791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:49:59.504045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:49:59.850347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:50:00.219217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:50:01.024342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:49:59.602625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:49:59.938603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:50:00.313649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:50:03.308266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.6990.6900.7520.752
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.6990.0001.0000.9930.9070.907
감면금액0.6900.0000.9931.0000.9080.908
부과금액0.7520.0000.9070.9081.0000.983
비과세감면율0.7520.0000.9070.9080.9831.000
2023-12-12T08:50:03.401544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도
세목명1.0000.000
과세년도0.0001.000
2023-12-12T08:50:03.498531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율세목명과세년도
비과세금액1.0000.9090.6920.8890.5000.000
감면금액0.9091.0000.5510.7390.4710.000
부과금액0.6920.5511.0000.5630.5000.000
비과세감면율0.8890.7390.5631.0000.5000.000
세목명0.5000.4710.5000.5001.0000.000
과세년도0.0000.0000.0000.0000.0001.000

Missing values

2023-12-12T08:50:01.143405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:50:01.270133image/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
0경기도파주시41480교육세201704000597876840000.0
1경기도파주시41480등록세2017<NA>128838900000.0
2경기도파주시41480재산세2017405998640001916669900011803019400050.64
3경기도파주시41480주민세201721472500063226000195389310001.42
4경기도파주시41480취득세201751065380003398143500021008718500018.61
5경기도파주시41480자동차세20177528060001433473000675450470003.24
6경기도파주시41480등록면허세201722503000586534000145122690004.2
7경기도파주시41480지역자원시설세2017640578000611624000166983420007.5
8경기도파주시41480교육세201805000643792520000.0
9경기도파주시41480등록세2018<NA>212733500000.0
시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
13경기도파주시41480자동차세20187911270001423707000679288100003.26
14경기도파주시41480등록면허세201812660000459055000186045270002.54
15경기도파주시41480지역자원시설세2018698546000663488000192906370007.06
16경기도파주시41480교육세201907000603385250000.0
17경기도파주시41480재산세2019489851070001216604800011373833300053.76
18경기도파주시41480주민세20198599000012905000203603440000.49
19경기도파주시41480취득세2019107115300004300886900021725873500024.73
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