Overview

Dataset statistics

Number of variables9
Number of observations48
Missing cells5
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory80.8 B

Variable types

Categorical4
Numeric5

Dataset

Description본 데이터는 경상남도 합천군의 년도별 지방세 비과감면율현황으로 세목명, 비과세금액, 감면금액, 부과금액, 비과세감면율 등의 정보를 제공하고 있습니다.
Author경상남도 합천군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15089298

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 3 other fieldsHigh correlation
부과금액 is highly overall correlated with 감면금액 and 1 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 비과세금액 and 3 other fieldsHigh correlation
비과세금액 has 5 (10.4%) missing valuesMissing
비과세금액 has 7 (14.6%) zerosZeros
부과금액 has 5 (10.4%) zerosZeros
비과세감면율 has 11 (22.9%) zerosZeros

Reproduction

Analysis started2023-12-11 01:01:26.460612
Analysis finished2023-12-11 01:01:29.085019
Duration2.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
경상남도
48 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 48
100.0%

Length

2023-12-11T10:01:29.144106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T10:01:29.225580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 48
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
합천군
48 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
합천군 48
100.0%

Length

2023-12-11T10:01:29.328706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T10:01:29.419308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
합천군 48
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
48890
48 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48890
2nd row48890
3rd row48890
4th row48890
5th row48890

Common Values

ValueCountFrequency (%)
48890 48
100.0%

Length

2023-12-11T10:01:29.499135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T10:01:29.575386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48890 48
100.0%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.5
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-11T10:01:29.707070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2019.5
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7258979
Coefficient of variation (CV)0.00085461642
Kurtosis-1.2751304
Mean2019.5
Median Absolute Deviation (MAD)1.5
Skewness0
Sum96936
Variance2.9787234
MonotonicityIncreasing
2023-12-11T10:01:29.853073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2017 8
16.7%
2018 8
16.7%
2019 8
16.7%
2020 8
16.7%
2021 8
16.7%
2022 8
16.7%
ValueCountFrequency (%)
2017 8
16.7%
2018 8
16.7%
2019 8
16.7%
2020 8
16.7%
2021 8
16.7%
2022 8
16.7%
ValueCountFrequency (%)
2022 8
16.7%
2021 8
16.7%
2020 8
16.7%
2019 8
16.7%
2018 8
16.7%
2017 8
16.7%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size516.0 B
교육세
6 
등록세
6 
재산세
6 
주민세
6 
취득세
6 
Other values (3)
18 

Length

Max length7
Median length3
Mean length3.875
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교육세 6
12.5%
등록세 6
12.5%
재산세 6
12.5%
주민세 6
12.5%
취득세 6
12.5%
자동차세 6
12.5%
등록면허세 6
12.5%
지역자원시설세 6
12.5%

Length

2023-12-11T10:01:30.019070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T10:01:30.165394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교육세 6
12.5%
등록세 6
12.5%
재산세 6
12.5%
주민세 6
12.5%
취득세 6
12.5%
자동차세 6
12.5%
등록면허세 6
12.5%
지역자원시설세 6
12.5%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct37
Distinct (%)86.0%
Missing5
Missing (%)10.4%
Infinite0
Infinite (%)0.0%
Mean5.3919484 × 108
Minimum0
Maximum2.923373 × 109
Zeros7
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-11T10:01:30.302696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15616000
median26703000
Q37.30145 × 108
95-th percentile2.734607 × 109
Maximum2.923373 × 109
Range2.923373 × 109
Interquartile range (IQR)7.24529 × 108

Descriptive statistics

Standard deviation9.4929071 × 108
Coefficient of variation (CV)1.7605708
Kurtosis1.3318145
Mean5.3919484 × 108
Median Absolute Deviation (MAD)26703000
Skewness1.677893
Sum2.3185378 × 1010
Variance9.0115285 × 1017
MonotonicityNot monotonic
2023-12-11T10:01:30.411691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 7
 
14.6%
19710000 1
 
2.1%
742611000 1
 
2.1%
27615000 1
 
2.1%
4292000 1
 
2.1%
99085000 1
 
2.1%
2870944000 1
 
2.1%
8227000 1
 
2.1%
1480531000 1
 
2.1%
27857000 1
 
2.1%
Other values (27) 27
56.2%
(Missing) 5
 
10.4%
ValueCountFrequency (%)
0 7
14.6%
4292000 1
 
2.1%
4397000 1
 
2.1%
4650000 1
 
2.1%
5540000 1
 
2.1%
5692000 1
 
2.1%
6835000 1
 
2.1%
7153000 1
 
2.1%
8227000 1
 
2.1%
8477000 1
 
2.1%
ValueCountFrequency (%)
2923373000 1
2.1%
2870944000 1
2.1%
2747194000 1
2.1%
2621324000 1
2.1%
2489391000 1
2.1%
2413175000 1
2.1%
1480531000 1
2.1%
1308133000 1
2.1%
1234738000 1
2.1%
749907000 1
2.1%

감면금액
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0970702 × 108
Minimum14000
Maximum1.988908 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-11T10:01:30.535616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14000
5-th percentile15000
Q111530250
median78093000
Q32.6541775 × 108
95-th percentile1.6249022 × 109
Maximum1.988908 × 109
Range1.988894 × 109
Interquartile range (IQR)2.538875 × 108

Descriptive statistics

Standard deviation5.3772127 × 108
Coefficient of variation (CV)1.7362256
Kurtosis3.3141117
Mean3.0970702 × 108
Median Absolute Deviation (MAD)77964000
Skewness2.1245391
Sum1.4865937 × 1010
Variance2.8914416 × 1017
MonotonicityNot monotonic
2023-12-11T10:01:30.663535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
15000 3
 
6.2%
16000 1
 
2.1%
180640000 1
 
2.1%
63577000 1
 
2.1%
1392996000 1
 
2.1%
191661000 1
 
2.1%
77763000 1
 
2.1%
24294000 1
 
2.1%
8164000 1
 
2.1%
498458000 1
 
2.1%
Other values (36) 36
75.0%
ValueCountFrequency (%)
14000 1
 
2.1%
15000 3
6.2%
16000 1
 
2.1%
50000 1
 
2.1%
208000 1
 
2.1%
5441000 1
 
2.1%
6289000 1
 
2.1%
6993000 1
 
2.1%
8164000 1
 
2.1%
8303000 1
 
2.1%
ValueCountFrequency (%)
1988908000 1
2.1%
1834792000 1
2.1%
1695143000 1
2.1%
1494455000 1
2.1%
1490296000 1
2.1%
1392996000 1
2.1%
547222000 1
2.1%
498458000 1
2.1%
467565000 1
2.1%
440535000 1
2.1%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct44
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4066031 × 109
Minimum0
Maximum1.1796898 × 1010
Zeros5
Zeros (%)10.4%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-11T10:01:30.814409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.0739975 × 108
median2.1718855 × 109
Q34.8760112 × 109
95-th percentile1.0911641 × 1010
Maximum1.1796898 × 1010
Range1.1796898 × 1010
Interquartile range (IQR)4.2686115 × 109

Descriptive statistics

Standard deviation3.6081416 × 109
Coefficient of variation (CV)1.0591611
Kurtosis-0.004874438
Mean3.4066031 × 109
Median Absolute Deviation (MAD)1.609588 × 109
Skewness1.0588382
Sum1.6351695 × 1011
Variance1.3018686 × 1019
MonotonicityNot monotonic
2023-12-11T10:01:30.940078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 5
 
10.4%
11796898000 1
 
2.1%
4034275000 1
 
2.1%
568401000 1
 
2.1%
9877546000 1
 
2.1%
6279213000 1
 
2.1%
1018499000 1
 
2.1%
679215000 1
 
2.1%
3719101000 1
 
2.1%
4274627000 1
 
2.1%
Other values (34) 34
70.8%
ValueCountFrequency (%)
0 5
10.4%
61955000 1
 
2.1%
539358000 1
 
2.1%
556194000 1
 
2.1%
568401000 1
 
2.1%
586065000 1
 
2.1%
586402000 1
 
2.1%
599212000 1
 
2.1%
610129000 1
 
2.1%
617948000 1
 
2.1%
ValueCountFrequency (%)
11796898000 1
2.1%
11597434000 1
2.1%
10915237000 1
2.1%
10904963000 1
2.1%
10083504000 1
2.1%
9877546000 1
2.1%
8412467000 1
2.1%
7065454000 1
2.1%
6706804000 1
2.1%
6418445000 1
2.1%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.969583
Minimum0
Maximum83.72
Zeros11
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-11T10:01:31.078682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.9275
median10.47
Q322.23
95-th percentile79.5955
Maximum83.72
Range83.72
Interquartile range (IQR)19.3025

Descriptive statistics

Standard deviation24.910279
Coefficient of variation (CV)1.3131695
Kurtosis2.1267267
Mean18.969583
Median Absolute Deviation (MAD)10.47
Skewness1.7927723
Sum910.54
Variance620.52201
MonotonicityNot monotonic
2023-12-11T10:01:31.183600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0.0 11
 
22.9%
2.95 1
 
2.1%
26.6 1
 
2.1%
3.49 1
 
2.1%
8.06 1
 
2.1%
18.16 1
 
2.1%
78.82 1
 
2.1%
23.44 1
 
2.1%
28.1 1
 
2.1%
9.82 1
 
2.1%
Other values (28) 28
58.3%
ValueCountFrequency (%)
0.0 11
22.9%
2.86 1
 
2.1%
2.95 1
 
2.1%
3.37 1
 
2.1%
3.41 1
 
2.1%
3.49 1
 
2.1%
3.79 1
 
2.1%
5.53 1
 
2.1%
5.64 1
 
2.1%
5.81 1
 
2.1%
ValueCountFrequency (%)
83.72 1
2.1%
81.43 1
2.1%
79.69 1
2.1%
79.42 1
2.1%
78.82 1
2.1%
75.65 1
2.1%
30.23 1
2.1%
28.1 1
2.1%
26.6 1
2.1%
23.7 1
2.1%

Interactions

2023-12-11T10:01:28.472636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:26.735611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:27.282648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:27.625110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:28.059737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:28.553262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:26.798525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:27.348718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:27.699068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:28.137666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:28.639335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:26.862939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:27.418248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:27.808933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:28.215394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:28.733336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:27.156779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:27.493877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:27.901465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:28.315342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:28.816098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:27.223556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:27.563777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:27.981541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:01:28.404101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T10:01:31.257209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명비과세금액감면금액부과금액비과세감면율
과세년도1.0000.0000.0000.0000.0000.000
세목명0.0001.0000.7410.7950.9380.865
비과세금액0.0000.7411.0000.9560.6860.809
감면금액0.0000.7950.9561.0000.8270.776
부과금액0.0000.9380.6860.8271.0000.662
비과세감면율0.0000.8650.8090.7760.6621.000
2023-12-11T10:01:31.343712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도비과세금액감면금액부과금액비과세감면율세목명
과세년도1.0000.0230.0850.0770.0960.000
비과세금액0.0231.0000.7660.4110.7910.515
감면금액0.0850.7661.0000.6860.7480.589
부과금액0.0770.4110.6861.0000.2800.610
비과세감면율0.0960.7910.7480.2801.0000.736
세목명0.0000.5150.5890.6100.7361.000

Missing values

2023-12-11T10:01:28.915159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T10:01:29.035444image/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

시도명시군구명자치단체코드과세년도세목명비과세금액감면금액부과금액비과세감면율
0경상남도합천군488902017교육세01600034429160000.0
1경상남도합천군488902017등록세<NA>544100000.0
2경상남도합천군488902017재산세2413175000402331000336285800083.72
3경상남도합천군488902017주민세19710000126060005561940005.81
4경상남도합천군488902017취득세74261100014902960001159743400019.25
5경상남도합천군488902017자동차세6018500018015900084124670002.86
6경상남도합천군488902017등록면허세554000010336900091515700011.9
7경상남도합천군488902017지역자원시설세812350002322400058640200017.81
8경상남도합천군488902018교육세01500033252720000.0
9경상남도합천군488902018등록세<NA>628900000.0
시도명시군구명자치단체코드과세년도세목명비과세금액감면금액부과금액비과세감면율
38경상남도합천군488902021등록면허세6835000879980009656910009.82
39경상남도합천군488902021지역자원시설세1049910002470400067861100019.11
40경상남도합천군488902022교육세05000037074490000.0
41경상남도합천군488902022등록세<NA>20800000.0
42경상남도합천군488902022재산세2923373000547222000458775800075.65
43경상남도합천군488902022주민세847700014633400065313100023.7
44경상남도합천군488902022취득세130813300019889080001090496300030.23
45경상남도합천군488902022자동차세2670300016691200057407710003.37
46경상남도합천군488902022등록면허세4397000588250008337300007.58
47경상남도합천군488902022지역자원시설세1188960002760000065926800022.22