Overview

Dataset statistics

Number of variables9
Number of observations31
Missing cells2
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory82.3 B

Variable types

Categorical5
Numeric4

Dataset

Description["2017~2020년 과세액 중 비과세액과 감면액이 차지하는 비율 현황을 제공하는 자료로서 국민 조세 혜택 규모를 파악하는 데 사용된다."]
Author강원도 화천군
URLhttps://www.data.go.kr/data/15080134/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 1 other fieldsHigh correlation
부과금액 is highly overall correlated with 세목명High correlation
비과세감면율 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
비과세금액 has 2 (6.5%) missing valuesMissing
비과세금액 has 5 (16.1%) zerosZeros
부과금액 has 2 (6.5%) zerosZeros
비과세감면율 has 2 (6.5%) zerosZeros

Reproduction

Analysis started2023-12-12 20:38:34.150902
Analysis finished2023-12-12 20:38:35.860937
Duration1.71 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
강원도
31 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원도 31
100.0%

Length

2023-12-13T05:38:35.917327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:38:36.011253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 31
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
화천군
31 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
화천군 31
100.0%

Length

2023-12-13T05:38:36.095758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:38:36.171461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화천군 31
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
42790
31 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row42790
2nd row42790
3rd row42790
4th row42790
5th row42790

Common Values

ValueCountFrequency (%)
42790 31
100.0%

Length

2023-12-13T05:38:36.251596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:38:36.331264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
42790 31
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
교육세
4 
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
Other values (3)
11 

Length

Max length7
Median length3
Mean length3.9032258
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교육세 4
12.9%
재산세 4
12.9%
주민세 4
12.9%
취득세 4
12.9%
자동차세 4
12.9%
등록면허세 4
12.9%
지역자원시설세 4
12.9%
등록세 3
9.7%

Length

2023-12-13T05:38:36.421579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:38:36.523966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교육세 4
12.9%
재산세 4
12.9%
주민세 4
12.9%
취득세 4
12.9%
자동차세 4
12.9%
등록면허세 4
12.9%
지역자원시설세 4
12.9%
등록세 3
9.7%

과세년도
Categorical

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
2017
8 
2018
8 
2020
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
25.8%
2018 8
25.8%
2020 8
25.8%
2019 7
22.6%

Length

2023-12-13T05:38:36.647836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:38:36.733580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 8
25.8%
2018 8
25.8%
2020 8
25.8%
2019 7
22.6%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct25
Distinct (%)86.2%
Missing2
Missing (%)6.5%
Infinite0
Infinite (%)0.0%
Mean5.7202741 × 108
Minimum0
Maximum3.716542 × 109
Zeros5
Zeros (%)16.1%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-13T05:38:36.816552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13150000
median19796000
Q33.09647 × 108
95-th percentile3.4375884 × 109
Maximum3.716542 × 109
Range3.716542 × 109
Interquartile range (IQR)3.06497 × 108

Descriptive statistics

Standard deviation1.1750911 × 109
Coefficient of variation (CV)2.0542566
Kurtosis3.0422011
Mean5.7202741 × 108
Median Absolute Deviation (MAD)19796000
Skewness2.1541151
Sum1.6588795 × 1010
Variance1.3808391 × 1018
MonotonicityNot monotonic
2023-12-13T05:38:36.920262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 5
 
16.1%
9060000 1
 
3.2%
309647000 1
 
3.2%
252892000 1
 
3.2%
20150000 1
 
3.2%
20278000 1
 
3.2%
589053000 1
 
3.2%
3150000 1
 
3.2%
3716542000 1
 
3.2%
246614000 1
 
3.2%
Other values (15) 15
48.4%
(Missing) 2
 
6.5%
ValueCountFrequency (%)
0 5
16.1%
1028000 1
 
3.2%
2870000 1
 
3.2%
3150000 1
 
3.2%
3498000 1
 
3.2%
9060000 1
 
3.2%
9520000 1
 
3.2%
10310000 1
 
3.2%
17127000 1
 
3.2%
17515000 1
 
3.2%
ValueCountFrequency (%)
3716542000 1
3.2%
3525048000 1
3.2%
3306399000 1
3.2%
3145929000 1
3.2%
589053000 1
3.2%
503049000 1
3.2%
389542000 1
3.2%
309647000 1
3.2%
252892000 1
3.2%
246614000 1
3.2%

감면금액
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3698432 × 108
Minimum164000
Maximum1.373003 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-13T05:38:37.048493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum164000
5-th percentile301500
Q14375000
median34186000
Q392908000
95-th percentile6.557185 × 108
Maximum1.373003 × 109
Range1.372839 × 109
Interquartile range (IQR)88533000

Descriptive statistics

Standard deviation2.9309563 × 108
Coefficient of variation (CV)2.139629
Kurtosis10.611049
Mean1.3698432 × 108
Median Absolute Deviation (MAD)33758000
Skewness3.1382858
Sum4.246514 × 109
Variance8.5905046 × 1016
MonotonicityNot monotonic
2023-12-13T05:38:37.156644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4650000 2
 
6.5%
197000 1
 
3.2%
428000 1
 
3.2%
8743000 1
 
3.2%
40431000 1
 
3.2%
87042000 1
 
3.2%
1373003000 1
 
3.2%
100315000 1
 
3.2%
5333000 1
 
3.2%
164000 1
 
3.2%
Other values (20) 20
64.5%
ValueCountFrequency (%)
164000 1
3.2%
197000 1
3.2%
406000 1
3.2%
428000 1
3.2%
504000 1
3.2%
3300000 1
3.2%
3445000 1
3.2%
4100000 1
3.2%
4650000 2
6.5%
5333000 1
3.2%
ValueCountFrequency (%)
1373003000 1
3.2%
691565000 1
3.2%
619872000 1
3.2%
577080000 1
3.2%
100315000 1
3.2%
100168000 1
3.2%
96451000 1
3.2%
94502000 1
3.2%
91314000 1
3.2%
89802000 1
3.2%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8301976 × 109
Minimum0
Maximum6.056689 × 109
Zeros2
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-13T05:38:37.268545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3713000
Q13.802435 × 108
median1.186722 × 109
Q33.0695965 × 109
95-th percentile5.6081715 × 109
Maximum6.056689 × 109
Range6.056689 × 109
Interquartile range (IQR)2.689353 × 109

Descriptive statistics

Standard deviation1.8654677 × 109
Coefficient of variation (CV)1.0192712
Kurtosis-0.24835497
Mean1.8301976 × 109
Median Absolute Deviation (MAD)9.37106 × 108
Skewness0.93707232
Sum5.6736127 × 1010
Variance3.4799698 × 1018
MonotonicityNot monotonic
2023-12-13T05:38:37.367128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 2
 
6.5%
3109827000 1
 
3.2%
1363628000 1
 
3.2%
547922000 1
 
3.2%
473660000 1
 
3.2%
3488001000 1
 
3.2%
5855518000 1
 
3.2%
270395000 1
 
3.2%
1456030000 1
 
3.2%
7426000 1
 
3.2%
Other values (20) 20
64.5%
ValueCountFrequency (%)
0 2
6.5%
7426000 1
3.2%
249616000 1
3.2%
270395000 1
3.2%
279879000 1
3.2%
290139000 1
3.2%
373258000 1
3.2%
387229000 1
3.2%
428668000 1
3.2%
433812000 1
3.2%
ValueCountFrequency (%)
6056689000 1
3.2%
5855518000 1
3.2%
5360825000 1
3.2%
4645996000 1
3.2%
3585026000 1
3.2%
3488001000 1
3.2%
3112784000 1
3.2%
3109827000 1
3.2%
3029366000 1
3.2%
2883961000 1
3.2%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.529677
Minimum0
Maximum273.06
Zeros2
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-13T05:38:37.461230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.005
Q13.07
median10.79
Q351.025
95-th percentile266.24
Maximum273.06
Range273.06
Interquartile range (IQR)47.955

Descriptive statistics

Standard deviation87.57454
Coefficient of variation (CV)1.7681226
Kurtosis2.9290117
Mean49.529677
Median Absolute Deviation (MAD)10.78
Skewness2.0880781
Sum1535.42
Variance7669.3
MonotonicityNot monotonic
2023-12-13T05:38:37.561715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.01 4
 
12.9%
0.0 2
 
6.5%
47.75 1
 
3.2%
12.79 1
 
3.2%
3.08 1
 
3.2%
33.51 1
 
3.2%
2.88 1
 
3.2%
262.14 1
 
3.2%
71.82 1
 
3.2%
68.5 1
 
3.2%
Other values (17) 17
54.8%
ValueCountFrequency (%)
0.0 2
6.5%
0.01 4
12.9%
2.88 1
 
3.2%
3.06 1
 
3.2%
3.08 1
 
3.2%
3.67 1
 
3.2%
3.86 1
 
3.2%
4.54 1
 
3.2%
4.58 1
 
3.2%
5.99 1
 
3.2%
ValueCountFrequency (%)
273.06 1
3.2%
266.63 1
3.2%
265.85 1
3.2%
262.14 1
3.2%
71.82 1
3.2%
68.5 1
3.2%
54.72 1
3.2%
54.3 1
3.2%
47.75 1
3.2%
33.51 1
3.2%

Interactions

2023-12-13T05:38:35.361773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:34.384229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:34.732682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:35.044145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:35.437268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:34.470037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:34.821325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:35.126699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:35.514789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:34.558214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:34.899399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:35.207745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:35.584598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:34.649421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:34.974319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:35.294803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:38:37.652145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.9310.6820.9000.945
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.9310.0001.0000.7910.9750.868
감면금액0.6820.0000.7911.0000.9820.364
부과금액0.9000.0000.9750.9821.0000.835
비과세감면율0.9450.0000.8680.3640.8351.000
2023-12-13T05:38:37.755432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2023-12-13T05:38:37.838944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율세목명과세년도
비과세금액1.0000.7910.2970.7420.6010.000
감면금액0.7911.0000.4940.6160.3330.000
부과금액0.2970.4941.0000.0300.5170.000
비과세감면율0.7420.6160.0301.0000.6360.000
세목명0.6010.3330.5170.6361.0000.000
과세년도0.0000.0000.0000.0000.0001.000

Missing values

2023-12-13T05:38:35.684190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:38:35.817641image/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
0강원도화천군42790교육세2017019700031098270000.01
1강원도화천군42790등록세2017<NA>50400000.0
2강원도화천군42790재산세20173145929000945020001186722000273.06
3강원도화천군42790주민세2017906000041000002901390004.54
4강원도화천군42790취득세2017309647000619872000605668900015.35
5강원도화천군42790자동차세2017171270009131400028064120003.86
6강원도화천군42790등록면허세201734980005412100038722900014.88
7강원도화천군42790지역자원시설세2017230192000965500044166900054.3
8강원도화천군42790교육세2018040600030293660000.01
9강원도화천군42790등록세2018<NA>344500000.0
시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
21강원도화천군42790등록면허세20191028000341860004286680008.21
22강원도화천군42790지역자원시설세2019246614000905500037325800068.5
23강원도화천군42790교육세2020016400031127840000.01
24강원도화천군42790등록세202005333000742600071.82
25강원도화천군42790재산세202037165420001003150001456030000262.14
26강원도화천군42790주민세2020315000046500002703950002.88
27강원도화천군42790취득세20205890530001373003000585551800033.51
28강원도화천군42790자동차세2020202780008704200034880010003.08
29강원도화천군42790등록면허세2020201500004043100047366000012.79
30강원도화천군42790지역자원시설세2020252892000874300054792200047.75