Overview

Dataset statistics

Number of variables9
Number of observations40
Missing cells8
Missing cells (%)2.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory80.2 B

Variable types

Categorical5
Text1
Numeric3

Dataset

Description지방세 비과/감면율 현황, 과세액 중 비과세액과 감면액이 차지하는 비율 현황 제공, 국민 조세 혜택 규모를 파악하는 데 사용
Author강원특별자치도 양양군
URLhttps://www.data.go.kr/data/15079480/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
감면금액 is highly overall correlated with 부과금액 and 1 other fieldsHigh correlation
부과금액 is highly overall correlated with 감면금액High correlation
비과세감면율 is highly overall correlated with 감면금액 and 1 other fieldsHigh correlation
세목명 is highly overall correlated with 비과세감면율High correlation
비과세금액 has 6 (15.0%) missing valuesMissing
부과금액 has 1 (2.5%) missing valuesMissing
비과세감면율 has 1 (2.5%) missing valuesMissing
감면금액 has unique valuesUnique
부과금액 has 3 (7.5%) zerosZeros
비과세감면율 has 5 (12.5%) zerosZeros

Reproduction

Analysis started2024-03-14 13:59:00.755482
Analysis finished2024-03-14 13:59:04.024680
Duration3.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size448.0 B
강원도
40 

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 40
100.0%

Length

2024-03-14T22:59:04.222349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:59:04.527571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 40
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size448.0 B
양양군
40 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
양양군 40
100.0%

Length

2024-03-14T22:59:04.846920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:59:05.149371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양양군 40
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size448.0 B
42830
40 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row42830
2nd row42830
3rd row42830
4th row42830
5th row42830

Common Values

ValueCountFrequency (%)
42830 40
100.0%

Length

2024-03-14T22:59:05.470293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:59:05.776844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
42830 40
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size448.0 B
교육세
5 
등록세
5 
재산세
5 
주민세
5 
취득세
5 
Other values (3)
15 

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 5
12.5%
등록세 5
12.5%
재산세 5
12.5%
주민세 5
12.5%
취득세 5
12.5%
자동차세 5
12.5%
등록면허세 5
12.5%
지역자원시설세 5
12.5%

Length

2024-03-14T22:59:06.145158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:59:06.483566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교육세 5
12.5%
등록세 5
12.5%
재산세 5
12.5%
주민세 5
12.5%
취득세 5
12.5%
자동차세 5
12.5%
등록면허세 5
12.5%
지역자원시설세 5
12.5%

과세년도
Categorical

Distinct5
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size448.0 B
2017
8 
2018
8 
2019
8 
2020
8 
2021
8 

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
20.0%
2018 8
20.0%
2019 8
20.0%
2020 8
20.0%
2021 8
20.0%

Length

2024-03-14T22:59:06.719583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:59:07.027227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 8
20.0%
2018 8
20.0%
2019 8
20.0%
2020 8
20.0%
2021 8
20.0%

비과세금액
Text

MISSING 

Distinct32
Distinct (%)94.1%
Missing6
Missing (%)15.0%
Memory size448.0 B
2024-03-14T22:59:07.710024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.5
Min length1

Characters and Unicode

Total characters255
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)91.2%

Sample

1st row0
2nd row4104548000
3rd row94722000
4th row842434000
5th row23628000
ValueCountFrequency (%)
0 3
 
9.1%
73507000 1
 
3.0%
5674000 1
 
3.0%
24331000 1
 
3.0%
951334000 1
 
3.0%
3253000 1
 
3.0%
4443648000 1
 
3.0%
25142000 1
 
3.0%
15862000 1
 
3.0%
25748000 1
 
3.0%
Other values (21) 21
63.6%
2024-03-14T22:59:08.627929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 108
42.4%
3 23
 
9.0%
4 21
 
8.2%
5 19
 
7.5%
2 19
 
7.5%
6 14
 
5.5%
1 13
 
5.1%
7 13
 
5.1%
8 12
 
4.7%
9 11
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 253
99.2%
Space Separator 2
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 108
42.7%
3 23
 
9.1%
4 21
 
8.3%
5 19
 
7.5%
2 19
 
7.5%
6 14
 
5.5%
1 13
 
5.1%
7 13
 
5.1%
8 12
 
4.7%
9 11
 
4.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 255
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 108
42.4%
3 23
 
9.0%
4 21
 
8.2%
5 19
 
7.5%
2 19
 
7.5%
6 14
 
5.5%
1 13
 
5.1%
7 13
 
5.1%
8 12
 
4.7%
9 11
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 255
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 108
42.4%
3 23
 
9.0%
4 21
 
8.2%
5 19
 
7.5%
2 19
 
7.5%
6 14
 
5.5%
1 13
 
5.1%
7 13
 
5.1%
8 12
 
4.7%
9 11
 
4.3%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4152738 × 108
Minimum10000
Maximum1.724862 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size488.0 B
2024-03-14T22:59:09.028584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile239950
Q15356500
median43281500
Q31.67754 × 108
95-th percentile1.3392112 × 109
Maximum1.724862 × 109
Range1.724852 × 109
Interquartile range (IQR)1.623975 × 108

Descriptive statistics

Standard deviation4.5018844 × 108
Coefficient of variation (CV)1.8639231
Kurtosis3.9149922
Mean2.4152738 × 108
Median Absolute Deviation (MAD)42894000
Skewness2.2421942
Sum9.661095 × 109
Variance2.0266964 × 1017
MonotonicityNot monotonic
2024-03-14T22:59:09.456104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
244000 1
 
2.5%
134006000 1
 
2.5%
19812000 1
 
2.5%
879000 1
 
2.5%
1176000 1
 
2.5%
387781000 1
 
2.5%
7200000 1
 
2.5%
1228265000 1
 
2.5%
119968000 1
 
2.5%
39574000 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
10000 1
2.5%
163000 1
2.5%
244000 1
2.5%
255000 1
2.5%
520000 1
2.5%
559000 1
2.5%
721000 1
2.5%
879000 1
2.5%
993000 1
2.5%
1176000 1
2.5%
ValueCountFrequency (%)
1724862000 1
2.5%
1425476000 1
2.5%
1334671000 1
2.5%
1228265000 1
2.5%
1116159000 1
2.5%
411838000 1
2.5%
387781000 1
2.5%
335004000 1
2.5%
287130000 1
2.5%
267423000 1
2.5%

부과금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct37
Distinct (%)94.9%
Missing1
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean4.6250211 × 109
Minimum0
Maximum2.7804623 × 1010
Zeros3
Zeros (%)7.5%
Negative0
Negative (%)0.0%
Memory size488.0 B
2024-03-14T22:59:09.846805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.88133 × 108
median3.184413 × 109
Q34.7746075 × 109
95-th percentile1.9747939 × 1010
Maximum2.7804623 × 1010
Range2.7804623 × 1010
Interquartile range (IQR)3.9864745 × 109

Descriptive statistics

Standard deviation6.5500368 × 109
Coefficient of variation (CV)1.4162177
Kurtosis4.5918037
Mean4.6250211 × 109
Median Absolute Deviation (MAD)2.315583 × 109
Skewness2.251392
Sum1.8037582 × 1011
Variance4.2902982 × 1019
MonotonicityNot monotonic
2024-03-14T22:59:10.244998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 3
 
7.5%
3913893000 1
 
2.5%
1237077000 1
 
2.5%
868830000 1
 
2.5%
4562337000 1
 
2.5%
13882000 1
 
2.5%
4883584000 1
 
2.5%
644087000 1
 
2.5%
21902918000 1
 
2.5%
4098817000 1
 
2.5%
Other values (27) 27
67.5%
ValueCountFrequency (%)
0 3
7.5%
13882000 1
 
2.5%
532895000 1
 
2.5%
570884000 1
 
2.5%
604189000 1
 
2.5%
606264000 1
 
2.5%
644087000 1
 
2.5%
786849000 1
 
2.5%
789417000 1
 
2.5%
825345000 1
 
2.5%
ValueCountFrequency (%)
27804623000 1
2.5%
21902918000 1
2.5%
19508497000 1
2.5%
17267159000 1
2.5%
14900426000 1
2.5%
5597492000 1
2.5%
5587142000 1
2.5%
5377439000 1
2.5%
5076416000 1
2.5%
4883584000 1
2.5%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct32
Distinct (%)82.1%
Missing1
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean17.855128
Minimum0
Maximum97.99
Zeros5
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size488.0 B
2024-03-14T22:59:10.639934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.75
median6.92
Q311.535
95-th percentile94.075
Maximum97.99
Range97.99
Interquartile range (IQR)7.785

Descriptive statistics

Standard deviation29.768806
Coefficient of variation (CV)1.6672412
Kurtosis3.2092203
Mean17.855128
Median Absolute Deviation (MAD)4.26
Skewness2.1789761
Sum696.35
Variance886.18183
MonotonicityNot monotonic
2024-03-14T22:59:11.036822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.0 5
 
12.5%
10.64 2
 
5.0%
10.0 2
 
5.0%
0.01 2
 
5.0%
3.9 1
 
2.5%
9.6 1
 
2.5%
17.9 1
 
2.5%
4.0 1
 
2.5%
4.66 1
 
2.5%
4.5 1
 
2.5%
Other values (22) 22
55.0%
ValueCountFrequency (%)
0.0 5
12.5%
0.01 2
 
5.0%
0.02 1
 
2.5%
1.6 1
 
2.5%
3.6 1
 
2.5%
3.9 1
 
2.5%
4.0 1
 
2.5%
4.5 1
 
2.5%
4.52 1
 
2.5%
4.66 1
 
2.5%
ValueCountFrequency (%)
97.99 1
2.5%
97.36 1
2.5%
93.71 1
2.5%
89.7 1
2.5%
86.7 1
2.5%
21.86 1
2.5%
19.04 1
2.5%
17.9 1
2.5%
13.14 1
2.5%
11.89 1
2.5%

Interactions

2024-03-14T22:59:02.579962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:59:01.060575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:59:01.833388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:59:02.791205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:59:01.326159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:59:02.094277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:59:02.932999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:59:01.582544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:59:02.339270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T22:59:11.287942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0001.0000.6620.7260.750
과세년도0.0001.0000.7150.0000.0000.000
비과세금액1.0000.7151.0001.0001.0001.000
감면금액0.6620.0001.0001.0000.9890.678
부과금액0.7260.0001.0000.9891.0000.503
비과세감면율0.7500.0001.0000.6780.5031.000
2024-03-14T22:59:11.558188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2024-03-14T22:59:12.003276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
감면금액부과금액비과세감면율세목명과세년도
감면금액1.0000.6790.6070.4260.000
부과금액0.6791.0000.2220.4880.000
비과세감면율0.6070.2221.0000.5590.000
세목명0.4260.4880.5591.0000.000
과세년도0.0000.0000.0000.0001.000

Missing values

2024-03-14T22:59:03.130285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:59:03.558978image/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.
2024-03-14T22:59:03.877402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
0강원도양양군42830교육세2017024400039138930000.01
1강원도양양군42830등록세2017<NA>55900000.0
2강원도양양군42830재산세20174104548000267423000466563100093.71
3강원도양양군42830주민세201794722000675000053289500019.04
4강원도양양군42830취득세201784243400011161590001490042600013.14
5강원도양양군42830자동차세20172362800013259700033212090004.7
6강원도양양군42830등록면허세20177918000491610008253450006.92
7강원도양양군42830지역자원시설세2017625700002143700078941700010.64
8강원도양양군42830교육세2018052000040914570000.01
9강원도양양군42830등록세2018<NA>1000000.0
시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
30강원도양양군42830등록면허세2020158620003957400012370770004.5
31강원도양양군42830지역자원시설세2020735070002035500093623300010.0
32강원도양양군42830교육세2021<NA>99300053774390000.0
33강원도양양군42830등록세2021255000<NA><NA>
34강원도양양군42830재산세20214443648000411838000559749200086.7
35강원도양양군42830주민세2021325300010516500060418900017.9
36강원도양양군42830취득세20219513340001724862000278046230009.6
37강원도양양군42830자동차세20212433100012042800036814830003.9
38강원도양양군42830등록면허세202156740005561100015382130004.0
39강원도양양군42830지역자원시설세2021849050002077700097517200010.8