Overview

Dataset statistics

Number of variables10
Number of observations153
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.8 KiB
Average record size in memory85.9 B

Variable types

Numeric4
Categorical4
Text1
DateTime1

Dataset

Description3개년도(2020~2022) 강원도 동해시 세원 유형별 과세 현황에 대한 데이터로 지방세 세원이 되는 과세물건 유형별 부과된 현황을 제공합니다.
URLhttps://www.data.go.kr/data/15079788/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
데이터기준일 has constant value ""Constant
순번 is highly overall correlated with 자치단체코드 and 1 other fieldsHigh correlation
자치단체코드 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
부과건수 is highly overall correlated with 부과금액(원) and 1 other fieldsHigh correlation
부과금액(원) is highly overall correlated with 부과건수High correlation
과세년도 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
세목명 is highly overall correlated with 부과건수High correlation
순번 has unique valuesUnique
부과건수 has 9 (5.9%) zerosZeros
부과금액(원) has 9 (5.9%) zerosZeros

Reproduction

Analysis started2023-12-12 08:07:40.145776
Analysis finished2023-12-12 08:07:42.743510
Duration2.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77
Minimum1
Maximum153
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T17:07:42.825534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.6
Q139
median77
Q3115
95-th percentile145.4
Maximum153
Range152
Interquartile range (IQR)76

Descriptive statistics

Standard deviation44.311398
Coefficient of variation (CV)0.5754727
Kurtosis-1.2
Mean77
Median Absolute Deviation (MAD)38
Skewness0
Sum11781
Variance1963.5
MonotonicityStrictly increasing
2023-12-12T17:07:43.031873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
106 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
105 1
 
0.7%
107 1
 
0.7%
Other values (143) 143
93.5%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
153 1
0.7%
152 1
0.7%
151 1
0.7%
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
강원특별자치도
153 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원특별자치도 153
100.0%

Length

2023-12-12T17:07:43.237310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:07:43.450107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원특별자치도 153
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
동해시
153 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동해시 153
100.0%

Length

2023-12-12T17:07:43.608703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:07:43.732485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동해시 153
100.0%

자치단체코드
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44876.065
Minimum42170
Maximum51170
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T17:07:43.854128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42170
5-th percentile42170
Q142170
median42170
Q351170
95-th percentile51170
Maximum51170
Range9000
Interquartile range (IQR)9000

Descriptive statistics

Standard deviation4140.3131
Coefficient of variation (CV)0.092261055
Kurtosis-1.2453733
Mean44876.065
Median Absolute Deviation (MAD)0
Skewness0.87811119
Sum6866038
Variance17142193
MonotonicityIncreasing
2023-12-12T17:07:43.991043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
42170 100
65.4%
51170 46
30.1%
42171 1
 
0.7%
42172 1
 
0.7%
42173 1
 
0.7%
42174 1
 
0.7%
42175 1
 
0.7%
42176 1
 
0.7%
42177 1
 
0.7%
ValueCountFrequency (%)
42170 100
65.4%
42171 1
 
0.7%
42172 1
 
0.7%
42173 1
 
0.7%
42174 1
 
0.7%
42175 1
 
0.7%
42176 1
 
0.7%
42177 1
 
0.7%
51170 46
30.1%
ValueCountFrequency (%)
51170 46
30.1%
42177 1
 
0.7%
42176 1
 
0.7%
42175 1
 
0.7%
42174 1
 
0.7%
42173 1
 
0.7%
42172 1
 
0.7%
42171 1
 
0.7%
42170 100
65.4%

과세년도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2021
54 
2020
53 
2022
46 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2021 54
35.3%
2020 53
34.6%
2022 46
30.1%

Length

2023-12-12T17:07:44.169319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:07:44.299422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 54
35.3%
2020 53
34.6%
2022 46
30.1%

세목명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
등록면허세
30 
취득세
23 
자동차세
21 
주민세
14 
지역자원시설세
13 
Other values (9)
52 

Length

Max length7
Median length5
Mean length4.254902
Min length2

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
등록면허세 30
19.6%
취득세 23
15.0%
자동차세 21
13.7%
주민세 14
9.2%
지역자원시설세 13
8.5%
재산세 13
8.5%
지방교육세 12
 
7.8%
지방소득세 12
 
7.8%
레저세 4
 
2.6%
지방소비세 3
 
2.0%
Other values (4) 8
 
5.2%

Length

2023-12-12T17:07:44.457623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록면허세 30
19.6%
취득세 23
15.0%
자동차세 21
13.7%
주민세 14
9.2%
지역자원시설세 13
8.5%
재산세 13
8.5%
지방교육세 12
 
7.8%
지방소득세 12
 
7.8%
레저세 4
 
2.6%
지방소비세 3
 
2.0%
Other values (4) 8
 
5.2%

세원 유형명
Text

Distinct90
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T17:07:44.770258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length5.248366
Min length2

Characters and Unicode

Total characters803
Distinct characters113
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)28.1%

Sample

1st row토지
2nd row일반건출물
3rd row주택
4th row차량
5th row기계장비
ValueCountFrequency (%)
토지 5
 
3.3%
선박 5
 
3.3%
담배소비세 5
 
3.3%
주택 4
 
2.6%
건축물 3
 
2.0%
기계장비 3
 
2.0%
차량 3
 
2.0%
지방소비세 3
 
2.0%
체납 3
 
2.0%
그밖의승용자동차 2
 
1.3%
Other values (80) 117
76.5%
2023-12-12T17:07:45.342018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 43
 
5.4%
등 30
 
3.7%
소 29
 
3.6%
( 28
 
3.5%
) 28
 
3.5%
자 23
 
2.9%
주 23
 
2.9%
기 22
 
2.7%
동 21
 
2.6%
차 20
 
2.5%
Other values (103) 536
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 728
90.7%
Open Punctuation 28
 
3.5%
Close Punctuation 28
 
3.5%
Other Punctuation 16
 
2.0%
Decimal Number 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 43
 
5.9%
등 30
 
4.1%
소 29
 
4.0%
자 23
 
3.2%
주 23
 
3.2%
기 22
 
3.0%
동 21
 
2.9%
차 20
 
2.7%
지 20
 
2.7%
득 19
 
2.6%
Other values (98) 478
65.7%
Other Punctuation
ValueCountFrequency (%)
, 14
87.5%
. 2
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Decimal Number
ValueCountFrequency (%)
3 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 728
90.7%
Common 75
 
9.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 43
 
5.9%
등 30
 
4.1%
소 29
 
4.0%
자 23
 
3.2%
주 23
 
3.2%
기 22
 
3.0%
동 21
 
2.9%
차 20
 
2.7%
지 20
 
2.7%
득 19
 
2.6%
Other values (98) 478
65.7%
Common
ValueCountFrequency (%)
( 28
37.3%
) 28
37.3%
, 14
18.7%
3 3
 
4.0%
. 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 728
90.7%
ASCII 75
 
9.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 43
 
5.9%
등 30
 
4.1%
소 29
 
4.0%
자 23
 
3.2%
주 23
 
3.2%
기 22
 
3.0%
동 21
 
2.9%
차 20
 
2.7%
지 20
 
2.7%
득 19
 
2.6%
Other values (98) 478
65.7%
ASCII
ValueCountFrequency (%)
( 28
37.3%
) 28
37.3%
, 14
18.7%
3 3
 
4.0%
. 2
 
2.7%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct124
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9419.2288
Minimum0
Maximum177105
Zeros9
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T17:07:45.560106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112
median622
Q39062
95-th percentile58430
Maximum177105
Range177105
Interquartile range (IQR)9050

Descriptive statistics

Standard deviation20843.994
Coefficient of variation (CV)2.2129194
Kurtosis28.010091
Mean9419.2288
Median Absolute Deviation (MAD)621
Skewness4.403553
Sum1441142
Variance4.3447207 × 108
MonotonicityNot monotonic
2023-12-12T17:07:45.775324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
5.9%
12 6
 
3.9%
2 5
 
3.3%
4 4
 
2.6%
5 3
 
2.0%
9 3
 
2.0%
1 3
 
2.0%
26 2
 
1.3%
3 2
 
1.3%
8 2
 
1.3%
Other values (114) 114
74.5%
ValueCountFrequency (%)
0 9
5.9%
1 3
 
2.0%
2 5
3.3%
3 2
 
1.3%
4 4
2.6%
5 3
 
2.0%
6 1
 
0.7%
8 2
 
1.3%
9 3
 
2.0%
11 1
 
0.7%
ValueCountFrequency (%)
177105 1
0.7%
67846 1
0.7%
67202 1
0.7%
60797 1
0.7%
60050 1
0.7%
59343 1
0.7%
59059 1
0.7%
58892 1
0.7%
58122 1
0.7%
41847 1
0.7%

부과금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct143
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9099323 × 109
Minimum0
Maximum1.4410738 × 1010
Zeros9
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T17:07:46.013043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q118819000
median3.44237 × 108
Q33.173122 × 109
95-th percentile7.5098294 × 109
Maximum1.4410738 × 1010
Range1.4410738 × 1010
Interquartile range (IQR)3.154303 × 109

Descriptive statistics

Standard deviation2.6490118 × 109
Coefficient of variation (CV)1.3869664
Kurtosis2.8071798
Mean1.9099323 × 109
Median Absolute Deviation (MAD)3.44237 × 108
Skewness1.6504569
Sum2.9221964 × 1011
Variance7.0172638 × 1018
MonotonicityNot monotonic
2023-12-12T17:07:46.549498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
5.9%
1044000 2
 
1.3%
90000 2
 
1.3%
90172000 1
 
0.7%
3099071000 1
 
0.7%
3424399000 1
 
0.7%
63629000 1
 
0.7%
8046091000 1
 
0.7%
14934000 1
 
0.7%
237206000 1
 
0.7%
Other values (133) 133
86.9%
ValueCountFrequency (%)
0 9
5.9%
13000 1
 
0.7%
22000 1
 
0.7%
35000 1
 
0.7%
47000 1
 
0.7%
80000 1
 
0.7%
90000 2
 
1.3%
101000 1
 
0.7%
203000 1
 
0.7%
241000 1
 
0.7%
ValueCountFrequency (%)
14410738000 1
0.7%
8482090000 1
0.7%
8109143000 1
0.7%
8080903000 1
0.7%
8046091000 1
0.7%
7795439000 1
0.7%
7568748000 1
0.7%
7527605000 1
0.7%
7497979000 1
0.7%
7478981000 1
0.7%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2023-07-04 00:00:00
Maximum2023-07-04 00:00:00
2023-12-12T17:07:46.709201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:46.843287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T17:07:42.013631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:40.610656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:41.145525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:41.549905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:42.157654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:40.759778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:41.258205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:41.684465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:42.260013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:40.867917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:41.350745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:41.791190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:42.390626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:41.007433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:41.454563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:41.888942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:07:46.975012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번자치단체코드과세년도세목명세원 유형명부과건수부과금액(원)
순번1.0001.0000.9610.7830.0000.1730.237
자치단체코드1.0001.0000.9910.4370.0000.0000.000
과세년도0.9610.9911.0000.2500.0000.0000.000
세목명0.7830.4370.2501.0000.9940.8400.762
세원 유형명0.0000.0000.0000.9941.0000.9860.872
부과건수0.1730.0000.0000.8400.9861.0000.362
부과금액(원)0.2370.0000.0000.7620.8720.3621.000
2023-12-12T17:07:47.132899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.135
세목명0.1351.000
2023-12-12T17:07:47.270609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번자치단체코드부과건수부과금액(원)과세년도세목명
순번1.0000.8330.0080.0130.9390.449
자치단체코드0.8331.000-0.0350.0280.9970.347
부과건수0.008-0.0351.0000.6410.0000.618
부과금액(원)0.0130.0280.6411.0000.0000.380
과세년도0.9390.9970.0000.0001.0000.135
세목명0.4490.3470.6180.3800.1351.000

Missing values

2023-12-12T17:07:42.543073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:07:42.679428image/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

순번시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액(원)데이터기준일
01강원특별자치도동해시421702020취득세토지197445640390002023-07-04
12강원특별자치도동해시421702020취득세일반건출물61848087850002023-07-04
23강원특별자치도동해시421702020취득세주택3959144107380002023-07-04
34강원특별자치도동해시421702020취득세차량740475276050002023-07-04
45강원특별자치도동해시421702020취득세기계장비5449812540002023-07-04
56강원특별자치도동해시421702020취득세선박682290660002023-07-04
67강원특별자치도동해시421702020취득세과점주주의취득분263729100002023-07-04
78강원특별자치도동해시421702020등록면허세부동산등기926712671440002023-07-04
89강원특별자치도동해시421702020등록면허세선박등기28133130002023-07-04
910강원특별자치도동해시421702020등록면허세자동차등록83771761970002023-07-04
순번시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액(원)데이터기준일
143144강원특별자치도동해시511702022주민세주민세(특별징수)002023-07-04
144145강원특별자치도동해시511702022주민세주민세(법인세분)002023-07-04
145146강원특별자치도동해시511702022주민세주민세(양도소득)002023-07-04
146147강원특별자치도동해시511702022주민세주민세(종합소득)002023-07-04
147148강원특별자치도동해시511702022등록면허세등록면허세(면허)140593130760002023-07-04
148149강원특별자치도동해시511702022등록면허세등록면허세(등록)1635813155710002023-07-04
149150강원특별자치도동해시511702022지역자원시설세지역자원시설세(소방)3298624277920002023-07-04
150151강원특별자치도동해시511702022지역자원시설세지역자원시설세(시설)3327374160002023-07-04
151152강원특별자치도동해시511702022지역자원시설세지역자원시설세(특자)3472568200002023-07-04
152153강원특별자치도동해시511702022체납체납6079737512670002023-07-04