Overview

Dataset statistics

Number of variables10
Number of observations49
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory88.7 B

Variable types

Categorical6
Numeric4

Dataset

Description강원도 춘천시의 연도별 지방세 과세 및 비과세 현황으로, 시도명, 시군구명, 자치단체코드, 과세년도, 세목명, 과세건수, 과세금액, 비과세건수, 비과세금액, 데이터기준일에 대한 자료를 제공
Author강원도 춘천시
URLhttps://www.data.go.kr/data/15079753/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
과세건수 is highly overall correlated with 과세금액 and 3 other fieldsHigh correlation
과세금액 is highly overall correlated with 과세건수 and 1 other fieldsHigh correlation
비과세건수 is highly overall correlated with 과세건수 and 2 other fieldsHigh correlation
비과세금액 is highly overall correlated with 과세건수 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 과세건수 and 3 other fieldsHigh correlation
과세건수 has 12 (24.5%) zerosZeros
과세금액 has 12 (24.5%) zerosZeros
비과세건수 has 17 (34.7%) zerosZeros
비과세금액 has 17 (34.7%) zerosZeros

Reproduction

Analysis started2023-12-12 13:16:56.775672
Analysis finished2023-12-12 13:16:59.242263
Duration2.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
강원도
49 

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 49
100.0%

Length

2023-12-12T22:16:59.303236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:16:59.391926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 49
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
춘천시
49 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
춘천시 49
100.0%

Length

2023-12-12T22:16:59.482545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:16:59.566928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
춘천시 49
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
42110
49 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row42110
2nd row42110
3rd row42110
4th row42110
5th row42110

Common Values

ValueCountFrequency (%)
42110 49
100.0%

Length

2023-12-12T22:16:59.657297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:16:59.736040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
42110 49
100.0%

과세년도
Categorical

Distinct4
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size524.0 B
2018
13 
2019
13 
2020
13 
2017
10 

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 (%)
2018 13
26.5%
2019 13
26.5%
2020 13
26.5%
2017 10
20.4%

Length

2023-12-12T22:16:59.861262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:16:59.964604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 13
26.5%
2019 13
26.5%
2020 13
26.5%
2017 10
20.4%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Memory size524.0 B
취득세
4 
등록세
4 
주민세
4 
재산세
4 
자동차세
4 
Other values (8)
29 

Length

Max length7
Median length5
Mean length4.1428571
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 4
8.2%
등록세 4
8.2%
주민세 4
8.2%
재산세 4
8.2%
자동차세 4
8.2%
담배소비세 4
8.2%
등록면허세 4
8.2%
지역자원시설세 4
8.2%
지방소득세 4
8.2%
교육세 4
8.2%
Other values (3) 9
18.4%

Length

2023-12-12T22:17:00.130670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 4
8.2%
등록세 4
8.2%
주민세 4
8.2%
재산세 4
8.2%
자동차세 4
8.2%
담배소비세 4
8.2%
등록면허세 4
8.2%
지역자원시설세 4
8.2%
지방소득세 4
8.2%
교육세 4
8.2%
Other values (3) 9
18.4%

과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean119011.82
Minimum0
Maximum581646
Zeros12
Zeros (%)24.5%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T22:17:00.267241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median89370
Q3141601
95-th percentile560208.6
Maximum581646
Range581646
Interquartile range (IQR)141595

Descriptive statistics

Standard deviation155075.68
Coefficient of variation (CV)1.3030276
Kurtosis3.7751801
Mean119011.82
Median Absolute Deviation (MAD)89364
Skewness2.0031352
Sum5831579
Variance2.4048466 × 1010
MonotonicityNot monotonic
2023-12-12T22:17:00.448710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 12
24.5%
119969 1
 
2.0%
218160 1
 
2.0%
205854 1
 
2.0%
89 1
 
2.0%
97549 1
 
2.0%
119117 1
 
2.0%
84268 1
 
2.0%
562065 1
 
2.0%
46203 1
 
2.0%
Other values (28) 28
57.1%
ValueCountFrequency (%)
0 12
24.5%
6 1
 
2.0%
89 1
 
2.0%
102 1
 
2.0%
107 1
 
2.0%
274 1
 
2.0%
39914 1
 
2.0%
40604 1
 
2.0%
40847 1
 
2.0%
46203 1
 
2.0%
ValueCountFrequency (%)
581646 1
2.0%
580575 1
2.0%
562065 1
2.0%
557424 1
2.0%
225319 1
2.0%
218160 1
2.0%
211274 1
2.0%
210572 1
2.0%
205854 1
2.0%
204939 1
2.0%

과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.593579 × 1010
Minimum0
Maximum1.1327037 × 1011
Zeros12
Zeros (%)24.5%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T22:17:00.604760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.41476 × 109
median7.993101 × 109
Q34.5939855 × 1010
95-th percentile8.9355581 × 1010
Maximum1.1327037 × 1011
Range1.1327037 × 1011
Interquartile range (IQR)4.0525095 × 1010

Descriptive statistics

Standard deviation2.9590018 × 1010
Coefficient of variation (CV)1.1408952
Kurtosis1.20053
Mean2.593579 × 1010
Median Absolute Deviation (MAD)7.993101 × 109
Skewness1.3024913
Sum1.2708537 × 1012
Variance8.7556914 × 1020
MonotonicityNot monotonic
2023-12-12T22:17:00.784761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 12
24.5%
6101778000 1
 
2.0%
48210553000 1
 
2.0%
50968243000 1
 
2.0%
18452323000 1
 
2.0%
5824361000 1
 
2.0%
7557421000 1
 
2.0%
55843719000 1
 
2.0%
28891633000 1
 
2.0%
113270368000 1
 
2.0%
Other values (28) 28
57.1%
ValueCountFrequency (%)
0 12
24.5%
5414760000 1
 
2.0%
5622919000 1
 
2.0%
5712509000 1
 
2.0%
5824361000 1
 
2.0%
5841858000 1
 
2.0%
6101778000 1
 
2.0%
6319197000 1
 
2.0%
7557421000 1
 
2.0%
7752000000 1
 
2.0%
ValueCountFrequency (%)
113270368000 1
2.0%
105903866000 1
2.0%
93307049000 1
2.0%
83428379000 1
2.0%
59852333000 1
2.0%
55881600000 1
2.0%
55843719000 1
2.0%
51126231000 1
2.0%
50968243000 1
2.0%
50537098000 1
2.0%

비과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9269.0612
Minimum0
Maximum53917
Zeros17
Zeros (%)34.7%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T22:17:00.945260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3595
Q311447
95-th percentile41920.4
Maximum53917
Range53917
Interquartile range (IQR)11447

Descriptive statistics

Standard deviation13990.934
Coefficient of variation (CV)1.509423
Kurtosis3.1584631
Mean9269.0612
Median Absolute Deviation (MAD)3595
Skewness1.877451
Sum454184
Variance1.9574623 × 108
MonotonicityNot monotonic
2023-12-12T22:17:01.117857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 17
34.7%
10049 1
 
2.0%
7 1
 
2.0%
50326 1
 
2.0%
25131 1
 
2.0%
5079 1
 
2.0%
5216 1
 
2.0%
70 1
 
2.0%
11447 1
 
2.0%
21503 1
 
2.0%
Other values (23) 23
46.9%
ValueCountFrequency (%)
0 17
34.7%
6 1
 
2.0%
7 1
 
2.0%
12 1
 
2.0%
21 1
 
2.0%
61 1
 
2.0%
70 1
 
2.0%
95 1
 
2.0%
3595 1
 
2.0%
4136 1
 
2.0%
ValueCountFrequency (%)
53917 1
2.0%
50326 1
2.0%
50284 1
2.0%
29375 1
2.0%
28219 1
2.0%
25131 1
2.0%
24509 1
2.0%
22460 1
2.0%
21503 1
2.0%
21325 1
2.0%

비과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)65.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.054507 × 109
Minimum0
Maximum3.7382413 × 1010
Zeros17
Zeros (%)34.7%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T22:17:01.262421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.37302 × 108
Q31.269261 × 109
95-th percentile3.302991 × 1010
Maximum3.7382413 × 1010
Range3.7382413 × 1010
Interquartile range (IQR)1.269261 × 109

Descriptive statistics

Standard deviation1.0408686 × 1010
Coefficient of variation (CV)2.0592882
Kurtosis3.5880669
Mean5.054507 × 109
Median Absolute Deviation (MAD)2.37302 × 108
Skewness2.1869388
Sum2.4767084 × 1011
Variance1.0834075 × 1020
MonotonicityNot monotonic
2023-12-12T22:17:01.425472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 17
34.7%
5000 2
 
4.1%
9022000 1
 
2.0%
5207006000 1
 
2.0%
35719619000 1
 
2.0%
1207399000 1
 
2.0%
237302000 1
 
2.0%
1069400000 1
 
2.0%
16810894000 1
 
2.0%
5625031000 1
 
2.0%
Other values (22) 22
44.9%
ValueCountFrequency (%)
0 17
34.7%
5000 2
 
4.1%
7000 1
 
2.0%
3329000 1
 
2.0%
3559000 1
 
2.0%
3647000 1
 
2.0%
9022000 1
 
2.0%
237302000 1
 
2.0%
246762000 1
 
2.0%
262460000 1
 
2.0%
ValueCountFrequency (%)
37382413000 1
2.0%
35719619000 1
2.0%
33870876000 1
2.0%
31768462000 1
2.0%
20845484000 1
2.0%
20834720000 1
2.0%
18711680000 1
2.0%
16810894000 1
2.0%
5625031000 1
2.0%
5207006000 1
2.0%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2022-06-20
49 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-06-20
2nd row2022-06-20
3rd row2022-06-20
4th row2022-06-20
5th row2022-06-20

Common Values

ValueCountFrequency (%)
2022-06-20 49
100.0%

Length

2023-12-12T22:17:01.581279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:17:01.685630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-06-20 49
100.0%

Interactions

2023-12-12T22:16:58.289542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:57.098942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:57.498446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:57.913963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:58.388844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:57.205679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:57.602128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:58.004259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:58.492159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:57.297315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:57.703971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:58.106185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:58.589482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:57.391695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:57.807867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:58.196706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:17:01.757045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명과세건수과세금액비과세건수비과세금액
과세년도1.0000.0000.0000.0000.0000.000
세목명0.0001.0000.9680.8740.8230.878
과세건수0.0000.9681.0000.8160.6040.496
과세금액0.0000.8740.8161.0000.6530.776
비과세건수0.0000.8230.6040.6531.0000.887
비과세금액0.0000.8780.4960.7760.8871.000
2023-12-12T22:17:01.860353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2023-12-12T22:17:01.982909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세건수과세금액비과세건수비과세금액과세년도세목명
과세건수1.0000.5530.7380.5710.0000.842
과세금액0.5531.0000.4310.4050.0000.594
비과세건수0.7380.4311.0000.9420.0000.524
비과세금액0.5710.4050.9421.0000.0000.625
과세년도0.0000.0000.0000.0001.0000.000
세목명0.8420.5940.5240.6250.0001.000

Missing values

2023-12-12T22:16:59.046194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:16:59.189517image/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

시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액데이터기준일
0강원도춘천시421102017취득세399148342837900010049187116800002022-06-20
1강원도춘천시421102017등록세00633290002022-06-20
2강원도춘천시421102017주민세1223355414760000897450298070002022-06-20
3강원도춘천시421102017재산세2049394341567900029375317684620002022-06-20
4강원도춘천시421102017자동차세198024459398550001513612692610002022-06-20
5강원도춘천시421102017담배소비세10719425801000002022-06-20
6강원도춘천시421102017등록면허세98098562291900035952624600002022-06-20
7강원도춘천시421102017지역자원시설세1416017803269000608910253810002022-06-20
8강원도춘천시421102017지방소득세7168446605484000002022-06-20
9강원도춘천시421102017교육세580575271660340002246036470002022-06-20
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