Overview

Dataset statistics

Number of variables9
Number of observations68
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory79.9 B

Variable types

Categorical4
Numeric5

Dataset

Description부산광역시 동래구 지방세 과세 현황(2017년~2022년) 데이터로 자치단체코드, 과세년도, 세목명, 과세건수, 과세금액, 비과세건수, 비과세금액에 대한 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15086944/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세건수 is highly overall correlated with 과세금액 and 3 other fieldsHigh correlation
과세금액 is highly overall correlated with 과세건수 and 2 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 과세건수High correlation
과세건수 has 16 (23.5%) zerosZeros
과세금액 has 16 (23.5%) zerosZeros
비과세건수 has 26 (38.2%) zerosZeros
비과세금액 has 27 (39.7%) zerosZeros

Reproduction

Analysis started2023-12-12 10:47:04.429006
Analysis finished2023-12-12 10:47:08.919836
Duration4.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
부산광역시
68 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 68
100.0%

Length

2023-12-12T19:47:09.045830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:47:09.180053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 68
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
동래구
68 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동래구 68
100.0%

Length

2023-12-12T19:47:09.331942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:47:09.466232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동래구 68
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
26260
68 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26260
2nd row26260
3rd row26260
4th row26260
5th row26260

Common Values

ValueCountFrequency (%)
26260 68
100.0%

Length

2023-12-12T19:47:09.605278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:47:09.754467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26260 68
100.0%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.6471
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-12T19:47:09.890326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2020
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.6550664
Coefficient of variation (CV)0.00081948301
Kurtosis-1.1999082
Mean2019.6471
Median Absolute Deviation (MAD)1
Skewness-0.063378183
Sum137336
Variance2.739245
MonotonicityIncreasing
2023-12-12T19:47:10.071075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2018 12
17.6%
2019 12
17.6%
2020 12
17.6%
2021 12
17.6%
2022 12
17.6%
2017 8
11.8%
ValueCountFrequency (%)
2017 8
11.8%
2018 12
17.6%
2019 12
17.6%
2020 12
17.6%
2021 12
17.6%
2022 12
17.6%
ValueCountFrequency (%)
2022 12
17.6%
2021 12
17.6%
2020 12
17.6%
2019 12
17.6%
2018 12
17.6%
2017 8
11.8%

세목명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size676.0 B
취득세
6 
주민세
6 
재산세
6 
자동차세
6 
등록면허세
6 
Other values (7)
38 

Length

Max length7
Median length5
Mean length4.2352941
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 6
8.8%
주민세 6
8.8%
재산세 6
8.8%
자동차세 6
8.8%
등록면허세 6
8.8%
지역자원시설세 6
8.8%
지방소득세 6
8.8%
교육세 6
8.8%
레저세 5
7.4%
담배소비세 5
7.4%
Other values (2) 10
14.7%

Length

2023-12-12T19:47:10.270539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 6
8.8%
주민세 6
8.8%
재산세 6
8.8%
자동차세 6
8.8%
등록면허세 6
8.8%
지역자원시설세 6
8.8%
지방소득세 6
8.8%
교육세 6
8.8%
레저세 5
7.4%
담배소비세 5
7.4%
Other values (2) 10
14.7%

과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct53
Distinct (%)77.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113385.25
Minimum0
Maximum557292
Zeros16
Zeros (%)23.5%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-12T19:47:10.464490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.75
median77427.5
Q3149100.75
95-th percentile523462.5
Maximum557292
Range557292
Interquartile range (IQR)149094

Descriptive statistics

Standard deviation146262.35
Coefficient of variation (CV)1.2899593
Kurtosis3.7022412
Mean113385.25
Median Absolute Deviation (MAD)73255
Skewness2.0230867
Sum7710197
Variance2.1392676 × 1010
MonotonicityNot monotonic
2023-12-12T19:47:10.661095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16
 
23.5%
12358 1
 
1.5%
92173 1
 
1.5%
79913 1
 
1.5%
184825 1
 
1.5%
80116 1
 
1.5%
548032 1
 
1.5%
12740 1
 
1.5%
115438 1
 
1.5%
150535 1
 
1.5%
Other values (43) 43
63.2%
ValueCountFrequency (%)
0 16
23.5%
6 1
 
1.5%
7 1
 
1.5%
9 1
 
1.5%
45 1
 
1.5%
10626 1
 
1.5%
12358 1
 
1.5%
12740 1
 
1.5%
13462 1
 
1.5%
14192 1
 
1.5%
ValueCountFrequency (%)
557292 1
1.5%
548032 1
1.5%
536630 1
1.5%
527855 1
1.5%
515305 1
1.5%
512956 1
1.5%
198845 1
1.5%
187623 1
1.5%
184825 1
1.5%
174937 1
1.5%

과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct53
Distinct (%)77.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1663006 × 1010
Minimum0
Maximum1.1608308 × 1011
Zeros16
Zeros (%)23.5%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-12T19:47:10.878947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.9184515 × 109
median7.0346065 × 109
Q33.900276 × 1010
95-th percentile7.6147636 × 1010
Maximum1.1608308 × 1011
Range1.1608308 × 1011
Interquartile range (IQR)3.6084308 × 1010

Descriptive statistics

Standard deviation2.7579149 × 1010
Coefficient of variation (CV)1.2730989
Kurtosis1.9768511
Mean2.1663006 × 1010
Median Absolute Deviation (MAD)7.0346065 × 109
Skewness1.568264
Sum1.4730844 × 1012
Variance7.6060945 × 1020
MonotonicityNot monotonic
2023-12-12T19:47:11.058444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16
 
23.5%
63580434000 1
 
1.5%
55840158000 1
 
1.5%
9568423000 1
 
1.5%
5325747000 1
 
1.5%
48412610000 1
 
1.5%
22268547000 1
 
1.5%
97974242000 1
 
1.5%
5141894000 1
 
1.5%
54106717000 1
 
1.5%
Other values (43) 43
63.2%
ValueCountFrequency (%)
0 16
23.5%
144806000 1
 
1.5%
3843000000 1
 
1.5%
3957351000 1
 
1.5%
4431710000 1
 
1.5%
4554473000 1
 
1.5%
4717851000 1
 
1.5%
4751779000 1
 
1.5%
4968850000 1
 
1.5%
5023859000 1
 
1.5%
ValueCountFrequency (%)
116083082000 1
1.5%
97974242000 1
1.5%
97431022000 1
1.5%
82808130000 1
1.5%
63778148000 1
1.5%
63580434000 1
1.5%
61828398000 1
1.5%
56261828000 1
1.5%
55840158000 1
1.5%
54106717000 1
1.5%

비과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct43
Distinct (%)63.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6964.1029
Minimum0
Maximum46748
Zeros26
Zeros (%)38.2%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-12T19:47:11.215544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1122.5
Q39118.5
95-th percentile33462.45
Maximum46748
Range46748
Interquartile range (IQR)9118.5

Descriptive statistics

Standard deviation11695.904
Coefficient of variation (CV)1.6794559
Kurtosis2.9948965
Mean6964.1029
Median Absolute Deviation (MAD)1122.5
Skewness1.9451075
Sum473559
Variance1.3679417 × 108
MonotonicityNot monotonic
2023-12-12T19:47:11.428113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0 26
38.2%
4578 1
 
1.5%
2221 1
 
1.5%
25779 1
 
1.5%
1701 1
 
1.5%
1214 1
 
1.5%
15 1
 
1.5%
4301 1
 
1.5%
9766 1
 
1.5%
42079 1
 
1.5%
Other values (33) 33
48.5%
ValueCountFrequency (%)
0 26
38.2%
1 1
 
1.5%
4 1
 
1.5%
11 1
 
1.5%
15 1
 
1.5%
18 1
 
1.5%
30 1
 
1.5%
393 1
 
1.5%
1112 1
 
1.5%
1133 1
 
1.5%
ValueCountFrequency (%)
46748 1
1.5%
42079 1
1.5%
41395 1
1.5%
35532 1
1.5%
29619 1
1.5%
27700 1
1.5%
25779 1
1.5%
25695 1
1.5%
23419 1
1.5%
21864 1
1.5%

비과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)61.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5373556 × 109
Minimum0
Maximum3.6838514 × 1010
Zeros27
Zeros (%)39.7%
Negative0
Negative (%)0.0%
Memory size744.0 B
2023-12-12T19:47:11.611566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median78218000
Q31.1019782 × 109
95-th percentile2.0612932 × 1010
Maximum3.6838514 × 1010
Range3.6838514 × 1010
Interquartile range (IQR)1.1019782 × 109

Descriptive statistics

Standard deviation7.8333697 × 109
Coefficient of variation (CV)2.2144705
Kurtosis5.2730871
Mean3.5373556 × 109
Median Absolute Deviation (MAD)78218000
Skewness2.3798178
Sum2.4054018 × 1011
Variance6.1361681 × 1019
MonotonicityNot monotonic
2023-12-12T19:47:11.791250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 27
39.7%
20515231000 1
 
1.5%
109302000 1
 
1.5%
1129362000 1
 
1.5%
73428000 1
 
1.5%
345070000 1
 
1.5%
3000 1
 
1.5%
10605534000 1
 
1.5%
209584000 1
 
1.5%
20665540000 1
 
1.5%
Other values (32) 32
47.1%
ValueCountFrequency (%)
0 27
39.7%
1000 1
 
1.5%
2000 1
 
1.5%
3000 1
 
1.5%
4000 1
 
1.5%
7000 1
 
1.5%
40758000 1
 
1.5%
73428000 1
 
1.5%
83008000 1
 
1.5%
107501000 1
 
1.5%
ValueCountFrequency (%)
36838514000 1
1.5%
26110133000 1
1.5%
22414226000 1
1.5%
20665540000 1
1.5%
20515231000 1
1.5%
18551842000 1
1.5%
17589894000 1
1.5%
15813735000 1
1.5%
14976145000 1
1.5%
13853339000 1
1.5%

Interactions

2023-12-12T19:47:07.794663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:04.701891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:05.578509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:06.297551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:07.123732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:07.944008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:04.797064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:05.683242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:06.448744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:07.256186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:08.090052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:04.915130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:05.813362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:06.616307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:07.393576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:08.260483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:05.022973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:05.933813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:06.793074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:07.537506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:08.402831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:05.113943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:06.133655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:06.943161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:47:07.646240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:47:11.917531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명과세건수과세금액비과세건수비과세금액
과세년도1.0000.0000.0000.0000.0000.000
세목명0.0001.0000.9690.8050.7590.451
과세건수0.0000.9691.0000.5910.7050.000
과세금액0.0000.8050.5911.0000.5540.878
비과세건수0.0000.7590.7050.5541.0000.720
비과세금액0.0000.4510.0000.8780.7201.000
2023-12-12T19:47:12.072962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도과세건수과세금액비과세건수비과세금액세목명
과세년도1.000-0.0050.046-0.058-0.0670.000
과세건수-0.0051.0000.5040.6250.5400.885
과세금액0.0460.5041.0000.5000.6050.492
비과세건수-0.0580.6250.5001.0000.9260.438
비과세금액-0.0670.5400.6050.9261.0000.196
세목명0.0000.8850.4920.4380.1961.000

Missing values

2023-12-12T19:47:08.594725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:47:08.823360image/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

시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액
0부산광역시동래구262602017취득세1235863580434000457820515231000
1부산광역시동래구262602017주민세11573244317100005395317590000
2부산광역시동래구262602017재산세134205378920510001686213853339000
3부산광역시동래구262602017자동차세14903618329554000187801156495000
4부산광역시동래구262602017등록면허세66327624025500039340758000
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6부산광역시동래구262602017지방소득세655864283730600000
7부산광역시동래구262602017교육세5129561691944700010
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9부산광역시동래구262602018주민세11659847178510009276319518000
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60부산광역시동래구262602022레저세4514480600000
61부산광역시동래구262602022담배소비세0000
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