Overview

Dataset statistics

Number of variables9
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory80.9 B

Variable types

Categorical5
Numeric4

Dataset

Description부산광역시중구_지방세과세현황_20211231
Author부산광역시 중구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15078397

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세건수 is highly overall correlated with 과세금액 and 1 other fieldsHigh correlation
과세금액 is highly overall correlated with 과세건수 and 1 other fieldsHigh correlation
비과세건수 is highly overall correlated with 비과세금액High correlation
비과세금액 is highly overall correlated with 비과세건수High correlation
세목명 is highly overall correlated with 과세건수 and 1 other fieldsHigh correlation
과세건수 has 8 (17.4%) zerosZeros
과세금액 has 8 (17.4%) zerosZeros
비과세건수 has 20 (43.5%) zerosZeros
비과세금액 has 20 (43.5%) zerosZeros

Reproduction

Analysis started2023-12-10 16:39:43.906419
Analysis finished2023-12-10 16:39:46.117167
Duration2.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
부산광역시
46 

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 46
100.0%

Length

2023-12-11T01:39:46.174492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:46.284724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 46
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
중구
46 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 46
100.0%

Length

2023-12-11T01:39:46.376811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:46.493434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 46
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
26110
46 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26110
2nd row26110
3rd row26110
4th row26110
5th row26110

Common Values

ValueCountFrequency (%)
26110 46
100.0%

Length

2023-12-11T01:39:46.587004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:46.679694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26110 46
100.0%

과세년도
Categorical

Distinct4
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
2018
12 
2019
12 
2020
12 
2021
10 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 12
26.1%
2019 12
26.1%
2020 12
26.1%
2021 10
21.7%

Length

2023-12-11T01:39:46.767922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:46.867595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 12
26.1%
2019 12
26.1%
2020 12
26.1%
2021 10
21.7%

세목명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Memory size500.0 B
취득세
4 
주민세
4 
재산세
4 
자동차세
4 
레저세
4 
Other values (7)
26 

Length

Max length7
Median length5
Mean length4.2173913
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 4
8.7%
주민세 4
8.7%
재산세 4
8.7%
자동차세 4
8.7%
레저세 4
8.7%
지방소비세 4
8.7%
등록면허세 4
8.7%
지역자원시설세 4
8.7%
지방소득세 4
8.7%
교육세 4
8.7%
Other values (2) 6
13.0%

Length

2023-12-11T01:39:47.022352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 4
8.7%
주민세 4
8.7%
재산세 4
8.7%
자동차세 4
8.7%
레저세 4
8.7%
지방소비세 4
8.7%
등록면허세 4
8.7%
지역자원시설세 4
8.7%
지방소득세 4
8.7%
교육세 4
8.7%
Other values (2) 6
13.0%

과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27355.804
Minimum0
Maximum118398
Zeros8
Zeros (%)17.4%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-11T01:39:47.184640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q138.25
median28096
Q334403
95-th percentile114237.5
Maximum118398
Range118398
Interquartile range (IQR)34364.75

Descriptive statistics

Standard deviation31730.413
Coefficient of variation (CV)1.1599152
Kurtosis3.1338802
Mean27355.804
Median Absolute Deviation (MAD)15977.5
Skewness1.7701648
Sum1258367
Variance1.0068191 × 109
MonotonicityNot monotonic
2023-12-11T01:39:47.346417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 8
 
17.4%
2312 1
 
2.2%
28223 1
 
2.2%
16 1
 
2.2%
6 1
 
2.2%
29082 1
 
2.2%
33360 1
 
2.2%
34906 1
 
2.2%
116213 1
 
2.2%
4536 1
 
2.2%
Other values (29) 29
63.0%
ValueCountFrequency (%)
0 8
17.4%
6 1
 
2.2%
7 1
 
2.2%
16 1
 
2.2%
38 1
 
2.2%
39 1
 
2.2%
45 1
 
2.2%
2312 1
 
2.2%
3127 1
 
2.2%
3648 1
 
2.2%
ValueCountFrequency (%)
118398 1
2.2%
116213 1
2.2%
114457 1
2.2%
113579 1
2.2%
44737 1
2.2%
43410 1
2.2%
41707 1
2.2%
40961 1
2.2%
36077 1
2.2%
35438 1
2.2%

과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.9084141 × 109
Minimum0
Maximum3.9814745 × 1010
Zeros8
Zeros (%)17.4%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-11T01:39:47.483580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.1697998 × 109
median3.368065 × 109
Q31.4033228 × 1010
95-th percentile3.5640581 × 1010
Maximum3.9814745 × 1010
Range3.9814745 × 1010
Interquartile range (IQR)1.1863429 × 1010

Descriptive statistics

Standard deviation1.1589553 × 1010
Coefficient of variation (CV)1.3009671
Kurtosis1.164436
Mean8.9084141 × 109
Median Absolute Deviation (MAD)2.880663 × 109
Skewness1.5268365
Sum4.0978705 × 1011
Variance1.3431775 × 1020
MonotonicityNot monotonic
2023-12-11T01:39:47.615233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 8
 
17.4%
16433972000 1
 
2.2%
4691175000 1
 
2.2%
481666000 1
 
2.2%
2536000000 1
 
2.2%
3122969000 1
 
2.2%
3585510000 1
 
2.2%
34560775000 1
 
2.2%
5931171000 1
 
2.2%
27973028000 1
 
2.2%
Other values (29) 29
63.0%
ValueCountFrequency (%)
0 8
17.4%
481666000 1
 
2.2%
493138000 1
 
2.2%
2032558000 1
 
2.2%
2047733000 1
 
2.2%
2536000000 1
 
2.2%
2594992000 1
 
2.2%
2696304000 1
 
2.2%
2711238000 1
 
2.2%
2726413000 1
 
2.2%
ValueCountFrequency (%)
39814745000 1
2.2%
39337420000 1
2.2%
36000516000 1
2.2%
34560775000 1
2.2%
27973028000 1
2.2%
24559659000 1
2.2%
22216338000 1
2.2%
21179383000 1
2.2%
19843131000 1
2.2%
19691725000 1
2.2%

비과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1673.1304
Minimum0
Maximum10805
Zeros20
Zeros (%)43.5%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-11T01:39:47.741299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median622
Q32304.5
95-th percentile7207.5
Maximum10805
Range10805
Interquartile range (IQR)2304.5

Descriptive statistics

Standard deviation2618.9411
Coefficient of variation (CV)1.5652941
Kurtosis4.2920489
Mean1673.1304
Median Absolute Deviation (MAD)622
Skewness2.0906587
Sum76964
Variance6858852.6
MonotonicityNot monotonic
2023-12-11T01:39:47.880178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 20
43.5%
859 1
 
2.2%
10805 1
 
2.2%
10 1
 
2.2%
785 1
 
2.2%
2042 1
 
2.2%
3941 1
 
2.2%
10075 1
 
2.2%
1660 1
 
2.2%
960 1
 
2.2%
Other values (17) 17
37.0%
ValueCountFrequency (%)
0 20
43.5%
4 1
 
2.2%
10 1
 
2.2%
480 1
 
2.2%
764 1
 
2.2%
785 1
 
2.2%
859 1
 
2.2%
939 1
 
2.2%
960 1
 
2.2%
1003 1
 
2.2%
ValueCountFrequency (%)
10805 1
2.2%
10075 1
2.2%
7506 1
2.2%
6312 1
2.2%
4505 1
2.2%
3941 1
2.2%
3898 1
2.2%
3859 1
2.2%
3632 1
2.2%
3434 1
2.2%

비과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2608327 × 109
Minimum0
Maximum9.599722 × 109
Zeros20
Zeros (%)43.5%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-11T01:39:47.996160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median41829500
Q36.85853 × 108
95-th percentile8.388036 × 109
Maximum9.599722 × 109
Range9.599722 × 109
Interquartile range (IQR)6.85853 × 108

Descriptive statistics

Standard deviation2.6608644 × 109
Coefficient of variation (CV)2.1104026
Kurtosis3.7284781
Mean1.2608327 × 109
Median Absolute Deviation (MAD)41829500
Skewness2.2162689
Sum5.7998302 × 1010
Variance7.0801996 × 1018
MonotonicityNot monotonic
2023-12-11T01:39:48.110331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 20
43.5%
1000 2
 
4.3%
4798888000 1
 
2.2%
837474000 1
 
2.2%
135117000 1
 
2.2%
44787000 1
 
2.2%
207982000 1
 
2.2%
9599722000 1
 
2.2%
899691000 1
 
2.2%
3380456000 1
 
2.2%
Other values (16) 16
34.8%
ValueCountFrequency (%)
0 20
43.5%
1000 2
 
4.3%
40908000 1
 
2.2%
42751000 1
 
2.2%
44787000 1
 
2.2%
123636000 1
 
2.2%
129762000 1
 
2.2%
130664000 1
 
2.2%
135117000 1
 
2.2%
146136000 1
 
2.2%
ValueCountFrequency (%)
9599722000 1
2.2%
9020445000 1
2.2%
8614572000 1
2.2%
7708428000 1
2.2%
5100619000 1
2.2%
4798888000 1
2.2%
4544479000 1
2.2%
3380456000 1
2.2%
914737000 1
2.2%
905791000 1
2.2%

Interactions

2023-12-11T01:39:45.513193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:44.230023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:44.707417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:45.113526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:45.611695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:44.348459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:44.804249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:45.223665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:45.721602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:44.475612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:44.904747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:45.336413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:45.804816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:44.604540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:45.001322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:39:45.420527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:39:48.438394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명과세건수과세금액비과세건수비과세금액
과세년도1.0000.0000.0000.0000.0000.000
세목명0.0001.0000.9990.8610.8260.814
과세건수0.0000.9991.0000.8790.8890.642
과세금액0.0000.8610.8791.0000.7340.948
비과세건수0.0000.8260.8890.7341.0000.756
비과세금액0.0000.8140.6420.9480.7561.000
2023-12-11T01:39:48.547336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도
세목명1.0000.000
과세년도0.0001.000
2023-12-11T01:39:48.674826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세건수과세금액비과세건수비과세금액과세년도세목명
과세건수1.0000.7790.4230.3840.0000.861
과세금액0.7791.0000.3560.4950.0000.550
비과세건수0.4230.3561.0000.9160.0000.497
비과세금액0.3840.4950.9161.0000.0000.418
과세년도0.0000.0000.0000.0001.0000.000
세목명0.8610.5500.4970.4180.0001.000

Missing values

2023-12-11T01:39:45.939042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:39:46.070195image/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
0부산광역시중구261102018취득세2312164339720008594798888000
1부산광역시중구261102018주민세3140943253830003632914737000
2부산광역시중구261102018재산세409611775284600063127708428000
3부산광역시중구261102018자동차세2769027633920003434230990000
4부산광역시중구261102018레저세45203255800000
5부산광역시중구261102018담배소비세0000
6부산광역시중구261102018지방소비세0000
7부산광역시중구261102018등록면허세2619530960940001385123636000
8부산광역시중구261102018도시계획세0000
9부산광역시중구261102018지역자원시설세2871832669200002955146136000
시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액
36부산광역시중구261102021취득세4536279730280009603380456000
37부산광역시중구261102021주민세2822346911750001660899691000
38부산광역시중구261102021재산세4473722216338000100759599722000
39부산광역시중구261102021자동차세2752127112380003941207982000
40부산광역시중구261102021레저세3849313800000
41부산광역시중구261102021지방소비세7259499200000
42부산광역시중구261102021등록면허세294793153230000204244787000
43부산광역시중구261102021지역자원시설세354383576466000785135117000
44부산광역시중구261102021지방소득세360773981474500000
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