Overview

Dataset statistics

Number of variables9
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory81.6 B

Variable types

Categorical5
Numeric4

Dataset

Description부산광역시연제구_지방세과세현황_20211020
Author부산광역시 연제구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15079133

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 1 other fieldsHigh correlation
비과세건수 is highly overall correlated with 과세건수 and 1 other fieldsHigh correlation
비과세금액 is highly overall correlated with 과세건수 and 1 other fieldsHigh correlation
세목명 is highly overall correlated with 과세건수 and 1 other fieldsHigh correlation
과세건수 has 10 (27.0%) zerosZeros
과세금액 has 10 (27.0%) zerosZeros
비과세건수 has 16 (43.2%) zerosZeros
비과세금액 has 16 (43.2%) zerosZeros

Reproduction

Analysis started2023-12-10 16:14:33.366984
Analysis finished2023-12-10 16:14:35.475179
Duration2.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
부산광역시
37 

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 37
100.0%

Length

2023-12-11T01:14:35.563106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:14:35.685007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 37
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
연제구
37 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연제구 37
100.0%

Length

2023-12-11T01:14:35.802087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:14:35.928633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
연제구 37
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
26470
37 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26470
2nd row26470
3rd row26470
4th row26470
5th row26470

Common Values

ValueCountFrequency (%)
26470 37
100.0%

Length

2023-12-11T01:14:36.056822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:14:36.209294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26470 37
100.0%

과세년도
Categorical

Distinct3
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
2017
13 
2018
12 
2019
12 

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 13
35.1%
2018 12
32.4%
2019 12
32.4%

Length

2023-12-11T01:14:36.348151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:14:36.496527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 13
35.1%
2018 12
32.4%
2019 12
32.4%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
취득세
3 
주민세
3 
재산세
3 
자동차세
3 
레저세
3 
Other values (8)
22 

Length

Max length7
Median length5
Mean length4.2162162
Min length3

Unique

Unique1 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 3
8.1%
주민세 3
8.1%
재산세 3
8.1%
자동차세 3
8.1%
레저세 3
8.1%
담배소비세 3
8.1%
지방소비세 3
8.1%
등록면허세 3
8.1%
도시계획세 3
8.1%
지역자원시설세 3
8.1%
Other values (3) 7
18.9%

Length

2023-12-11T01:14:36.669764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 3
8.1%
주민세 3
8.1%
재산세 3
8.1%
자동차세 3
8.1%
레저세 3
8.1%
담배소비세 3
8.1%
지방소비세 3
8.1%
등록면허세 3
8.1%
도시계획세 3
8.1%
지역자원시설세 3
8.1%
Other values (3) 7
18.9%

과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80918.432
Minimum0
Maximum419696
Zeros10
Zeros (%)27.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-11T01:14:36.931251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median61264
Q3115712
95-th percentile404574.8
Maximum419696
Range419696
Interquartile range (IQR)115712

Descriptive statistics

Standard deviation111067.08
Coefficient of variation (CV)1.3725807
Kurtosis4.5593513
Mean80918.432
Median Absolute Deviation (MAD)61251
Skewness2.1543276
Sum2993982
Variance1.2335897 × 1010
MonotonicityNot monotonic
2023-12-11T01:14:37.094995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 10
27.0%
13 2
 
5.4%
12577 1
 
2.7%
125854 1
 
2.7%
419696 1
 
2.7%
63939 1
 
2.7%
144541 1
 
2.7%
68049 1
 
2.7%
12 1
 
2.7%
118252 1
 
2.7%
Other values (17) 17
45.9%
ValueCountFrequency (%)
0 10
27.0%
12 1
 
2.7%
13 2
 
5.4%
8608 1
 
2.7%
9090 1
 
2.7%
12577 1
 
2.7%
57028 1
 
2.7%
60216 1
 
2.7%
61264 1
 
2.7%
63615 1
 
2.7%
ValueCountFrequency (%)
419696 1
2.7%
409382 1
2.7%
403373 1
2.7%
144541 1
2.7%
125854 1
2.7%
123152 1
2.7%
118252 1
2.7%
117700 1
2.7%
115923 1
2.7%
115712 1
2.7%

과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4869541 × 1010
Minimum0
Maximum6.2172429 × 1010
Zeros10
Zeros (%)27.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-11T01:14:37.251254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.12311 × 109
Q31.7107148 × 1010
95-th percentile4.7017881 × 1010
Maximum6.2172429 × 1010
Range6.2172429 × 1010
Interquartile range (IQR)1.7107148 × 1010

Descriptive statistics

Standard deviation1.7856685 × 1010
Coefficient of variation (CV)1.2008901
Kurtosis0.23875765
Mean1.4869541 × 1010
Median Absolute Deviation (MAD)6.12311 × 109
Skewness1.2182599
Sum5.5017303 × 1011
Variance3.1886119 × 1020
MonotonicityNot monotonic
2023-12-11T01:14:37.410234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 10
27.0%
62172429000 1
 
2.7%
4724800000 1
 
2.7%
16505745000 1
 
2.7%
43621423000 1
 
2.7%
4598947000 1
 
2.7%
6123110000 1
 
2.7%
6421650000 1
 
2.7%
14716868000 1
 
2.7%
37186774000 1
 
2.7%
Other values (18) 18
48.6%
ValueCountFrequency (%)
0 10
27.0%
4199351000 1
 
2.7%
4458966000 1
 
2.7%
4579942000 1
 
2.7%
4598947000 1
 
2.7%
4724800000 1
 
2.7%
4874016000 1
 
2.7%
5365462000 1
 
2.7%
5819415000 1
 
2.7%
6123110000 1
 
2.7%
ValueCountFrequency (%)
62172429000 1
2.7%
51053895000 1
2.7%
46008878000 1
2.7%
44572315000 1
2.7%
43910749000 1
2.7%
43621423000 1
2.7%
37186774000 1
2.7%
33769184000 1
2.7%
30528118000 1
2.7%
17107148000 1
2.7%

비과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)59.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7133.6486
Minimum0
Maximum35683
Zeros16
Zeros (%)43.2%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-11T01:14:37.552723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median32
Q310934
95-th percentile30907.6
Maximum35683
Range35683
Interquartile range (IQR)10934

Descriptive statistics

Standard deviation10839.438
Coefficient of variation (CV)1.5194803
Kurtosis1.1886472
Mean7133.6486
Median Absolute Deviation (MAD)32
Skewness1.5245792
Sum263945
Variance1.1749342 × 108
MonotonicityNot monotonic
2023-12-11T01:14:38.044689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 16
43.2%
12744 1
 
2.7%
2539 1
 
2.7%
13 1
 
2.7%
1197 1
 
2.7%
2764 1
 
2.7%
35683 1
 
2.7%
30056 1
 
2.7%
10934 1
 
2.7%
18431 1
 
2.7%
Other values (12) 12
32.4%
ValueCountFrequency (%)
0 16
43.2%
1 1
 
2.7%
13 1
 
2.7%
32 1
 
2.7%
1197 1
 
2.7%
2184 1
 
2.7%
2539 1
 
2.7%
2764 1
 
2.7%
5389 1
 
2.7%
7089 1
 
2.7%
ValueCountFrequency (%)
35683 1
2.7%
34314 1
2.7%
30056 1
2.7%
29077 1
2.7%
23467 1
2.7%
18431 1
2.7%
18091 1
2.7%
13147 1
2.7%
12744 1
2.7%
10934 1
2.7%

비과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5013648 × 109
Minimum0
Maximum2.4385851 × 1010
Zeros16
Zeros (%)43.2%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-11T01:14:38.284746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median341000
Q31.48528 × 109
95-th percentile2.0051726 × 1010
Maximum2.4385851 × 1010
Range2.4385851 × 1010
Interquartile range (IQR)1.48528 × 109

Descriptive statistics

Standard deviation7.2716323 × 109
Coefficient of variation (CV)2.0767994
Kurtosis2.4906235
Mean3.5013648 × 109
Median Absolute Deviation (MAD)341000
Skewness2.0116652
Sum1.295505 × 1011
Variance5.2876636 × 1019
MonotonicityNot monotonic
2023-12-11T01:14:38.556146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 16
43.2%
2000 2
 
5.4%
16919811000 1
 
2.7%
150180000 1
 
2.7%
553598000 1
 
2.7%
140300000 1
 
2.7%
1484194000 1
 
2.7%
19374405000 1
 
2.7%
2072303000 1
 
2.7%
24385851000 1
 
2.7%
Other values (11) 11
29.7%
ValueCountFrequency (%)
0 16
43.2%
2000 2
 
5.4%
341000 1
 
2.7%
112846000 1
 
2.7%
140300000 1
 
2.7%
150180000 1
 
2.7%
553598000 1
 
2.7%
562645000 1
 
2.7%
580960000 1
 
2.7%
1338878000 1
 
2.7%
ValueCountFrequency (%)
24385851000 1
2.7%
22761009000 1
2.7%
19374405000 1
2.7%
17623261000 1
2.7%
16919811000 1
2.7%
15880367000 1
2.7%
2072303000 1
2.7%
2063248000 1
2.7%
2061015000 1
2.7%
1485280000 1
2.7%

Interactions

2023-12-11T01:14:34.825048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:33.672888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.064579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.474174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.906695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:33.757374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.162327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.551546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.996042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:33.871793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.259615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.638308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:35.091228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:33.964812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.377905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.729113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:14:38.690875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명과세건수과세금액비과세건수비과세금액
과세년도1.0000.0000.0000.0000.1970.000
세목명0.0001.0000.9390.8910.6730.777
과세건수0.0000.9391.0000.5360.4040.000
과세금액0.0000.8910.5361.0000.8480.996
비과세건수0.1970.6730.4040.8481.0000.990
비과세금액0.0000.7770.0000.9960.9901.000
2023-12-11T01:14:38.863382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2023-12-11T01:14:38.994272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세건수과세금액비과세건수비과세금액과세년도세목명
과세건수1.0000.5050.6010.5230.0000.739
과세금액0.5051.0000.4510.4640.0000.620
비과세건수0.6010.4511.0000.9520.0910.336
비과세금액0.5230.4640.9521.0000.0000.492
과세년도0.0000.0000.0910.0001.0000.000
세목명0.7390.6200.3360.4920.0001.000

Missing values

2023-12-11T01:14:35.205557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:14:35.402023image/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
0부산광역시연제구264702017취득세12577621724290001274416919811000
1부산광역시연제구264702017등록세001341000
2부산광역시연제구264702017주민세91188457994200053892061015000
3부산광역시연제구264702017재산세109446305281180001314715880367000
4부산광역시연제구264702017자동차세11592314075637000290771338878000
5부산광역시연제구264702017레저세13708731800000
6부산광역시연제구264702017담배소비세0000
7부산광역시연제구264702017지방소비세0000
8부산광역시연제구264702017등록면허세6361558194150002184112846000
9부산광역시연제구264702017도시계획세0000
시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액
27부산광역시연제구264702019재산세117700371867740003005619374405000
28부산광역시연제구264702019자동차세11825214716868000356831484194000
29부산광역시연제구264702019레저세12642165000000
30부산광역시연제구264702019담배소비세0000
31부산광역시연제구264702019지방소비세0000
32부산광역시연제구264702019등록면허세6804961231100002764140300000
33부산광역시연제구264702019도시계획세0000
34부산광역시연제구264702019지역자원시설세14454145989470001197553598000
35부산광역시연제구264702019지방소득세639394362142300000
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