Overview

Dataset statistics

Number of variables11
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory99.1 B

Variable types

Categorical5
Numeric6

Dataset

Description부산광역시연제구_지방세징수현황_20191231
Author부산광역시 연제구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15079356

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
부과금액 is highly overall correlated with 수납급액 and 5 other fieldsHigh correlation
수납급액 is highly overall correlated with 부과금액 and 4 other fieldsHigh correlation
환급금액 is highly overall correlated with 부과금액 and 3 other fieldsHigh correlation
결손금액 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
미수납 금액 is highly overall correlated with 부과금액 and 4 other fieldsHigh correlation
징수율 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 부과금액 and 3 other fieldsHigh correlation
부과금액 has 12 (28.6%) zerosZeros
수납급액 has 12 (28.6%) zerosZeros
환급금액 has 15 (35.7%) zerosZeros
결손금액 has 21 (50.0%) zerosZeros
미수납 금액 has 15 (35.7%) zerosZeros
징수율 has 12 (28.6%) zerosZeros

Reproduction

Analysis started2023-12-10 16:43:57.603346
Analysis finished2023-12-10 16:44:04.285592
Duration6.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
부산광역시
42 

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 42
100.0%

Length

2023-12-11T01:44:04.411773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:44:04.646994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 42
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
연제구
42 

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 42
100.0%

Length

2023-12-11T01:44:04.826852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:44:04.961847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
연제구 42
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
26470
42 

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 42
100.0%

Length

2023-12-11T01:44:05.115916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:44:05.284112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26470 42
100.0%

과세년도
Categorical

Distinct3
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size468.0 B
2017
14 
2018
14 
2019
14 

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 14
33.3%
2018 14
33.3%
2019 14
33.3%

Length

2023-12-11T01:44:05.442895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:44:05.606204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 14
33.3%
2018 14
33.3%
2019 14
33.3%

세목명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size468.0 B
도축세
3 
레저세
3 
재산세
3 
주민세
3 
취득세
3 
Other values (9)
27 

Length

Max length7
Median length6
Mean length4.3571429
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
도축세 3
 
7.1%
레저세 3
 
7.1%
재산세 3
 
7.1%
주민세 3
 
7.1%
취득세 3
 
7.1%
자동차세 3
 
7.1%
과년도수입 3
 
7.1%
담배소비세 3
 
7.1%
도시계획세 3
 
7.1%
등록면허세 3
 
7.1%
Other values (4) 12
28.6%

Length

2023-12-11T01:44:05.889530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도축세 3
 
7.1%
레저세 3
 
7.1%
재산세 3
 
7.1%
주민세 3
 
7.1%
취득세 3
 
7.1%
자동차세 3
 
7.1%
과년도수입 3
 
7.1%
담배소비세 3
 
7.1%
도시계획세 3
 
7.1%
등록면허세 3
 
7.1%
Other values (4) 12
28.6%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.354229 × 1010
Minimum0
Maximum6.2172429 × 1010
Zeros12
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-11T01:44:06.082355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.074789 × 109
Q31.6375571 × 1010
95-th percentile4.593705 × 1010
Maximum6.2172429 × 1010
Range6.2172429 × 1010
Interquartile range (IQR)1.6375571 × 1010

Descriptive statistics

Standard deviation1.7159758 × 1010
Coefficient of variation (CV)1.2671238
Kurtosis0.77707169
Mean1.354229 × 1010
Median Absolute Deviation (MAD)6.074789 × 109
Skewness1.3981415
Sum5.6877619 × 1011
Variance2.9445728 × 1020
MonotonicityNot monotonic
2023-12-11T01:44:06.308167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 12
28.6%
7087318000 1
 
2.4%
4598947000 1
 
2.4%
43621423000 1
 
2.4%
16505745000 1
 
2.4%
6123110000 1
 
2.4%
6453575000 1
 
2.4%
14716868000 1
 
2.4%
46008878000 1
 
2.4%
5365462000 1
 
2.4%
Other values (21) 21
50.0%
ValueCountFrequency (%)
0 12
28.6%
4199351000 1
 
2.4%
4458966000 1
 
2.4%
4579942000 1
 
2.4%
4598947000 1
 
2.4%
4724800000 1
 
2.4%
4874016000 1
 
2.4%
5365462000 1
 
2.4%
5819415000 1
 
2.4%
6039876000 1
 
2.4%
ValueCountFrequency (%)
62172429000 1
2.4%
51053895000 1
2.4%
46008878000 1
2.4%
44572315000 1
2.4%
43910749000 1
2.4%
43621423000 1
2.4%
37186774000 1
2.4%
33769184000 1
2.4%
30528118000 1
2.4%
17107148000 1
2.4%

수납급액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2849325 × 1010
Minimum0
Maximum6.2097138 × 1010
Zeros12
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-11T01:44:06.500391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.9254955 × 109
Q31.5768014 × 1010
95-th percentile4.5729978 × 1010
Maximum6.2097138 × 1010
Range6.2097138 × 1010
Interquartile range (IQR)1.5768014 × 1010

Descriptive statistics

Standard deviation1.699888 × 1010
Coefficient of variation (CV)1.3229395
Kurtosis0.92818368
Mean1.2849325 × 1010
Median Absolute Deviation (MAD)4.9254955 × 109
Skewness1.4420925
Sum5.3967167 × 1011
Variance2.8896191 × 1020
MonotonicityNot monotonic
2023-12-11T01:44:06.795642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 12
28.6%
7087318000 1
 
2.4%
4524592000 1
 
2.4%
41917518000 1
 
2.4%
15903929000 1
 
2.4%
6095848000 1
 
2.4%
2297292000 1
 
2.4%
13045353000 1
 
2.4%
45896851000 1
 
2.4%
5171597000 1
 
2.4%
Other values (21) 21
50.0%
ValueCountFrequency (%)
0 12
28.6%
1556910000 1
 
2.4%
1643833000 1
 
2.4%
2297292000 1
 
2.4%
4083863000 1
 
2.4%
4387536000 1
 
2.4%
4387616000 1
 
2.4%
4524592000 1
 
2.4%
4657604000 1
 
2.4%
4679394000 1
 
2.4%
ValueCountFrequency (%)
62097138000 1
2.4%
50690383000 1
2.4%
45896851000 1
2.4%
42559382000 1
2.4%
41917518000 1
2.4%
41787183000 1
2.4%
36558005000 1
2.4%
33161119000 1
2.4%
29869079000 1
2.4%
16520803000 1
2.4%

환급금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3004662 × 108
Minimum0
Maximum1.791516 × 109
Zeros15
Zeros (%)35.7%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-11T01:44:07.005242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10790000
Q31.2878025 × 108
95-th percentile1.3888177 × 109
Maximum1.791516 × 109
Range1.791516 × 109
Interquartile range (IQR)1.2878025 × 108

Descriptive statistics

Standard deviation4.9172032 × 108
Coefficient of variation (CV)2.1374812
Kurtosis3.5627213
Mean2.3004662 × 108
Median Absolute Deviation (MAD)10790000
Skewness2.2292882
Sum9.661958 × 109
Variance2.4178888 × 1017
MonotonicityNot monotonic
2023-12-11T01:44:07.211974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 15
35.7%
16386000 1
 
2.4%
3533000 1
 
2.4%
1618364000 1
 
2.4%
80185000 1
 
2.4%
99861000 1
 
2.4%
1150177000 1
 
2.4%
172101000 1
 
2.4%
138420000 1
 
2.4%
2191000 1
 
2.4%
Other values (18) 18
42.9%
ValueCountFrequency (%)
0 15
35.7%
1241000 1
 
2.4%
2191000 1
 
2.4%
3533000 1
 
2.4%
4495000 1
 
2.4%
7576000 1
 
2.4%
8190000 1
 
2.4%
13390000 1
 
2.4%
14817000 1
 
2.4%
16386000 1
 
2.4%
ValueCountFrequency (%)
1791516000 1
2.4%
1618364000 1
2.4%
1396529000 1
2.4%
1242303000 1
2.4%
1151496000 1
2.4%
1150177000 1
2.4%
172101000 1
2.4%
169776000 1
2.4%
168231000 1
2.4%
166385000 1
2.4%

결손금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91022000
Minimum0
Maximum1.134625 × 109
Zeros21
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-11T01:44:07.418193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4000
Q32225500
95-th percentile8.013977 × 108
Maximum1.134625 × 109
Range1.134625 × 109
Interquartile range (IQR)2225500

Descriptive statistics

Standard deviation2.5483913 × 108
Coefficient of variation (CV)2.7997532
Kurtosis9.0236143
Mean91022000
Median Absolute Deviation (MAD)4000
Skewness3.08147
Sum3.822924 × 109
Variance6.4942983 × 1016
MonotonicityNot monotonic
2023-12-11T01:44:07.619463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 21
50.0%
5568000 1
 
2.4%
290469000 1
 
2.4%
1135000 1
 
2.4%
153000 1
 
2.4%
856086000 1
 
2.4%
4162000 1
 
2.4%
175000 1
 
2.4%
8000 1
 
2.4%
472000 1
 
2.4%
Other values (12) 12
28.6%
ValueCountFrequency (%)
0 21
50.0%
8000 1
 
2.4%
40000 1
 
2.4%
46000 1
 
2.4%
144000 1
 
2.4%
153000 1
 
2.4%
175000 1
 
2.4%
181000 1
 
2.4%
472000 1
 
2.4%
1014000 1
 
2.4%
ValueCountFrequency (%)
1134625000 1
2.4%
856086000 1
2.4%
825413000 1
2.4%
345107000 1
2.4%
324107000 1
2.4%
290469000 1
2.4%
16313000 1
2.4%
15117000 1
2.4%
5568000 1
2.4%
4162000 1
2.4%

미수납 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0194267 × 108
Minimum0
Maximum3.57063 × 109
Zeros15
Zeros (%)35.7%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-11T01:44:07.824974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median93659000
Q36.263745 × 108
95-th percentile3.2241101 × 109
Maximum3.57063 × 109
Range3.57063 × 109
Interquartile range (IQR)6.263745 × 108

Descriptive statistics

Standard deviation9.7224203 × 108
Coefficient of variation (CV)1.6151738
Kurtosis3.1993338
Mean6.0194267 × 108
Median Absolute Deviation (MAD)93659000
Skewness1.9572325
Sum2.5281592 × 1010
Variance9.4525457 × 1017
MonotonicityNot monotonic
2023-12-11T01:44:08.022982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 15
35.7%
45225000 1
 
2.4%
74355000 1
 
2.4%
1413436000 1
 
2.4%
600681000 1
 
2.4%
27109000 1
 
2.4%
3300197000 1
 
2.4%
1667353000 1
 
2.4%
112027000 1
 
2.4%
193690000 1
 
2.4%
Other values (18) 18
42.9%
ValueCountFrequency (%)
0 15
35.7%
24676000 1
 
2.4%
27109000 1
 
2.4%
45225000 1
 
2.4%
70958000 1
 
2.4%
74355000 1
 
2.4%
75291000 1
 
2.4%
112027000 1
 
2.4%
115488000 1
 
2.4%
192182000 1
 
2.4%
ValueCountFrequency (%)
3570630000 1
2.4%
3418167000 1
2.4%
3300197000 1
2.4%
1778459000 1
2.4%
1688826000 1
2.4%
1667353000 1
2.4%
1656220000 1
2.4%
1594039000 1
2.4%
1413436000 1
2.4%
659039000 1
2.4%

징수율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.333333
Minimum0
Maximum100
Zeros12
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-11T01:44:08.204030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median96
Q398
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)98

Descriptive statistics

Standard deviation44.774049
Coefficient of variation (CV)0.69596967
Kurtosis-1.5302524
Mean64.333333
Median Absolute Deviation (MAD)4
Skewness-0.67843809
Sum2702
Variance2004.7154
MonotonicityNot monotonic
2023-12-11T01:44:08.367053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 12
28.6%
100 7
16.7%
96 6
14.3%
98 5
11.9%
89 2
 
4.8%
97 2
 
4.8%
95 2
 
4.8%
99 2
 
4.8%
27 1
 
2.4%
88 1
 
2.4%
Other values (2) 2
 
4.8%
ValueCountFrequency (%)
0 12
28.6%
25 1
 
2.4%
27 1
 
2.4%
36 1
 
2.4%
88 1
 
2.4%
89 2
 
4.8%
95 2
 
4.8%
96 6
14.3%
97 2
 
4.8%
98 5
11.9%
ValueCountFrequency (%)
100 7
16.7%
99 2
 
4.8%
98 5
11.9%
97 2
 
4.8%
96 6
14.3%
95 2
 
4.8%
89 2
 
4.8%
88 1
 
2.4%
36 1
 
2.4%
27 1
 
2.4%

Interactions

2023-12-11T01:44:02.657097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:58.228132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:59.434051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:00.270992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:01.096084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:01.885803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:02.784034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:58.438148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:59.583440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:00.402105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:01.232109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:02.006382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:02.923129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:58.655972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:59.712007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:00.533954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:01.378014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:02.129140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:03.056171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:58.953600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:59.864624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:00.691617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:01.523368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:02.274337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:03.191092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:59.150131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:59.985404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:00.830574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:01.651855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:02.378284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:03.358156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:43:59.297486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:00.143401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:00.972420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:01.771220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:02.534649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:44:08.515580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
과세년도1.0000.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.8880.9000.5900.7590.9440.926
부과금액0.0000.8881.0000.9890.1680.3640.6800.497
수납급액0.0000.9000.9891.0000.2070.4760.7270.244
환급금액0.0000.5900.1680.2071.0000.8120.6900.615
결손금액0.0000.7590.3640.4760.8121.0000.9240.862
미수납 금액0.0000.9440.6800.7270.6900.9241.0000.919
징수율0.0000.9260.4970.2440.6150.8620.9191.000
2023-12-11T01:44:08.701226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도
세목명1.0000.000
과세년도0.0001.000
2023-12-11T01:44:08.858986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과금액수납급액환급금액결손금액미수납 금액징수율과세년도세목명
부과금액1.0000.9730.7520.5310.7060.6510.0000.599
수납급액0.9731.0000.6640.4350.6110.7260.0000.619
환급금액0.7520.6641.0000.8090.9120.3190.0000.312
결손금액0.5310.4350.8091.0000.8450.0920.0000.450
미수납 금액0.7060.6110.9120.8451.0000.2110.0000.732
징수율0.6510.7260.3190.0920.2111.0000.0000.693
과세년도0.0000.0000.0000.0000.0000.0001.0000.000
세목명0.5990.6190.3120.4500.7320.6930.0001.000

Missing values

2023-12-11T01:44:03.566372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:44:04.184327image/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

시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
0부산광역시연제구264702017도축세000000
1부산광역시연제구264702017레저세70873180007087318000000100
2부산광역시연제구264702017재산세305281180002986907900014817000065903900098
3부산광역시연제구264702017주민세45799420004387616000757600014400019218200096
4부산광역시연제구264702017취득세621724290006209713800075893000075291000100
5부산광역시연제구264702017자동차세140756370001248155800016977600040000159403900089
6부산광역시연제구264702017과년도수입603987600016438330001396529000825413000357063000027
7부산광역시연제구264702017담배소비세000000
8부산광역시연제구264702017도시계획세000000
9부산광역시연제구264702017등록면허세5819415000579473900028254000024676000100
시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
32부산광역시연제구264702019취득세46008878000458968510001384200000112027000100
33부산광역시연제구264702019자동차세14716868000130453530001721010004162000166735300089
34부산광역시연제구264702019과년도수입645357500022972920001150177000856086000330019700036
35부산광역시연제구264702019담배소비세000000
36부산광역시연제구264702019도시계획세000000
37부산광역시연제구264702019등록면허세612311000060958480009986100015300027109000100
38부산광역시연제구264702019지방교육세165057450001590392900080185000113500060068100096
39부산광역시연제구264702019지방소득세43621423000419175180001618364000290469000141343600096
40부산광역시연제구264702019지방소비세000000
41부산광역시연제구264702019지역자원시설세45989470004524592000353300007435500098