Overview

Dataset statistics

Number of variables11
Number of observations80
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.6 KiB
Average record size in memory97.6 B

Variable types

Categorical4
Numeric7

Dataset

Description지방세 부과액에 대한 연도별 세목별 징수현황을 제공하여,지자체의 재정자주도·재정자립도 산출하는 기초 및 납세 협력도 및 조세 순응도를 확인하는 자료로 활용하는데 목적을 두고 있습니다.
Author울산광역시 울주군
URLhttps://www.data.go.kr/data/15080222/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
부과금액 is highly overall correlated with 수납급액 and 4 other fieldsHigh correlation
수납급액 is highly overall correlated with 부과금액 and 3 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
미수납금액 is highly overall correlated with 부과금액 and 4 other fieldsHigh correlation
징수율 is highly overall correlated with 세목명High correlation
세목명 is highly overall correlated with 부과금액 and 3 other fieldsHigh correlation
부과금액 has 16 (20.0%) zerosZeros
수납급액 has 16 (20.0%) zerosZeros
환급금액 has 23 (28.7%) zerosZeros
결손금액 has 34 (42.5%) zerosZeros
미수납금액 has 26 (32.5%) zerosZeros
징수율 has 16 (20.0%) zerosZeros

Reproduction

Analysis started2024-04-13 11:53:21.433330
Analysis finished2024-04-13 11:53:34.320388
Duration12.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size768.0 B
울산광역시
80 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
울산광역시 80
100.0%

Length

2024-04-13T20:53:34.429232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T20:53:34.598879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울산광역시 80
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size768.0 B
울주군
80 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
울주군 80
100.0%

Length

2024-04-13T20:53:34.769847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T20:53:34.932362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울주군 80
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size768.0 B
31710
80 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row31710
2nd row31710
3rd row31710
4th row31710
5th row31710

Common Values

ValueCountFrequency (%)
31710 80
100.0%

Length

2024-04-13T20:53:35.099751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T20:53:35.394800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
31710 80
100.0%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.45
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size848.0 B
2024-04-13T20:53:35.550220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2019
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7276603
Coefficient of variation (CV)0.00085551031
Kurtosis-1.2889692
Mean2019.45
Median Absolute Deviation (MAD)1.5
Skewness0.041238905
Sum161556
Variance2.9848101
MonotonicityIncreasing
2024-04-13T20:53:35.743873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2017 14
17.5%
2018 14
17.5%
2019 13
16.2%
2020 13
16.2%
2021 13
16.2%
2022 13
16.2%
ValueCountFrequency (%)
2017 14
17.5%
2018 14
17.5%
2019 13
16.2%
2020 13
16.2%
2021 13
16.2%
2022 13
16.2%
ValueCountFrequency (%)
2022 13
16.2%
2021 13
16.2%
2020 13
16.2%
2019 13
16.2%
2018 14
17.5%
2017 14
17.5%

세목명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size768.0 B
레저세
6 
재산세
6 
주민세
6 
취득세
6 
자동차세
6 
Other values (9)
50 

Length

Max length7
Median length5
Mean length4.425
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
레저세 6
 
7.5%
재산세 6
 
7.5%
주민세 6
 
7.5%
취득세 6
 
7.5%
자동차세 6
 
7.5%
과년도수입 6
 
7.5%
담배소비세 6
 
7.5%
도시계획세 6
 
7.5%
등록면허세 6
 
7.5%
지방교육세 6
 
7.5%
Other values (4) 20
25.0%

Length

2024-04-13T20:53:35.971445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
레저세 6
 
7.5%
재산세 6
 
7.5%
주민세 6
 
7.5%
취득세 6
 
7.5%
자동차세 6
 
7.5%
과년도수입 6
 
7.5%
담배소비세 6
 
7.5%
도시계획세 6
 
7.5%
등록면허세 6
 
7.5%
지방교육세 6
 
7.5%
Other values (4) 20
25.0%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct65
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6809992 × 1010
Minimum0
Maximum1.6505 × 1011
Zeros16
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size848.0 B
2024-04-13T20:53:36.207825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.8111502 × 109
median1.7765843 × 1010
Q35.7350457 × 1010
95-th percentile1.2115 × 1011
Maximum1.6505 × 1011
Range1.6505 × 1011
Interquartile range (IQR)4.9539307 × 1010

Descriptive statistics

Standard deviation4.1813657 × 1010
Coefficient of variation (CV)1.1359323
Kurtosis0.98838034
Mean3.6809992 × 1010
Median Absolute Deviation (MAD)1.7765843 × 1010
Skewness1.3560451
Sum2.9447994 × 1012
Variance1.7483819 × 1021
MonotonicityNot monotonic
2024-04-13T20:53:36.526371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16
 
20.0%
36638720000 1
 
1.2%
17407426000 1
 
1.2%
17603102000 1
 
1.2%
10363006000 1
 
1.2%
33305169000 1
 
1.2%
103000000000 1
 
1.2%
4095000000 1
 
1.2%
31285599000 1
 
1.2%
78521753000 1
 
1.2%
Other values (55) 55
68.8%
ValueCountFrequency (%)
0 16
20.0%
119104000 1
 
1.2%
2864448000 1
 
1.2%
4004785000 1
 
1.2%
4095000000 1
 
1.2%
9049867000 1
 
1.2%
9755752000 1
 
1.2%
10207985000 1
 
1.2%
10256866000 1
 
1.2%
10363006000 1
 
1.2%
ValueCountFrequency (%)
165050000000 1
1.2%
152000000000 1
1.2%
145000000000 1
1.2%
124000000000 1
1.2%
121000000000 1
1.2%
120000000000 1
1.2%
116000000000 1
1.2%
109000000000 1
1.2%
108000000000 1
1.2%
103000000000 1
1.2%

수납급액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct65
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5120753 × 1010
Minimum-1.1420051 × 1010
Maximum1.6225 × 1011
Zeros16
Zeros (%)20.0%
Negative2
Negative (%)2.5%
Memory size848.0 B
2024-04-13T20:53:36.776935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.1420051 × 1010
5-th percentile0
Q11.8737878 × 109
median1.7616236 × 1010
Q35.5203406 × 1010
95-th percentile1.2015 × 1011
Maximum1.6225 × 1011
Range1.7367005 × 1011
Interquartile range (IQR)5.3329618 × 1010

Descriptive statistics

Standard deviation4.1730005 × 1010
Coefficient of variation (CV)1.1881865
Kurtosis0.91549681
Mean3.5120753 × 1010
Median Absolute Deviation (MAD)1.7616236 × 1010
Skewness1.3318784
Sum2.8096603 × 1012
Variance1.7413933 × 1021
MonotonicityNot monotonic
2024-04-13T20:53:37.032375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16
 
20.0%
35746626000 1
 
1.2%
3559692000 1
 
1.2%
17603102000 1
 
1.2%
10351989000 1
 
1.2%
32375360000 1
 
1.2%
100000000000 1
 
1.2%
4095000000 1
 
1.2%
30765904000 1
 
1.2%
76157358000 1
 
1.2%
Other values (55) 55
68.8%
ValueCountFrequency (%)
-11420051000 1
 
1.2%
-1617346000 1
 
1.2%
0 16
20.0%
119104000 1
 
1.2%
1170785000 1
 
1.2%
2108122000 1
 
1.2%
2885410000 1
 
1.2%
3559692000 1
 
1.2%
4004785000 1
 
1.2%
4095000000 1
 
1.2%
ValueCountFrequency (%)
162250000000 1
1.2%
148000000000 1
1.2%
142000000000 1
1.2%
123000000000 1
1.2%
120000000000 1
1.2%
119000000000 1
1.2%
115000000000 1
1.2%
107000000000 1
1.2%
106000000000 1
1.2%
100000000000 1
1.2%

환급금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct58
Distinct (%)72.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.6618838 × 108
Minimum0
Maximum1.7832874 × 1010
Zeros23
Zeros (%)28.7%
Negative0
Negative (%)0.0%
Memory size848.0 B
2024-04-13T20:53:37.286251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median41818000
Q33.7849575 × 108
95-th percentile5.0230948 × 109
Maximum1.7832874 × 1010
Range1.7832874 × 1010
Interquartile range (IQR)3.7849575 × 108

Descriptive statistics

Standard deviation2.4302404 × 109
Coefficient of variation (CV)2.805672
Kurtosis30.818406
Mean8.6618838 × 108
Median Absolute Deviation (MAD)41818000
Skewness5.007685
Sum6.929507 × 1010
Variance5.9060686 × 1018
MonotonicityNot monotonic
2024-04-13T20:53:37.547827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 23
28.7%
56216000 1
 
1.2%
5192115000 1
 
1.2%
22265000 1
 
1.2%
41895000 1
 
1.2%
178026000 1
 
1.2%
1950751000 1
 
1.2%
13448000 1
 
1.2%
61841000 1
 
1.2%
26008000 1
 
1.2%
Other values (48) 48
60.0%
ValueCountFrequency (%)
0 23
28.7%
16000 1
 
1.2%
381000 1
 
1.2%
2369000 1
 
1.2%
4644000 1
 
1.2%
4665000 1
 
1.2%
6268000 1
 
1.2%
10501000 1
 
1.2%
11209000 1
 
1.2%
13448000 1
 
1.2%
ValueCountFrequency (%)
17832874000 1
1.2%
7880965000 1
1.2%
5343410000 1
1.2%
5192115000 1
1.2%
5014199000 1
1.2%
4504944000 1
1.2%
3793707000 1
1.2%
3623712000 1
1.2%
1950751000 1
1.2%
1905367000 1
1.2%

결손금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct47
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9593986 × 108
Minimum0
Maximum5.796782 × 109
Zeros34
Zeros (%)42.5%
Negative0
Negative (%)0.0%
Memory size848.0 B
2024-04-13T20:53:37.807039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median185500
Q38582000
95-th percentile2.9035922 × 109
Maximum5.796782 × 109
Range5.796782 × 109
Interquartile range (IQR)8582000

Descriptive statistics

Standard deviation1.0385296 × 109
Coefficient of variation (CV)3.509259
Kurtosis15.151787
Mean2.9593986 × 108
Median Absolute Deviation (MAD)185500
Skewness3.9349394
Sum2.3675189 × 1010
Variance1.0785438 × 1018
MonotonicityNot monotonic
2024-04-13T20:53:38.058058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 34
42.5%
7000 1
 
1.2%
2376000 1
 
1.2%
4440766000 1
 
1.2%
262000 1
 
1.2%
25977000 1
 
1.2%
373812000 1
 
1.2%
69328000 1
 
1.2%
2645000 1
 
1.2%
87026000 1
 
1.2%
Other values (37) 37
46.2%
ValueCountFrequency (%)
0 34
42.5%
7000 1
 
1.2%
12000 1
 
1.2%
72000 1
 
1.2%
76000 1
 
1.2%
91000 1
 
1.2%
173000 1
 
1.2%
198000 1
 
1.2%
262000 1
 
1.2%
499000 1
 
1.2%
ValueCountFrequency (%)
5796782000 1
1.2%
4440766000 1
1.2%
3885788000 1
1.2%
3702281000 1
1.2%
2861556000 1
1.2%
1239089000 1
1.2%
373812000 1
1.2%
247809000 1
1.2%
226165000 1
1.2%
185374000 1
1.2%

미수납금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct55
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4035845 × 109
Minimum0
Maximum1.1422943 × 1010
Zeros26
Zeros (%)32.5%
Negative0
Negative (%)0.0%
Memory size848.0 B
2024-04-13T20:53:38.319921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.18874 × 108
Q31.770819 × 109
95-th percentile8.8757052 × 109
Maximum1.1422943 × 1010
Range1.1422943 × 1010
Interquartile range (IQR)1.770819 × 109

Descriptive statistics

Standard deviation2.5469761 × 109
Coefficient of variation (CV)1.8146226
Kurtosis6.7261997
Mean1.4035845 × 109
Median Absolute Deviation (MAD)3.18874 × 108
Skewness2.6780209
Sum1.1228676 × 1011
Variance6.4870875 × 1018
MonotonicityNot monotonic
2024-04-13T20:53:38.576172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 26
32.5%
1737621000 1
 
1.2%
814470000 1
 
1.2%
1779348000 1
 
1.2%
9406968000 1
 
1.2%
10755000 1
 
1.2%
903832000 1
 
1.2%
1970090000 1
 
1.2%
450367000 1
 
1.2%
2361750000 1
 
1.2%
Other values (45) 45
56.2%
ValueCountFrequency (%)
0 26
32.5%
7241000 1
 
1.2%
8214000 1
 
1.2%
9002000 1
 
1.2%
9590000 1
 
1.2%
10755000 1
 
1.2%
10932000 1
 
1.2%
124041000 1
 
1.2%
151894000 1
 
1.2%
171035000 1
 
1.2%
ValueCountFrequency (%)
11422943000 1
1.2%
10582599000 1
1.2%
9406968000 1
1.2%
9188450000 1
1.2%
8859245000 1
1.2%
8159126000 1
1.2%
3733853000 1
1.2%
3494451000 1
1.2%
2733189000 1
1.2%
2628301000 1
1.2%

징수율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct51
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.963875
Minimum-398.68
Maximum100
Zeros16
Zeros (%)20.0%
Negative2
Negative (%)2.5%
Memory size848.0 B
2024-04-13T20:53:38.952705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-398.68
5-th percentile0
Q114.8275
median97.56
Q399.1225
95-th percentile100
Maximum100
Range498.68
Interquartile range (IQR)84.295

Descriptive statistics

Standard deviation67.871578
Coefficient of variation (CV)1.0135551
Kurtosis27.433017
Mean66.963875
Median Absolute Deviation (MAD)1.915
Skewness-4.363207
Sum5357.11
Variance4606.5511
MonotonicityNot monotonic
2024-04-13T20:53:39.207598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 16
 
20.0%
100.0 10
 
12.5%
99.89 3
 
3.8%
96.99 3
 
3.8%
99.91 2
 
2.5%
14.37 1
 
1.2%
98.93 1
 
1.2%
96.94 1
 
1.2%
20.45 1
 
1.2%
97.21 1
 
1.2%
Other values (41) 41
51.2%
ValueCountFrequency (%)
-398.68 1
 
1.2%
-15.51 1
 
1.2%
0.0 16
20.0%
10.09 1
 
1.2%
14.37 1
 
1.2%
14.98 1
 
1.2%
20.45 1
 
1.2%
95.8 1
 
1.2%
96.2 1
 
1.2%
96.23 1
 
1.2%
ValueCountFrequency (%)
100.0 10
12.5%
99.93 1
 
1.2%
99.91 2
 
2.5%
99.89 3
 
3.8%
99.64 1
 
1.2%
99.63 1
 
1.2%
99.29 1
 
1.2%
99.13 1
 
1.2%
99.12 1
 
1.2%
99.08 1
 
1.2%

Interactions

2024-04-13T20:53:32.671295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:23.112903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:24.856221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:26.626864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:28.374389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:30.281951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:31.536692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:32.853886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:23.365588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:25.104158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:26.871627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:28.622998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:30.530629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:31.773401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:33.102679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:23.615998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:25.355173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:27.123075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:28.878262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:30.789700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:31.930750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:33.302251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:23.866412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:25.611839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:27.373646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:29.140537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:30.940830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:32.082637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:33.455443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:24.122290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:25.882030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:27.631755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:29.403186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:31.099717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:32.239536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:33.601780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:24.372420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:26.136356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:27.882644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:29.657377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:31.248114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:32.390670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:33.741940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:24.617047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:26.383078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:28.129608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:30.033801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:31.395423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:53:32.532491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-13T20:53:39.379362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명부과금액수납급액환급금액결손금액미수납금액징수율
과세년도1.0000.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.9020.9150.6170.4040.8830.928
부과금액0.0000.9021.0000.9960.6410.0000.7530.567
수납급액0.0000.9150.9961.0000.6410.0000.7570.721
환급금액0.0000.6170.6410.6411.0000.8050.7450.564
결손금액0.0000.4040.0000.0000.8051.0000.8760.672
미수납금액0.0000.8830.7530.7570.7450.8761.0000.742
징수율0.0000.9280.5670.7210.5640.6720.7421.000
2024-04-13T20:53:39.578239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도부과금액수납급액환급금액결손금액미수납금액징수율세목명
과세년도1.0000.0850.0800.0810.184-0.0130.2320.000
부과금액0.0851.0000.9770.7230.5810.7220.2980.643
수납급액0.0800.9771.0000.6030.4600.5930.3800.675
환급금액0.0810.7230.6031.0000.8210.912-0.0150.354
결손금액0.1840.5810.4600.8211.0000.813-0.0830.195
미수납금액-0.0130.7220.5930.9120.8131.000-0.1680.513
징수율0.2320.2980.380-0.015-0.083-0.1681.0000.621
세목명0.0000.6430.6750.3540.1950.5130.6211.000

Missing values

2024-04-13T20:53:33.936664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-13T20:53:34.207583image/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

시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납금액징수율
0울산광역시울주군317102017도축세000000.0
1울산광역시울주군317102017레저세000000.0
2울산광역시울주군317102017재산세58306242000565686210001223520000173762100097.02
3울산광역시울주군317102017주민세171135030001689220700017492000700022128900098.71
4울산광역시울주군317102017취득세1160000000001150000000003905400000102026600099.12
5울산광역시울주군317102017자동차세5823941500056041587000247457000808000219702000096.23
6울산광역시울주군317102017과년도수입11598324000117078500050141990001239089000918845000010.09
7울산광역시울주군317102017담배소비세1859606000018596060000000100.0
8울산광역시울주군317102017도시계획세000000.0
9울산광역시울주군317102017등록면허세1025686600010249625000417410000724100099.93
시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납금액징수율
70울산광역시울주군317102022취득세88520775000881892420004310320001416900031736400099.63
71울산광역시울주군317102022자동차세49027837000473114110003770100001649000171477700096.5
72울산광역시울주군317102022과년도수입10427568000-1617346000788096500038857880008159126000-15.51
73울산광역시울주군317102022담배소비세17629371000176293710001600000100.0
74울산광역시울주군317102022도시계획세000000.0
75울산광역시울주군317102022등록면허세9049867000904008800041075000777000900200099.89
76울산광역시울주군317102022지방교육세3481273200034072795000173491000286400073707300097.87
77울산광역시울주군317102022지방소득세1650500000001622500000003793707000171939000262830100098.3
78울산광역시울주군317102022지방소비세1020798500010207985000000100.0
79울산광역시울주군317102022지역자원시설세34517987000343919990006268000194700012404100099.64