Overview

Dataset statistics

Number of variables12
Number of observations66
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory106.0 B

Variable types

Categorical6
Numeric6

Dataset

Description광주광역시 남구 2023년 기준 최근 5개년 징수현황 데이터 입니다.(시도명,시군구명,자치단체코드,세목명,부과금액,수납금액,환급금액,결손금액,미수납금액,징수율)
URLhttps://www.data.go.kr/data/15116634/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일자 has constant value ""Constant
부과금액 is highly overall correlated with 수납급액 and 4 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 3 other fieldsHigh correlation
미수납 금액 is highly overall correlated with 부과금액 and 3 other fieldsHigh correlation
징수율 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 징수율 High correlation
부과금액 has 17 (25.8%) zerosZeros
수납급액 has 17 (25.8%) zerosZeros
환급금액 has 21 (31.8%) zerosZeros
결손금액 has 21 (31.8%) zerosZeros
미수납 금액 has 21 (31.8%) zerosZeros
징수율 has 17 (25.8%) zerosZeros

Reproduction

Analysis started2023-12-12 00:00:03.682864
Analysis finished2023-12-12 00:00:07.834424
Duration4.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
광주광역시
66 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주광역시 66
100.0%

Length

2023-12-12T09:00:07.897411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:00:07.987548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주광역시 66
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
남구
66 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남구 66
100.0%

Length

2023-12-12T09:00:08.080725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:00:08.172774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남구 66
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
29155
66 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row29155
2nd row29155
3rd row29155
4th row29155
5th row29155

Common Values

ValueCountFrequency (%)
29155 66
100.0%

Length

2023-12-12T09:00:08.269202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:00:08.363740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
29155 66
100.0%

과세년도
Categorical

Distinct5
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size660.0 B
2018
14 
2019
13 
2020
13 
2021
13 
2022
13 

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 14
21.2%
2019 13
19.7%
2020 13
19.7%
2021 13
19.7%
2022 13
19.7%

Length

2023-12-12T09:00:08.486284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:00:08.597034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 14
21.2%
2019 13
19.7%
2020 13
19.7%
2021 13
19.7%
2022 13
19.7%

세목명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size660.0 B
레저세
5 
재산세
5 
주민세
5 
취득세
5 
자동차세
5 
Other values (9)
41 

Length

Max length7
Median length5
Mean length4.4393939
Min length3

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
레저세 5
 
7.6%
재산세 5
 
7.6%
주민세 5
 
7.6%
취득세 5
 
7.6%
자동차세 5
 
7.6%
과년도수입 5
 
7.6%
담배소비세 5
 
7.6%
도시계획세 5
 
7.6%
등록면허세 5
 
7.6%
지방교육세 5
 
7.6%
Other values (4) 16
24.2%

Length

2023-12-12T09:00:08.738709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
레저세 5
 
7.6%
재산세 5
 
7.6%
주민세 5
 
7.6%
취득세 5
 
7.6%
자동차세 5
 
7.6%
과년도수입 5
 
7.6%
담배소비세 5
 
7.6%
도시계획세 5
 
7.6%
등록면허세 5
 
7.6%
지방교육세 5
 
7.6%
Other values (4) 16
24.2%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct50
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5129952 × 1010
Minimum0
Maximum9.6675308 × 1010
Zeros17
Zeros (%)25.8%
Negative0
Negative (%)0.0%
Memory size726.0 B
2023-12-12T09:00:08.874000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q128518500
median4.563971 × 109
Q31.9590903 × 1010
95-th percentile6.9662451 × 1010
Maximum9.6675308 × 1010
Range9.6675308 × 1010
Interquartile range (IQR)1.9562384 × 1010

Descriptive statistics

Standard deviation2.1755226 × 1010
Coefficient of variation (CV)1.4378913
Kurtosis3.9144312
Mean1.5129952 × 1010
Median Absolute Deviation (MAD)4.563971 × 109
Skewness2.0194541
Sum9.9857683 × 1011
Variance4.7328985 × 1020
MonotonicityNot monotonic
2023-12-12T09:00:09.066652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17
25.8%
3912765000 1
 
1.5%
3706378000 1
 
1.5%
32269241000 1
 
1.5%
3426575000 1
 
1.5%
96675308000 1
 
1.5%
19677503000 1
 
1.5%
204613000 1
 
1.5%
5725817000 1
 
1.5%
17068319000 1
 
1.5%
Other values (40) 40
60.6%
ValueCountFrequency (%)
0 17
25.8%
114074000 1
 
1.5%
204613000 1
 
1.5%
1842459000 1
 
1.5%
2789673000 1
 
1.5%
3053433000 1
 
1.5%
3214624000 1
 
1.5%
3223223000 1
 
1.5%
3307815000 1
 
1.5%
3309054000 1
 
1.5%
ValueCountFrequency (%)
96675308000 1
1.5%
81565261000 1
1.5%
73088261000 1
1.5%
72093540000 1
1.5%
62369185000 1
1.5%
40647749000 1
1.5%
40240349000 1
1.5%
40089231000 1
1.5%
36659834000 1
1.5%
35287082000 1
1.5%

수납급액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct50
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4675196 × 1010
Minimum-1.124735 × 109
Maximum9.6670615 × 1010
Zeros17
Zeros (%)25.8%
Negative1
Negative (%)1.5%
Memory size726.0 B
2023-12-12T09:00:09.192222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.124735 × 109
5-th percentile0
Q10
median4.3442615 × 109
Q31.8102195 × 1010
95-th percentile6.9581521 × 1010
Maximum9.6670615 × 1010
Range9.779535 × 1010
Interquartile range (IQR)1.8102195 × 1010

Descriptive statistics

Standard deviation2.1643788 × 1010
Coefficient of variation (CV)1.4748551
Kurtosis4.1856203
Mean1.4675196 × 1010
Median Absolute Deviation (MAD)4.3442615 × 109
Skewness2.0787701
Sum9.6856295 × 1011
Variance4.6845355 × 1020
MonotonicityNot monotonic
2023-12-12T09:00:09.592052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17
25.8%
3816867000 1
 
1.5%
3652473000 1
 
1.5%
31668342000 1
 
1.5%
3300298000 1
 
1.5%
96670615000 1
 
1.5%
18216944000 1
 
1.5%
-1124735000 1
 
1.5%
5711395000 1
 
1.5%
16542920000 1
 
1.5%
Other values (40) 40
60.6%
ValueCountFrequency (%)
-1124735000 1
 
1.5%
0 17
25.8%
114074000 1
 
1.5%
411813000 1
 
1.5%
1271496000 1
 
1.5%
2405294000 1
 
1.5%
2574518000 1
 
1.5%
2951634000 1
 
1.5%
2992458000 1
 
1.5%
3066691000 1
 
1.5%
ValueCountFrequency (%)
96670615000 1
1.5%
81470952000 1
1.5%
72834161000 1
1.5%
72060127000 1
1.5%
62145704000 1
1.5%
39082554000 1
1.5%
38547428000 1
1.5%
38478005000 1
1.5%
35330032000 1
1.5%
34263167000 1
1.5%

환급금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4747147 × 108
Minimum0
Maximum3.919513 × 109
Zeros21
Zeros (%)31.8%
Negative0
Negative (%)0.0%
Memory size726.0 B
2023-12-12T09:00:09.715240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median14047500
Q32.7735125 × 108
95-th percentile1.6493258 × 109
Maximum3.919513 × 109
Range3.919513 × 109
Interquartile range (IQR)2.7735125 × 108

Descriptive statistics

Standard deviation7.4272243 × 108
Coefficient of variation (CV)2.1375062
Kurtosis9.8712407
Mean3.4747147 × 108
Median Absolute Deviation (MAD)14047500
Skewness2.9834184
Sum2.2933117 × 1010
Variance5.516366 × 1017
MonotonicityNot monotonic
2023-12-12T09:00:09.854203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 21
31.8%
1686668000 1
 
1.5%
1333408000 1
 
1.5%
1397000 1
 
1.5%
21766000 1
 
1.5%
809000 1
 
1.5%
214094000 1
 
1.5%
424214000 1
 
1.5%
3919513000 1
 
1.5%
21905000 1
 
1.5%
Other values (36) 36
54.5%
ValueCountFrequency (%)
0 21
31.8%
273000 1
 
1.5%
404000 1
 
1.5%
654000 1
 
1.5%
809000 1
 
1.5%
1315000 1
 
1.5%
1397000 1
 
1.5%
1781000 1
 
1.5%
2152000 1
 
1.5%
2345000 1
 
1.5%
ValueCountFrequency (%)
3919513000 1
1.5%
3079113000 1
1.5%
1686668000 1
1.5%
1652534000 1
1.5%
1639701000 1
1.5%
1592010000 1
1.5%
1509338000 1
1.5%
1455058000 1
1.5%
1333408000 1
1.5%
902793000 1
1.5%

결손금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3521539 × 108
Minimum0
Maximum1.085808 × 109
Zeros21
Zeros (%)31.8%
Negative0
Negative (%)0.0%
Memory size726.0 B
2023-12-12T09:00:09.998740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11081500
Q31.210825 × 108
95-th percentile6.95341 × 108
Maximum1.085808 × 109
Range1.085808 × 109
Interquartile range (IQR)1.210825 × 108

Descriptive statistics

Standard deviation2.5809156 × 108
Coefficient of variation (CV)1.9087439
Kurtosis4.3832767
Mean1.3521539 × 108
Median Absolute Deviation (MAD)11081500
Skewness2.2676638
Sum8.924216 × 109
Variance6.6611252 × 1016
MonotonicityNot monotonic
2023-12-12T09:00:10.134305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 21
31.8%
180619000 1
 
1.5%
645124000 1
 
1.5%
8885000 1
 
1.5%
33558000 1
 
1.5%
8648000 1
 
1.5%
251000 1
 
1.5%
187301000 1
 
1.5%
630706000 1
 
1.5%
7123000 1
 
1.5%
Other values (36) 36
54.5%
ValueCountFrequency (%)
0 21
31.8%
251000 1
 
1.5%
2216000 1
 
1.5%
2325000 1
 
1.5%
3679000 1
 
1.5%
3855000 1
 
1.5%
3900000 1
 
1.5%
6346000 1
 
1.5%
7123000 1
 
1.5%
8648000 1
 
1.5%
ValueCountFrequency (%)
1085808000 1
1.5%
1006106000 1
1.5%
806771000 1
1.5%
712080000 1
1.5%
645124000 1
1.5%
644076000 1
1.5%
630706000 1
1.5%
630371000 1
1.5%
377014000 1
1.5%
356549000 1
1.5%

미수납 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1954047 × 108
Minimum0
Maximum1.720766 × 109
Zeros21
Zeros (%)31.8%
Negative0
Negative (%)0.0%
Memory size726.0 B
2023-12-12T09:00:10.253640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median75121000
Q35.313305 × 108
95-th percentile1.2621162 × 109
Maximum1.720766 × 109
Range1.720766 × 109
Interquartile range (IQR)5.313305 × 108

Descriptive statistics

Standard deviation4.5297599 × 108
Coefficient of variation (CV)1.4175857
Kurtosis1.6306597
Mean3.1954047 × 108
Median Absolute Deviation (MAD)75121000
Skewness1.5419424
Sum2.1089671 × 1010
Variance2.0518725 × 1017
MonotonicityNot monotonic
2023-12-12T09:00:10.401152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 21
31.8%
843296000 1
 
1.5%
1117220000 1
 
1.5%
45020000 1
 
1.5%
567341000 1
 
1.5%
117629000 1
 
1.5%
4442000 1
 
1.5%
1273258000 1
 
1.5%
698642000 1
 
1.5%
7299000 1
 
1.5%
Other values (36) 36
54.5%
ValueCountFrequency (%)
0 21
31.8%
4442000 1
 
1.5%
7299000 1
 
1.5%
8339000 1
 
1.5%
11190000 1
 
1.5%
11881000 1
 
1.5%
14300000 1
 
1.5%
15684000 1
 
1.5%
26366000 1
 
1.5%
28863000 1
 
1.5%
ValueCountFrequency (%)
1720766000 1
1.5%
1631526000 1
1.5%
1541128000 1
1.5%
1273258000 1
1.5%
1228691000 1
1.5%
1117220000 1
1.5%
1004810000 1
1.5%
934824000 1
1.5%
843296000 1
1.5%
829723000 1
1.5%

징수율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct44
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.346061
Minimum-549.69
Maximum100
Zeros17
Zeros (%)25.8%
Negative1
Negative (%)1.5%
Memory size726.0 B
2023-12-12T09:00:10.537375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-549.69
5-th percentile0
Q10
median96.18
Q398.4925
95-th percentile100
Maximum100
Range649.69
Interquartile range (IQR)98.4925

Descriptive statistics

Standard deviation87.321415
Coefficient of variation (CV)1.4713936
Kurtosis36.87268
Mean59.346061
Median Absolute Deviation (MAD)3.61
Skewness-5.4112985
Sum3916.84
Variance7625.0295
MonotonicityNot monotonic
2023-12-12T09:00:10.681364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0.0 17
25.8%
100.0 5
 
7.6%
96.15 2
 
3.0%
99.75 2
 
3.0%
99.7 1
 
1.5%
-549.69 1
 
1.5%
96.36 1
 
1.5%
95.62 1
 
1.5%
98.7 1
 
1.5%
98.55 1
 
1.5%
Other values (34) 34
51.5%
ValueCountFrequency (%)
-549.69 1
 
1.5%
0.0 17
25.8%
22.35 1
 
1.5%
45.58 1
 
1.5%
59.46 1
 
1.5%
63.86 1
 
1.5%
88.94 1
 
1.5%
90.96 1
 
1.5%
91.86 1
 
1.5%
92.58 1
 
1.5%
ValueCountFrequency (%)
100.0 5
7.6%
99.95 1
 
1.5%
99.88 1
 
1.5%
99.8 1
 
1.5%
99.75 2
 
3.0%
99.7 1
 
1.5%
99.65 1
 
1.5%
99.64 1
 
1.5%
99.59 1
 
1.5%
98.7 1
 
1.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
2022-12-31
66 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-31
2nd row2022-12-31
3rd row2022-12-31
4th row2022-12-31
5th row2022-12-31

Common Values

ValueCountFrequency (%)
2022-12-31 66
100.0%

Length

2023-12-12T09:00:10.803671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:00:10.898888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-31 66
100.0%

Interactions

2023-12-12T09:00:06.981456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:04.025928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:04.646949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:05.291866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:05.837418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:06.366550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:07.060603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:04.130921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:04.740202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:05.385520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:05.922835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:06.486141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:07.141400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:04.231659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:04.833400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:05.469382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:06.016397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:06.593093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:07.253287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:04.346652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:04.955380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:05.558814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:06.108084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:06.717124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:07.349627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:04.453770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:05.069147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:05.640372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:06.184931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:06.800522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:07.451664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:04.553715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:05.182773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:05.738724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:06.275423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:00:06.890660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:00:10.954905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
과세년도1.0000.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.8090.8070.7860.5340.7480.971
부과금액0.0000.8091.0001.0000.4340.5450.7090.388
수납급액0.0000.8071.0001.0000.4730.5660.6570.388
환급금액0.0000.7860.4340.4731.0000.7410.7870.274
결손금액0.0000.5340.5450.5660.7411.0000.7280.000
미수납 금액0.0000.7480.7090.6570.7870.7281.0000.364
징수율0.0000.9710.3880.3880.2740.0000.3641.000
2023-12-12T09:00:11.055719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도
세목명1.0000.000
과세년도0.0001.000
2023-12-12T09:00:11.136450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과금액수납급액환급금액결손금액미수납 금액징수율과세년도세목명
부과금액1.0000.9880.7150.6210.6620.6760.0000.489
수납급액0.9881.0000.6470.5630.6090.7000.0000.488
환급금액0.7150.6471.0000.8750.8880.2300.0000.386
결손금액0.6210.5630.8751.0000.9030.1620.0000.248
미수납 금액0.6620.6090.8880.9031.0000.1300.0000.403
징수율0.6760.7000.2300.1620.1301.0000.0000.545
과세년도0.0000.0000.0000.0000.0000.0001.0000.000
세목명0.4890.4880.3860.2480.4030.5450.0001.000

Missing values

2023-12-12T09:00:07.603966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:00:07.770029image/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 금액징수율데이터기준일자
0광주광역시남구291552018도축세000000.02022-12-31
1광주광역시남구291552018레저세000000.02022-12-31
2광주광역시남구291552018재산세23538914000229772450001984100037701400018465500097.612022-12-31
3광주광역시남구291552018주민세3214624000299245800039200003367000018849600093.092022-12-31
4광주광역시남구291552018취득세62369185000621457040002890200001994800020353300099.642022-12-31
5광주광역시남구291552018자동차세1815927500016151129000324706000287380000172076600088.942022-12-31
6광주광역시남구291552018과년도수입43294800002574518000902793000100610600074885600059.462022-12-31
7광주광역시남구291552018담배소비세000000.02022-12-31
8광주광역시남구291552018도시계획세000000.02022-12-31
9광주광역시남구291552018등록면허세480402600047844870001290900038550001568400099.592022-12-31
시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율데이터기준일자
56광주광역시남구291552022취득세73088261000728341610003030860001870350006706500099.652022-12-31
57광주광역시남구291552022자동차세198956590001857317800044758000093790000122869100093.352022-12-31
58광주광역시남구291552022과년도수입278967300012714960001652534000108580800043236900045.582022-12-31
59광주광역시남구291552022담배소비세000000.02022-12-31
60광주광역시남구291552022도시계획세000000.02022-12-31
61광주광역시남구291552022등록면허세479846200047842560001952100023250001188100099.72022-12-31
62광주광역시남구291552022지방교육세15405323000149250360001517200005155100042873600096.882022-12-31
63광주광역시남구291552022지방소득세4064774900039082554000163970100063037100093482400096.152022-12-31
64광주광역시남구291552022지방소비세1230494700012304947000000100.02022-12-31
65광주광역시남구291552022지역자원시설세395555200039042670001315000249190002636600098.72022-12-31