Overview

Dataset statistics

Number of variables12
Number of observations39
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory107.4 B

Variable types

Categorical5
Numeric6
DateTime1

Dataset

Description인천광역시 중구에서 부과되는 지방세 세목별 징수현황에 대한 데이터로 세목명, 부과금액, 수납금액, 환급금액, 결손금액, 징수율 등을 제공합니다.
URLhttps://www.data.go.kr/data/15079265/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
부과금액 is highly overall correlated with 수납급액 and 3 other fieldsHigh correlation
수납급액 is highly overall correlated with 부과금액 and 1 other fieldsHigh correlation
환급금액 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
결손금액 is highly overall correlated with 환급금액 and 1 other fieldsHigh correlation
미수납 금액 is highly overall correlated with 부과금액 and 3 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 6 (15.4%) zerosZeros
수납급액 has 6 (15.4%) zerosZeros
환급금액 has 12 (30.8%) zerosZeros
결손금액 has 17 (43.6%) zerosZeros
미수납 금액 has 12 (30.8%) zerosZeros
징수율 has 6 (15.4%) zerosZeros

Reproduction

Analysis started2023-12-12 01:32:17.642544
Analysis finished2023-12-12 01:32:22.648086
Duration5.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
인천광역시
39 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 39
100.0%

Length

2023-12-12T10:32:22.734642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:32:22.850390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 39
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
중구
39 

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 39
100.0%

Length

2023-12-12T10:32:22.962731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:32:23.091366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 39
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
28110
39 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28110
2nd row28110
3rd row28110
4th row28110
5th row28110

Common Values

ValueCountFrequency (%)
28110 39
100.0%

Length

2023-12-12T10:32:23.211684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:32:23.311375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28110 39
100.0%

과세년도
Categorical

Distinct3
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size444.0 B
2020
13 
2021
13 
2022
13 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 13
33.3%
2021 13
33.3%
2022 13
33.3%

Length

2023-12-12T10:32:23.438435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:32:23.568605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 13
33.3%
2021 13
33.3%
2022 13
33.3%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size444.0 B
레저세
3 
재산세
3 
주민세
3 
취득세
3 
자동차세
3 
Other values (8)
24 

Length

Max length7
Median length5
Mean length4.4615385
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
레저세 3
 
7.7%
재산세 3
 
7.7%
주민세 3
 
7.7%
취득세 3
 
7.7%
자동차세 3
 
7.7%
과년도수입 3
 
7.7%
담배소비세 3
 
7.7%
도시계획세 3
 
7.7%
등록면허세 3
 
7.7%
지방교육세 3
 
7.7%
Other values (3) 9
23.1%

Length

2023-12-12T10:32:23.700043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
레저세 3
 
7.7%
재산세 3
 
7.7%
주민세 3
 
7.7%
취득세 3
 
7.7%
자동차세 3
 
7.7%
과년도수입 3
 
7.7%
담배소비세 3
 
7.7%
도시계획세 3
 
7.7%
등록면허세 3
 
7.7%
지방교육세 3
 
7.7%
Other values (3) 9
23.1%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1344941 × 1010
Minimum-1.4597873 × 1010
Maximum2.4403146 × 1011
Zeros6
Zeros (%)15.4%
Negative1
Negative (%)2.6%
Memory size483.0 B
2023-12-12T10:32:23.838167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.4597873 × 1010
5-th percentile0
Q11.280752 × 109
median1.316677 × 1010
Q34.5538203 × 1010
95-th percentile1.4497593 × 1011
Maximum2.4403146 × 1011
Range2.5862934 × 1011
Interquartile range (IQR)4.4257451 × 1010

Descriptive statistics

Standard deviation6.3061421 × 1010
Coefficient of variation (CV)1.5252512
Kurtosis3.0885486
Mean4.1344941 × 1010
Median Absolute Deviation (MAD)1.2930516 × 1010
Skewness1.8871129
Sum1.6124527 × 1012
Variance3.9767428 × 1021
MonotonicityNot monotonic
2023-12-12T10:32:23.988809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 6
 
15.4%
1392504000 1
 
2.6%
244031465000 1
 
2.6%
79989967000 1
 
2.6%
260000000 1
 
2.6%
14291256000 1
 
2.6%
5945555000 1
 
2.6%
135711109000 1
 
2.6%
21173359000 1
 
2.6%
13905334000 1
 
2.6%
Other values (24) 24
61.5%
ValueCountFrequency (%)
-14597873000 1
 
2.6%
0 6
15.4%
236254000 1
 
2.6%
260000000 1
 
2.6%
1169000000 1
 
2.6%
1392504000 1
 
2.6%
2575693000 1
 
2.6%
5945555000 1
 
2.6%
7817669000 1
 
2.6%
9672465000 1
 
2.6%
ValueCountFrequency (%)
244031465000 1
2.6%
228359288000 1
2.6%
135711109000 1
2.6%
131502535000 1
2.6%
127771506000 1
2.6%
123727441000 1
2.6%
115296334000 1
2.6%
101281686000 1
2.6%
79989967000 1
2.6%
48344497000 1
2.6%

수납급액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9884358 × 1010
Minimum-2.5342654 × 1010
Maximum2.4313547 × 1011
Zeros6
Zeros (%)15.4%
Negative2
Negative (%)5.1%
Memory size483.0 B
2023-12-12T10:32:24.211953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.5342654 × 1010
5-th percentile-30174300
Q14.967995 × 108
median1.1945322 × 1010
Q34.456555 × 1010
95-th percentile1.4241576 × 1011
Maximum2.4313547 × 1011
Range2.6847813 × 1011
Interquartile range (IQR)4.406875 × 1010

Descriptive statistics

Standard deviation6.3059816 × 1010
Coefficient of variation (CV)1.5810664
Kurtosis3.1786565
Mean3.9884358 × 1010
Median Absolute Deviation (MAD)1.1945322 × 1010
Skewness1.8904248
Sum1.5554899 × 1012
Variance3.9765404 × 1021
MonotonicityNot monotonic
2023-12-12T10:32:24.394182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 6
 
15.4%
1392504000 1
 
2.6%
243135473000 1
 
2.6%
77933813000 1
 
2.6%
260000000 1
 
2.6%
13794486000 1
 
2.6%
5945555000 1
 
2.6%
132888374000 1
 
2.6%
20936725000 1
 
2.6%
12036830000 1
 
2.6%
Other values (24) 24
61.5%
ValueCountFrequency (%)
-25342654000 1
 
2.6%
-301743000 1
 
2.6%
0 6
15.4%
236254000 1
 
2.6%
260000000 1
 
2.6%
733599000 1
 
2.6%
1169000000 1
 
2.6%
1392504000 1
 
2.6%
2575693000 1
 
2.6%
5945555000 1
 
2.6%
ValueCountFrequency (%)
243135473000 1
2.6%
228162263000 1
2.6%
132888374000 1
2.6%
130989109000 1
2.6%
124741832000 1
2.6%
120990583000 1
2.6%
111903531000 1
2.6%
98802266000 1
2.6%
77933813000 1
2.6%
47329895000 1
2.6%

환급금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4791937 × 109
Minimum0
Maximum3.0596805 × 1010
Zeros12
Zeros (%)30.8%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T10:32:24.817648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median38278000
Q32.497755 × 108
95-th percentile6.7013072 × 109
Maximum3.0596805 × 1010
Range3.0596805 × 1010
Interquartile range (IQR)2.497755 × 108

Descriptive statistics

Standard deviation5.0779616 × 109
Coefficient of variation (CV)3.4329254
Kurtosis30.153473
Mean1.4791937 × 109
Median Absolute Deviation (MAD)38278000
Skewness5.2826285
Sum5.7688555 × 1010
Variance2.5785694 × 1019
MonotonicityNot monotonic
2023-12-12T10:32:24.952201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 12
30.8%
30351000 1
 
2.6%
6848000 1
 
2.6%
2758649000 1
 
2.6%
146026000 1
 
2.6%
54456000 1
 
2.6%
6924860000 1
 
2.6%
221708000 1
 
2.6%
824925000 1
 
2.6%
3901000 1
 
2.6%
Other values (18) 18
46.2%
ValueCountFrequency (%)
0 12
30.8%
3901000 1
 
2.6%
4183000 1
 
2.6%
6848000 1
 
2.6%
7142000 1
 
2.6%
7720000 1
 
2.6%
17535000 1
 
2.6%
30351000 1
 
2.6%
38278000 1
 
2.6%
40072000 1
 
2.6%
ValueCountFrequency (%)
30596805000 1
2.6%
6924860000 1
2.6%
6676468000 1
2.6%
4749299000 1
2.6%
2758649000 1
2.6%
1974775000 1
2.6%
1012052000 1
2.6%
824925000 1
2.6%
691721000 1
2.6%
277843000 1
2.6%

결손금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5537677 × 108
Minimum0
Maximum2.543597 × 109
Zeros17
Zeros (%)43.6%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T10:32:25.133988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median165000
Q36630500
95-th percentile1.2726801 × 109
Maximum2.543597 × 109
Range2.543597 × 109
Interquartile range (IQR)6630500

Descriptive statistics

Standard deviation4.9683555 × 108
Coefficient of variation (CV)3.197618
Kurtosis14.929991
Mean1.5537677 × 108
Median Absolute Deviation (MAD)165000
Skewness3.7520381
Sum6.059694 × 109
Variance2.4684557 × 1017
MonotonicityNot monotonic
2023-12-12T10:32:25.274246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 17
43.6%
165000 1
 
2.6%
781000 1
 
2.6%
108333000 1
 
2.6%
2834000 1
 
2.6%
1501000 1
 
2.6%
1268892000 1
 
2.6%
1969000 1
 
2.6%
149000 1
 
2.6%
13858000 1
 
2.6%
Other values (13) 13
33.3%
ValueCountFrequency (%)
0 17
43.6%
10000 1
 
2.6%
149000 1
 
2.6%
165000 1
 
2.6%
166000 1
 
2.6%
222000 1
 
2.6%
781000 1
 
2.6%
1501000 1
 
2.6%
1827000 1
 
2.6%
1969000 1
 
2.6%
ValueCountFrequency (%)
2543597000 1
2.6%
1306773000 1
2.6%
1268892000 1
2.6%
721269000 1
2.6%
108333000 1
2.6%
33749000 1
2.6%
18622000 1
2.6%
16032000 1
2.6%
13858000 1
2.6%
7159000 1
2.6%

미수납 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3052068 × 109
Minimum0
Maximum8.201184 × 109
Zeros12
Zeros (%)30.8%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T10:32:25.414200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.22339 × 108
Q31.7262235 × 109
95-th percentile6.9814546 × 109
Maximum8.201184 × 109
Range8.201184 × 109
Interquartile range (IQR)1.7262235 × 109

Descriptive statistics

Standard deviation2.1252408 × 109
Coefficient of variation (CV)1.628279
Kurtosis5.0569703
Mean1.3052068 × 109
Median Absolute Deviation (MAD)4.22339 × 108
Skewness2.3151987
Sum5.0903065 × 1010
Variance4.5166483 × 1018
MonotonicityNot monotonic
2023-12-12T10:32:25.558379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 12
30.8%
43114000 1
 
2.6%
518234000 1
 
2.6%
3284470000 1
 
2.6%
1011768000 1
 
2.6%
51864000 1
 
2.6%
6850520000 1
 
2.6%
1866535000 1
 
2.6%
895992000 1
 
2.6%
236485000 1
 
2.6%
Other values (18) 18
46.2%
ValueCountFrequency (%)
0 12
30.8%
39148000 1
 
2.6%
43114000 1
 
2.6%
51864000 1
 
2.6%
180993000 1
 
2.6%
194841000 1
 
2.6%
236485000 1
 
2.6%
248195000 1
 
2.6%
422339000 1
 
2.6%
478148000 1
 
2.6%
ValueCountFrequency (%)
8201184000 1
2.6%
8159866000 1
2.6%
6850520000 1
2.6%
3284470000 1
2.6%
3029674000 1
2.6%
2808877000 1
2.6%
2703109000 1
2.6%
2479420000 1
2.6%
1866535000 1
2.6%
1751748000 1
2.6%

징수율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79.511538
Minimum-3.86
Maximum173.61
Zeros6
Zeros (%)15.4%
Negative1
Negative (%)2.6%
Memory size483.0 B
2023-12-12T10:32:25.741024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.86
5-th percentile0
Q186.68
median97.82
Q399.615
95-th percentile100
Maximum173.61
Range177.47
Interquartile range (IQR)12.935

Descriptive statistics

Standard deviation42.632882
Coefficient of variation (CV)0.53618485
Kurtosis0.45725416
Mean79.511538
Median Absolute Deviation (MAD)1.81
Skewness-1.0551529
Sum3100.95
Variance1817.5627
MonotonicityNot monotonic
2023-12-12T10:32:25.964976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
100.0 6
 
15.4%
0.0 6
 
15.4%
99.62 1
 
2.6%
96.81 1
 
2.6%
97.06 1
 
2.6%
97.9 1
 
2.6%
99.56 1
 
2.6%
-3.86 1
 
2.6%
86.56 1
 
2.6%
99.63 1
 
2.6%
Other values (19) 19
48.7%
ValueCountFrequency (%)
-3.86 1
 
2.6%
0.0 6
15.4%
7.19 1
 
2.6%
86.56 1
 
2.6%
86.65 1
 
2.6%
86.71 1
 
2.6%
96.52 1
 
2.6%
96.81 1
 
2.6%
97.06 1
 
2.6%
97.21 1
 
2.6%
ValueCountFrequency (%)
173.61 1
 
2.6%
100.0 6
15.4%
99.91 1
 
2.6%
99.63 1
 
2.6%
99.62 1
 
2.6%
99.61 1
 
2.6%
99.59 1
 
2.6%
99.56 1
 
2.6%
98.98 1
 
2.6%
98.88 1
 
2.6%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
Minimum2023-08-10 00:00:00
Maximum2023-08-10 00:00:00
2023-12-12T10:32:26.095090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:26.236223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T10:32:21.590661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:18.036254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:18.729078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:19.468401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:20.238935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:20.914113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:21.717486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:18.146191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:18.829217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:19.600875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:20.365662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:21.005661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:21.849172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:18.271815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:18.948189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:19.728550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:20.468246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:21.122777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:21.961796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:18.397286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:19.058337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:19.859471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:20.593274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:21.259344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:22.053708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:18.514029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:19.181744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:19.977946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:20.699436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:21.363791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:22.171456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:18.612875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:19.320860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:20.095154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:20.798995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:32:21.483126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:32:26.316289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
과세년도1.0000.0000.0000.0000.0000.0380.0000.000
세목명0.0001.0000.8660.8920.2810.3100.8950.814
부과금액0.0000.8661.0000.9980.4860.6320.8020.509
수납급액0.0000.8920.9981.0000.5070.6450.8410.654
환급금액0.0000.2810.4860.5071.0001.0000.7750.694
결손금액0.0380.3100.6320.6451.0001.0000.7990.749
미수납 금액0.0000.8950.8020.8410.7750.7991.0000.608
징수율0.0000.8140.5090.6540.6940.7490.6081.000
2023-12-12T10:32:26.436604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2023-12-12T10:32:26.538157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과금액수납급액환급금액결손금액미수납 금액징수율과세년도세목명
부과금액1.0000.9790.5840.3250.5800.1440.0000.578
수납급액0.9791.0000.4710.2210.4610.2310.0000.625
환급금액0.5840.4711.0000.7130.874-0.0560.0000.110
결손금액0.3250.2210.7131.0000.728-0.1500.0000.120
미수납 금액0.5800.4610.8740.7281.000-0.1810.0000.625
징수율0.1440.231-0.056-0.150-0.1811.0000.0000.571
과세년도0.0000.0000.0000.0000.0000.0001.0000.000
세목명0.5780.6250.1100.1200.6250.5710.0001.000

Missing values

2023-12-12T10:32:22.341960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:32:22.576903image/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 금액징수율데이터기준일
0인천광역시중구281102020레저세13925040001392504000000100.02023-08-10
1인천광역시중구281102020재산세127771506000124741832000549190000302967400097.632023-08-10
2인천광역시중구281102020주민세18732423000184840630001753500016500024819500098.672023-08-10
3인천광역시중구281102020취득세131502535000130989109000691721000051342600099.612023-08-10
4인천광역시중구281102020자동차세12844673000111378720002778430006102000170069900086.712023-08-10
5인천광역시중구281102020과년도수입-14597873000-253426540003059680500025435970008201184000173.612023-08-10
6인천광역시중구281102020담배소비세000000.02023-08-10
7인천광역시중구281102020도시계획세000000.02023-08-10
8인천광역시중구281102020등록면허세96724650009633151000382780001660003914800099.592023-08-10
9인천광역시중구281102020지방교육세3499375300034017940000127309000182700097398600097.212023-08-10
시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율데이터기준일
29인천광역시중구281102022취득세244031465000243135473000824925000089599200099.632023-08-10
30인천광역시중구281102022자동차세13905334000120368300002217080001969000186653500086.562023-08-10
31인천광역시중구281102022과년도수입7817669000-301743000692486000012688920006850520000-3.862023-08-10
32인천광역시중구281102022담배소비세000000.02023-08-10
33인천광역시중구281102022도시계획세000000.02023-08-10
34인천광역시중구281102022등록면허세11998687000119453220005445600015010005186400099.562023-08-10
35인천광역시중구281102022지방교육세48344497000473298950001460260002834000101176800097.92023-08-10
36인천광역시중구281102022지방소득세1152963340001119035310002758649000108333000328447000097.062023-08-10
37인천광역시중구281102022지방소비세25756930002575693000000100.02023-08-10
38인천광역시중구281102022지역자원시설세1626271300015743698000684800078100051823400096.812023-08-10