Overview

Dataset statistics

Number of variables12
Number of observations67
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory106.0 B

Variable types

Categorical5
Numeric6
DateTime1

Dataset

Description인천광역시 남동구 지방세 징수 현황(과세년도, 세목명, 부과금액, 수납금액, 환급금액, 결손금액, 미수납 금액, 징수율, 데이터기준일)등을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15079469&srcSe=7661IVAWM27C61E190

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 5 other fieldsHigh correlation
수납급액 is highly overall correlated with 부과금액 and 5 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 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 20 (29.9%) zerosZeros
수납급액 has 20 (29.9%) zerosZeros
환급금액 has 22 (32.8%) zerosZeros
결손금액 has 27 (40.3%) zerosZeros
미수납 금액 has 22 (32.8%) zerosZeros
징수율 has 20 (29.9%) zerosZeros

Reproduction

Analysis started2024-03-18 02:01:28.881664
Analysis finished2024-03-18 02:01:33.421125
Duration4.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
인천광역시
67 

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 67
100.0%

Length

2024-03-18T11:01:33.478715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:01:33.578433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 67
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
남동구
67 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남동구 67
100.0%

Length

2024-03-18T11:01:33.657394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:01:33.729120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남동구 67
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
28200
67 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28200
2nd row28200
3rd row28200
4th row28200
5th row28200

Common Values

ValueCountFrequency (%)
28200 67
100.0%

Length

2024-03-18T11:01:33.805504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:01:33.876600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28200 67
100.0%

과세년도
Categorical

Distinct5
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
2017
14 
2018
14 
2019
13 
2020
13 
2021
13 

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
20.9%
2018 14
20.9%
2019 13
19.4%
2020 13
19.4%
2021 13
19.4%

Length

2024-03-18T11:01:33.953744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:01:34.037029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 14
20.9%
2018 14
20.9%
2019 13
19.4%
2020 13
19.4%
2021 13
19.4%

세목명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Memory size668.0 B
레저세
5 
재산세
5 
주민세
5 
취득세
5 
자동차세
5 
Other values (9)
42 

Length

Max length7
Median length5
Mean length4.4179104
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
레저세 5
 
7.5%
재산세 5
 
7.5%
주민세 5
 
7.5%
취득세 5
 
7.5%
자동차세 5
 
7.5%
과년도수입 5
 
7.5%
담배소비세 5
 
7.5%
도시계획세 5
 
7.5%
등록면허세 5
 
7.5%
지방교육세 5
 
7.5%
Other values (4) 17
25.4%

Length

2024-03-18T11:01:34.152507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
레저세 5
 
7.5%
재산세 5
 
7.5%
주민세 5
 
7.5%
취득세 5
 
7.5%
자동차세 5
 
7.5%
과년도수입 5
 
7.5%
담배소비세 5
 
7.5%
도시계획세 5
 
7.5%
등록면허세 5
 
7.5%
지방교육세 5
 
7.5%
Other values (4) 17
25.4%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)71.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1250727 × 1010
Minimum0
Maximum3.2691 × 1011
Zeros20
Zeros (%)29.9%
Negative0
Negative (%)0.0%
Memory size735.0 B
2024-03-18T11:01:34.267331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.6911436 × 1010
Q36.136875 × 1010
95-th percentile2.607441 × 1011
Maximum3.2691 × 1011
Range3.2691 × 1011
Interquartile range (IQR)6.136875 × 1010

Descriptive statistics

Standard deviation7.7624475 × 1010
Coefficient of variation (CV)1.5146024
Kurtosis4.2158599
Mean5.1250727 × 1010
Median Absolute Deviation (MAD)1.6911436 × 1010
Skewness2.1433774
Sum3.4337987 × 1012
Variance6.0255591 × 1021
MonotonicityNot monotonic
2024-03-18T11:01:34.392193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 20
29.9%
44200639000 1
 
1.5%
15336788000 1
 
1.5%
107279000000 1
 
1.5%
17903719000 1
 
1.5%
304107000000 1
 
1.5%
63046303000 1
 
1.5%
15332896000 1
 
1.5%
16911436000 1
 
1.5%
48134440000 1
 
1.5%
Other values (38) 38
56.7%
ValueCountFrequency (%)
0 20
29.9%
2360000000 1
 
1.5%
2520000000 1
 
1.5%
13265616000 1
 
1.5%
14869667000 1
 
1.5%
15162670000 1
 
1.5%
15332896000 1
 
1.5%
15336788000 1
 
1.5%
15362471000 1
 
1.5%
15626804000 1
 
1.5%
ValueCountFrequency (%)
326910000000 1
1.5%
304107000000 1
1.5%
266929000000 1
1.5%
265875000000 1
1.5%
248772000000 1
1.5%
151574000000 1
1.5%
130049000000 1
1.5%
123138000000 1
1.5%
120915000000 1
1.5%
120115000000 1
1.5%

수납급액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)71.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9127889 × 1010
Minimum0
Maximum3.26321 × 1011
Zeros20
Zeros (%)29.9%
Negative0
Negative (%)0.0%
Memory size735.0 B
2024-03-18T11:01:34.528869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.5472337 × 1010
Q35.6094155 × 1010
95-th percentile2.604852 × 1011
Maximum3.26321 × 1011
Range3.26321 × 1011
Interquartile range (IQR)5.6094155 × 1010

Descriptive statistics

Standard deviation7.7480264 × 1010
Coefficient of variation (CV)1.5771136
Kurtosis4.4610774
Mean4.9127889 × 1010
Median Absolute Deviation (MAD)1.5472337 × 1010
Skewness2.2018366
Sum3.2915686 × 1012
Variance6.0031913 × 1021
MonotonicityNot monotonic
2024-03-18T11:01:34.645927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 20
29.9%
42076195000 1
 
1.5%
14878594000 1
 
1.5%
104597000000 1
 
1.5%
17381107000 1
 
1.5%
303902000000 1
 
1.5%
58062091000 1
 
1.5%
3983392000 1
 
1.5%
16845932000 1
 
1.5%
46248162000 1
 
1.5%
Other values (38) 38
56.7%
ValueCountFrequency (%)
0 20
29.9%
2360000000 1
 
1.5%
2520000000 1
 
1.5%
3649288000 1
 
1.5%
3983392000 1
 
1.5%
5014304000 1
 
1.5%
6640701000 1
 
1.5%
6826066000 1
 
1.5%
14302667000 1
 
1.5%
14878594000 1
 
1.5%
ValueCountFrequency (%)
326321000000 1
1.5%
303902000000 1
1.5%
266560000000 1
1.5%
265593000000 1
1.5%
248567000000 1
1.5%
146046000000 1
1.5%
125827000000 1
1.5%
118003000000 1
1.5%
116230000000 1
1.5%
114209000000 1
1.5%

환급금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)68.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.8277697 × 108
Minimum0
Maximum8.219699 × 109
Zeros22
Zeros (%)32.8%
Negative0
Negative (%)0.0%
Memory size735.0 B
2024-03-18T11:01:34.810714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median57930000
Q37.590155 × 108
95-th percentile4.4391798 × 109
Maximum8.219699 × 109
Range8.219699 × 109
Interquartile range (IQR)7.590155 × 108

Descriptive statistics

Standard deviation1.790041 × 109
Coefficient of variation (CV)2.0277387
Kurtosis6.1488926
Mean8.8277697 × 108
Median Absolute Deviation (MAD)57930000
Skewness2.5405512
Sum5.9146057 × 1010
Variance3.2042467 × 1018
MonotonicityNot monotonic
2024-03-18T11:01:34.950961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 22
32.8%
3813532000 1
 
1.5%
3492328000 1
 
1.5%
15234000 1
 
1.5%
301678000 1
 
1.5%
12819000 1
 
1.5%
1310103000 1
 
1.5%
1093487000 1
 
1.5%
7000539000 1
 
1.5%
52168000 1
 
1.5%
Other values (36) 36
53.7%
ValueCountFrequency (%)
0 22
32.8%
12819000 1
 
1.5%
15234000 1
 
1.5%
16876000 1
 
1.5%
20247000 1
 
1.5%
26416000 1
 
1.5%
29172000 1
 
1.5%
37215000 1
 
1.5%
40645000 1
 
1.5%
45215000 1
 
1.5%
ValueCountFrequency (%)
8219699000 1
1.5%
7000539000 1
1.5%
6339993000 1
1.5%
4638303000 1
1.5%
3974559000 1
1.5%
3915311000 1
1.5%
3813532000 1
1.5%
3492328000 1
1.5%
3080753000 1
1.5%
3027687000 1
1.5%

결손금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct41
Distinct (%)61.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6746512 × 108
Minimum0
Maximum4.690163 × 109
Zeros27
Zeros (%)40.3%
Negative0
Negative (%)0.0%
Memory size735.0 B
2024-03-18T11:01:35.050743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1432000
Q323388500
95-th percentile1.4452471 × 109
Maximum4.690163 × 109
Range4.690163 × 109
Interquartile range (IQR)23388500

Descriptive statistics

Standard deviation7.8568968 × 108
Coefficient of variation (CV)2.9375407
Kurtosis18.642834
Mean2.6746512 × 108
Median Absolute Deviation (MAD)1432000
Skewness4.087066
Sum1.7920163 × 1010
Variance6.1730828 × 1017
MonotonicityNot monotonic
2024-03-18T11:01:35.156205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 27
40.3%
66206000 1
 
1.5%
131186000 1
 
1.5%
3022000 1
 
1.5%
8902000 1
 
1.5%
18517000 1
 
1.5%
4690163000 1
 
1.5%
1432000 1
 
1.5%
23252000 1
 
1.5%
1150515000 1
 
1.5%
Other values (31) 31
46.3%
ValueCountFrequency (%)
0 27
40.3%
43000 1
 
1.5%
56000 1
 
1.5%
72000 1
 
1.5%
108000 1
 
1.5%
209000 1
 
1.5%
345000 1
 
1.5%
1432000 1
 
1.5%
1766000 1
 
1.5%
2159000 1
 
1.5%
ValueCountFrequency (%)
4690163000 1
1.5%
3490354000 1
1.5%
1722773000 1
1.5%
1452598000 1
1.5%
1428095000 1
1.5%
1150515000 1
1.5%
1004024000 1
1.5%
968315000 1
1.5%
821329000 1
1.5%
475961000 1
1.5%

미수납 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)68.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8553664 × 109
Minimum0
Maximum1.2260414 × 1010
Zeros22
Zeros (%)32.8%
Negative0
Negative (%)0.0%
Memory size735.0 B
2024-03-18T11:01:35.261367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.56035 × 108
Q32.8790325 × 109
95-th percentile6.5519248 × 109
Maximum1.2260414 × 1010
Range1.2260414 × 1010
Interquartile range (IQR)2.8790325 × 109

Descriptive statistics

Standard deviation2.8053169 × 109
Coefficient of variation (CV)1.5120016
Kurtosis3.9504345
Mean1.8553664 × 109
Median Absolute Deviation (MAD)4.56035 × 108
Skewness1.9804714
Sum1.2430955 × 1011
Variance7.8698028 × 1018
MonotonicityNot monotonic
2024-03-18T11:01:35.373041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 22
32.8%
3071556000 1
 
1.5%
3256805000 1
 
1.5%
456035000 1
 
1.5%
2550401000 1
 
1.5%
519590000 1
 
1.5%
196527000 1
 
1.5%
4965695000 1
 
1.5%
6659341000 1
 
1.5%
64072000 1
 
1.5%
Other values (36) 36
53.7%
ValueCountFrequency (%)
0 22
32.8%
64072000 1
 
1.5%
77107000 1
 
1.5%
77627000 1
 
1.5%
83078000 1
 
1.5%
181584000 1
 
1.5%
196527000 1
 
1.5%
256137000 1
 
1.5%
281679000 1
 
1.5%
336039000 1
 
1.5%
ValueCountFrequency (%)
12260414000 1
1.5%
11384036000 1
1.5%
9876852000 1
1.5%
6659341000 1
1.5%
6301287000 1
1.5%
6175600000 1
1.5%
5660641000 1
1.5%
5656600000 1
1.5%
4965695000 1
1.5%
4833484000 1
1.5%

징수율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)67.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.99403
Minimum0
Maximum100
Zeros20
Zeros (%)29.9%
Negative0
Negative (%)0.0%
Memory size735.0 B
2024-03-18T11:01:35.488212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median95.19
Q397.06
95-th percentile99.911
Maximum100
Range100
Interquartile range (IQR)97.06

Descriptive statistics

Standard deviation44.816829
Coefficient of variation (CV)0.71144567
Kurtosis-1.5868509
Mean62.99403
Median Absolute Deviation (MAD)4.63
Skewness-0.61627298
Sum4220.6
Variance2008.5482
MonotonicityNot monotonic
2024-03-18T11:01:35.600745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0.0 20
29.9%
96.84 2
 
3.0%
96.75 2
 
3.0%
100.0 2
 
3.0%
96.36 1
 
1.5%
99.61 1
 
1.5%
96.13 1
 
1.5%
97.01 1
 
1.5%
97.5 1
 
1.5%
97.08 1
 
1.5%
Other values (35) 35
52.2%
ValueCountFrequency (%)
0.0 20
29.9%
21.45 1
 
1.5%
25.98 1
 
1.5%
29.12 1
 
1.5%
33.98 1
 
1.5%
50.06 1
 
1.5%
88.8 1
 
1.5%
89.02 1
 
1.5%
90.65 1
 
1.5%
92.09 1
 
1.5%
ValueCountFrequency (%)
100.0 2
3.0%
99.93 1
1.5%
99.92 1
1.5%
99.89 1
1.5%
99.86 1
1.5%
99.82 1
1.5%
99.61 1
1.5%
99.5 1
1.5%
99.49 1
1.5%
99.44 1
1.5%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
Minimum2023-02-17 00:00:00
Maximum2023-02-17 00:00:00
2024-03-18T11:01:35.683035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:35.758826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-18T11:01:32.670858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:30.274889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:30.937820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.377180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.753743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:32.160880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:32.748287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:30.471589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.012191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.444479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.821425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:32.238634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:32.813536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:30.677716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.092578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.516732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.886339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:32.322715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:32.874499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:30.739385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.154918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.573725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.958734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:32.384618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:32.933226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:30.803111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.219205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.632164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:32.024554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:32.452209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:32.997819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:30.871539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.298532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:31.696193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:32.098127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:01:32.548729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T11:01:35.969996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
과세년도1.0000.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.8470.8470.6970.6310.8460.809
부과금액0.0000.8471.0001.0000.5980.2690.8290.000
수납급액0.0000.8471.0001.0000.5980.2690.8290.000
환급금액0.0000.6970.5980.5981.0000.9470.9500.820
결손금액0.0000.6310.2690.2690.9471.0000.8220.868
미수납 금액0.0000.8460.8290.8290.9500.8221.0000.815
징수율0.0000.8090.0000.0000.8200.8680.8151.000
2024-03-18T11:01:36.051073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2024-03-18T11:01:36.117006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과금액수납급액환급금액결손금액미수납 금액징수율과세년도세목명
부과금액1.0000.9870.8180.6900.7390.6640.0000.556
수납급액0.9871.0000.7670.6440.6820.7110.0000.556
환급금액0.8180.7671.0000.8430.8960.4090.0000.374
결손금액0.6900.6440.8431.0000.7940.3770.0000.345
미수납 금액0.7390.6820.8960.7941.0000.2890.0000.554
징수율0.6640.7110.4090.3770.2891.0000.0000.529
과세년도0.0000.0000.0000.0000.0000.0001.0000.000
세목명0.5560.5560.3740.3450.5540.5290.0001.000

Missing values

2024-03-18T11:01:33.092122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T11:01:33.217376image/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
0인천광역시남동구282002017도축세000000.02023-02-17
1인천광역시남동구282002017레저세000000.02023-02-17
2인천광역시남동구282002017재산세924806250008955918500069418000345000292109500096.842023-02-17
3인천광역시남동구282002017주민세1737526800016716918000499420007200065827800096.212023-02-17
4인천광역시남동구282002017취득세2669290000002665600000009532320002058300034789700099.862023-02-17
5인천광역시남동구282002017자동차세55121346000489457460006940660000617560000088.82023-02-17
6인천광역시남동구282002017과년도수입17219669000501430400063399930008213290001138403600029.122023-02-17
7인천광역시남동구282002017담배소비세000000.02023-02-17
8인천광역시남동구282002017도시계획세000000.02023-02-17
9인천광역시남동구282002017등록면허세163706230001611448600059538000025613700098.442023-02-17
시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율데이터기준일
57인천광역시남동구282002021취득세326910000000326321000000709369000903400057988100099.822023-02-17
58인천광역시남동구282002021자동차세61690180000568467350008581480009961000483348400092.152023-02-17
59인천광역시남동구282002021과년도수입1326561600066407010003915311000968315000565660000050.062023-02-17
60인천광역시남동구282002021담배소비세000000.02023-02-17
61인천광역시남동구282002021도시계획세000000.02023-02-17
62인천광역시남동구282002021등록면허세1562680400015548968000604170002090007762700099.52023-02-17
63인천광역시남동구282002021지방교육세503814290004854898400027469400026756000180568900096.362023-02-17
64인천광역시남동구282002021지방소득세15157400000014604600000039745590001722773000380563000096.352023-02-17
65인천광역시남동구282002021지방소비세23600000002360000000000100.02023-02-17
66인천광역시남동구282002021지역자원시설세1590606000015472337000202470009768400033603900097.272023-02-17