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

Categorical6
Numeric6

Dataset

Description해당자료는 경기도 구리시의 지방세징수현황 2019년기준 2018년기준 2017년 기 준 현황 자료(시군구명, 자치단체코드, 과세년도, 세목명, 환급금액, 미수납 금액 등)을 제공합니다.
URLhttps://www.data.go.kr/data/15080568/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 3 other fieldsHigh correlation
수납급액 is highly overall correlated with 부과금액 and 3 other fieldsHigh correlation
환급금액 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
결손금액 is highly overall correlated with 미수납 금액High correlation
미수납 금액 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 10 (14.9%) zerosZeros
수납급액 has 10 (14.9%) zerosZeros
환급금액 has 20 (29.9%) zerosZeros
결손금액 has 51 (76.1%) zerosZeros
미수납 금액 has 22 (32.8%) zerosZeros
징수율 has 10 (14.9%) zerosZeros

Reproduction

Analysis started2023-12-12 03:48:06.347306
Analysis finished2023-12-12 03:48:11.652339
Duration5.31 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
경기도
67 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 67
100.0%

Length

2023-12-12T12:48:11.763875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:48:11.912195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 67
100.0%

시군구명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구리시 67
100.0%

Length

2023-12-12T12:48:12.080729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:48:12.229775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구리시 67
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
41310
67 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41310
2nd row41310
3rd row41310
4th row41310
5th row41310

Common Values

ValueCountFrequency (%)
41310 67
100.0%

Length

2023-12-12T12:48:12.357320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:48:12.455648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41310 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

2023-12-12T12:48:12.563960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:48:12.701967image/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

2023-12-12T12:48:12.875492image/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 

Distinct58
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9802201 × 1010
Minimum0
Maximum1.1812 × 1011
Zeros10
Zeros (%)14.9%
Negative0
Negative (%)0.0%
Memory size735.0 B
2023-12-12T12:48:13.058608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.3369125 × 109
median1.1969322 × 1010
Q32.6269986 × 1010
95-th percentile7.714087 × 1010
Maximum1.1812 × 1011
Range1.1812 × 1011
Interquartile range (IQR)2.2933073 × 1010

Descriptive statistics

Standard deviation2.5681082 × 1010
Coefficient of variation (CV)1.2968802
Kurtosis5.5660519
Mean1.9802201 × 1010
Median Absolute Deviation (MAD)1.1331144 × 1010
Skewness2.2534265
Sum1.3267474 × 1012
Variance6.5951796 × 1020
MonotonicityNot monotonic
2023-12-12T12:48:13.563730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
14.9%
3145000000 1
 
1.5%
30916884000 1
 
1.5%
3870362000 1
 
1.5%
944620000 1
 
1.5%
44296294000 1
 
1.5%
3529850000 1
 
1.5%
116517000000 1
 
1.5%
28876003000 1
 
1.5%
14672230000 1
 
1.5%
Other values (48) 48
71.6%
ValueCountFrequency (%)
0 10
14.9%
270409000 1
 
1.5%
944620000 1
 
1.5%
3006000000 1
 
1.5%
3009987000 1
 
1.5%
3115917000 1
 
1.5%
3145000000 1
 
1.5%
3234779000 1
 
1.5%
3439046000 1
 
1.5%
3529850000 1
 
1.5%
ValueCountFrequency (%)
118120000000 1
1.5%
116517000000 1
1.5%
88894081000 1
1.5%
79469290000 1
1.5%
71707889000 1
1.5%
46834674000 1
1.5%
44296294000 1
1.5%
41725172000 1
1.5%
41088217000 1
1.5%
38570798000 1
1.5%

수납급액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct58
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8459678 × 1010
Minimum0
Maximum1.18083 × 1011
Zeros10
Zeros (%)14.9%
Negative0
Negative (%)0.0%
Memory size735.0 B
2023-12-12T12:48:13.764436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.0539265 × 109
median6.252458 × 109
Q32.5086826 × 1010
95-th percentile7.683317 × 1010
Maximum1.18083 × 1011
Range1.18083 × 1011
Interquartile range (IQR)2.20329 × 1010

Descriptive statistics

Standard deviation2.5689705 × 1010
Coefficient of variation (CV)1.3916659
Kurtosis5.7558111
Mean1.8459678 × 1010
Median Absolute Deviation (MAD)6.252458 × 109
Skewness2.3211512
Sum1.2367984 × 1012
Variance6.5996093 × 1020
MonotonicityNot monotonic
2023-12-12T12:48:13.973068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
14.9%
3145000000 1
 
1.5%
29235309000 1
 
1.5%
3813666000 1
 
1.5%
944620000 1
 
1.5%
43649615000 1
 
1.5%
3378258000 1
 
1.5%
114763000000 1
 
1.5%
27299867000 1
 
1.5%
2758878000 1
 
1.5%
Other values (48) 48
71.6%
ValueCountFrequency (%)
0 10
14.9%
270409000 1
 
1.5%
944620000 1
 
1.5%
2758878000 1
 
1.5%
2815868000 1
 
1.5%
2999551000 1
 
1.5%
3006000000 1
 
1.5%
3033518000 1
 
1.5%
3074335000 1
 
1.5%
3145000000 1
 
1.5%
ValueCountFrequency (%)
118083000000 1
1.5%
114763000000 1
1.5%
88040414000 1
1.5%
79121091000 1
1.5%
71494687000 1
1.5%
46164131000 1
1.5%
43649615000 1
1.5%
40890323000 1
1.5%
38815090000 1
1.5%
37681022000 1
1.5%

환급금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)71.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0752239 × 108
Minimum0
Maximum4.665689 × 109
Zeros20
Zeros (%)29.9%
Negative0
Negative (%)0.0%
Memory size735.0 B
2023-12-12T12:48:14.244543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11972000
Q32.07032 × 108
95-th percentile1.381098 × 109
Maximum4.665689 × 109
Range4.665689 × 109
Interquartile range (IQR)2.07032 × 108

Descriptive statistics

Standard deviation7.2008468 × 108
Coefficient of variation (CV)2.3415683
Kurtosis20.529408
Mean3.0752239 × 108
Median Absolute Deviation (MAD)11972000
Skewness4.0320514
Sum2.0604 × 1010
Variance5.1852195 × 1017
MonotonicityNot monotonic
2023-12-12T12:48:14.485464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 20
29.9%
90999000 1
 
1.5%
942000 1
 
1.5%
9227000 1
 
1.5%
11373000 1
 
1.5%
421007000 1
 
1.5%
236698000 1
 
1.5%
2241980000 1
 
1.5%
13327000 1
 
1.5%
13920000 1
 
1.5%
Other values (38) 38
56.7%
ValueCountFrequency (%)
0 20
29.9%
229000 1
 
1.5%
621000 1
 
1.5%
942000 1
 
1.5%
1457000 1
 
1.5%
1810000 1
 
1.5%
2814000 1
 
1.5%
3301000 1
 
1.5%
3350000 1
 
1.5%
4852000 1
 
1.5%
ValueCountFrequency (%)
4665689000 1
1.5%
2241980000 1
1.5%
1705487000 1
1.5%
1395492000 1
1.5%
1347512000 1
1.5%
1261771000 1
1.5%
1177711000 1
1.5%
1092470000 1
1.5%
910569000 1
1.5%
786514000 1
1.5%

결손금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)25.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2135079 × 108
Minimum0
Maximum2.27968 × 109
Zeros51
Zeros (%)76.1%
Negative0
Negative (%)0.0%
Memory size735.0 B
2023-12-12T12:48:14.661012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1.3015561 × 109
Maximum2.27968 × 109
Range2.27968 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.4402671 × 108
Coefficient of variation (CV)3.6590343
Kurtosis12.787982
Mean1.2135079 × 108
Median Absolute Deviation (MAD)0
Skewness3.6738268
Sum8.130503 × 109
Variance1.9715972 × 1017
MonotonicityNot monotonic
2023-12-12T12:48:14.838854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 51
76.1%
1399651000 1
 
1.5%
1753086000 1
 
1.5%
2496000 1
 
1.5%
25000 1
 
1.5%
23000 1
 
1.5%
2279680000 1
 
1.5%
30000 1
 
1.5%
247000 1
 
1.5%
3629000 1
 
1.5%
Other values (7) 7
 
10.4%
ValueCountFrequency (%)
0 51
76.1%
4000 1
 
1.5%
6000 1
 
1.5%
20000 1
 
1.5%
23000 1
 
1.5%
25000 1
 
1.5%
30000 1
 
1.5%
32000 1
 
1.5%
247000 1
 
1.5%
489000 1
 
1.5%
ValueCountFrequency (%)
2279680000 1
1.5%
1753086000 1
1.5%
1618417000 1
1.5%
1399651000 1
1.5%
1072668000 1
1.5%
3629000 1
1.5%
2496000 1
1.5%
489000 1
1.5%
247000 1
1.5%
32000 1
1.5%

미수납 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)68.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2211756 × 109
Minimum0
Maximum1.1436831 × 1010
Zeros22
Zeros (%)32.8%
Negative0
Negative (%)0.0%
Memory size735.0 B
2023-12-12T12:48:15.067810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.286 × 108
Q38.717055 × 108
95-th percentile9.483141 × 109
Maximum1.1436831 × 1010
Range1.1436831 × 1010
Interquartile range (IQR)8.717055 × 108

Descriptive statistics

Standard deviation2.6463245 × 109
Coefficient of variation (CV)2.1670302
Kurtosis7.8998103
Mean1.2211756 × 109
Median Absolute Deviation (MAD)1.286 × 108
Skewness2.9644982
Sum8.1818767 × 1010
Variance7.0030332 × 1018
MonotonicityNot monotonic
2023-12-12T12:48:15.304804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 22
32.8%
1973874000 1
 
1.5%
1677946000 1
 
1.5%
56696000 1
 
1.5%
646679000 1
 
1.5%
151345000 1
 
1.5%
1754313000 1
 
1.5%
1576106000 1
 
1.5%
9633672000 1
 
1.5%
18909000 1
 
1.5%
Other values (36) 36
53.7%
ValueCountFrequency (%)
0 22
32.8%
18909000 1
 
1.5%
19803000 1
 
1.5%
22885000 1
 
1.5%
23592000 1
 
1.5%
28584000 1
 
1.5%
36946000 1
 
1.5%
41582000 1
 
1.5%
51707000 1
 
1.5%
56696000 1
 
1.5%
ValueCountFrequency (%)
11436831000 1
1.5%
10540175000 1
1.5%
9706930000 1
1.5%
9633672000 1
1.5%
9131902000 1
1.5%
2802570000 1
1.5%
2387976000 1
1.5%
2273127000 1
1.5%
1973874000 1
1.5%
1895916000 1
1.5%

징수율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct44
Distinct (%)65.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.523134
Minimum0
Maximum100
Zeros10
Zeros (%)14.9%
Negative0
Negative (%)0.0%
Memory size735.0 B
2023-12-12T12:48:15.504511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q191.69
median97.3
Q399.595
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)7.905

Descriptive statistics

Standard deviation37.985981
Coefficient of variation (CV)0.48999543
Kurtosis0.1325206
Mean77.523134
Median Absolute Deviation (MAD)2.7
Skewness-1.4171077
Sum5194.05
Variance1442.9348
MonotonicityNot monotonic
2023-12-12T12:48:15.708319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
100.0 12
 
17.9%
0.0 10
 
14.9%
98.54 3
 
4.5%
97.86 2
 
3.0%
99.68 1
 
1.5%
99.54 1
 
1.5%
97.3 1
 
1.5%
94.56 1
 
1.5%
95.71 1
 
1.5%
98.49 1
 
1.5%
Other values (34) 34
50.7%
ValueCountFrequency (%)
0.0 10
14.9%
18.8 1
 
1.5%
21.26 1
 
1.5%
25.03 1
 
1.5%
26.04 1
 
1.5%
32.92 1
 
1.5%
90.85 1
 
1.5%
91.17 1
 
1.5%
92.21 1
 
1.5%
92.25 1
 
1.5%
ValueCountFrequency (%)
100.0 12
17.9%
99.97 1
 
1.5%
99.7 1
 
1.5%
99.68 1
 
1.5%
99.65 1
 
1.5%
99.61 1
 
1.5%
99.58 1
 
1.5%
99.56 1
 
1.5%
99.54 1
 
1.5%
99.04 1
 
1.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-06-21
67 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-21
2nd row2023-06-21
3rd row2023-06-21
4th row2023-06-21
5th row2023-06-21

Common Values

ValueCountFrequency (%)
2023-06-21 67
100.0%

Length

2023-12-12T12:48:15.862124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:48:16.002136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-21 67
100.0%

Interactions

2023-12-12T12:48:10.443067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:06.737104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:07.449701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:08.189451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:08.900472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:09.661367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:10.563408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:06.869643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:07.557693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:08.336512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:09.038608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:09.795149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:10.695500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:06.993778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:07.674627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:08.467377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:09.203239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:09.935130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:10.801521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:07.099278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:07.784068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:08.575684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:09.314711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:10.067427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:10.924721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:07.219164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:07.904577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:08.682791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:09.421338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:10.193670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:11.062589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:07.352240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:08.059714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:08.799931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:09.562900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:48:10.318586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:48:16.095156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
과세년도1.0000.0000.0000.0000.1130.0000.0000.000
세목명0.0001.0000.9280.9160.5920.4640.7900.801
부과금액0.0000.9281.0000.9990.0110.0000.4330.295
수납급액0.0000.9160.9991.0000.0000.0000.2530.000
환급금액0.1130.5920.0110.0001.0000.8790.9470.742
결손금액0.0000.4640.0000.0000.8791.0000.8270.968
미수납 금액0.0000.7900.4330.2530.9470.8271.0000.842
징수율0.0000.8010.2950.0000.7420.9680.8421.000
2023-12-12T12:48:16.237606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2023-12-12T12:48:16.375973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과금액수납급액환급금액결손금액미수납 금액징수율과세년도세목명
부과금액1.0000.9580.7580.2120.7090.2180.0000.585
수납급액0.9581.0000.6160.0420.5450.3650.0000.562
환급금액0.7580.6161.0000.4860.903-0.1710.0670.314
결손금액0.2120.0420.4861.0000.554-0.2890.0000.238
미수납 금액0.7090.5450.9030.5541.000-0.3120.0000.505
징수율0.2180.365-0.171-0.289-0.3121.0000.0000.533
과세년도0.0000.0000.0670.0000.0000.0001.0000.000
세목명0.5850.5620.3140.2380.5050.5330.0001.000

Missing values

2023-12-12T12:48:11.233582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:48:11.538915image/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
0경기도구리시413102017도축세000000.02023-06-21
1경기도구리시413102017레저세65771750006577175000000100.02023-06-21
2경기도구리시413102017재산세353494860003459422000016087000075526600097.862023-06-21
3경기도구리시413102017주민세30099870002815868000621000019411900093.552023-06-21
4경기도구리시413102017취득세8889408100088040414000450352000085366700099.042023-06-21
5경기도구리시413102017자동차세22523550000207777120001748230000174583800092.252023-06-21
6경기도구리시413102017과년도수입14106132000299955100017054870001399651000970693000021.262023-06-21
7경기도구리시413102017담배소비세1227910900012279109000000100.02023-06-21
8경기도구리시413102017도시계획세000000.02023-06-21
9경기도구리시413102017등록면허세601561200059920200002038300002359200099.612023-06-21
시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율데이터기준일자
57경기도구리시413102021취득세11812000000011808300000039945000003694600099.972023-06-21
58경기도구리시413102021자동차세25346930000237448250002126530000160210500093.682023-06-21
59경기도구리시413102021과년도수입16227056000534206800013954920001753086000913190200032.922023-06-21
60경기도구리시413102021담배소비세1227642900012276429000181000000100.02023-06-21
61경기도구리시413102021도시계획세000000.02023-06-21
62경기도구리시413102021등록면허세573979200057199890002106900001980300099.652023-06-21
63경기도구리시413102021지방교육세2565170300025102187000100901000054951600097.862023-06-21
64경기도구리시413102021지방소득세410882170003881509000013475120000227312700094.472023-06-21
65경기도구리시413102021지방소비세30060000003006000000000100.02023-06-21
66경기도구리시413102021지역자원시설세40190650003960517000335000005854800098.542023-06-21