Overview

Dataset statistics

Number of variables12
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory106.5 B

Variable types

Categorical5
Numeric6
DateTime1

Dataset

Description경기도 용인시 처인구, 기흥구, 수지구 지방세 부과액에 대한 세목별 징수 현황입니다. 부과금액, 수납금액, 환급금액 등의 데이터를 제공합니다. ※ 데이터기준일자 : 2021-12-31
URLhttps://www.data.go.kr/data/15078562/fileData.do

Alerts

시도명 has constant value ""Constant
과세년도 has constant value ""Constant
데이터기준일자 has constant value ""Constant
시군구명 is highly overall correlated with 자치단체코드High correlation
자치단체코드 is highly overall correlated with 시군구명High correlation
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 4 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
부과금액 has 23 (44.2%) zerosZeros
수납급액 has 23 (44.2%) zerosZeros
환급금액 has 25 (48.1%) zerosZeros
결손금액 has 27 (51.9%) zerosZeros
미수납 금액 has 25 (48.1%) zerosZeros
징수율 has 23 (44.2%) zerosZeros

Reproduction

Analysis started2023-12-12 13:02:56.482839
Analysis finished2023-12-12 13:03:01.091321
Duration4.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
경기도
52 

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 52
100.0%

Length

2023-12-12T22:03:01.173917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:03:01.275940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 52
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size548.0 B
용인시
13 
용인시 기흥구
13 
용인시 수지구
13 
용인시 처인구
13 

Length

Max length7
Median length7
Mean length6
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용인시 13
25.0%
용인시 기흥구 13
25.0%
용인시 수지구 13
25.0%
용인시 처인구 13
25.0%

Length

2023-12-12T22:03:01.396196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:03:01.540651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용인시 52
57.1%
기흥구 13
 
14.3%
수지구 13
 
14.3%
처인구 13
 
14.3%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size548.0 B
41460
13 
41463
13 
41465
13 
41461
13 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41460
2nd row41460
3rd row41460
4th row41460
5th row41460

Common Values

ValueCountFrequency (%)
41460 13
25.0%
41463 13
25.0%
41465 13
25.0%
41461 13
25.0%

Length

2023-12-12T22:03:01.669562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:03:01.790669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41460 13
25.0%
41463 13
25.0%
41465 13
25.0%
41461 13
25.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
2021
52 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 52
100.0%

Length

2023-12-12T22:03:01.905831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:03:01.996347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 52
100.0%

세목명
Categorical

Distinct13
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
레저세
4 
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
Other values (8)
32 

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 4
 
7.7%
재산세 4
 
7.7%
주민세 4
 
7.7%
취득세 4
 
7.7%
자동차세 4
 
7.7%
과년도수입 4
 
7.7%
담배소비세 4
 
7.7%
도시계획세 4
 
7.7%
등록면허세 4
 
7.7%
지방교육세 4
 
7.7%
Other values (3) 12
23.1%

Length

2023-12-12T22:03:02.120161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
레저세 4
 
7.7%
재산세 4
 
7.7%
주민세 4
 
7.7%
취득세 4
 
7.7%
자동차세 4
 
7.7%
과년도수입 4
 
7.7%
담배소비세 4
 
7.7%
도시계획세 4
 
7.7%
등록면허세 4
 
7.7%
지방교육세 4
 
7.7%
Other values (3) 12
23.1%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)57.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5984992 × 1010
Minimum0
Maximum3.05207 × 1011
Zeros23
Zeros (%)44.2%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T22:03:02.238672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.0702536 × 1010
Q34.9085582 × 1010
95-th percentile2.8273245 × 1011
Maximum3.05207 × 1011
Range3.05207 × 1011
Interquartile range (IQR)4.9085582 × 1010

Descriptive statistics

Standard deviation8.127973 × 1010
Coefficient of variation (CV)1.7675273
Kurtosis4.4967199
Mean4.5984992 × 1010
Median Absolute Deviation (MAD)1.0702536 × 1010
Skewness2.2758301
Sum2.3912196 × 1012
Variance6.6063945 × 1021
MonotonicityNot monotonic
2023-12-12T22:03:02.364101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 23
44.2%
47675008000 1
 
1.9%
10625364000 1
 
1.9%
10779708000 1
 
1.9%
111158000000 1
 
1.9%
75993189000 1
 
1.9%
17414106000 1
 
1.9%
53317305000 1
 
1.9%
25016510000 1
 
1.9%
98656789000 1
 
1.9%
Other values (20) 20
38.5%
ValueCountFrequency (%)
0 23
44.2%
5932978000 1
 
1.9%
9393258000 1
 
1.9%
10625364000 1
 
1.9%
10779708000 1
 
1.9%
13397556000 1
 
1.9%
14114948000 1
 
1.9%
15418077000 1
 
1.9%
15770669000 1
 
1.9%
17414106000 1
 
1.9%
ValueCountFrequency (%)
305207000000 1
1.9%
297109000000 1
1.9%
290961000000 1
1.9%
276000000000 1
1.9%
140979000000 1
1.9%
123840000000 1
1.9%
118960000000 1
1.9%
111158000000 1
1.9%
110665000000 1
1.9%
98656789000 1
1.9%

수납급액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)57.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3933939 × 1010
Minimum-1.922236 × 109
Maximum3.04504 × 1011
Zeros23
Zeros (%)44.2%
Negative1
Negative (%)1.9%
Memory size600.0 B
2023-12-12T22:03:02.477124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.922236 × 109
5-th percentile0
Q10
median6.938727 × 109
Q34.8256244 × 1010
95-th percentile2.717184 × 1011
Maximum3.04504 × 1011
Range3.0642624 × 1011
Interquartile range (IQR)4.8256244 × 1010

Descriptive statistics

Standard deviation7.9878269 × 1010
Coefficient of variation (CV)1.8181449
Kurtosis4.6069328
Mean4.3933939 × 1010
Median Absolute Deviation (MAD)6.938727 × 109
Skewness2.2969181
Sum2.2845648 × 1012
Variance6.3805378 × 1021
MonotonicityNot monotonic
2023-12-12T22:03:02.599015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 23
44.2%
46569224000 1
 
1.9%
10448010000 1
 
1.9%
10779708000 1
 
1.9%
107778000000 1
 
1.9%
74154640000 1
 
1.9%
17377609000 1
 
1.9%
53317305000 1
 
1.9%
6009848000 1
 
1.9%
94998023000 1
 
1.9%
Other values (20) 20
38.5%
ValueCountFrequency (%)
-1922236000 1
 
1.9%
0 23
44.2%
5768336000 1
 
1.9%
6009848000 1
 
1.9%
7867606000 1
 
1.9%
9263122000 1
 
1.9%
10448010000 1
 
1.9%
10779708000 1
 
1.9%
13035706000 1
 
1.9%
14096685000 1
 
1.9%
ValueCountFrequency (%)
304504000000 1
1.9%
296549000000 1
1.9%
275256000000 1
1.9%
268824000000 1
1.9%
138461000000 1
1.9%
118968000000 1
1.9%
112257000000 1
1.9%
108628000000 1
1.9%
107778000000 1
1.9%
94998023000 1
1.9%

환급금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)53.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0283837 × 109
Minimum0
Maximum1.4946078 × 1010
Zeros25
Zeros (%)48.1%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T22:03:02.744947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2785000
Q32.7295875 × 108
95-th percentile7.0402272 × 109
Maximum1.4946078 × 1010
Range1.4946078 × 1010
Interquartile range (IQR)2.7295875 × 108

Descriptive statistics

Standard deviation2.9546511 × 109
Coefficient of variation (CV)2.8731018
Kurtosis12.742951
Mean1.0283837 × 109
Median Absolute Deviation (MAD)2785000
Skewness3.5566707
Sum5.3475953 × 1010
Variance8.7299629 × 1018
MonotonicityNot monotonic
2023-12-12T22:03:02.857572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 25
48.1%
67091000 1
 
1.9%
8541000 1
 
1.9%
5555220000 1
 
1.9%
195311000 1
 
1.9%
97065000 1
 
1.9%
8855236000 1
 
1.9%
359808000 1
 
1.9%
830706000 1
 
1.9%
36630000 1
 
1.9%
Other values (18) 18
34.6%
ValueCountFrequency (%)
0 25
48.1%
2411000 1
 
1.9%
3159000 1
 
1.9%
8541000 1
 
1.9%
11367000 1
 
1.9%
12648000 1
 
1.9%
36630000 1
 
1.9%
46569000 1
 
1.9%
67091000 1
 
1.9%
97065000 1
 
1.9%
ValueCountFrequency (%)
14946078000 1
1.9%
11743231000 1
1.9%
8855236000 1
1.9%
5555220000 1
1.9%
4228719000 1
1.9%
3025729000 1
1.9%
830706000 1
1.9%
739392000 1
1.9%
669561000 1
1.9%
615005000 1
1.9%

결손금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.6182569 × 108
Minimum0
Maximum1.8535523 × 1010
Zeros27
Zeros (%)51.9%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T22:03:02.975058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32178500
95-th percentile2.3629099 × 109
Maximum1.8535523 × 1010
Range1.8535523 × 1010
Interquartile range (IQR)2178500

Descriptive statistics

Standard deviation2.6997301 × 109
Coefficient of variation (CV)4.8052806
Kurtosis40.463811
Mean5.6182569 × 108
Median Absolute Deviation (MAD)0
Skewness6.1675797
Sum2.9214936 × 1010
Variance7.2885427 × 1018
MonotonicityNot monotonic
2023-12-12T22:03:03.087040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 27
51.9%
360000 1
 
1.9%
73000 1
 
1.9%
67437000 1
 
1.9%
5852000 1
 
1.9%
269000 1
 
1.9%
2284587000 1
 
1.9%
2480000 1
 
1.9%
527000 1
 
1.9%
1471000 1
 
1.9%
Other values (16) 16
30.8%
ValueCountFrequency (%)
0 27
51.9%
73000 1
 
1.9%
82000 1
 
1.9%
101000 1
 
1.9%
139000 1
 
1.9%
165000 1
 
1.9%
269000 1
 
1.9%
332000 1
 
1.9%
360000 1
 
1.9%
472000 1
 
1.9%
ValueCountFrequency (%)
18535523000 1
1.9%
5769961000 1
1.9%
2458638000 1
1.9%
2284587000 1
1.9%
67437000 1
1.9%
41604000 1
1.9%
25687000 1
1.9%
8066000 1
1.9%
5852000 1
1.9%
3891000 1
1.9%

미수납 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)53.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4892503 × 109
Minimum0
Maximum1.6722075 × 1010
Zeros25
Zeros (%)48.1%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T22:03:03.209903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median27176000
Q31.6335615 × 109
95-th percentile7.1555653 × 109
Maximum1.6722075 × 1010
Range1.6722075 × 1010
Interquartile range (IQR)1.6335615 × 109

Descriptive statistics

Standard deviation3.149169 × 109
Coefficient of variation (CV)2.1146002
Kurtosis11.796966
Mean1.4892503 × 109
Median Absolute Deviation (MAD)27176000
Skewness3.2126505
Sum7.7441017 × 1010
Variance9.9172652 × 1018
MonotonicityNot monotonic
2023-12-12T22:03:03.328574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 25
48.1%
18124000 1
 
1.9%
177281000 1
 
1.9%
3313283000 1
 
1.9%
1832697000 1
 
1.9%
36228000 1
 
1.9%
16722075000 1
 
1.9%
3656286000 1
 
1.9%
702161000 1
 
1.9%
360379000 1
 
1.9%
Other values (18) 18
34.6%
ValueCountFrequency (%)
0 25
48.1%
18124000 1
 
1.9%
36228000 1
 
1.9%
41318000 1
 
1.9%
130035000 1
 
1.9%
164560000 1
 
1.9%
177281000 1
 
1.9%
270375000 1
 
1.9%
360379000 1
 
1.9%
397405000 1
 
1.9%
ValueCountFrequency (%)
16722075000 1
1.9%
11570352000 1
1.9%
7759319000 1
1.9%
6661585000 1
1.9%
4846566000 1
1.9%
3952048000 1
1.9%
3656286000 1
1.9%
3601211000 1
1.9%
3313283000 1
1.9%
2706053000 1
1.9%

징수율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)55.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.820192
Minimum-12.47
Maximum100
Zeros23
Zeros (%)44.2%
Negative1
Negative (%)1.9%
Memory size600.0 B
2023-12-12T22:03:03.440026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-12.47
5-th percentile0
Q10
median67.165
Q398.1725
95-th percentile99.837
Maximum100
Range112.47
Interquartile range (IQR)98.1725

Descriptive statistics

Standard deviation48.707443
Coefficient of variation (CV)0.97766469
Kurtosis-2.0332816
Mean49.820192
Median Absolute Deviation (MAD)32.835
Skewness-0.045721947
Sum2590.65
Variance2372.415
MonotonicityNot monotonic
2023-12-12T22:03:03.553787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 23
44.2%
100.0 2
 
3.8%
98.21 1
 
1.9%
98.33 1
 
1.9%
96.96 1
 
1.9%
97.58 1
 
1.9%
99.79 1
 
1.9%
24.02 1
 
1.9%
96.29 1
 
1.9%
99.77 1
 
1.9%
Other values (19) 19
36.5%
ValueCountFrequency (%)
-12.47 1
 
1.9%
0.0 23
44.2%
24.02 1
 
1.9%
43.5 1
 
1.9%
90.83 1
 
1.9%
92.39 1
 
1.9%
92.77 1
 
1.9%
94.37 1
 
1.9%
96.07 1
 
1.9%
96.29 1
 
1.9%
ValueCountFrequency (%)
100.0 2
3.8%
99.87 1
1.9%
99.81 1
1.9%
99.79 1
1.9%
99.78 1
1.9%
99.77 1
1.9%
99.73 1
1.9%
98.64 1
1.9%
98.61 1
1.9%
98.33 1
1.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
Minimum2021-12-31 00:00:00
Maximum2021-12-31 00:00:00
2023-12-12T22:03:03.664594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:03:03.749796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T22:03:00.115374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:56.827548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:57.361465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:57.844162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:58.446471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:59.101892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:03:00.213463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:56.911761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:57.441517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:57.926466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:58.570569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:59.236835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:03:00.322869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:56.998716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:57.521628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:58.017323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:58.677594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:59.352497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:03:00.444828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:57.091192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:57.601715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:58.139704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:58.779976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:59.773915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:03:00.552945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:57.195499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:57.690274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:58.247648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:58.887624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:59.894774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:03:00.661563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:57.280846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:57.769644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:58.346855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:02:59.000109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:03:00.000735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:03:03.823010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드세목명부과금액수납급액환급금액결손금액미수납 금액징수율
시군구명1.0001.0000.0000.1050.2570.2330.0000.1610.427
자치단체코드1.0001.0000.0000.1050.2570.2330.0000.1610.427
세목명0.0000.0001.0000.7440.6980.2540.5400.4530.418
부과금액0.1050.1050.7441.0000.9520.4140.0000.5020.189
수납급액0.2570.2570.6980.9521.0000.6370.7390.5770.313
환급금액0.2330.2330.2540.4140.6371.0000.9950.9030.857
결손금액0.0000.0000.5400.0000.7390.9951.0000.8920.832
미수납 금액0.1610.1610.4530.5020.5770.9030.8921.0000.921
징수율0.4270.4270.4180.1890.3130.8570.8320.9211.000
2023-12-12T22:03:03.943305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명시군구명자치단체코드
세목명1.0000.0000.000
시군구명0.0001.0001.000
자치단체코드0.0001.0001.000
2023-12-12T22:03:04.044053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과금액수납급액환급금액결손금액미수납 금액징수율시군구명자치단체코드세목명
부과금액1.0000.9510.8730.7590.8570.7570.0490.0490.446
수납급액0.9511.0000.7410.6320.7260.8350.1480.1480.390
환급금액0.8730.7411.0000.8860.9630.5200.1420.1420.095
결손금액0.7590.6320.8861.0000.9250.4390.0000.0000.305
미수납 금액0.8570.7260.9630.9251.0000.4820.0960.0960.202
징수율0.7570.8350.5200.4390.4821.0000.3550.3550.209
시군구명0.0490.1480.1420.0000.0960.3551.0001.0000.000
자치단체코드0.0490.1480.1420.0000.0960.3551.0001.0000.000
세목명0.4460.3900.0950.3050.2020.2090.0000.0001.000

Missing values

2023-12-12T22:03:00.806511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:03:01.010961image/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
0경기도용인시414602021레저세000000.02021-12-31
1경기도용인시414602021재산세000000.02021-12-31
2경기도용인시414602021주민세000000.02021-12-31
3경기도용인시414602021취득세000000.02021-12-31
4경기도용인시414602021자동차세000000.02021-12-31
5경기도용인시414602021과년도수입000000.02021-12-31
6경기도용인시414602021담배소비세000000.02021-12-31
7경기도용인시414602021도시계획세000000.02021-12-31
8경기도용인시414602021등록면허세000000.02021-12-31
9경기도용인시414602021지방교육세000000.02021-12-31
시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율데이터기준일자
42경기도용인시 처인구414612021취득세30520700000030450400000083070600052700070216100099.772021-12-31
43경기도용인시 처인구414612021자동차세98656789000949980230003598080002480000365628600096.292021-12-31
44경기도용인시 처인구414612021과년도수입250165100006009848000885523600022845870001672207500024.022021-12-31
45경기도용인시 처인구414612021담배소비세5331730500053317305000000100.02021-12-31
46경기도용인시 처인구414612021도시계획세000000.02021-12-31
47경기도용인시 처인구414612021등록면허세1741410600017377609000970650002690003622800099.792021-12-31
48경기도용인시 처인구414612021지방교육세75993189000741546400001953110005852000183269700097.582021-12-31
49경기도용인시 처인구414612021지방소득세111158000000107778000000555522000067437000331328300096.962021-12-31
50경기도용인시 처인구414612021지방소비세1077970800010779708000000100.02021-12-31
51경기도용인시 처인구414612021지역자원시설세106253640001044801000085410007300017728100098.332021-12-31