Overview

Dataset statistics

Number of variables12
Number of observations54
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory106.4 B

Variable types

Categorical5
Numeric6
DateTime1

Dataset

Description강원도 춘천시 2017~2020년 지방세 부과액에 대한 세목별 징수현황에 대한 데이터입니다. 지자체의 재정자주도·재정자립도 산출하는 기초 및 납세 협력도 및 조세 순응도를 확인하는 자료로 활용 가능합니다.
Author강원도 춘천시
URLhttps://www.data.go.kr/data/15079742/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 4 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 3 other fieldsHigh correlation
징수율 is highly overall correlated with 수납급액High correlation
세목명 is highly overall correlated with 부과금액 and 1 other fieldsHigh correlation
부과금액 has 13 (24.1%) zerosZeros
수납급액 has 13 (24.1%) zerosZeros
환급금액 has 16 (29.6%) zerosZeros
결손금액 has 21 (38.9%) zerosZeros
미수납 금액 has 18 (33.3%) zerosZeros
징수율 has 13 (24.1%) zerosZeros

Reproduction

Analysis started2023-12-12 12:03:20.772980
Analysis finished2023-12-12 12:03:26.005569
Duration5.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
강원도
54 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원도 54
100.0%

Length

2023-12-12T21:03:26.077935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:03:26.190345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 54
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
춘천시
54 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
춘천시 54
100.0%

Length

2023-12-12T21:03:26.296980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:03:26.433169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
춘천시 54
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
42110
54 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row42110
2nd row42110
3rd row42110
4th row42110
5th row42110

Common Values

ValueCountFrequency (%)
42110 54
100.0%

Length

2023-12-12T21:03:26.541445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:03:26.632222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
42110 54
100.0%

과세년도
Categorical

Distinct4
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size564.0 B
2017
14 
2018
14 
2019
13 
2020
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
25.9%
2018 14
25.9%
2019 13
24.1%
2020 13
24.1%

Length

2023-12-12T21:03:26.732233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:03:26.841840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 14
25.9%
2018 14
25.9%
2019 13
24.1%
2020 13
24.1%

세목명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
레저세
4 
재산세
4 
주민세
4 
취득세
4 
자동차세
4 
Other values (9)
34 

Length

Max length7
Median length5
Mean length4.4074074
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
레저세 4
 
7.4%
재산세 4
 
7.4%
주민세 4
 
7.4%
취득세 4
 
7.4%
자동차세 4
 
7.4%
과년도수입 4
 
7.4%
담배소비세 4
 
7.4%
도시계획세 4
 
7.4%
등록면허세 4
 
7.4%
지방교육세 4
 
7.4%
Other values (4) 14
25.9%

Length

2023-12-12T21:03:26.976840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
레저세 4
 
7.4%
재산세 4
 
7.4%
주민세 4
 
7.4%
취득세 4
 
7.4%
자동차세 4
 
7.4%
과년도수입 4
 
7.4%
담배소비세 4
 
7.4%
도시계획세 4
 
7.4%
등록면허세 4
 
7.4%
지방교육세 4
 
7.4%
Other values (4) 14
25.9%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5053389 × 1010
Minimum0
Maximum1.1327 × 1011
Zeros13
Zeros (%)24.1%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T21:03:27.109367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.4667998 × 109
median1.5694812 × 1010
Q34.4523657 × 1010
95-th percentile8.6885913 × 1010
Maximum1.1327 × 1011
Range1.1327 × 1011
Interquartile range (IQR)3.9056857 × 1010

Descriptive statistics

Standard deviation2.8456455 × 1010
Coefficient of variation (CV)1.1358326
Kurtosis1.6211649
Mean2.5053389 × 1010
Median Absolute Deviation (MAD)1.5694812 × 1010
Skewness1.3998263
Sum1.352883 × 1012
Variance8.0976983 × 1020
MonotonicityNot monotonic
2023-12-12T21:03:27.241240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 13
24.1%
6319197000 1
 
1.9%
50968243000 1
 
1.9%
12937300000 1
 
1.9%
18452323000 1
 
1.9%
5824361000 1
 
1.9%
28891633000 1
 
1.9%
55843719000 1
 
1.9%
7367265000 1
 
1.9%
50537098000 1
 
1.9%
Other values (32) 32
59.3%
ValueCountFrequency (%)
0 13
24.1%
5414760000 1
 
1.9%
5622919000 1
 
1.9%
5712509000 1
 
1.9%
5824361000 1
 
1.9%
5841858000 1
 
1.9%
6101778000 1
 
1.9%
6319197000 1
 
1.9%
7289678000 1
 
1.9%
7367265000 1
 
1.9%
ValueCountFrequency (%)
113270000000 1
1.9%
105904000000 1
1.9%
93307049000 1
1.9%
83428379000 1
1.9%
59852333000 1
1.9%
55881600000 1
1.9%
55843719000 1
1.9%
51126231000 1
1.9%
50968243000 1
1.9%
50537098000 1
1.9%

수납급액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3353268 × 1010
Minimum0
Maximum1.12423 × 1011
Zeros13
Zeros (%)24.1%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T21:03:27.386920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.3120672 × 109
median7.970028 × 109
Q34.2302947 × 1010
95-th percentile8.663998 × 1010
Maximum1.12423 × 1011
Range1.12423 × 1011
Interquartile range (IQR)3.999088 × 1010

Descriptive statistics

Standard deviation2.8046077 × 1010
Coefficient of variation (CV)1.2009487
Kurtosis1.7981396
Mean2.3353268 × 1010
Median Absolute Deviation (MAD)7.970028 × 109
Skewness1.4828937
Sum1.2610765 × 1012
Variance7.8658245 × 1020
MonotonicityNot monotonic
2023-12-12T21:03:27.514565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 13
24.1%
6165875000 1
 
1.9%
47815257000 1
 
1.9%
1351103000 1
 
1.9%
18452323000 1
 
1.9%
5798263000 1
 
1.9%
27483487000 1
 
1.9%
53864157000 1
 
1.9%
7207249000 1
 
1.9%
49119427000 1
 
1.9%
Other values (32) 32
59.3%
ValueCountFrequency (%)
0 13
24.1%
1351103000 1
 
1.9%
5194960000 1
 
1.9%
5480940000 1
 
1.9%
5602323000 1
 
1.9%
5798263000 1
 
1.9%
5814561000 1
 
1.9%
5862940000 1
 
1.9%
6165875000 1
 
1.9%
7136355000 1
 
1.9%
ValueCountFrequency (%)
112423000000 1
1.9%
100594000000 1
1.9%
93088929000 1
1.9%
83167469000 1
1.9%
58422264000 1
1.9%
53931102000 1
1.9%
53864157000 1
1.9%
49119427000 1
1.9%
48057125000 1
1.9%
47815257000 1
1.9%

환급금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2155822 × 108
Minimum0
Maximum5.432514 × 109
Zeros16
Zeros (%)29.6%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T21:03:27.656242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median25273500
Q32.687275 × 108
95-th percentile2.0632398 × 109
Maximum5.432514 × 109
Range5.432514 × 109
Interquartile range (IQR)2.687275 × 108

Descriptive statistics

Standard deviation9.5329093 × 108
Coefficient of variation (CV)2.2613506
Kurtosis14.505057
Mean4.2155822 × 108
Median Absolute Deviation (MAD)25273500
Skewness3.4769203
Sum2.2764144 × 1010
Variance9.087636 × 1017
MonotonicityNot monotonic
2023-12-12T21:03:27.791256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 16
29.6%
39590000 1
 
1.9%
312184000 1
 
1.9%
265264000 1
 
1.9%
5432514000 1
 
1.9%
34960000 1
 
1.9%
109864000 1
 
1.9%
1430794000 1
 
1.9%
7267000 1
 
1.9%
95919000 1
 
1.9%
Other values (29) 29
53.7%
ValueCountFrequency (%)
0 16
29.6%
40000 1
 
1.9%
888000 1
 
1.9%
3421000 1
 
1.9%
4004000 1
 
1.9%
4101000 1
 
1.9%
5321000 1
 
1.9%
7267000 1
 
1.9%
12600000 1
 
1.9%
14130000 1
 
1.9%
ValueCountFrequency (%)
5432514000 1
1.9%
2885172000 1
1.9%
2167936000 1
1.9%
2006865000 1
1.9%
1761370000 1
1.9%
1545842000 1
1.9%
1488771000 1
1.9%
1430794000 1
1.9%
688027000 1
1.9%
528071000 1
1.9%

결손금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4228476 × 108
Minimum0
Maximum3.567012 × 109
Zeros21
Zeros (%)38.9%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T21:03:27.924643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median150500
Q35281000
95-th percentile2.3483575 × 109
Maximum3.567012 × 109
Range3.567012 × 109
Interquartile range (IQR)5281000

Descriptive statistics

Standard deviation7.9327445 × 108
Coefficient of variation (CV)3.2741409
Kurtosis11.165559
Mean2.4228476 × 108
Median Absolute Deviation (MAD)150500
Skewness3.4764492
Sum1.3083377 × 1010
Variance6.2928435 × 1017
MonotonicityNot monotonic
2023-12-12T21:03:28.135844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 21
38.9%
803000 1
 
1.9%
3417949000 1
 
1.9%
580000 1
 
1.9%
5489000 1
 
1.9%
557754000 1
 
1.9%
18166000 1
 
1.9%
86000 1
 
1.9%
2262000 1
 
1.9%
524000 1
 
1.9%
Other values (24) 24
44.4%
ValueCountFrequency (%)
0 21
38.9%
31000 1
 
1.9%
43000 1
 
1.9%
86000 1
 
1.9%
97000 1
 
1.9%
99000 1
 
1.9%
131000 1
 
1.9%
170000 1
 
1.9%
524000 1
 
1.9%
528000 1
 
1.9%
ValueCountFrequency (%)
3567012000 1
1.9%
3417949000 1
1.9%
2564166000 1
1.9%
2232153000 1
1.9%
557754000 1
1.9%
479065000 1
1.9%
118179000 1
1.9%
51311000 1
1.9%
26667000 1
1.9%
18166000 1
1.9%

미수납 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)68.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.457837 × 109
Minimum0
Maximum1.5623268 × 1010
Zeros18
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T21:03:28.302238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.739455 × 108
Q31.413853 × 109
95-th percentile7.5522722 × 109
Maximum1.5623268 × 1010
Range1.5623268 × 1010
Interquartile range (IQR)1.413853 × 109

Descriptive statistics

Standard deviation2.9127499 × 109
Coefficient of variation (CV)1.9979942
Kurtosis11.61375
Mean1.457837 × 109
Median Absolute Deviation (MAD)1.739455 × 108
Skewness3.2158592
Sum7.8723197 × 1010
Variance8.484112 × 1018
MonotonicityNot monotonic
2023-12-12T21:03:28.470543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 18
33.3%
1417585000 1
 
1.9%
5310049000 1
 
1.9%
3146543000 1
 
1.9%
8168248000 1
 
1.9%
25518000 1
 
1.9%
1402657000 1
 
1.9%
1421808000 1
 
1.9%
141850000 1
 
1.9%
152519000 1
 
1.9%
Other values (27) 27
50.0%
ValueCountFrequency (%)
0 18
33.3%
17514000 1
 
1.9%
20553000 1
 
1.9%
25518000 1
 
1.9%
27166000 1
 
1.9%
141850000 1
 
1.9%
152519000 1
 
1.9%
152636000 1
 
1.9%
156079000 1
 
1.9%
166809000 1
 
1.9%
ValueCountFrequency (%)
15623268000 1
1.9%
10477843000 1
1.9%
8168248000 1
1.9%
7220593000 1
1.9%
5310049000 1
1.9%
3170265000 1
1.9%
3146543000 1
1.9%
3067317000 1
1.9%
2754975000 1
1.9%
2507706000 1
1.9%

징수율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)68.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.178704
Minimum0
Maximum100
Zeros13
Zeros (%)24.1%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T21:03:28.631847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115.285
median96.02
Q397.8825
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)82.5975

Descriptive statistics

Standard deviation42.903669
Coefficient of variation (CV)0.62018608
Kurtosis-1.0796849
Mean69.178704
Median Absolute Deviation (MAD)3.52
Skewness-0.9310178
Sum3735.65
Variance1840.7248
MonotonicityNot monotonic
2023-12-12T21:03:28.794279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0.0 13
24.1%
100.0 5
 
9.3%
99.77 2
 
3.7%
97.83 1
 
1.9%
94.99 1
 
1.9%
93.81 1
 
1.9%
10.44 1
 
1.9%
99.55 1
 
1.9%
95.13 1
 
1.9%
96.46 1
 
1.9%
Other values (27) 27
50.0%
ValueCountFrequency (%)
0.0 13
24.1%
10.44 1
 
1.9%
29.82 1
 
1.9%
44.52 1
 
1.9%
51.05 1
 
1.9%
93.1 1
 
1.9%
93.43 1
 
1.9%
93.81 1
 
1.9%
94.0 1
 
1.9%
94.21 1
 
1.9%
ValueCountFrequency (%)
100.0 5
9.3%
99.77 2
 
3.7%
99.69 1
 
1.9%
99.63 1
 
1.9%
99.55 1
 
1.9%
99.53 1
 
1.9%
99.25 1
 
1.9%
97.95 1
 
1.9%
97.9 1
 
1.9%
97.83 1
 
1.9%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
Minimum2022-06-20 00:00:00
Maximum2022-06-20 00:00:00
2023-12-12T21:03:28.928533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:29.055951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T21:03:24.938560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:21.126467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:21.770642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:22.395861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:23.141000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:23.888218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:25.048025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:21.234556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:21.863474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:22.504433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:23.270742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:24.014461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:25.156471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:21.328727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:21.980115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:22.606479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:23.394492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:24.123262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:25.296577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:21.441913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:22.083844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:22.720528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:23.536507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:24.241720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:25.412773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:21.553267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:22.191243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:22.872091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:23.638024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:24.378468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:25.534603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:21.657854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:22.302390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:23.023050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:23.773250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:24.503801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:03:29.202639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
과세년도1.0000.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.8550.8790.6900.6530.5650.697
부과금액0.0000.8551.0000.9930.8190.2450.6050.389
수납급액0.0000.8790.9931.0000.7480.0000.1540.000
환급금액0.0000.6900.8190.7481.0000.8690.8470.959
결손금액0.0000.6530.2450.0000.8691.0000.9090.906
미수납 금액0.0000.5650.6050.1540.8470.9091.0000.953
징수율0.0000.6970.3890.0000.9590.9060.9531.000
2023-12-12T21:03:29.330107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2023-12-12T21:03:29.440303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과금액수납급액환급금액결손금액미수납 금액징수율과세년도세목명
부과금액1.0000.9890.8080.6020.7490.4690.0000.551
수납급액0.9891.0000.7460.5370.6800.5310.0000.594
환급금액0.8080.7461.0000.8170.8970.2330.0000.386
결손금액0.6020.5370.8171.0000.7980.1550.0000.367
미수납 금액0.7490.6800.8970.7981.0000.0430.0000.262
징수율0.4690.5310.2330.1550.0431.0000.0000.392
과세년도0.0000.0000.0000.0000.0000.0001.0000.000
세목명0.5510.5940.3860.3670.2620.3920.0001.000

Missing values

2023-12-12T21:03:25.715456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:03:25.923941image/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
0강원도춘천시421102017도축세000000.02022-06-20
1강원도춘천시421102017레저세000000.02022-06-20
2강원도춘천시421102017재산세4341567900040903316000395900004657000250770600094.212022-06-20
3강원도춘천시421102017주민세541476000051949600004101000021980000095.942022-06-20
4강원도춘천시421102017취득세8342837900083167469000688027000026091000099.692022-06-20
5강원도춘천시421102017자동차세459398550004276949100023830500099000317026500093.12022-06-20
6강원도춘천시421102017과년도수입273426670008152387000176137000035670120001562326800029.822022-06-20
7강원도춘천시421102017담배소비세1942580100019425801000000100.02022-06-20
8강원도춘천시421102017도시계획세000000.02022-06-20
9강원도춘천시421102017등록면허세5622919000560232300029555000430002055300099.632022-06-20
시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율데이터기준일
44강원도춘천시421102020취득세113270000000112423000000528071000226200084474000099.252022-06-20
45강원도춘천시421102020자동차세42067362000393024930003154450009894000275497500093.432022-06-20
46강원도춘천시421102020과년도수입19309715000985696900028851720002232153000722059300051.052022-06-20
47강원도춘천시421102020담배소비세19762742000197627420002099200000100.02022-06-20
48강원도춘천시421102020도시계획세000000.02022-06-20
49강원도춘천시421102020등록면허세78053530007787669000392680001700001751400099.772022-06-20
50강원도춘천시421102020지방교육세31296176000302407460001655590002927000105250300096.632022-06-20
51강원도춘천시421102020지방소득세59852333000584222640002006865000118179000131189000097.612022-06-20
52강원도춘천시421102020지방소비세77520000007752000000000100.02022-06-20
53강원도춘천시421102020지역자원시설세7921053000773994000053210003100018108200097.712022-06-20