Overview

Dataset statistics

Number of variables11
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory94.2 B

Variable types

Categorical5
Text5
Numeric1

Dataset

Description지방세 부과액에 대한 세목별 징수 현황으로 지자체의 재정자주고,재정자립도를 산출하는 기초 및 납세 협력도 및 조세 순응도를 확인하는 자료로 활용
Author전라남도 완도군
URLhttps://www.data.go.kr/data/15078452/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
징수율 is highly overall correlated with 세목명High correlation
세목명 is highly overall correlated with 징수율High correlation
징수율 has 11 (26.8%) zerosZeros

Reproduction

Analysis started2023-12-12 23:32:01.591271
Analysis finished2023-12-12 23:32:02.165333
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
전라남도
41 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 41
100.0%

Length

2023-12-13T08:32:02.217642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:32:02.290703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 41
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
완도군
41 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
완도군 41
100.0%

Length

2023-12-13T08:32:02.362538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:32:02.436049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완도군 41
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
46890
41 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46890
2nd row46890
3rd row46890
4th row46890
5th row46890

Common Values

ValueCountFrequency (%)
46890 41
100.0%

Length

2023-12-13T08:32:02.512387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:32:02.589824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46890 41
100.0%

과세년도
Categorical

Distinct3
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
2017
14 
2018
14 
2019
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
34.1%
2018 14
34.1%
2019 13
31.7%

Length

2023-12-13T08:32:02.662473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:32:02.743155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 14
34.1%
2018 14
34.1%
2019 13
31.7%

세목명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Memory size460.0 B
레저세
3 
재산세
3 
주민세
3 
취득세
3 
자동차세
3 
Other values (9)
26 

Length

Max length7
Median length5
Mean length4.3902439
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
레저세 3
 
7.3%
재산세 3
 
7.3%
주민세 3
 
7.3%
취득세 3
 
7.3%
자동차세 3
 
7.3%
과년도수입 3
 
7.3%
담배소비세 3
 
7.3%
도시계획세 3
 
7.3%
등록면허세 3
 
7.3%
지방교육세 3
 
7.3%
Other values (4) 11
26.8%

Length

2023-12-13T08:32:02.836835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
레저세 3
 
7.3%
재산세 3
 
7.3%
주민세 3
 
7.3%
취득세 3
 
7.3%
자동차세 3
 
7.3%
과년도수입 3
 
7.3%
담배소비세 3
 
7.3%
도시계획세 3
 
7.3%
등록면허세 3
 
7.3%
지방교육세 3
 
7.3%
Other values (4) 11
26.8%

부과금액
Text

Distinct31
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T08:32:02.971184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length9.8780488
Min length3

Characters and Unicode

Total characters405
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)73.2%

Sample

1st row -
2nd row -
3rd row2,444,067,000
4th row541,579,000
5th row8,658,281,000
ValueCountFrequency (%)
11
26.8%
4,463,207,000 1
 
2.4%
3,962,517,000 1
 
2.4%
4,122,285,000 1
 
2.4%
991,100,000 1
 
2.4%
4,480,010,000 1
 
2.4%
1,351,023,000 1
 
2.4%
6,948,406,000 1
 
2.4%
9,195,637,000 1
 
2.4%
640,311,000 1
 
2.4%
Other values (21) 21
51.2%
2023-12-13T08:32:03.221064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 110
27.2%
, 81
20.0%
4 29
 
7.2%
22
 
5.4%
1 22
 
5.4%
9 22
 
5.4%
5 20
 
4.9%
8 20
 
4.9%
2 17
 
4.2%
6 17
 
4.2%
Other values (3) 45
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 291
71.9%
Other Punctuation 81
 
20.0%
Space Separator 22
 
5.4%
Dash Punctuation 11
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 110
37.8%
4 29
 
10.0%
1 22
 
7.6%
9 22
 
7.6%
5 20
 
6.9%
8 20
 
6.9%
2 17
 
5.8%
6 17
 
5.8%
7 17
 
5.8%
3 17
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 81
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 405
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 110
27.2%
, 81
20.0%
4 29
 
7.2%
22
 
5.4%
1 22
 
5.4%
9 22
 
5.4%
5 20
 
4.9%
8 20
 
4.9%
2 17
 
4.2%
6 17
 
4.2%
Other values (3) 45
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 405
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 110
27.2%
, 81
20.0%
4 29
 
7.2%
22
 
5.4%
1 22
 
5.4%
9 22
 
5.4%
5 20
 
4.9%
8 20
 
4.9%
2 17
 
4.2%
6 17
 
4.2%
Other values (3) 45
11.1%

수납급액
Text

Distinct31
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T08:32:03.372374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length9.7317073
Min length3

Characters and Unicode

Total characters399
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)73.2%

Sample

1st row -
2nd row -
3rd row2,344,616,000
4th row487,332,000
5th row8,645,560,000
ValueCountFrequency (%)
11
26.8%
4,463,207,000 1
 
2.4%
3,780,405,000 1
 
2.4%
3,947,665,000 1
 
2.4%
986,824,000 1
 
2.4%
4,480,010,000 1
 
2.4%
753,780,000 1
 
2.4%
6,417,709,000 1
 
2.4%
9,137,373,000 1
 
2.4%
595,373,000 1
 
2.4%
Other values (21) 21
51.2%
2023-12-13T08:32:03.611014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 114
28.6%
, 78
19.5%
3 33
 
8.3%
4 30
 
7.5%
22
 
5.5%
7 21
 
5.3%
6 19
 
4.8%
5 18
 
4.5%
8 16
 
4.0%
2 13
 
3.3%
Other values (3) 35
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 288
72.2%
Other Punctuation 78
 
19.5%
Space Separator 22
 
5.5%
Dash Punctuation 11
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 114
39.6%
3 33
 
11.5%
4 30
 
10.4%
7 21
 
7.3%
6 19
 
6.6%
5 18
 
6.2%
8 16
 
5.6%
2 13
 
4.5%
9 13
 
4.5%
1 11
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 78
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 399
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 114
28.6%
, 78
19.5%
3 33
 
8.3%
4 30
 
7.5%
22
 
5.5%
7 21
 
5.3%
6 19
 
4.8%
5 18
 
4.5%
8 16
 
4.0%
2 13
 
3.3%
Other values (3) 35
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 399
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 114
28.6%
, 78
19.5%
3 33
 
8.3%
4 30
 
7.5%
22
 
5.5%
7 21
 
5.3%
6 19
 
4.8%
5 18
 
4.5%
8 16
 
4.0%
2 13
 
3.3%
Other values (3) 35
 
8.8%

환급금액
Text

Distinct29
Distinct (%)70.7%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T08:32:03.755462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.1219512
Min length3

Characters and Unicode

Total characters292
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)68.3%

Sample

1st row -
2nd row -
3rd row883,000
4th row1,066,000
5th row22,465,000
ValueCountFrequency (%)
13
31.7%
1,551,000 1
 
2.4%
72,227,000 1
 
2.4%
17,055,000 1
 
2.4%
5,544,000 1
 
2.4%
156,051,000 1
 
2.4%
53,899,000 1
 
2.4%
32,257,000 1
 
2.4%
463,000 1
 
2.4%
3,403,000 1
 
2.4%
Other values (19) 19
46.3%
2023-12-13T08:32:04.073742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 91
31.2%
, 49
16.8%
26
 
8.9%
1 15
 
5.1%
5 15
 
5.1%
3 14
 
4.8%
4 14
 
4.8%
- 13
 
4.5%
2 13
 
4.5%
7 13
 
4.5%
Other values (3) 29
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 204
69.9%
Other Punctuation 49
 
16.8%
Space Separator 26
 
8.9%
Dash Punctuation 13
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 91
44.6%
1 15
 
7.4%
5 15
 
7.4%
3 14
 
6.9%
4 14
 
6.9%
2 13
 
6.4%
7 13
 
6.4%
6 12
 
5.9%
9 9
 
4.4%
8 8
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 49
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 292
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 91
31.2%
, 49
16.8%
26
 
8.9%
1 15
 
5.1%
5 15
 
5.1%
3 14
 
4.8%
4 14
 
4.8%
- 13
 
4.5%
2 13
 
4.5%
7 13
 
4.5%
Other values (3) 29
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 292
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 91
31.2%
, 49
16.8%
26
 
8.9%
1 15
 
5.1%
5 15
 
5.1%
3 14
 
4.8%
4 14
 
4.8%
- 13
 
4.5%
2 13
 
4.5%
7 13
 
4.5%
Other values (3) 29
 
9.9%

결손금액
Text

Distinct28
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T08:32:04.236818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.1463415
Min length3

Characters and Unicode

Total characters293
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)65.9%

Sample

1st row -
2nd row -
3rd row13,000,000
4th row3,615,000
5th row90,000
ValueCountFrequency (%)
14
34.1%
13,000,000 1
 
2.4%
97,352,000 1
 
2.4%
9,482,000 1
 
2.4%
1,063,000 1
 
2.4%
333,901,000 1
 
2.4%
18,535,000 1
 
2.4%
9,457,000 1
 
2.4%
12,444,000 1
 
2.4%
18,528,000 1
 
2.4%
Other values (18) 18
43.9%
2023-12-13T08:32:04.928934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 91
31.1%
, 51
17.4%
28
 
9.6%
5 16
 
5.5%
1 15
 
5.1%
- 14
 
4.8%
6 14
 
4.8%
3 13
 
4.4%
9 13
 
4.4%
4 13
 
4.4%
Other values (3) 25
 
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 200
68.3%
Other Punctuation 51
 
17.4%
Space Separator 28
 
9.6%
Dash Punctuation 14
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 91
45.5%
5 16
 
8.0%
1 15
 
7.5%
6 14
 
7.0%
3 13
 
6.5%
9 13
 
6.5%
4 13
 
6.5%
7 9
 
4.5%
2 9
 
4.5%
8 7
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 51
100.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 293
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 91
31.1%
, 51
17.4%
28
 
9.6%
5 16
 
5.5%
1 15
 
5.1%
- 14
 
4.8%
6 14
 
4.8%
3 13
 
4.4%
9 13
 
4.4%
4 13
 
4.4%
Other values (3) 25
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 293
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 91
31.1%
, 51
17.4%
28
 
9.6%
5 16
 
5.5%
1 15
 
5.1%
- 14
 
4.8%
6 14
 
4.8%
3 13
 
4.4%
9 13
 
4.4%
4 13
 
4.4%
Other values (3) 25
 
8.5%

미수납 금액
Text

Distinct28
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T08:32:05.139305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.8292683
Min length3

Characters and Unicode

Total characters321
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)65.9%

Sample

1st row -
2nd row -
3rd row86,451,000
4th row50,632,000
5th row12,631,000
ValueCountFrequency (%)
14
34.1%
86,451,000 1
 
2.4%
84,760,000 1
 
2.4%
165,138,000 1
 
2.4%
3,213,000 1
 
2.4%
263,342,000 1
 
2.4%
512,162,000 1
 
2.4%
48,807,000 1
 
2.4%
32,494,000 1
 
2.4%
63,277,000 1
 
2.4%
Other values (18) 18
43.9%
2023-12-13T08:32:05.499279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 94
29.3%
, 54
16.8%
28
 
8.7%
2 23
 
7.2%
3 18
 
5.6%
1 17
 
5.3%
6 15
 
4.7%
4 15
 
4.7%
- 14
 
4.4%
8 11
 
3.4%
Other values (3) 32
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 225
70.1%
Other Punctuation 54
 
16.8%
Space Separator 28
 
8.7%
Dash Punctuation 14
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 94
41.8%
2 23
 
10.2%
3 18
 
8.0%
1 17
 
7.6%
6 15
 
6.7%
4 15
 
6.7%
8 11
 
4.9%
5 11
 
4.9%
9 11
 
4.9%
7 10
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 54
100.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 321
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 94
29.3%
, 54
16.8%
28
 
8.7%
2 23
 
7.2%
3 18
 
5.6%
1 17
 
5.3%
6 15
 
4.7%
4 15
 
4.7%
- 14
 
4.4%
8 11
 
3.4%
Other values (3) 32
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 321
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 94
29.3%
, 54
16.8%
28
 
8.7%
2 23
 
7.2%
3 18
 
5.6%
1 17
 
5.3%
6 15
 
4.7%
4 15
 
4.7%
- 14
 
4.4%
8 11
 
3.4%
Other values (3) 32
 
10.0%

징수율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.836098
Minimum0
Maximum100
Zeros11
Zeros (%)26.8%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-13T08:32:05.658730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median92.72
Q397.11
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)97.11

Descriptive statistics

Standard deviation42.5653
Coefficient of variation (CV)0.62747272
Kurtosis-1.0157627
Mean67.836098
Median Absolute Deviation (MAD)6.81
Skewness-0.95746889
Sum2781.28
Variance1811.8048
MonotonicityNot monotonic
2023-12-13T08:32:05.788698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 11
26.8%
100.0 3
 
7.3%
99.57 2
 
4.9%
99.53 1
 
2.4%
97.58 1
 
2.4%
95.4 1
 
2.4%
95.76 1
 
2.4%
55.79 1
 
2.4%
92.36 1
 
2.4%
99.37 1
 
2.4%
Other values (18) 18
43.9%
ValueCountFrequency (%)
0.0 11
26.8%
55.79 1
 
2.4%
64.18 1
 
2.4%
69.24 1
 
2.4%
89.97 1
 
2.4%
89.98 1
 
2.4%
92.21 1
 
2.4%
92.24 1
 
2.4%
92.36 1
 
2.4%
92.41 1
 
2.4%
ValueCountFrequency (%)
100.0 3
7.3%
99.85 1
 
2.4%
99.57 2
4.9%
99.53 1
 
2.4%
99.37 1
 
2.4%
98.4 1
 
2.4%
97.58 1
 
2.4%
97.11 1
 
2.4%
97.07 1
 
2.4%
96.16 1
 
2.4%

Interactions

2023-12-13T08:32:01.888972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:32:05.884219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
과세년도1.0000.0000.1930.1930.1480.1510.1510.000
세목명0.0001.0000.7900.7900.7270.7730.7730.821
부과금액0.1930.7901.0001.0001.0001.0001.0001.000
수납급액0.1930.7901.0001.0001.0001.0001.0001.000
환급금액0.1480.7271.0001.0001.0001.0001.0000.981
결손금액0.1510.7731.0001.0001.0001.0001.0000.970
미수납 금액0.1510.7731.0001.0001.0001.0001.0000.970
징수율0.0000.8211.0001.0000.9810.9700.9701.000
2023-12-13T08:32:05.988590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2023-12-13T08:32:06.090245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
징수율과세년도세목명
징수율1.0000.0000.522
과세년도0.0001.0000.000
세목명0.5220.0001.000

Missing values

2023-12-13T08:32:01.986486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:32:02.117884image/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 금액징수율
0전라남도완도군468902017도축세-----0.0
1전라남도완도군468902017레저세-----0.0
2전라남도완도군468902017재산세2,444,067,0002,344,616,000883,00013,000,00086,451,00095.93
3전라남도완도군468902017주민세541,579,000487,332,0001,066,0003,615,00050,632,00089.98
4전라남도완도군468902017취득세8,658,281,0008,645,560,00022,465,00090,00012,631,00099.85
5전라남도완도군468902017자동차세5,482,264,0004,932,371,00020,242,00016,504,000533,389,00089.97
6전라남도완도군468902017과년도수입1,094,026,000757,556,00077,436,000116,071,000220,399,00069.24
7전라남도완도군468902017담배소비세4,601,128,0004,601,128,000---100.0
8전라남도완도군468902017도시계획세-----0.0
9전라남도완도군468902017등록면허세841,875,000838,243,0001,416,000589,0003,043,00099.57
시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
31전라남도완도군468902019취득세9,195,637,0009,137,373,00032,257,0009,457,00048,807,00099.37
32전라남도완도군468902019자동차세6,948,406,0006,417,709,00053,899,00018,535,000512,162,00092.36
33전라남도완도군468902019과년도수입1,351,023,000753,780,000156,051,000333,901,000263,342,00055.79
34전라남도완도군468902019담배소비세4,480,010,0004,480,010,000---100.0
35전라남도완도군468902019도시계획세-----0.0
36전라남도완도군468902019등록면허세991,100,000986,824,0005,544,0001,063,0003,213,00099.57
37전라남도완도군468902019지방교육세4,122,285,0003,947,665,00017,055,0009,482,000165,138,00095.76
38전라남도완도군468902019지방소득세3,962,517,0003,780,405,00072,227,00097,352,00084,760,00095.4
39전라남도완도군468902019지방소비세-----0.0
40전라남도완도군468902019지역자원시설세485,093,000473,345,000196,0004,086,0007,662,00097.58