Overview

Dataset statistics

Number of variables9
Number of observations39
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory77.4 B

Variable types

Categorical5
Text4

Dataset

Description연도별 지방세 과세 및 비과세 현황을 세목별로 제공함으로 지방세 부과 규모 및 비과세로 받는 국민 조세 혜택 규모를 파악하는 데 사용
Author전라남도 완도군
URLhttps://www.data.go.kr/data/15078648/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant

Reproduction

Analysis started2023-12-12 19:59:26.787525
Analysis finished2023-12-12 19:59:27.385520
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
전라남도
39 

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 39
100.0%

Length

2023-12-13T04:59:27.456546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:59:27.552708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 39
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
완도군
39 

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 39
100.0%

Length

2023-12-13T04:59:27.646807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:59:27.748206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완도군 39
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
46890
39 

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 39
100.0%

Length

2023-12-13T04:59:27.864793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:59:27.964966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46890 39
100.0%

과세년도
Categorical

Distinct3
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size444.0 B
2017
13 
2018
13 
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 13
33.3%
2018 13
33.3%
2019 13
33.3%

Length

2023-12-13T04:59:28.067078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:59:28.175674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 13
33.3%
2018 13
33.3%
2019 13
33.3%

세목명
Categorical

Distinct13
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size444.0 B
취득세
3 
등록세
3 
주민세
3 
재산세
3 
자동차세
3 
Other values (8)
24 

Length

Max length7
Median length5
Mean length4.1538462
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row취득세
2nd row등록세
3rd row주민세
4th row재산세
5th row자동차세

Common Values

ValueCountFrequency (%)
취득세 3
 
7.7%
등록세 3
 
7.7%
주민세 3
 
7.7%
재산세 3
 
7.7%
자동차세 3
 
7.7%
레저세 3
 
7.7%
담배소비세 3
 
7.7%
지방소비세 3
 
7.7%
등록면허세 3
 
7.7%
도시계획세 3
 
7.7%
Other values (3) 9
23.1%

Length

2023-12-13T04:59:28.330561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 3
 
7.7%
등록세 3
 
7.7%
주민세 3
 
7.7%
재산세 3
 
7.7%
자동차세 3
 
7.7%
레저세 3
 
7.7%
담배소비세 3
 
7.7%
지방소비세 3
 
7.7%
등록면허세 3
 
7.7%
도시계획세 3
 
7.7%
Other values (3) 9
23.1%

과세건수
Text

Distinct28
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-13T04:59:28.508975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.7692308
Min length2

Characters and Unicode

Total characters186
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 (%)69.2%

Sample

1st row9,470
2nd row -
3rd row27,422
4th row59,775
5th row32,850
ValueCountFrequency (%)
12
30.8%
9,470 1
 
2.6%
10,511 1
 
2.6%
11,387 1
 
2.6%
26,072 1
 
2.6%
82 1
 
2.6%
35,701 1
 
2.6%
63,259 1
 
2.6%
28,176 1
 
2.6%
9,798 1
 
2.6%
Other values (18) 18
46.2%
2023-12-13T04:59:28.802238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
12.9%
, 24
12.9%
1 20
10.8%
7 17
9.1%
0 15
8.1%
2 14
7.5%
6 13
7.0%
- 12
6.5%
4 10
 
5.4%
5 10
 
5.4%
Other values (3) 27
14.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 126
67.7%
Space Separator 24
 
12.9%
Other Punctuation 24
 
12.9%
Dash Punctuation 12
 
6.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
15.9%
7 17
13.5%
0 15
11.9%
2 14
11.1%
6 13
10.3%
4 10
7.9%
5 10
7.9%
3 10
7.9%
9 9
7.1%
8 8
 
6.3%
Space Separator
ValueCountFrequency (%)
24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 186
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
24
12.9%
, 24
12.9%
1 20
10.8%
7 17
9.1%
0 15
8.1%
2 14
7.5%
6 13
7.0%
- 12
6.5%
4 10
 
5.4%
5 10
 
5.4%
Other values (3) 27
14.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 186
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24
12.9%
, 24
12.9%
1 20
10.8%
7 17
9.1%
0 15
8.1%
2 14
7.5%
6 13
7.0%
- 12
6.5%
4 10
 
5.4%
5 10
 
5.4%
Other values (3) 27
14.5%

과세금액
Text

Distinct28
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-13T04:59:29.014970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length9.4615385
Min length3

Characters and Unicode

Total characters369
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 (%)69.2%

Sample

1st row8,658,281,000
2nd row -
3rd row541,579,000
4th row2,444,067,000
5th row5,482,264,000
ValueCountFrequency (%)
12
30.8%
8,658,281,000 1
 
2.6%
3,962,517,000 1
 
2.6%
521,695,000 1
 
2.6%
991,100,000 1
 
2.6%
4,480,010,000 1
 
2.6%
6,948,406,000 1
 
2.6%
2,790,895,000 1
 
2.6%
640,311,000 1
 
2.6%
9,195,637,000 1
 
2.6%
Other values (18) 18
46.2%
2023-12-13T04:59:29.381721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 97
26.3%
, 72
19.5%
4 25
 
6.8%
24
 
6.5%
8 21
 
5.7%
5 20
 
5.4%
9 20
 
5.4%
6 19
 
5.1%
1 17
 
4.6%
2 16
 
4.3%
Other values (3) 38
 
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 261
70.7%
Other Punctuation 72
 
19.5%
Space Separator 24
 
6.5%
Dash Punctuation 12
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 97
37.2%
4 25
 
9.6%
8 21
 
8.0%
5 20
 
7.7%
9 20
 
7.7%
6 19
 
7.3%
1 17
 
6.5%
2 16
 
6.1%
7 13
 
5.0%
3 13
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 72
100.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 369
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 97
26.3%
, 72
19.5%
4 25
 
6.8%
24
 
6.5%
8 21
 
5.7%
5 20
 
5.4%
9 20
 
5.4%
6 19
 
5.1%
1 17
 
4.6%
2 16
 
4.3%
Other values (3) 38
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 369
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 97
26.3%
, 72
19.5%
4 25
 
6.8%
24
 
6.5%
8 21
 
5.7%
5 20
 
5.4%
9 20
 
5.4%
6 19
 
5.1%
1 17
 
4.6%
2 16
 
4.3%
Other values (3) 38
 
10.3%

비과세건수
Text

Distinct25
Distinct (%)64.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-13T04:59:29.566916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.6153846
Min length1

Characters and Unicode

Total characters141
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

Unique24 ?
Unique (%)61.5%

Sample

1st row1,520
2nd row7
3rd row3,143
4th row11,892
5th row3,519
ValueCountFrequency (%)
15
38.5%
1,520 1
 
2.6%
4,549 1
 
2.6%
754 1
 
2.6%
1,810 1
 
2.6%
4,822 1
 
2.6%
13,571 1
 
2.6%
4,223 1
 
2.6%
5 1
 
2.6%
1,912 1
 
2.6%
Other values (15) 15
38.5%
2023-12-13T04:59:29.925469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
21.3%
1 17
12.1%
- 15
10.6%
, 15
10.6%
4 11
 
7.8%
3 10
 
7.1%
2 9
 
6.4%
9 8
 
5.7%
5 8
 
5.7%
7 7
 
5.0%
Other values (3) 11
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
57.4%
Space Separator 30
 
21.3%
Dash Punctuation 15
 
10.6%
Other Punctuation 15
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
21.0%
4 11
13.6%
3 10
12.3%
2 9
11.1%
9 8
9.9%
5 8
9.9%
7 7
8.6%
8 5
 
6.2%
0 5
 
6.2%
6 1
 
1.2%
Space Separator
ValueCountFrequency (%)
30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 141
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
30
21.3%
1 17
12.1%
- 15
10.6%
, 15
10.6%
4 11
 
7.8%
3 10
 
7.1%
2 9
 
6.4%
9 8
 
5.7%
5 8
 
5.7%
7 7
 
5.0%
Other values (3) 11
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 141
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30
21.3%
1 17
12.1%
- 15
10.6%
, 15
10.6%
4 11
 
7.8%
3 10
 
7.1%
2 9
 
6.4%
9 8
 
5.7%
5 8
 
5.7%
7 7
 
5.0%
Other values (3) 11
 
7.8%

비과세금액
Text

Distinct23
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-13T04:59:30.130586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.4871795
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

Unique21 ?
Unique (%)53.8%

Sample

1st row1,708,229,000
2nd row2,232,000
3rd row454,283,000
4th row1,464,646,000
5th row250,394,000
ValueCountFrequency (%)
16
41.0%
4,000 2
 
5.1%
98,838,000 1
 
2.6%
1,708,229,000 1
 
2.6%
245,165,000 1
 
2.6%
103,548,000 1
 
2.6%
233,977,000 1
 
2.6%
1,564,827,000 1
 
2.6%
439,512,000 1
 
2.6%
1,394,000 1
 
2.6%
Other values (13) 13
33.3%
2023-12-13T04:59:30.493095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 77
26.4%
, 50
17.1%
32
11.0%
4 21
 
7.2%
2 19
 
6.5%
- 16
 
5.5%
1 15
 
5.1%
3 14
 
4.8%
5 12
 
4.1%
8 11
 
3.8%
Other values (3) 25
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 194
66.4%
Other Punctuation 50
 
17.1%
Space Separator 32
 
11.0%
Dash Punctuation 16
 
5.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 77
39.7%
4 21
 
10.8%
2 19
 
9.8%
1 15
 
7.7%
3 14
 
7.2%
5 12
 
6.2%
8 11
 
5.7%
9 10
 
5.2%
6 9
 
4.6%
7 6
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 50
100.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 292
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 77
26.4%
, 50
17.1%
32
11.0%
4 21
 
7.2%
2 19
 
6.5%
- 16
 
5.5%
1 15
 
5.1%
3 14
 
4.8%
5 12
 
4.1%
8 11
 
3.8%
Other values (3) 25
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 292
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 77
26.4%
, 50
17.1%
32
11.0%
4 21
 
7.2%
2 19
 
6.5%
- 16
 
5.5%
1 15
 
5.1%
3 14
 
4.8%
5 12
 
4.1%
8 11
 
3.8%
Other values (3) 25
 
8.6%

Correlations

2023-12-13T04:59:30.632061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명과세건수과세금액비과세건수비과세금액
과세년도1.0000.0000.0000.0000.0000.000
세목명0.0001.0000.8250.8250.7660.794
과세건수0.0000.8251.0001.0000.9830.979
과세금액0.0000.8251.0001.0000.9830.979
비과세건수0.0000.7660.9830.9831.0001.000
비과세금액0.0000.7940.9790.9791.0001.000
2023-12-13T04:59:30.768950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도
세목명1.0000.000
과세년도0.0001.000
2023-12-13T04:59:30.863684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000

Missing values

2023-12-13T04:59:27.101271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:59:27.313550image/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

시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액
0전라남도완도군468902017취득세9,4708,658,281,0001,5201,708,229,000
1전라남도완도군468902017등록세--72,232,000
2전라남도완도군468902017주민세27,422541,579,0003,143454,283,000
3전라남도완도군468902017재산세59,7752,444,067,00011,8921,464,646,000
4전라남도완도군468902017자동차세32,8505,482,264,0003,519250,394,000
5전라남도완도군468902017레저세----
6전라남도완도군468902017담배소비세1064,601,128,000--
7전라남도완도군468902017지방소비세----
8전라남도완도군468902017등록면허세23,795841,875,0001,448140,264,000
9전라남도완도군468902017도시계획세----
시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액
29전라남도완도군468902019재산세63,2592,790,895,00013,5711,564,827,000
30전라남도완도군468902019자동차세35,7016,948,406,0004,822233,977,000
31전라남도완도군468902019레저세----
32전라남도완도군468902019담배소비세824,480,010,000--
33전라남도완도군468902019지방소비세----
34전라남도완도군468902019등록면허세26,072991,100,0001,810103,548,000
35전라남도완도군468902019도시계획세----
36전라남도완도군468902019지역자원시설세11,387521,695,000754105,713,000
37전라남도완도군468902019지방소득세10,5113,962,517,000--
38전라남도완도군468902019교육세114,4664,122,285,000504,000