Overview

Dataset statistics

Number of variables11
Number of observations67
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory92.0 B

Variable types

Categorical6
Text5

Dataset

Description지방세 개방형 데이터 구축된 자료중 2017년 ~ 2021년도에 대한 경상남도 진주시 지방세 징수현황에 대한 자료입니다.
Author경상남도 진주시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15080428

Alerts

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

Reproduction

Analysis started2024-04-06 08:00:52.983220
Analysis finished2024-04-06 08:00:53.830735
Duration0.85 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
경상남도
67 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 67
100.0%

Length

2024-04-06T17:00:53.935924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:00:54.094844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 67
100.0%

시군구명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진주시 67
100.0%

Length

2024-04-06T17:00:54.249525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:00:54.392686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진주시 67
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
48170
67 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48170
2nd row48170
3rd row48170
4th row48170
5th row48170

Common Values

ValueCountFrequency (%)
48170 67
100.0%

Length

2024-04-06T17:00:54.559589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:00:54.713690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48170 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

2024-04-06T17:00:54.862054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:00:55.025399image/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

Distinct27
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Memory size668.0 B
지역자원시설세
 
4
레저세
 
4
재산세
 
4
주민세
 
4
취득세
 
4
Other values (22)
47 

Length

Max length9
Median length7
Mean length4.8059701
Min length3

Unique

Unique13 ?
Unique (%)19.4%

Sample

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

Common Values

ValueCountFrequency (%)
지역자원시설세 4
 
6.0%
레저세 4
 
6.0%
재산세 4
 
6.0%
주민세 4
 
6.0%
취득세 4
 
6.0%
자동차세 4
 
6.0%
과년도수입 4
 
6.0%
담배소비세 4
 
6.0%
도시계획세 4
 
6.0%
등록면허세 4
 
6.0%
Other values (17) 27
40.3%

Length

2024-04-06T17:00:55.196534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지역자원시설세 5
 
7.5%
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%
Other values (4) 17
25.4%

부과금액
Text

Distinct53
Distinct (%)79.1%
Missing0
Missing (%)0.0%
Memory size668.0 B
2024-04-06T17:00:55.510262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.6567164
Min length2

Characters and Unicode

Total characters647
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)77.6%

Sample

1st row
2nd row
3rd row47156625000
4th row7879543000
5th row119589000000
ValueCountFrequency (%)
47156625000 1
 
1.9%
7879543000 1
 
1.9%
62684910000 1
 
1.9%
8241187000 1
 
1.9%
57640472000 1
 
1.9%
9245042000 1
 
1.9%
129371000000 1
 
1.9%
65602980000 1
 
1.9%
18282944000 1
 
1.9%
22938648000 1
 
1.9%
Other values (42) 42
80.8%
2024-04-06T17:00:56.046958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 203
31.4%
82
12.7%
2 50
 
7.7%
8 44
 
6.8%
1 43
 
6.6%
9 41
 
6.3%
5 40
 
6.2%
6 38
 
5.9%
3 38
 
5.9%
4 36
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 565
87.3%
Space Separator 82
 
12.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 203
35.9%
2 50
 
8.8%
8 44
 
7.8%
1 43
 
7.6%
9 41
 
7.3%
5 40
 
7.1%
6 38
 
6.7%
3 38
 
6.7%
4 36
 
6.4%
7 32
 
5.7%
Space Separator
ValueCountFrequency (%)
82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 647
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 203
31.4%
82
12.7%
2 50
 
7.7%
8 44
 
6.8%
1 43
 
6.6%
9 41
 
6.3%
5 40
 
6.2%
6 38
 
5.9%
3 38
 
5.9%
4 36
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 647
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 203
31.4%
82
12.7%
2 50
 
7.7%
8 44
 
6.8%
1 43
 
6.6%
9 41
 
6.3%
5 40
 
6.2%
6 38
 
5.9%
3 38
 
5.9%
4 36
 
5.6%

수납급액
Text

Distinct53
Distinct (%)79.1%
Missing0
Missing (%)0.0%
Memory size668.0 B
2024-04-06T17:00:56.527039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.5970149
Min length2

Characters and Unicode

Total characters643
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)77.6%

Sample

1st row
2nd row
3rd row45971723000
4th row7639547000
5th row119466000000
ValueCountFrequency (%)
45971723000 1
 
1.9%
7639547000 1
 
1.9%
60647742000 1
 
1.9%
8022327000 1
 
1.9%
55955618000 1
 
1.9%
9005116000 1
 
1.9%
129147000000 1
 
1.9%
62353334000 1
 
1.9%
3853191000 1
 
1.9%
22938648000 1
 
1.9%
Other values (42) 42
80.8%
2024-04-06T17:00:57.921193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 205
31.9%
82
 
12.8%
2 57
 
8.9%
5 49
 
7.6%
1 46
 
7.2%
3 40
 
6.2%
6 36
 
5.6%
4 35
 
5.4%
7 33
 
5.1%
8 31
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 561
87.2%
Space Separator 82
 
12.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 205
36.5%
2 57
 
10.2%
5 49
 
8.7%
1 46
 
8.2%
3 40
 
7.1%
6 36
 
6.4%
4 35
 
6.2%
7 33
 
5.9%
8 31
 
5.5%
9 29
 
5.2%
Space Separator
ValueCountFrequency (%)
82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 643
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 205
31.9%
82
 
12.8%
2 57
 
8.9%
5 49
 
7.6%
1 46
 
7.2%
3 40
 
6.2%
6 36
 
5.6%
4 35
 
5.4%
7 33
 
5.1%
8 31
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 643
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 205
31.9%
82
 
12.8%
2 57
 
8.9%
5 49
 
7.6%
1 46
 
7.2%
3 40
 
6.2%
6 36
 
5.6%
4 35
 
5.4%
7 33
 
5.1%
8 31
 
4.8%

환급금액
Text

Distinct49
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Memory size668.0 B
2024-04-06T17:00:58.379696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.3731343
Min length2

Characters and Unicode

Total characters494
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)71.6%

Sample

1st row
2nd row
3rd row105852000
4th row12991000
5th row471411000
ValueCountFrequency (%)
105852000 1
 
2.1%
12991000 1
 
2.1%
3626403000 1
 
2.1%
9705000 1
 
2.1%
98495000 1
 
2.1%
3356000 1
 
2.1%
658581000 1
 
2.1%
391575000 1
 
2.1%
2708018000 1
 
2.1%
27920000 1
 
2.1%
Other values (38) 38
79.2%
2024-04-06T17:00:58.907961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 162
32.8%
86
17.4%
2 38
 
7.7%
1 37
 
7.5%
3 30
 
6.1%
5 29
 
5.9%
4 27
 
5.5%
6 26
 
5.3%
8 22
 
4.5%
9 19
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 408
82.6%
Space Separator 86
 
17.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 162
39.7%
2 38
 
9.3%
1 37
 
9.1%
3 30
 
7.4%
5 29
 
7.1%
4 27
 
6.6%
6 26
 
6.4%
8 22
 
5.4%
9 19
 
4.7%
7 18
 
4.4%
Space Separator
ValueCountFrequency (%)
86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 494
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 162
32.8%
86
17.4%
2 38
 
7.7%
1 37
 
7.5%
3 30
 
6.1%
5 29
 
5.9%
4 27
 
5.5%
6 26
 
5.3%
8 22
 
4.5%
9 19
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 494
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 162
32.8%
86
17.4%
2 38
 
7.7%
1 37
 
7.5%
3 30
 
6.1%
5 29
 
5.9%
4 27
 
5.5%
6 26
 
5.3%
8 22
 
4.5%
9 19
 
3.8%

결손금액
Text

Distinct37
Distinct (%)55.2%
Missing0
Missing (%)0.0%
Memory size668.0 B
2024-04-06T17:00:59.237130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.2089552
Min length2

Characters and Unicode

Total characters349
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)53.7%

Sample

1st row
2nd row
3rd row6000
4th row72000
5th row
ValueCountFrequency (%)
6000 1
 
2.8%
72000 1
 
2.8%
937000 1
 
2.8%
14795000 1
 
2.8%
2810859000 1
 
2.8%
298000 1
 
2.8%
5453000 1
 
2.8%
3993000 1
 
2.8%
217000 1
 
2.8%
37794000 1
 
2.8%
Other values (26) 26
72.2%
2024-04-06T17:00:59.805201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 116
33.2%
98
28.1%
1 20
 
5.7%
9 20
 
5.7%
4 18
 
5.2%
2 17
 
4.9%
3 17
 
4.9%
7 12
 
3.4%
6 11
 
3.2%
5 10
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 251
71.9%
Space Separator 98
 
28.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 116
46.2%
1 20
 
8.0%
9 20
 
8.0%
4 18
 
7.2%
2 17
 
6.8%
3 17
 
6.8%
7 12
 
4.8%
6 11
 
4.4%
5 10
 
4.0%
8 10
 
4.0%
Space Separator
ValueCountFrequency (%)
98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 349
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 116
33.2%
98
28.1%
1 20
 
5.7%
9 20
 
5.7%
4 18
 
5.2%
2 17
 
4.9%
3 17
 
4.9%
7 12
 
3.4%
6 11
 
3.2%
5 10
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 349
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 116
33.2%
98
28.1%
1 20
 
5.7%
9 20
 
5.7%
4 18
 
5.2%
2 17
 
4.9%
3 17
 
4.9%
7 12
 
3.4%
6 11
 
3.2%
5 10
 
2.9%

미수납 금액
Text

Distinct46
Distinct (%)68.7%
Missing0
Missing (%)0.0%
Memory size668.0 B
2024-04-06T17:01:00.182227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.7164179
Min length2

Characters and Unicode

Total characters517
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)67.2%

Sample

1st row
2nd row
3rd row1184896000
4th row239924000
5th row122831000
ValueCountFrequency (%)
1361960000 1
 
2.2%
16860000 1
 
2.2%
1218038000 1
 
2.2%
2037110000 1
 
2.2%
218833000 1
 
2.2%
1675664000 1
 
2.2%
238989000 1
 
2.2%
223910000 1
 
2.2%
3234851000 1
 
2.2%
11618894000 1
 
2.2%
Other values (35) 35
77.8%
2024-04-06T17:01:00.720707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 157
30.4%
89
17.2%
1 49
 
9.5%
2 39
 
7.5%
8 34
 
6.6%
3 31
 
6.0%
4 28
 
5.4%
9 27
 
5.2%
5 25
 
4.8%
6 24
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 428
82.8%
Space Separator 89
 
17.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 157
36.7%
1 49
 
11.4%
2 39
 
9.1%
8 34
 
7.9%
3 31
 
7.2%
4 28
 
6.5%
9 27
 
6.3%
5 25
 
5.8%
6 24
 
5.6%
7 14
 
3.3%
Space Separator
ValueCountFrequency (%)
89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 517
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 157
30.4%
89
17.2%
1 49
 
9.5%
2 39
 
7.5%
8 34
 
6.6%
3 31
 
6.0%
4 28
 
5.4%
9 27
 
5.2%
5 25
 
4.8%
6 24
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 517
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 157
30.4%
89
17.2%
1 49
 
9.5%
2 39
 
7.5%
8 34
 
6.6%
3 31
 
6.0%
4 28
 
5.4%
9 27
 
5.2%
5 25
 
4.8%
6 24
 
4.6%

징수율
Categorical

Distinct27
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Memory size668.0 B
15 
100
7 
99.9
5 
96.9
5 
97
 
3
Other values (22)
32 

Length

Max length4
Median length4
Mean length3.2985075
Min length2

Unique

Unique14 ?
Unique (%)20.9%

Sample

1st row
2nd row
3rd row97.5
4th row97
5th row99.9

Common Values

ValueCountFrequency (%)
15
22.4%
100 7
 
10.4%
99.9 5
 
7.5%
96.9 5
 
7.5%
97 3
 
4.5%
97.2 3
 
4.5%
99.8 3
 
4.5%
97.6 2
 
3.0%
95 2
 
3.0%
97.1 2
 
3.0%
Other values (17) 20
29.9%

Length

2024-04-06T17:01:00.941105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
100 7
 
13.5%
96.9 5
 
9.6%
99.9 5
 
9.6%
97 3
 
5.8%
97.2 3
 
5.8%
99.8 3
 
5.8%
96.7 2
 
3.8%
97.4 2
 
3.8%
96.3 2
 
3.8%
97.1 2
 
3.8%
Other values (16) 18
34.6%

Correlations

2024-04-06T17:01:01.093746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
과세년도1.0000.0000.3490.3490.2390.3580.1500.000
세목명0.0001.0000.9080.9080.8490.8690.7570.869
부과금액0.3490.9081.0001.0001.0001.0001.0001.000
수납급액0.3490.9081.0001.0001.0001.0001.0001.000
환급금액0.2390.8491.0001.0001.0001.0001.0000.998
결손금액0.3580.8691.0001.0001.0001.0001.0000.988
미수납 금액0.1500.7571.0001.0001.0001.0001.0000.998
징수율0.0000.8691.0001.0000.9980.9880.9981.000
2024-04-06T17:01:01.287596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
징수율세목명과세년도
징수율1.0000.3020.000
세목명0.3021.0000.000
과세년도0.0000.0001.000
2024-04-06T17:01:01.443012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명징수율
과세년도1.0000.0000.000
세목명0.0001.0000.302
징수율0.0000.3021.000

Missing values

2024-04-06T17:00:53.492953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:00:53.740111image/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
0경상남도진주시481702017도축세
1경상남도진주시481702017레저세
2경상남도진주시481702017재산세47156625000459717230001058520006000118489600097.5
3경상남도진주시481702017주민세78795430007639547000129910007200023992400097
4경상남도진주시481702017취득세11958900000011946600000047141100012283100099.9
5경상남도진주시481702017자동차세66211206000629282210002846670001192000328179300095
6경상남도진주시481702017과년도수입1514282100048260500001791459000966071000935070000031.9
7경상남도진주시481702017담배소비세2299739100022997391000100
8경상남도진주시481702017도시계획세
9경상남도진주시481702017등록면허세78405960007821711000221120001888500099.8
시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납 금액징수율
57경상남도진주시481702021취득세1244370000001239220000006297640001483200050041300099.6
58경상남도진주시481702021자동차세696933320006641825000040604300019383000325569900095.3
59경상남도진주시481702021과년도수입167323150003671120000422928600012252790001183591600021.9
60경상남도진주시481702021담배소비세2226523600022265236000482000100
61경상남도진주시481702021도시계획세
62경상남도진주시481702021등록면허세2510371600025086316000668760004140001698600099.9
63경상남도진주시481702021지방교육세389794520003776274500018108100010465000120624200096.9
64경상남도진주시481702021지방소득세8841360800085934062000392974000065563000241398300097.2
65경상남도진주시481702021지방소비세1058556000010585560000100
66경상남도진주시481702021지역자원시설세9411902000905920100028135000794900034475200096.3