Overview

Dataset statistics

Number of variables10
Number of observations78
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory84.7 B

Variable types

Categorical6
Numeric1
Text3

Dataset

Description체납액 규모별 체납건수를 납세자 유형별로 제공합니다. 그리고 체납정책 수립시 기초자료로 활용되는 데이터를 제공합니다.
Author경상북도 성주군
URLhttps://www.data.go.kr/data/15078624/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2024-04-17 18:42:26.301750
Analysis finished2024-04-17 18:42:26.780603
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
경상북도
78 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 78
100.0%

Length

2024-04-18T03:42:26.826585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:42:26.892737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 78
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
성주군
78 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성주군 78
100.0%

Length

2024-04-18T03:42:26.963244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:42:27.031304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성주군 78
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
47840
78 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47840
2nd row47840
3rd row47840
4th row47840
5th row47840

Common Values

ValueCountFrequency (%)
47840 78
100.0%

Length

2024-04-18T03:42:27.101078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:42:27.170289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47840 78
100.0%

과세년도
Categorical

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size756.0 B
2019
29 
2018
26 
2017
23 

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 (%)
2019 29
37.2%
2018 26
33.3%
2017 23
29.5%

Length

2024-04-18T03:42:27.238913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:42:27.313009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 29
37.2%
2018 26
33.3%
2017 23
29.5%

세목명
Categorical

Distinct6
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size756.0 B
지방소득세
23 
재산세
19 
취득세
15 
자동차세
9 
주민세
9 

Length

Max length5
Median length3
Mean length3.7820513
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row등록면허세
2nd row자동차세
3rd row자동차세
4th row자동차세
5th row재산세

Common Values

ValueCountFrequency (%)
지방소득세 23
29.5%
재산세 19
24.4%
취득세 15
19.2%
자동차세 9
 
11.5%
주민세 9
 
11.5%
등록면허세 3
 
3.8%

Length

2024-04-18T03:42:27.405549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:42:27.510300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 23
29.5%
재산세 19
24.4%
취득세 15
19.2%
자동차세 9
 
11.5%
주민세 9
 
11.5%
등록면허세 3
 
3.8%

체납액구간
Categorical

Distinct10
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size756.0 B
10만원 미만
18 
10만원~30만원미만
15 
30만원~50만원미만
13 
1백만원~3백만원미만
9 
50만원~1백만원미만
9 
Other values (5)
14 

Length

Max length11
Median length11
Mean length10.064103
Min length7

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st row10만원 미만
2nd row10만원 미만
3rd row10만원~30만원미만
4th row30만원~50만원미만
5th row10만원 미만

Common Values

ValueCountFrequency (%)
10만원 미만 18
23.1%
10만원~30만원미만 15
19.2%
30만원~50만원미만 13
16.7%
1백만원~3백만원미만 9
11.5%
50만원~1백만원미만 9
11.5%
3백만원~5백만원미만 7
 
9.0%
5백만원~1천만원미만 3
 
3.8%
1천만원~3천만원미만 2
 
2.6%
3천만원~5천만원미만 1
 
1.3%
5천만원~1억원미만 1
 
1.3%

Length

2024-04-18T03:42:27.609659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:42:27.725096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 18
18.8%
미만 18
18.8%
10만원~30만원미만 15
15.6%
30만원~50만원미만 13
13.5%
1백만원~3백만원미만 9
9.4%
50만원~1백만원미만 9
9.4%
3백만원~5백만원미만 7
 
7.3%
5백만원~1천만원미만 3
 
3.1%
1천만원~3천만원미만 2
 
2.1%
3천만원~5천만원미만 1
 
1.0%

체납건수
Real number (ℝ)

Distinct37
Distinct (%)47.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.461538
Minimum1
Maximum906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2024-04-18T03:42:27.840030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6.5
Q326.25
95-th percentile482.7
Maximum906
Range905
Interquartile range (IQR)23.25

Descriptive statistics

Standard deviation179.66084
Coefficient of variation (CV)2.3193555
Kurtosis8.2634646
Mean77.461538
Median Absolute Deviation (MAD)5.5
Skewness2.9136095
Sum6042
Variance32278.018
MonotonicityNot monotonic
2024-04-18T03:42:27.947525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 11
 
14.1%
3 10
 
12.8%
2 7
 
9.0%
4 5
 
6.4%
24 3
 
3.8%
11 3
 
3.8%
5 3
 
3.8%
7 3
 
3.8%
6 3
 
3.8%
27 2
 
2.6%
Other values (27) 28
35.9%
ValueCountFrequency (%)
1 11
14.1%
2 7
9.0%
3 10
12.8%
4 5
6.4%
5 3
 
3.8%
6 3
 
3.8%
7 3
 
3.8%
8 1
 
1.3%
9 1
 
1.3%
10 1
 
1.3%
ValueCountFrequency (%)
906 1
1.3%
689 1
1.3%
628 1
1.3%
617 1
1.3%
459 1
1.3%
403 1
1.3%
401 1
1.3%
388 1
1.3%
301 1
1.3%
208 1
1.3%

체납금액
Text

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2024-04-18T03:42:28.157254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.987179
Min length9

Characters and Unicode

Total characters857
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)100.0%

Sample

1st row 332,160
2nd row 17,297,610
3rd row 14,870,240
4th row 964,380
5th row 7,879,530
ValueCountFrequency (%)
332,160 1
 
1.3%
1,176,810 1
 
1.3%
26,340,240 1
 
1.3%
8,932,800 1
 
1.3%
16,348,860 1
 
1.3%
6,421,700 1
 
1.3%
66,125,550 1
 
1.3%
31,726,790 1
 
1.3%
1,039,240 1
 
1.3%
1,099,880 1
 
1.3%
Other values (68) 68
87.2%
2024-04-18T03:42:28.481184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
156
18.2%
, 143
16.7%
0 118
13.8%
1 70
8.2%
7 59
 
6.9%
3 51
 
6.0%
6 51
 
6.0%
2 49
 
5.7%
4 49
 
5.7%
8 39
 
4.6%
Other values (2) 72
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 558
65.1%
Space Separator 156
 
18.2%
Other Punctuation 143
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 118
21.1%
1 70
12.5%
7 59
10.6%
3 51
9.1%
6 51
9.1%
2 49
8.8%
4 49
8.8%
8 39
 
7.0%
5 38
 
6.8%
9 34
 
6.1%
Space Separator
ValueCountFrequency (%)
156
100.0%
Other Punctuation
ValueCountFrequency (%)
, 143
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 857
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
156
18.2%
, 143
16.7%
0 118
13.8%
1 70
8.2%
7 59
 
6.9%
3 51
 
6.0%
6 51
 
6.0%
2 49
 
5.7%
4 49
 
5.7%
8 39
 
4.6%
Other values (2) 72
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 857
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
156
18.2%
, 143
16.7%
0 118
13.8%
1 70
8.2%
7 59
 
6.9%
3 51
 
6.0%
6 51
 
6.0%
2 49
 
5.7%
4 49
 
5.7%
8 39
 
4.6%
Other values (2) 72
8.4%

누적체납건수
Text

Distinct48
Distinct (%)61.5%
Missing0
Missing (%)0.0%
Memory size756.0 B
2024-04-18T03:42:28.645019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.0512821
Min length3

Characters and Unicode

Total characters316
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)42.3%

Sample

1st row 94
2nd row 1,656
3rd row 374
4th row 11
5th row 1,971
ValueCountFrequency (%)
7 5
 
6.4%
15 5
 
6.4%
5 5
 
6.4%
12 3
 
3.8%
1 3
 
3.8%
6 3
 
3.8%
9 3
 
3.8%
18 3
 
3.8%
8 3
 
3.8%
4 2
 
2.6%
Other values (38) 43
55.1%
2024-04-18T03:42:28.912134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
156
49.4%
1 32
 
10.1%
2 21
 
6.6%
5 19
 
6.0%
4 15
 
4.7%
6 14
 
4.4%
3 14
 
4.4%
7 13
 
4.1%
9 10
 
3.2%
8 10
 
3.2%
Other values (2) 12
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Space Separator 156
49.4%
Decimal Number 153
48.4%
Other Punctuation 7
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 32
20.9%
2 21
13.7%
5 19
12.4%
4 15
9.8%
6 14
9.2%
3 14
9.2%
7 13
8.5%
9 10
 
6.5%
8 10
 
6.5%
0 5
 
3.3%
Space Separator
ValueCountFrequency (%)
156
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 316
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
156
49.4%
1 32
 
10.1%
2 21
 
6.6%
5 19
 
6.0%
4 15
 
4.7%
6 14
 
4.4%
3 14
 
4.4%
7 13
 
4.1%
9 10
 
3.2%
8 10
 
3.2%
Other values (2) 12
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 316
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
156
49.4%
1 32
 
10.1%
2 21
 
6.6%
5 19
 
6.0%
4 15
 
4.7%
6 14
 
4.4%
3 14
 
4.4%
7 13
 
4.1%
9 10
 
3.2%
8 10
 
3.2%
Other values (2) 12
 
3.8%

누적체납금액
Text

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2024-04-18T03:42:29.132087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.474359
Min length9

Characters and Unicode

Total characters895
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)100.0%

Sample

1st row 1,008,300
2nd row 97,089,300
3rd row 58,162,700
4th row 3,621,920
5th row 33,350,050
ValueCountFrequency (%)
1,008,300 1
 
1.3%
4,756,660 1
 
1.3%
56,624,390 1
 
1.3%
23,748,920 1
 
1.3%
61,075,730 1
 
1.3%
11,425,870 1
 
1.3%
151,262,360 1
 
1.3%
148,846,050 1
 
1.3%
3,803,260 1
 
1.3%
9,691,310 1
 
1.3%
Other values (68) 68
87.2%
2024-04-18T03:42:29.456639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
156
17.4%
, 153
17.1%
0 122
13.6%
1 76
8.5%
6 59
 
6.6%
3 57
 
6.4%
2 57
 
6.4%
4 52
 
5.8%
7 46
 
5.1%
5 45
 
5.0%
Other values (2) 72
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 586
65.5%
Space Separator 156
 
17.4%
Other Punctuation 153
 
17.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 122
20.8%
1 76
13.0%
6 59
10.1%
3 57
9.7%
2 57
9.7%
4 52
8.9%
7 46
 
7.8%
5 45
 
7.7%
8 40
 
6.8%
9 32
 
5.5%
Space Separator
ValueCountFrequency (%)
156
100.0%
Other Punctuation
ValueCountFrequency (%)
, 153
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 895
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
156
17.4%
, 153
17.1%
0 122
13.6%
1 76
8.5%
6 59
 
6.6%
3 57
 
6.4%
2 57
 
6.4%
4 52
 
5.8%
7 46
 
5.1%
5 45
 
5.0%
Other values (2) 72
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 895
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
156
17.4%
, 153
17.1%
0 122
13.6%
1 76
8.5%
6 59
 
6.6%
3 57
 
6.4%
2 57
 
6.4%
4 52
 
5.8%
7 46
 
5.1%
5 45
 
5.0%
Other values (2) 72
8.0%

Interactions

2024-04-18T03:42:26.560147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T03:42:29.537058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0001.0000.2391.000
세목명0.0001.0000.0000.4021.0000.7541.000
체납액구간0.0000.0001.0000.0001.0000.0001.000
체납건수0.0000.4020.0001.0001.0001.0001.000
체납금액1.0001.0001.0001.0001.0001.0001.000
누적체납건수0.2390.7540.0001.0001.0001.0001.000
누적체납금액1.0001.0001.0001.0001.0001.0001.000
2024-04-18T03:42:29.617056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간과세년도
세목명1.0000.0000.000
체납액구간0.0001.0000.000
과세년도0.0000.0001.000
2024-04-18T03:42:29.683638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수과세년도세목명체납액구간
체납건수1.0000.0000.2050.000
과세년도0.0001.0000.0000.000
세목명0.2050.0001.0000.000
체납액구간0.0000.0000.0001.000

Missing values

2024-04-18T03:42:26.637673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T03:42:26.739940image/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

시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
0경상북도성주군478402017등록면허세10만원 미만27332,160941,008,300
1경상북도성주군478402017자동차세10만원 미만30117,297,6101,65697,089,300
2경상북도성주군478402017자동차세10만원~30만원미만8814,870,24037458,162,700
3경상북도성주군478402017자동차세30만원~50만원미만3964,380113,621,920
4경상북도성주군478402017재산세10만원 미만4597,879,5301,97133,350,050
5경상북도성주군478402017재산세10만원~30만원미만172,813,420568,891,720
6경상북도성주군478402017재산세1백만원~3백만원미만45,011,090913,135,100
7경상북도성주군478402017재산세30만원~50만원미만72,443,820155,589,360
8경상북도성주군478402017재산세3백만원~5백만원미만27,127,16027,127,160
9경상북도성주군478402017재산세50만원~1백만원미만74,832,63096,283,640
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
68경상북도성주군478402019지방소득세30만원~50만원미만125,028,7502711,224,080
69경상북도성주군478402019지방소득세3백만원~5백만원미만517,980,9101349,147,670
70경상북도성주군478402019지방소득세50만원~1백만원미만107,359,8903625,722,930
71경상북도성주군478402019지방소득세5백만원~1천만원미만19,263,980536,825,180
72경상북도성주군478402019취득세10만원 미만9344,150271,108,150
73경상북도성주군478402019취득세10만원~30만원미만3484,230244,518,800
74경상북도성주군478402019취득세1백만원~3백만원미만12,853,690812,545,000
75경상북도성주군478402019취득세30만원~50만원미만31,283,75052,102,380
76경상북도성주군478402019취득세3백만원~5백만원미만14,476,420414,719,930
77경상북도성주군478402019취득세50만원~1백만원미만21,767,66096,524,320