Overview

Dataset statistics

Number of variables10
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory88.9 B

Variable types

Categorical6
Text2
Numeric2

Dataset

Description경기도 과천시의 지방세 체납현황으로 세목명, 체납액구간, 체납건수, 체납금액 누적체납건수 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15078690/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
누적체납건수 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:06:16.388681
Analysis finished2023-12-12 01:06:17.499450
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
경기도
27 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 27
100.0%

Length

2023-12-12T10:06:17.578150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:06:17.678710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 27
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
과천시
27 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
과천시 27
100.0%

Length

2023-12-12T10:06:17.789942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:06:17.913196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
과천시 27
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
41290
27 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41290
2nd row41290
3rd row41290
4th row41290
5th row41290

Common Values

ValueCountFrequency (%)
41290 27
100.0%

Length

2023-12-12T10:06:18.048603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:06:18.176185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41290 27
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
2022
27 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 27
100.0%

Length

2023-12-12T10:06:18.298957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:06:18.403593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 27
100.0%

세목명
Categorical

Distinct6
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size348.0 B
지방소득세
10 
재산세
9 
자동차세
3 
주민세
2 
취득세
2 

Length

Max length5
Median length4
Mean length3.9259259
Min length3

Unique

Unique1 ?
Unique (%)3.7%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 10
37.0%
재산세 9
33.3%
자동차세 3
 
11.1%
주민세 2
 
7.4%
취득세 2
 
7.4%
등록면허세 1
 
3.7%

Length

2023-12-12T10:06:18.530769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:06:18.660468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 10
37.0%
재산세 9
33.3%
자동차세 3
 
11.1%
주민세 2
 
7.4%
취득세 2
 
7.4%
등록면허세 1
 
3.7%

체납액구간
Categorical

Distinct10
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
10만원 미만
5 
10만원~30만원미만
4 
30만원~50만원미만
3 
50만원~1백만원미만
3 
1천만원~3천만원미만
3 
Other values (5)
9 

Length

Max length11
Median length11
Mean length10.222222
Min length7

Unique

Unique1 ?
Unique (%)3.7%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 5
18.5%
10만원~30만원미만 4
14.8%
30만원~50만원미만 3
11.1%
50만원~1백만원미만 3
11.1%
1천만원~3천만원미만 3
11.1%
1백만원~3백만원미만 2
 
7.4%
3백만원~5백만원미만 2
 
7.4%
5백만원~1천만원미만 2
 
7.4%
3천만원~5천만원미만 2
 
7.4%
5천만원~1억원미만 1
 
3.7%

Length

2023-12-12T10:06:18.796781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:06:18.941497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 5
15.6%
미만 5
15.6%
10만원~30만원미만 4
12.5%
30만원~50만원미만 3
9.4%
50만원~1백만원미만 3
9.4%
1천만원~3천만원미만 3
9.4%
1백만원~3백만원미만 2
 
6.2%
3백만원~5백만원미만 2
 
6.2%
5백만원~1천만원미만 2
 
6.2%
3천만원~5천만원미만 2
 
6.2%

체납건수
Text

Distinct24
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T10:06:19.114274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2
Min length1

Characters and Unicode

Total characters54
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

Unique21 ?
Unique (%)77.8%

Sample

1st row109
2nd row218
3rd row475
4th row179
5th row230
ValueCountFrequency (%)
1 2
 
7.4%
6 2
 
7.4%
2
 
7.4%
104 1
 
3.7%
179 1
 
3.7%
10 1
 
3.7%
17 1
 
3.7%
475 1
 
3.7%
4 1
 
3.7%
31 1
 
3.7%
Other values (14) 14
51.9%
2023-12-12T10:06:19.456426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
24.1%
7 6
11.1%
4 6
11.1%
5 5
 
9.3%
6 4
 
7.4%
3 4
 
7.4%
2 4
 
7.4%
9 4
 
7.4%
0 4
 
7.4%
- 2
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52
96.3%
Dash Punctuation 2
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
25.0%
7 6
11.5%
4 6
11.5%
5 5
 
9.6%
6 4
 
7.7%
3 4
 
7.7%
2 4
 
7.7%
9 4
 
7.7%
0 4
 
7.7%
8 2
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
24.1%
7 6
11.1%
4 6
11.1%
5 5
 
9.3%
6 4
 
7.4%
3 4
 
7.4%
2 4
 
7.4%
9 4
 
7.4%
0 4
 
7.4%
- 2
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
24.1%
7 6
11.1%
4 6
11.1%
5 5
 
9.3%
6 4
 
7.4%
3 4
 
7.4%
2 4
 
7.4%
9 4
 
7.4%
0 4
 
7.4%
- 2
 
3.7%

체납금액
Text

Distinct26
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T10:06:19.659091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.3703704
Min length3

Characters and Unicode

Total characters199
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

Unique25 ?
Unique (%)92.6%

Sample

1st row2089690
2nd row8905880
3rd row66165390
4th row33882860
5th row6637570
ValueCountFrequency (%)
2
 
7.4%
8905880 1
 
3.7%
272337720 1
 
3.7%
43514760 1
 
3.7%
132471260 1
 
3.7%
40039170 1
 
3.7%
15601290 1
 
3.7%
30231460 1
 
3.7%
7456400 1
 
3.7%
6235730 1
 
3.7%
Other values (16) 16
59.3%
2023-12-12T10:06:20.012790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38
19.1%
3 27
13.6%
6 23
11.6%
2 22
11.1%
8 19
9.5%
1 16
8.0%
7 16
8.0%
4 14
 
7.0%
9 9
 
4.5%
5 9
 
4.5%
Other values (2) 6
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 193
97.0%
Space Separator 4
 
2.0%
Dash Punctuation 2
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38
19.7%
3 27
14.0%
6 23
11.9%
2 22
11.4%
8 19
9.8%
1 16
8.3%
7 16
8.3%
4 14
 
7.3%
9 9
 
4.7%
5 9
 
4.7%
Space Separator
ValueCountFrequency (%)
4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 199
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38
19.1%
3 27
13.6%
6 23
11.6%
2 22
11.1%
8 19
9.5%
1 16
8.0%
7 16
8.0%
4 14
 
7.0%
9 9
 
4.5%
5 9
 
4.5%
Other values (2) 6
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 199
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38
19.1%
3 27
13.6%
6 23
11.6%
2 22
11.1%
8 19
9.5%
1 16
8.0%
7 16
8.0%
4 14
 
7.0%
9 9
 
4.5%
5 9
 
4.5%
Other values (2) 6
 
3.0%

누적체납건수
Real number (ℝ)

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean294.14815
Minimum3
Maximum3316
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T10:06:20.194501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6.2
Q158
median105
Q3246.5
95-th percentile730.1
Maximum3316
Range3313
Interquartile range (IQR)188.5

Descriptive statistics

Standard deviation632.62638
Coefficient of variation (CV)2.1507066
Kurtosis21.887625
Mean294.14815
Median Absolute Deviation (MAD)91
Skewness4.5158353
Sum7942
Variance400216.13
MonotonicityNot monotonic
2023-12-12T10:06:20.376100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
219 1
 
3.7%
302 1
 
3.7%
5 1
 
3.7%
3 1
 
3.7%
14 1
 
3.7%
21 1
 
3.7%
81 1
 
3.7%
72 1
 
3.7%
34 1
 
3.7%
189 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
3 1
3.7%
5 1
3.7%
9 1
3.7%
14 1
3.7%
21 1
3.7%
34 1
3.7%
57 1
3.7%
59 1
3.7%
72 1
3.7%
77 1
3.7%
ValueCountFrequency (%)
3316 1
3.7%
800 1
3.7%
567 1
3.7%
420 1
3.7%
406 1
3.7%
302 1
3.7%
266 1
3.7%
227 1
3.7%
219 1
3.7%
215 1
3.7%

누적체납금액
Real number (ℝ)

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1312534 × 108
Minimum2147580
Maximum6.4442309 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T10:06:20.535577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2147580
5-th percentile4494571
Q112762535
median46772990
Q31.0352879 × 108
95-th percentile5.2055383 × 108
Maximum6.4442309 × 108
Range6.4227551 × 108
Interquartile range (IQR)90766255

Descriptive statistics

Standard deviation1.6797817 × 108
Coefficient of variation (CV)1.4848854
Kurtosis4.7628096
Mean1.1312534 × 108
Median Absolute Deviation (MAD)38889450
Skewness2.287224
Sum3.0543841 × 109
Variance2.8216664 × 1016
MonotonicityNot monotonic
2023-12-12T10:06:20.702714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
4093090 1
 
3.7%
11383970 1
 
3.7%
35937710 1
 
3.7%
2147580 1
 
3.7%
578723630 1
 
3.7%
384824310 1
 
3.7%
644423090 1
 
3.7%
190738230 1
 
3.7%
84949930 1
 
3.7%
142970440 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
2147580 1
3.7%
4093090 1
3.7%
5431360 1
3.7%
7883540 1
3.7%
10003330 1
3.7%
11383970 1
3.7%
11528170 1
3.7%
13996900 1
3.7%
16215880 1
3.7%
25442310 1
3.7%
ValueCountFrequency (%)
644423090 1
3.7%
578723630 1
3.7%
384824310 1
3.7%
248793970 1
3.7%
190738230 1
3.7%
142970440 1
3.7%
111039420 1
3.7%
96018160 1
3.7%
95524480 1
3.7%
89498150 1
3.7%

Interactions

2023-12-12T10:06:16.910769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:06:16.694267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:06:17.029126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:06:16.797185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:06:20.819290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.9971.0000.6330.000
체납액구간0.0001.0000.7880.9370.0000.769
체납건수0.9970.7881.0001.0001.0000.000
체납금액1.0000.9371.0001.0001.0001.000
누적체납건수0.6330.0001.0001.0001.0000.000
누적체납금액0.0000.7690.0001.0000.0001.000
2023-12-12T10:06:20.947923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명
체납액구간1.0000.000
세목명0.0001.000
2023-12-12T10:06:21.036613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
누적체납건수누적체납금액세목명체납액구간
누적체납건수1.000-0.3400.4340.000
누적체납금액-0.3401.0000.0000.493
세목명0.4340.0001.0000.000
체납액구간0.0000.4930.0001.000

Missing values

2023-12-12T10:06:17.209219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:06:17.419237image/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
0경기도과천시412902022등록면허세10만원 미만10920896902194093090
1경기도과천시412902022자동차세10만원 미만218890588030211383970
2경기도과천시412902022자동차세10만원~30만원미만4756616539080080662800
3경기도과천시412902022자동차세30만원~50만원미만1793388286040646772990
4경기도과천시412902022재산세10만원 미만23066375704207883540
5경기도과천시412902022재산세10만원~30만원미만45636842021513996900
6경기도과천시412902022재산세30만원~50만원미만1134734107710003330
7경기도과천시412902022재산세50만원~1백만원미만352080201011025442310
8경기도과천시412902022재산세1백만원~3백만원미만6769963450181111039420
9경기도과천시412902022재산세3백만원~5백만원미만28572286305996018160
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
17경기도과천시412902022지방소득세30만원~50만원미만4962357308711528170
18경기도과천시412902022지방소득세50만원~1백만원미만26745640010529675820
19경기도과천시412902022지방소득세1백만원~3백만원미만3130231460189142970440
20경기도과천시412902022지방소득세3백만원~5백만원미만4156012903484949930
21경기도과천시412902022지방소득세5백만원~1천만원미만64003917072190738230
22경기도과천시412902022지방소득세1천만원~3천만원미만1713247126081644423090
23경기도과천시412902022지방소득세3천만원~5천만원미만14351476021384824310
24경기도과천시412902022지방소득세5천만원~1억원미만627233772014578723630
25경기도과천시412902022취득세50만원~1백만원미만--32147580
26경기도과천시412902022취득세1천만원~3천만원미만--535937710