Overview

Dataset statistics

Number of variables10
Number of observations178
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.1 KiB
Average record size in memory86.7 B

Variable types

Categorical6
Numeric4

Dataset

Description경상북도 구미시의 지방세 체납액 규모별 체납현황에 대한 데이터로 지방자치단체코드, 과세연도, 세목명, 체납액 구간, 체납건수, 체납금액, 누적 체납건수, 누적체납금액를 제공합니다. ※ 매년 통계연감이 확정된 최근 3년간 자료를 연도별로 나타냄
URLhttps://www.data.go.kr/data/15078362/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
체납건수 is highly overall correlated with 누적체납건수High correlation
체납금액 is highly overall correlated with 누적체납금액High correlation
누적체납건수 is highly overall correlated with 체납건수High correlation
누적체납금액 is highly overall correlated with 체납금액High correlation
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:32:10.047505
Analysis finished2023-12-12 11:32:13.425903
Duration3.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
경상북도
178 

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 178
100.0%

Length

2023-12-12T20:32:13.536896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:32:13.733367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 178
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
구미시
178 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구미시 178
100.0%

Length

2023-12-12T20:32:14.018984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:32:14.186010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구미시 178
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
47190
178 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47190
2nd row47190
3rd row47190
4th row47190
5th row47190

Common Values

ValueCountFrequency (%)
47190 178
100.0%

Length

2023-12-12T20:32:14.362425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:32:14.543169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47190 178
100.0%

과세년도
Categorical

Distinct4
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2018
46 
2019
46 
2021
44 
2020
42 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 46
25.8%
2019 46
25.8%
2021 44
24.7%
2020 42
23.6%

Length

2023-12-12T20:32:14.727034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:32:14.908841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 46
25.8%
2019 46
25.8%
2021 44
24.7%
2020 42
23.6%

세목명
Categorical

Distinct7
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
지방소득세
43 
취득세
39 
재산세
38 
주민세
21 
자동차세
16 
Other values (2)
21 

Length

Max length7
Median length3
Mean length3.9325843
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 43
24.2%
취득세 39
21.9%
재산세 38
21.3%
주민세 21
11.8%
자동차세 16
 
9.0%
지역자원시설세 11
 
6.2%
등록면허세 10
 
5.6%

Length

2023-12-12T20:32:15.114749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:32:15.365991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 43
24.2%
취득세 39
21.9%
재산세 38
21.3%
주민세 21
11.8%
자동차세 16
 
9.0%
지역자원시설세 11
 
6.2%
등록면허세 10
 
5.6%

체납액구간
Categorical

Distinct13
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
10만원 미만
28 
10만원~30만원미만
26 
30만원~50만원미만
22 
50만원~1백만원미만
21 
1백만원~3백만원미만
16 
Other values (8)
65 

Length

Max length11
Median length11
Mean length10.213483
Min length7

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row10만원 미만
2nd row10만원~30만원미만
3rd row1천만원~3천만원미만
4th row5백만원~1천만원미만
5th row10만원 미만

Common Values

ValueCountFrequency (%)
10만원 미만 28
15.7%
10만원~30만원미만 26
14.6%
30만원~50만원미만 22
12.4%
50만원~1백만원미만 21
11.8%
1백만원~3백만원미만 16
9.0%
5백만원~1천만원미만 14
7.9%
1천만원~3천만원미만 13
7.3%
3백만원~5백만원미만 12
6.7%
5천만원~1억원미만 9
 
5.1%
3천만원~5천만원미만 7
 
3.9%
Other values (3) 10
 
5.6%

Length

2023-12-12T20:32:15.685713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 28
13.6%
미만 28
13.6%
10만원~30만원미만 26
12.6%
30만원~50만원미만 22
10.7%
50만원~1백만원미만 21
10.2%
1백만원~3백만원미만 16
7.8%
5백만원~1천만원미만 14
6.8%
1천만원~3천만원미만 13
6.3%
3백만원~5백만원미만 12
5.8%
5천만원~1억원미만 9
 
4.4%
Other values (4) 17
8.3%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)53.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean789.91573
Minimum1
Maximum20250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T20:32:15.933332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median17
Q3149
95-th percentile5275
Maximum20250
Range20249
Interquartile range (IQR)145

Descriptive statistics

Standard deviation2558.8159
Coefficient of variation (CV)3.239353
Kurtosis31.249624
Mean789.91573
Median Absolute Deviation (MAD)16
Skewness5.1255492
Sum140605
Variance6547538.9
MonotonicityNot monotonic
2023-12-12T20:32:16.805179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 21
 
11.8%
2 11
 
6.2%
3 11
 
6.2%
17 6
 
3.4%
7 6
 
3.4%
4 6
 
3.4%
8 5
 
2.8%
15 4
 
2.2%
5 4
 
2.2%
31 4
 
2.2%
Other values (85) 100
56.2%
ValueCountFrequency (%)
1 21
11.8%
2 11
6.2%
3 11
6.2%
4 6
 
3.4%
5 4
 
2.2%
6 2
 
1.1%
7 6
 
3.4%
8 5
 
2.8%
9 3
 
1.7%
10 4
 
2.2%
ValueCountFrequency (%)
20250 1
0.6%
18110 1
0.6%
10071 1
0.6%
9300 1
0.6%
6770 1
0.6%
6606 1
0.6%
6289 1
0.6%
5327 1
0.6%
5309 1
0.6%
5269 1
0.6%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct178
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.369886 × 108
Minimum111240
Maximum1.3216909 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T20:32:17.119028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum111240
5-th percentile514623
Q18922310
median70608830
Q32.178142 × 108
95-th percentile4.1459861 × 108
Maximum1.3216909 × 109
Range1.3215797 × 109
Interquartile range (IQR)2.0889189 × 108

Descriptive statistics

Standard deviation1.9202294 × 108
Coefficient of variation (CV)1.401744
Kurtosis12.120742
Mean1.369886 × 108
Median Absolute Deviation (MAD)67919775
Skewness2.9519161
Sum2.438397 × 1010
Variance3.6872809 × 1016
MonotonicityNot monotonic
2023-12-12T20:32:17.412605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7747840 1
 
0.6%
25100850 1
 
0.6%
121904400 1
 
0.6%
249690430 1
 
0.6%
105160490 1
 
0.6%
227423830 1
 
0.6%
325110 1
 
0.6%
616080 1
 
0.6%
576550 1
 
0.6%
3729980 1
 
0.6%
Other values (168) 168
94.4%
ValueCountFrequency (%)
111240 1
0.6%
192650 1
0.6%
259810 1
0.6%
321360 1
0.6%
325110 1
0.6%
370350 1
0.6%
392700 1
0.6%
399520 1
0.6%
466700 1
0.6%
523080 1
0.6%
ValueCountFrequency (%)
1321690940 1
0.6%
1045645090 1
0.6%
888829600 1
0.6%
865825680 1
0.6%
742409950 1
0.6%
589311120 1
0.6%
528770450 1
0.6%
496760860 1
0.6%
438498170 1
0.6%
410381040 1
0.6%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct136
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3554.7416
Minimum1
Maximum61365
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T20:32:17.679820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.85
Q119.25
median137.5
Q3671.5
95-th percentile31625.7
Maximum61365
Range61364
Interquartile range (IQR)652.25

Descriptive statistics

Standard deviation10660.488
Coefficient of variation (CV)2.9989489
Kurtosis12.142516
Mean3554.7416
Median Absolute Deviation (MAD)125
Skewness3.524663
Sum632744
Variance1.1364601 × 108
MonotonicityNot monotonic
2023-12-12T20:32:17.954901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17 5
 
2.8%
22 4
 
2.2%
9 4
 
2.2%
15 3
 
1.7%
7 3
 
1.7%
12 3
 
1.7%
8 3
 
1.7%
16 3
 
1.7%
151 3
 
1.7%
10 3
 
1.7%
Other values (126) 144
80.9%
ValueCountFrequency (%)
1 3
1.7%
2 3
1.7%
3 1
 
0.6%
4 2
1.1%
5 3
1.7%
6 2
1.1%
7 3
1.7%
8 3
1.7%
9 4
2.2%
10 3
1.7%
ValueCountFrequency (%)
61365 1
0.6%
58098 1
0.6%
41270 1
0.6%
41171 1
0.6%
41115 1
0.6%
40231 1
0.6%
39918 1
0.6%
36001 1
0.6%
34922 1
0.6%
31044 1
0.6%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct178
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.910285 × 108
Minimum432600
Maximum6.6957899 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T20:32:18.225305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum432600
5-th percentile3452225.5
Q164773258
median3.0451046 × 108
Q38.0625975 × 108
95-th percentile1.5587061 × 109
Maximum6.6957899 × 109
Range6.6953573 × 109
Interquartile range (IQR)7.4148649 × 108

Descriptive statistics

Standard deviation9.6057005 × 108
Coefficient of variation (CV)1.6252517
Kurtosis23.220395
Mean5.910285 × 108
Median Absolute Deviation (MAD)2.8163586 × 108
Skewness4.3399464
Sum1.0520307 × 1011
Variance9.2269482 × 1017
MonotonicityNot monotonic
2023-12-12T20:32:18.505023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25640690 1
 
0.6%
61971230 1
 
0.6%
866579220 1
 
0.6%
866465860 1
 
0.6%
505985920 1
 
0.6%
1284430690 1
 
0.6%
1072240 1
 
0.6%
3655350 1
 
0.6%
8887120 1
 
0.6%
27055690 1
 
0.6%
Other values (168) 168
94.4%
ValueCountFrequency (%)
432600 1
0.6%
487320 1
0.6%
543840 1
0.6%
747130 1
0.6%
1072240 1
0.6%
1191910 1
0.6%
2393720 1
0.6%
2646570 1
0.6%
3039270 1
0.6%
3525100 1
0.6%
ValueCountFrequency (%)
6695789860 1
0.6%
6675348660 1
0.6%
5806960260 1
0.6%
4761315170 1
0.6%
1951154590 1
0.6%
1939215530 1
0.6%
1801655640 1
0.6%
1714629130 1
0.6%
1577595220 1
0.6%
1555372780 1
0.6%

Interactions

2023-12-12T20:32:12.506882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:10.590180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:11.281979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:11.888646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:12.659853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:10.775846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:11.441837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:12.054243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:12.798343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:10.944205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:11.586428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:12.198000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:12.925988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:11.093760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:11.737432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:32:12.355024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:32:18.704187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.1500.0000.037
세목명0.0001.0000.1280.6250.3570.4260.392
체납액구간0.0000.1281.0000.0000.6950.0000.411
체납건수0.0000.6250.0001.0000.6290.8950.630
체납금액0.1500.3570.6950.6291.0000.7630.966
누적체납건수0.0000.4260.0000.8950.7631.0000.784
누적체납금액0.0370.3920.4110.6300.9660.7841.000
2023-12-12T20:32:18.917703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도체납액구간세목명
과세년도1.0000.0000.000
체납액구간0.0001.0000.055
세목명0.0000.0551.000
2023-12-12T20:32:19.088733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.3610.9520.3060.0000.2600.000
체납금액0.3611.0000.2460.9330.0940.1970.383
누적체납건수0.9520.2461.0000.2630.0000.2430.000
누적체납금액0.3060.9330.2631.0000.0300.2460.211
과세년도0.0000.0940.0000.0301.0000.0000.000
세목명0.2600.1970.2430.2460.0001.0000.055
체납액구간0.0000.3830.0000.2110.0000.0551.000

Missing values

2023-12-12T20:32:13.124631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:32:13.338868image/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
0경상북도구미시471902018등록면허세10만원 미만4157747840139825640690
1경상북도구미시471902018등록면허세10만원~30만원미만33213604432600
2경상북도구미시471902018등록면허세1천만원~3천만원미만220250720220250720
3경상북도구미시471902018등록면허세5백만원~1천만원미만1942951019429510
4경상북도구미시471902018자동차세10만원 미만3316154358270309041519096760
5경상북도구미시471902018자동차세10만원~30만원미만4580742409950297124761315170
6경상북도구미시471902018자동차세30만원~50만원미만12241761780952339611650
7경상북도구미시471902018자동차세50만원~1백만원미만158332080177110193920
8경상북도구미시471902018재산세10만원 미만351911455052011915377076950
9경상북도구미시471902018재산세10만원~30만원미만633922037301918300137670
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
168경상북도구미시471902021취득세10만원 미만178603301828135160
169경상북도구미시471902021취득세10만원~30만원미만9177909012923544990
170경상북도구미시471902021취득세1백만원~3백만원미만1628522950101175380040
171경상북도구미시471902021취득세1억원~3억원미만229631695071271309440
172경상북도구미시471902021취득세1천만원~3천만원미만36497309016313193320
173경상북도구미시471902021취득세30만원~50만원미만41612940176555890
174경상북도구미시471902021취득세3백만원~5백만원미만273411001764049110
175경상북도구미시471902021취득세50만원~1백만원미만642510509366945700
176경상북도구미시471902021취득세5백만원~1천만원미만1878328020143187210
177경상북도구미시471902021취득세5천만원~1억원미만4281051220171188172750