Overview

Dataset statistics

Number of variables10
Number of observations170
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.4 KiB
Average record size in memory86.8 B

Variable types

Categorical6
Numeric4

Dataset

Description체납액 규모별 체납건수를 납세자 유형별로 제공체납액 구간별 건수 및 금액 누적 체납건수 및 금액 제공체납정책 수립시 기초자료 활용
Author전북특별자치도 완주군
URLhttps://www.data.go.kr/data/15078412/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 started2024-04-21 01:47:07.576002
Analysis finished2024-04-21 01:47:11.051106
Duration3.48 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
전라북도
170 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 170
100.0%

Length

2024-04-21T10:47:11.109120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:47:11.203610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 170
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
완주군
170 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
완주군 170
100.0%

Length

2024-04-21T10:47:11.292362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:47:11.379972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완주군 170
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
45710
170 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row45710
2nd row45710
3rd row45710
4th row45710
5th row45710

Common Values

ValueCountFrequency (%)
45710 170
100.0%

Length

2024-04-21T10:47:11.485660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:47:11.581661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
45710 170
100.0%

과세년도
Categorical

Distinct5
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2020
38 
2019
37 
2021
35 
2018
34 
2017
26 

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 (%)
2020 38
22.4%
2019 37
21.8%
2021 35
20.6%
2018 34
20.0%
2017 26
15.3%

Length

2024-04-21T10:47:11.677061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:47:11.780896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 38
22.4%
2019 37
21.8%
2021 35
20.6%
2018 34
20.0%
2017 26
15.3%

세목명
Categorical

Distinct8
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
지방소득세
44 
재산세
39 
취득세
37 
주민세
24 
자동차세
18 
Other values (3)
8 

Length

Max length7
Median length3
Mean length3.7294118
Min length3

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 44
25.9%
재산세 39
22.9%
취득세 37
21.8%
주민세 24
14.1%
자동차세 18
10.6%
등록면허세 5
 
2.9%
지역자원시설세 2
 
1.2%
등록세 1
 
0.6%

Length

2024-04-21T10:47:11.895318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:47:12.040393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 44
25.9%
재산세 39
22.9%
취득세 37
21.8%
주민세 24
14.1%
자동차세 18
10.6%
등록면허세 5
 
2.9%
지역자원시설세 2
 
1.2%
등록세 1
 
0.6%

체납액구간
Categorical

Distinct11
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
10만원 미만
32 
10만원~30만원미만
25 
30만원~50만원미만
23 
50만원~1백만원미만
23 
1백만원~3백만원미만
17 
Other values (6)
50 

Length

Max length11
Median length11
Mean length10.205882
Min length7

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row10만원 미만
2nd row10만원 미만
3rd row10만원~30만원미만
4th row30만원~50만원미만
5th row50만원~1백만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 32
18.8%
10만원~30만원미만 25
14.7%
30만원~50만원미만 23
13.5%
50만원~1백만원미만 23
13.5%
1백만원~3백만원미만 17
10.0%
3백만원~5백만원미만 15
8.8%
1천만원~3천만원미만 13
7.6%
5백만원~1천만원미만 12
 
7.1%
3천만원~5천만원미만 6
 
3.5%
1억원~3억원미만 3
 
1.8%

Length

2024-04-21T10:47:12.230819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 32
15.8%
미만 32
15.8%
10만원~30만원미만 25
12.4%
30만원~50만원미만 23
11.4%
50만원~1백만원미만 23
11.4%
1백만원~3백만원미만 17
8.4%
3백만원~5백만원미만 15
7.4%
1천만원~3천만원미만 13
6.4%
5백만원~1천만원미만 12
 
5.9%
3천만원~5천만원미만 6
 
3.0%
Other values (2) 4
 
2.0%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)43.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean265.38824
Minimum1
Maximum6074
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-21T10:47:12.363571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median8.5
Q354
95-th percentile1440.75
Maximum6074
Range6073
Interquartile range (IQR)51

Descriptive statistics

Standard deviation839.22803
Coefficient of variation (CV)3.1622654
Kurtosis25.042983
Mean265.38824
Median Absolute Deviation (MAD)7.5
Skewness4.7569381
Sum45116
Variance704303.69
MonotonicityNot monotonic
2024-04-21T10:47:12.493069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 25
 
14.7%
2 13
 
7.6%
4 13
 
7.6%
3 10
 
5.9%
5 9
 
5.3%
7 6
 
3.5%
6 6
 
3.5%
12 5
 
2.9%
10 4
 
2.4%
8 3
 
1.8%
Other values (64) 76
44.7%
ValueCountFrequency (%)
1 25
14.7%
2 13
7.6%
3 10
 
5.9%
4 13
7.6%
5 9
 
5.3%
6 6
 
3.5%
7 6
 
3.5%
8 3
 
1.8%
9 3
 
1.8%
10 4
 
2.4%
ValueCountFrequency (%)
6074 1
0.6%
5333 1
0.6%
4051 1
0.6%
3899 1
0.6%
3048 1
0.6%
2354 1
0.6%
1820 1
0.6%
1704 1
0.6%
1461 1
0.6%
1416 1
0.6%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct170
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33308104
Minimum2750
Maximum2.6818398 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-21T10:47:12.626811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2750
5-th percentile400158
Q13237295
median14603415
Q348572440
95-th percentile1.2860298 × 108
Maximum2.6818398 × 108
Range2.6818123 × 108
Interquartile range (IQR)45335145

Descriptive statistics

Standard deviation44856946
Coefficient of variation (CV)1.3467277
Kurtosis5.7100939
Mean33308104
Median Absolute Deviation (MAD)13413180
Skewness2.1904476
Sum5.6623777 × 109
Variance2.0121456 × 1015
MonotonicityNot monotonic
2024-04-21T10:47:12.778652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
589970 1
 
0.6%
122172650 1
 
0.6%
69825690 1
 
0.6%
3111580 1
 
0.6%
8330970 1
 
0.6%
1934010 1
 
0.6%
2677300 1
 
0.6%
10730470 1
 
0.6%
19823800 1
 
0.6%
62828620 1
 
0.6%
Other values (160) 160
94.1%
ValueCountFrequency (%)
2750 1
0.6%
101960 1
0.6%
102660 1
0.6%
116590 1
0.6%
144610 1
0.6%
153470 1
0.6%
219460 1
0.6%
223850 1
0.6%
294390 1
0.6%
529430 1
0.6%
ValueCountFrequency (%)
268183980 1
0.6%
180487010 1
0.6%
180092680 1
0.6%
171756780 1
0.6%
169893880 1
0.6%
162129900 1
0.6%
146302430 1
0.6%
144850760 1
0.6%
132588700 1
0.6%
123731540 1
0.6%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct92
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean711.41176
Minimum1
Maximum18143
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-21T10:47:13.102227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15.25
median20
Q3119.5
95-th percentile3732.1
Maximum18143
Range18142
Interquartile range (IQR)114.25

Descriptive statistics

Standard deviation2392.0422
Coefficient of variation (CV)3.3623877
Kurtosis28.540561
Mean711.41176
Median Absolute Deviation (MAD)17
Skewness5.0346979
Sum120940
Variance5721865.9
MonotonicityNot monotonic
2024-04-21T10:47:13.257839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 12
 
7.1%
1 10
 
5.9%
5 9
 
5.3%
4 6
 
3.5%
6 6
 
3.5%
7 6
 
3.5%
2 6
 
3.5%
12 4
 
2.4%
27 4
 
2.4%
18 4
 
2.4%
Other values (82) 103
60.6%
ValueCountFrequency (%)
1 10
5.9%
2 6
3.5%
3 12
7.1%
4 6
3.5%
5 9
5.3%
6 6
3.5%
7 6
3.5%
8 2
 
1.2%
9 3
 
1.8%
10 3
 
1.8%
ValueCountFrequency (%)
18143 1
0.6%
15949 1
0.6%
10616 1
0.6%
9445 1
0.6%
8568 1
0.6%
7568 1
0.6%
5214 1
0.6%
4669 1
0.6%
3850 1
0.6%
3588 1
0.6%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct170
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72972785
Minimum51410
Maximum6.0937343 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-21T10:47:13.410017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51410
5-th percentile1091756.5
Q16554077.5
median30852570
Q31.0022909 × 108
95-th percentile2.8829664 × 108
Maximum6.0937343 × 108
Range6.0932202 × 108
Interquartile range (IQR)93675015

Descriptive statistics

Standard deviation1.067005 × 108
Coefficient of variation (CV)1.4621958
Kurtosis7.8223098
Mean72972785
Median Absolute Deviation (MAD)28367850
Skewness2.5691356
Sum1.2405373 × 1010
Variance1.1384997 × 1016
MonotonicityNot monotonic
2024-04-21T10:47:13.557031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1266670 1
 
0.6%
436888750 1
 
0.6%
143966190 1
 
0.6%
5785370 1
 
0.6%
40800780 1
 
0.6%
4362390 1
 
0.6%
8960460 1
 
0.6%
21264310 1
 
0.6%
37397870 1
 
0.6%
207028280 1
 
0.6%
Other values (160) 160
94.1%
ValueCountFrequency (%)
51410 1
0.6%
101960 1
0.6%
153470 1
0.6%
371210 1
0.6%
567610 1
0.6%
571330 1
0.6%
790790 1
0.6%
862000 1
0.6%
1014640 1
0.6%
1186010 1
0.6%
ValueCountFrequency (%)
609373430 1
0.6%
586460730 1
0.6%
452465350 1
0.6%
436888750 1
0.6%
416566850 1
0.6%
360087490 1
0.6%
314716100 1
0.6%
310470830 1
0.6%
294507540 1
0.6%
280705550 1
0.6%

Interactions

2024-04-21T10:47:10.387143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:09.156564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:09.667519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:10.013807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:10.465785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:09.297587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:09.763847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:10.110513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:10.564120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:09.491609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:09.851018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:10.209168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:10.695593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:09.574035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:09.931399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:47:10.297940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:47:13.671858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.2220.0000.164
세목명0.0001.0000.0800.2210.2050.2120.222
체납액구간0.0000.0801.0000.1030.5220.0000.491
체납건수0.0000.2210.1031.0000.7880.9490.679
체납금액0.2220.2050.5220.7881.0000.6200.837
누적체납건수0.0000.2120.0000.9490.6201.0000.682
누적체납금액0.1640.2220.4910.6790.8370.6821.000
2024-04-21T10:47:13.842606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간과세년도
세목명1.0000.0320.000
체납액구간0.0321.0000.000
과세년도0.0000.0001.000
2024-04-21T10:47:14.006042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.3720.9760.4010.0000.0740.044
체납금액0.3721.0000.3390.9720.1360.0700.275
누적체납건수0.9760.3391.0000.4090.0000.1130.000
누적체납금액0.4010.9720.4091.0000.0960.0730.246
과세년도0.0000.1360.0000.0961.0000.0000.000
세목명0.0740.0700.1130.0730.0001.0000.032
체납액구간0.0440.2750.0000.2460.0000.0321.000

Missing values

2024-04-21T10:47:10.821558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:47:10.988654image/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
0전라북도완주군457102017등록면허세10만원 미만46589970871266670
1전라북도완주군457102017자동차세10만원 미만3291441075084535479590
2전라북도완주군457102017자동차세10만원~30만원미만36359703320837138387450
3전라북도완주군457102017자동차세30만원~50만원미만1655295103712675500
4전라북도완주군457102017자동차세50만원~1백만원미만2102215052831810
5전라북도완주군457102017재산세10만원 미만182032065210521486790760
6전라북도완주군457102017재산세10만원~30만원미만65997365012017537670
7전라북도완주군457102017재산세1백만원~3백만원미만613519230918222620
8전라북도완주군457102017재산세1천만원~3천만원미만110996490110996490
9전라북도완주군457102017재산세30만원~50만원미만3110090051751330
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
160전라북도완주군457102021지방소득세50만원~1백만원미만493556269013091676540
161전라북도완주군457102021지방소득세5백만원~1천만원미만1410276347040280705550
162전라북도완주군457102021취득세10만원 미만16694980411822880
163전라북도완주군457102021취득세10만원~30만원미만101461550182684180
164전라북도완주군457102021취득세1백만원~3백만원미만22343141902742726900
165전라북도완주군457102021취득세1천만원~3천만원미만2452879405109702100
166전라북도완주군457102021취득세30만원~50만원미만51925950114229830
167전라북도완주군457102021취득세3백만원~5백만원미만14653720623450280
168전라북도완주군457102021취득세50만원~1백만원미만641016602115541380
169전라북도완주군457102021취득세5백만원~1천만원미만323842580431613120