Overview

Dataset statistics

Number of variables10
Number of observations73
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory87.8 B

Variable types

Categorical6
Numeric4

Dataset

Description2017~2020년 체납액 규모별 체납 건수를 납세자 유형별로 제공하는 자료로써 체납정책 수립시 기초자료로 활용된다.
Author강원도 화천군
URLhttps://www.data.go.kr/data/15080137/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 12:44:53.292088
Analysis finished2023-12-12 12:44:56.428107
Duration3.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
강원도
73 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원도 73
100.0%

Length

2023-12-12T21:44:56.509283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:44:56.607441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 73
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
화천군
73 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
화천군 73
100.0%

Length

2023-12-12T21:44:56.722688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:44:56.821407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화천군 73
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
42790
73 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row42790
2nd row42790
3rd row42790
4th row42790
5th row42790

Common Values

ValueCountFrequency (%)
42790 73
100.0%

Length

2023-12-12T21:44:56.937418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:44:57.059104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
42790 73
100.0%

과세년도
Categorical

Distinct4
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
2020
22 
2019
20 
2018
19 
2017
12 

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 22
30.1%
2019 20
27.4%
2018 19
26.0%
2017 12
16.4%

Length

2023-12-12T21:44:57.218989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:44:57.350941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 22
30.1%
2019 20
27.4%
2018 19
26.0%
2017 12
16.4%

세목명
Categorical

Distinct6
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size716.0 B
지방소득세
23 
재산세
21 
자동차세
11 
취득세
9 
주민세
5 

Length

Max length5
Median length4
Mean length3.890411
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 23
31.5%
재산세 21
28.8%
자동차세 11
15.1%
취득세 9
 
12.3%
주민세 5
 
6.8%
등록면허세 4
 
5.5%

Length

2023-12-12T21:44:57.514428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:44:57.674666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 23
31.5%
재산세 21
28.8%
자동차세 11
15.1%
취득세 9
 
12.3%
주민세 5
 
6.8%
등록면허세 4
 
5.5%

체납액구간
Categorical

Distinct8
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size716.0 B
10만원 미만
23 
10만원~30만원미만
14 
50만원~1백만원미만
9 
30만원~50만원미만
9 
1천만원~3천만원미만
7 
Other values (3)
11 

Length

Max length11
Median length11
Mean length9.739726
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 23
31.5%
10만원~30만원미만 14
19.2%
50만원~1백만원미만 9
 
12.3%
30만원~50만원미만 9
 
12.3%
1천만원~3천만원미만 7
 
9.6%
1백만원~3백만원미만 7
 
9.6%
3천만원~5천만원미만 2
 
2.7%
5백만원~1천만원미만 2
 
2.7%

Length

2023-12-12T21:44:57.847578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:44:58.003392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 23
24.0%
미만 23
24.0%
10만원~30만원미만 14
14.6%
50만원~1백만원미만 9
 
9.4%
30만원~50만원미만 9
 
9.4%
1천만원~3천만원미만 7
 
7.3%
1백만원~3백만원미만 7
 
7.3%
3천만원~5천만원미만 2
 
2.1%
5백만원~1천만원미만 2
 
2.1%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.520548
Minimum1
Maximum1007
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T21:44:58.154899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q329
95-th percentile333.2
Maximum1007
Range1006
Interquartile range (IQR)27

Descriptive statistics

Standard deviation172.02189
Coefficient of variation (CV)2.5105154
Kurtosis16.916164
Mean68.520548
Median Absolute Deviation (MAD)3
Skewness3.9002209
Sum5002
Variance29591.531
MonotonicityNot monotonic
2023-12-12T21:44:58.299504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 18
24.7%
2 13
17.8%
3 5
 
6.8%
4 3
 
4.1%
5 3
 
4.1%
8 3
 
4.1%
9 2
 
2.7%
19 2
 
2.7%
62 1
 
1.4%
833 1
 
1.4%
Other values (22) 22
30.1%
ValueCountFrequency (%)
1 18
24.7%
2 13
17.8%
3 5
 
6.8%
4 3
 
4.1%
5 3
 
4.1%
6 1
 
1.4%
8 3
 
4.1%
9 2
 
2.7%
11 1
 
1.4%
14 1
 
1.4%
ValueCountFrequency (%)
1007 1
1.4%
833 1
1.4%
481 1
1.4%
383 1
1.4%
300 1
1.4%
253 1
1.4%
246 1
1.4%
224 1
1.4%
170 1
1.4%
148 1
1.4%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6567797.7
Minimum16020
Maximum45277790
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T21:44:58.453296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16020
5-th percentile112962
Q1854730
median2349370
Q39016370
95-th percentile27443786
Maximum45277790
Range45261770
Interquartile range (IQR)8161640

Descriptive statistics

Standard deviation9695770.6
Coefficient of variation (CV)1.476259
Kurtosis5.1304153
Mean6567797.7
Median Absolute Deviation (MAD)2069330
Skewness2.2690215
Sum4.7944923 × 108
Variance9.4007967 × 1013
MonotonicityNot monotonic
2023-12-12T21:44:58.625706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180890 1
 
1.4%
22057650 1
 
1.4%
29146760 1
 
1.4%
9769720 1
 
1.4%
2070460 1
 
1.4%
5461710 1
 
1.4%
16020 1
 
1.4%
26308470 1
 
1.4%
3138010 1
 
1.4%
671210 1
 
1.4%
Other values (63) 63
86.3%
ValueCountFrequency (%)
16020 1
1.4%
23420 1
1.4%
54220 1
1.4%
108600 1
1.4%
115870 1
1.4%
171350 1
1.4%
180890 1
1.4%
258190 1
1.4%
274140 1
1.4%
310770 1
1.4%
ValueCountFrequency (%)
45277790 1
1.4%
41312060 1
1.4%
31461930 1
1.4%
29146760 1
1.4%
26308470 1
1.4%
25812380 1
1.4%
23718540 1
1.4%
22057650 1
1.4%
14278130 1
1.4%
14017050 1
1.4%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)53.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158.89041
Minimum1
Maximum2219
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T21:44:58.751634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median9
Q360
95-th percentile902.2
Maximum2219
Range2218
Interquartile range (IQR)56

Descriptive statistics

Standard deviation405.58115
Coefficient of variation (CV)2.5525842
Kurtosis14.203617
Mean158.89041
Median Absolute Deviation (MAD)7
Skewness3.6471009
Sum11599
Variance164496.07
MonotonicityNot monotonic
2023-12-12T21:44:58.895761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
3 6
 
8.2%
1 6
 
8.2%
4 5
 
6.8%
6 5
 
6.8%
2 5
 
6.8%
5 4
 
5.5%
7 4
 
5.5%
34 2
 
2.7%
18 2
 
2.7%
9 2
 
2.7%
Other values (29) 32
43.8%
ValueCountFrequency (%)
1 6
8.2%
2 5
6.8%
3 6
8.2%
4 5
6.8%
5 4
5.5%
6 5
6.8%
7 4
5.5%
8 1
 
1.4%
9 2
 
2.7%
10 1
 
1.4%
ValueCountFrequency (%)
2219 1
1.4%
1965 1
1.4%
1212 1
1.4%
1132 1
1.4%
749 1
1.4%
731 1
1.4%
481 1
1.4%
478 1
1.4%
449 1
1.4%
410 1
1.4%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13391488
Minimum86300
Maximum78287110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2023-12-12T21:44:59.346152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum86300
5-th percentile231462
Q11473040
median5518700
Q316055780
95-th percentile56099564
Maximum78287110
Range78200810
Interquartile range (IQR)14582740

Descriptive statistics

Standard deviation18768697
Coefficient of variation (CV)1.4015393
Kurtosis3.5603864
Mean13391488
Median Absolute Deviation (MAD)4812010
Skewness2.0081958
Sum9.7757865 × 108
Variance3.5226399 × 1014
MonotonicityNot monotonic
2023-12-12T21:44:59.510718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
281410 1
 
1.4%
43018190 1
 
1.4%
68672160 1
 
1.4%
19415990 1
 
1.4%
3729000 1
 
1.4%
5461710 1
 
1.4%
102320 1
 
1.4%
26308470 1
 
1.4%
6530400 1
 
1.4%
1410470 1
 
1.4%
Other values (63) 63
86.3%
ValueCountFrequency (%)
86300 1
1.4%
102320 1
1.4%
108600 1
1.4%
156540 1
1.4%
281410 1
1.4%
302710 1
1.4%
310770 1
1.4%
350350 1
1.4%
444850 1
1.4%
560900 1
1.4%
ValueCountFrequency (%)
78287110 1
1.4%
76190540 1
1.4%
68672160 1
1.4%
63637490 1
1.4%
51074280 1
1.4%
45277790 1
1.4%
43018190 1
1.4%
39525400 1
1.4%
39025710 1
1.4%
36975050 1
1.4%

Interactions

2023-12-12T21:44:55.769829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:54.378370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:54.915886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:55.360662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:55.872578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:54.513069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:55.034328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:55.477309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:55.981531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:54.611240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:55.142035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:55.577353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:56.066428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:54.724687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:55.234346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:44:55.655141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:44:59.635222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.4150.2660.000
세목명0.0001.0000.1430.4690.0000.4410.000
체납액구간0.0000.1431.0000.0000.7590.0000.550
체납건수0.0000.4690.0001.0000.7180.9910.558
체납금액0.4150.0000.7590.7181.0000.7430.787
누적체납건수0.2660.4410.0000.9910.7431.0000.647
누적체납금액0.0000.0000.5500.5580.7870.6471.000
2023-12-12T21:44:59.753315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간과세년도세목명
체납액구간1.0000.0000.068
과세년도0.0001.0000.000
세목명0.0680.0001.000
2023-12-12T21:44:59.846663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.2550.9300.2110.0000.2980.000
체납금액0.2551.0000.2300.9590.1780.0000.346
누적체납건수0.9300.2301.0000.2770.1780.2770.000
누적체납금액0.2110.9590.2771.0000.0000.0000.305
과세년도0.0000.1780.1780.0001.0000.0000.000
세목명0.2980.0000.2770.0000.0001.0000.068
체납액구간0.0000.3460.0000.3050.0000.0681.000

Missing values

2023-12-12T21:44:56.214738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:44:56.355848image/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
0강원도화천군427902017등록면허세10만원 미만1418089025281410
1강원도화천군427902017자동차세10만원 미만291132580602352650
2강원도화천군427902017자동차세10만원~30만원미만193029050366083380
3강원도화천군427902017재산세10만원 미만14823711404787472040
4강원도화천군427902017재산세10만원~30만원미만237606071151850
5강원도화천군427902017재산세1천만원~3천만원미만112520570339025710
6강원도화천군427902017재산세50만원~1백만원미만2142219074734980
7강원도화천군427902017주민세10만원 미만22431642204495955560
8강원도화천군427902017지방소득세10만원 미만511587010302710
9강원도화천군427902017지방소득세10만원~30만원미만11713503444850
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
63강원도화천군427902020지방소득세10만원~30만원미만112014540193621960
64강원도화천군427902020지방소득세1백만원~3백만원미만572188001624159740
65강원도화천군427902020지방소득세1천만원~3천만원미만241312060578287110
66강원도화천군427902020지방소득세30만원~50만원미만270271062113180
67강원도화천군427902020지방소득세50만원~1백만원미만961404801812670880
68강원도화천군427902020취득세10만원 미만3542206156540
69강원도화천군427902020취득세10만원~30만원미만23503502350350
70강원도화천군427902020취득세1백만원~3백만원미만2372544023725440
71강원도화천군427902020취득세30만원~50만원미만4137990041379900
72강원도화천군427902020취득세50만원~1백만원미만2121491031908080