Overview

Dataset statistics

Number of variables11
Number of observations230
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.0 KiB
Average record size in memory93.6 B

Variable types

Categorical7
Boolean1
Numeric3

Dataset

Description(납부년도 2017~2019) 지방세 세목별 납부매체, 납부매체전자고지여부, 납부건수, 납부금액, 납부매체비율에 대한 자료
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=346&beforeMenuCd=DOM_000000201001001000&publicdatapk=15080738

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
납부매체전자고지여부 is highly overall correlated with 납부매체High correlation
납부매체 is highly overall correlated with 납부매체전자고지여부High correlation
납부건수 is highly overall correlated with 납부금액 and 1 other fieldsHigh correlation
납부금액 is highly overall correlated with 납부건수 and 1 other fieldsHigh correlation
납부매체비율 is highly overall correlated with 납부건수 and 1 other fieldsHigh correlation
납부금액 has unique valuesUnique
납부매체비율 has 5 (2.2%) zerosZeros

Reproduction

Analysis started2024-01-09 22:19:06.661586
Analysis finished2024-01-09 22:19:07.743005
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
충청남도
230 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 230
100.0%

Length

2024-01-10T07:19:07.790554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:19:07.855150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 230
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
공주시
230 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공주시 230
100.0%

Length

2024-01-10T07:19:07.925835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:19:07.990975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공주시 230
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
44150
230 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44150
2nd row44150
3rd row44150
4th row44150
5th row44150

Common Values

ValueCountFrequency (%)
44150 230
100.0%

Length

2024-01-10T07:19:08.058439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:19:08.126466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44150 230
100.0%

납부년도
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2019
80 
2017
76 
2018
74 

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 80
34.8%
2017 76
33.0%
2018 74
32.2%

Length

2024-01-10T07:19:08.196606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:19:08.268452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 80
34.8%
2017 76
33.0%
2018 74
32.2%

세목명
Categorical

Distinct12
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
등록면허세
31 
자동차세
31 
재산세
31 
주민세
31 
지방소득세
27 
Other values (7)
79 

Length

Max length7
Median length6
Mean length4
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
등록면허세 31
13.5%
자동차세 31
13.5%
재산세 31
13.5%
주민세 31
13.5%
지방소득세 27
11.7%
취득세 25
10.9%
등록세 20
8.7%
지역자원시설세 16
7.0%
면허세 8
 
3.5%
종합토지세 5
 
2.2%
Other values (2) 5
 
2.2%

Length

2024-01-10T07:19:08.360904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록면허세 31
13.5%
자동차세 31
13.5%
재산세 31
13.5%
주민세 31
13.5%
지방소득세 27
11.7%
취득세 25
10.9%
등록세 20
8.7%
지역자원시설세 16
7.0%
면허세 8
 
3.5%
종합토지세 5
 
2.2%
Other values (2) 5
 
2.2%

납부매체
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
ARS
33 
은행창구
30 
가상계좌
27 
기타
26 
자동화기기
25 
Other values (5)
89 

Length

Max length5
Median length4
Mean length3.873913
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
ARS 33
14.3%
은행창구 30
13.0%
가상계좌 27
11.7%
기타 26
11.3%
자동화기기 25
10.9%
인터넷지로 24
10.4%
지자체방문 24
10.4%
위택스 23
10.0%
자동이체 12
 
5.2%
페이사납부 6
 
2.6%

Length

2024-01-10T07:19:08.461132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:19:08.556352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ars 33
14.3%
은행창구 30
13.0%
가상계좌 27
11.7%
기타 26
11.3%
자동화기기 25
10.9%
인터넷지로 24
10.4%
지자체방문 24
10.4%
위택스 23
10.0%
자동이체 12
 
5.2%
페이사납부 6
 
2.6%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size362.0 B
False
124 
True
106 
ValueCountFrequency (%)
False 124
53.9%
True 106
46.1%
2024-01-10T07:19:08.646147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct186
Distinct (%)80.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4478.2826
Minimum1
Maximum46109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-10T07:19:08.729290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q120.5
median636
Q34422.5
95-th percentile22056.4
Maximum46109
Range46108
Interquartile range (IQR)4402

Descriptive statistics

Standard deviation8487.357
Coefficient of variation (CV)1.8952258
Kurtosis7.7387087
Mean4478.2826
Median Absolute Deviation (MAD)632
Skewness2.721692
Sum1030005
Variance72035228
MonotonicityNot monotonic
2024-01-10T07:19:08.835473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 14
 
6.1%
4 8
 
3.5%
2 6
 
2.6%
9 4
 
1.7%
3 4
 
1.7%
8 3
 
1.3%
11 3
 
1.3%
19 3
 
1.3%
90 2
 
0.9%
6 2
 
0.9%
Other values (176) 181
78.7%
ValueCountFrequency (%)
1 14
6.1%
2 6
2.6%
3 4
 
1.7%
4 8
3.5%
5 1
 
0.4%
6 2
 
0.9%
7 1
 
0.4%
8 3
 
1.3%
9 4
 
1.7%
10 2
 
0.9%
ValueCountFrequency (%)
46109 1
0.4%
44039 1
0.4%
39756 1
0.4%
37221 1
0.4%
34761 1
0.4%
34580 1
0.4%
32514 1
0.4%
31762 1
0.4%
31304 1
0.4%
25204 1
0.4%

납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct230
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7050043 × 109
Minimum70
Maximum1.5680864 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-10T07:19:08.943855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum70
5-th percentile39801
Q16331655
median1.2367123 × 108
Q31.2775812 × 109
95-th percentile1.1320415 × 1010
Maximum1.5680864 × 1010
Range1.5680864 × 1010
Interquartile range (IQR)1.2712496 × 109

Descriptive statistics

Standard deviation3.4599603 × 109
Coefficient of variation (CV)2.0292971
Kurtosis5.513418
Mean1.7050043 × 109
Median Absolute Deviation (MAD)1.2360346 × 108
Skewness2.5113886
Sum3.9215099 × 1011
Variance1.1971325 × 1019
MonotonicityNot monotonic
2024-01-10T07:19:09.072615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
622620 1
 
0.4%
185095790 1
 
0.4%
7185960 1
 
0.4%
90325220 1
 
0.4%
731226720 1
 
0.4%
1482960 1
 
0.4%
39720 1
 
0.4%
320972370 1
 
0.4%
504530 1
 
0.4%
197345750 1
 
0.4%
Other values (220) 220
95.7%
ValueCountFrequency (%)
70 1
0.4%
250 1
0.4%
1000 1
0.4%
2710 1
0.4%
3700 1
0.4%
7340 1
0.4%
7500 1
0.4%
9520 1
0.4%
10300 1
0.4%
18900 1
0.4%
ValueCountFrequency (%)
15680864230 1
0.4%
15599450900 1
0.4%
14048101610 1
0.4%
13634731450 1
0.4%
13487825130 1
0.4%
13322427200 1
0.4%
13142528390 1
0.4%
13006558090 1
0.4%
12676981690 1
0.4%
11930201370 1
0.4%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct180
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.17413
Minimum0
Maximum89.63
Zeros5
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-10T07:19:09.193141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01
Q10.28
median5.285
Q317.715
95-th percentile43.403
Maximum89.63
Range89.63
Interquartile range (IQR)17.435

Descriptive statistics

Standard deviation16.332088
Coefficient of variation (CV)1.3415404
Kurtosis5.449033
Mean12.17413
Median Absolute Deviation (MAD)5.265
Skewness2.0962704
Sum2800.05
Variance266.73711
MonotonicityNot monotonic
2024-01-10T07:19:09.332333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 12
 
5.2%
0.02 11
 
4.8%
0.09 5
 
2.2%
0.0 5
 
2.2%
0.04 5
 
2.2%
0.11 4
 
1.7%
0.59 3
 
1.3%
0.41 3
 
1.3%
0.03 2
 
0.9%
3.78 2
 
0.9%
Other values (170) 178
77.4%
ValueCountFrequency (%)
0.0 5
2.2%
0.01 12
5.2%
0.02 11
4.8%
0.03 2
 
0.9%
0.04 5
2.2%
0.05 1
 
0.4%
0.06 1
 
0.4%
0.07 2
 
0.9%
0.08 1
 
0.4%
0.09 5
2.2%
ValueCountFrequency (%)
89.63 1
0.4%
87.83 1
0.4%
86.44 1
0.4%
59.07 1
0.4%
58.6 1
0.4%
57.77 1
0.4%
53.76 1
0.4%
51.56 1
0.4%
50.74 1
0.4%
50.37 1
0.4%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2019-12-31
230 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-12-31
2nd row2019-12-31
3rd row2019-12-31
4th row2019-12-31
5th row2019-12-31

Common Values

ValueCountFrequency (%)
2019-12-31 230
100.0%

Length

2024-01-10T07:19:09.453523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:19:09.540344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-12-31 230
100.0%

Interactions

2024-01-10T07:19:07.369927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:19:06.959089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:19:07.156500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:19:07.426760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:19:07.021504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:19:07.219688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:19:07.498420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:19:07.097341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:19:07.305146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:19:09.600876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
납부년도1.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.0000.0000.1990.4210.612
납부매체0.0000.0001.0000.9930.5970.5280.512
납부매체전자고지여부0.0000.0000.9931.0000.1020.0000.207
납부건수0.0000.1990.5970.1021.0000.8760.706
납부금액0.0000.4210.5280.0000.8761.0000.610
납부매체비율0.0000.6120.5120.2070.7060.6101.000
2024-01-10T07:19:09.710610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부매체전자고지여부납부매체세목명납부년도
납부매체전자고지여부1.0000.9070.0000.000
납부매체0.9071.0000.0000.000
세목명0.0000.0001.0000.000
납부년도0.0000.0000.0001.000
2024-01-10T07:19:09.808231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율납부년도세목명납부매체납부매체전자고지여부
납부건수1.0000.8550.8480.0000.0830.2200.075
납부금액0.8551.0000.6820.0000.1890.1860.000
납부매체비율0.8480.6821.0000.0000.3090.2720.153
납부년도0.0000.0000.0001.0000.0000.0000.000
세목명0.0830.1890.3090.0001.0000.0000.000
납부매체0.2200.1860.2720.0000.0001.0000.907
납부매체전자고지여부0.0750.0000.1530.0000.0000.9071.000

Missing values

2024-01-10T07:19:07.582211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:19:07.697020image/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

시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율데이터기준일
0충청남도공주시441502017등록면허세ARSN426226201.92019-12-31
1충청남도공주시441502017등록면허세ARSY2309000.092019-12-31
2충청남도공주시441502017자동차세ARSN113923364934051.562019-12-31
3충청남도공주시441502017자동차세ARSY99618000.412019-12-31
4충청남도공주시441502017재산세ARSN6959709753031.462019-12-31
5충청남도공주시441502017재산세ARSY94486500.412019-12-31
6충청남도공주시441502017주민세ARSN270410179012.222019-12-31
7충청남도공주시441502017주민세ARSY131841600.592019-12-31
8충청남도공주시441502017지방소득세ARSN2075859000.912019-12-31
9충청남도공주시441502017지방소득세ARSY1879500.052019-12-31
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율데이터기준일
220충청남도공주시441502019재산세지자체방문N59017904609026.92019-12-31
221충청남도공주시441502019주민세지자체방문N2771087463012.632019-12-31
222충청남도공주시441502019지방소득세지자체방문N104285821004.742019-12-31
223충청남도공주시441502019취득세지자체방문N1617017126407.342019-12-31
224충청남도공주시441502019등록면허세페이사납부Y4780000.592019-12-31
225충청남도공주시441502019자동차세페이사납부Y1361868690020.092019-12-31
226충청남도공주시441502019재산세페이사납부Y3412704887050.372019-12-31
227충청남도공주시441502019주민세페이사납부Y191283074028.212019-12-31
228충청남도공주시441502019지방소득세페이사납부Y173400.152019-12-31
229충청남도공주시441502019취득세페이사납부Y464934300.592019-12-31