Overview

Dataset statistics

Number of variables11
Number of observations324
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.9 KiB
Average record size in memory94.4 B

Variable types

Numeric4
Categorical6
Boolean1

Dataset

Description세목별 및 연도별로 신용카드, 가상계좌 등 지방세 납부매체별 납부현황과 납부건수, 납부금액, 납부 매체비율등의 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15078644/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
납부매체전자고지여부 is highly overall correlated with 납부매체High correlation
납부매체 is highly overall correlated with 납부매체전자고지여부High correlation
연번 is highly overall correlated with 납부년도High correlation
납부건수 is highly overall correlated with 납부금액 and 1 other fieldsHigh correlation
납부금액 is highly overall correlated with 납부건수High correlation
납부매체비율 is highly overall correlated with 납부건수High correlation
납부년도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
납부매체비율 has 7 (2.2%) zerosZeros

Reproduction

Analysis started2023-12-11 23:10:16.340261
Analysis finished2023-12-11 23:10:18.833683
Duration2.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct324
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162.5
Minimum1
Maximum324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-12T08:10:18.948854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.15
Q181.75
median162.5
Q3243.25
95-th percentile307.85
Maximum324
Range323
Interquartile range (IQR)161.5

Descriptive statistics

Standard deviation93.67497
Coefficient of variation (CV)0.57646135
Kurtosis-1.2
Mean162.5
Median Absolute Deviation (MAD)81
Skewness0
Sum52650
Variance8775
MonotonicityStrictly increasing
2023-12-12T08:10:19.144865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
205 1
 
0.3%
223 1
 
0.3%
222 1
 
0.3%
221 1
 
0.3%
220 1
 
0.3%
219 1
 
0.3%
218 1
 
0.3%
217 1
 
0.3%
216 1
 
0.3%
Other values (314) 314
96.9%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
324 1
0.3%
323 1
0.3%
322 1
0.3%
321 1
0.3%
320 1
0.3%
319 1
0.3%
318 1
0.3%
317 1
0.3%
316 1
0.3%
315 1
0.3%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
전라남도
324 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 324
100.0%

Length

2023-12-12T08:10:19.333795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:10:19.463464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 324
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
장흥군
324 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장흥군 324
100.0%

Length

2023-12-12T08:10:19.571338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:10:19.676736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장흥군 324
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
46800
324 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46800
2nd row46800
3rd row46800
4th row46800
5th row46800

Common Values

ValueCountFrequency (%)
46800 324
100.0%

Length

2023-12-12T08:10:19.794406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:10:19.896587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46800 324
100.0%

납부년도
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2021
74 
2020
69 
2019
62 
2017
60 
2018
59 

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 (%)
2021 74
22.8%
2020 69
21.3%
2019 62
19.1%
2017 60
18.5%
2018 59
18.2%

Length

2023-12-12T08:10:20.025274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:10:20.131853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 74
22.8%
2020 69
21.3%
2019 62
19.1%
2017 60
18.5%
2018 59
18.2%

세목명
Categorical

Distinct12
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
자동차세
49 
재산세
49 
주민세
48 
등록면허세
43 
지방소득세
38 
Other values (7)
97 

Length

Max length7
Median length6
Mean length3.9537037
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 49
15.1%
재산세 49
15.1%
주민세 48
14.8%
등록면허세 43
13.3%
지방소득세 38
11.7%
취득세 38
11.7%
등록세 23
7.1%
지역자원시설세 17
 
5.2%
담배소비세 10
 
3.1%
면허세 4
 
1.2%
Other values (2) 5
 
1.5%

Length

2023-12-12T08:10:20.297554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
자동차세 49
15.1%
재산세 49
15.1%
주민세 48
14.8%
등록면허세 43
13.3%
지방소득세 38
11.7%
취득세 38
11.7%
등록세 23
7.1%
지역자원시설세 17
 
5.2%
담배소비세 10
 
3.1%
면허세 4
 
1.2%
Other values (2) 5
 
1.5%

납부매체
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
가상계좌
44 
은행창구
43 
기타
40 
자동화기기
40 
위택스
37 
Other values (5)
120 

Length

Max length5
Median length4
Mean length3.9351852
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가상계좌 44
13.6%
은행창구 43
13.3%
기타 40
12.3%
자동화기기 40
12.3%
위택스 37
11.4%
인터넷지로 32
9.9%
지자체방문 32
9.9%
ARS 22
6.8%
자동이체 20
6.2%
페이사납부 14
 
4.3%

Length

2023-12-12T08:10:20.431441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:10:20.561673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가상계좌 44
13.6%
은행창구 43
13.3%
기타 40
12.3%
자동화기기 40
12.3%
위택스 37
11.4%
인터넷지로 32
9.9%
지자체방문 32
9.9%
ars 22
6.8%
자동이체 20
6.2%
페이사납부 14
 
4.3%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size456.0 B
False
174 
True
150 
ValueCountFrequency (%)
False 174
53.7%
True 150
46.3%
2023-12-12T08:10:20.693973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct248
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2074.5185
Minimum1
Maximum19317
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-12T08:10:20.804552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q129
median266.5
Q32556.75
95-th percentile10548.15
Maximum19317
Range19316
Interquartile range (IQR)2527.75

Descriptive statistics

Standard deviation3567.1885
Coefficient of variation (CV)1.719526
Kurtosis4.6960222
Mean2074.5185
Median Absolute Deviation (MAD)264.5
Skewness2.2242983
Sum672144
Variance12724834
MonotonicityNot monotonic
2023-12-12T08:10:21.208799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 18
 
5.6%
2 13
 
4.0%
27 4
 
1.2%
25 4
 
1.2%
33 4
 
1.2%
7 4
 
1.2%
15 4
 
1.2%
4 4
 
1.2%
30 3
 
0.9%
19 3
 
0.9%
Other values (238) 263
81.2%
ValueCountFrequency (%)
1 18
5.6%
2 13
4.0%
3 2
 
0.6%
4 4
 
1.2%
5 1
 
0.3%
6 3
 
0.9%
7 4
 
1.2%
8 1
 
0.3%
11 1
 
0.3%
12 2
 
0.6%
ValueCountFrequency (%)
19317 1
0.3%
16425 1
0.3%
14945 1
0.3%
14699 1
0.3%
14601 1
0.3%
14442 1
0.3%
14333 1
0.3%
14157 1
0.3%
12971 1
0.3%
12799 1
0.3%

납부금액
Real number (ℝ)

HIGH CORRELATION 

Distinct322
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9509048 × 108
Minimum1020
Maximum6.8956 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-12T08:10:21.358813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1020
5-th percentile75676
Q13005307.5
median54892100
Q35.1697977 × 108
95-th percentile2.8358123 × 109
Maximum6.8956 × 109
Range6.895599 × 109
Interquartile range (IQR)5.1397446 × 108

Descriptive statistics

Standard deviation1.0240132 × 109
Coefficient of variation (CV)2.0683356
Kurtosis13.479231
Mean4.9509048 × 108
Median Absolute Deviation (MAD)54571675
Skewness3.3804976
Sum1.6040932 × 1011
Variance1.0486031 × 1018
MonotonicityNot monotonic
2023-12-12T08:10:21.546502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11000 2
 
0.6%
6180 2
 
0.6%
247010 1
 
0.3%
755550817 1
 
0.3%
66449030 1
 
0.3%
71885750 1
 
0.3%
304410 1
 
0.3%
9626570 1
 
0.3%
2882789220 1
 
0.3%
588050 1
 
0.3%
Other values (312) 312
96.3%
ValueCountFrequency (%)
1020 1
0.3%
3040 1
0.3%
6000 1
0.3%
6180 2
0.6%
6240 1
0.3%
9430 1
0.3%
11000 2
0.6%
16780 1
0.3%
17930 1
0.3%
18930 1
0.3%
ValueCountFrequency (%)
6895600000 1
0.3%
6874825000 1
0.3%
5465048220 1
0.3%
5392250290 1
0.3%
4130744590 1
0.3%
3959181280 1
0.3%
3929181750 1
0.3%
3711269450 1
0.3%
3570453630 1
0.3%
3521577110 1
0.3%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct276
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.814784
Minimum0
Maximum93.16
Zeros7
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-12T08:10:21.696998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.05
Q11.7725
median9.665
Q320.2875
95-th percentile53.1625
Maximum93.16
Range93.16
Interquartile range (IQR)18.515

Descriptive statistics

Standard deviation17.691624
Coefficient of variation (CV)1.1941871
Kurtosis4.5626173
Mean14.814784
Median Absolute Deviation (MAD)8.505
Skewness1.9538227
Sum4799.99
Variance312.99357
MonotonicityNot monotonic
2023-12-12T08:10:21.868876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 7
 
2.2%
0.06 6
 
1.9%
0.04 6
 
1.9%
0.05 4
 
1.2%
3.7 4
 
1.2%
22.22 4
 
1.2%
2.77 3
 
0.9%
13.15 2
 
0.6%
1.23 2
 
0.6%
0.3 2
 
0.6%
Other values (266) 284
87.7%
ValueCountFrequency (%)
0.0 7
2.2%
0.01 1
 
0.3%
0.03 1
 
0.3%
0.04 6
1.9%
0.05 4
1.2%
0.06 6
1.9%
0.07 1
 
0.3%
0.08 2
 
0.6%
0.09 2
 
0.6%
0.1 2
 
0.6%
ValueCountFrequency (%)
93.16 1
0.3%
92.61 1
0.3%
91.95 1
0.3%
91.0 1
0.3%
87.91 1
0.3%
69.23 1
0.3%
62.96 1
0.3%
61.37 1
0.3%
59.46 1
0.3%
56.63 1
0.3%

Interactions

2023-12-12T08:10:18.040390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:16.733718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:17.151423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:17.548089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:18.148855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:16.824647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:17.241343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:17.649343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:18.265056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:16.947186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:17.340368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:17.774698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:18.379822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:17.058232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:17.430829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:10:17.946968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:10:21.971412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
연번1.0000.9940.0000.6990.0000.0000.0620.000
납부년도0.9941.0000.0000.0000.0000.0000.0000.000
세목명0.0000.0001.0000.0000.0000.3410.7660.574
납부매체0.6990.0000.0001.0001.0000.6480.3480.483
납부매체전자고지여부0.0000.0000.0001.0001.0000.1250.1980.267
납부건수0.0000.0000.3410.6480.1251.0000.5370.636
납부금액0.0620.0000.7660.3480.1980.5371.0000.220
납부매체비율0.0000.0000.5740.4830.2670.6360.2201.000
2023-12-12T08:10:22.087351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부매체전자고지여부납부매체납부년도세목명
납부매체전자고지여부1.0000.9710.0000.000
납부매체0.9711.0000.0000.000
납부년도0.0000.0001.0000.000
세목명0.0000.0000.0001.000
2023-12-12T08:10:22.177085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번납부건수납부금액납부매체비율납부년도세목명납부매체납부매체전자고지여부
연번1.000-0.030-0.009-0.0290.8840.0000.2820.000
납부건수-0.0301.0000.7750.6420.0000.1490.2490.094
납부금액-0.0090.7751.0000.4270.0000.4500.1710.147
납부매체비율-0.0290.6420.4271.0000.0000.2850.2430.264
납부년도0.8840.0000.0000.0001.0000.0000.0000.000
세목명0.0000.1490.4500.2850.0001.0000.0000.000
납부매체0.2820.2490.1710.2430.0000.0001.0000.971
납부매체전자고지여부0.0000.0940.1470.2640.0000.0000.9711.000

Missing values

2023-12-12T08:10:18.545024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:10:18.745364image/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

연번시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
01전라남도장흥군468002017자동차세ARSN124701020.0
12전라남도장흥군468002017재산세ARSN212878040.0
23전라남도장흥군468002017주민세ARSN22266040.0
34전라남도장흥군468002017등록면허세가상계좌Y28684618043010.32
45전라남도장흥군468002017자동차세가상계좌Y8109130855658029.17
56전라남도장흥군468002017재산세가상계좌Y1149171480129041.34
67전라남도장흥군468002017주민세가상계좌Y424915936265015.28
78전라남도장흥군468002017지방소득세가상계좌Y8075161812502.9
89전라남도장흥군468002017지역자원시설세가상계좌Y85628700.03
910전라남도장흥군468002017취득세가상계좌Y2673920439200.96
연번시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
314315전라남도장흥군468002021재산세지자체방문N1305477845020.25
315316전라남도장흥군468002021주민세지자체방문N3820332405.92
316317전라남도장흥군468002021지방소득세지자체방문N27110330904.21
317318전라남도장흥군468002021취득세지자체방문N251007741003.89
318319전라남도장흥군468002021등록면허세페이사납부Y273796504.11
319320전라남도장흥군468002021자동차세페이사납부Y1643476519024.96
320321전라남도장흥군468002021재산세페이사납부Y3611637010054.95
321322전라남도장흥군468002021주민세페이사납부Y102127451015.53
322323전라남도장흥군468002021지방소득세페이사납부Y111401000.15
323324전라남도장흥군468002021취득세페이사납부Y217579500.3