Overview

Dataset statistics

Number of variables10
Number of observations251
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.0 KiB
Average record size in memory85.5 B

Variable types

Categorical6
Boolean1
Numeric3

Dataset

Description3년간(2019~2021) 신용카드, 가상계좌, ARS, 은행창구수납 등 지방세 납부매체별 납부 건수, 납부금액 및 납부매체 비율 등의 항목을 제공합니다
Author전라남도 나주시
URLhttps://www.data.go.kr/data/15079580/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
납부매체 is highly overall correlated with 납부매체전자고지여부High correlation
납부매체전자고지여부 is highly overall correlated with 납부매체High 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 72 (28.7%) zerosZeros

Reproduction

Analysis started2023-12-12 08:46:12.283840
Analysis finished2023-12-12 08:46:13.906092
Duration1.62 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
전라남도
251 

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 251
100.0%

Length

2023-12-12T17:46:13.987941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:46:14.110555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 251
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
나주시
251 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
나주시 251
100.0%

Length

2023-12-12T17:46:14.215459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:46:14.330389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
나주시 251
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
46170
251 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46170
2nd row46170
3rd row46170
4th row46170
5th row46170

Common Values

ValueCountFrequency (%)
46170 251
100.0%

Length

2023-12-12T17:46:14.462501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:46:14.604433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46170 251
100.0%

납부년도
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2020
86 
2021
84 
2019
81 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2020 86
34.3%
2021 84
33.5%
2019 81
32.3%

Length

2023-12-12T17:46:14.743115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:46:14.872447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 86
34.3%
2021 84
33.5%
2019 81
32.3%

세목명
Categorical

Distinct13
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
자동차세
33 
재산세
33 
주민세
33 
등록면허세
32 
지방소득세
29 
Other values (8)
91 

Length

Max length7
Median length5
Mean length4.0239044
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 33
13.1%
재산세 33
13.1%
주민세 33
13.1%
등록면허세 32
12.7%
지방소득세 29
11.6%
취득세 26
10.4%
등록세 19
7.6%
지역자원시설세 16
6.4%
면허세 10
 
4.0%
종합토지세 8
 
3.2%
Other values (3) 12
 
4.8%

Length

2023-12-12T17:46:15.044809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
자동차세 33
13.1%
재산세 33
13.1%
주민세 33
13.1%
등록면허세 32
12.7%
지방소득세 29
11.6%
취득세 26
10.4%
등록세 19
7.6%
지역자원시설세 16
6.4%
면허세 10
 
4.0%
종합토지세 8
 
3.2%
Other values (3) 12
 
4.8%

납부매체
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
ARS
38 
기타
34 
가상계좌
31 
위택스
27 
인터넷지로
26 
Other values (5)
95 

Length

Max length5
Median length4
Mean length3.8047809
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지자체방문
2nd row페이사납부
3rd row페이사납부
4th row페이사납부
5th row페이사납부

Common Values

ValueCountFrequency (%)
ARS 38
15.1%
기타 34
13.5%
가상계좌 31
12.4%
위택스 27
10.8%
인터넷지로 26
10.4%
은행창구 25
10.0%
자동화기기 24
9.6%
지자체방문 18
7.2%
페이사납부 16
6.4%
자동이체 12
 
4.8%

Length

2023-12-12T17:46:15.233292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:46:15.393008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ars 38
15.1%
기타 34
13.5%
가상계좌 31
12.4%
위택스 27
10.8%
인터넷지로 26
10.4%
은행창구 25
10.0%
자동화기기 24
9.6%
지자체방문 18
7.2%
페이사납부 16
6.4%
자동이체 12
 
4.8%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size383.0 B
True
126 
False
125 
ValueCountFrequency (%)
True 126
50.2%
False 125
49.8%
2023-12-12T17:46:15.556240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct193
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5220.761
Minimum1
Maximum70523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T17:46:15.684926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q121
median556
Q34837.5
95-th percentile26644
Maximum70523
Range70522
Interquartile range (IQR)4816.5

Descriptive statistics

Standard deviation10932.609
Coefficient of variation (CV)2.0940643
Kurtosis14.018845
Mean5220.761
Median Absolute Deviation (MAD)555
Skewness3.493981
Sum1310411
Variance1.1952194 × 108
MonotonicityNot monotonic
2023-12-12T17:46:16.176436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 15
 
6.0%
3 7
 
2.8%
5 7
 
2.8%
6 5
 
2.0%
2 5
 
2.0%
28 4
 
1.6%
7 4
 
1.6%
4 4
 
1.6%
9 4
 
1.6%
19 3
 
1.2%
Other values (183) 193
76.9%
ValueCountFrequency (%)
1 15
6.0%
2 5
 
2.0%
3 7
2.8%
4 4
 
1.6%
5 7
2.8%
6 5
 
2.0%
7 4
 
1.6%
8 1
 
0.4%
9 4
 
1.6%
10 2
 
0.8%
ValueCountFrequency (%)
70523 1
0.4%
64657 1
0.4%
59845 1
0.4%
57183 1
0.4%
52614 1
0.4%
48448 1
0.4%
33760 1
0.4%
33696 1
0.4%
31883 1
0.4%
30333 1
0.4%

납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct251
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2854159 × 109
Minimum2960
Maximum3.0310644 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T17:46:16.371700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2960
5-th percentile47540
Q11534940
median92511700
Q31.7629991 × 109
95-th percentile1.2543099 × 1010
Maximum3.0310644 × 1010
Range3.0310641 × 1010
Interquartile range (IQR)1.7614642 × 109

Descriptive statistics

Standard deviation4.7677612 × 109
Coefficient of variation (CV)2.0861678
Kurtosis10.817724
Mean2.2854159 × 109
Median Absolute Deviation (MAD)92477710
Skewness3.0174015
Sum5.736394 × 1011
Variance2.2731547 × 1019
MonotonicityNot monotonic
2023-12-12T17:46:16.566122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20195740 1
 
0.4%
5525410 1
 
0.4%
35379750 1
 
0.4%
1049850 1
 
0.4%
182610550 1
 
0.4%
124236070 1
 
0.4%
10029450 1
 
0.4%
307010 1
 
0.4%
4975760 1
 
0.4%
666046390 1
 
0.4%
Other values (241) 241
96.0%
ValueCountFrequency (%)
2960 1
0.4%
4250 1
0.4%
4370 1
0.4%
5140 1
0.4%
6300 1
0.4%
7720 1
0.4%
15000 1
0.4%
15760 1
0.4%
23340 1
0.4%
24980 1
0.4%
ValueCountFrequency (%)
30310643580 1
0.4%
30054556730 1
0.4%
20981677700 1
0.4%
18109236700 1
0.4%
18013775640 1
0.4%
17725025260 1
0.4%
16970425530 1
0.4%
16303189110 1
0.4%
13539916010 1
0.4%
13490892640 1
0.4%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct91
Distinct (%)36.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.925896
Minimum0
Maximum50
Zeros72
Zeros (%)28.7%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T17:46:16.724116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q318.25
95-th percentile45.75
Maximum50
Range50
Interquartile range (IQR)18.25

Descriptive statistics

Standard deviation14.259526
Coefficient of variation (CV)1.1956775
Kurtosis0.48670972
Mean11.925896
Median Absolute Deviation (MAD)7
Skewness1.2142327
Sum2993.4
Variance203.33409
MonotonicityNot monotonic
2023-12-12T17:46:16.891694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 72
28.7%
1.0 9
 
3.6%
9.0 8
 
3.2%
2.0 8
 
3.2%
8.0 6
 
2.4%
10.0 5
 
2.0%
16.0 5
 
2.0%
49.0 5
 
2.0%
7.0 5
 
2.0%
22.0 4
 
1.6%
Other values (81) 124
49.4%
ValueCountFrequency (%)
0.0 72
28.7%
0.1 4
 
1.6%
0.2 2
 
0.8%
0.3 4
 
1.6%
0.5 2
 
0.8%
0.6 1
 
0.4%
1.0 9
 
3.6%
1.4 1
 
0.4%
1.7 1
 
0.4%
2.0 8
 
3.2%
ValueCountFrequency (%)
50.0 1
 
0.4%
49.4 1
 
0.4%
49.0 5
2.0%
48.8 1
 
0.4%
48.1 1
 
0.4%
48.0 1
 
0.4%
46.0 3
1.2%
45.5 1
 
0.4%
44.0 1
 
0.4%
43.4 1
 
0.4%

Interactions

2023-12-12T17:46:13.255061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:46:12.640144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:46:12.954991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:46:13.377178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:46:12.738082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:46:13.069235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:46:13.492532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:46:12.845168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:46:13.157178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:46:17.017426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
납부년도1.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.0000.0000.1150.4580.633
납부매체0.0000.0001.0000.9930.4260.3730.594
납부매체전자고지여부0.0000.0000.9931.0000.0540.0000.213
납부건수0.0000.1150.4260.0541.0000.6070.629
납부금액0.0000.4580.3730.0000.6071.0000.496
납부매체비율0.0000.6330.5940.2130.6290.4961.000
2023-12-12T17:46:17.139427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부매체세목명납부매체전자고지여부납부년도
납부매체1.0000.0000.9090.000
세목명0.0001.0000.0000.000
납부매체전자고지여부0.9090.0001.0000.000
납부년도0.0000.0000.0001.000
2023-12-12T17:46:17.257536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율납부년도세목명납부매체납부매체전자고지여부
납부건수1.0000.8510.7780.0000.0470.2080.052
납부금액0.8511.0000.6090.0000.2250.1870.000
납부매체비율0.7780.6091.0000.0000.3180.2350.224
납부년도0.0000.0000.0001.0000.0000.0000.000
세목명0.0470.2250.3180.0001.0000.0000.000
납부매체0.2080.1870.2350.0000.0001.0000.909
납부매체전자고지여부0.0520.0000.2240.0000.0000.9091.000

Missing values

2023-12-12T17:46:13.636597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:46:13.828934image/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

시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
0전라남도나주시461702019취득세지자체방문N292019574016.5
1전라남도나주시461702019자동차세페이사납부Y2493945276024.5
2전라남도나주시461702019재산세페이사납부Y4886364003048.1
3전라남도나주시461702019주민세페이사납부Y275355540027.1
4전라남도나주시461702019지방소득세페이사납부Y31253200.3
5전라남도나주시461702019등록면허세ARSN7814063101.7
6전라남도나주시461702019등록면허세ARSY1150000.0
7전라남도나주시461702019면허세ARSN6735000.1
8전라남도나주시461702019자동차세ARSN227447091211049.4
9전라남도나주시461702019자동차세ARSY56259600.1
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
241전라남도나주시461702021등록면허세가상계좌Y187554438795209.0
242전라남도나주시461702021등록세가상계좌Y105140200.0
243전라남도나주시461702021자동차세가상계좌Y57183855336635028.0
244전라남도나주시461702021재산세가상계좌Y705231630318911035.0
245전라남도나주시461702021종합토지세가상계좌Y73013900.0
246전라남도나주시461702021주민세가상계좌Y33760309943316017.0
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