Overview

Dataset statistics

Number of variables10
Number of observations63
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory87.1 B

Variable types

Categorical6
Boolean1
Numeric3

Dataset

Description신용카드,가상계좌 등 지방세 납부매체별 납부 현황에 관련한 데이터로, 전자송달 시장 규모 및 편익 분석 및 수수료 산정시 기초자료로 활용합니다.
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/15080077/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
납부년도 has constant value ""Constant
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
세목명 is highly overall correlated with 납부매체전자고지여부High correlation
납부매체전자고지여부 is highly overall correlated with 세목명High correlation
납부금액 has unique valuesUnique
납부매체비율 has 3 (4.8%) zerosZeros

Reproduction

Analysis started2024-05-04 08:12:57.020649
Analysis finished2024-05-04 08:13:01.981415
Duration4.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
제주특별자치도
63 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주특별자치도 63
100.0%

Length

2024-05-04T08:13:02.195899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:13:02.442522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주특별자치도 63
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
서귀포시
63 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서귀포시 63
100.0%

Length

2024-05-04T08:13:02.860497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:13:03.175639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서귀포시 63
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
50130
63 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50130
2nd row50130
3rd row50130
4th row50130
5th row50130

Common Values

ValueCountFrequency (%)
50130 63
100.0%

Length

2024-05-04T08:13:03.594413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:13:03.920955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50130 63
100.0%

납부년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023
63 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 63
100.0%

Length

2024-05-04T08:13:04.579558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:13:05.055368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 63
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
주민세
8 
재산세
8 
자동차세
8 
등록면허세
8 
취득세
7 
Other values (5)
24 

Length

Max length7
Median length3
Mean length3.8888889
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row취득세
2nd row등록세
3rd row면허세
4th row주민세
5th row재산세

Common Values

ValueCountFrequency (%)
주민세 8
12.7%
재산세 8
12.7%
자동차세 8
12.7%
등록면허세 8
12.7%
취득세 7
11.1%
등록세 7
11.1%
지방소득세 7
11.1%
면허세 4
6.3%
종합토지세 3
 
4.8%
지역자원시설세 3
 
4.8%

Length

2024-05-04T08:13:05.520940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:13:05.997917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주민세 8
12.7%
재산세 8
12.7%
자동차세 8
12.7%
등록면허세 8
12.7%
취득세 7
11.1%
등록세 7
11.1%
지방소득세 7
11.1%
면허세 4
6.3%
종합토지세 3
 
4.8%
지역자원시설세 3
 
4.8%

납부매체
Categorical

Distinct8
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Memory size636.0 B
가상계좌
10 
기타
10 
지자체방문
9 
ARS
8 
위택스
8 
Other values (3)
18 

Length

Max length7
Median length5
Mean length3.9047619
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가상계좌 10
15.9%
기타 10
15.9%
지자체방문 9
14.3%
ARS 8
12.7%
위택스 8
12.7%
은행창구 7
11.1%
CD/ATM기 7
11.1%
자동이체 4
 
6.3%

Length

2024-05-04T08:13:06.562747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:13:06.989163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가상계좌 10
15.9%
기타 10
15.9%
지자체방문 9
14.3%
ars 8
12.7%
위택스 8
12.7%
은행창구 7
11.1%
cd/atm기 7
11.1%
자동이체 4
 
6.3%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size195.0 B
True
38 
False
25 
ValueCountFrequency (%)
True 38
60.3%
False 25
39.7%
2024-05-04T08:13:07.495845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10830.54
Minimum1
Maximum95463
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-05-04T08:13:07.925594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q1280.5
median5142
Q313752
95-th percentile37227.4
Maximum95463
Range95462
Interquartile range (IQR)13471.5

Descriptive statistics

Standard deviation16678.857
Coefficient of variation (CV)1.5399839
Kurtosis11.478138
Mean10830.54
Median Absolute Deviation (MAD)5118
Skewness3.0046914
Sum682324
Variance2.7818426 × 108
MonotonicityNot monotonic
2024-05-04T08:13:08.369710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 3
 
4.8%
4128 1
 
1.6%
75 1
 
1.6%
11253 1
 
1.6%
22620 1
 
1.6%
6148 1
 
1.6%
8002 1
 
1.6%
302 1
 
1.6%
7 1
 
1.6%
4239 1
 
1.6%
Other values (51) 51
81.0%
ValueCountFrequency (%)
1 1
 
1.6%
3 1
 
1.6%
4 3
4.8%
6 1
 
1.6%
7 1
 
1.6%
9 1
 
1.6%
10 1
 
1.6%
24 1
 
1.6%
32 1
 
1.6%
58 1
 
1.6%
ValueCountFrequency (%)
95463 1
1.6%
66907 1
1.6%
42457 1
1.6%
37605 1
1.6%
33829 1
1.6%
32169 1
1.6%
29581 1
1.6%
24258 1
1.6%
22620 1
1.6%
21194 1
1.6%

납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9665124 × 109
Minimum23620
Maximum6.545922 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-05-04T08:13:08.830404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23620
5-th percentile120422
Q143660415
median9.7489714 × 108
Q36.4500262 × 109
95-th percentile2.1776965 × 1010
Maximum6.545922 × 1010
Range6.5459197 × 1010
Interquartile range (IQR)6.4063658 × 109

Descriptive statistics

Standard deviation9.9299257 × 109
Coefficient of variation (CV)1.999376
Kurtosis22.103733
Mean4.9665124 × 109
Median Absolute Deviation (MAD)9.7306724 × 108
Skewness4.1079359
Sum3.1289028 × 1011
Variance9.8603425 × 1019
MonotonicityNot monotonic
2024-05-04T08:13:09.271810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4414874330 1
 
1.6%
211970 1
 
1.6%
1228760200 1
 
1.6%
4949714300 1
 
1.6%
30371500 1
 
1.6%
25515469250 1
 
1.6%
53287110 1
 
1.6%
51250 1
 
1.6%
64613790 1
 
1.6%
4815731970 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
23620 1
1.6%
51250 1
1.6%
69060 1
1.6%
110250 1
1.6%
211970 1
1.6%
223260 1
1.6%
239910 1
1.6%
354790 1
1.6%
1829900 1
1.6%
3374740 1
1.6%
ValueCountFrequency (%)
65459220200 1
1.6%
25515469250 1
1.6%
22518851730 1
1.6%
22197179590 1
1.6%
17995038220 1
1.6%
13147035610 1
1.6%
12697310270 1
1.6%
12682928350 1
1.6%
12631229760 1
1.6%
11697316700 1
1.6%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct56
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.697937
Minimum0
Maximum60.59
Zeros3
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-05-04T08:13:09.717390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01
Q10.5235
median7.81
Q320.145
95-th percentile39.379
Maximum60.59
Range60.59
Interquartile range (IQR)19.6215

Descriptive statistics

Standard deviation14.105238
Coefficient of variation (CV)1.1108292
Kurtosis1.6875417
Mean12.697937
Median Absolute Deviation (MAD)7.77
Skewness1.354479
Sum799.97
Variance198.95775
MonotonicityNot monotonic
2024-05-04T08:13:10.272145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 6
 
9.5%
0.0 3
 
4.8%
20.68 1
 
1.6%
0.23 1
 
1.6%
26.92 1
 
1.6%
54.12 1
 
1.6%
14.71 1
 
1.6%
15.33 1
 
1.6%
0.58 1
 
1.6%
8.12 1
 
1.6%
Other values (46) 46
73.0%
ValueCountFrequency (%)
0.0 3
4.8%
0.01 6
9.5%
0.02 1
 
1.6%
0.03 1
 
1.6%
0.04 1
 
1.6%
0.07 1
 
1.6%
0.22 1
 
1.6%
0.23 1
 
1.6%
0.467 1
 
1.6%
0.58 1
 
1.6%
ValueCountFrequency (%)
60.59 1
1.6%
54.12 1
1.6%
40.67 1
1.6%
39.77 1
1.6%
35.86 1
1.6%
31.48 1
1.6%
31.27 1
1.6%
30.91 1
1.6%
29.735 1
1.6%
27.88 1
1.6%

Interactions

2024-05-04T08:13:00.213974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:12:57.815145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:12:59.066746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:13:00.496192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:12:58.377708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:12:59.386818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:13:00.796070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:12:58.678762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:12:59.902612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T08:13:10.563881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
세목명1.0000.0000.9930.2640.4840.522
납부매체0.0001.0000.0000.0000.0000.156
납부매체전자고지여부0.9930.0001.0000.3210.1670.429
납부건수0.2640.0000.3211.0000.5930.779
납부금액0.4840.0000.1670.5931.0000.385
납부매체비율0.5220.1560.4290.7790.3851.000
2024-05-04T08:13:10.869552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납부매체전자고지여부납부매체
세목명1.0000.8620.000
납부매체전자고지여부0.8621.0000.000
납부매체0.0000.0001.000
2024-05-04T08:13:11.198276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율세목명납부매체납부매체전자고지여부
납부건수1.0000.7740.9000.1230.0000.327
납부금액0.7741.0000.7020.2140.0000.206
납부매체비율0.9000.7021.0000.2620.0590.402
세목명0.1230.2140.2621.0000.0000.862
납부매체0.0000.0000.0590.0001.0000.000
납부매체전자고지여부0.3270.2060.4020.8620.0001.000

Missing values

2024-05-04T08:13:01.282010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T08:13:01.792732image/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
0제주특별자치도서귀포시501302023취득세ARSN4128441487433020.68
1제주특별자치도서귀포시501302023등록세ARSN42119700.02
2제주특별자치도서귀포시501302023면허세ARSY1236200.01
3제주특별자치도서귀포시501302023주민세ARSY1375184617106.89
4제주특별자치도서귀포시501302023재산세ARSY6285143797480031.48
5제주특별자치도서귀포시501302023자동차세ARSY6172103415945030.91
6제주특별자치도서귀포시501302023등록면허세ARSY1742587521008.72
7제주특별자치도서귀포시501302023지방소득세ARSN2591150850601.3
8제주특별자치도서귀포시501302023취득세가상계좌N1898131470356100.79
9제주특별자치도서귀포시501302023등록세가상계좌N433747400.0
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
53제주특별자치도서귀포시501302023취득세기타N97487237915501.18
54제주특별자치도서귀포시501302023지역자원시설세기타Y581172786200.07
55제주특별자치도서귀포시501302023지방소득세기타N164931263122976019.99
56제주특별자치도서귀포시501302023주민세기타Y985597489714011.95
57제주특별자치도서귀포시501302023종합토지세기타N42232600.0
58제주특별자치도서귀포시501302023재산세기타Y295811017906912035.86
59제주특별자치도서귀포시501302023자동차세기타Y15751204367469019.09
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