Overview

Dataset statistics

Number of variables10
Number of observations69
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory86.9 B

Variable types

Categorical6
Boolean1
Numeric3

Dataset

Description전자송달 시장 규모 및 편익 분석, 수수료 산정시 기초자료 활용하기 위하여 신용카드,가상계좌 등 지방세 납부매체*별 납부 현황을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=352&beforeMenuCd=DOM_000000201001001000&publicdatapk=15078652

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
납부년도 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 1 (1.4%) zerosZeros

Reproduction

Analysis started2024-01-09 21:48:10.606541
Analysis finished2024-01-09 21:48:11.789495
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
충청남도
69 

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 69
100.0%

Length

2024-01-10T06:48:11.838986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:48:11.909928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 69
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
예산군
69 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
예산군 69
100.0%

Length

2024-01-10T06:48:11.984329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:48:12.065991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
예산군 69
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
44810
69 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44810
2nd row44810
3rd row44810
4th row44810
5th row44810

Common Values

ValueCountFrequency (%)
44810 69
100.0%

Length

2024-01-10T06:48:12.144427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:48:12.221310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44810 69
100.0%

납부년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
2021
69 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 69
100.0%

Length

2024-01-10T06:48:12.318090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:48:12.404232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 69
100.0%

세목명
Categorical

Distinct12
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
등록면허세
9 
자동차세
9 
재산세
9 
주민세
8 
지방소득세
8 
Other values (7)
26 

Length

Max length7
Median length5
Mean length4.0869565
Min length3

Unique

Unique2 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
등록면허세 9
13.0%
자동차세 9
13.0%
재산세 9
13.0%
주민세 8
11.6%
지방소득세 8
11.6%
취득세 8
11.6%
등록세 6
8.7%
지역자원시설세 5
7.2%
담배소비세 3
 
4.3%
종합토지세 2
 
2.9%
Other values (2) 2
 
2.9%

Length

2024-01-10T06:48:12.487098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록면허세 9
13.0%
자동차세 9
13.0%
재산세 9
13.0%
주민세 8
11.6%
지방소득세 8
11.6%
취득세 8
11.6%
등록세 6
8.7%
지역자원시설세 5
7.2%
담배소비세 3
 
4.3%
종합토지세 2
 
2.9%
Other values (2) 2
 
2.9%

납부매체
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size684.0 B
가상계좌
10 
은행창구
10 
위택스
9 
기타
8 
인터넷지로
8 
Other values (4)
24 

Length

Max length5
Median length4
Mean length4.057971
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가상계좌 10
14.5%
은행창구 10
14.5%
위택스 9
13.0%
기타 8
11.6%
인터넷지로 8
11.6%
자동화기기 8
11.6%
지자체방문 7
10.1%
페이사납부 6
8.7%
자동이체 3
 
4.3%

Length

2024-01-10T06:48:12.595899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:48:12.691255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가상계좌 10
14.5%
은행창구 10
14.5%
위택스 9
13.0%
기타 8
11.6%
인터넷지로 8
11.6%
자동화기기 8
11.6%
지자체방문 7
10.1%
페이사납부 6
8.7%
자동이체 3
 
4.3%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size201.0 B
True
36 
False
33 
ValueCountFrequency (%)
True 36
52.2%
False 33
47.8%
2024-01-10T06:48:12.783249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct65
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3749.5797
Minimum1
Maximum46678
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2024-01-10T06:48:12.865334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q198
median727
Q33650
95-th percentile14726.4
Maximum46678
Range46677
Interquartile range (IQR)3552

Descriptive statistics

Standard deviation7727.1565
Coefficient of variation (CV)2.060806
Kurtosis16.371271
Mean3749.5797
Median Absolute Deviation (MAD)720
Skewness3.7117087
Sum258721
Variance59708947
MonotonicityNot monotonic
2024-01-10T06:48:12.965939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 2
 
2.9%
5 2
 
2.9%
4 2
 
2.9%
6 2
 
2.9%
16186 1
 
1.4%
8644 1
 
1.4%
99 1
 
1.4%
3286 1
 
1.4%
12537 1
 
1.4%
5918 1
 
1.4%
Other values (55) 55
79.7%
ValueCountFrequency (%)
1 1
1.4%
2 2
2.9%
4 2
2.9%
5 2
2.9%
6 2
2.9%
7 1
1.4%
8 1
1.4%
10 1
1.4%
19 1
1.4%
20 1
1.4%
ValueCountFrequency (%)
46678 1
1.4%
33866 1
1.4%
19323 1
1.4%
16186 1
1.4%
12537 1
1.4%
12491 1
1.4%
11328 1
1.4%
11148 1
1.4%
10465 1
1.4%
9479 1
1.4%

납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct69
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7091114 × 109
Minimum3600
Maximum1.2540206 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2024-01-10T06:48:13.069811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3600
5-th percentile64482
Q19936780
median2.4019995 × 108
Q31.5662579 × 109
95-th percentile9.1952005 × 109
Maximum1.2540206 × 1010
Range1.2540203 × 1010
Interquartile range (IQR)1.5563211 × 109

Descriptive statistics

Standard deviation3.0291969 × 109
Coefficient of variation (CV)1.7723812
Kurtosis3.3349042
Mean1.7091114 × 109
Median Absolute Deviation (MAD)2.3901561 × 108
Skewness2.0641235
Sum1.1792868 × 1011
Variance9.1760336 × 1018
MonotonicityNot monotonic
2024-01-10T06:48:13.184068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44710 1
 
1.4%
1223163950 1
 
1.4%
1337470250 1
 
1.4%
27201720 1
 
1.4%
395814630 1
 
1.4%
1566257910 1
 
1.4%
725765160 1
 
1.4%
23510290 1
 
1.4%
2708260 1
 
1.4%
75859760 1
 
1.4%
Other values (59) 59
85.5%
ValueCountFrequency (%)
3600 1
1.4%
23610 1
1.4%
44300 1
1.4%
44710 1
1.4%
94140 1
1.4%
275000 1
1.4%
496620 1
1.4%
754000 1
1.4%
1184340 1
1.4%
2171730 1
1.4%
ValueCountFrequency (%)
12540206400 1
1.4%
10057140000 1
1.4%
10009429720 1
1.4%
9424191440 1
1.4%
8851714050 1
1.4%
8510046380 1
1.4%
7622586120 1
1.4%
6117324100 1
1.4%
5310866770 1
1.4%
4798584760 1
1.4%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct65
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.043333
Minimum0
Maximum86.44
Zeros1
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size753.0 B
2024-01-10T06:48:13.288787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.014
Q10.38
median5.24
Q316.79
95-th percentile45.2
Maximum86.44
Range86.44
Interquartile range (IQR)16.41

Descriptive statistics

Standard deviation17.87411
Coefficient of variation (CV)1.3703636
Kurtosis3.8800746
Mean13.043333
Median Absolute Deviation (MAD)5.18
Skewness1.9074963
Sum899.99
Variance319.4838
MonotonicityNot monotonic
2024-01-10T06:48:13.389503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.06 3
 
4.3%
0.01 3
 
4.3%
5.14 1
 
1.4%
45.76 1
 
1.4%
24.44 1
 
1.4%
0.28 1
 
1.4%
9.29 1
 
1.4%
64.44 1
 
1.4%
30.42 1
 
1.4%
11.78 1
 
1.4%
Other values (55) 55
79.7%
ValueCountFrequency (%)
0.0 1
 
1.4%
0.01 3
4.3%
0.02 1
 
1.4%
0.03 1
 
1.4%
0.06 3
4.3%
0.11 1
 
1.4%
0.12 1
 
1.4%
0.14 1
 
1.4%
0.15 1
 
1.4%
0.17 1
 
1.4%
ValueCountFrequency (%)
86.44 1
1.4%
64.44 1
1.4%
54.45 1
1.4%
45.76 1
1.4%
44.36 1
1.4%
42.18 1
1.4%
40.16 1
1.4%
38.77 1
1.4%
38.44 1
1.4%
38.43 1
1.4%

Interactions

2024-01-10T06:48:11.203055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:48:10.839032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:48:11.015268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:48:11.260120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:48:10.893950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:48:11.074414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:48:11.323328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:48:10.955731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:48:11.143950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:48:13.469555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
세목명1.0000.0000.0000.0000.5850.206
납부매체0.0001.0001.0000.1060.0000.522
납부매체전자고지여부0.0001.0001.0000.0000.0000.237
납부건수0.0000.1060.0001.0000.6600.685
납부금액0.5850.0000.0000.6601.0000.000
납부매체비율0.2060.5220.2370.6850.0001.000
2024-01-10T06:48:13.575170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부매체전자고지여부납부매체세목명
납부매체전자고지여부1.0000.9460.000
납부매체0.9461.0000.000
세목명0.0000.0001.000
2024-01-10T06:48:13.670592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율세목명납부매체납부매체전자고지여부
납부건수1.0000.7710.8590.0000.0340.000
납부금액0.7711.0000.6260.2880.0000.000
납부매체비율0.8590.6261.0000.0690.1850.221
세목명0.0000.2880.0691.0000.0000.000
납부매체0.0340.0000.1850.0001.0000.946
납부매체전자고지여부0.0000.0000.2210.0000.9461.000

Missing values

2024-01-10T06:48:11.643096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:48:11.747836image/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
0충청남도예산군448102021담배소비세가상계좌Y2447100.0
1충청남도예산군448102021등록면허세가상계좌Y1249138707293011.29
2충청남도예산군448102021등록세가상계좌Y171333940500.15
3충청남도예산군448102021자동차세가상계좌Y33866479858476030.61
4충청남도예산군448102021재산세가상계좌Y46678762258612042.18
5충청남도예산군448102021종합토지세가상계좌Y6443000.01
6충청남도예산군448102021주민세가상계좌Y365012664684203.3
7충청남도예산군448102021지방소득세가상계좌Y1046561173241009.46
8충청남도예산군448102021지역자원시설세가상계좌Y123452062200.11
9충청남도예산군448102021취득세가상계좌Y3202100094297202.89
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
59충청남도예산군448102021재산세지자체방문N88615367740027.74
60충청남도예산군448102021주민세지자체방문N17786313405.54
61충청남도예산군448102021지방소득세지자체방문N104354346203.26
62충청남도예산군448102021취득세지자체방문N33324019995010.43
63충청남도예산군448102021등록면허세페이사납부Y10911843405.24
64충청남도예산군448102021자동차세페이사납부Y80613392492038.77
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