Overview

Dataset statistics

Number of variables11
Number of observations136
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.5 KiB
Average record size in memory94.0 B

Variable types

Categorical7
Boolean1
Numeric3

Dataset

Description상기 데이터는 연도별 신용카드, 가상계좌 등 지방세 납부매체별 납부 현황을 제공하여 전자송달 시장 규모 및 편익 분석, 수수료 산정시 기초자료로 활용
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=348&beforeMenuCd=DOM_000000201001001000&publicdatapk=15079997

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일자 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 4 (2.9%) zerosZeros

Reproduction

Analysis started2024-01-09 21:38:30.611059
Analysis finished2024-01-09 21:38:31.869114
Duration1.26 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
충청남도
136 

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 136
100.0%

Length

2024-01-10T06:38:31.933558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:38:32.028647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 136
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
부여군
136 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부여군 136
100.0%

Length

2024-01-10T06:38:32.125688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:38:32.218953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부여군 136
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
44760
136 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44760
2nd row44760
3rd row44760
4th row44760
5th row44760

Common Values

ValueCountFrequency (%)
44760 136
100.0%

Length

2024-01-10T06:38:32.318381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:38:32.401851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44760 136
100.0%

납부년도
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2021
70 
2020
66 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2021 70
51.5%
2020 66
48.5%

Length

2024-01-10T06:38:32.476990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:38:32.550532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 70
51.5%
2020 66
48.5%

세목명
Categorical

Distinct13
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
등록면허세
18 
자동차세
18 
재산세
18 
주민세
18 
지방소득세
16 
Other values (8)
48 

Length

Max length7
Median length5
Mean length3.9485294
Min length3

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
등록면허세 18
13.2%
자동차세 18
13.2%
재산세 18
13.2%
주민세 18
13.2%
지방소득세 16
11.8%
취득세 16
11.8%
등록세 12
8.8%
담배소비세 7
 
5.1%
종합토지세 4
 
2.9%
지역자원시설세 4
 
2.9%
Other values (3) 5
 
3.7%

Length

2024-01-10T06:38:32.638494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록면허세 18
13.2%
자동차세 18
13.2%
재산세 18
13.2%
주민세 18
13.2%
지방소득세 16
11.8%
취득세 16
11.8%
등록세 12
8.8%
담배소비세 7
 
5.1%
종합토지세 4
 
2.9%
지역자원시설세 4
 
2.9%
Other values (3) 5
 
3.7%

납부매체
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
가상계좌
22 
위택스
18 
은행창구
18 
지자체방문
16 
인터넷지로
15 
Other values (4)
47 

Length

Max length5
Median length4
Mean length4.0955882
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가상계좌 22
16.2%
위택스 18
13.2%
은행창구 18
13.2%
지자체방문 16
11.8%
인터넷지로 15
11.0%
자동화기기 14
10.3%
기타 13
9.6%
페이사납부 12
8.8%
자동이체 8
 
5.9%

Length

2024-01-10T06:38:32.746799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:38:32.842298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가상계좌 22
16.2%
위택스 18
13.2%
은행창구 18
13.2%
지자체방문 16
11.8%
인터넷지로 15
11.0%
자동화기기 14
10.3%
기타 13
9.6%
페이사납부 12
8.8%
자동이체 8
 
5.9%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size268.0 B
True
75 
False
61 
ValueCountFrequency (%)
True 75
55.1%
False 61
44.9%
2024-01-10T06:38:32.936350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct118
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3372.7941
Minimum1
Maximum37711
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-01-10T06:38:33.020714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.75
Q192.25
median525.5
Q33554.5
95-th percentile13653
Maximum37711
Range37710
Interquartile range (IQR)3462.25

Descriptive statistics

Standard deviation6473.4149
Coefficient of variation (CV)1.9193033
Kurtosis11.152413
Mean3372.7941
Median Absolute Deviation (MAD)523.5
Skewness3.1470882
Sum458700
Variance41905100
MonotonicityNot monotonic
2024-01-10T06:38:33.132783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 7
 
5.1%
2 6
 
4.4%
4 5
 
3.7%
464 2
 
1.5%
494 2
 
1.5%
20 2
 
1.5%
8903 1
 
0.7%
3 1
 
0.7%
543 1
 
0.7%
3764 1
 
0.7%
Other values (108) 108
79.4%
ValueCountFrequency (%)
1 7
5.1%
2 6
4.4%
3 1
 
0.7%
4 5
3.7%
6 1
 
0.7%
7 1
 
0.7%
14 1
 
0.7%
17 1
 
0.7%
19 1
 
0.7%
20 2
 
1.5%
ValueCountFrequency (%)
37711 1
0.7%
34773 1
0.7%
25936 1
0.7%
25686 1
0.7%
23327 1
0.7%
22002 1
0.7%
14301 1
0.7%
13437 1
0.7%
13356 1
0.7%
12819 1
0.7%

납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct136
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9323215 × 108
Minimum7500
Maximum8.5894914 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-01-10T06:38:33.243190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7500
5-th percentile63075
Q110034740
median1.3286755 × 108
Q39.0154582 × 108
95-th percentile5.6045232 × 109
Maximum8.5894914 × 109
Range8.5894839 × 109
Interquartile range (IQR)8.9151108 × 108

Descriptive statistics

Standard deviation1.8838011 × 109
Coefficient of variation (CV)1.8966373
Kurtosis6.2581254
Mean9.9323215 × 108
Median Absolute Deviation (MAD)1.3273169 × 108
Skewness2.5577869
Sum1.3507957 × 1011
Variance3.5487067 × 1018
MonotonicityNot monotonic
2024-01-10T06:38:33.352522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2148480130 1
 
0.7%
131060440 1
 
0.7%
453239150 1
 
0.7%
1499374050 1
 
0.7%
344837910 1
 
0.7%
2877066770 1
 
0.7%
520060 1
 
0.7%
6420681330 1
 
0.7%
280499160 1
 
0.7%
40950 1
 
0.7%
Other values (126) 126
92.6%
ValueCountFrequency (%)
7500 1
0.7%
8220 1
0.7%
8400 1
0.7%
30830 1
0.7%
35050 1
0.7%
38690 1
0.7%
40950 1
0.7%
70450 1
0.7%
90870 1
0.7%
180850 1
0.7%
ValueCountFrequency (%)
8589491440 1
0.7%
8332455910 1
0.7%
8238544000 1
0.7%
8237900000 1
0.7%
6420681330 1
0.7%
6204990410 1
0.7%
5954681150 1
0.7%
5487803950 1
0.7%
5267557900 1
0.7%
4002071010 1
0.7%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct112
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.235147
Minimum0
Maximum88.78
Zeros4
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-01-10T06:38:33.460694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.02
Q11.1975
median8.455
Q318.9425
95-th percentile46.9925
Maximum88.78
Range88.78
Interquartile range (IQR)17.745

Descriptive statistics

Standard deviation16.444808
Coefficient of variation (CV)1.2425104
Kurtosis4.4657885
Mean13.235147
Median Absolute Deviation (MAD)8.335
Skewness1.9334123
Sum1799.98
Variance270.43172
MonotonicityNot monotonic
2024-01-10T06:38:33.563731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02 10
 
7.4%
0.0 4
 
2.9%
0.05 3
 
2.2%
0.04 3
 
2.2%
0.1 3
 
2.2%
10.27 2
 
1.5%
0.14 2
 
1.5%
0.01 2
 
1.5%
0.03 2
 
1.5%
9.38 2
 
1.5%
Other values (102) 103
75.7%
ValueCountFrequency (%)
0.0 4
 
2.9%
0.01 2
 
1.5%
0.02 10
7.4%
0.03 2
 
1.5%
0.04 3
 
2.2%
0.05 3
 
2.2%
0.07 1
 
0.7%
0.1 3
 
2.2%
0.14 2
 
1.5%
0.28 1
 
0.7%
ValueCountFrequency (%)
88.78 1
0.7%
79.53 1
0.7%
56.26 1
0.7%
55.57 1
0.7%
51.12 1
0.7%
49.45 1
0.7%
47.69 1
0.7%
46.76 1
0.7%
43.57 1
0.7%
42.63 1
0.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2022-08-31
136 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-31
2nd row2022-08-31
3rd row2022-08-31
4th row2022-08-31
5th row2022-08-31

Common Values

ValueCountFrequency (%)
2022-08-31 136
100.0%

Length

2024-01-10T06:38:33.660547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:38:33.730632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-31 136
100.0%

Interactions

2024-01-10T06:38:31.384546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:30.921746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:31.148090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:31.470812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:31.001674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:31.236677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:31.544716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:31.071201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:31.311256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:38:33.778015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
납부년도1.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.0000.0000.2430.4930.559
납부매체0.0000.0001.0001.0000.3170.3610.587
납부매체전자고지여부0.0000.0001.0001.0000.0000.1940.217
납부건수0.0000.2430.3170.0001.0000.5470.614
납부금액0.0000.4930.3610.1940.5471.0000.306
납부매체비율0.0000.5590.5870.2170.6140.3061.000
2024-01-10T06:38:33.859875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부매체전자고지여부납부매체세목명납부년도
납부매체전자고지여부1.0000.9740.0000.000
납부매체0.9741.0000.0000.000
세목명0.0000.0001.0000.000
납부년도0.0000.0000.0001.000
2024-01-10T06:38:33.937876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율납부년도세목명납부매체납부매체전자고지여부
납부건수1.0000.7300.8110.0000.1100.1700.000
납부금액0.7301.0000.5120.0000.2440.1860.141
납부매체비율0.8110.5121.0000.0000.2740.2220.210
납부년도0.0000.0000.0001.0000.0000.0000.000
세목명0.1100.2440.2740.0001.0000.0000.000
납부매체0.1700.1860.2220.0000.0001.0000.974
납부매체전자고지여부0.0000.1410.2100.0000.0000.9741.000

Missing values

2024-01-10T06:38:31.653606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:38:31.809966image/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

시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율데이터기준일자
0충청남도부여군447602020담배소비세가상계좌Y1921484801300.022022-08-31
1충청남도부여군447602020등록면허세가상계좌Y80212214238709.382022-08-31
2충청남도부여군447602020등록세가상계좌Y3661406400.042022-08-31
3충청남도부여군447602020자동차세가상계좌Y23327317913393027.292022-08-31
4충청남도부여군447602020재산세가상계좌Y34773318162190040.682022-08-31
5충청남도부여군447602020종합토지세가상계좌Y176369600.022022-08-31
6충청남도부여군447602020주민세가상계좌Y1281940726893015.02022-08-31
7충청남도부여군447602020지방소득세가상계좌Y538018734846006.292022-08-31
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