Overview

Dataset statistics

Number of variables10
Number of observations201
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.8 KiB
Average record size in memory85.7 B

Variable types

Categorical6
Boolean1
Numeric3

Dataset

Description2017~2021년도 충청남도 보령시 지방세 관련 신용카드,가상계좌 등 지방세 납부매체*별 납부 현황 항목에 대한 자료를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=350&beforeMenuCd=DOM_000000201001001000&publicdatapk=15079092

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
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
납부매체비율 has 10 (5.0%) zerosZeros

Reproduction

Analysis started2024-01-09 22:06:45.087452
Analysis finished2024-01-09 22:06:46.329650
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
충청남도
201 

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 201
100.0%

Length

2024-01-10T07:06:46.389417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:06:46.489055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 201
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
보령시
201 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보령시 201
100.0%

Length

2024-01-10T07:06:46.586877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:06:46.681670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보령시 201
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
44180
201 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44180
2nd row44180
3rd row44180
4th row44180
5th row44180

Common Values

ValueCountFrequency (%)
44180 201
100.0%

Length

2024-01-10T07:06:46.782976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:06:46.875564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44180 201
100.0%

납부년도
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2019
72 
2017
66 
2018
63 

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 (%)
2019 72
35.8%
2017 66
32.8%
2018 63
31.3%

Length

2024-01-10T07:06:46.972676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:06:47.074246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 72
35.8%
2017 66
32.8%
2018 63
31.3%

세목명
Categorical

Distinct12
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
등록면허세
25 
자동차세
25 
재산세
25 
주민세
25 
지방소득세
22 
Other values (7)
79 

Length

Max length7
Median length3
Mean length3.9054726
Min length3

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
등록면허세 25
12.4%
자동차세 25
12.4%
재산세 25
12.4%
주민세 25
12.4%
지방소득세 22
10.9%
취득세 22
10.9%
등록세 16
8.0%
면허세 16
8.0%
종합토지세 13
6.5%
지역자원시설세 7
 
3.5%
Other values (2) 5
 
2.5%

Length

2024-01-10T07:06:47.168774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록면허세 25
12.4%
자동차세 25
12.4%
재산세 25
12.4%
주민세 25
12.4%
지방소득세 22
10.9%
취득세 22
10.9%
등록세 16
8.0%
면허세 16
8.0%
종합토지세 13
6.5%
지역자원시설세 7
 
3.5%
Other values (2) 5
 
2.5%

납부매체
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
가상계좌
30 
은행창구
30 
기타
26 
지자체방문
26 
자동화기기
25 
Other values (4)
64 

Length

Max length5
Median length4
Mean length4.0248756
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가상계좌 30
14.9%
은행창구 30
14.9%
기타 26
12.9%
지자체방문 26
12.9%
자동화기기 25
12.4%
위택스 23
11.4%
인터넷지로 23
11.4%
자동이체 12
 
6.0%
페이사납부 6
 
3.0%

Length

2024-01-10T07:06:47.265238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:06:47.367431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가상계좌 30
14.9%
은행창구 30
14.9%
기타 26
12.9%
지자체방문 26
12.9%
자동화기기 25
12.4%
위택스 23
11.4%
인터넷지로 23
11.4%
자동이체 12
 
6.0%
페이사납부 6
 
3.0%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size333.0 B
False
107 
True
94 
ValueCountFrequency (%)
False 107
53.2%
True 94
46.8%
2024-01-10T07:06:47.463698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct169
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4937.8557
Minimum1
Maximum41644
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-01-10T07:06:47.775854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q146
median1332
Q35501
95-th percentile23139
Maximum41644
Range41643
Interquartile range (IQR)5455

Descriptive statistics

Standard deviation8220.0452
Coefficient of variation (CV)1.6646993
Kurtosis5.9086423
Mean4937.8557
Median Absolute Deviation (MAD)1328
Skewness2.4171404
Sum992509
Variance67569142
MonotonicityNot monotonic
2024-01-10T07:06:47.873421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 14
 
7.0%
2 4
 
2.0%
5 4
 
2.0%
6 3
 
1.5%
12 3
 
1.5%
13 3
 
1.5%
246 2
 
1.0%
25 2
 
1.0%
4 2
 
1.0%
9 2
 
1.0%
Other values (159) 162
80.6%
ValueCountFrequency (%)
1 14
7.0%
2 4
 
2.0%
3 2
 
1.0%
4 2
 
1.0%
5 4
 
2.0%
6 3
 
1.5%
7 1
 
0.5%
8 1
 
0.5%
9 2
 
1.0%
11 1
 
0.5%
ValueCountFrequency (%)
41644 1
0.5%
39402 1
0.5%
37082 1
0.5%
34414 1
0.5%
34342 1
0.5%
31360 1
0.5%
29611 1
0.5%
28677 1
0.5%
27706 1
0.5%
24111 1
0.5%

납부금액
Real number (ℝ)

HIGH CORRELATION 

Distinct200
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9460842 × 109
Minimum3550
Maximum1.5768463 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-01-10T07:06:47.974064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3550
5-th percentile30130
Q114850550
median3.6681191 × 108
Q32.5302126 × 109
95-th percentile8.9550232 × 109
Maximum1.5768463 × 1010
Range1.5768459 × 1010
Interquartile range (IQR)2.5153621 × 109

Descriptive statistics

Standard deviation3.2153681 × 109
Coefficient of variation (CV)1.6522246
Kurtosis3.5275657
Mean1.9460842 × 109
Median Absolute Deviation (MAD)3.6670035 × 108
Skewness2.0212013
Sum3.9116292 × 1011
Variance1.0338592 × 1019
MonotonicityNot monotonic
2024-01-10T07:06:48.085423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10300 2
 
1.0%
282957110 1
 
0.5%
393165760 1
 
0.5%
4465670 1
 
0.5%
376800 1
 
0.5%
5510752290 1
 
0.5%
7216577690 1
 
0.5%
152770 1
 
0.5%
775559880 1
 
0.5%
3323013970 1
 
0.5%
Other values (190) 190
94.5%
ValueCountFrequency (%)
3550 1
0.5%
4500 1
0.5%
5150 1
0.5%
6180 1
0.5%
10300 2
1.0%
14810 1
0.5%
15110 1
0.5%
17470 1
0.5%
20600 1
0.5%
30130 1
0.5%
ValueCountFrequency (%)
15768462950 1
0.5%
12567404820 1
0.5%
12407140100 1
0.5%
12308818170 1
0.5%
11948722880 1
0.5%
11876651180 1
0.5%
11303691120 1
0.5%
11069514930 1
0.5%
10171130590 1
0.5%
9876110560 1
0.5%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct161
Distinct (%)80.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.43801
Minimum0
Maximum83.71
Zeros10
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-01-10T07:06:48.200090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01
Q10.15
median7.63
Q317.17
95-th percentile40.26
Maximum83.71
Range83.71
Interquartile range (IQR)17.02

Descriptive statistics

Standard deviation15.434398
Coefficient of variation (CV)1.2409058
Kurtosis5.1317543
Mean12.43801
Median Absolute Deviation (MAD)7.57
Skewness1.952621
Sum2500.04
Variance238.22066
MonotonicityNot monotonic
2024-01-10T07:06:48.304528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 12
 
6.0%
0.0 10
 
5.0%
0.06 5
 
2.5%
0.03 4
 
2.0%
0.02 4
 
2.0%
0.13 3
 
1.5%
0.16 3
 
1.5%
0.05 3
 
1.5%
0.09 2
 
1.0%
0.1 2
 
1.0%
Other values (151) 153
76.1%
ValueCountFrequency (%)
0.0 10
5.0%
0.01 12
6.0%
0.02 4
 
2.0%
0.03 4
 
2.0%
0.04 1
 
0.5%
0.05 3
 
1.5%
0.06 5
2.5%
0.07 1
 
0.5%
0.08 1
 
0.5%
0.09 2
 
1.0%
ValueCountFrequency (%)
83.71 1
0.5%
83.33 1
0.5%
80.61 1
0.5%
49.56 1
0.5%
49.18 1
0.5%
49.16 1
0.5%
48.55 1
0.5%
44.92 1
0.5%
44.64 1
0.5%
42.81 1
0.5%

Interactions

2024-01-10T07:06:45.859719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:45.396226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:45.591278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:45.933248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:45.453164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:45.678901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:46.024978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:45.525105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:06:45.775481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:06:48.376309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
납부년도1.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.0000.2730.2390.5470.618
납부매체0.0000.0001.0001.0000.3390.4870.505
납부매체전자고지여부0.0000.2731.0001.0000.1340.0000.149
납부건수0.0000.2390.3390.1341.0000.6040.677
납부금액0.0000.5470.4870.0000.6041.0000.396
납부매체비율0.0000.6180.5050.1490.6770.3961.000
2024-01-10T07:06:48.461697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부매체전자고지여부납부매체세목명납부년도
납부매체전자고지여부1.0000.9820.2060.000
납부매체0.9821.0000.0000.000
세목명0.2060.0001.0000.000
납부년도0.0000.0000.0001.000
2024-01-10T07:06:48.535337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율납부년도세목명납부매체납부매체전자고지여부
납부건수1.0000.7020.8670.0000.1000.1600.099
납부금액0.7021.0000.5630.0000.2670.1730.000
납부매체비율0.8670.5631.0000.0000.3550.2940.157
납부년도0.0000.0000.0001.0000.0000.0000.000
세목명0.1000.2670.3550.0001.0000.0000.206
납부매체0.1600.1730.2940.0000.0001.0000.982
납부매체전자고지여부0.0990.0000.1570.0000.2060.9821.000

Missing values

2024-01-10T07:06:46.131843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:06:46.274182image/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
0충청남도보령시441802017등록면허세가상계좌Y1068728295711010.97
1충청남도보령시441802017등록세가상계좌Y1525906100.02
2충청남도보령시441802017면허세가상계좌Y292941400.03
3충청남도보령시441802017자동차세가상계좌Y31360463444147032.18
4충청남도보령시441802017재산세가상계좌Y34414499241715035.32
5충청남도보령시441802017종합토지세가상계좌Y21073300.0
6충청남도보령시441802017주민세가상계좌Y1698255914091017.43
7충청남도보령시441802017지방소득세가상계좌Y290828739694502.98
8충청남도보령시441802017지역자원시설세가상계좌Y1329839204300.01
9충청남도보령시441802017취득세가상계좌Y1033157684629501.06
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
191충청남도보령시441802019종합토지세지자체방문N2301300.02
192충청남도보령시441802019주민세지자체방문N16903933208014.85
193충청남도보령시441802019지방소득세지자체방문N3681371292403.23
194충청남도보령시441802019취득세지자체방문N2344414115102.06
195충청남도보령시441802019등록면허세페이사납부Y145000.16
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