Overview

Dataset statistics

Number of variables12
Number of observations97
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.8 KiB
Average record size in memory103.4 B

Variable types

Numeric4
Categorical6
Boolean1
DateTime1

Dataset

Description남양주시의 납부년도별 세목명, 납부매체, 납부매체전자고지여부, 납부건수, 납부금액, 납부매체비율로 구성된 데이터입니다. 시군구명
Author경기도 남양주시
URLhttps://www.data.go.kr/data/15102886/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
납부년도 has constant value ""Constant
데이터기준일자 has constant value ""Constant
번호 is highly overall correlated with 납부매체 and 1 other fieldsHigh 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
납부매체 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
납부매체전자고지여부 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
번호 has unique valuesUnique
납부금액 has unique valuesUnique
납부매체비율 has 14 (14.4%) zerosZeros

Reproduction

Analysis started2023-12-12 16:43:20.912340
Analysis finished2023-12-12 16:43:23.019299
Duration2.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49
Minimum1
Maximum97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-13T01:43:23.097288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.8
Q125
median49
Q373
95-th percentile92.2
Maximum97
Range96
Interquartile range (IQR)48

Descriptive statistics

Standard deviation28.145456
Coefficient of variation (CV)0.57439705
Kurtosis-1.2
Mean49
Median Absolute Deviation (MAD)24
Skewness0
Sum4753
Variance792.16667
MonotonicityStrictly increasing
2023-12-13T01:43:23.240048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
74 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
67 1
 
1.0%
66 1
 
1.0%
65 1
 
1.0%
Other values (87) 87
89.7%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%
90 1
1.0%
89 1
1.0%
88 1
1.0%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
경기도
97 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 97
100.0%

Length

2023-12-13T01:43:23.368614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:43:23.457895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 97
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
남양주시
97 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남양주시 97
100.0%

Length

2023-12-13T01:43:23.572297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:43:23.661796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남양주시 97
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
41360
97 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41360
2nd row41360
3rd row41360
4th row41360
5th row41360

Common Values

ValueCountFrequency (%)
41360 97
100.0%

Length

2023-12-13T01:43:23.761961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:43:23.883055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41360 97
100.0%

납부년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
2021
97 

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 97
100.0%

Length

2023-12-13T01:43:23.994728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:43:24.101470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 97
100.0%

세목명
Categorical

Distinct13
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size908.0 B
등록면허세
11 
자동차세
11 
재산세
11 
주민세
11 
지방소득세
10 
Other values (8)
43 

Length

Max length7
Median length5
Mean length4.1237113
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
등록면허세 11
11.3%
자동차세 11
11.3%
재산세 11
11.3%
주민세 11
11.3%
지방소득세 10
10.3%
지역자원시설세 9
9.3%
취득세 9
9.3%
면허세 7
7.2%
등록세 7
7.2%
종합토지세 5
5.2%
Other values (3) 6
6.2%

Length

2023-12-13T01:43:24.229689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
등록면허세 11
11.3%
자동차세 11
11.3%
재산세 11
11.3%
주민세 11
11.3%
지방소득세 10
10.3%
지역자원시설세 9
9.3%
취득세 9
9.3%
면허세 7
7.2%
등록세 7
7.2%
종합토지세 5
5.2%
Other values (3) 6
6.2%

납부매체
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size908.0 B
ARS
14 
기타
13 
가상계좌
12 
자동화기기
10 
지자체방문
10 
Other values (5)
38 

Length

Max length5
Median length4
Mean length3.8659794
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
ARS 14
14.4%
기타 13
13.4%
가상계좌 12
12.4%
자동화기기 10
10.3%
지자체방문 10
10.3%
위택스 9
9.3%
은행창구 9
9.3%
인터넷지로 9
9.3%
페이사납부 7
7.2%
자동이체 4
 
4.1%

Length

2023-12-13T01:43:24.779095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:43:24.970214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ars 14
14.4%
기타 13
13.4%
가상계좌 12
12.4%
자동화기기 10
10.3%
지자체방문 10
10.3%
위택스 9
9.3%
은행창구 9
9.3%
인터넷지로 9
9.3%
페이사납부 7
7.2%
자동이체 4
 
4.1%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size229.0 B
False
51 
True
46 
ValueCountFrequency (%)
False 51
52.6%
True 46
47.4%
2023-12-13T01:43:25.152144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct86
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20156.598
Minimum1
Maximum292218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-13T01:43:25.297595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q138
median1664
Q314775
95-th percentile90711.6
Maximum292218
Range292217
Interquartile range (IQR)14737

Descriptive statistics

Standard deviation49268.308
Coefficient of variation (CV)2.4442769
Kurtosis17.006653
Mean20156.598
Median Absolute Deviation (MAD)1663
Skewness3.9866412
Sum1955190
Variance2.4273661 × 109
MonotonicityNot monotonic
2023-12-13T01:43:25.499567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 6
 
6.2%
2 4
 
4.1%
7 3
 
3.1%
14 2
 
2.1%
1102 1
 
1.0%
4201 1
 
1.0%
51 1
 
1.0%
13928 1
 
1.0%
6604 1
 
1.0%
14160 1
 
1.0%
Other values (76) 76
78.4%
ValueCountFrequency (%)
1 6
6.2%
2 4
4.1%
3 1
 
1.0%
5 1
 
1.0%
7 3
3.1%
11 1
 
1.0%
13 1
 
1.0%
14 2
 
2.1%
15 1
 
1.0%
22 1
 
1.0%
ValueCountFrequency (%)
292218 1
1.0%
265989 1
1.0%
197624 1
1.0%
151521 1
1.0%
142314 1
1.0%
77811 1
1.0%
77747 1
1.0%
66195 1
1.0%
63609 1
1.0%
38971 1
1.0%

납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2765643 × 1010
Minimum5220
Maximum4.09 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-13T01:43:25.695262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5220
5-th percentile39772
Q12637030
median5.4916901 × 108
Q35.3778425 × 109
95-th percentile5.1825923 × 1010
Maximum4.09 × 1011
Range4.0899999 × 1011
Interquartile range (IQR)5.3752055 × 109

Descriptive statistics

Standard deviation4.4954985 × 1010
Coefficient of variation (CV)3.5215605
Kurtosis64.237956
Mean1.2765643 × 1010
Median Absolute Deviation (MAD)5.4901495 × 108
Skewness7.4823188
Sum1.2382674 × 1012
Variance2.0209507 × 1021
MonotonicityNot monotonic
2023-12-13T01:43:25.903754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14074020 1
 
1.0%
6336635040 1
 
1.0%
45026830 1
 
1.0%
2286779640 1
 
1.0%
68550000 1
 
1.0%
4842505220 1
 
1.0%
983006000 1
 
1.0%
83756100 1
 
1.0%
15049062400 1
 
1.0%
117584760 1
 
1.0%
Other values (87) 87
89.7%
ValueCountFrequency (%)
5220 1
1.0%
6300 1
1.0%
13600 1
1.0%
13640 1
1.0%
18540 1
1.0%
45080 1
1.0%
118100 1
1.0%
147100 1
1.0%
154060 1
1.0%
195840 1
1.0%
ValueCountFrequency (%)
409000000000 1
1.0%
111000000000 1
1.0%
93501029030 1
1.0%
63328095320 1
1.0%
54537202160 1
1.0%
51148102730 1
1.0%
45208704070 1
1.0%
39480521030 1
1.0%
36668624030 1
1.0%
35441412090 1
1.0%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct71
Distinct (%)73.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.309485
Minimum0
Maximum49.22
Zeros14
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-13T01:43:26.094124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.04
median3.92
Q317.61
95-th percentile37.744
Maximum49.22
Range49.22
Interquartile range (IQR)17.57

Descriptive statistics

Standard deviation13.017426
Coefficient of variation (CV)1.262665
Kurtosis0.50510141
Mean10.309485
Median Absolute Deviation (MAD)3.92
Skewness1.1940006
Sum1000.02
Variance169.45337
MonotonicityNot monotonic
2023-12-13T01:43:26.258709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 14
 
14.4%
0.02 5
 
5.2%
0.04 4
 
4.1%
0.13 3
 
3.1%
0.03 2
 
2.1%
0.01 2
 
2.1%
0.12 2
 
2.1%
0.08 2
 
2.1%
28.16 1
 
1.0%
14.68 1
 
1.0%
Other values (61) 61
62.9%
ValueCountFrequency (%)
0.0 14
14.4%
0.01 2
 
2.1%
0.02 5
 
5.2%
0.03 2
 
2.1%
0.04 4
 
4.1%
0.06 1
 
1.0%
0.07 1
 
1.0%
0.08 2
 
2.1%
0.12 2
 
2.1%
0.13 3
 
3.1%
ValueCountFrequency (%)
49.22 1
1.0%
46.34 1
1.0%
44.35 1
1.0%
39.57 1
1.0%
38.48 1
1.0%
37.56 1
1.0%
35.2 1
1.0%
33.37 1
1.0%
30.47 1
1.0%
29.4 1
1.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
Minimum2023-02-02 00:00:00
Maximum2023-02-02 00:00:00
2023-12-13T01:43:26.401622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:26.517482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T01:43:22.386535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:21.256719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:21.673273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:22.001430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:22.470256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:21.398084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:21.753441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:22.105219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:22.551777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:21.485791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:21.831367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:22.196242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:22.635356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:21.591955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:21.916234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:43:22.289299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:43:26.609370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
번호1.0000.0000.9850.8420.2670.1590.000
세목명0.0001.0000.0000.0000.0000.0000.286
납부매체0.9850.0001.0000.9930.3780.2800.493
납부매체전자고지여부0.8420.0000.9931.0000.1170.2700.000
납부건수0.2670.0000.3780.1171.0000.6440.626
납부금액0.1590.0000.2800.2700.6441.0000.019
납부매체비율0.0000.2860.4930.0000.6260.0191.000
2023-12-13T01:43:26.739116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부매체납부매체전자고지여부세목명
납부매체1.0000.8840.000
납부매체전자고지여부0.8841.0000.000
세목명0.0000.0001.000
2023-12-13T01:43:26.867096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호납부건수납부금액납부매체비율세목명납부매체납부매체전자고지여부
번호1.0000.0790.0450.1730.0000.7840.646
납부건수0.0791.0000.8340.9120.0000.1960.119
납부금액0.0450.8341.0000.7470.0000.1660.172
납부매체비율0.1730.9120.7471.0000.1140.1670.000
세목명0.0000.0000.0000.1141.0000.0000.000
납부매체0.7840.1960.1660.1670.0001.0000.884
납부매체전자고지여부0.6460.1190.1720.0000.0000.8841.000

Missing values

2023-12-13T01:43:22.774619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:43:22.947712image/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

번호시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율데이터기준일자
01경기도남양주시413602021등록면허세ARSN1102140740201.942023-02-02
12경기도남양주시413602021등록면허세ARSY131958400.022023-02-02
23경기도남양주시413602021면허세ARSN432800900.082023-02-02
34경기도남양주시413602021자동차세ARSN26329512868245046.342023-02-02
45경기도남양주시413602021자동차세ARSY117143178900.212023-02-02
56경기도남양주시413602021재산세ARSN20002537784253035.22023-02-02
67경기도남양주시413602021재산세ARSY2226370300.042023-02-02
78경기도남양주시413602021종합토지세ARSN51540600.012023-02-02
89경기도남양주시413602021주민세ARSN742011726021013.062023-02-02
910경기도남양주시413602021주민세ARSY749408000.132023-02-02
번호시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율데이터기준일자
8788경기도남양주시413602021지방소득세지자체방문N16645491690104.052023-02-02
8889경기도남양주시413602021지역자원시설세지자체방문N626171200.152023-02-02
8990경기도남양주시413602021취득세지자체방문N2952105971020307.182023-02-02
9091경기도남양주시413602021등록면허세페이사납부Y1560211876203.522023-02-02
9192경기도남양주시413602021자동차세페이사납부Y17523304813153039.572023-02-02
9293경기도남양주시413602021재산세페이사납부Y14775342685478033.372023-02-02
9394경기도남양주시413602021주민세페이사납부Y1030811547729023.282023-02-02
9495경기도남양주시413602021지방소득세페이사납부Y80209210500.182023-02-02
9596경기도남양주시413602021지역자원시설세페이사납부Y152200.02023-02-02
9697경기도남양주시413602021취득세페이사납부Y34682554000.082023-02-02