Overview

Dataset statistics

Number of variables11
Number of observations235
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.5 KiB
Average record size in memory93.6 B

Variable types

Categorical6
Boolean1
Numeric3
DateTime1

Dataset

Description인천광역시 중구의 지방세 납부 현황에 대한 데이터로 납부년도, 세목명, 납부매체, 납부건수, 금액, 납부매체(방법)비율 등을 제공합니다.
URLhttps://www.data.go.kr/data/15079303/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
납부매체 is highly overall correlated with 납부매체전자고지여부High correlation
납부매체전자고지여부 is highly overall correlated with 납부매체High 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 11 (4.7%) zerosZeros

Reproduction

Analysis started2023-12-12 09:34:20.084982
Analysis finished2023-12-12 09:34:21.686903
Duration1.6 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
인천광역시
235 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 235
100.0%

Length

2023-12-12T18:34:21.761723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:34:21.863746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 235
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
중구
235 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 235
100.0%

Length

2023-12-12T18:34:21.978034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:34:22.071576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 235
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
28110
235 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28110
2nd row28110
3rd row28110
4th row28110
5th row28110

Common Values

ValueCountFrequency (%)
28110 235
100.0%

Length

2023-12-12T18:34:22.207003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:34:22.302645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28110 235
100.0%

납부년도
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2021
80 
2020
79 
2022
76 

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 80
34.0%
2020 79
33.6%
2022 76
32.3%

Length

2023-12-12T18:34:22.394984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:34:22.499923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 80
34.0%
2020 79
33.6%
2022 76
32.3%

세목명
Categorical

Distinct13
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
재산세
31 
등록면허세
30 
자동차세
30 
주민세
30 
지방소득세
27 
Other values (8)
87 

Length

Max length7
Median length5
Mean length3.9957447
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row등록면허세
2nd row자동차세
3rd row재산세
4th row주민세
5th row지방소득세

Common Values

ValueCountFrequency (%)
재산세 31
13.2%
등록면허세 30
12.8%
자동차세 30
12.8%
주민세 30
12.8%
지방소득세 27
11.5%
취득세 26
11.1%
지역자원시설세 15
6.4%
등록세 15
6.4%
종합토지세 11
 
4.7%
면허세 9
 
3.8%
Other values (3) 11
 
4.7%

Length

2023-12-12T18:34:22.628645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재산세 31
13.2%
등록면허세 30
12.8%
자동차세 30
12.8%
주민세 30
12.8%
지방소득세 27
11.5%
취득세 26
11.1%
지역자원시설세 15
6.4%
등록세 15
6.4%
종합토지세 11
 
4.7%
면허세 9
 
3.8%
Other values (3) 11
 
4.7%

납부매체
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
가상계좌
29 
자동화기기
29 
기타
28 
위택스
28 
지자체방문
28 
Other values (6)
93 

Length

Max length5
Median length4
Mean length3.9617021
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
가상계좌 29
12.3%
자동화기기 29
12.3%
기타 28
11.9%
위택스 28
11.9%
지자체방문 28
11.9%
은행창구 23
9.8%
인터넷지로 20
8.5%
ARS 19
8.1%
페이사납부 18
7.7%
자동이체 12
5.1%

Length

2023-12-12T18:34:22.790527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가상계좌 29
12.3%
자동화기기 29
12.3%
기타 28
11.9%
위택스 28
11.9%
지자체방문 28
11.9%
은행창구 23
9.8%
인터넷지로 20
8.5%
ars 19
8.1%
페이사납부 18
7.7%
자동이체 12
5.1%

납부매체전자고지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size367.0 B
False
127 
True
108 
ValueCountFrequency (%)
False 127
54.0%
True 108
46.0%
2023-12-12T18:34:22.901849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납부건수
Real number (ℝ)

HIGH CORRELATION 

Distinct193
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6873.2723
Minimum1
Maximum97151
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T18:34:23.103219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q127.5
median1613
Q35631
95-th percentile34494
Maximum97151
Range97150
Interquartile range (IQR)5603.5

Descriptive statistics

Standard deviation14829.475
Coefficient of variation (CV)2.1575567
Kurtosis15.90365
Mean6873.2723
Median Absolute Deviation (MAD)1609
Skewness3.7489102
Sum1615219
Variance2.1991332 × 108
MonotonicityNot monotonic
2023-12-12T18:34:23.302302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 9
 
3.8%
2 8
 
3.4%
3 7
 
3.0%
4 5
 
2.1%
7 5
 
2.1%
37 3
 
1.3%
6 3
 
1.3%
15 2
 
0.9%
5 2
 
0.9%
28 2
 
0.9%
Other values (183) 189
80.4%
ValueCountFrequency (%)
1 9
3.8%
2 8
3.4%
3 7
3.0%
4 5
2.1%
5 2
 
0.9%
6 3
 
1.3%
7 5
2.1%
8 1
 
0.4%
10 2
 
0.9%
11 1
 
0.4%
ValueCountFrequency (%)
97151 1
0.4%
90433 1
0.4%
83097 1
0.4%
73064 1
0.4%
70446 1
0.4%
69088 1
0.4%
43045 1
0.4%
41825 1
0.4%
38422 1
0.4%
37834 1
0.4%

납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct235
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9897601 × 109
Minimum12180
Maximum1.67128 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T18:34:23.478359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12180
5-th percentile98007
Q18762780
median4.131324 × 108
Q34.1428518 × 109
95-th percentile4.3905911 × 1010
Maximum1.67128 × 1011
Range1.6712799 × 1011
Interquartile range (IQR)4.134089 × 109

Descriptive statistics

Standard deviation1.9068875 × 1010
Coefficient of variation (CV)2.7281158
Kurtosis37.021393
Mean6.9897601 × 109
Median Absolute Deviation (MAD)4.1294832 × 108
Skewness5.3740036
Sum1.6425936 × 1012
Variance3.6362199 × 1020
MonotonicityNot monotonic
2023-12-12T18:34:23.665097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2925810 1
 
0.4%
6166060 1
 
0.4%
400604480 1
 
0.4%
7238181580 1
 
0.4%
260000000 1
 
0.4%
895130 1
 
0.4%
8818364080 1
 
0.4%
18026320 1
 
0.4%
343772210 1
 
0.4%
3241592220 1
 
0.4%
Other values (225) 225
95.7%
ValueCountFrequency (%)
12180 1
0.4%
12950 1
0.4%
13100 1
0.4%
19830 1
0.4%
27390 1
0.4%
28630 1
0.4%
29100 1
0.4%
56700 1
0.4%
79010 1
0.4%
83600 1
0.4%
ValueCountFrequency (%)
167128000000 1
0.4%
155274000000 1
0.4%
74591765120 1
0.4%
68445299890 1
0.4%
57130770530 1
0.4%
53459332430 1
0.4%
49340098750 1
0.4%
49126634210 1
0.4%
48096471430 1
0.4%
45767763180 1
0.4%

납부매체비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct178
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.191277
Minimum0
Maximum100
Zeros11
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T18:34:23.832577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01
Q10.085
median8.32
Q317.28
95-th percentile46.809
Maximum100
Range100
Interquartile range (IQR)17.195

Descriptive statistics

Standard deviation16.853176
Coefficient of variation (CV)1.2776001
Kurtosis4.3899612
Mean13.191277
Median Absolute Deviation (MAD)8.26
Skewness1.9054802
Sum3099.95
Variance284.02954
MonotonicityNot monotonic
2023-12-12T18:34:24.017358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 19
 
8.1%
0.0 11
 
4.7%
0.03 8
 
3.4%
0.02 6
 
2.6%
0.05 5
 
2.1%
0.07 3
 
1.3%
0.04 3
 
1.3%
0.06 3
 
1.3%
0.22 2
 
0.9%
3.02 2
 
0.9%
Other values (168) 173
73.6%
ValueCountFrequency (%)
0.0 11
4.7%
0.01 19
8.1%
0.02 6
 
2.6%
0.03 8
3.4%
0.04 3
 
1.3%
0.05 5
 
2.1%
0.06 3
 
1.3%
0.07 3
 
1.3%
0.08 1
 
0.4%
0.09 2
 
0.9%
ValueCountFrequency (%)
100.0 1
0.4%
78.62 1
0.4%
74.39 1
0.4%
71.28 1
0.4%
62.07 1
0.4%
61.53 1
0.4%
52.15 1
0.4%
51.86 1
0.4%
51.64 1
0.4%
51.14 1
0.4%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2023-08-09 00:00:00
Maximum2023-08-09 00:00:00
2023-12-12T18:34:24.168102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:34:24.312119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T18:34:21.038835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:34:20.475741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:34:20.755568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:34:21.134607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:34:20.559902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:34:20.850168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:34:21.247022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:34:20.659578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:34:20.948256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:34:24.421335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율
납부년도1.0000.0000.0000.0000.0000.0860.000
세목명0.0001.0000.0000.0000.0830.3930.550
납부매체0.0000.0001.0001.0000.4000.2580.698
납부매체전자고지여부0.0000.0001.0001.0000.3310.0610.280
납부건수0.0000.0830.4000.3311.0000.6430.438
납부금액0.0860.3930.2580.0610.6431.0000.276
납부매체비율0.0000.5500.6980.2800.4380.2761.000
2023-12-12T18:34:24.569073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명납부년도납부매체납부매체전자고지여부
세목명1.0000.0000.0000.000
납부년도0.0001.0000.0000.000
납부매체0.0000.0001.0000.980
납부매체전자고지여부0.0000.0000.9801.000
2023-12-12T18:34:24.699039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납부건수납부금액납부매체비율납부년도세목명납부매체납부매체전자고지여부
납부건수1.0000.8440.8240.0000.0340.2000.245
납부금액0.8441.0000.6570.0330.2030.1290.038
납부매체비율0.8240.6571.0000.0000.2710.4080.275
납부년도0.0000.0330.0001.0000.0000.0000.000
세목명0.0340.2030.2710.0001.0000.0000.000
납부매체0.2000.1290.4080.0000.0001.0000.980
납부매체전자고지여부0.2450.0380.2750.0000.0000.9801.000

Missing values

2023-12-12T18:34:21.432494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:34:21.613861image/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

시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율데이터기준일
0인천광역시중구281102020등록면허세ARSN8929258102.352023-08-09
1인천광역시중구281102020자동차세ARSN141428155936037.392023-08-09
2인천광역시중구281102020재산세ARSN195346078261051.642023-08-09
3인천광역시중구281102020주민세ARSN23787844106.272023-08-09
4인천광역시중구281102020지방소득세ARSN67187016001.772023-08-09
5인천광역시중구281102020취득세ARSN22540888800.582023-08-09
6인천광역시중구281102020등록면허세가상계좌Y189028613913808.012023-08-09
7인천광역시중구281102020면허세가상계좌Y183852300.012023-08-09
8인천광역시중구281102020자동차세가상계좌Y69088929264574029.282023-08-09
9인천광역시중구281102020재산세가상계좌Y830976844529989035.222023-08-09
시도명시군구명자치단체코드납부년도세목명납부매체납부매체전자고지여부납부건수납부금액납부매체비율데이터기준일
225인천광역시중구281102022종합토지세지자체방문N42106300.022023-08-09
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