Overview

Dataset statistics

Number of variables10
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory89.8 B

Variable types

Categorical6
Numeric4

Dataset

Description부산광역시금정구_지방세체납현황_20221221
Author부산광역시 금정구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15079661

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
체납건수 is highly overall correlated with 누적체납건수 and 1 other fieldsHigh correlation
체납금액 is highly overall correlated with 누적체납금액High correlation
누적체납건수 is highly overall correlated with 체납건수High correlation
누적체납금액 is highly overall correlated with 체납건수 and 1 other fieldsHigh correlation
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:21:40.572228
Analysis finished2023-12-10 16:21:43.315762
Duration2.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
부산광역시
35 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 35
100.0%

Length

2023-12-11T01:21:43.400750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:21:43.553194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 35
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
금정구
35 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
금정구 35
100.0%

Length

2023-12-11T01:21:43.682726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:21:43.808533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
금정구 35
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
26410
35 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26410
2nd row26410
3rd row26410
4th row26410
5th row26410

Common Values

ValueCountFrequency (%)
26410 35
100.0%

Length

2023-12-11T01:21:43.929191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:21:44.035002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26410 35
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
2021
35 

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 35
100.0%

Length

2023-12-11T01:21:44.170307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:21:44.302135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 35
100.0%

세목명
Categorical

Distinct7
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
지방소득세
10 
재산세
8 
취득세
7 
자동차세
4 
주민세
4 
Other values (2)
2 

Length

Max length7
Median length3
Mean length3.8571429
Min length3

Unique

Unique2 ?
Unique (%)5.7%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 10
28.6%
재산세 8
22.9%
취득세 7
20.0%
자동차세 4
 
11.4%
주민세 4
 
11.4%
등록면허세 1
 
2.9%
지역자원시설세 1
 
2.9%

Length

2023-12-11T01:21:44.452468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:21:44.615980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 10
28.6%
재산세 8
22.9%
취득세 7
20.0%
자동차세 4
 
11.4%
주민세 4
 
11.4%
등록면허세 1
 
2.9%
지역자원시설세 1
 
2.9%

체납액구간
Categorical

Distinct10
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
10만원 미만
7 
10만원~30만원미만
5 
30만원~50만원미만
5 
50만원~1백만원미만
5 
1백만원~3백만원미만
3 
Other values (5)
10 

Length

Max length11
Median length11
Mean length10.142857
Min length7

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row10만원 미만
2nd row10만원 미만
3rd row10만원~30만원미만
4th row30만원~50만원미만
5th row50만원~1백만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 7
20.0%
10만원~30만원미만 5
14.3%
30만원~50만원미만 5
14.3%
50만원~1백만원미만 5
14.3%
1백만원~3백만원미만 3
8.6%
5백만원~1천만원미만 3
8.6%
1천만원~3천만원미만 2
 
5.7%
3백만원~5백만원미만 2
 
5.7%
5천만원~1억원미만 2
 
5.7%
3천만원~5천만원미만 1
 
2.9%

Length

2023-12-11T01:21:44.850590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:21:45.037563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 7
16.7%
미만 7
16.7%
10만원~30만원미만 5
11.9%
30만원~50만원미만 5
11.9%
50만원~1백만원미만 5
11.9%
1백만원~3백만원미만 3
7.1%
5백만원~1천만원미만 3
7.1%
1천만원~3천만원미만 2
 
4.8%
3백만원~5백만원미만 2
 
4.8%
5천만원~1억원미만 2
 
4.8%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean620.05714
Minimum1
Maximum9934
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-11T01:21:45.220953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median38
Q3157
95-th percentile2567.5
Maximum9934
Range9933
Interquartile range (IQR)151

Descriptive statistics

Standard deviation1793.2907
Coefficient of variation (CV)2.8921378
Kurtosis22.580207
Mean620.05714
Median Absolute Deviation (MAD)37
Skewness4.5206652
Sum21702
Variance3215891.6
MonotonicityNot monotonic
2023-12-11T01:21:45.377059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 4
 
11.4%
4 2
 
5.7%
3 2
 
5.7%
7 2
 
5.7%
764 1
 
2.9%
115 1
 
2.9%
11 1
 
2.9%
38 1
 
2.9%
49 1
 
2.9%
5 1
 
2.9%
Other values (19) 19
54.3%
ValueCountFrequency (%)
1 4
11.4%
3 2
5.7%
4 2
5.7%
5 1
 
2.9%
7 2
5.7%
10 1
 
2.9%
11 1
 
2.9%
14 1
 
2.9%
23 1
 
2.9%
27 1
 
2.9%
ValueCountFrequency (%)
9934 1
2.9%
3677 1
2.9%
2092 1
2.9%
1643 1
2.9%
1342 1
2.9%
989 1
2.9%
764 1
2.9%
229 1
2.9%
199 1
2.9%
115 1
2.9%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95106265
Minimum616890
Maximum4.0908218 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-11T01:21:45.549789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum616890
5-th percentile1336905
Q14784000
median46478150
Q31.3585648 × 108
95-th percentile3.501503 × 108
Maximum4.0908218 × 108
Range4.0846529 × 108
Interquartile range (IQR)1.3107248 × 108

Descriptive statistics

Standard deviation1.1841183 × 108
Coefficient of variation (CV)1.2450476
Kurtosis0.77452524
Mean95106265
Median Absolute Deviation (MAD)43841070
Skewness1.3746319
Sum3.3287193 × 109
Variance1.4021362 × 1016
MonotonicityNot monotonic
2023-12-11T01:21:45.729316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
25745670 1
 
2.9%
80319140 1
 
2.9%
409082180 1
 
2.9%
32835820 1
 
2.9%
113244940 1
 
2.9%
359622730 1
 
2.9%
77457350 1
 
2.9%
290187150 1
 
2.9%
346090690 1
 
2.9%
836020 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
616890 1
2.9%
836020 1
2.9%
1551570 1
2.9%
1676290 1
2.9%
1695870 1
2.9%
2184750 1
2.9%
2637080 1
2.9%
2860100 1
2.9%
4417580 1
2.9%
5150420 1
2.9%
ValueCountFrequency (%)
409082180 1
2.9%
359622730 1
2.9%
346090690 1
2.9%
290187150 1
2.9%
281082060 1
2.9%
225447220 1
2.9%
211261400 1
2.9%
189439820 1
2.9%
158468010 1
2.9%
113244940 1
2.9%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1973.4571
Minimum1
Maximum32948
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-11T01:21:45.903268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q111
median67
Q3311.5
95-th percentile8960.5
Maximum32948
Range32947
Interquartile range (IQR)300.5

Descriptive statistics

Standard deviation5956.9537
Coefficient of variation (CV)3.0185371
Kurtosis22.583466
Mean1973.4571
Median Absolute Deviation (MAD)62
Skewness4.5107846
Sum69071
Variance35485297
MonotonicityNot monotonic
2023-12-11T01:21:46.084796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
18 3
 
8.6%
1 3
 
8.6%
10 3
 
8.6%
1923 1
 
2.9%
27 1
 
2.9%
12 1
 
2.9%
9 1
 
2.9%
7 1
 
2.9%
29 1
 
2.9%
129 1
 
2.9%
Other values (19) 19
54.3%
ValueCountFrequency (%)
1 3
8.6%
5 1
 
2.9%
7 1
 
2.9%
9 1
 
2.9%
10 3
8.6%
12 1
 
2.9%
18 3
8.6%
27 1
 
2.9%
29 1
 
2.9%
36 1
 
2.9%
ValueCountFrequency (%)
32948 1
2.9%
9426 1
2.9%
8761 1
2.9%
8748 1
2.9%
2318 1
2.9%
2289 1
2.9%
1923 1
2.9%
625 1
2.9%
319 1
2.9%
304 1
2.9%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7982192 × 108
Minimum963380
Maximum1.4504754 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-11T01:21:46.232608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum963380
5-th percentile4658259
Q19506930
median68687430
Q33.14722 × 108
95-th percentile4.7840001 × 108
Maximum1.4504754 × 109
Range1.449512 × 109
Interquartile range (IQR)3.0521507 × 108

Descriptive statistics

Standard deviation2.7305475 × 108
Coefficient of variation (CV)1.5184732
Kurtosis13.585754
Mean1.7982192 × 108
Median Absolute Deviation (MAD)62207640
Skewness3.2518411
Sum6.2937671 × 109
Variance7.4558899 × 1016
MonotonicityNot monotonic
2023-12-11T01:21:46.411431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
64954840 1
 
2.9%
391795190 1
 
2.9%
409082180 1
 
2.9%
66488440 1
 
2.9%
136026650 1
 
2.9%
359622730 1
 
2.9%
195175990 1
 
2.9%
305926570 1
 
2.9%
346090690 1
 
2.9%
963380 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
963380 1
2.9%
3433630 1
2.9%
5183100 1
2.9%
5244280 1
2.9%
6479790 1
2.9%
6604690 1
2.9%
7227340 1
2.9%
7765380 1
2.9%
9068710 1
2.9%
9945150 1
2.9%
ValueCountFrequency (%)
1450475380 1
2.9%
640141630 1
2.9%
409082180 1
2.9%
391795190 1
2.9%
359622730 1
2.9%
357658970 1
2.9%
346090690 1
2.9%
326905660 1
2.9%
323517430 1
2.9%
305926570 1
2.9%

Interactions

2023-12-11T01:21:42.302846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:40.877129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:41.318336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:41.835388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:42.385172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:40.956671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:41.435915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:41.938822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:42.485707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:41.075719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:41.553881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:42.086746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:42.576988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:41.198528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:41.677538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:42.206378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:21:46.580957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.1170.0000.4560.322
체납액구간0.0001.0000.0000.6360.0000.000
체납건수0.1170.0001.0000.9370.8980.917
체납금액0.0000.6360.9371.0000.7760.939
누적체납건수0.4560.0000.8980.7761.0000.807
누적체납금액0.3220.0000.9170.9390.8071.000
2023-12-11T01:21:46.723540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명
체납액구간1.0000.000
세목명0.0001.000
2023-12-11T01:21:46.842267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.4720.9710.6030.0000.000
체납금액0.4721.0000.3190.9430.0000.239
누적체납건수0.9710.3191.0000.4980.3160.000
누적체납금액0.6030.9430.4981.0000.1360.000
세목명0.0000.0000.3160.1361.0000.000
체납액구간0.0000.2390.0000.0000.0001.000

Missing values

2023-12-11T01:21:42.747939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:21:43.242021image/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

시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
0부산광역시금정구264102021등록면허세10만원 미만76425745670192364954840
1부산광역시금정구264102021자동차세10만원 미만2092803191409426391795190
2부산광역시금정구264102021자동차세10만원~30만원미만164328108206087481450475380
3부산광역시금정구264102021자동차세30만원~50만원미만9132212800319111989610
4부산광역시금정구264102021자동차세50만원~1백만원미만31551570189945150
5부산광역시금정구264102021재산세10만원 미만36771584680108761326905660
6부산광역시금정구264102021재산세10만원~30만원미만13422112614002289357658970
7부산광역시금정구264102021재산세1백만원~3백만원미만569621748085138768710
8부산광역시금정구264102021재산세1천만원~3천만원미만114663770114663770
9부산광역시금정구264102021재산세30만원~50만원미만19976146150304115198290
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
25부산광역시금정구264102021지방소득세5백만원~1천만원미만4229018715045305926570
26부산광역시금정구264102021지방소득세5천만원~1억원미만53460906905346090690
27부산광역시금정구264102021지역자원시설세10만원 미만4983602067963380
28부산광역시금정구264102021취득세10만원 미만3816958701295183100
29부산광역시금정구264102021취득세10만원~30만원미만112184750295244280
30부산광역시금정구264102021취득세1백만원~3백만원미만3441758079068710
31부산광역시금정구264102021취득세30만원~50만원미만4167629093433630
32부산광역시금정구264102021취득세50만원~1백만원미만42860100127765380
33부산광역시금정구264102021취득세5백만원~1천만원미만1647979016479790
34부산광역시금정구264102021취득세5천만원~1억원미만150560200150560200