Overview

Dataset statistics

Number of variables10
Number of observations38
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory89.5 B

Variable types

Categorical6
Numeric4

Dataset

Description부산광역시 연제구 지방세 체납 현황에 대한 데이터로 체납 건수, 체납 금액, 누적 체납 금액 등 항목의 데이터를 제공합니다.
Author부산광역시 연제구
URLhttps://www.data.go.kr/data/15079357/fileData.do

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 체납건수 and 1 other fieldsHigh correlation
누적체납금액 is highly overall correlated with 체납건수 and 2 other fieldsHigh correlation
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:45:58.482360
Analysis finished2023-12-12 06:46:00.365402
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
부산광역시
38 

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 38
100.0%

Length

2023-12-12T15:46:00.728647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:46:00.810908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 38
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
연제구
38 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연제구 38
100.0%

Length

2023-12-12T15:46:00.896333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:46:00.975285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
연제구 38
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
26470
38 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26470
2nd row26470
3rd row26470
4th row26470
5th row26470

Common Values

ValueCountFrequency (%)
26470 38
100.0%

Length

2023-12-12T15:46:01.073490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:46:01.156562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26470 38
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
2022
38 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 38
100.0%

Length

2023-12-12T15:46:01.242535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:46:01.327400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 38
100.0%

세목명
Categorical

Distinct7
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Memory size436.0 B
취득세
11 
지방소득세
9 
재산세
8 
자동차세
4 
주민세
3 
Other values (2)
3 

Length

Max length7
Median length3
Mean length3.8421053
Min length3

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 11
28.9%
지방소득세 9
23.7%
재산세 8
21.1%
자동차세 4
 
10.5%
주민세 3
 
7.9%
지역자원시설세 2
 
5.3%
등록면허세 1
 
2.6%

Length

2023-12-12T15:46:01.416209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:46:01.519937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취득세 11
28.9%
지방소득세 9
23.7%
재산세 8
21.1%
자동차세 4
 
10.5%
주민세 3
 
7.9%
지역자원시설세 2
 
5.3%
등록면허세 1
 
2.6%

체납액구간
Categorical

Distinct11
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
10만원 미만
7 
10만원~30만원미만
6 
30만원~50만원미만
5 
50만원~1백만원미만
4 
1백만원~3백만원미만
3 
Other values (6)
13 

Length

Max length11
Median length11
Mean length10.184211
Min length7

Unique

Unique2 ?
Unique (%)5.3%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 7
18.4%
10만원~30만원미만 6
15.8%
30만원~50만원미만 5
13.2%
50만원~1백만원미만 4
10.5%
1백만원~3백만원미만 3
7.9%
1천만원~3천만원미만 3
7.9%
3백만원~5백만원미만 3
7.9%
5백만원~1천만원미만 3
7.9%
3천만원~5천만원미만 2
 
5.3%
3억원~5억원미만 1
 
2.6%

Length

2023-12-12T15:46:01.632575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 7
15.6%
미만 7
15.6%
10만원~30만원미만 6
13.3%
30만원~50만원미만 5
11.1%
50만원~1백만원미만 4
8.9%
1백만원~3백만원미만 3
6.7%
1천만원~3천만원미만 3
6.7%
3백만원~5백만원미만 3
6.7%
5백만원~1천만원미만 3
6.7%
3천만원~5천만원미만 2
 
4.4%
Other values (2) 2
 
4.4%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)68.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean519.86842
Minimum1
Maximum8745
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T15:46:01.740694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median13.5
Q391.5
95-th percentile2085.95
Maximum8745
Range8744
Interquartile range (IQR)88.5

Descriptive statistics

Standard deviation1532.1852
Coefficient of variation (CV)2.9472557
Kurtosis23.484255
Mean519.86842
Median Absolute Deviation (MAD)12.5
Skewness4.579689
Sum19755
Variance2347591.4
MonotonicityNot monotonic
2023-12-12T15:46:01.840883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 4
 
10.5%
3 4
 
10.5%
2 4
 
10.5%
5 2
 
5.3%
16 2
 
5.3%
6 2
 
5.3%
760 1
 
2.6%
830 1
 
2.6%
7 1
 
2.6%
13 1
 
2.6%
Other values (16) 16
42.1%
ValueCountFrequency (%)
1 4
10.5%
2 4
10.5%
3 4
10.5%
5 2
5.3%
6 2
5.3%
7 1
 
2.6%
9 1
 
2.6%
13 1
 
2.6%
14 1
 
2.6%
16 2
5.3%
ValueCountFrequency (%)
8745 1
2.6%
3185 1
2.6%
1892 1
2.6%
1823 1
2.6%
1485 1
2.6%
830 1
2.6%
760 1
2.6%
237 1
2.6%
213 1
2.6%
92 1
2.6%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72368844
Minimum236690
Maximum3.4687653 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T15:46:01.963607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum236690
5-th percentile410935
Q18626562.5
median39115165
Q388242718
95-th percentile2.6040256 × 108
Maximum3.4687653 × 108
Range3.4663984 × 108
Interquartile range (IQR)79616155

Descriptive statistics

Standard deviation90458341
Coefficient of variation (CV)1.2499625
Kurtosis2.311267
Mean72368844
Median Absolute Deviation (MAD)37792665
Skewness1.7242055
Sum2.7500161 × 109
Variance8.1827114 × 1015
MonotonicityNot monotonic
2023-12-12T15:46:02.085972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
26822170 1
 
2.6%
12221410 1
 
2.6%
84843410 1
 
2.6%
48065770 1
 
2.6%
112908470 1
 
2.6%
236690 1
 
2.6%
422560 1
 
2.6%
345060 1
 
2.6%
600940 1
 
2.6%
11676490 1
 
2.6%
Other values (28) 28
73.7%
ValueCountFrequency (%)
236690 1
2.6%
345060 1
2.6%
422560 1
2.6%
600940 1
2.6%
1104270 1
2.6%
1540730 1
2.6%
1924150 1
2.6%
2560060 1
2.6%
5475830 1
2.6%
7609920 1
2.6%
ValueCountFrequency (%)
346876530 1
2.6%
311316180 1
2.6%
251417800 1
2.6%
248358800 1
2.6%
218323380 1
2.6%
149302800 1
2.6%
132158240 1
2.6%
112908470 1
2.6%
90056040 1
2.6%
89375820 1
2.6%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1674.6316
Minimum1
Maximum30823
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T15:46:02.205494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q19.25
median29
Q3292
95-th percentile7742.35
Maximum30823
Range30822
Interquartile range (IQR)282.75

Descriptive statistics

Standard deviation5305.748
Coefficient of variation (CV)3.1683076
Kurtosis25.877277
Mean1674.6316
Median Absolute Deviation (MAD)28
Skewness4.8374018
Sum63636
Variance28150962
MonotonicityNot monotonic
2023-12-12T15:46:02.326117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 4
 
10.5%
29 2
 
5.3%
2 2
 
5.3%
11 2
 
5.3%
1947 1
 
2.6%
22 1
 
2.6%
201 1
 
2.6%
35 1
 
2.6%
253 1
 
2.6%
64 1
 
2.6%
Other values (22) 22
57.9%
ValueCountFrequency (%)
1 4
10.5%
2 2
5.3%
5 1
 
2.6%
6 1
 
2.6%
8 1
 
2.6%
9 1
 
2.6%
10 1
 
2.6%
11 2
5.3%
12 1
 
2.6%
17 1
 
2.6%
ValueCountFrequency (%)
30823 1
2.6%
8515 1
2.6%
7606 1
2.6%
7088 1
2.6%
2690 1
2.6%
2365 1
2.6%
1947 1
2.6%
694 1
2.6%
347 1
2.6%
305 1
2.6%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5432336 × 108
Minimum332600
Maximum1.2772029 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T15:46:02.482406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum332600
5-th percentile1938926
Q117570435
median80240390
Q31.4860978 × 108
95-th percentile4.7274995 × 108
Maximum1.2772029 × 109
Range1.2768703 × 109
Interquartile range (IQR)1.3103934 × 108

Descriptive statistics

Standard deviation2.3780815 × 108
Coefficient of variation (CV)1.5409731
Kurtosis13.382231
Mean1.5432336 × 108
Median Absolute Deviation (MAD)66360615
Skewness3.2958552
Sum5.8642878 × 109
Variance5.6552717 × 1016
MonotonicityNot monotonic
2023-12-12T15:46:02.693356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
68836340 1
 
2.6%
21390200 1
 
2.6%
84843410 1
 
2.6%
174886870 1
 
2.6%
146923250 1
 
2.6%
332600 1
 
2.6%
422560 1
 
2.6%
2206520 1
 
2.6%
5340720 1
 
2.6%
11676490 1
 
2.6%
Other values (28) 28
73.7%
ValueCountFrequency (%)
332600 1
2.6%
422560 1
2.6%
2206520 1
2.6%
3514540 1
2.6%
3834450 1
2.6%
5340720 1
2.6%
11676490 1
2.6%
13809280 1
2.6%
13950270 1
2.6%
16297180 1
2.6%
ValueCountFrequency (%)
1277202870 1
2.6%
661960930 1
2.6%
439359780 1
2.6%
360223060 1
2.6%
352547690 1
2.6%
346876530 1
2.6%
306289000 1
2.6%
264095670 1
2.6%
174886870 1
2.6%
149171950 1
2.6%

Interactions

2023-12-12T15:45:59.732275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:58.748678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:59.041302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:59.399311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:59.811539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:58.815568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:59.136870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:59.471948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:59.917459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:58.890708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:59.231015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:59.571964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:00.015511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:58.959904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:59.309931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:45:59.652124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:46:02.891741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.4700.2610.5460.171
체납액구간0.0001.0000.0000.3960.0000.000
체납건수0.4700.0001.0000.9201.0000.876
체납금액0.2610.3960.9201.0000.9930.928
누적체납건수0.5460.0001.0000.9931.0000.988
누적체납금액0.1710.0000.8760.9280.9881.000
2023-12-12T15:46:03.038806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간
세목명1.0000.000
체납액구간0.0001.000
2023-12-12T15:46:03.133624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.3850.9580.5840.3080.000
체납금액0.3851.0000.2700.9400.1500.169
누적체납건수0.9580.2701.0000.5100.4040.000
누적체납금액0.5840.9400.5101.0000.1120.000
세목명0.3080.1500.4040.1121.0000.000
체납액구간0.0000.1690.0000.0000.0001.000

Missing values

2023-12-12T15:46:00.193455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:46:00.318151image/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
0부산광역시연제구264702022등록면허세10만원 미만76026822170194768836340
1부산광역시연제구264702022자동차세10만원 미만1892808121608515360223060
2부산광역시연제구264702022자동차세10만원~30만원미만182331131618076061277202870
3부산광역시연제구264702022자동차세30만원~50만원미만9232309930305105029640
4부산광역시연제구264702022자동차세50만원~1백만원미만315407302916297180
5부산광역시연제구264702022재산세10만원 미만31851493028007088306289000
6부산광역시연제구264702022재산세10만원~30만원미만14852483588002690439359780
7부산광역시연제구264702022재산세1백만원~3백만원미만478063443085149171950
8부산광역시연제구264702022재산세1천만원~3천만원미만5780650808115397850
9부산광역시연제구264702022재산세30만원~50만원미만23789375820347129398020
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
28부산광역시연제구264702022취득세10만원~30만원미만3600940295340720
29부산광역시연제구264702022취득세1백만원~3백만원미만5122214101121390200
30부산광역시연제구264702022취득세1천만원~3천만원미만111676490111676490
31부산광역시연제구264702022취득세30만원~50만원미만31104270103514540
32부산광역시연제구264702022취득세3백만원~5백만원미만27609920622576330
33부산광역시연제구264702022취득세3억원~5억원미만13468765301346876530
34부산광역시연제구264702022취득세3천만원~5천만원미만145378540145378540
35부산광역시연제구264702022취득세50만원~1백만원미만319241502113809280
36부산광역시연제구264702022취득세5백만원~1천만원미만213835290531134650
37부산광역시연제구264702022취득세5천만원~1억원미만190056040190056040