Overview

Dataset statistics

Number of variables11
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory97.1 B

Variable types

Categorical7
Numeric4

Dataset

Description지방세 체납현황에 대한 데이터로 체납액 금액구간, 체납건수, 체납금액, 누적체납건수, 누적체납금액 등의 항목을 제공합니다.
Author경상북도 안동시
URLhttps://www.data.go.kr/data/15079512/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
데이터 기준일 has constant value ""Constant
체납건수 is highly overall correlated with 누적체납건수High correlation
체납금액 is highly overall correlated with 누적체납금액High correlation
누적체납건수 is highly overall correlated with 체납건수High correlation
누적체납금액 is highly overall correlated with 체납금액High correlation
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:30:44.229788
Analysis finished2024-04-06 08:30:49.097796
Duration4.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
경상북도
42 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 42
100.0%

Length

2024-04-06T17:30:49.206424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:30:49.459956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 42
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
안동시
42 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안동시 42
100.0%

Length

2024-04-06T17:30:49.649568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:30:49.841822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안동시 42
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
47170
42 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47170
2nd row47170
3rd row47170
4th row47170
5th row47170

Common Values

ValueCountFrequency (%)
47170 42
100.0%

Length

2024-04-06T17:30:50.039294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:30:50.615825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47170 42
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
2022
42 

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 42
100.0%

Length

2024-04-06T17:30:50.802968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:30:51.010828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 42
100.0%

세목명
Categorical

Distinct7
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size468.0 B
취득세
11 
재산세
9 
지방소득세
8 
주민세
5 
자동차세
4 
Other values (2)
5 

Length

Max length7
Median length3
Mean length3.8571429
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 11
26.2%
재산세 9
21.4%
지방소득세 8
19.0%
주민세 5
11.9%
자동차세 4
 
9.5%
지역자원시설세 3
 
7.1%
등록면허세 2
 
4.8%

Length

2024-04-06T17:30:51.230197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:30:51.520746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취득세 11
26.2%
재산세 9
21.4%
지방소득세 8
19.0%
주민세 5
11.9%
자동차세 4
 
9.5%
지역자원시설세 3
 
7.1%
등록면허세 2
 
4.8%

체납액구간
Categorical

Distinct11
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size468.0 B
10만원 미만
7 
10만원~30만원미만
7 
30만원~50만원미만
6 
50만원~1백만원미만
5 
1백만원~3백만원미만
4 
Other values (6)
13 

Length

Max length11
Median length11
Mean length10.238095
Min length7

Unique

Unique2 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 7
16.7%
10만원~30만원미만 7
16.7%
30만원~50만원미만 6
14.3%
50만원~1백만원미만 5
11.9%
1백만원~3백만원미만 4
9.5%
1천만원~3천만원미만 3
7.1%
3백만원~5백만원미만 3
7.1%
5백만원~1천만원미만 3
7.1%
5천만원~1억원미만 2
 
4.8%
1억원~3억원미만 1
 
2.4%

Length

2024-04-06T17:30:51.783548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 7
14.3%
미만 7
14.3%
10만원~30만원미만 7
14.3%
30만원~50만원미만 6
12.2%
50만원~1백만원미만 5
10.2%
1백만원~3백만원미만 4
8.2%
1천만원~3천만원미만 3
6.1%
3백만원~5백만원미만 3
6.1%
5백만원~1천만원미만 3
6.1%
5천만원~1억원미만 2
 
4.1%
Other values (2) 2
 
4.1%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean448.95238
Minimum1
Maximum6495
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-04-06T17:30:52.026311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.25
median16.5
Q3100.5
95-th percentile1993.85
Maximum6495
Range6494
Interquartile range (IQR)97.25

Descriptive statistics

Standard deviation1343.4418
Coefficient of variation (CV)2.9923927
Kurtosis14.836697
Mean448.95238
Median Absolute Deviation (MAD)15
Skewness3.8630808
Sum18856
Variance1804835.9
MonotonicityNot monotonic
2024-04-06T17:30:52.291093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 6
 
14.3%
2 3
 
7.1%
16 3
 
7.1%
24 2
 
4.8%
4 2
 
4.8%
17 2
 
4.8%
70 2
 
4.8%
3 2
 
4.8%
177 1
 
2.4%
429 1
 
2.4%
Other values (18) 18
42.9%
ValueCountFrequency (%)
1 6
14.3%
2 3
7.1%
3 2
 
4.8%
4 2
 
4.8%
6 1
 
2.4%
10 1
 
2.4%
11 1
 
2.4%
12 1
 
2.4%
15 1
 
2.4%
16 3
7.1%
ValueCountFrequency (%)
6495 1
2.4%
5663 1
2.4%
2012 1
2.4%
1649 1
2.4%
843 1
2.4%
665 1
2.4%
429 1
2.4%
177 1
2.4%
152 1
2.4%
120 1
2.4%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59700123
Minimum109740
Maximum2.8393784 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-04-06T17:30:52.606062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum109740
5-th percentile568780
Q15154485
median35685140
Q31.0685782 × 108
95-th percentile1.6832272 × 108
Maximum2.8393784 × 108
Range2.838281 × 108
Interquartile range (IQR)1.0170334 × 108

Descriptive statistics

Standard deviation64620784
Coefficient of variation (CV)1.082423
Kurtosis1.9849459
Mean59700123
Median Absolute Deviation (MAD)34320875
Skewness1.3368313
Sum2.5074052 × 109
Variance4.1758458 × 1015
MonotonicityNot monotonic
2024-04-06T17:30:52.860871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
10775470 1
 
2.4%
5007740 1
 
2.4%
27078500 1
 
2.4%
62036360 1
 
2.4%
47313820 1
 
2.4%
109691230 1
 
2.4%
109740 1
 
2.4%
666480 1
 
2.4%
377210 1
 
2.4%
880540 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
109740 1
2.4%
377210 1
2.4%
563750 1
2.4%
664350 1
2.4%
666480 1
2.4%
880540 1
2.4%
1847990 1
2.4%
2458220 1
2.4%
4185870 1
2.4%
4387240 1
2.4%
ValueCountFrequency (%)
283937840 1
2.4%
177717580 1
2.4%
169524410 1
2.4%
145490570 1
2.4%
140981980 1
2.4%
133858770 1
2.4%
129777790 1
2.4%
126945060 1
2.4%
110435310 1
2.4%
109691230 1
2.4%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1457
Minimum1
Maximum16518
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-04-06T17:30:53.103291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.05
Q116.5
median60.5
Q3276.25
95-th percentile11310.35
Maximum16518
Range16517
Interquartile range (IQR)259.75

Descriptive statistics

Standard deviation3961.2317
Coefficient of variation (CV)2.7187589
Kurtosis7.7898946
Mean1457
Median Absolute Deviation (MAD)53
Skewness2.9815324
Sum61194
Variance15691357
MonotonicityNot monotonic
2024-04-06T17:30:53.464417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
71 2
 
4.8%
3 2
 
4.8%
1 2
 
4.8%
1843 1
 
2.4%
480 1
 
2.4%
44 1
 
2.4%
142 1
 
2.4%
268 1
 
2.4%
24 1
 
2.4%
16 1
 
2.4%
Other values (29) 29
69.0%
ValueCountFrequency (%)
1 2
4.8%
2 1
2.4%
3 2
4.8%
5 1
2.4%
10 1
2.4%
12 1
2.4%
13 1
2.4%
14 1
2.4%
16 1
2.4%
18 1
2.4%
ValueCountFrequency (%)
16518 1
2.4%
14313 1
2.4%
11336 1
2.4%
10823 1
2.4%
1906 1
2.4%
1843 1
2.4%
1109 1
2.4%
480 1
2.4%
426 1
2.4%
366 1
2.4%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.990063 × 108
Minimum377210
Maximum1.871477 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-04-06T17:30:54.241523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum377210
5-th percentile2176189
Q124764298
median97993355
Q32.6613139 × 108
95-th percentile4.8690786 × 108
Maximum1.871477 × 109
Range1.8710998 × 109
Interquartile range (IQR)2.413671 × 108

Descriptive statistics

Standard deviation3.1360084 × 108
Coefficient of variation (CV)1.5758337
Kurtosis19.92074
Mean1.990063 × 108
Median Absolute Deviation (MAD)89573445
Skewness3.970033
Sum8.3582647 × 109
Variance9.8345487 × 1016
MonotonicityNot monotonic
2024-04-06T17:30:54.678638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
30732910 1
 
2.4%
13983590 1
 
2.4%
55793810 1
 
2.4%
263202980 1
 
2.4%
188561920 1
 
2.4%
487515350 1
 
2.4%
567300 1
 
2.4%
2544200 1
 
2.4%
377210 1
 
2.4%
2808670 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
377210 1
2.4%
567300 1
2.4%
2156820 1
2.4%
2544200 1
2.4%
2808670 1
2.4%
6795500 1
2.4%
9415030 1
2.4%
13983590 1
2.4%
17133080 1
2.4%
19104120 1
2.4%
ValueCountFrequency (%)
1871477010 1
2.4%
707875800 1
2.4%
487515350 1
2.4%
475365540 1
2.4%
439885270 1
2.4%
433353000 1
2.4%
343614730 1
2.4%
325178030 1
2.4%
320996420 1
2.4%
292185540 1
2.4%

데이터 기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
2022-12-31
42 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-31
2nd row2022-12-31
3rd row2022-12-31
4th row2022-12-31
5th row2022-12-31

Common Values

ValueCountFrequency (%)
2022-12-31 42
100.0%

Length

2024-04-06T17:30:54.978558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:30:55.184840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-31 42
100.0%

Interactions

2024-04-06T17:30:47.793827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:45.101300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:46.014101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:46.872746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:48.031769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:45.335149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:46.209731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:47.043795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:48.206303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:45.597279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:46.388153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:47.241768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:48.375292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:45.794816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:46.550196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:30:47.494431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:30:55.340006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.4150.3810.5090.450
체납액구간0.0001.0000.0000.0000.0000.000
체납건수0.4150.0001.0000.7021.0000.660
체납금액0.3810.0000.7021.0000.5560.915
누적체납건수0.5090.0001.0000.5561.0000.717
누적체납금액0.4500.0000.6600.9150.7171.000
2024-04-06T17:30:55.614404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간
세목명1.0000.000
체납액구간0.0001.000
2024-04-06T17:30:55.788390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.3970.9630.4350.2520.000
체납금액0.3971.0000.3440.9390.2190.000
누적체납건수0.9630.3441.0000.4420.3430.000
누적체납금액0.4350.9390.4421.0000.3040.000
세목명0.2520.2190.3430.3041.0000.000
체납액구간0.0000.0000.0000.0000.0001.000

Missing values

2024-04-06T17:30:48.666164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:30:48.981091image/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

시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액데이터 기준일
0경상북도안동시471702022등록면허세10만원 미만665107754701843307329102022-12-31
1경상북도안동시471702022등록면허세10만원~30만원미만46643501221568202022-12-31
2경상북도안동시471702022자동차세10만원 미만201282516120108234753655402022-12-31
3경상북도안동시471702022자동차세10만원~30만원미만16492839378401133618714770102022-12-31
4경상북도안동시471702022자동차세30만원~50만원미만104360472304261485706802022-12-31
5경상북도안동시471702022자동차세50만원~1백만원미만156375032191041202022-12-31
6경상북도안동시471702022재산세10만원 미만6495133858770165183436147302022-12-31
7경상북도안동시471702022재산세10만원~30만원미만84314098198019063209964202022-12-31
8경상북도안동시471702022재산세1백만원~3백만원미만901454905702794398852702022-12-31
9경상북도안동시471702022재산세1천만원~3천만원미만6129777790132316468502022-12-31
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액데이터 기준일
32경상북도안동시471702022취득세10만원~30만원미만24500774073139835902022-12-31
33경상북도안동시471702022취득세1백만원~3백만원미만284845951056959056802022-12-31
34경상북도안동시471702022취득세1억원~3억원미만110469742011046974202022-12-31
35경상북도안동시471702022취득세1천만원~3천만원미만1279254605873070902022-12-31
36경상북도안동시471702022취득세30만원~50만원미만1143872401867955002022-12-31
37경상북도안동시471702022취득세3백만원~5백만원미만41600849014516028402022-12-31
38경상북도안동시471702022취득세3천만원~5천만원미만13532305031251230902022-12-31
39경상북도안동시471702022취득세50만원~1백만원미만171288891036265405002022-12-31
40경상북도안동시471702022취득세5백만원~1천만원미만21550406010709161702022-12-31
41경상북도안동시471702022취득세5천만원~1억원미만216952441021695244102022-12-31