Overview

Dataset statistics

Number of variables11
Number of observations138
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.8 KiB
Average record size in memory95.0 B

Variable types

Categorical7
Numeric4

Dataset

Description경기도 용인시 처인구, 기흥구, 수지구 지방세 체납액 규모별 체납 건수 현황입니다. 체납건수, 체납금액, 누적체납금액 등의 데이터를 제공합니다. ※ 데이터기준일자 : 2021-12-31
Author공공데이터포털
URLhttps://www.data.go.kr/data/15078583/fileData.do

Alerts

시도명 has constant value ""Constant
과세년도 has constant value ""Constant
데이터기준일자 has constant value ""Constant
시군구명 is highly overall correlated with 자치단체코드High correlation
자치단체코드 is highly overall correlated with 시군구명High correlation
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

Reproduction

Analysis started2024-04-17 11:48:46.639807
Analysis finished2024-04-17 11:48:48.512199
Duration1.87 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
경기도
138 

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 138
100.0%

Length

2024-04-17T20:48:48.568463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:48:48.653544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 138
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
용인시 처인구
51 
용인시 기흥구
45 
용인시 수지구
42 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용인시 처인구
2nd row용인시 기흥구
3rd row용인시 수지구
4th row용인시 처인구
5th row용인시 기흥구

Common Values

ValueCountFrequency (%)
용인시 처인구 51
37.0%
용인시 기흥구 45
32.6%
용인시 수지구 42
30.4%

Length

2024-04-17T20:48:48.737687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:48:48.840158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용인시 138
50.0%
처인구 51
 
18.5%
기흥구 45
 
16.3%
수지구 42
 
15.2%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
41461
51 
41463
45 
41465
42 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41461
2nd row41463
3rd row41465
4th row41461
5th row41463

Common Values

ValueCountFrequency (%)
41461 51
37.0%
41463 45
32.6%
41465 42
30.4%

Length

2024-04-17T20:48:48.930740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:48:49.013312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41461 51
37.0%
41463 45
32.6%
41465 42
30.4%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2021
138 

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 138
100.0%

Length

2024-04-17T20:48:49.110074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:48:49.189509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 138
100.0%

세목명
Categorical

Distinct7
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
지방소득세
34 
재산세
33 
취득세
31 
주민세
16 
자동차세
12 
Other values (2)
12 

Length

Max length7
Median length3
Mean length3.8115942
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 34
24.6%
재산세 33
23.9%
취득세 31
22.5%
주민세 16
11.6%
자동차세 12
 
8.7%
등록면허세 8
 
5.8%
지역자원시설세 4
 
2.9%

Length

2024-04-17T20:48:49.284860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:48:49.390851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 34
24.6%
재산세 33
23.9%
취득세 31
22.5%
주민세 16
11.6%
자동차세 12
 
8.7%
등록면허세 8
 
5.8%
지역자원시설세 4
 
2.9%

체납액구간
Categorical

Distinct14
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
10만원 미만
21 
10만원~30만원미만
18 
50만원~1백만원미만
16 
30만원~50만원미만
15 
1백만원~3백만원미만
12 
Other values (9)
56 

Length

Max length11
Median length11
Mean length10.188406
Min length6

Unique

Unique2 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 21
15.2%
10만원~30만원미만 18
13.0%
50만원~1백만원미만 16
11.6%
30만원~50만원미만 15
10.9%
1백만원~3백만원미만 12
8.7%
5백만원~1천만원미만 11
8.0%
3백만원~5백만원미만 10
7.2%
1천만원~3천만원미만 9
6.5%
3천만원~5천만원미만 9
6.5%
5천만원~1억원미만 8
 
5.8%
Other values (4) 9
6.5%

Length

2024-04-17T20:48:49.504858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 21
13.2%
미만 21
13.2%
10만원~30만원미만 18
11.3%
50만원~1백만원미만 16
10.1%
30만원~50만원미만 15
9.4%
1백만원~3백만원미만 12
7.5%
5백만원~1천만원미만 11
6.9%
3백만원~5백만원미만 10
6.3%
1천만원~3천만원미만 9
5.7%
3천만원~5천만원미만 9
5.7%
Other values (5) 17
10.7%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct86
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean678.32609
Minimum1
Maximum13656
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-17T20:48:49.608654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median22.5
Q3220
95-th percentile4083.8
Maximum13656
Range13655
Interquartile range (IQR)216

Descriptive statistics

Standard deviation2011.3744
Coefficient of variation (CV)2.9652029
Kurtosis25.356675
Mean678.32609
Median Absolute Deviation (MAD)21.5
Skewness4.723013
Sum93609
Variance4045627.2
MonotonicityNot monotonic
2024-04-17T20:48:49.731423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 17
 
12.3%
3 10
 
7.2%
2 7
 
5.1%
4 6
 
4.3%
7 5
 
3.6%
8 4
 
2.9%
26 3
 
2.2%
6 2
 
1.4%
28 2
 
1.4%
12 2
 
1.4%
Other values (76) 80
58.0%
ValueCountFrequency (%)
1 17
12.3%
2 7
5.1%
3 10
7.2%
4 6
 
4.3%
5 2
 
1.4%
6 2
 
1.4%
7 5
 
3.6%
8 4
 
2.9%
9 1
 
0.7%
10 1
 
0.7%
ValueCountFrequency (%)
13656 1
0.7%
13536 1
0.7%
7777 1
0.7%
7088 1
0.7%
5109 1
0.7%
4883 1
0.7%
4145 1
0.7%
4073 1
0.7%
3046 1
0.7%
2912 1
0.7%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct138
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0638013 × 108
Minimum14210
Maximum2.2654728 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-17T20:48:49.853085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14210
5-th percentile459642
Q114286962
median1.0243981 × 108
Q32.9273462 × 108
95-th percentile6.7826914 × 108
Maximum2.2654728 × 109
Range2.2654585 × 109
Interquartile range (IQR)2.7844766 × 108

Descriptive statistics

Standard deviation3.0513194 × 108
Coefficient of variation (CV)1.4784948
Kurtosis20.081505
Mean2.0638013 × 108
Median Absolute Deviation (MAD)99687835
Skewness3.7671481
Sum2.8480458 × 1010
Variance9.3105503 × 1016
MonotonicityNot monotonic
2024-04-17T20:48:49.978181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27301630 1
 
0.7%
151490080 1
 
0.7%
171863560 1
 
0.7%
916832090 1
 
0.7%
317625040 1
 
0.7%
486493150 1
 
0.7%
606842820 1
 
0.7%
151109110 1
 
0.7%
100012230 1
 
0.7%
14210 1
 
0.7%
Other values (128) 128
92.8%
ValueCountFrequency (%)
14210 1
0.7%
49160 1
0.7%
112470 1
0.7%
114760 1
0.7%
141180 1
0.7%
203940 1
0.7%
299570 1
0.7%
487890 1
0.7%
734030 1
0.7%
991590 1
0.7%
ValueCountFrequency (%)
2265472750 1
0.7%
1849614050 1
0.7%
931894220 1
0.7%
916832090 1
0.7%
788224740 1
0.7%
725183530 1
0.7%
723458580 1
0.7%
670294530 1
0.7%
636047790 1
0.7%
606842820 1
0.7%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5551.5
Minimum1
Maximum85565
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-17T20:48:50.092669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q150
median193.5
Q31600
95-th percentile35538
Maximum85565
Range85564
Interquartile range (IQR)1550

Descriptive statistics

Standard deviation14954.536
Coefficient of variation (CV)2.693783
Kurtosis16.662207
Mean5551.5
Median Absolute Deviation (MAD)178
Skewness3.8697576
Sum766107
Variance2.2363815 × 108
MonotonicityNot monotonic
2024-04-17T20:48:50.203820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
131 6
 
4.3%
3 5
 
3.6%
1 4
 
2.9%
9221 3
 
2.2%
33 3
 
2.2%
1600 3
 
2.2%
26 3
 
2.2%
237 3
 
2.2%
1252 3
 
2.2%
366 3
 
2.2%
Other values (37) 102
73.9%
ValueCountFrequency (%)
1 4
2.9%
2 2
 
1.4%
3 5
3.6%
4 1
 
0.7%
5 1
 
0.7%
8 2
 
1.4%
11 3
2.2%
13 3
2.2%
18 1
 
0.7%
26 3
2.2%
ValueCountFrequency (%)
85565 3
2.2%
35985 3
2.2%
35538 3
2.2%
29787 3
2.2%
23238 3
2.2%
13657 3
2.2%
9221 3
2.2%
4255 3
2.2%
3931 3
2.2%
2523 3
2.2%

누적체납금액
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)39.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.230636 × 109
Minimum399670
Maximum6.0857565 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-17T20:48:50.319610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum399670
5-th percentile4982235.5
Q11.4149578 × 108
median8.1219948 × 108
Q31.7125983 × 109
95-th percentile4.1304463 × 109
Maximum6.0857565 × 109
Range6.0853568 × 109
Interquartile range (IQR)1.5711025 × 109

Descriptive statistics

Standard deviation1.3789578 × 109
Coefficient of variation (CV)1.1205245
Kurtosis2.512599
Mean1.230636 × 109
Median Absolute Deviation (MAD)7.3173493 × 108
Skewness1.6102768
Sum1.6982776 × 1011
Variance1.9015246 × 1018
MonotonicityNot monotonic
2024-04-17T20:48:50.439939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
248884620 3
 
2.2%
3973691020 3
 
2.2%
169476110 3
 
2.2%
47652580 3
 
2.2%
27624120 3
 
2.2%
123638590 3
 
2.2%
393165160 3
 
2.2%
764082790 3
 
2.2%
2710383970 3
 
2.2%
4246854410 3
 
2.2%
Other values (45) 108
78.3%
ValueCountFrequency (%)
399670 1
 
0.7%
549060 2
1.4%
991590 1
 
0.7%
1294740 3
2.2%
5632970 1
 
0.7%
6612870 1
 
0.7%
9431900 3
2.2%
24932120 1
 
0.7%
27624120 3
2.2%
40141730 3
2.2%
ValueCountFrequency (%)
6085756470 3
2.2%
5120399100 1
 
0.7%
4246854410 3
2.2%
4109903720 3
2.2%
3973691020 3
2.2%
2710383970 3
2.2%
2646194260 3
2.2%
2353844600 3
2.2%
2229380240 3
2.2%
2131434280 3
2.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2021-12-31
138 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-12-31
2nd row2021-12-31
3rd row2021-12-31
4th row2021-12-31
5th row2021-12-31

Common Values

ValueCountFrequency (%)
2021-12-31 138
100.0%

Length

2024-04-17T20:48:50.564826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:48:50.649589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-12-31 138
100.0%

Interactions

2024-04-17T20:48:47.984599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:46.946525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:47.452093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:47.720451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:48.070996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:47.016858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:47.526642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:47.792420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:48.147857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:47.315394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:47.591895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:47.857326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:48.223122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:47.378208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:47.652634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:48:47.917650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T20:48:50.701663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드세목명체납액구간체납건수체납금액누적체납건수누적체납금액
시군구명1.0001.0000.0000.0000.0000.0000.0000.000
자치단체코드1.0001.0000.0000.0000.0000.0000.0000.000
세목명0.0000.0001.0000.0000.3080.3900.5840.561
체납액구간0.0000.0000.0001.0000.0000.8530.5080.784
체납건수0.0000.0000.3080.0001.0000.3680.9310.417
체납금액0.0000.0000.3900.8530.3681.0000.2220.771
누적체납건수0.0000.0000.5840.5080.9310.2221.0000.673
누적체납금액0.0000.0000.5610.7840.4170.7710.6731.000
2024-04-17T20:48:50.795138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간시군구명자치단체코드세목명
체납액구간1.0000.0000.0000.000
시군구명0.0001.0001.0000.000
자치단체코드0.0001.0001.0000.000
세목명0.0000.0000.0001.000
2024-04-17T20:48:50.890308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액시군구명자치단체코드세목명체납액구간
체납건수1.0000.3750.9480.4440.0000.0000.1870.000
체납금액0.3751.0000.2310.9200.0000.0000.1460.483
누적체납건수0.9480.2311.0000.3710.0000.0000.3960.269
누적체납금액0.4440.9200.3711.0000.0000.0000.3430.483
시군구명0.0000.0000.0000.0001.0001.0000.0000.000
자치단체코드0.0000.0000.0000.0001.0001.0000.0000.000
세목명0.1870.1460.3960.3430.0000.0001.0000.000
체납액구간0.0000.4830.2690.4830.0000.0000.0001.000

Missing values

2024-04-17T20:48:48.337276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T20:48:48.464040image/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

시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액데이터기준일자
0경기도용인시 처인구414612021등록면허세10만원 미만14992730163092212488846202021-12-31
1경기도용인시 기흥구414632021등록면허세10만원 미만11284085958092212488846202021-12-31
2경기도용인시 수지구414652021등록면허세10만원 미만5191897944092212488846202021-12-31
3경기도용인시 처인구414612021등록면허세10만원~30만원미만120394035490602021-12-31
4경기도용인시 기흥구414632021등록면허세10만원~30만원미만114118035490602021-12-31
5경기도용인시 처인구414612021등록면허세1백만원~3백만원미만12810140256329702021-12-31
6경기도용인시 처인구414612021등록면허세50만원~1백만원미만199159019915902021-12-31
7경기도용인시 처인구414612021등록면허세5백만원~1천만원미만16612870166128702021-12-31
8경기도용인시 처인구414612021자동차세10만원 미만48832169812303553816362192402021-12-31
9경기도용인시 기흥구414632021자동차세10만원 미만30461426492303553816362192402021-12-31
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액데이터기준일자
128경기도용인시 수지구414652021취득세3천만원~5천만원미만130263470114434493402021-12-31
129경기도용인시 처인구414612021취득세50만원~1백만원미만15106918201521096096202021-12-31
130경기도용인시 기흥구414632021취득세50만원~1백만원미만431465601521096096202021-12-31
131경기도용인시 수지구414652021취득세50만원~1백만원미만321836801521096096202021-12-31
132경기도용인시 처인구414612021취득세5백만원~1천만원미만7454408601078133959902021-12-31
133경기도용인시 기흥구414632021취득세5백만원~1천만원미만9701224201078133959902021-12-31
134경기도용인시 수지구414652021취득세5백만원~1천만원미만3208045201078133959902021-12-31
135경기도용인시 수지구414652021취득세5억원~10억원미만159067542015906754202021-12-31
136경기도용인시 처인구414612021취득세5천만원~1억원미만18521235085038091702021-12-31
137경기도용인시 기흥구414632021취득세5천만원~1억원미만318866052085038091702021-12-31