Overview

Dataset statistics

Number of variables10
Number of observations158
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.4 KiB
Average record size in memory86.8 B

Variable types

Categorical6
Numeric4

Dataset

Description대전광역시 중구의 지방세 체납액 구간을 7단계로 나누어 각 구간별로 지방세 체납액과 건수를 확인할 수 있고, 누적 체납건수와 체납금액도 비교해볼 수 있습니다.
URLhttps://www.data.go.kr/data/15078589/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
체납건수 is highly overall correlated with 체납금액 and 2 other fieldsHigh correlation
체납금액 is highly overall correlated with 체납건수 and 2 other fieldsHigh correlation
누적체납건수 is highly overall correlated with 체납건수 and 2 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 09:16:17.267931
Analysis finished2023-12-12 09:16:20.083570
Duration2.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
대전광역시
158 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전광역시 158
100.0%

Length

2023-12-12T18:16:20.171314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:16:20.308107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 158
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
중구
158 

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 158
100.0%

Length

2023-12-12T18:16:20.453049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:16:20.582519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 158
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
30140
158 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30140
2nd row30140
3rd row30140
4th row30140
5th row30140

Common Values

ValueCountFrequency (%)
30140 158
100.0%

Length

2023-12-12T18:16:20.704460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:16:20.813100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30140 158
100.0%

과세연도
Categorical

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2020
38 
2021
38 
2019
29 
2017
27 
2018
26 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2020 38
24.1%
2021 38
24.1%
2019 29
18.4%
2017 27
17.1%
2018 26
16.5%

Length

2023-12-12T18:16:20.937190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:16:21.083267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 38
24.1%
2021 38
24.1%
2019 29
18.4%
2017 27
17.1%
2018 26
16.5%

세목명
Categorical

Distinct7
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
재산세
39 
지방소득세
38 
취득세
25 
자동차세
20 
주민세
20 
Other values (2)
16 

Length

Max length7
Median length3
Mean length3.9367089
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 39
24.7%
지방소득세 38
24.1%
취득세 25
15.8%
자동차세 20
12.7%
주민세 20
12.7%
지역자원시설세 10
 
6.3%
등록면허세 6
 
3.8%

Length

2023-12-12T18:16:21.249894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:16:21.434825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 39
24.7%
지방소득세 38
24.1%
취득세 25
15.8%
자동차세 20
12.7%
주민세 20
12.7%
지역자원시설세 10
 
6.3%
등록면허세 6
 
3.8%

체납액구간
Categorical

Distinct12
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
10만원 미만
35 
10만원~30만원미만
29 
30만원~50만원미만
24 
50만원~1백만원미만
24 
1백만원~3백만원미만
14 
Other values (7)
32 

Length

Max length11
Median length11
Mean length10.06962
Min length7

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 35
22.2%
10만원~30만원미만 29
18.4%
30만원~50만원미만 24
15.2%
50만원~1백만원미만 24
15.2%
1백만원~3백만원미만 14
 
8.9%
3백만원~5백만원미만 9
 
5.7%
5백만원~1천만원미만 9
 
5.7%
1천만원~3천만원미만 7
 
4.4%
5천만원~1억원미만 3
 
1.9%
3천만원~5천만원미만 2
 
1.3%
Other values (2) 2
 
1.3%

Length

2023-12-12T18:16:21.661213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 35
18.1%
미만 35
18.1%
10만원~30만원미만 29
15.0%
30만원~50만원미만 24
12.4%
50만원~1백만원미만 24
12.4%
1백만원~3백만원미만 14
 
7.3%
3백만원~5백만원미만 9
 
4.7%
5백만원~1천만원미만 9
 
4.7%
1천만원~3천만원미만 7
 
3.6%
5천만원~1억원미만 3
 
1.6%
Other values (3) 4
 
2.1%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct78
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean477.44937
Minimum1
Maximum10205
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T18:16:21.876442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.25
median11.5
Q3132.5
95-th percentile2886
Maximum10205
Range10204
Interquartile range (IQR)129.25

Descriptive statistics

Standard deviation1388.8572
Coefficient of variation (CV)2.90891
Kurtosis25.796692
Mean477.44937
Median Absolute Deviation (MAD)10.5
Skewness4.6867771
Sum75437
Variance1928924.4
MonotonicityNot monotonic
2023-12-12T18:16:22.394917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 21
 
13.3%
4 18
 
11.4%
2 11
 
7.0%
3 8
 
5.1%
6 6
 
3.8%
7 4
 
2.5%
15 4
 
2.5%
8 3
 
1.9%
19 3
 
1.9%
5 3
 
1.9%
Other values (68) 77
48.7%
ValueCountFrequency (%)
1 21
13.3%
2 11
7.0%
3 8
 
5.1%
4 18
11.4%
5 3
 
1.9%
6 6
 
3.8%
7 4
 
2.5%
8 3
 
1.9%
9 2
 
1.3%
10 2
 
1.3%
ValueCountFrequency (%)
10205 1
0.6%
9123 1
0.6%
6170 1
0.6%
4571 1
0.6%
3525 1
0.6%
3119 1
0.6%
3088 1
0.6%
3022 1
0.6%
2862 1
0.6%
2802 1
0.6%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct158
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55754824
Minimum4160
Maximum5.4243964 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T18:16:22.586894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4160
5-th percentile231358.5
Q12526335
median18660155
Q364734055
95-th percentile2.2850285 × 108
Maximum5.4243964 × 108
Range5.4243548 × 108
Interquartile range (IQR)62207720

Descriptive statistics

Standard deviation98264972
Coefficient of variation (CV)1.7624479
Kurtosis10.578893
Mean55754824
Median Absolute Deviation (MAD)17955145
Skewness3.0913545
Sum8.8092621 × 109
Variance9.6560048 × 1015
MonotonicityNot monotonic
2023-12-12T18:16:22.799340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6207500 1
 
0.6%
220470 1
 
0.6%
74962450 1
 
0.6%
39943080 1
 
0.6%
59027400 1
 
0.6%
35193130 1
 
0.6%
66026510 1
 
0.6%
101616150 1
 
0.6%
180590800 1
 
0.6%
183750 1
 
0.6%
Other values (148) 148
93.7%
ValueCountFrequency (%)
4160 1
0.6%
48470 1
0.6%
79970 1
0.6%
133700 1
0.6%
142570 1
0.6%
183750 1
0.6%
199630 1
0.6%
220470 1
0.6%
233280 1
0.6%
287370 1
0.6%
ValueCountFrequency (%)
542439640 1
0.6%
502174090 1
0.6%
484722470 1
0.6%
462077610 1
0.6%
456294600 1
0.6%
276524600 1
0.6%
262209200 1
0.6%
232978750 1
0.6%
227712980 1
0.6%
209000900 1
0.6%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct100
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1250.1076
Minimum1
Maximum27180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T18:16:23.025307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.85
Q110
median28
Q3304.75
95-th percentile7446.2
Maximum27180
Range27179
Interquartile range (IQR)294.75

Descriptive statistics

Standard deviation3765.9265
Coefficient of variation (CV)3.0124819
Kurtosis27.634453
Mean1250.1076
Median Absolute Deviation (MAD)25
Skewness4.8600417
Sum197517
Variance14182203
MonotonicityNot monotonic
2023-12-12T18:16:23.208661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 8
 
5.1%
11 5
 
3.2%
16 5
 
3.2%
2 5
 
3.2%
7 5
 
3.2%
17 5
 
3.2%
3 5
 
3.2%
4 4
 
2.5%
5 4
 
2.5%
8 3
 
1.9%
Other values (90) 109
69.0%
ValueCountFrequency (%)
1 8
5.1%
2 5
3.2%
3 5
3.2%
4 4
2.5%
5 4
2.5%
6 2
 
1.3%
7 5
3.2%
8 3
 
1.9%
9 3
 
1.9%
10 2
 
1.3%
ValueCountFrequency (%)
27180 1
0.6%
26429 1
0.6%
16224 1
0.6%
10054 1
0.6%
10045 1
0.6%
9657 1
0.6%
9094 1
0.6%
8796 1
0.6%
7208 1
0.6%
7132 1
0.6%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct158
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1585842 × 108
Minimum34300
Maximum1.7047442 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T18:16:23.378414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34300
5-th percentile687920
Q17330585
median35010510
Q31.1298537 × 108
95-th percentile4.4788115 × 108
Maximum1.7047442 × 109
Range1.7047099 × 109
Interquartile range (IQR)1.0565478 × 108

Descriptive statistics

Standard deviation2.3346793 × 108
Coefficient of variation (CV)2.0151142
Kurtosis26.572716
Mean1.1585842 × 108
Median Absolute Deviation (MAD)32576615
Skewness4.6688374
Sum1.830563 × 1010
Variance5.4507277 × 1016
MonotonicityNot monotonic
2023-12-12T18:16:23.579300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9906480 1
 
0.6%
955270 1
 
0.6%
101401100 1
 
0.6%
78843700 1
 
0.6%
59027400 1
 
0.6%
35193130 1
 
0.6%
165684680 1
 
0.6%
101616150 1
 
0.6%
180590800 1
 
0.6%
692150 1
 
0.6%
Other values (148) 148
93.7%
ValueCountFrequency (%)
34300 1
0.6%
321670 1
0.6%
325030 1
0.6%
365830 1
0.6%
500580 1
0.6%
508400 1
0.6%
530250 1
0.6%
663950 1
0.6%
692150 1
0.6%
734800 1
0.6%
ValueCountFrequency (%)
1704744230 1
0.6%
1647504300 1
0.6%
1162781830 1
0.6%
620342190 1
0.6%
555088410 1
0.6%
529816530 1
0.6%
502174090 1
0.6%
456294600 1
0.6%
446396420 1
0.6%
398723230 1
0.6%

Interactions

2023-12-12T18:16:19.117706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:17.709270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:18.193702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:18.648292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:19.241548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:17.866374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:18.296105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:18.754637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:19.381303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:17.979896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:18.404966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:18.878586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:19.591013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:18.089898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:18.520665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:16:18.987033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:16:23.703862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세연도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세연도1.0000.0000.0000.0000.2250.0000.153
세목명0.0001.0000.1970.2930.2000.3270.241
체납액구간0.0000.1971.0000.0000.6570.0000.386
체납건수0.0000.2930.0001.0000.8410.9330.789
체납금액0.2250.2000.6570.8411.0000.6730.856
누적체납건수0.0000.3270.0000.9330.6731.0000.896
누적체납금액0.1530.2410.3860.7890.8560.8961.000
2023-12-12T18:16:23.822468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세연도세목명체납액구간
과세연도1.0000.0000.000
세목명0.0001.0000.093
체납액구간0.0000.0931.000
2023-12-12T18:16:23.937765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세연도세목명체납액구간
체납건수1.0000.6180.9610.6550.0000.1600.000
체납금액0.6181.0000.5040.9760.1400.1090.342
누적체납건수0.9610.5041.0000.5840.0000.2000.000
누적체납금액0.6550.9760.5841.0000.1050.1460.156
과세연도0.0000.1400.0000.1051.0000.0000.000
세목명0.1600.1090.2000.1460.0001.0000.093
체납액구간0.0000.3420.0000.1560.0000.0931.000

Missing values

2023-12-12T18:16:19.800246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:16:20.007418image/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

시도명시군구명자치단체코드과세연도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
0대전광역시중구301402017등록면허세10만원 미만19262075003279906480
1대전광역시중구301402017자동차세10만원 미만840357148102575110830716
2대전광역시중구301402017자동차세10만원~30만원미만8611442740802365387363440
3대전광역시중구301402017자동차세30만원~50만원미만29969220010434827890
4대전광역시중구301402017자동차세50만원~1백만원미만52918500116661440
5대전광역시중구301402017재산세10만원 미만63425932470185368732070
6대전광역시중구301402017재산세10만원~30만원미만1311873958036453915660
7대전광역시중구301402017재산세1백만원~3백만원미만225499601421125560
8대전광역시중구301402017재산세30만원~50만원미만829833202910895770
9대전광역시중구301402017재산세3백만원~5백만원미만518162860725694220
시도명시군구명자치단체코드과세연도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
148대전광역시중구301402021지방소득세5백만원~1천만원미만2919555175033221261140
149대전광역시중구301402021지방소득세5천만원~1억원미만32622092004349153360
150대전광역시중구301402021지역자원시설세10만원 미만117997028874220
151대전광역시중구301402021지역자원시설세10만원~30만원미만4108596051269710
152대전광역시중구301402021취득세10만원 미만723328029952060
153대전광역시중구301402021취득세10만원~30만원미만61414410204047890
154대전광역시중구301402021취득세1백만원~3백만원미만3400096045446160
155대전광역시중구301402021취득세3백만원~5백만원미만1429219014292190
156대전광역시중구301402021취득세50만원~1백만원미만317440101410421580
157대전광역시중구301402021취득세5백만원~1천만원미만214368930214368930