Overview

Dataset statistics

Number of variables10
Number of observations43
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory89.1 B

Variable types

Categorical6
Numeric4

Dataset

Description경기도 이천시 지방세 체납 현황에 대한 과세연도, 세목명, 체납액구간, 체납건수, 체납금액, 누적체납건수, 누적체납금액에 대한 정보를 제공
Author경기도 이천시
URLhttps://www.data.go.kr/data/15079110/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 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 08:24:36.497453
Analysis finished2024-04-06 08:24:41.344974
Duration4.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
경기도
43 

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 43
100.0%

Length

2024-04-06T17:24:41.509557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:24:41.762676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 43
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
이천시
43 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이천시 43
100.0%

Length

2024-04-06T17:24:42.020202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:24:42.396430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이천시 43
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
41500
43 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41500
2nd row41500
3rd row41500
4th row41500
5th row41500

Common Values

ValueCountFrequency (%)
41500 43
100.0%

Length

2024-04-06T17:24:42.758860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:24:43.034116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41500 43
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
2022
43 

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 43
100.0%

Length

2024-04-06T17:24:43.326383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:24:43.571306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 43
100.0%

세목명
Categorical

Distinct7
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
지방소득세
11 
재산세
10 
취득세
10 
주민세
6 
자동차세
4 
Other values (2)
2 

Length

Max length7
Median length3
Mean length3.744186
Min length3

Unique

Unique2 ?
Unique (%)4.7%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 11
25.6%
재산세 10
23.3%
취득세 10
23.3%
주민세 6
14.0%
자동차세 4
 
9.3%
등록면허세 1
 
2.3%
지역자원시설세 1
 
2.3%

Length

2024-04-06T17:24:43.783535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:24:44.136616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 11
25.6%
재산세 10
23.3%
취득세 10
23.3%
주민세 6
14.0%
자동차세 4
 
9.3%
등록면허세 1
 
2.3%
지역자원시설세 1
 
2.3%

체납액구간
Categorical

Distinct11
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Memory size476.0 B
10만원 미만
7 
10만원~30만원미만
5 
30만원~50만원미만
5 
50만원~1백만원미만
5 
1백만원~3백만원미만
4 
Other values (6)
17 

Length

Max length11
Median length11
Mean length10.232558
Min length7

Unique

Unique1 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 7
16.3%
10만원~30만원미만 5
11.6%
30만원~50만원미만 5
11.6%
50만원~1백만원미만 5
11.6%
1백만원~3백만원미만 4
9.3%
3백만원~5백만원미만 4
9.3%
1천만원~3천만원미만 3
7.0%
3천만원~5천만원미만 3
7.0%
5백만원~1천만원미만 3
7.0%
5천만원~1억원미만 3
7.0%

Length

2024-04-06T17:24:44.643687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 7
14.0%
미만 7
14.0%
10만원~30만원미만 5
10.0%
30만원~50만원미만 5
10.0%
50만원~1백만원미만 5
10.0%
1백만원~3백만원미만 4
8.0%
3백만원~5백만원미만 4
8.0%
1천만원~3천만원미만 3
6.0%
3천만원~5천만원미만 3
6.0%
5백만원~1천만원미만 3
6.0%
Other values (2) 4
8.0%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean610.72093
Minimum1
Maximum9942
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-04-06T17:24:45.317995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.1
Q16
median35
Q3182.5
95-th percentile2771.2
Maximum9942
Range9941
Interquartile range (IQR)176.5

Descriptive statistics

Standard deviation1728.7781
Coefficient of variation (CV)2.830717
Kurtosis21.027455
Mean610.72093
Median Absolute Deviation (MAD)32
Skewness4.3088697
Sum26261
Variance2988673.8
MonotonicityNot monotonic
2024-04-06T17:24:45.640515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
3 4
 
9.3%
1 3
 
7.0%
2 2
 
4.7%
6 2
 
4.7%
35 2
 
4.7%
402 1
 
2.3%
144 1
 
2.3%
30 1
 
2.3%
153 1
 
2.3%
45 1
 
2.3%
Other values (25) 25
58.1%
ValueCountFrequency (%)
1 3
7.0%
2 2
4.7%
3 4
9.3%
4 1
 
2.3%
6 2
4.7%
7 1
 
2.3%
8 1
 
2.3%
9 1
 
2.3%
11 1
 
2.3%
14 1
 
2.3%
ValueCountFrequency (%)
9942 1
2.3%
4635 1
2.3%
2814 1
2.3%
2386 1
2.3%
2145 1
2.3%
1377 1
2.3%
837 1
2.3%
402 1
2.3%
252 1
2.3%
247 1
2.3%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2404013 × 108
Minimum408030
Maximum5.1360158 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-04-06T17:24:45.877987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum408030
5-th percentile1630193
Q113152765
median71440200
Q31.9104416 × 108
95-th percentile3.6343605 × 108
Maximum5.1360158 × 108
Range5.1319355 × 108
Interquartile range (IQR)1.778914 × 108

Descriptive statistics

Standard deviation1.3183978 × 108
Coefficient of variation (CV)1.06288
Kurtosis0.64694832
Mean1.2404013 × 108
Median Absolute Deviation (MAD)67990370
Skewness1.1340425
Sum5.3337257 × 109
Variance1.7381727 × 1016
MonotonicityNot monotonic
2024-04-06T17:24:46.206010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
12129310 1
 
2.3%
123684620 1
 
2.3%
350031150 1
 
2.3%
513601580 1
 
2.3%
59397450 1
 
2.3%
177492410 1
 
2.3%
159128790 1
 
2.3%
111744740 1
 
2.3%
253810800 1
 
2.3%
111592950 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
408030 1
2.3%
1228840 1
2.3%
1499940 1
2.3%
2802470 1
2.3%
3449830 1
2.3%
4036650 1
2.3%
5142460 1
2.3%
6701080 1
2.3%
7389000 1
2.3%
9430500 1
2.3%
ValueCountFrequency (%)
513601580 1
2.3%
412871310 1
2.3%
364925480 1
2.3%
350031150 1
2.3%
341409420 1
2.3%
264877510 1
2.3%
261880600 1
2.3%
253810800 1
2.3%
253533280 1
2.3%
215411230 1
2.3%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1936.8837
Minimum2
Maximum24308
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-04-06T17:24:46.593389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3.1
Q124
median84
Q3475.5
95-th percentile14330.4
Maximum24308
Range24306
Interquartile range (IQR)451.5

Descriptive statistics

Standard deviation5110.1594
Coefficient of variation (CV)2.6383408
Kurtosis10.004065
Mean1936.8837
Median Absolute Deviation (MAD)77
Skewness3.1878303
Sum83286
Variance26113729
MonotonicityNot monotonic
2024-04-06T17:24:46.837510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
2 2
 
4.7%
21 2
 
4.7%
4 2
 
4.7%
2377 1
 
2.3%
7 1
 
2.3%
523 1
 
2.3%
121 1
 
2.3%
341 1
 
2.3%
184 1
 
2.3%
15 1
 
2.3%
Other values (30) 30
69.8%
ValueCountFrequency (%)
2 2
4.7%
3 1
2.3%
4 2
4.7%
7 1
2.3%
8 1
2.3%
15 1
2.3%
16 1
2.3%
21 2
4.7%
27 1
2.3%
29 1
2.3%
ValueCountFrequency (%)
24308 1
2.3%
15912 1
2.3%
14485 1
2.3%
12939 1
2.3%
4186 1
2.3%
3274 1
2.3%
2377 1
2.3%
1117 1
2.3%
531 1
2.3%
523 1
2.3%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7212771 × 108
Minimum732120
Maximum2.4155812 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-04-06T17:24:47.074626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum732120
5-th percentile10927989
Q152942000
median1.6718695 × 108
Q34.9195395 × 108
95-th percentile9.8292591 × 108
Maximum2.4155812 × 109
Range2.4148491 × 109
Interquartile range (IQR)4.3901195 × 108

Descriptive statistics

Standard deviation4.9486135 × 108
Coefficient of variation (CV)1.3298159
Kurtosis8.4323365
Mean3.7212771 × 108
Median Absolute Deviation (MAD)1.5626148 × 108
Skewness2.6744647
Sum1.6001491 × 1010
Variance2.4488776 × 1017
MonotonicityNot monotonic
2024-04-06T17:24:47.326514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
33039280 1
 
2.3%
723428760 1
 
2.3%
478137120 1
 
2.3%
2027437060 1
 
2.3%
136493400 1
 
2.3%
708959530 1
 
2.3%
563149090 1
 
2.3%
351520840 1
 
2.3%
990273290 1
 
2.3%
505770780 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
732120 1
2.3%
3929370 1
2.3%
10925470 1
2.3%
10950660 1
2.3%
14328700 1
2.3%
27101270 1
2.3%
28595180 1
2.3%
30623330 1
2.3%
33039280 1
2.3%
35092260 1
2.3%
ValueCountFrequency (%)
2415581180 1
2.3%
2027437060 1
2.3%
990273290 1
2.3%
916799460 1
2.3%
724138050 1
2.3%
723428760 1
2.3%
715532700 1
2.3%
708959530 1
2.3%
563149090 1
2.3%
511273060 1
2.3%

Interactions

2024-04-06T17:24:40.118533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:37.367123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:38.288624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:39.195641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:40.304264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:37.579048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:38.551599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:39.436045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:40.488772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:37.824817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:38.758322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:39.665273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:40.667525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:38.059596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:38.990260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:39.908106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:24:47.518594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.1850.2910.0910.203
체납액구간0.0001.0000.0000.4670.0000.314
체납건수0.1850.0001.0000.7220.9800.305
체납금액0.2910.4670.7221.0000.8430.878
누적체납건수0.0910.0000.9800.8431.0000.396
누적체납금액0.2030.3140.3050.8780.3961.000
2024-04-06T17:24:47.724331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명
체납액구간1.0000.000
세목명0.0001.000
2024-04-06T17:24:47.941896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.3480.9780.3560.0990.000
체납금액0.3481.0000.2880.9460.0000.210
누적체납건수0.9780.2881.0000.3310.0000.000
누적체납금액0.3560.9460.3311.0000.0000.145
세목명0.0990.0000.0000.0001.0000.000
체납액구간0.0000.2100.0000.1450.0001.000

Missing values

2024-04-06T17:24:40.926303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:24:41.235980image/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
0경기도이천시415002022등록면허세10만원 미만83712129310237733039280
1경기도이천시415002022자동차세10만원 미만281412368462015912723428760
2경기도이천시415002022자동차세10만원~30만원미만2386412871310144852415581180
3경기도이천시415002022자동차세30만원~50만원미만12644419860430149357530
4경기도이천시415002022자동차세50만원~1백만원미만634498304327101270
5경기도이천시415002022재산세10만원 미만463515349281012939411606390
6경기도이천시415002022재산세10만원~30만원미만21453649254804186715532700
7경기도이천시415002022재산세1백만원~3백만원미만201341409420441724138050
8경기도이천시415002022재산세1천만원~3천만원미만1826487751031449234120
9경기도이천시415002022재산세30만원~50만원미만25295274210449167186950
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
33경기도이천시415002022취득세10만원 미만351499940843929370
34경기도이천시415002022취득세10만원~30만원미만1528024707114328700
35경기도이천시415002022취득세1백만원~3백만원미만162604197077140446030
36경기도이천시415002022취득세1천만원~3천만원미만815576471021357326630
37경기도이천시415002022취득세30만원~50만원미만312288402710925470
38경기도이천시415002022취득세3백만원~5백만원미만6231674301659210840
39경기도이천시415002022취득세3천만원~5천만원미만132308720272377940
40경기도이천시415002022취득세50만원~1백만원미만751424604735092260
41경기도이천시415002022취득세5백만원~1천만원미만31906031021151467230
42경기도이천시415002022취득세5천만원~1억원미만1568397902155245790