Overview

Dataset statistics

Number of variables10
Number of observations39
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory89.4 B

Variable types

Categorical6
Numeric4

Dataset

Description대구광역시 달서구_지방세 체납 현황_20201231
Author대구광역시 달서구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15079282&dataSetDetailId=150792821826418ed14d5&provdMethod=FILE

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 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 started2023-12-10 18:48:48.852607
Analysis finished2023-12-10 18:48:52.045851
Duration3.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
대구광역시
39 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 39
100.0%

Length

2023-12-11T03:48:52.138242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:48:52.257782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 39
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
달서구
39 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
달서구 39
100.0%

Length

2023-12-11T03:48:52.399215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:48:52.544492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
달서구 39
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
27290
39 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row27290
2nd row27290
3rd row27290
4th row27290
5th row27290

Common Values

ValueCountFrequency (%)
27290 39
100.0%

Length

2023-12-11T03:48:52.681598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:48:52.831057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
27290 39
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
2020
39 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 39
100.0%

Length

2023-12-11T03:48:52.974545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:48:53.128705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 39
100.0%

세목명
Categorical

Distinct7
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size444.0 B
재산세
10 
지방소득세
9 
취득세
8 
주민세
5 
자동차세
4 
Other values (2)
3 

Length

Max length7
Median length3
Mean length3.8205128
Min length3

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 10
25.6%
지방소득세 9
23.1%
취득세 8
20.5%
주민세 5
12.8%
자동차세 4
 
10.3%
지역자원시설세 2
 
5.1%
등록면허세 1
 
2.6%

Length

2023-12-11T03:48:53.290708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:48:53.474953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 10
25.6%
지방소득세 9
23.1%
취득세 8
20.5%
주민세 5
12.8%
자동차세 4
 
10.3%
지역자원시설세 2
 
5.1%
등록면허세 1
 
2.6%

체납액구간
Categorical

Distinct10
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
10만원 미만
7 
10만원~30만원미만
6 
30만원~50만원미만
5 
50만원~1백만원미만
5 
1백만원~3백만원미만
4 
Other values (5)
12 

Length

Max length11
Median length11
Mean length10.25641
Min length7

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 7
17.9%
10만원~30만원미만 6
15.4%
30만원~50만원미만 5
12.8%
50만원~1백만원미만 5
12.8%
1백만원~3백만원미만 4
10.3%
1천만원~3천만원미만 3
7.7%
3백만원~5백만원미만 3
7.7%
5백만원~1천만원미만 3
7.7%
3천만원~5천만원미만 2
 
5.1%
5천만원~1억원미만 1
 
2.6%

Length

2023-12-11T03:48:53.701140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:48:53.914395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 7
15.2%
미만 7
15.2%
10만원~30만원미만 6
13.0%
30만원~50만원미만 5
10.9%
50만원~1백만원미만 5
10.9%
1백만원~3백만원미만 4
8.7%
1천만원~3천만원미만 3
6.5%
3백만원~5백만원미만 3
6.5%
5백만원~1천만원미만 3
6.5%
3천만원~5천만원미만 2
 
4.3%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean911.38462
Minimum1
Maximum15113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T03:48:54.139172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median15
Q3214.5
95-th percentile4083.9
Maximum15113
Range15112
Interquartile range (IQR)209.5

Descriptive statistics

Standard deviation2620.2773
Coefficient of variation (CV)2.875051
Kurtosis23.579873
Mean911.38462
Median Absolute Deviation (MAD)14
Skewness4.5546693
Sum35544
Variance6865853
MonotonicityNot monotonic
2023-12-11T03:48:54.352624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 5
 
12.8%
2 3
 
7.7%
5 2
 
5.1%
12 2
 
5.1%
13 2
 
5.1%
8 2
 
5.1%
14 1
 
2.6%
17 1
 
2.6%
1827 1
 
2.6%
193 1
 
2.6%
Other values (19) 19
48.7%
ValueCountFrequency (%)
1 5
12.8%
2 3
7.7%
4 1
 
2.6%
5 2
 
5.1%
8 2
 
5.1%
9 1
 
2.6%
12 2
 
5.1%
13 2
 
5.1%
14 1
 
2.6%
15 1
 
2.6%
ValueCountFrequency (%)
15113 1
2.6%
4317 1
2.6%
4058 1
2.6%
4042 1
2.6%
2902 1
2.6%
1827 1
2.6%
947 1
2.6%
569 1
2.6%
544 1
2.6%
226 1
2.6%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94718203
Minimum4960
Maximum7.051425 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T03:48:54.573071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4960
5-th percentile433245
Q17382910
median61228080
Q31.0694016 × 108
95-th percentile2.5491648 × 108
Maximum7.051425 × 108
Range7.0513754 × 108
Interquartile range (IQR)99557250

Descriptive statistics

Standard deviation1.3659216 × 108
Coefficient of variation (CV)1.4420899
Kurtosis11.23679
Mean94718203
Median Absolute Deviation (MAD)52608420
Skewness3.0757988
Sum3.6940099 × 109
Variance1.8657419 × 1016
MonotonicityNot monotonic
2023-12-11T03:48:54.810025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
32163420 1
 
2.6%
192683870 1
 
2.6%
159650810 1
 
2.6%
78805320 1
 
2.6%
78775520 1
 
2.6%
95065980 1
 
2.6%
33471400 1
 
2.6%
135430290 1
 
2.6%
107625330 1
 
2.6%
4960 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
4960 1
2.6%
369390 1
2.6%
440340 1
2.6%
2238410 1
2.6%
3297170 1
2.6%
4179580 1
2.6%
4980050 1
2.6%
5151560 1
2.6%
6063780 1
2.6%
6146160 1
2.6%
ValueCountFrequency (%)
705142500 1
2.6%
484830340 1
2.6%
229370500 1
2.6%
211115940 1
2.6%
195345530 1
2.6%
192683870 1
2.6%
159650810 1
2.6%
135430290 1
2.6%
117930670 1
2.6%
107625330 1
2.6%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2080.8205
Minimum1
Maximum41976
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T03:48:55.045421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q110.5
median38
Q3435.5
95-th percentile8102.2
Maximum41976
Range41975
Interquartile range (IQR)425

Descriptive statistics

Standard deviation6967.837
Coefficient of variation (CV)3.3486007
Kurtosis29.951669
Mean2080.8205
Median Absolute Deviation (MAD)37
Skewness5.2554561
Sum81152
Variance48550752
MonotonicityNot monotonic
2023-12-11T03:48:55.260354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
2 3
 
7.7%
1 3
 
7.7%
35 2
 
5.1%
1609 1
 
2.6%
18 1
 
2.6%
174 1
 
2.6%
5 1
 
2.6%
365 1
 
2.6%
28 1
 
2.6%
379 1
 
2.6%
Other values (24) 24
61.5%
ValueCountFrequency (%)
1 3
7.7%
2 3
7.7%
3 1
 
2.6%
4 1
 
2.6%
5 1
 
2.6%
6 1
 
2.6%
15 1
 
2.6%
16 1
 
2.6%
18 1
 
2.6%
19 1
 
2.6%
ValueCountFrequency (%)
41976 1
2.6%
9886 1
2.6%
7904 1
2.6%
7443 1
2.6%
4323 1
2.6%
3492 1
2.6%
1609 1
2.6%
1248 1
2.6%
649 1
2.6%
492 1
2.6%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.631085 × 108
Minimum145910
Maximum1.3094372 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T03:48:55.489997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum145910
5-th percentile5586375
Q123733470
median95042820
Q31.5871865 × 108
95-th percentile6.2195927 × 108
Maximum1.3094372 × 109
Range1.3092913 × 109
Interquartile range (IQR)1.3498518 × 108

Descriptive statistics

Standard deviation2.4988377 × 108
Coefficient of variation (CV)1.5320095
Kurtosis11.578291
Mean1.631085 × 108
Median Absolute Deviation (MAD)71486300
Skewness3.1133681
Sum6.3612313 × 109
Variance6.2441898 × 1016
MonotonicityNot monotonic
2023-12-11T03:48:55.729414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
53886960 1
 
2.6%
351037060 1
 
2.6%
274827300 1
 
2.6%
95042820 1
 
2.6%
144469710 1
 
2.6%
108735090 1
 
2.6%
33471400 1
 
2.6%
258167870 1
 
2.6%
115873360 1
 
2.6%
145910 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
145910 1
2.6%
369390 1
2.6%
6166040 1
2.6%
6592330 1
2.6%
14240630 1
2.6%
15273130 1
2.6%
19658690 1
2.6%
21389080 1
2.6%
23384760 1
2.6%
23556520 1
2.6%
ValueCountFrequency (%)
1309437200 1
2.6%
707853250 1
2.6%
612415490 1
2.6%
491194000 1
2.6%
351037060 1
2.6%
274827300 1
2.6%
258167870 1
2.6%
250218380 1
2.6%
227100250 1
2.6%
172967590 1
2.6%

Interactions

2023-12-11T03:48:51.114659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:49.197240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:49.733599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:50.605713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:51.252663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:49.324021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:49.881174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:50.740715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:51.384577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:49.462470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:50.033592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:50.880322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:51.499852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:49.597465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:50.155688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:48:50.992834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T03:48:55.880213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.2560.2990.2910.000
체납액구간0.0001.0000.0000.0000.0000.000
체납건수0.2560.0001.0000.7940.9740.897
체납금액0.2990.0000.7941.0000.8970.948
누적체납건수0.2910.0000.9740.8971.0000.960
누적체납금액0.0000.0000.8970.9480.9601.000
2023-12-11T03:48:56.056959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간
세목명1.0000.000
체납액구간0.0001.000
2023-12-11T03:48:56.198995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.6800.9610.7780.1580.000
체납금액0.6801.0000.5400.9630.1880.000
누적체납건수0.9610.5401.0000.6600.1830.000
누적체납금액0.7780.9630.6601.0000.0000.000
세목명0.1580.1880.1830.0001.0000.000
체납액구간0.0000.0000.0000.0000.0001.000

Missing values

2023-12-11T03:48:51.702331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T03:48:51.966226image/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
0대구광역시달서구272902020등록면허세10만원 미만94732163420160953886960
1대구광역시달서구272902020자동차세10만원 미만43171926838707904351037060
2대구광역시달서구272902020자동차세10만원~30만원미만405870514250074431309437200
3대구광역시달서구272902020자동차세30만원~50만원미만22679157500492172967590
4대구광역시달서구272902020자동차세50만원~1백만원미만841795803519658690
5대구광역시달서구272902020재산세10만원 미만40422293705009886491194000
6대구광역시달서구272902020재산세10만원~30만원미만29024848303404323707853250
7대구광역시달서구272902020재산세1백만원~3백만원미만7011793067085139329530
8대구광역시달서구272902020재산세1천만원~3천만원미만5894783406104182730
9대구광역시달서구272902020재산세30만원~50만원미만544211115940649250218380
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
29대구광역시달서구272902020지역자원시설세10만원 미만149604145910
30대구광역시달서구272902020지역자원시설세10만원~30만원미만23693902369390
31대구광역시달서구272902020취득세10만원 미만124403401456166040
32대구광역시달서구272902020취득세10만원~30만원미만14223841012121389080
33대구광역시달서구272902020취득세1백만원~3백만원미만12167426801625239390
34대구광역시달서구272902020취득세1천만원~3천만원미만237928010237928010
35대구광역시달서구272902020취득세30만원~50만원미만1351515603714240630
36대구광역시달서구272902020취득세3백만원~5백만원미만1329717026592330
37대구광역시달서구272902020취득세50만원~1백만원미만961461603523384760
38대구광역시달서구272902020취득세5백만원~1천만원미만217452780323556520