Overview

Dataset statistics

Number of variables9
Number of observations30
Missing cells26
Missing cells (%)9.6%
Duplicate rows1
Duplicate rows (%)3.3%
Total size in memory2.4 KiB
Average record size in memory82.4 B

Variable types

DateTime1
Categorical8

Dataset

Description미추홀구주민 1인당 또는 세대 당 부담된 지방세액에 대한 데이터로 주민1인당 부담금액, 세대당 부담금액, 지방세 금액, 인구수 등을 제공합니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15078872&srcSe=7661IVAWM27C61E190

Alerts

Dataset has 1 (3.3%) duplicate rowsDuplicates
인구수 is highly overall correlated with 시도명 and 6 other fieldsHigh correlation
시군구명 is highly overall correlated with 시도명 and 6 other fieldsHigh correlation
자치단체코드 is highly overall correlated with 시도명 and 6 other fieldsHigh correlation
주민1인당 부담금액 is highly overall correlated with 시도명 and 6 other fieldsHigh correlation
지방세 금액 is highly overall correlated with 시도명 and 6 other fieldsHigh correlation
세대수 is highly overall correlated with 시도명 and 6 other fieldsHigh correlation
세대당부담금액 is highly overall correlated with 시도명 and 6 other fieldsHigh correlation
시도명 is highly overall correlated with 시군구명 and 6 other fieldsHigh correlation
주민1인당 부담금액 is highly imbalanced (64.1%)Imbalance
세대당부담금액 is highly imbalanced (64.1%)Imbalance
지방세 금액 is highly imbalanced (64.1%)Imbalance
인구수 is highly imbalanced (64.1%)Imbalance
세대수 is highly imbalanced (64.1%)Imbalance
과세년도 has 26 (86.7%) missing valuesMissing

Reproduction

Analysis started2024-01-28 09:58:04.546766
Analysis finished2024-01-28 09:58:05.087684
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

과세년도
Date

MISSING 

Distinct4
Distinct (%)100.0%
Missing26
Missing (%)86.7%
Memory size372.0 B
Minimum2018-12-31 00:00:00
Maximum2022-12-31 00:00:00
2024-01-28T18:58:05.123279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:58:05.203989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

시도명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
26 
인천광역시
4 

Length

Max length5
Median length4
Mean length4.1333333
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천광역시
2nd row인천광역시
3rd row인천광역시
4th row인천광역시
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 26
86.7%
인천광역시 4
 
13.3%

Length

2024-01-28T18:58:05.306550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:58:05.398588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
86.7%
인천광역시 4
 
13.3%

시군구명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
26 
미추홀구
4 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미추홀구
2nd row미추홀구
3rd row미추홀구
4th row미추홀구
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 26
86.7%
미추홀구 4
 
13.3%

Length

2024-01-28T18:58:05.477214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:58:05.548574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
86.7%
미추홀구 4
 
13.3%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
26 
28177
4 

Length

Max length5
Median length4
Mean length4.1333333
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28177
2nd row28177
3rd row28177
4th row28177
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 26
86.7%
28177 4
 
13.3%

Length

2024-01-28T18:58:05.634303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:58:05.719431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
86.7%
28177 4
 
13.3%

주민1인당 부담금액
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
26 
737910
 
1
864720
 
1
978817
 
1
1022883
 
1

Length

Max length7
Median length4
Mean length4.3
Min length4

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row737910
2nd row864720
3rd row978817
4th row1022883
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 26
86.7%
737910 1
 
3.3%
864720 1
 
3.3%
978817 1
 
3.3%
1022883 1
 
3.3%

Length

2024-01-28T18:58:05.818177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:58:05.902454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
86.7%
737910 1
 
3.3%
864720 1
 
3.3%
978817 1
 
3.3%
1022883 1
 
3.3%

세대당부담금액
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
26 
1668000
 
1
1912410
 
1
2102105
 
1
2131455
 
1

Length

Max length7
Median length4
Mean length4.4
Min length4

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row1668000
2nd row1912410
3rd row2102105
4th row2131455
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 26
86.7%
1668000 1
 
3.3%
1912410 1
 
3.3%
2102105 1
 
3.3%
2131455 1
 
3.3%

Length

2024-01-28T18:58:05.989578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:58:06.078522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
86.7%
1668000 1
 
3.3%
1912410 1
 
3.3%
2102105 1
 
3.3%
2131455 1
 
3.3%

지방세 금액
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
26 
307000000000
 
1
354000000000
 
1
396000000000
 
1
415294869220
 
1

Length

Max length12
Median length4
Mean length5.0666667
Min length4

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row307000000000
2nd row354000000000
3rd row396000000000
4th row415294869220
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 26
86.7%
307000000000 1
 
3.3%
354000000000 1
 
3.3%
396000000000 1
 
3.3%
415294869220 1
 
3.3%

Length

2024-01-28T18:58:06.173962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:58:06.264056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
86.7%
307000000000 1
 
3.3%
354000000000 1
 
3.3%
396000000000 1
 
3.3%
415294869220 1
 
3.3%

인구수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
26 
416542
 
1
408862
 
1
404343
 
1
406004
 
1

Length

Max length6
Median length4
Mean length4.2666667
Min length4

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row416542
2nd row408862
3rd row404343
4th row406004
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 26
86.7%
416542 1
 
3.3%
408862 1
 
3.3%
404343 1
 
3.3%
406004 1
 
3.3%

Length

2024-01-28T18:58:06.365548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:58:06.457848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
86.7%
416542 1
 
3.3%
408862 1
 
3.3%
404343 1
 
3.3%
406004 1
 
3.3%

세대수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
26 
184275
 
1
184872
 
1
188277
 
1
194841
 
1

Length

Max length6
Median length4
Mean length4.2666667
Min length4

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row184275
2nd row184872
3rd row188277
4th row194841
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 26
86.7%
184275 1
 
3.3%
184872 1
 
3.3%
188277 1
 
3.3%
194841 1
 
3.3%

Length

2024-01-28T18:58:06.552929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:58:06.641057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
86.7%
184275 1
 
3.3%
184872 1
 
3.3%
188277 1
 
3.3%
194841 1
 
3.3%

Correlations

2024-01-28T18:58:06.700990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도주민1인당 부담금액세대당부담금액지방세 금액인구수세대수
과세년도1.0001.0001.0001.0001.0001.000
주민1인당 부담금액1.0001.0001.0001.0001.0001.000
세대당부담금액1.0001.0001.0001.0001.0001.000
지방세 금액1.0001.0001.0001.0001.0001.000
인구수1.0001.0001.0001.0001.0001.000
세대수1.0001.0001.0001.0001.0001.000
2024-01-28T18:58:06.787405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인구수시군구명자치단체코드주민1인당 부담금액지방세 금액세대수세대당부담금액시도명
인구수1.0001.0001.0001.0001.0001.0001.0001.000
시군구명1.0001.0001.0001.0001.0001.0001.0001.000
자치단체코드1.0001.0001.0001.0001.0001.0001.0001.000
주민1인당 부담금액1.0001.0001.0001.0001.0001.0001.0001.000
지방세 금액1.0001.0001.0001.0001.0001.0001.0001.000
세대수1.0001.0001.0001.0001.0001.0001.0001.000
세대당부담금액1.0001.0001.0001.0001.0001.0001.0001.000
시도명1.0001.0001.0001.0001.0001.0001.0001.000
2024-01-28T18:58:06.878808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명시군구명자치단체코드주민1인당 부담금액세대당부담금액지방세 금액인구수세대수
시도명1.0001.0001.0001.0001.0001.0001.0001.000
시군구명1.0001.0001.0001.0001.0001.0001.0001.000
자치단체코드1.0001.0001.0001.0001.0001.0001.0001.000
주민1인당 부담금액1.0001.0001.0001.0001.0001.0001.0001.000
세대당부담금액1.0001.0001.0001.0001.0001.0001.0001.000
지방세 금액1.0001.0001.0001.0001.0001.0001.0001.000
인구수1.0001.0001.0001.0001.0001.0001.0001.000
세대수1.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2024-01-28T18:58:04.932883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T18:58:05.047535image/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

과세년도시도명시군구명자치단체코드주민1인당 부담금액세대당부담금액지방세 금액인구수세대수
02018-12-31인천광역시미추홀구281777379101668000307000000000416542184275
12019-12-31인천광역시미추홀구281778647201912410354000000000408862184872
22020-12-31인천광역시미추홀구281779788172102105396000000000404343188277
32022-12-31인천광역시미추홀구2817710228832131455415294869220406004194841
4<NA><NA><NA><NA><NA><NA><NA><NA><NA>
5<NA><NA><NA><NA><NA><NA><NA><NA><NA>
6<NA><NA><NA><NA><NA><NA><NA><NA><NA>
7<NA><NA><NA><NA><NA><NA><NA><NA><NA>
8<NA><NA><NA><NA><NA><NA><NA><NA><NA>
9<NA><NA><NA><NA><NA><NA><NA><NA><NA>
과세년도시도명시군구명자치단체코드주민1인당 부담금액세대당부담금액지방세 금액인구수세대수
20<NA><NA><NA><NA><NA><NA><NA><NA><NA>
21<NA><NA><NA><NA><NA><NA><NA><NA><NA>
22<NA><NA><NA><NA><NA><NA><NA><NA><NA>
23<NA><NA><NA><NA><NA><NA><NA><NA><NA>
24<NA><NA><NA><NA><NA><NA><NA><NA><NA>
25<NA><NA><NA><NA><NA><NA><NA><NA><NA>
26<NA><NA><NA><NA><NA><NA><NA><NA><NA>
27<NA><NA><NA><NA><NA><NA><NA><NA><NA>
28<NA><NA><NA><NA><NA><NA><NA><NA><NA>
29<NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

과세년도시도명시군구명자치단체코드주민1인당 부담금액세대당부담금액지방세 금액인구수세대수# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA>26