Overview

Dataset statistics

Number of variables3
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory704.0 B
Average record size in memory32.0 B

Variable types

Text1
Numeric2

Dataset

Description인천광역시 부평구 국민기초생활보장 특례 수급자 현황 데이터는 각 동별 특례 수급자 가수 수와 인원 수에 대한 정보를 제공하고 있습니다.
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15118001&srcSe=7661IVAWM27C61E190

Alerts

가구 is highly overall correlated with 인원High correlation
인원 is highly overall correlated with 가구High correlation
동별 has unique valuesUnique

Reproduction

Analysis started2024-01-28 08:40:34.770812
Analysis finished2024-01-28 08:40:35.278249
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

동별
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-01-28T17:40:35.390351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.9545455
Min length3

Characters and Unicode

Total characters87
Distinct characters20
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row부평1동
2nd row부평2동
3rd row부평3동
4th row부평4동
5th row부평5동
ValueCountFrequency (%)
부평1동 1
 
4.5%
부평2동 1
 
4.5%
십정1동 1
 
4.5%
일신동 1
 
4.5%
부개3동 1
 
4.5%
부개2동 1
 
4.5%
부개1동 1
 
4.5%
삼산2동 1
 
4.5%
삼산1동 1
 
4.5%
갈산2동 1
 
4.5%
Other values (12) 12
54.5%
2024-01-28T17:40:35.661231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 22
25.3%
부 9
10.3%
산 8
 
9.2%
1 7
 
8.0%
2 7
 
8.0%
평 6
 
6.9%
곡 4
 
4.6%
3 3
 
3.4%
개 3
 
3.4%
4 2
 
2.3%
Other values (10) 16
18.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66
75.9%
Decimal Number 21
 
24.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 22
33.3%
부 9
13.6%
산 8
 
12.1%
평 6
 
9.1%
곡 4
 
6.1%
개 3
 
4.5%
청 2
 
3.0%
천 2
 
3.0%
갈 2
 
3.0%
삼 2
 
3.0%
Other values (4) 6
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 7
33.3%
2 7
33.3%
3 3
14.3%
4 2
 
9.5%
5 1
 
4.8%
6 1
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66
75.9%
Common 21
 
24.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 22
33.3%
부 9
13.6%
산 8
 
12.1%
평 6
 
9.1%
곡 4
 
6.1%
개 3
 
4.5%
청 2
 
3.0%
천 2
 
3.0%
갈 2
 
3.0%
삼 2
 
3.0%
Other values (4) 6
 
9.1%
Common
ValueCountFrequency (%)
1 7
33.3%
2 7
33.3%
3 3
14.3%
4 2
 
9.5%
5 1
 
4.8%
6 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66
75.9%
ASCII 21
 
24.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 22
33.3%
부 9
13.6%
산 8
 
12.1%
평 6
 
9.1%
곡 4
 
6.1%
개 3
 
4.5%
청 2
 
3.0%
천 2
 
3.0%
갈 2
 
3.0%
삼 2
 
3.0%
Other values (4) 6
 
9.1%
ASCII
ValueCountFrequency (%)
1 7
33.3%
2 7
33.3%
3 3
14.3%
4 2
 
9.5%
5 1
 
4.8%
6 1
 
4.8%

가구
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.272727
Minimum7
Maximum72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-01-28T17:40:35.768714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile8.05
Q115.75
median20.5
Q330.5
95-th percentile61.9
Maximum72
Range65
Interquartile range (IQR)14.75

Descriptive statistics

Standard deviation18.812817
Coefficient of variation (CV)0.68980328
Kurtosis0.53361253
Mean27.272727
Median Absolute Deviation (MAD)9.5
Skewness1.2105229
Sum600
Variance353.92208
MonotonicityNot monotonic
2024-01-28T17:40:35.856022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
19 2
 
9.1%
10 2
 
9.1%
20 2
 
9.1%
29 2
 
9.1%
23 1
 
4.5%
62 1
 
4.5%
18 1
 
4.5%
9 1
 
4.5%
7 1
 
4.5%
72 1
 
4.5%
Other values (8) 8
36.4%
ValueCountFrequency (%)
7 1
4.5%
8 1
4.5%
9 1
4.5%
10 2
9.1%
15 1
4.5%
18 1
4.5%
19 2
9.1%
20 2
9.1%
21 1
4.5%
23 1
4.5%
ValueCountFrequency (%)
72 1
4.5%
62 1
4.5%
60 1
4.5%
56 1
4.5%
35 1
4.5%
31 1
4.5%
29 2
9.1%
27 1
4.5%
23 1
4.5%
21 1
4.5%

인원
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.863636
Minimum7
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-01-28T17:40:35.955562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile9.05
Q120
median29.5
Q340.25
95-th percentile78.85
Maximum90
Range83
Interquartile range (IQR)20.25

Descriptive statistics

Standard deviation23.91711
Coefficient of variation (CV)0.68601879
Kurtosis0.35717007
Mean34.863636
Median Absolute Deviation (MAD)10.5
Skewness1.1137864
Sum767
Variance572.02814
MonotonicityNot monotonic
2024-01-28T17:40:36.054655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20 2
 
9.1%
31 2
 
9.1%
36 1
 
4.5%
79 1
 
4.5%
12 1
 
4.5%
7 1
 
4.5%
27 1
 
4.5%
44 1
 
4.5%
28 1
 
4.5%
90 1
 
4.5%
Other values (10) 10
45.5%
ValueCountFrequency (%)
7 1
4.5%
9 1
4.5%
10 1
4.5%
12 1
4.5%
15 1
4.5%
20 2
9.1%
23 1
4.5%
24 1
4.5%
27 1
4.5%
28 1
4.5%
ValueCountFrequency (%)
90 1
4.5%
79 1
4.5%
76 1
4.5%
72 1
4.5%
44 1
4.5%
41 1
4.5%
38 1
4.5%
36 1
4.5%
34 1
4.5%
31 2
9.1%

Interactions

2024-01-28T17:40:35.033307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:40:34.866064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:40:35.113084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:40:34.953530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T17:40:36.135779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동별가구인원
동별1.0001.0001.000
가구1.0001.0000.984
인원1.0000.9841.000
2024-01-28T17:40:36.209146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가구인원
가구1.0000.983
인원0.9831.000

Missing values

2024-01-28T17:40:35.187768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T17:40:35.252289image/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

동별가구인원
0부평1동1920
1부평2동3541
2부평3동6072
3부평4동5676
4부평5동3138
5부평6동2131
6산곡1동1523
7산곡2동1010
8산곡3동2024
9산곡4동89
동별가구인원
12갈산1동2331
13갈산2동2934
14삼산1동7290
15삼산2동2028
16부개1동2944
17부개2동1927
18부개3동77
19일신동912
20십정1동1820
21십정2동6279