Overview

Dataset statistics

Number of variables3
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory678.0 B
Average record size in memory30.8 B

Variable types

Text1
Numeric1
DateTime1

Dataset

Description김천시의 데이터목록등록 가능한 기초생활수급자(생계급여,의료급여,주거급여,교육급여)읍면동 인원수(중복제외)를 통계자료를 활용하여 작성한 파일각 읍면동별 기초수급자의 인원수가 차이가 있으며 기초수급자 자격은 재산소득등의 사유에 따라 변동이 가능하여 숫자는 동일해도 대상자가 변동될 가능성도 있음
Author경상북도 김천시
URLhttps://www.data.go.kr/data/15126776/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
행정동명 has unique valuesUnique
인원 수(명) has unique valuesUnique

Reproduction

Analysis started2024-03-14 23:03:53.784798
Analysis finished2024-03-14 23:03:54.496885
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size304.0 B
2024-03-15T08:03:55.060722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.0454545
Min length2

Characters and Unicode

Total characters67
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row아포읍
2nd row농소면
3rd row남면
4th row개령면
5th row감문면
ValueCountFrequency (%)
아포읍 1
 
4.5%
농소면 1
 
4.5%
지좌동 1
 
4.5%
대곡동 1
 
4.5%
대신동 1
 
4.5%
양금동 1
 
4.5%
평화남산동 1
 
4.5%
자산동 1
 
4.5%
증산면 1
 
4.5%
대덕면 1
 
4.5%
Other values (12) 12
54.5%
2024-03-15T08:03:56.090914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 14
20.9%
동 7
 
10.4%
산 4
 
6.0%
대 4
 
6.0%
곡 2
 
3.0%
남 2
 
3.0%
항 2
 
3.0%
감 2
 
3.0%
지 2
 
3.0%
아 1
 
1.5%
Other values (27) 27
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 14
20.9%
동 7
 
10.4%
산 4
 
6.0%
대 4
 
6.0%
곡 2
 
3.0%
남 2
 
3.0%
항 2
 
3.0%
감 2
 
3.0%
지 2
 
3.0%
아 1
 
1.5%
Other values (27) 27
40.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 14
20.9%
동 7
 
10.4%
산 4
 
6.0%
대 4
 
6.0%
곡 2
 
3.0%
남 2
 
3.0%
항 2
 
3.0%
감 2
 
3.0%
지 2
 
3.0%
아 1
 
1.5%
Other values (27) 27
40.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 14
20.9%
동 7
 
10.4%
산 4
 
6.0%
대 4
 
6.0%
곡 2
 
3.0%
남 2
 
3.0%
항 2
 
3.0%
감 2
 
3.0%
지 2
 
3.0%
아 1
 
1.5%
Other values (27) 27
40.3%

인원 수(명)
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean367.22727
Minimum52
Maximum1351
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size326.0 B
2024-03-15T08:03:56.477088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum52
5-th percentile82.25
Q1138.75
median179
Q3349
95-th percentile1314
Maximum1351
Range1299
Interquartile range (IQR)210.25

Descriptive statistics

Standard deviation386.77888
Coefficient of variation (CV)1.0532412
Kurtosis2.1121073
Mean367.22727
Median Absolute Deviation (MAD)94.5
Skewness1.7305392
Sum8079
Variance149597.9
MonotonicityNot monotonic
2024-03-15T08:03:56.883545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
351 1
 
4.5%
52 1
 
4.5%
340 1
 
4.5%
896 1
 
4.5%
1351 1
 
4.5%
1336 1
 
4.5%
301 1
 
4.5%
778 1
 
4.5%
609 1
 
4.5%
82 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
52 1
4.5%
82 1
4.5%
87 1
4.5%
94 1
4.5%
99 1
4.5%
135 1
4.5%
150 1
4.5%
153 1
4.5%
163 1
4.5%
174 1
4.5%
ValueCountFrequency (%)
1351 1
4.5%
1336 1
4.5%
896 1
4.5%
778 1
4.5%
609 1
4.5%
351 1
4.5%
343 1
4.5%
340 1
4.5%
301 1
4.5%
227 1
4.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size304.0 B
Minimum2024-02-20 00:00:00
Maximum2024-02-20 00:00:00
2024-03-15T08:03:57.233767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:03:57.461371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T08:03:53.904703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T08:03:57.579689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동명인원 수(명)
행정동명1.0001.000
인원 수(명)1.0001.000

Missing values

2024-03-15T08:03:54.231725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T08:03:54.428274image/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

행정동명인원 수(명)데이터기준일자
0아포읍3512024-02-20
1농소면1532024-02-20
2남면1502024-02-20
3개령면942024-02-20
4감문면2272024-02-20
5어모면3432024-02-20
6봉산면1632024-02-20
7대항면1752024-02-20
8감천면872024-02-20
9조마면1352024-02-20
행정동명인원 수(명)데이터기준일자
12부항면522024-02-20
13대덕면1742024-02-20
14증산면822024-02-20
15자산동6092024-02-20
16평화남산동7782024-02-20
17양금동3012024-02-20
18대신동13362024-02-20
19대곡동13512024-02-20
20지좌동8962024-02-20
21율곡동3402024-02-20