Overview

Dataset statistics

Number of variables3
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory907.0 B
Average record size in memory29.3 B

Variable types

Text1
Numeric1
DateTime1

Dataset

Description경기도 시흥시 등록된 치매환자 거주지현황입니다. (시흥시 치매환자 거주지 현황에는 법정동, 치매환자수가 있습니다.)
URLhttps://www.data.go.kr/data/15029867/fileData.do

Alerts

데이터기준일 has constant value ""Constant
동이름 has unique valuesUnique
환자수 has 1 (3.2%) zerosZeros

Reproduction

Analysis started2023-12-12 04:38:35.895138
Analysis finished2023-12-12 04:38:36.274202
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

동이름
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T13:38:36.441579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters93
Distinct characters52
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

Unique31 ?
Unique (%)100.0%

Sample

1st row거모동
2nd row계수동
3rd row과림동
4th row광석동
5th row군자동
ValueCountFrequency (%)
거모동 1
 
3.2%
배곧동 1
 
3.2%
하중동 1
 
3.2%
하상동 1
 
3.2%
포동 1
 
3.2%
죽율동 1
 
3.2%
조남동 1
 
3.2%
정왕동 1
 
3.2%
장현동 1
 
3.2%
장곡동 1
 
3.2%
Other values (21) 21
67.7%
2023-12-12T13:38:36.864558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 31
33.3%
산 3
 
3.2%
현 3
 
3.2%
곡 3
 
3.2%
하 2
 
2.2%
화 2
 
2.2%
정 2
 
2.2%
장 2
 
2.2%
왕 2
 
2.2%
거 1
 
1.1%
Other values (42) 42
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 31
33.3%
산 3
 
3.2%
현 3
 
3.2%
곡 3
 
3.2%
하 2
 
2.2%
화 2
 
2.2%
정 2
 
2.2%
장 2
 
2.2%
왕 2
 
2.2%
거 1
 
1.1%
Other values (42) 42
45.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 31
33.3%
산 3
 
3.2%
현 3
 
3.2%
곡 3
 
3.2%
하 2
 
2.2%
화 2
 
2.2%
정 2
 
2.2%
장 2
 
2.2%
왕 2
 
2.2%
거 1
 
1.1%
Other values (42) 42
45.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 31
33.3%
산 3
 
3.2%
현 3
 
3.2%
곡 3
 
3.2%
하 2
 
2.2%
화 2
 
2.2%
정 2
 
2.2%
장 2
 
2.2%
왕 2
 
2.2%
거 1
 
1.1%
Other values (42) 42
45.2%

환자수
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.612903
Minimum0
Maximum527
Zeros1
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T13:38:37.023707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q17
median33
Q3114.5
95-th percentile291.5
Maximum527
Range527
Interquartile range (IQR)107.5

Descriptive statistics

Standard deviation116.98338
Coefficient of variation (CV)1.3664223
Kurtosis6.0307028
Mean85.612903
Median Absolute Deviation (MAD)28
Skewness2.2783194
Sum2654
Variance13685.112
MonotonicityNot monotonic
2023-12-12T13:38:37.170489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
5 4
 
12.9%
15 2
 
6.5%
29 2
 
6.5%
7 2
 
6.5%
108 1
 
3.2%
0 1
 
3.2%
74 1
 
3.2%
55 1
 
3.2%
48 1
 
3.2%
133 1
 
3.2%
Other values (15) 15
48.4%
ValueCountFrequency (%)
0 1
 
3.2%
1 1
 
3.2%
5 4
12.9%
6 1
 
3.2%
7 2
6.5%
11 1
 
3.2%
15 2
6.5%
27 1
 
3.2%
29 2
6.5%
33 1
 
3.2%
ValueCountFrequency (%)
527 1
3.2%
312 1
3.2%
271 1
3.2%
248 1
3.2%
159 1
3.2%
151 1
3.2%
133 1
3.2%
121 1
3.2%
108 1
3.2%
89 1
3.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2023-08-03 00:00:00
Maximum2023-08-03 00:00:00
2023-12-12T13:38:37.284631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:37.446512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T13:38:35.997531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:38:37.579436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동이름환자수
동이름1.0001.000
환자수1.0001.000

Missing values

2023-12-12T13:38:36.149941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:38:36.239317image/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

동이름환자수데이터기준일
0거모동1592023-08-03
1계수동72023-08-03
2과림동112023-08-03
3광석동52023-08-03
4군자동52023-08-03
5금이동62023-08-03
6논곡동292023-08-03
7능곡동1512023-08-03
8대야동2712023-08-03
9도창동332023-08-03
동이름환자수데이터기준일
21은행동2482023-08-03
22장곡동1212023-08-03
23장현동702023-08-03
24정왕동5272023-08-03
25조남동1332023-08-03
26죽율동152023-08-03
27포동482023-08-03
28하상동552023-08-03
29하중동742023-08-03
30화정동02023-08-03