Overview

Dataset statistics

Number of variables7
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory61.9 B

Variable types

Categorical2
Text1
Numeric3
DateTime1

Dataset

Description경기도 수원시 독거노인현황에 대한 데이터로 시도명, 시군구명, 읍면동명, 총인원수, 남, 여 등의 항목을 제공합니다.(구별,동별, 남녀별 독거노인수를 표시한 데이터로 주민등록상 1인가구 기준으로 작성하였으며 저소득 독거노인 집계와는 무관한 자료임.)
Author경기도 수원시
URLhttps://www.data.go.kr/data/15066474/fileData.do

Alerts

시도명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
총인원수 is highly overall correlated with 남 and 1 other fieldsHigh correlation
남 is highly overall correlated with 총인원수 and 1 other fieldsHigh correlation
여 is highly overall correlated with 총인원수 and 1 other fieldsHigh correlation
읍면동명 has unique valuesUnique
총인원수 has unique valuesUnique

Reproduction

Analysis started2024-03-14 14:16:15.205721
Analysis finished2024-03-14 14:16:18.006419
Duration2.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size480.0 B
수원시
44 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수원시 44
100.0%

Length

2024-03-14T23:16:18.112520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:16:18.281234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수원시 44
100.0%

시군구명
Categorical

Distinct4
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size480.0 B
권선구
12 
영통구
12 
장안구
10 
팔달구
10 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
권선구 12
27.3%
영통구 12
27.3%
장안구 10
22.7%
팔달구 10
22.7%

Length

2024-03-14T23:16:18.587427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:16:18.914342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
권선구 12
27.3%
영통구 12
27.3%
장안구 10
22.7%
팔달구 10
22.7%

읍면동명
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-03-14T23:16:19.806161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.5454545
Min length2

Characters and Unicode

Total characters156
Distinct characters51
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

Unique44 ?
Unique (%)100.0%

Sample

1st row파장동
2nd row율천동
3rd row정자1동
4th row정자2동
5th row정자3동
ValueCountFrequency (%)
파장동 1
 
2.3%
율천동 1
 
2.3%
매탄1동 1
 
2.3%
매산동 1
 
2.3%
고등동 1
 
2.3%
화서1동 1
 
2.3%
화서2동 1
 
2.3%
지동 1
 
2.3%
우만1동 1
 
2.3%
우만2동 1
 
2.3%
Other values (34) 34
77.3%
2024-03-14T23:16:20.869645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 44
28.2%
1 10
 
6.4%
2 10
 
6.4%
매 7
 
4.5%
3 4
 
2.6%
탄 4
 
2.6%
영 4
 
2.6%
통 3
 
1.9%
서 3
 
1.9%
선 3
 
1.9%
Other values (41) 64
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 131
84.0%
Decimal Number 25
 
16.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 44
33.6%
매 7
 
5.3%
탄 4
 
3.1%
영 4
 
3.1%
통 3
 
2.3%
서 3
 
2.3%
선 3
 
2.3%
화 3
 
2.3%
원 3
 
2.3%
자 3
 
2.3%
Other values (37) 54
41.2%
Decimal Number
ValueCountFrequency (%)
1 10
40.0%
2 10
40.0%
3 4
 
16.0%
4 1
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 131
84.0%
Common 25
 
16.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 44
33.6%
매 7
 
5.3%
탄 4
 
3.1%
영 4
 
3.1%
통 3
 
2.3%
서 3
 
2.3%
선 3
 
2.3%
화 3
 
2.3%
원 3
 
2.3%
자 3
 
2.3%
Other values (37) 54
41.2%
Common
ValueCountFrequency (%)
1 10
40.0%
2 10
40.0%
3 4
 
16.0%
4 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 131
84.0%
ASCII 25
 
16.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 44
33.6%
매 7
 
5.3%
탄 4
 
3.1%
영 4
 
3.1%
통 3
 
2.3%
서 3
 
2.3%
선 3
 
2.3%
화 3
 
2.3%
원 3
 
2.3%
자 3
 
2.3%
Other values (37) 54
41.2%
ASCII
ValueCountFrequency (%)
1 10
40.0%
2 10
40.0%
3 4
 
16.0%
4 1
 
4.0%

총인원수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean927.38636
Minimum233
Maximum1699
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T23:16:21.097320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum233
5-th percentile412.9
Q1577.75
median898
Q31253.75
95-th percentile1612.1
Maximum1699
Range1466
Interquartile range (IQR)676

Descriptive statistics

Standard deviation411.00677
Coefficient of variation (CV)0.44318829
Kurtosis-1.037974
Mean927.38636
Median Absolute Deviation (MAD)326.5
Skewness0.34013295
Sum40805
Variance168926.57
MonotonicityNot monotonic
2024-03-14T23:16:21.333903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1355 1
 
2.3%
569 1
 
2.3%
939 1
 
2.3%
1246 1
 
2.3%
579 1
 
2.3%
1041 1
 
2.3%
1607 1
 
2.3%
507 1
 
2.3%
1421 1
 
2.3%
460 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
233 1
2.3%
405 1
2.3%
412 1
2.3%
418 1
2.3%
431 1
2.3%
460 1
2.3%
484 1
2.3%
501 1
2.3%
507 1
2.3%
569 1
2.3%
ValueCountFrequency (%)
1699 1
2.3%
1685 1
2.3%
1613 1
2.3%
1607 1
2.3%
1548 1
2.3%
1504 1
2.3%
1421 1
2.3%
1402 1
2.3%
1356 1
2.3%
1355 1
2.3%

남
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean309
Minimum56
Maximum676
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T23:16:21.572339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum56
5-th percentile114.6
Q1168.25
median314.5
Q3423
95-th percentile559.25
Maximum676
Range620
Interquartile range (IQR)254.75

Descriptive statistics

Standard deviation158.75343
Coefficient of variation (CV)0.51376514
Kurtosis-0.88412317
Mean309
Median Absolute Deviation (MAD)144.5
Skewness0.40267664
Sum13596
Variance25202.651
MonotonicityNot monotonic
2024-03-14T23:16:21.922381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
199 2
 
4.5%
375 2
 
4.5%
476 1
 
2.3%
208 1
 
2.3%
416 1
 
2.3%
147 1
 
2.3%
410 1
 
2.3%
521 1
 
2.3%
126 1
 
2.3%
495 1
 
2.3%
Other values (32) 32
72.7%
ValueCountFrequency (%)
56 1
2.3%
113 1
2.3%
114 1
2.3%
118 1
2.3%
126 1
2.3%
131 1
2.3%
136 1
2.3%
147 1
2.3%
154 1
2.3%
160 1
2.3%
ValueCountFrequency (%)
676 1
2.3%
597 1
2.3%
563 1
2.3%
538 1
2.3%
521 1
2.3%
520 1
2.3%
498 1
2.3%
495 1
2.3%
476 1
2.3%
466 1
2.3%

여
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean618.38636
Minimum177
Maximum1147
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T23:16:22.324134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum177
5-th percentile293.2
Q1400.5
median585.5
Q3832.25
95-th percentile1078.8
Maximum1147
Range970
Interquartile range (IQR)431.75

Descriptive statistics

Standard deviation265.30222
Coefficient of variation (CV)0.42902339
Kurtosis-0.95602611
Mean618.38636
Median Absolute Deviation (MAD)210.5
Skewness0.3588597
Sum27209
Variance70385.266
MonotonicityNot monotonic
2024-03-14T23:16:22.945213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
300 3
 
6.8%
697 2
 
4.5%
879 1
 
2.3%
343 1
 
2.3%
596 1
 
2.3%
830 1
 
2.3%
432 1
 
2.3%
631 1
 
2.3%
1086 1
 
2.3%
381 1
 
2.3%
Other values (31) 31
70.5%
ValueCountFrequency (%)
177 1
 
2.3%
276 1
 
2.3%
292 1
 
2.3%
300 3
6.8%
302 1
 
2.3%
318 1
 
2.3%
343 1
 
2.3%
372 1
 
2.3%
381 1
 
2.3%
407 1
 
2.3%
ValueCountFrequency (%)
1147 1
2.3%
1102 1
2.3%
1086 1
2.3%
1038 1
2.3%
1028 1
2.3%
945 1
2.3%
937 1
2.3%
926 1
2.3%
912 1
2.3%
879 1
2.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size480.0 B
Minimum2023-12-31 00:00:00
Maximum2023-12-31 00:00:00
2024-03-14T23:16:23.284278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:16:23.576524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-14T23:16:16.942161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:16:15.457397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:16:16.207698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:16:17.187999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:16:15.714704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:16:16.463525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:16:17.430769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:16:15.968584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:16:16.708542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:16:23.787140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명읍면동명총인원수남여
시군구명1.0001.0000.2140.5680.148
읍면동명1.0001.0001.0001.0001.000
총인원수0.2141.0001.0000.6960.958
남0.5681.0000.6961.0000.491
여0.1481.0000.9580.4911.000
2024-03-14T23:16:24.048258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총인원수남여시군구명
총인원수1.0000.9510.9800.075
남0.9511.0000.8830.341
여0.9800.8831.0000.000
시군구명0.0750.3410.0001.000

Missing values

2024-03-14T23:16:17.727486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:16:17.928473image/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

시도명시군구명읍면동명총인원수남여데이터기준일자
0수원시장안구파장동13554768792023-12-31
1수원시장안구율천동10183216972023-12-31
2수원시장안구정자1동9252127132023-12-31
3수원시장안구정자2동150446610382023-12-31
4수원시장안구정자3동6421694732023-12-31
5수원시장안구영화동16136769372023-12-31
6수원시장안구송죽동9803756052023-12-31
7수원시장안구조원1동169959711022023-12-31
8수원시장안구조원2동5841544302023-12-31
9수원시장안구연무동13564449122023-12-31
시도명시군구명읍면동명총인원수남여데이터기준일자
34수원시영통구매탄3동7582285302023-12-31
35수원시영통구매탄4동7691995702023-12-31
36수원시영통구원천동11333407932023-12-31
37수원시영통구광교1동4311313002023-12-31
38수원시영통구광교2동7472105372023-12-31
39수원시영통구영통1동5741144602023-12-31
40수원시영통구영통2동4051132922023-12-31
41수원시영통구영통3동4841663182023-12-31
42수원시영통구망포1동4181183002023-12-31
43수원시영통구망포2동233561772023-12-31