Overview

Dataset statistics

Number of variables6
Number of observations173
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory52.8 B

Variable types

Categorical2
Numeric4

Dataset

Description경기도 용인시 자녀수별 세대 현황입니다. 읍면동, 자녀수, 세대수, 전체 자녀수 남, 전체 자녀수 여 데이터를 제공합니다.※ 데이터기준일자 : 2023-10-20
Author경기도 용인시
URLhttps://www.data.go.kr/data/15124563/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
자녀수 is highly overall correlated with 세대수 and 2 other fieldsHigh correlation
세대수 is highly overall correlated with 자녀수 and 2 other fieldsHigh correlation
전체 자녀수 남 is highly overall correlated with 자녀수 and 2 other fieldsHigh correlation
전체 자녀수 여 is highly overall correlated with 자녀수 and 2 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 11:58:08.553680
Analysis finished2023-12-12 11:58:10.678535
Duration2.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Categorical

Distinct38
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
남사읍
 
6
동천동
 
5
성복동
 
5
상현2동
 
5
양지면
 
5
Other values (33)
147 

Length

Max length5
Median length3
Mean length3.3757225
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row포곡읍
2nd row포곡읍
3rd row포곡읍
4th row포곡읍
5th row모현읍

Common Values

ValueCountFrequency (%)
남사읍 6
 
3.5%
동천동 5
 
2.9%
성복동 5
 
2.9%
상현2동 5
 
2.9%
양지면 5
 
2.9%
중앙동 5
 
2.9%
역북동 5
 
2.9%
유림동 5
 
2.9%
동부동 5
 
2.9%
영덕1동 5
 
2.9%
Other values (28) 122
70.5%

Length

2023-12-12T20:58:10.762492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남사읍 6
 
3.5%
보라동 5
 
2.9%
동천동 5
 
2.9%
구성동 5
 
2.9%
마북동 5
 
2.9%
신갈동 5
 
2.9%
동백2동 5
 
2.9%
동백3동 5
 
2.9%
죽전1동 5
 
2.9%
신봉동 5
 
2.9%
Other values (28) 122
70.5%

자녀수
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8092486
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T20:58:10.894998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3440333
Coefficient of variation (CV)0.47843162
Kurtosis-1.0895738
Mean2.8092486
Median Absolute Deviation (MAD)1
Skewness0.15021217
Sum486
Variance1.8064256
MonotonicityNot monotonic
2023-12-12T20:58:11.024762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 38
22.0%
2 38
22.0%
3 38
22.0%
4 38
22.0%
5 20
11.6%
6 1
 
0.6%
ValueCountFrequency (%)
1 38
22.0%
2 38
22.0%
3 38
22.0%
4 38
22.0%
5 20
11.6%
6 1
 
0.6%
ValueCountFrequency (%)
6 1
 
0.6%
5 20
11.6%
4 38
22.0%
3 38
22.0%
2 38
22.0%
1 38
22.0%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct129
Distinct (%)74.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean573.68786
Minimum1
Maximum2842
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T20:58:11.161879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q114
median200
Q31113
95-th percentile1889.4
Maximum2842
Range2841
Interquartile range (IQR)1099

Descriptive statistics

Standard deviation711.28013
Coefficient of variation (CV)1.2398382
Kurtosis0.69544636
Mean573.68786
Median Absolute Deviation (MAD)198
Skewness1.2310426
Sum99248
Variance505919.43
MonotonicityNot monotonic
2023-12-12T20:58:11.306510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 13
 
7.5%
15 5
 
2.9%
2 5
 
2.9%
3 5
 
2.9%
6 4
 
2.3%
5 4
 
2.3%
13 3
 
1.7%
8 2
 
1.2%
1512 2
 
1.2%
152 2
 
1.2%
Other values (119) 128
74.0%
ValueCountFrequency (%)
1 13
7.5%
2 5
 
2.9%
3 5
 
2.9%
5 4
 
2.3%
6 4
 
2.3%
7 2
 
1.2%
8 2
 
1.2%
10 2
 
1.2%
11 1
 
0.6%
12 1
 
0.6%
ValueCountFrequency (%)
2842 1
0.6%
2838 1
0.6%
2701 1
0.6%
2613 1
0.6%
2479 1
0.6%
2320 1
0.6%
2190 1
0.6%
1960 1
0.6%
1941 1
0.6%
1855 1
0.6%

전체 자녀수 남
Real number (ℝ)

HIGH CORRELATION 

Distinct141
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean477.39884
Minimum1
Maximum2821
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T20:58:11.494497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q128
median248
Q3674
95-th percentile1662.6
Maximum2821
Range2820
Interquartile range (IQR)646

Descriptive statistics

Standard deviation592.92498
Coefficient of variation (CV)1.2419908
Kurtosis2.7998119
Mean477.39884
Median Absolute Deviation (MAD)238
Skewness1.6888408
Sum82590
Variance351560.03
MonotonicityNot monotonic
2023-12-12T20:58:11.969532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 6
 
3.5%
1 5
 
2.9%
10 3
 
1.7%
28 3
 
1.7%
20 3
 
1.7%
7 3
 
1.7%
9 3
 
1.7%
58 2
 
1.2%
5 2
 
1.2%
16 2
 
1.2%
Other values (131) 141
81.5%
ValueCountFrequency (%)
1 5
2.9%
2 2
 
1.2%
3 6
3.5%
4 2
 
1.2%
5 2
 
1.2%
6 2
 
1.2%
7 3
1.7%
9 3
1.7%
10 3
1.7%
11 1
 
0.6%
ValueCountFrequency (%)
2821 1
0.6%
2767 1
0.6%
2616 1
0.6%
2213 1
0.6%
1972 1
0.6%
1746 1
0.6%
1731 1
0.6%
1724 1
0.6%
1665 1
0.6%
1661 1
0.6%

전체 자녀수 여
Real number (ℝ)

HIGH CORRELATION 

Distinct139
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean457.82659
Minimum1
Maximum2855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T20:58:12.141980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q129
median254
Q3628
95-th percentile1593.2
Maximum2855
Range2854
Interquartile range (IQR)599

Descriptive statistics

Standard deviation573.35506
Coefficient of variation (CV)1.2523411
Kurtosis3.3115679
Mean457.82659
Median Absolute Deviation (MAD)242
Skewness1.7873578
Sum79204
Variance328736.03
MonotonicityNot monotonic
2023-12-12T20:58:12.319793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 8
 
4.6%
2 4
 
2.3%
7 3
 
1.7%
1 3
 
1.7%
69 3
 
1.7%
8 3
 
1.7%
6 2
 
1.2%
29 2
 
1.2%
14 2
 
1.2%
223 2
 
1.2%
Other values (129) 141
81.5%
ValueCountFrequency (%)
1 3
 
1.7%
2 4
2.3%
3 1
 
0.6%
4 8
4.6%
5 1
 
0.6%
6 2
 
1.2%
7 3
 
1.7%
8 3
 
1.7%
10 2
 
1.2%
11 2
 
1.2%
ValueCountFrequency (%)
2855 1
0.6%
2635 1
0.6%
2610 1
0.6%
2167 1
0.6%
1948 1
0.6%
1748 1
0.6%
1665 1
0.6%
1652 1
0.6%
1631 1
0.6%
1568 1
0.6%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-10-20
173 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-20
2nd row2023-10-20
3rd row2023-10-20
4th row2023-10-20
5th row2023-10-20

Common Values

ValueCountFrequency (%)
2023-10-20 173
100.0%

Length

2023-12-12T20:58:12.497431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:58:12.616421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-20 173
100.0%

Interactions

2023-12-12T20:58:10.124714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:08.767354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:09.227136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:09.708377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:10.218713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:08.893575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:09.350484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:09.824022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:10.313857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:09.003595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:09.459260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:09.936902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:10.396249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:09.114606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:09.583820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:10.041951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:58:12.692404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동자녀수세대수전체 자녀수 남전체 자녀수 여
읍면동1.0000.0000.6120.0000.000
자녀수0.0001.0000.6170.7000.676
세대수0.6120.6171.0000.8930.901
전체 자녀수 남0.0000.7000.8931.0000.992
전체 자녀수 여0.0000.6760.9010.9921.000
2023-12-12T20:58:12.833226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자녀수세대수전체 자녀수 남전체 자녀수 여읍면동
자녀수1.000-0.889-0.823-0.8100.000
세대수-0.8891.0000.9810.9770.236
전체 자녀수 남-0.8230.9811.0000.9930.000
전체 자녀수 여-0.8100.9770.9931.0000.000
읍면동0.0000.2360.0000.0001.000

Missing values

2023-12-12T20:58:10.530391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:58:10.634356image/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

읍면동자녀수세대수전체 자녀수 남전체 자녀수 여데이터기준일자
0포곡읍19995604392023-10-20
1포곡읍21063109110352023-10-20
2포곡읍32183203342023-10-20
3포곡읍42451452023-10-20
4모현읍17603953652023-10-20
5모현읍28398957832023-10-20
6모현읍31572282432023-10-20
7모현읍41020202023-10-20
8모현읍51322023-10-20
9이동읍15552972582023-10-20
읍면동자녀수세대수전체 자녀수 남전체 자녀수 여데이터기준일자
163상현2동51412023-10-20
164상현3동113026746282023-10-20
165상현3동21395137514152023-10-20
166상현3동31652522432023-10-20
167상현3동4510102023-10-20
168성복동12479126312162023-10-20
169성복동22838282128552023-10-20
170성복동33755445812023-10-20
171성복동42548522023-10-20
172성복동51142023-10-20