Overview

Dataset statistics

Number of variables3
Number of observations476
Missing cells23
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.2 KiB
Average record size in memory26.3 B

Variable types

Numeric2
Categorical1

Dataset

Description- 시도별 합계 출산율 정보를 제공합니다. - 합계 출산율은 가임여성 1명이 평균적으로 몇 명의 자녀를 낳는가를 의미합니다. - 단위: 가임여성 1명당 명 - 데이터 제공처: KOSIS 국가통계포털
Author제주특별자치도 미래성장과
URLhttps://www.jejudatahub.net/data/view/data/884

Alerts

기준 연도 is highly overall correlated with 합계 출산율High correlation
합계 출산율 is highly overall correlated with 기준 연도High correlation
합계 출산율 has 23 (4.8%) missing valuesMissing

Reproduction

Analysis started2023-12-11 20:11:03.269373
Analysis finished2023-12-11 20:11:03.825923
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준 연도
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2006.5
Minimum1993
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-12T05:11:03.881426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1993
5-th percentile1994
Q11999.75
median2006.5
Q32013.25
95-th percentile2019
Maximum2020
Range27
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.0862456
Coefficient of variation (CV)0.0040300252
Kurtosis-1.2030869
Mean2006.5
Median Absolute Deviation (MAD)7
Skewness0
Sum955094
Variance65.387368
MonotonicityDecreasing
2023-12-12T05:11:03.991735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
2020 17
 
3.6%
2005 17
 
3.6%
1993 17
 
3.6%
1994 17
 
3.6%
1995 17
 
3.6%
1996 17
 
3.6%
1997 17
 
3.6%
1998 17
 
3.6%
1999 17
 
3.6%
2000 17
 
3.6%
Other values (18) 306
64.3%
ValueCountFrequency (%)
1993 17
3.6%
1994 17
3.6%
1995 17
3.6%
1996 17
3.6%
1997 17
3.6%
1998 17
3.6%
1999 17
3.6%
2000 17
3.6%
2001 17
3.6%
2002 17
3.6%
ValueCountFrequency (%)
2020 17
3.6%
2019 17
3.6%
2018 17
3.6%
2017 17
3.6%
2016 17
3.6%
2015 17
3.6%
2014 17
3.6%
2013 17
3.6%
2012 17
3.6%
2011 17
3.6%

시도
Categorical

Distinct17
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
서울특별시
 
28
부산광역시
 
28
대구광역시
 
28
인천광역시
 
28
광주광역시
 
28
Other values (12)
336 

Length

Max length7
Median length5
Mean length4.6470588
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row부산광역시
3rd row대구광역시
4th row인천광역시
5th row광주광역시

Common Values

ValueCountFrequency (%)
서울특별시 28
 
5.9%
부산광역시 28
 
5.9%
대구광역시 28
 
5.9%
인천광역시 28
 
5.9%
광주광역시 28
 
5.9%
대전광역시 28
 
5.9%
울산광역시 28
 
5.9%
세종특별자치시 28
 
5.9%
경기도 28
 
5.9%
강원도 28
 
5.9%
Other values (7) 196
41.2%

Length

2023-12-12T05:11:04.118387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 28
 
5.9%
강원도 28
 
5.9%
경상남도 28
 
5.9%
경상북도 28
 
5.9%
전라남도 28
 
5.9%
전라북도 28
 
5.9%
충청남도 28
 
5.9%
충청북도 28
 
5.9%
경기도 28
 
5.9%
부산광역시 28
 
5.9%
Other values (7) 196
41.2%

합계 출산율
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct353
Distinct (%)77.9%
Missing23
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean1.3372318
Minimum0.642
Maximum1.893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-12T05:11:04.307865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.642
5-th percentile0.9442
Q11.184
median1.321
Q31.518
95-th percentile1.7604
Maximum1.893
Range1.251
Interquartile range (IQR)0.334

Descriptive statistics

Standard deviation0.2451902
Coefficient of variation (CV)0.18335655
Kurtosis-0.48363435
Mean1.3372318
Median Absolute Deviation (MAD)0.168
Skewness-0.0080651176
Sum605.766
Variance0.060118236
MonotonicityNot monotonic
2023-12-12T05:11:04.467614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.272 4
 
0.8%
1.186 4
 
0.8%
1.261 3
 
0.6%
1.358 3
 
0.6%
1.566 3
 
0.6%
1.274 3
 
0.6%
1.338 3
 
0.6%
1.234 3
 
0.6%
1.642 3
 
0.6%
0.94 3
 
0.6%
Other values (343) 421
88.4%
(Missing) 23
 
4.8%
ValueCountFrequency (%)
0.642 1
0.2%
0.717 1
0.2%
0.747 1
0.2%
0.761 1
0.2%
0.805 1
0.2%
0.807 1
0.2%
0.811 1
0.2%
0.827 1
0.2%
0.829 1
0.2%
0.836 1
0.2%
ValueCountFrequency (%)
1.893 1
0.2%
1.867 1
0.2%
1.861 1
0.2%
1.847 1
0.2%
1.83 1
0.2%
1.828 1
0.2%
1.825 1
0.2%
1.821 1
0.2%
1.818 1
0.2%
1.815 1
0.2%

Interactions

2023-12-12T05:11:03.489152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:11:03.340748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:11:03.571351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:11:03.410644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T05:11:04.575266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준 연도시도합계 출산율
기준 연도1.0000.0000.765
시도0.0001.0000.494
합계 출산율0.7650.4941.000
2023-12-12T05:11:04.663257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준 연도합계 출산율시도
기준 연도1.000-0.6370.000
합계 출산율-0.6371.0000.215
시도0.0000.2151.000

Missing values

2023-12-12T05:11:03.734733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T05:11:03.799859image/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

기준 연도시도합계 출산율
02020서울특별시0.642
12020부산광역시0.747
22020대구광역시0.807
32020인천광역시0.829
42020광주광역시0.811
52020대전광역시0.805
62020울산광역시0.984
72020세종특별자치시1.277
82020경기도0.878
92020강원도1.036
기준 연도시도합계 출산율
4661993세종특별자치시<NA>
4671993경기도1.861
4681993강원도1.518
4691993충청북도1.715
4701993충청남도1.602
4711993전라북도1.607
4721993전라남도1.642
4731993경상북도1.613
4741993경상남도1.79
4751993제주특별자치도1.847