Overview

Dataset statistics

Number of variables5
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory48.4 B

Variable types

Categorical2
Numeric3

Dataset

Description광주광역시 연도별(2018~2022) 주민등록인구현황 통계입니다. 주민등록인구는 주민등록신고에 기반한 통계로 매월 말일을 기준으로 집계합니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15114070/fileData.do

Alerts

총인구수(명) is highly overall correlated with 남자인구수(명) and 2 other fieldsHigh correlation
남자인구수(명) is highly overall correlated with 총인구수(명) and 2 other fieldsHigh correlation
여자인구수(명) is highly overall correlated with 총인구수(명) and 2 other fieldsHigh correlation
구분 is highly overall correlated with 총인구수(명) and 2 other fieldsHigh correlation
총인구수(명) has unique valuesUnique

Reproduction

Analysis started2024-04-17 18:36:00.184685
Analysis finished2024-04-17 18:36:01.091785
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2018
6 
2019
6 
2020
6 
2021
6 
2022
6 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 6
20.0%
2019 6
20.0%
2020 6
20.0%
2021 6
20.0%
2022 6
20.0%

Length

2024-04-18T03:36:01.138027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:36:01.215910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 6
20.0%
2019 6
20.0%
2020 6
20.0%
2021 6
20.0%
2022 6
20.0%

구분
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
동구
5 
서구
5 
남구
5 
북구
5 
광산구
5 
Other values (2)
5 

Length

Max length5
Median length2
Mean length2.5666667
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row동구
2nd row서구
3rd row남구
4th row북구
5th row광산구

Common Values

ValueCountFrequency (%)
동구 5
16.7%
서구 5
16.7%
남구 5
16.7%
북구 5
16.7%
광산구 5
16.7%
광주광역시 4
13.3%
광주 1
 
3.3%

Length

2024-04-18T03:36:01.306046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:36:01.390728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동구 5
16.7%
서구 5
16.7%
남구 5
16.7%
북구 5
16.7%
광산구 5
16.7%
광주광역시 4
13.3%
광주 1
 
3.3%

총인구수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean482568.47
Minimum94475
Maximum1459336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T03:36:01.480874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum94475
5-th percentile100525.4
Q1215773.5
median352413
Q3429601.75
95-th percentile1453585.3
Maximum1459336
Range1364861
Interquartile range (IQR)213828.25

Descriptive statistics

Standard deviation453378.64
Coefficient of variation (CV)0.93951154
Kurtosis1.159575
Mean482568.47
Median Absolute Deviation (MAD)110856.5
Skewness1.6206066
Sum14477054
Variance2.0555219 × 1011
MonotonicityNot monotonic
2024-04-18T03:36:01.584500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
94475 1
 
3.3%
405579 1
 
3.3%
1431050 1
 
3.3%
400654 1
 
3.3%
424707 1
 
3.3%
212379 1
 
3.3%
287401 1
 
3.3%
105909 1
 
3.3%
1441611 1
 
3.3%
404221 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
94475 1
3.3%
98585 1
3.3%
102897 1
3.3%
103470 1
3.3%
105909 1
3.3%
212379 1
3.3%
214579 1
3.3%
215575 1
3.3%
216369 1
3.3%
218060 1
3.3%
ValueCountFrequency (%)
1459336 1
3.3%
1456468 1
3.3%
1450062 1
3.3%
1441611 1
3.3%
1431050 1
3.3%
439773 1
3.3%
433533 1
3.3%
430431 1
3.3%
427114 1
3.3%
424707 1
3.3%

남자인구수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean260797.83
Minimum46902
Maximum722581
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T03:36:01.680113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46902
5-th percentile49703.95
Q1104509.5
median202725
Q3214847.75
95-th percentile719213.6
Maximum722581
Range675679
Interquartile range (IQR)110338.25

Descriptive statistics

Standard deviation237639.77
Coefficient of variation (CV)0.91120301
Kurtosis0.2411344
Mean260797.83
Median Absolute Deviation (MAD)79848.5
Skewness1.3727793
Sum7823935
Variance5.647266 × 1010
MonotonicityNot monotonic
2024-04-18T03:36:01.770149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
713015 2
 
6.7%
46902 1
 
3.3%
149540 1
 
3.3%
707299 1
 
3.3%
201971 1
 
3.3%
210416 1
 
3.3%
101881 1
 
3.3%
140726 1
 
3.3%
52305 1
 
3.3%
203707 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
46902 1
3.3%
48799 1
3.3%
50810 1
3.3%
52305 1
3.3%
101881 1
3.3%
103257 1
3.3%
103542 1
3.3%
104337 1
3.3%
105027 1
3.3%
140726 1
3.3%
ValueCountFrequency (%)
722581 1
3.3%
720740 1
3.3%
717348 1
3.3%
713015 2
6.7%
707299 1
3.3%
218323 1
3.3%
215260 1
3.3%
213611 1
3.3%
211999 1
3.3%
210416 1
3.3%

여자인구수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean266375.33
Minimum47573
Maximum736755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-18T03:36:01.863597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47573
5-th percentile50821.45
Q1112283
median199598.5
Q3217909.75
95-th percentile734371.7
Maximum736755
Range689182
Interquartile range (IQR)105626.75

Descriptive statistics

Standard deviation242225.32
Coefficient of variation (CV)0.90933842
Kurtosis0.26511204
Mean266375.33
Median Absolute Deviation (MAD)69744.5
Skewness1.3875132
Sum7991260
Variance5.8673107 × 1010
MonotonicityNot monotonic
2024-04-18T03:36:01.961492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
728596 2
 
6.7%
47573 1
 
3.3%
154632 1
 
3.3%
723751 1
 
3.3%
198683 1
 
3.3%
214291 1
 
3.3%
110498 1
 
3.3%
146675 1
 
3.3%
53604 1
 
3.3%
200514 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
47573 1
3.3%
49786 1
3.3%
52087 1
3.3%
53604 1
3.3%
110498 1
3.3%
111322 1
3.3%
112032 1
3.3%
112033 1
3.3%
113033 1
3.3%
146675 1
3.3%
ValueCountFrequency (%)
736755 1
3.3%
735728 1
3.3%
732714 1
3.3%
728596 2
6.7%
723751 1
3.3%
221450 1
3.3%
218273 1
3.3%
216820 1
3.3%
215115 1
3.3%
214291 1
3.3%

Interactions

2024-04-18T03:36:00.739516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:36:00.325340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:36:00.521371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:36:00.813657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:36:00.389061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:36:00.591476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:36:00.879954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:36:00.455208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:36:00.659530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T03:36:02.028048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도구분총인구수(명)남자인구수(명)여자인구수(명)
연도1.0000.0000.0000.0000.000
구분0.0001.0001.0000.9540.954
총인구수(명)0.0001.0001.0000.9990.999
남자인구수(명)0.0000.9540.9991.0001.000
여자인구수(명)0.0000.9540.9991.0001.000
2024-04-18T03:36:02.100713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도구분
연도1.0000.000
구분0.0001.000
2024-04-18T03:36:02.162518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총인구수(명)남자인구수(명)여자인구수(명)연도구분
총인구수(명)1.0000.8820.8820.0000.941
남자인구수(명)0.8821.0000.9990.0000.896
여자인구수(명)0.8820.9991.0000.0000.896
연도0.0000.0000.0001.0000.000
구분0.9410.8960.8960.0001.000

Missing values

2024-04-18T03:36:00.986447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T03:36:01.064091image/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

연도구분총인구수(명)남자인구수(명)여자인구수(명)
02018동구944754690247573
12018서구304172149540154632
22018남구216369104337112032
32018북구439773218323221450
42018광산구404547203479201068
52018광주광역시1459336722581736755
62019동구985854879949786
72019서구300975147671153304
82019남구218060105027113033
92019북구433533215260218273
연도구분총인구수(명)남자인구수(명)여자인구수(명)
202021남구215575103542112033
212021북구427114211999215115
222021광산구404221203707200514
232021광주1441611713015728596
242022동구1059095230553604
252022서구287401140726146675
262022남구212379101881110498
272022북구424707210416214291
282022광산구400654201971198683
292022광주광역시1431050707299723751