Overview

Dataset statistics

Number of variables4
Number of observations175
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory34.8 B

Variable types

Categorical3
Numeric1

Dataset

Description경상남도 창원시의 월별, 구별 유동인구수입니다. 항목은 기준년월, 소지역블럭코드, 구, 유동인구수 입니다.
Author경상남도 창원시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15091829

Alerts

구단위코드 is highly overall correlated with 유동인구수 and 1 other fieldsHigh correlation
구 is highly overall correlated with 유동인구수 and 1 other fieldsHigh correlation
유동인구수 is highly overall correlated with 구단위코드 and 1 other fieldsHigh correlation
유동인구수 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:55:34.565158
Analysis finished2023-12-11 00:55:34.906802
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

Distinct35
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2020-01
 
5
2020-10
 
5
2020-03
 
5
2020-04
 
5
2020-05
 
5
Other values (30)
150 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-01
2nd row2020-01
3rd row2020-01
4th row2020-01
5th row2020-01

Common Values

ValueCountFrequency (%)
2020-01 5
 
2.9%
2020-10 5
 
2.9%
2020-03 5
 
2.9%
2020-04 5
 
2.9%
2020-05 5
 
2.9%
2020-06 5
 
2.9%
2020-07 5
 
2.9%
2020-08 5
 
2.9%
2021-05 5
 
2.9%
2020-02 5
 
2.9%
Other values (25) 125
71.4%

Length

2023-12-11T09:55:34.967667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-01 5
 
2.9%
2021-07 5
 
2.9%
2021-09 5
 
2.9%
2021-10 5
 
2.9%
2021-11 5
 
2.9%
2021-12 5
 
2.9%
2022-01 5
 
2.9%
2022-02 5
 
2.9%
2021-08 5
 
2.9%
2022-03 5
 
2.9%
Other values (25) 125
71.4%

구단위코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
48121
35 
48123
35 
48125
35 
48127
35 
48129
35 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48121
2nd row48123
3rd row48125
4th row48127
5th row48129

Common Values

ValueCountFrequency (%)
48121 35
20.0%
48123 35
20.0%
48125 35
20.0%
48127 35
20.0%
48129 35
20.0%

Length

2023-12-11T09:55:35.078451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:55:35.186825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48121 35
20.0%
48123 35
20.0%
48125 35
20.0%
48127 35
20.0%
48129 35
20.0%

구
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
의창구
35 
성산구
35 
마산합포구
35 
마산회원구
35 
진해구
35 

Length

Max length5
Median length3
Mean length3.8
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의창구
2nd row성산구
3rd row마산합포구
4th row마산회원구
5th row진해구

Common Values

ValueCountFrequency (%)
의창구 35
20.0%
성산구 35
20.0%
마산합포구 35
20.0%
마산회원구 35
20.0%
진해구 35
20.0%

Length

2023-12-11T09:55:35.304621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:55:35.411927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의창구 35
20.0%
성산구 35
20.0%
마산합포구 35
20.0%
마산회원구 35
20.0%
진해구 35
20.0%

유동인구수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct175
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16640070
Minimum10452688
Maximum24329496
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-11T09:55:35.536677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10452688
5-th percentile13547479
Q114163614
median15732771
Q319051028
95-th percentile23064076
Maximum24329496
Range13876808
Interquartile range (IQR)4887414

Descriptive statistics

Standard deviation3240643.2
Coefficient of variation (CV)0.19474937
Kurtosis-0.44610294
Mean16640070
Median Absolute Deviation (MAD)1763086
Skewness0.80213377
Sum2.9120123 × 109
Variance1.0501768 × 1013
MonotonicityNot monotonic
2023-12-11T09:55:35.697287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19858672 1
 
0.6%
24125985 1
 
0.6%
15470115 1
 
0.6%
13637498 1
 
0.6%
13627854 1
 
0.6%
16428321 1
 
0.6%
23039675 1
 
0.6%
15614098 1
 
0.6%
13907649 1
 
0.6%
13867184 1
 
0.6%
Other values (165) 165
94.3%
ValueCountFrequency (%)
10452688 1
0.6%
10638427 1
0.6%
11851428 1
0.6%
12208321 1
0.6%
12302191 1
0.6%
12477835 1
0.6%
12961831 1
0.6%
13444608 1
0.6%
13518507 1
0.6%
13559896 1
0.6%
ValueCountFrequency (%)
24329496 1
0.6%
24125985 1
0.6%
23907304 1
0.6%
23676880 1
0.6%
23457824 1
0.6%
23263935 1
0.6%
23199803 1
0.6%
23197936 1
0.6%
23121011 1
0.6%
23039675 1
0.6%

Interactions

2023-12-11T09:55:34.693461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:55:35.802661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년월구단위코드구유동인구수
기준년월1.0000.0000.0000.000
구단위코드0.0001.0001.0000.934
구0.0001.0001.0000.934
유동인구수0.0000.9340.9341.000
2023-12-11T09:55:35.890907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구단위코드기준년월구
구단위코드1.0000.0001.000
기준년월0.0001.0000.000
구1.0000.0001.000
2023-12-11T09:55:35.965951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유동인구수기준년월구단위코드구
유동인구수1.0000.0000.6440.644
기준년월0.0001.0000.0000.000
구단위코드0.6440.0001.0001.000
구0.6440.0001.0001.000

Missing values

2023-12-11T09:55:34.805218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:55:34.877368image/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

기준년월구단위코드구유동인구수
02020-0148121의창구19858672
12020-0148123성산구24125985
22020-0148125마산합포구16513981
32020-0148127마산회원구16183841
42020-0148129진해구15441798
52020-0248121의창구18029590
62020-0248123성산구21798043
72020-0248125마산합포구15027378
82020-0248127마산회원구14641041
92020-0248129진해구14390647
기준년월구단위코드구유동인구수
1652022-1048121의창구17285468
1662022-1048123성산구23676880
1672022-1048125마산합포구16375569
1682022-1048127마산회원구14275937
1692022-1048129진해구14201601
1702022-1148121의창구16601049
1712022-1148123성산구23457824
1722022-1148125마산합포구15636846
1732022-1148127마산회원구13969685
1742022-1148129진해구13706191