Overview

Dataset statistics

Number of variables6
Number of observations171
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory51.8 B

Variable types

Categorical2
Text1
Numeric3

Dataset

Description부산광역시_기장군_읍면별인구현황_20171130
Author부산광역시 기장군
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3072537

Alerts

행정구역(군) has constant value ""Constant
세대수 is highly overall correlated with 인구수(남) and 1 other fieldsHigh correlation
인구수(남) is highly overall correlated with 세대수 and 1 other fieldsHigh correlation
인구수(여) is highly overall correlated with 세대수 and 1 other fieldsHigh correlation
행정구역(리(통)) has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:31:52.531883
Analysis finished2023-12-10 17:31:55.086218
Duration2.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정구역(군)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
기장군
171 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기장군 171
100.0%

Length

2023-12-11T02:31:55.246141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:31:55.497971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기장군 171
100.0%

행정구역(읍면)
Categorical

Distinct5
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
정관읍
53 
기장읍
45 
일광면
26 
장안읍
25 
철마면
22 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정관읍 53
31.0%
기장읍 45
26.3%
일광면 26
15.2%
장안읍 25
14.6%
철마면 22
12.9%

Length

2023-12-11T02:31:55.741337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:31:56.020557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정관읍 53
31.0%
기장읍 45
26.3%
일광면 26
15.2%
장안읍 25
14.6%
철마면 22
12.9%

행정구역(리(통))
Text

UNIQUE 

Distinct171
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-11T02:31:56.658478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length7.2046784
Min length6

Characters and Unicode

Total characters1232
Distinct characters112
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)100.0%

Sample

1st row동부1(1통)
2nd row동부2(2통)
3rd row서부(3통)
4th row동서(4통)
5th row두화(5통)
ValueCountFrequency (%)
동부1(1통 1
 
0.6%
방곡4(47통 1
 
0.6%
후동(4통 1
 
0.6%
용수7(40통 1
 
0.6%
매학(41통 1
 
0.6%
모전8(42통 1
 
0.6%
용수8(43통 1
 
0.6%
달산6(44통 1
 
0.6%
대전(45통 1
 
0.6%
방곡3(46통 1
 
0.6%
Other values (161) 161
94.2%
2023-12-11T02:31:57.652326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 171
13.9%
통 171
13.9%
) 171
13.9%
1 84
 
6.8%
2 73
 
5.9%
3 51
 
4.1%
4 43
 
3.5%
5 27
 
2.2%
6 21
 
1.7%
곡 17
 
1.4%
Other values (102) 403
32.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 524
42.5%
Decimal Number 366
29.7%
Open Punctuation 171
 
13.9%
Close Punctuation 171
 
13.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
통 171
32.6%
곡 17
 
3.2%
동 16
 
3.1%
전 16
 
3.1%
리 13
 
2.5%
산 13
 
2.5%
수 13
 
2.5%
용 11
 
2.1%
모 10
 
1.9%
덕 9
 
1.7%
Other values (90) 235
44.8%
Decimal Number
ValueCountFrequency (%)
1 84
23.0%
2 73
19.9%
3 51
13.9%
4 43
11.7%
5 27
 
7.4%
6 21
 
5.7%
0 17
 
4.6%
7 17
 
4.6%
9 17
 
4.6%
8 16
 
4.4%
Open Punctuation
ValueCountFrequency (%)
( 171
100.0%
Close Punctuation
ValueCountFrequency (%)
) 171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 708
57.5%
Hangul 524
42.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
통 171
32.6%
곡 17
 
3.2%
동 16
 
3.1%
전 16
 
3.1%
리 13
 
2.5%
산 13
 
2.5%
수 13
 
2.5%
용 11
 
2.1%
모 10
 
1.9%
덕 9
 
1.7%
Other values (90) 235
44.8%
Common
ValueCountFrequency (%)
( 171
24.2%
) 171
24.2%
1 84
11.9%
2 73
10.3%
3 51
 
7.2%
4 43
 
6.1%
5 27
 
3.8%
6 21
 
3.0%
0 17
 
2.4%
7 17
 
2.4%
Other values (2) 33
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 708
57.5%
Hangul 524
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 171
24.2%
) 171
24.2%
1 84
11.9%
2 73
10.3%
3 51
 
7.2%
4 43
 
6.1%
5 27
 
3.8%
6 21
 
3.0%
0 17
 
2.4%
7 17
 
2.4%
Other values (2) 33
 
4.7%
Hangul
ValueCountFrequency (%)
통 171
32.6%
곡 17
 
3.2%
동 16
 
3.1%
전 16
 
3.1%
리 13
 
2.5%
산 13
 
2.5%
수 13
 
2.5%
용 11
 
2.1%
모 10
 
1.9%
덕 9
 
1.7%
Other values (90) 235
44.8%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct144
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean383.08772
Minimum3
Maximum1960
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T02:31:57.966052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile40.5
Q168
median160
Q3641.5
95-th percentile1126.5
Maximum1960
Range1957
Interquartile range (IQR)573.5

Descriptive statistics

Standard deviation420.78941
Coefficient of variation (CV)1.0984153
Kurtosis1.628688
Mean383.08772
Median Absolute Deviation (MAD)114
Skewness1.4254382
Sum65508
Variance177063.73
MonotonicityNot monotonic
2023-12-11T02:31:58.286623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
124 4
 
2.3%
51 4
 
2.3%
41 3
 
1.8%
67 3
 
1.8%
50 2
 
1.2%
52 2
 
1.2%
46 2
 
1.2%
48 2
 
1.2%
68 2
 
1.2%
56 2
 
1.2%
Other values (134) 145
84.8%
ValueCountFrequency (%)
3 1
 
0.6%
13 1
 
0.6%
19 1
 
0.6%
28 1
 
0.6%
30 1
 
0.6%
34 2
1.2%
39 1
 
0.6%
40 1
 
0.6%
41 3
1.8%
42 1
 
0.6%
ValueCountFrequency (%)
1960 1
0.6%
1887 1
0.6%
1696 1
0.6%
1562 1
0.6%
1510 1
0.6%
1454 1
0.6%
1185 1
0.6%
1143 1
0.6%
1136 1
0.6%
1117 1
0.6%

인구수(남)
Real number (ℝ)

HIGH CORRELATION 

Distinct148
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean467.23392
Minimum4
Maximum2668
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T02:31:58.627997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile40
Q168.5
median174
Q3760.5
95-th percentile1528
Maximum2668
Range2664
Interquartile range (IQR)692

Descriptive statistics

Standard deviation559.8776
Coefficient of variation (CV)1.1982811
Kurtosis2.2999759
Mean467.23392
Median Absolute Deviation (MAD)126
Skewness1.615364
Sum79897
Variance313462.92
MonotonicityNot monotonic
2023-12-11T02:31:58.954768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47 3
 
1.8%
57 3
 
1.8%
49 3
 
1.8%
48 3
 
1.8%
115 2
 
1.2%
285 2
 
1.2%
18 2
 
1.2%
60 2
 
1.2%
40 2
 
1.2%
80 2
 
1.2%
Other values (138) 147
86.0%
ValueCountFrequency (%)
4 1
0.6%
13 1
0.6%
18 2
1.2%
27 1
0.6%
38 1
0.6%
39 2
1.2%
40 2
1.2%
42 2
1.2%
44 1
0.6%
45 1
0.6%
ValueCountFrequency (%)
2668 1
0.6%
2425 1
0.6%
2275 1
0.6%
2230 1
0.6%
2037 1
0.6%
1881 1
0.6%
1796 1
0.6%
1578 1
0.6%
1547 1
0.6%
1509 1
0.6%

인구수(여)
Real number (ℝ)

HIGH CORRELATION 

Distinct145
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean476.33918
Minimum4
Maximum2662
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-11T02:31:59.267264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile33
Q160.5
median178
Q3733.5
95-th percentile1615
Maximum2662
Range2658
Interquartile range (IQR)673

Descriptive statistics

Standard deviation583.30078
Coefficient of variation (CV)1.2245492
Kurtosis2.0477427
Mean476.33918
Median Absolute Deviation (MAD)136
Skewness1.5866986
Sum81454
Variance340239.8
MonotonicityNot monotonic
2023-12-11T02:31:59.677188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42 4
 
2.3%
145 3
 
1.8%
51 3
 
1.8%
48 3
 
1.8%
47 3
 
1.8%
55 2
 
1.2%
52 2
 
1.2%
68 2
 
1.2%
59 2
 
1.2%
75 2
 
1.2%
Other values (135) 145
84.8%
ValueCountFrequency (%)
4 1
0.6%
6 1
0.6%
17 2
1.2%
18 1
0.6%
25 1
0.6%
27 1
0.6%
31 2
1.2%
35 1
0.6%
36 2
1.2%
37 1
0.6%
ValueCountFrequency (%)
2662 1
0.6%
2500 1
0.6%
2303 1
0.6%
2256 1
0.6%
2247 1
0.6%
1895 1
0.6%
1826 1
0.6%
1698 1
0.6%
1672 1
0.6%
1558 1
0.6%

Interactions

2023-12-11T02:31:54.131520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:31:52.967681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:31:53.556094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:31:54.310097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:31:53.177781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:31:53.781090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:31:54.501830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:31:53.360922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:31:53.960922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:31:59.922728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정구역(읍면)세대수인구수(남)인구수(여)
행정구역(읍면)1.0000.4290.3160.420
세대수0.4291.0000.9650.961
인구수(남)0.3160.9651.0000.989
인구수(여)0.4200.9610.9891.000
2023-12-11T02:32:00.160730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수인구수(남)인구수(여)행정구역(읍면)
세대수1.0000.9830.9840.188
인구수(남)0.9831.0000.9880.133
인구수(여)0.9840.9881.0000.183
행정구역(읍면)0.1880.1330.1831.000

Missing values

2023-12-11T02:31:54.762081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:31:54.987447image/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

행정구역(군)행정구역(읍면)행정구역(리(통))세대수인구수(남)인구수(여)
0기장군기장읍동부1(1통)89011061000
1기장군기장읍동부2(2통)8401007982
2기장군기장읍서부(3통)178195202
3기장군기장읍동서(4통)11711388
4기장군기장읍두화(5통)13136
5기장군기장읍교리1(6통)91712421255
6기장군기장읍소정1(7통)919483
7기장군기장읍소정2(8통)424239
8기장군기장읍오신(9통)514851
9기장군기장읍내동(10통)515135
행정구역(군)행정구역(읍면)행정구역(리(통))세대수인구수(남)인구수(여)
161기장군철마면대곡(13통)525954
162기장군철마면고촌(14통)124131137
163기장군철마면사등(15통)464527
164기장군철마면안평(16통)181174158
165기장군철마면송정1(17통)210221167
166기장군철마면입석(19통)137150140
167기장군철마면임기(20통)271284257
168기장군철마면고촌2(21통)107110581168
169기장군철마면고촌3(22통)455666695
170기장군철마면고촌4(23통)452657656