Overview

Dataset statistics

Number of variables20
Number of observations338
Missing cells563
Missing cells (%)8.3%
Duplicate rows2
Duplicate rows (%)0.6%
Total size in memory53.3 KiB
Average record size in memory161.4 B

Variable types

Unsupported18
Text1
Categorical1

Dataset

Description서울특별시 중랑구의 연령별 인구 분포 정보를 제공합니다. 연령별 인구현황, 주민등록자,거주자,거주불명자,재외국민 등의 정보를 제공합니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15030497/fileData.do

Alerts

Dataset has 2 (0.6%) duplicate rowsDuplicates
Unnamed: 0 has 338 (100.0%) missing valuesMissing
연령별(만)인구현황(기관별) has 225 (66.6%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 16 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 17 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 18 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 19 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-17 11:36:49.524017
Analysis finished2024-04-17 11:36:49.911540
Duration0.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing338
Missing (%)100.0%
Memory size3.1 KiB

연령별(만)인구현황(기관별)
Text

MISSING 

Distinct113
Distinct (%)100.0%
Missing225
Missing (%)66.6%
Memory size2.8 KiB
2024-04-17T20:36:50.119096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0442478
Min length2

Characters and Unicode

Total characters344
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)100.0%

Sample

1st row연령
2nd row합 계
3rd row0세
4th row1세
5th row2세
ValueCountFrequency (%)
24세 1
 
0.9%
68세 1
 
0.9%
81세 1
 
0.9%
80세 1
 
0.9%
79세 1
 
0.9%
78세 1
 
0.9%
77세 1
 
0.9%
76세 1
 
0.9%
75세 1
 
0.9%
74세 1
 
0.9%
Other values (105) 105
91.3%
2024-04-17T20:36:50.501951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 111
32.3%
1 33
 
9.6%
0 22
 
6.4%
2 21
 
6.1%
7 21
 
6.1%
9 21
 
6.1%
4 21
 
6.1%
8 21
 
6.1%
6 21
 
6.1%
5 21
 
6.1%
Other values (8) 31
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 223
64.8%
Other Letter 117
34.0%
Space Separator 4
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 33
14.8%
0 22
9.9%
2 21
9.4%
7 21
9.4%
9 21
9.4%
4 21
9.4%
8 21
9.4%
6 21
9.4%
5 21
9.4%
3 21
9.4%
Other Letter
ValueCountFrequency (%)
세 111
94.9%
합 1
 
0.9%
계 1
 
0.9%
연 1
 
0.9%
령 1
 
0.9%
이 1
 
0.9%
상 1
 
0.9%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 227
66.0%
Hangul 117
34.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 33
14.5%
0 22
9.7%
2 21
9.3%
7 21
9.3%
9 21
9.3%
4 21
9.3%
8 21
9.3%
6 21
9.3%
5 21
9.3%
3 21
9.3%
Hangul
ValueCountFrequency (%)
세 111
94.9%
합 1
 
0.9%
계 1
 
0.9%
연 1
 
0.9%
령 1
 
0.9%
이 1
 
0.9%
상 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 227
66.0%
Hangul 117
34.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 111
94.9%
합 1
 
0.9%
계 1
 
0.9%
연 1
 
0.9%
령 1
 
0.9%
이 1
 
0.9%
상 1
 
0.9%
ASCII
ValueCountFrequency (%)
1 33
14.5%
0 22
9.7%
2 21
9.3%
7 21
9.3%
9 21
9.3%
4 21
9.3%
8 21
9.3%
6 21
9.3%
5 21
9.3%
3 21
9.3%

Unnamed: 2
Categorical

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
계
112 
남
112 
여
112 
<NA>
 
2

Length

Max length4
Median length1
Mean length1.0177515
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row계
4th row남
5th row여

Common Values

ValueCountFrequency (%)
계 112
33.1%
남 112
33.1%
여 112
33.1%
<NA> 2
 
0.6%

Length

2024-04-17T20:36:50.625792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:36:50.724404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계 112
33.1%
남 112
33.1%
여 112
33.1%
na 2
 
0.6%

Unnamed: 3
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 4
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 5
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 6
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 7
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 8
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 9
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 10
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 11
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 12
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 13
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 14
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 15
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 16
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 17
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 18
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Unnamed: 19
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.8 KiB

Missing values

2024-04-17T20:36:49.650199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T20:36:49.834989image/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

Unnamed: 0연령별(만)인구현황(기관별)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
0<NA>연령<NA>중랑구면목본동면목제2동면목제3.8동면목제4동면목제5동면목제7동상봉제1동상봉제2동중화제1동중화제2동묵제1동묵제2동망우본동망우제3동신내1동신내2동
1<NA><NA><NA>인구수인구수인구수인구수인구수인구수인구수인구수인구수인구수인구수인구수인구수인구수인구수인구수인구수
2<NA>합 계계38500333031237862462318358146702144323393202381904524334339971839835594158763826519952
3<NA><NA>남1891861630211845121949115733610717113519723937212483162298990175967991184639479
4<NA><NA>여195817167291194112429924373341072612042105159673118511776894081799878851980210473
5<NA>0세계1791141112985611010912211810888138722375414484
6<NA><NA>남881715339264861705264456834107327140
7<NA><NA>여910705959306248526644437038130227344
8<NA>1세계17741137587711391181221147794147992064818183
9<NA><NA>남880613537337061525432517158112218844
Unnamed: 0연령별(만)인구현황(기관별)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
328<NA><NA>여20000000000000011
329<NA>108세계10000000100000000
330<NA><NA>남00000000000000000
331<NA><NA>여10000000100000000
332<NA>109세계20000000000000020
333<NA><NA>남00000000000000000
334<NA><NA>여20000000000000020
335<NA>110세 이상계10000000000100000
336<NA><NA>남00000000000000000
337<NA><NA>여10000000000100000

Duplicate rows

Most frequently occurring

연령별(만)인구현황(기관별)Unnamed: 2# duplicates
0<NA>남112
1<NA>여112