Overview

Dataset statistics

Number of variables14
Number of observations27
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory117.9 B

Variable types

Categorical1
Text1
Unsupported12

Dataset

Description서대문구의 노후시간 별 주택현황 통계입니다.
Author서울특별시 서대문구
URLhttps://www.data.go.kr/data/15062006/fileData.do

Alerts

기간 is highly imbalanced (77.1%)Imbalance
자치구 has 1 (3.7%) missing valuesMissing
20년~30년미만 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
30년 이상 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
30년 이상.1 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

Reproduction

Analysis started2023-12-12 03:03:55.043457
Analysis finished2023-12-12 03:03:55.525222
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기간
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
<NA>
26 
2018
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row<NA>
2nd row2018
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 26
96.3%
2018 1
 
3.7%

Length

2023-12-12T12:03:55.630242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:03:55.766207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
96.3%
2018 1
 
3.7%

자치구
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing1
Missing (%)3.7%
Memory size348.0 B
2023-12-12T12:03:56.024181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0769231
Min length2

Characters and Unicode

Total characters80
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row서울시
2nd row종로구
3rd row중구
4th row용산구
5th row성동구
ValueCountFrequency (%)
서울시 1
 
3.8%
종로구 1
 
3.8%
송파구 1
 
3.8%
강남구 1
 
3.8%
서초구 1
 
3.8%
관악구 1
 
3.8%
동작구 1
 
3.8%
영등포구 1
 
3.8%
금천구 1
 
3.8%
구로구 1
 
3.8%
Other values (16) 16
61.5%
2023-12-12T12:03:56.491732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 26
32.5%
서 4
 
5.0%
강 4
 
5.0%
동 4
 
5.0%
성 2
 
2.5%
천 2
 
2.5%
북 2
 
2.5%
문 2
 
2.5%
대 2
 
2.5%
포 2
 
2.5%
Other values (28) 30
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 26
32.5%
서 4
 
5.0%
강 4
 
5.0%
동 4
 
5.0%
성 2
 
2.5%
천 2
 
2.5%
북 2
 
2.5%
문 2
 
2.5%
대 2
 
2.5%
포 2
 
2.5%
Other values (28) 30
37.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 26
32.5%
서 4
 
5.0%
강 4
 
5.0%
동 4
 
5.0%
성 2
 
2.5%
천 2
 
2.5%
북 2
 
2.5%
문 2
 
2.5%
대 2
 
2.5%
포 2
 
2.5%
Other values (28) 30
37.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 26
32.5%
서 4
 
5.0%
강 4
 
5.0%
동 4
 
5.0%
성 2
 
2.5%
천 2
 
2.5%
북 2
 
2.5%
문 2
 
2.5%
대 2
 
2.5%
포 2
 
2.5%
Other values (28) 30
37.5%

20년~30년미만
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

Unnamed: 3
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

Unnamed: 4
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

Unnamed: 5
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

Unnamed: 6
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

Unnamed: 7
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

30년 이상
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

Unnamed: 9
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

30년 이상.1
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

Unnamed: 11
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

Unnamed: 12
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

Unnamed: 13
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

Correlations

2023-12-12T12:03:56.634453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자치구
자치구1.000

Missing values

2023-12-12T12:03:55.196626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:03:55.427623image/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

기간자치구20년~30년미만Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 730년 이상Unnamed: 930년 이상.1Unnamed: 11Unnamed: 12Unnamed: 13
0<NA><NA>계단독주택아파트연립주택다세대주택비거주용 건물내 주택계단독주택아파트연립주택다세대주택비거주용 건물내 주택
12018서울시7948651377604332545472215740611723508928150326265298345774778510942
2<NA>종로구13407265233872776427731512353858014161276673408
3<NA>중구5396166910479931394293702340021863268481409
4<NA>용산구15642451153431605399918421465923586667982317449
5<NA>성동구21845507112667494319841511760532140431275596525
6<NA>광진구287508201139681877406563911149543128721488802556
7<NA>동대문구191037236772458930255291715210744281315081314773
8<NA>중랑구4202310547259251805306268411051654671121451089560
9<NA>성북구2999381651129035066543489186001405115091542925573
기간자치구20년~30년미만Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 730년 이상Unnamed: 930년 이상.1Unnamed: 11Unnamed: 12Unnamed: 13
17<NA>강서구662195285485892050976353295503965140220571720406
18<NA>구로구3123758531581729876288292187255365777234681726394
19<NA>금천구15390386774011653233913010448473928911659887272
20<NA>영등포구24930695115553294179833425880649717115829821618
21<NA>동작구3526562991903829486627353138976635361510802136431
22<NA>관악구37729936110989405012753576158717871337613142814496
23<NA>서초구22990255711458341349026603076328622452514041657315
24<NA>강남구37886356626804262739659244487918933925114322058245
25<NA>송파구4455446932595536379403866362633120296904202546487
26<NA>강동구1843850878151193228034652681844611826111982464434