Overview

Dataset statistics

Number of variables4
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory39.6 B

Variable types

Text1
Categorical3

Dataset

Description인천교통공사에서 교통약자를 위해 설치한 2019년12월31일 기준 엘리베이터, 에스컬레이터 등 시설현황(역사명, 엘리베이터 외부, 엘리베이터 내부, 휠체어리프트)
URLhttps://www.data.go.kr/data/15001445/fileData.do

Alerts

휠체어리프트 is highly imbalanced (72.8%)Imbalance
역사명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:25:25.112070
Analysis finished2023-12-12 18:25:25.429276
Duration0.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

역사명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-13T03:25:25.581429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.0689655
Min length3

Characters and Unicode

Total characters118
Distinct characters70
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row계 양
2nd row귤 현
3rd row박 촌
4th row임 학
5th row계 산
ValueCountFrequency (%)
동 3
 
6.7%
계 2
 
4.4%
수 2
 
4.4%
학 2
 
4.4%
산 2
 
4.4%
인 1
 
2.2%
문학경기장 1
 
2.2%
선 1
 
2.2%
신 1
 
2.2%
연 1
 
2.2%
Other values (29) 29
64.4%
2023-12-13T03:25:25.952491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
 
13.6%
인 5
 
4.2%
평 4
 
3.4%
부 4
 
3.4%
구 3
 
2.5%
동 3
 
2.5%
학 3
 
2.5%
지 3
 
2.5%
천 3
 
2.5%
크 3
 
2.5%
Other values (60) 71
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102
86.4%
Space Separator 16
 
13.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 5
 
4.9%
평 4
 
3.9%
부 4
 
3.9%
구 3
 
2.9%
동 3
 
2.9%
학 3
 
2.9%
지 3
 
2.9%
천 3
 
2.9%
크 3
 
2.9%
리 2
 
2.0%
Other values (59) 69
67.6%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102
86.4%
Common 16
 
13.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 5
 
4.9%
평 4
 
3.9%
부 4
 
3.9%
구 3
 
2.9%
동 3
 
2.9%
학 3
 
2.9%
지 3
 
2.9%
천 3
 
2.9%
크 3
 
2.9%
리 2
 
2.0%
Other values (59) 69
67.6%
Common
ValueCountFrequency (%)
16
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102
86.4%
ASCII 16
 
13.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
100.0%
Hangul
ValueCountFrequency (%)
인 5
 
4.9%
평 4
 
3.9%
부 4
 
3.9%
구 3
 
2.9%
동 3
 
2.9%
학 3
 
2.9%
지 3
 
2.9%
천 3
 
2.9%
크 3
 
2.9%
리 2
 
2.0%
Other values (59) 69
67.6%

엘리베이터 외부
Categorical

Distinct4
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size364.0 B
1
18 
2
7 
0
3 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.4%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 18
62.1%
2 7
 
24.1%
0 3
 
10.3%
3 1
 
3.4%

Length

2023-12-13T03:25:26.103324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:25:26.221170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 18
62.1%
2 7
 
24.1%
0 3
 
10.3%
3 1
 
3.4%

엘리베이터 내부
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
2
19 
1
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 19
65.5%
1 10
34.5%

Length

2023-12-13T03:25:26.340701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:25:26.456299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 19
65.5%
1 10
34.5%

휠체어리프트
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size364.0 B
0
27 
3
 
1
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)6.9%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 27
93.1%
3 1
 
3.4%
1 1
 
3.4%

Length

2023-12-13T03:25:26.617413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:25:26.781840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 27
93.1%
3 1
 
3.4%
1 1
 
3.4%

Correlations

2023-12-13T03:25:26.848641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역사명엘리베이터 외부엘리베이터 내부휠체어리프트
역사명1.0001.0001.0001.000
엘리베이터 외부1.0001.0000.0000.127
엘리베이터 내부1.0000.0001.0000.169
휠체어리프트1.0000.1270.1691.000
2023-12-13T03:25:26.939213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
엘리베이터 내부엘리베이터 외부휠체어리프트
엘리베이터 내부1.0000.0000.268
엘리베이터 외부0.0001.0000.100
휠체어리프트0.2680.1001.000
2023-12-13T03:25:27.039943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
엘리베이터 외부엘리베이터 내부휠체어리프트
엘리베이터 외부1.0000.0000.100
엘리베이터 내부0.0001.0000.268
휠체어리프트0.1000.2681.000

Missing values

2023-12-13T03:25:25.298915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:25:25.391870image/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

역사명엘리베이터 외부엘리베이터 내부휠체어리프트
0계 양020
1귤 현110
2박 촌120
3임 학110
4계 산120
5경인교대120
6작 전110
7갈 산020
8부평구청020
9부평시장220
역사명엘리베이터 외부엘리베이터 내부휠체어리프트
19신 연 수210
20원 인 재120
21동 춘110
22동 막211
23캠퍼스타운320
24테크노파크220
25지식정보단지220
26인천대입구120
27센트럴파크120
28국제업무지구220