Overview

Dataset statistics

Number of variables5
Number of observations68
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory45.9 B

Variable types

Categorical3
Text1
Numeric1

Dataset

Description인천교통공사에서 운영중인 인천1호선, 인천2호선, 7호선(인천구간+부천구간) 2023년 5월 31일 기준 엘리베이터 설치현황입니다. (호선,역사명,엘리베이터 외부,엘리베이터 내부,휠체어리프트)
Author인천교통공사
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15083478&srcSe=7661IVAWM27C61E190

Alerts

휠체어리프트 is highly imbalanced (86.1%)Imbalance

Reproduction

Analysis started2024-04-19 06:58:34.047662
Analysis finished2024-04-19 06:58:34.510780
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

호선
Categorical

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
1
30 
2
27 
7
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 30
44.1%
2 27
39.7%
7 11
 
16.2%

Length

2024-04-19T15:58:34.568843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:58:34.660074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 30
44.1%
2 27
39.7%
7 11
 
16.2%

역사명
Text

Distinct66
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-04-19T15:58:34.994234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6.5
Mean length4.0882353
Min length2

Characters and Unicode

Total characters278
Distinct characters122
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

Unique64 ?
Unique (%)94.1%

Sample

1st row계 양
2nd row귤 현
3rd row박 촌
4th row임 학
5th row계 산
ValueCountFrequency (%)
동 3
 
3.6%
인천시청 2
 
2.4%
부평구청 2
 
2.4%
수 2
 
2.4%
학 2
 
2.4%
계 2
 
2.4%
산 2
 
2.4%
가재울 1
 
1.2%
가정(루원시티 1
 
1.2%
가정중앙시장 1
 
1.2%
Other values (66) 66
78.6%
2024-04-19T15:58:35.410832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
 
5.8%
시 11
 
4.0%
천 10
 
3.6%
인 8
 
2.9%
장 8
 
2.9%
부 8
 
2.9%
청 7
 
2.5%
동 7
 
2.5%
구 6
 
2.2%
가 5
 
1.8%
Other values (112) 192
69.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 256
92.1%
Space Separator 16
 
5.8%
Close Punctuation 3
 
1.1%
Open Punctuation 3
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 11
 
4.3%
천 10
 
3.9%
인 8
 
3.1%
장 8
 
3.1%
부 8
 
3.1%
청 7
 
2.7%
동 7
 
2.7%
구 6
 
2.3%
가 5
 
2.0%
원 5
 
2.0%
Other values (109) 181
70.7%
Space Separator
ValueCountFrequency (%)
16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 256
92.1%
Common 22
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 11
 
4.3%
천 10
 
3.9%
인 8
 
3.1%
장 8
 
3.1%
부 8
 
3.1%
청 7
 
2.7%
동 7
 
2.7%
구 6
 
2.3%
가 5
 
2.0%
원 5
 
2.0%
Other values (109) 181
70.7%
Common
ValueCountFrequency (%)
16
72.7%
) 3
 
13.6%
( 3
 
13.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 256
92.1%
ASCII 22
 
7.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
72.7%
) 3
 
13.6%
( 3
 
13.6%
Hangul
ValueCountFrequency (%)
시 11
 
4.3%
천 10
 
3.9%
인 8
 
3.1%
장 8
 
3.1%
부 8
 
3.1%
청 7
 
2.7%
동 7
 
2.7%
구 6
 
2.3%
가 5
 
2.0%
원 5
 
2.0%
Other values (109) 181
70.7%

엘리베이터 외부
Categorical

Distinct5
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
2
29 
1
27 
0
4 
3
4 
4
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 29
42.6%
1 27
39.7%
0 4
 
5.9%
3 4
 
5.9%
4 4
 
5.9%

Length

2024-04-19T15:58:35.534526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:58:35.632522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 29
42.6%
1 27
39.7%
0 4
 
5.9%
3 4
 
5.9%
4 4
 
5.9%

엘리베이터 내부
Real number (ℝ)

Distinct6
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0588235
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-04-19T15:58:35.738182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile4
Maximum7
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.104703
Coefficient of variation (CV)0.53657003
Kurtosis9.2187969
Mean2.0588235
Median Absolute Deviation (MAD)0
Skewness2.7553283
Sum140
Variance1.2203687
MonotonicityNot monotonic
2024-04-19T15:58:35.833793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 46
67.6%
1 15
 
22.1%
4 2
 
2.9%
3 2
 
2.9%
6 2
 
2.9%
7 1
 
1.5%
ValueCountFrequency (%)
1 15
 
22.1%
2 46
67.6%
3 2
 
2.9%
4 2
 
2.9%
6 2
 
2.9%
7 1
 
1.5%
ValueCountFrequency (%)
7 1
 
1.5%
6 2
 
2.9%
4 2
 
2.9%
3 2
 
2.9%
2 46
67.6%
1 15
 
22.1%

휠체어리프트
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
0
66 
2
 
1
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
0 66
97.1%
2 1
 
1.5%
1 1
 
1.5%

Length

2024-04-19T15:58:35.955521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:58:36.052594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 66
97.1%
2 1
 
1.5%
1 1
 
1.5%

Interactions

2024-04-19T15:58:34.264935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T15:58:36.117793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선역사명엘리베이터 외부엘리베이터 내부휠체어리프트
호선1.0000.0000.3490.6010.000
역사명0.0001.0000.0000.0001.000
엘리베이터 외부0.3490.0001.0000.2900.000
엘리베이터 내부0.6010.0000.2901.0000.000
휠체어리프트0.0001.0000.0000.0001.000
2024-04-19T15:58:36.229390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선엘리베이터 외부휠체어리프트
호선1.0000.2760.000
엘리베이터 외부0.2761.0000.000
휠체어리프트0.0000.0001.000
2024-04-19T15:58:36.317032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
엘리베이터 내부호선엘리베이터 외부휠체어리프트
엘리베이터 내부1.0000.2960.1960.000
호선0.2961.0000.2760.000
엘리베이터 외부0.1960.2761.0000.000
휠체어리프트0.0000.0000.0001.000

Missing values

2024-04-19T15:58:34.393022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T15:58:34.476394image/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

호선역사명엘리베이터 외부엘리베이터 내부휠체어리프트
01계 양020
11귤 현110
21박 촌120
31임 학110
41계 산120
51경인교대120
61작 전110
71갈 산020
81부평구청020
91부평시장220
호선역사명엘리베이터 외부엘리베이터 내부휠체어리프트
587부천종합운동장220
597춘의210
607신중동310
617부천시청210
627상동220
637삼산체육관220
647굴포천220
657부평구청360
667산곡220
677석남470