Overview

Dataset statistics

Number of variables6
Number of observations336
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.2 KiB
Average record size in memory52.4 B

Variable types

Categorical2
Text1
Numeric3

Dataset

Description부산도시철도 역사 내 통신사별 와이파이(Wi-Fi) 설치 현황 데이터로, 각 역의 대합실, 승강장 내 와이파이(Wi-Fi) 설치 수량
URLhttps://www.data.go.kr/data/3077196/fileData.do

Alerts

대합실 is highly overall correlated with 수량High correlation
승강장 is highly overall correlated with 수량High correlation
수량 is highly overall correlated with 대합실 and 1 other fieldsHigh correlation
대합실 has 8 (2.4%) zerosZeros

Reproduction

Analysis started2023-12-12 23:43:07.703785
Analysis finished2023-12-12 23:43:08.719884
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회사명
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
SKT
114 
KT
111 
LGU+
111 

Length

Max length4
Median length3
Mean length3
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
SKT 114
33.9%
KT 111
33.0%
LGU+ 111
33.0%

Length

2023-12-13T08:43:08.780686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:43:08.868720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
skt 114
33.9%
kt 111
33.0%
lgu 111
33.0%

호선
Categorical

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2
129 
1
114 
3
51 
4
42 

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 (%)
2 129
38.4%
1 114
33.9%
3 51
 
15.2%
4 42
 
12.5%

Length

2023-12-13T08:43:08.953035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:43:09.041188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 129
38.4%
1 114
33.9%
3 51
 
15.2%
4 42
 
12.5%

역사명
Text

Distinct108
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-13T08:43:09.288349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length2
Mean length2.4583333
Min length2

Characters and Unicode

Total characters826
Distinct characters134
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

Unique0 ?
Unique (%)0.0%

Sample

1st row다대포해수욕장
2nd row다대포항
3rd row낫개
4th row신장림
5th row장림
ValueCountFrequency (%)
연산 6
 
1.8%
미남 6
 
1.8%
덕천 6
 
1.8%
동래 6
 
1.8%
수영 6
 
1.8%
서면 6
 
1.8%
가야 3
 
0.9%
냉정 3
 
0.9%
화명 3
 
0.9%
부산대양산캠퍼스 3
 
0.9%
Other values (99) 291
85.8%
2023-12-13T08:43:09.663634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 54
 
6.5%
대 43
 
5.2%
동 29
 
3.5%
남 24
 
2.9%
부 24
 
2.9%
포 22
 
2.7%
장 21
 
2.5%
사 18
 
2.2%
서 18
 
2.2%
금 15
 
1.8%
Other values (124) 558
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 823
99.6%
Space Separator 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 54
 
6.6%
대 43
 
5.2%
동 29
 
3.5%
남 24
 
2.9%
부 24
 
2.9%
포 22
 
2.7%
장 21
 
2.6%
사 18
 
2.2%
서 18
 
2.2%
금 15
 
1.8%
Other values (123) 555
67.4%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 823
99.6%
Common 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 54
 
6.6%
대 43
 
5.2%
동 29
 
3.5%
남 24
 
2.9%
부 24
 
2.9%
포 22
 
2.7%
장 21
 
2.6%
사 18
 
2.2%
서 18
 
2.2%
금 15
 
1.8%
Other values (123) 555
67.4%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 823
99.6%
ASCII 3
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 54
 
6.6%
대 43
 
5.2%
동 29
 
3.5%
남 24
 
2.9%
부 24
 
2.9%
포 22
 
2.7%
장 21
 
2.6%
사 18
 
2.2%
서 18
 
2.2%
금 15
 
1.8%
Other values (123) 555
67.4%
ASCII
ValueCountFrequency (%)
3
100.0%

대합실
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9791667
Minimum0
Maximum8
Zeros8
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T08:43:09.783144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q32
95-th percentile3
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.86534294
Coefficient of variation (CV)0.43722591
Kurtosis9.625773
Mean1.9791667
Median Absolute Deviation (MAD)0
Skewness1.791994
Sum665
Variance0.74881841
MonotonicityNot monotonic
2023-12-13T08:43:09.887189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 218
64.9%
1 63
 
18.8%
3 31
 
9.2%
4 12
 
3.6%
0 8
 
2.4%
6 2
 
0.6%
8 1
 
0.3%
5 1
 
0.3%
ValueCountFrequency (%)
0 8
 
2.4%
1 63
 
18.8%
2 218
64.9%
3 31
 
9.2%
4 12
 
3.6%
5 1
 
0.3%
6 2
 
0.6%
8 1
 
0.3%
ValueCountFrequency (%)
8 1
 
0.3%
6 2
 
0.6%
5 1
 
0.3%
4 12
 
3.6%
3 31
 
9.2%
2 218
64.9%
1 63
 
18.8%
0 8
 
2.4%

승강장
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.514881
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T08:43:09.977820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q34
95-th percentile4
Maximum6
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9556206
Coefficient of variation (CV)0.27187851
Kurtosis0.15585605
Mean3.514881
Median Absolute Deviation (MAD)0
Skewness-0.56917959
Sum1181
Variance0.91321073
MonotonicityNot monotonic
2023-12-13T08:43:10.068802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
4 226
67.3%
2 73
 
21.7%
3 23
 
6.8%
6 8
 
2.4%
1 4
 
1.2%
5 2
 
0.6%
ValueCountFrequency (%)
1 4
 
1.2%
2 73
 
21.7%
3 23
 
6.8%
4 226
67.3%
5 2
 
0.6%
6 8
 
2.4%
ValueCountFrequency (%)
6 8
 
2.4%
5 2
 
0.6%
4 226
67.3%
3 23
 
6.8%
2 73
 
21.7%
1 4
 
1.2%

수량
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4940476
Minimum2
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T08:43:10.157811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q15
median6
Q36
95-th percentile8
Maximum12
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3821766
Coefficient of variation (CV)0.25157711
Kurtosis1.727786
Mean5.4940476
Median Absolute Deviation (MAD)1
Skewness0.16254589
Sum1846
Variance1.9104122
MonotonicityNot monotonic
2023-12-13T08:43:10.254260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
6 165
49.1%
5 48
 
14.3%
4 45
 
13.4%
3 31
 
9.2%
7 26
 
7.7%
8 13
 
3.9%
10 3
 
0.9%
2 3
 
0.9%
12 1
 
0.3%
9 1
 
0.3%
ValueCountFrequency (%)
2 3
 
0.9%
3 31
 
9.2%
4 45
 
13.4%
5 48
 
14.3%
6 165
49.1%
7 26
 
7.7%
8 13
 
3.9%
9 1
 
0.3%
10 3
 
0.9%
12 1
 
0.3%
ValueCountFrequency (%)
12 1
 
0.3%
10 3
 
0.9%
9 1
 
0.3%
8 13
 
3.9%
7 26
 
7.7%
6 165
49.1%
5 48
 
14.3%
4 45
 
13.4%
3 31
 
9.2%
2 3
 
0.9%

Interactions

2023-12-13T08:43:08.357815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:43:07.917481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:43:08.148122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:43:08.434452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:43:07.988485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:43:08.222835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:43:08.502958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:43:08.067817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:43:08.287817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:43:10.322011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회사명호선대합실승강장수량
회사명1.0000.0000.0970.0000.111
호선0.0001.0000.6620.5850.625
대합실0.0970.6621.0000.2970.862
승강장0.0000.5850.2971.0000.762
수량0.1110.6250.8620.7621.000
2023-12-13T08:43:10.404707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회사명호선
회사명1.0000.000
호선0.0001.000
2023-12-13T08:43:10.480320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대합실승강장수량회사명호선
대합실1.0000.2250.7380.0600.344
승강장0.2251.0000.7740.0000.416
수량0.7380.7741.0000.0850.413
회사명0.0600.0000.0851.0000.000
호선0.3440.4160.4130.0001.000

Missing values

2023-12-13T08:43:08.590019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:43:08.683728image/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

회사명호선역사명대합실승강장수량
0SKT1다대포해수욕장6612
1SKT1다대포항4610
2SKT1낫개246
3SKT1신장림268
4SKT1장림369
5SKT1동매4610
6SKT1신평145
7SKT1하단246
8SKT1당리347
9SKT1사하347
회사명호선역사명대합실승강장수량
326LGU+4충렬사415
327LGU+4명장145
328LGU+4서동145
329LGU+4금사134
330LGU+4반여농산물145
331LGU+4석대123
332LGU+4영산대123
333LGU+4윗반송123
334LGU+4고촌123
335LGU+4안평123