Overview

Dataset statistics

Number of variables3
Number of observations197
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory25.7 B

Variable types

Numeric1
Categorical1
Text1

Dataset

Description강원도 태백시 버스승강장 데이터입니다.태백시 버스승강장 위치, 명칭 등 기본적인 버스승강장 정보를 제공합니다.
Author강원특별자치도 태백시
URLhttps://www.data.go.kr/data/15041743/fileData.do

Alerts

번호 is highly overall correlated with 동 명High correlation
동 명 is highly overall correlated with 번호High correlation
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:15:25.492437
Analysis finished2023-12-12 03:15:25.937182
Duration0.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct197
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99
Minimum1
Maximum197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T12:15:26.038713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.8
Q150
median99
Q3148
95-th percentile187.2
Maximum197
Range196
Interquartile range (IQR)98

Descriptive statistics

Standard deviation57.013156
Coefficient of variation (CV)0.57589047
Kurtosis-1.2
Mean99
Median Absolute Deviation (MAD)49
Skewness0
Sum19503
Variance3250.5
MonotonicityStrictly increasing
2023-12-12T12:15:26.264243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
125 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
Other values (187) 187
94.9%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
197 1
0.5%
196 1
0.5%
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%

동 명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
삼수동
45 
문곡소도동
36 
구문소동
32 
황연동
25 
철암동
23 
Other values (3)
36 

Length

Max length5
Median length3
Mean length3.5279188
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상장동
2nd row상장동
3rd row상장동
4th row상장동
5th row문곡소도동

Common Values

ValueCountFrequency (%)
삼수동 45
22.8%
문곡소도동 36
18.3%
구문소동 32
16.2%
황연동 25
12.7%
철암동 23
11.7%
상장동 17
 
8.6%
장성동 10
 
5.1%
황지동 9
 
4.6%

Length

2023-12-12T12:15:26.466217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:15:26.645196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
삼수동 45
22.8%
문곡소도동 36
18.3%
구문소동 32
16.2%
황연동 25
12.7%
철암동 23
11.7%
상장동 17
 
8.6%
장성동 10
 
5.1%
황지동 9
 
4.6%

위치(인근건물명)
Text

Distinct157
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T12:15:26.990208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length5.0964467
Min length2

Characters and Unicode

Total characters1004
Distinct characters206
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)60.4%

Sample

1st row1주공아파트
2nd row현대아파트(대학길)
3rd row예채아파트
4th row현대아파트
5th row광원아파트
ValueCountFrequency (%)
문곡소도동주민센터 3
 
1.5%
메밀뜰 3
 
1.5%
금성연립 2
 
1.0%
한보5단지 2
 
1.0%
삼방동 2
 
1.0%
철암초등학교 2
 
1.0%
백산역 2
 
1.0%
고원아파트 2
 
1.0%
등광사 2
 
1.0%
쇠바우 2
 
1.0%
Other values (151) 179
89.1%
2023-12-12T12:15:27.505903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
파 29
 
2.9%
트 28
 
2.8%
동 27
 
2.7%
아 27
 
2.7%
백 24
 
2.4%
학 22
 
2.2%
교 22
 
2.2%
태 21
 
2.1%
원 20
 
2.0%
소 20
 
2.0%
Other values (196) 764
76.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 967
96.3%
Decimal Number 13
 
1.3%
Close Punctuation 8
 
0.8%
Open Punctuation 8
 
0.8%
Space Separator 4
 
0.4%
Other Punctuation 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 29
 
3.0%
트 28
 
2.9%
동 27
 
2.8%
아 27
 
2.8%
백 24
 
2.5%
학 22
 
2.3%
교 22
 
2.3%
태 21
 
2.2%
원 20
 
2.1%
소 20
 
2.1%
Other values (187) 727
75.2%
Decimal Number
ValueCountFrequency (%)
2 6
46.2%
3 3
23.1%
5 2
 
15.4%
1 1
 
7.7%
0 1
 
7.7%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 967
96.3%
Common 37
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 29
 
3.0%
트 28
 
2.9%
동 27
 
2.8%
아 27
 
2.8%
백 24
 
2.5%
학 22
 
2.3%
교 22
 
2.3%
태 21
 
2.2%
원 20
 
2.1%
소 20
 
2.1%
Other values (187) 727
75.2%
Common
ValueCountFrequency (%)
) 8
21.6%
( 8
21.6%
2 6
16.2%
4
10.8%
, 4
10.8%
3 3
 
8.1%
5 2
 
5.4%
1 1
 
2.7%
0 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 967
96.3%
ASCII 37
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
파 29
 
3.0%
트 28
 
2.9%
동 27
 
2.8%
아 27
 
2.8%
백 24
 
2.5%
학 22
 
2.3%
교 22
 
2.3%
태 21
 
2.2%
원 20
 
2.1%
소 20
 
2.1%
Other values (187) 727
75.2%
ASCII
ValueCountFrequency (%)
) 8
21.6%
( 8
21.6%
2 6
16.2%
4
10.8%
, 4
10.8%
3 3
 
8.1%
5 2
 
5.4%
1 1
 
2.7%
0 1
 
2.7%

Interactions

2023-12-12T12:15:25.682056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:15:27.624238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호동 명
번호1.0000.865
동 명0.8651.000
2023-12-12T12:15:27.737269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호동 명
번호1.0000.657
동 명0.6571.000

Missing values

2023-12-12T12:15:25.815802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:15:25.898063image/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

번호동 명위치(인근건물명)
01상장동1주공아파트
12상장동현대아파트(대학길)
23상장동예채아파트
34상장동현대아파트
45문곡소도동광원아파트
56상장동서학로
67상장동서학로(02리조트 입구)
78상장동오투진입로
89상장동서학마을입구
910상장동태백도서관
번호동 명위치(인근건물명)
187188장성동태백초등학교
188189장성동태백병원
189190구문소동문곡소도동주민센터
190191구문소동태백기계공고
191192구문소동구문소
192193황연동하나엽린
193194철암동상철암아파트
194195철암동철암주민센터, 보건소
195196삼수동브라이튼아파트
196197삼수동화전초등학교