Overview

Dataset statistics

Number of variables5
Number of observations43
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory45.1 B

Variable types

Categorical2
Text1
Numeric2

Dataset

Description부산2호선에 포함된 도시광역철도역들의 철도운영기관명, 선명, 역명, 경도, 위도의 데이터가 포함된 파일데이터 입니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15041166/fileData.do

Alerts

철도운영기관명 has constant value ""Constant
선명 has constant value ""Constant
역명 has unique valuesUnique
경도 has unique valuesUnique
위도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:21:52.048549
Analysis finished2023-12-12 12:21:53.227564
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
부산교통공사
43 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산교통공사 43
100.0%

Length

2023-12-12T21:21:53.289860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:21:53.397019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산교통공사 43
100.0%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
2호선
43 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2호선
2nd row2호선
3rd row2호선
4th row2호선
5th row2호선

Common Values

ValueCountFrequency (%)
2호선 43
100.0%

Length

2023-12-12T21:21:53.497432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:21:53.613142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2호선 43
100.0%

역명
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T21:21:53.844219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length2
Mean length5.1162791
Min length2

Characters and Unicode

Total characters220
Distinct characters106
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row장산(해운대백병원)
2nd row중동
3rd row해운대
4th row동백
5th row벡스코(시립미술관)
ValueCountFrequency (%)
장산(해운대백병원 1
 
2.3%
개금 1
 
2.3%
주례 1
 
2.3%
감전(사상구청 1
 
2.3%
사상(서부터미널 1
 
2.3%
덕포 1
 
2.3%
모덕 1
 
2.3%
모라 1
 
2.3%
구남 1
 
2.3%
구명 1
 
2.3%
Other values (33) 33
76.7%
2023-12-12T21:21:54.252283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 14
 
6.4%
) 14
 
6.4%
대 11
 
5.0%
산 9
 
4.1%
부 6
 
2.7%
동 6
 
2.7%
원 5
 
2.3%
구 5
 
2.3%
· 5
 
2.3%
남 4
 
1.8%
Other values (96) 141
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 179
81.4%
Open Punctuation 14
 
6.4%
Close Punctuation 14
 
6.4%
Uppercase Letter 8
 
3.6%
Other Punctuation 5
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 11
 
6.1%
산 9
 
5.0%
부 6
 
3.4%
동 6
 
3.4%
원 5
 
2.8%
구 5
 
2.8%
남 4
 
2.2%
금 4
 
2.2%
청 4
 
2.2%
학 3
 
1.7%
Other values (86) 122
68.2%
Uppercase Letter
ValueCountFrequency (%)
B 2
25.0%
S 1
12.5%
K 1
12.5%
O 1
12.5%
C 1
12.5%
X 1
12.5%
E 1
12.5%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Other Punctuation
ValueCountFrequency (%)
· 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 179
81.4%
Common 33
 
15.0%
Latin 8
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 11
 
6.1%
산 9
 
5.0%
부 6
 
3.4%
동 6
 
3.4%
원 5
 
2.8%
구 5
 
2.8%
남 4
 
2.2%
금 4
 
2.2%
청 4
 
2.2%
학 3
 
1.7%
Other values (86) 122
68.2%
Latin
ValueCountFrequency (%)
B 2
25.0%
S 1
12.5%
K 1
12.5%
O 1
12.5%
C 1
12.5%
X 1
12.5%
E 1
12.5%
Common
ValueCountFrequency (%)
( 14
42.4%
) 14
42.4%
· 5
 
15.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 179
81.4%
ASCII 36
 
16.4%
None 5
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 14
38.9%
) 14
38.9%
B 2
 
5.6%
S 1
 
2.8%
K 1
 
2.8%
O 1
 
2.8%
C 1
 
2.8%
X 1
 
2.8%
E 1
 
2.8%
Hangul
ValueCountFrequency (%)
대 11
 
6.1%
산 9
 
5.0%
부 6
 
3.4%
동 6
 
3.4%
원 5
 
2.8%
구 5
 
2.8%
남 4
 
2.2%
금 4
 
2.2%
청 4
 
2.2%
학 3
 
1.7%
Other values (86) 122
68.2%
None
ValueCountFrequency (%)
· 5
100.0%

경도
Real number (ℝ)

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.05465
Minimum128.98396
Maximum129.17699
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T21:21:54.399253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.98396
5-th percentile128.98592
Q1129.01125
median129.03275
Q3129.10426
95-th percentile129.15781
Maximum129.17699
Range0.193031
Interquartile range (IQR)0.0930125

Descriptive statistics

Standard deviation0.057209234
Coefficient of variation (CV)0.00044329464
Kurtosis-0.87867733
Mean129.05465
Median Absolute Deviation (MAD)0.034649
Skewness0.61085402
Sum5549.3499
Variance0.0032728965
MonotonicityNot monotonic
2023-12-12T21:21:54.599731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
129.176986 1
 
2.3%
129.168604 1
 
2.3%
129.003077 1
 
2.3%
128.991146 1
 
2.3%
128.984621 1
 
2.3%
128.983955 1
 
2.3%
128.985621 1
 
2.3%
128.988655 1
 
2.3%
128.994928 1
 
2.3%
128.999322 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
128.983955 1
2.3%
128.984621 1
2.3%
128.985621 1
2.3%
128.988655 1
2.3%
128.991146 1
2.3%
128.994928 1
2.3%
128.999322 1
2.3%
129.003077 1
2.3%
129.005673 1
2.3%
129.009198 1
2.3%
ValueCountFrequency (%)
129.176986 1
2.3%
129.168604 1
2.3%
129.158908 1
2.3%
129.147897 1
2.3%
129.138933 1
2.3%
129.131745 1
2.3%
129.121909 1
2.3%
129.114713 1
2.3%
129.113168 1
2.3%
129.110961 1
2.3%

위도
Real number (ℝ)

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.188748
Minimum35.134731
Maximum35.338728
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T21:21:54.769082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.134731
5-th percentile35.135775
Q135.153193
median35.165227
Q335.20637
95-th percentile35.31609
Maximum35.338728
Range0.20399673
Interquartile range (IQR)0.0531765

Descriptive statistics

Standard deviation0.056651542
Coefficient of variation (CV)0.0016099335
Kurtosis0.89058014
Mean35.188748
Median Absolute Deviation (MAD)0.015456
Skewness1.4032147
Sum1513.1162
Variance0.0032093972
MonotonicityNot monotonic
2023-12-12T21:21:54.951113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
35.169914 1
 
2.3%
35.1667 1
 
2.3%
35.150508 1
 
2.3%
35.155528 1
 
2.3%
35.162361 1
 
2.3%
35.173754 1
 
2.3%
35.180366 1
 
2.3%
35.189663 1
 
2.3%
35.196804 1
 
2.3%
35.20252 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
35.134731 1
2.3%
35.135153 1
2.3%
35.135574 1
2.3%
35.137585 1
2.3%
35.139151 1
2.3%
35.142139 1
2.3%
35.145817 1
2.3%
35.149771 1
2.3%
35.150508 1
2.3%
35.151254 1
2.3%
ValueCountFrequency (%)
35.33872773 1
2.3%
35.325359 1
2.3%
35.316955 1
2.3%
35.308302 1
2.3%
35.280406 1
2.3%
35.267248 1
2.3%
35.258656 1
2.3%
35.246714 1
2.3%
35.236278 1
2.3%
35.223356 1
2.3%

Interactions

2023-12-12T21:21:52.488509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:21:52.232311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:21:52.616245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:21:52.351541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:21:55.055423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명경도위도
역명1.0001.0001.000
경도1.0001.0000.175
위도1.0000.1751.000
2023-12-12T21:21:55.142609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경도위도
경도1.000-0.374
위도-0.3741.000

Missing values

2023-12-12T21:21:53.078944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:21:53.190670image/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

철도운영기관명선명역명경도위도
0부산교통공사2호선장산(해운대백병원)129.17698635.169914
1부산교통공사2호선중동129.16860435.1667
2부산교통공사2호선해운대129.15890835.163672
3부산교통공사2호선동백129.14789735.161484
4부산교통공사2호선벡스코(시립미술관)129.13893335.168844
5부산교통공사2호선센텀시티(BEXCO·신세계)129.13174535.168827
6부산교통공사2호선민락129.12190935.167228
7부산교통공사2호선수영129.11471335.165227
8부산교통공사2호선광안129.11316835.157916
9부산교통공사2호선금련산129.11096135.149771
철도운영기관명선명역명경도위도
33부산교통공사2호선수정(방송통신대)129.00919835.223356
34부산교통공사2호선화명129.01391835.236278
35부산교통공사2호선율리129.01291835.246714
36부산교통공사2호선동원129.01239235.258656
37부산교통공사2호선금곡129.01690535.267248
38부산교통공사2호선호포129.01709735.280406
39부산교통공사2호선증산129.01024635.308302
40부산교통공사2호선부산대양산캠퍼스129.01394135.316955
41부산교통공사2호선남양산(범어)129.01945735.325359
42부산교통공사2호선양산(시청·동원과학기술대학교)129.02639135.338728