Overview

Dataset statistics

Number of variables8
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory70.6 B

Variable types

Text1
Categorical5
Numeric2

Dataset

Description대전교통공사 22개역사 외부 엘리베이터 위치정보/대전교통공사의 역사에 운행 중인 엘레베이터의 각종 현황 자료 입니다.
Author대전교통공사
URLhttps://www.data.go.kr/data/15043922/fileData.do

Alerts

내외 has constant value ""Constant
운행구간(상부) has constant value ""Constant
위도(WGS84) is highly overall correlated with 경도(WGS84)High correlation
경도(WGS84) is highly overall correlated with 위도(WGS84)High correlation
호기 is highly overall correlated with 설치위치High correlation
설치위치 is highly overall correlated with 호기High correlation
경도(WGS84) has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:22:41.466885
Analysis finished2023-12-12 09:22:42.957916
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

역사
Text

Distinct22
Distinct (%)59.5%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T18:22:43.093113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.972973
Min length3

Characters and Unicode

Total characters147
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)24.3%

Sample

1st row판암역
2nd row판암역
3rd row신흥역
4th row대동역
5th row대동역
ValueCountFrequency (%)
월드컵경기장역 4
 
10.8%
대전역 2
 
5.4%
갈마역 2
 
5.4%
갑천역 2
 
5.4%
노은역 2
 
5.4%
현충원역 2
 
5.4%
유성온천역 2
 
5.4%
지족역 2
 
5.4%
월평역 2
 
5.4%
정부청사역 2
 
5.4%
Other values (12) 15
40.5%
2023-12-12T18:22:43.526812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
역 37
25.2%
월 6
 
4.1%
대 6
 
4.1%
청 4
 
2.7%
전 4
 
2.7%
천 4
 
2.7%
드 4
 
2.7%
기 4
 
2.7%
컵 4
 
2.7%
경 4
 
2.7%
Other values (40) 70
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 147
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 37
25.2%
월 6
 
4.1%
대 6
 
4.1%
청 4
 
2.7%
전 4
 
2.7%
천 4
 
2.7%
드 4
 
2.7%
기 4
 
2.7%
컵 4
 
2.7%
경 4
 
2.7%
Other values (40) 70
47.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 147
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 37
25.2%
월 6
 
4.1%
대 6
 
4.1%
청 4
 
2.7%
전 4
 
2.7%
천 4
 
2.7%
드 4
 
2.7%
기 4
 
2.7%
컵 4
 
2.7%
경 4
 
2.7%
Other values (40) 70
47.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 147
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
역 37
25.2%
월 6
 
4.1%
대 6
 
4.1%
청 4
 
2.7%
전 4
 
2.7%
천 4
 
2.7%
드 4
 
2.7%
기 4
 
2.7%
컵 4
 
2.7%
경 4
 
2.7%
Other values (40) 70
47.6%

호기
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size428.0 B
1
22 
2
13 
3
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)5.4%

Sample

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

Common Values

ValueCountFrequency (%)
1 22
59.5%
2 13
35.1%
3 1
 
2.7%
4 1
 
2.7%

Length

2023-12-12T18:22:43.688016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:22:43.830902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 22
59.5%
2 13
35.1%
3 1
 
2.7%
4 1
 
2.7%

내외
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
외
37 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
외 37
100.0%

Length

2023-12-12T18:22:43.958313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:22:44.100245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외 37
100.0%

설치위치
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
1,2번출구측
10 
3,4번출구측
8 
2번출구측
4 
3번출구측
4 
1번출구측
3 
Other values (7)
8 

Length

Max length8
Median length7
Mean length6.2432432
Min length5

Unique

Unique6 ?
Unique (%)16.2%

Sample

1st row1,2번출구측
2nd row3,4번출구측
3rd row2번출구측
4th row1번출구측
5th row8번출구측

Common Values

ValueCountFrequency (%)
1,2번출구측 10
27.0%
3,4번출구측 8
21.6%
2번출구측 4
 
10.8%
3번출구측 4
 
10.8%
1번출구측 3
 
8.1%
5,6번출구측 2
 
5.4%
8번출구측 1
 
2.7%
4번출구측 1
 
2.7%
7,8번출구측 1
 
2.7%
대합실 하선중앙 1
 
2.7%
Other values (2) 2
 
5.4%

Length

2023-12-12T18:22:44.212598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1,2번출구측 10
25.6%
3,4번출구측 8
20.5%
2번출구측 4
 
10.3%
3번출구측 4
 
10.3%
1번출구측 3
 
7.7%
5,6번출구측 2
 
5.1%
8번출구측 1
 
2.6%
4번출구측 1
 
2.6%
7,8번출구측 1
 
2.6%
대합실 1
 
2.6%
Other values (4) 4
 
10.3%

운행구간(상부)
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
지상
37 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지상 37
100.0%

Length

2023-12-12T18:22:44.347135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:22:44.456161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지상 37
100.0%

운행구간(하부)
Categorical

Distinct3
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
지하1층
28 
지하2층
6 
지하3층
3 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지하1층
2nd row지하1층
3rd row지하2층
4th row지하1층
5th row지하1층

Common Values

ValueCountFrequency (%)
지하1층 28
75.7%
지하2층 6
 
16.2%
지하3층 3
 
8.1%

Length

2023-12-12T18:22:44.614336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:22:44.752038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하1층 28
75.7%
지하2층 6
 
16.2%
지하3층 3
 
8.1%

위도(WGS84)
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.35208
Minimum36.316781
Maximum36.392258
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T18:22:44.944342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.316781
5-th percentile36.321544
Q136.331038
median36.356442
Q336.366549
95-th percentile36.385876
Maximum36.392258
Range0.0754767
Interquartile range (IQR)0.0355111

Descriptive statistics

Standard deviation0.020771891
Coefficient of variation (CV)0.00057140859
Kurtosis-0.73614808
Mean36.35208
Median Absolute Deviation (MAD)0.0108269
Skewness0.039108812
Sum1345.027
Variance0.00043147144
MonotonicityNot monotonic
2023-12-12T18:22:45.132335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
36.3922577 2
 
5.4%
36.3580127 1
 
2.7%
36.3543047 1
 
2.7%
36.3544892 1
 
2.7%
36.3533357 1
 
2.7%
36.3539617 1
 
2.7%
36.356442 1
 
2.7%
36.3592271 1
 
2.7%
36.3595818 1
 
2.7%
36.3665492 1
 
2.7%
Other values (26) 26
70.3%
ValueCountFrequency (%)
36.316781 1
2.7%
36.3196845 1
2.7%
36.3220094 1
2.7%
36.3226653 1
2.7%
36.325057 1
2.7%
36.3283245 1
2.7%
36.3285124 1
2.7%
36.329342 1
2.7%
36.3295694 1
2.7%
36.3310381 1
2.7%
ValueCountFrequency (%)
36.3922577 2
5.4%
36.3842811 1
2.7%
36.384278 1
2.7%
36.3741338 1
2.7%
36.3740502 1
2.7%
36.3672028 1
2.7%
36.3671966 1
2.7%
36.3666493 1
2.7%
36.3665492 1
2.7%
36.3595818 1
2.7%

경도(WGS84)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.37345
Minimum127.31421
Maximum127.45882
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T18:22:45.305369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.31421
5-th percentile127.31753
Q1127.3212
median127.37259
Q3127.41249
95-th percentile127.45044
Maximum127.45882
Range0.1446072
Interquartile range (IQR)0.091284

Descriptive statistics

Standard deviation0.048453639
Coefficient of variation (CV)0.0003804061
Kurtosis-1.2820425
Mean127.37345
Median Absolute Deviation (MAD)0.0510619
Skewness0.29864744
Sum4712.8178
Variance0.0023477551
MonotonicityNot monotonic
2023-12-12T18:22:45.481441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
127.4586979 1
 
2.7%
127.3175295 1
 
2.7%
127.3544829 1
 
2.7%
127.3541671 1
 
2.7%
127.3417902 1
 
2.7%
127.3413766 1
 
2.7%
127.3309636 1
 
2.7%
127.3212047 1
 
2.7%
127.3215272 1
 
2.7%
127.3175302 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
127.3142078 1
2.7%
127.3175295 1
2.7%
127.3175302 1
2.7%
127.3176536 1
2.7%
127.3181104 1
2.7%
127.3181446 1
2.7%
127.3181912 1
2.7%
127.3193579 1
2.7%
127.3196255 1
2.7%
127.3212047 1
2.7%
ValueCountFrequency (%)
127.458815 1
2.7%
127.4586979 1
2.7%
127.4483749 1
2.7%
127.4431461 1
2.7%
127.4428755 1
2.7%
127.4329277 1
2.7%
127.4327435 1
2.7%
127.4253481 1
2.7%
127.419443 1
2.7%
127.4124887 1
2.7%

Interactions

2023-12-12T18:22:42.071027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:41.805803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:42.224050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:41.934709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:22:45.617951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역사호기설치위치운행구간(하부)위도(WGS84)경도(WGS84)
역사1.0000.0000.2900.9760.9921.000
호기0.0001.0000.9780.0000.0000.000
설치위치0.2900.9781.0000.6050.5210.486
운행구간(하부)0.9760.0000.6051.0000.6550.596
위도(WGS84)0.9920.0000.5210.6551.0000.907
경도(WGS84)1.0000.0000.4860.5960.9071.000
2023-12-12T18:22:45.732141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치호기운행구간(하부)
설치위치1.0000.7000.277
호기0.7001.0000.000
운행구간(하부)0.2770.0001.000
2023-12-12T18:22:45.842702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도(WGS84)경도(WGS84)호기설치위치운행구간(하부)
위도(WGS84)1.000-0.7710.0000.2170.443
경도(WGS84)-0.7711.0000.0000.1940.385
호기0.0000.0001.0000.7000.000
설치위치0.2170.1940.7001.0000.277
운행구간(하부)0.4430.3850.0000.2771.000

Missing values

2023-12-12T18:22:42.399643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:22:42.553928image/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

역사호기내외설치위치운행구간(상부)운행구간(하부)위도(WGS84)경도(WGS84)
0판암역1외1,2번출구측지상지하1층36.392258127.458698
1판암역2외3,4번출구측지상지하1층36.316781127.458815
2신흥역1외2번출구측지상지하2층36.319685127.448375
3대동역1외1번출구측지상지하1층36.329569127.443146
4대동역2외8번출구측지상지하1층36.329342127.442875
5대전역1외1번출구측지상지하3층36.331437127.432744
6대전역2외3번출구측지상지하3층36.331038127.432928
7중앙로역1외2번출구측지상지하3층36.328325127.425348
8중구청역1외3번출구측지상지하2층36.325057127.419443
9서대전네거리역1외1번출구측지상지하2층36.322009127.412489
역사호기내외설치위치운행구간(상부)운행구간(하부)위도(WGS84)경도(WGS84)
27현충원역2외3,4번출구측지상지하1층36.359582127.321527
28월드컵경기장역1외1,2번출구측지상지하1층36.366549127.31753
29월드컵경기장역2외3,4번출구측지상지하1층36.367203127.31753
30월드컵경기장역3외5,6번출구측지상지하1층36.367197127.318191
31월드컵경기장역4외7번출구측지상지하1층36.366649127.318145
32노은역1외1,2번출구측지상지하1층36.37405127.317654
33노은역2외3,4번출구측지상지하1층36.374134127.31811
34지족역1외3,4번출구측지상지하1층36.384278127.319358
35지족역2외1번 출구측지상지하2층36.384281127.319626
36반석역1외2번출구측지상지하2층36.392258127.314208