Overview

Dataset statistics

Number of variables6
Number of observations115
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory53.1 B

Variable types

Numeric3
Text2
Categorical1

Dataset

Description서울교통공사 전동휠체어 급속충전기 운영정보 입니다. 해당 데이터는 연번, 호선, 역번호, 역명, 운영수량, 설치위치 정보로 구성되어 있습니다. 2022년 9월 기준
Author서울교통공사
URLhttps://www.data.go.kr/data/15085994/fileData.do

Alerts

충전기수 has constant value ""Constant
연번 is highly overall correlated with 호선 and 1 other fieldsHigh correlation
호선 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
고유역번호(외부역코드) is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
고유역번호(외부역코드) has unique valuesUnique
역명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:29:13.931642
Analysis finished2023-12-12 08:29:15.506489
Duration1.57 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58
Minimum1
Maximum115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T17:29:15.600576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.7
Q129.5
median58
Q386.5
95-th percentile109.3
Maximum115
Range114
Interquartile range (IQR)57

Descriptive statistics

Standard deviation33.341666
Coefficient of variation (CV)0.5748563
Kurtosis-1.2
Mean58
Median Absolute Deviation (MAD)29
Skewness0
Sum6670
Variance1111.6667
MonotonicityStrictly increasing
2023-12-12T17:29:15.814727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
74 1
 
0.9%
86 1
 
0.9%
85 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
Other values (105) 105
91.3%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
115 1
0.9%
114 1
0.9%
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%

호선
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1913043
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T17:29:15.969409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median6
Q37
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.0386427
Coefficient of variation (CV)0.39270337
Kurtosis-0.92023647
Mean5.1913043
Median Absolute Deviation (MAD)1
Skewness-0.41589193
Sum597
Variance4.1560641
MonotonicityIncreasing
2023-12-12T17:29:16.114090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
7 24
20.9%
6 20
17.4%
5 17
14.8%
2 14
12.2%
4 14
12.2%
8 14
12.2%
3 8
 
7.0%
1 4
 
3.5%
ValueCountFrequency (%)
1 4
 
3.5%
2 14
12.2%
3 8
 
7.0%
4 14
12.2%
5 17
14.8%
6 20
17.4%
7 24
20.9%
8 14
12.2%
ValueCountFrequency (%)
8 14
12.2%
7 24
20.9%
6 20
17.4%
5 17
14.8%
4 14
12.2%
3 8
 
7.0%
2 14
12.2%
1 4
 
3.5%

고유역번호(외부역코드)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1852.0696
Minimum152
Maximum2828
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T17:29:16.272331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum152
5-th percentile208.4
Q1415
median2611
Q32723.5
95-th percentile2822.3
Maximum2828
Range2676
Interquartile range (IQR)2308.5

Descriptive statistics

Standard deviation1138.2939
Coefficient of variation (CV)0.61460646
Kurtosis-1.5843633
Mean1852.0696
Median Absolute Deviation (MAD)135
Skewness-0.64003742
Sum212988
Variance1295713
MonotonicityNot monotonic
2023-12-12T17:29:16.464290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
152 1
 
0.9%
2644 1
 
0.9%
2723 1
 
0.9%
2721 1
 
0.9%
2720 1
 
0.9%
2717 1
 
0.9%
2716 1
 
0.9%
2715 1
 
0.9%
2714 1
 
0.9%
2713 1
 
0.9%
Other values (105) 105
91.3%
ValueCountFrequency (%)
152 1
0.9%
153 1
0.9%
157 1
0.9%
159 1
0.9%
205 1
0.9%
207 1
0.9%
209 1
0.9%
210 1
0.9%
211 1
0.9%
212 1
0.9%
ValueCountFrequency (%)
2828 1
0.9%
2827 1
0.9%
2826 1
0.9%
2825 1
0.9%
2824 1
0.9%
2823 1
0.9%
2822 1
0.9%
2821 1
0.9%
2820 1
0.9%
2816 1
0.9%

역명
Text

UNIQUE 

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T17:29:16.802583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length4.9826087
Min length3

Characters and Unicode

Total characters573
Distinct characters158
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

Unique115 ?
Unique (%)100.0%

Sample

1st row종각역
2nd row종로3가역(1호선)
3rd row제기동역
4th row동묘앞역(1호선)
5th row동대문역사문화공원역(2호선)
ValueCountFrequency (%)
종각역 1
 
0.9%
역촌역 1
 
0.9%
중화역 1
 
0.9%
먹골역 1
 
0.9%
하계역 1
 
0.9%
중계역 1
 
0.9%
노원역(7호선 1
 
0.9%
마들역 1
 
0.9%
수락산역 1
 
0.9%
도봉산역 1
 
0.9%
Other values (105) 105
91.3%
2023-12-12T17:29:17.265080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
역 117
 
20.4%
( 27
 
4.7%
) 27
 
4.7%
호 25
 
4.4%
선 24
 
4.2%
대 17
 
3.0%
산 10
 
1.7%
문 10
 
1.7%
화 9
 
1.6%
동 9
 
1.6%
Other values (148) 298
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 491
85.7%
Decimal Number 28
 
4.9%
Open Punctuation 27
 
4.7%
Close Punctuation 27
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 117
23.8%
호 25
 
5.1%
선 24
 
4.9%
대 17
 
3.5%
산 10
 
2.0%
문 10
 
2.0%
화 9
 
1.8%
동 9
 
1.8%
구 8
 
1.6%
수 8
 
1.6%
Other values (138) 254
51.7%
Decimal Number
ValueCountFrequency (%)
4 6
21.4%
2 5
17.9%
7 5
17.9%
6 4
14.3%
3 3
10.7%
5 2
 
7.1%
1 2
 
7.1%
8 1
 
3.6%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 491
85.7%
Common 82
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 117
23.8%
호 25
 
5.1%
선 24
 
4.9%
대 17
 
3.5%
산 10
 
2.0%
문 10
 
2.0%
화 9
 
1.8%
동 9
 
1.8%
구 8
 
1.6%
수 8
 
1.6%
Other values (138) 254
51.7%
Common
ValueCountFrequency (%)
( 27
32.9%
) 27
32.9%
4 6
 
7.3%
2 5
 
6.1%
7 5
 
6.1%
6 4
 
4.9%
3 3
 
3.7%
5 2
 
2.4%
1 2
 
2.4%
8 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 491
85.7%
ASCII 82
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
역 117
23.8%
호 25
 
5.1%
선 24
 
4.9%
대 17
 
3.5%
산 10
 
2.0%
문 10
 
2.0%
화 9
 
1.8%
동 9
 
1.8%
구 8
 
1.6%
수 8
 
1.6%
Other values (138) 254
51.7%
ASCII
ValueCountFrequency (%)
( 27
32.9%
) 27
32.9%
4 6
 
7.3%
2 5
 
6.1%
7 5
 
6.1%
6 4
 
4.9%
3 3
 
3.7%
5 2
 
2.4%
1 2
 
2.4%
8 1
 
1.2%

충전기수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
1
115 

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 (%)
1 115
100.0%

Length

2023-12-12T17:29:17.416866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:17.558766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 115
100.0%

설치위치
Text

Distinct110
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T17:29:17.907674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length29
Mean length17.443478
Min length4

Characters and Unicode

Total characters2006
Distinct characters175
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)92.2%

Sample

1st row3, 4번 출구쪽 게이트 방면 45m 지점
2nd row12번 출구로 내려와서 20m 지점
3rd row1번 출구 개찰구 앞 5m 지점
4th rowB1층 상선 승강장 2-2 지점
5th row2번출구 하부 비상출입문 옆
ValueCountFrequency (%)
옆 46
 
8.9%
지하1층 36
 
7.0%
벽면 18
 
3.5%
대합실 18
 
3.5%
지점 15
 
2.9%
출구 14
 
2.7%
지하2층 12
 
2.3%
게이트 9
 
1.7%
화장실 9
 
1.7%
e/l 9
 
1.7%
Other values (193) 330
64.0%
2023-12-12T17:29:18.523377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
404
 
20.1%
지 84
 
4.2%
층 75
 
3.7%
1 75
 
3.7%
하 68
 
3.4%
실 57
 
2.8%
옆 50
 
2.5%
구 47
 
2.3%
출 40
 
2.0%
번 39
 
1.9%
Other values (165) 1067
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1289
64.3%
Space Separator 404
 
20.1%
Decimal Number 185
 
9.2%
Uppercase Letter 55
 
2.7%
Other Punctuation 24
 
1.2%
Lowercase Letter 17
 
0.8%
Close Punctuation 15
 
0.7%
Open Punctuation 15
 
0.7%
Dash Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 84
 
6.5%
층 75
 
5.8%
하 68
 
5.3%
실 57
 
4.4%
옆 50
 
3.9%
구 47
 
3.6%
출 40
 
3.1%
번 39
 
3.0%
이 28
 
2.2%
면 26
 
2.0%
Other values (139) 775
60.1%
Decimal Number
ValueCountFrequency (%)
1 75
40.5%
2 37
20.0%
3 20
 
10.8%
4 15
 
8.1%
5 12
 
6.5%
0 10
 
5.4%
7 6
 
3.2%
6 5
 
2.7%
8 3
 
1.6%
9 2
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
E 17
30.9%
B 14
25.5%
L 11
20.0%
M 7
12.7%
S 3
 
5.5%
V 3
 
5.5%
Other Punctuation
ValueCountFrequency (%)
/ 17
70.8%
, 5
 
20.8%
# 1
 
4.2%
. 1
 
4.2%
Space Separator
ValueCountFrequency (%)
404
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
→ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1289
64.3%
Common 645
32.2%
Latin 72
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 84
 
6.5%
층 75
 
5.8%
하 68
 
5.3%
실 57
 
4.4%
옆 50
 
3.9%
구 47
 
3.6%
출 40
 
3.1%
번 39
 
3.0%
이 28
 
2.2%
면 26
 
2.0%
Other values (139) 775
60.1%
Common
ValueCountFrequency (%)
404
62.6%
1 75
 
11.6%
2 37
 
5.7%
3 20
 
3.1%
/ 17
 
2.6%
) 15
 
2.3%
4 15
 
2.3%
( 15
 
2.3%
5 12
 
1.9%
0 10
 
1.6%
Other values (9) 25
 
3.9%
Latin
ValueCountFrequency (%)
m 17
23.6%
E 17
23.6%
B 14
19.4%
L 11
15.3%
M 7
9.7%
S 3
 
4.2%
V 3
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1289
64.3%
ASCII 716
35.7%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
404
56.4%
1 75
 
10.5%
2 37
 
5.2%
3 20
 
2.8%
/ 17
 
2.4%
m 17
 
2.4%
E 17
 
2.4%
) 15
 
2.1%
4 15
 
2.1%
( 15
 
2.1%
Other values (15) 84
 
11.7%
Hangul
ValueCountFrequency (%)
지 84
 
6.5%
층 75
 
5.8%
하 68
 
5.3%
실 57
 
4.4%
옆 50
 
3.9%
구 47
 
3.6%
출 40
 
3.1%
번 39
 
3.0%
이 28
 
2.2%
면 26
 
2.0%
Other values (139) 775
60.1%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

Interactions

2023-12-12T17:29:14.676915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:29:14.156421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:29:14.394366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:29:15.079557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:29:14.245448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:29:14.476727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:29:15.169624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:29:14.323619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:29:14.587364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:29:18.673183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선고유역번호(외부역코드)
연번1.0000.9180.902
호선0.9181.0000.993
고유역번호(외부역코드)0.9020.9931.000
2023-12-12T17:29:18.786634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선고유역번호(외부역코드)
연번1.0000.9881.000
호선0.9881.0000.988
고유역번호(외부역코드)1.0000.9881.000

Missing values

2023-12-12T17:29:15.284767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:29:15.458873image/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

연번호선고유역번호(외부역코드)역명충전기수설치위치
011152종각역13, 4번 출구쪽 게이트 방면 45m 지점
121153종로3가역(1호선)112번 출구로 내려와서 20m 지점
231157제기동역11번 출구 개찰구 앞 5m 지점
341159동묘앞역(1호선)1B1층 상선 승강장 2-2 지점
452205동대문역사문화공원역(2호선)12번출구 하부 비상출입문 옆
562207상왕십리역1지하1층 대합실 중앙
672209한양대역12번출구
782210뚝섬역1대합실 3번출구 E/V옆
892211성수역1가대합실 해피박스옆
9102212건대입구역(2호선)1대합실 위생자판기 옆
연번호선고유역번호(외부역코드)역명충전기수설치위치
10510682816석촌역1지하 1층 종점환기실 앞
10610782820장지역1지하1층 E/L 4호기 앞
10710882821복정역1안내센터 옆 또는 지하 1층 화장실 입구 옆
10810982828남위례역1지상2층 수유실 앞
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