Overview

Dataset statistics

Number of variables12
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory103.7 B

Variable types

Numeric3
Text8
Categorical1

Dataset

Description파일 다운로드
Author서울교통공사
URLhttps://data.seoul.go.kr/dataList/OA-13213/F/1/datasetView.do

Alerts

연번 is highly overall correlated with 단위High correlation
1호선 is highly overall correlated with 8호선High correlation
8호선 is highly overall correlated with 1호선High correlation
단위 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
장비명 has unique valuesUnique
1호선 has 4 (14.3%) zerosZeros
8호선 has 6 (21.4%) zerosZeros

Reproduction

Analysis started2024-04-29 16:44:25.634107
Analysis finished2024-04-29 16:44:27.108596
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.5
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-04-30T01:44:27.179499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.35
Q17.75
median14.5
Q321.25
95-th percentile26.65
Maximum28
Range27
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.2259751
Coefficient of variation (CV)0.56730863
Kurtosis-1.2
Mean14.5
Median Absolute Deviation (MAD)7
Skewness0
Sum406
Variance67.666667
MonotonicityStrictly increasing
2024-04-30T01:44:27.323551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 1
 
3.6%
16 1
 
3.6%
28 1
 
3.6%
27 1
 
3.6%
26 1
 
3.6%
25 1
 
3.6%
24 1
 
3.6%
23 1
 
3.6%
22 1
 
3.6%
21 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1 1
3.6%
2 1
3.6%
3 1
3.6%
4 1
3.6%
5 1
3.6%
6 1
3.6%
7 1
3.6%
8 1
3.6%
9 1
3.6%
10 1
3.6%
ValueCountFrequency (%)
28 1
3.6%
27 1
3.6%
26 1
3.6%
25 1
3.6%
24 1
3.6%
23 1
3.6%
22 1
3.6%
21 1
3.6%
20 1
3.6%
19 1
3.6%

시설명
Text

Distinct15
Distinct (%)53.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-30T01:44:27.485832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.75
Min length3

Characters and Unicode

Total characters133
Distinct characters44
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

Unique8 ?
Unique (%)28.6%

Sample

1st row교환설비
2nd row교환설비
3rd row열차무선
4th row열차무선
5th row열차무선
ValueCountFrequency (%)
정보통신망 5
17.9%
열차무선 3
10.7%
선로설비 3
10.7%
화상모니터링 3
10.7%
교환설비 2
 
7.1%
전화기 2
 
7.1%
비상통화장치 2
 
7.1%
재난방송 1
 
3.6%
광전송설비 1
 
3.6%
무정전전원설비 1
 
3.6%
Other values (5) 5
17.9%
2024-04-30T01:44:27.811801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 10
 
7.5%
설 8
 
6.0%
선 7
 
5.3%
화 7
 
5.3%
정 7
 
5.3%
통 7
 
5.3%
보 6
 
4.5%
전 5
 
3.8%
망 5
 
3.8%
신 5
 
3.8%
Other values (34) 66
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 10
 
7.5%
설 8
 
6.0%
선 7
 
5.3%
화 7
 
5.3%
정 7
 
5.3%
통 7
 
5.3%
보 6
 
4.5%
전 5
 
3.8%
망 5
 
3.8%
신 5
 
3.8%
Other values (34) 66
49.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 10
 
7.5%
설 8
 
6.0%
선 7
 
5.3%
화 7
 
5.3%
정 7
 
5.3%
통 7
 
5.3%
보 6
 
4.5%
전 5
 
3.8%
망 5
 
3.8%
신 5
 
3.8%
Other values (34) 66
49.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 10
 
7.5%
설 8
 
6.0%
선 7
 
5.3%
화 7
 
5.3%
정 7
 
5.3%
통 7
 
5.3%
보 6
 
4.5%
전 5
 
3.8%
망 5
 
3.8%
신 5
 
3.8%
Other values (34) 66
49.6%

장비명
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-30T01:44:28.007190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.2857143
Min length2

Characters and Unicode

Total characters148
Distinct characters87
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st rowIP교환기
2nd row게이트웨이
3rd row기지국
4th row이동국
5th rowIRCP
ValueCountFrequency (%)
ip교환기 1
 
3.6%
게이트웨이 1
 
3.6%
음성유도기 1
 
3.6%
콜폰 1
 
3.6%
승강장 1
 
3.6%
워크그룹스위치 1
 
3.6%
에지스위치 1
 
3.6%
백본스위치 1
 
3.6%
코어스위치 1
 
3.6%
방화벽 1
 
3.6%
Other values (18) 18
64.3%
2024-04-30T01:44:28.300927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
치 5
 
3.4%
스 5
 
3.4%
( 5
 
3.4%
) 5
 
3.4%
선 4
 
2.7%
위 4
 
2.7%
전 4
 
2.7%
비 4
 
2.7%
설 4
 
2.7%
기 3
 
2.0%
Other values (77) 105
70.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
84.5%
Uppercase Letter 12
 
8.1%
Open Punctuation 5
 
3.4%
Close Punctuation 5
 
3.4%
Other Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
치 5
 
4.0%
스 5
 
4.0%
선 4
 
3.2%
위 4
 
3.2%
전 4
 
3.2%
비 4
 
3.2%
설 4
 
3.2%
기 3
 
2.4%
이 3
 
2.4%
용 3
 
2.4%
Other values (67) 86
68.8%
Uppercase Letter
ValueCountFrequency (%)
R 3
25.0%
V 2
16.7%
P 2
16.7%
I 2
16.7%
D 1
 
8.3%
N 1
 
8.3%
C 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125
84.5%
Latin 12
 
8.1%
Common 11
 
7.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
치 5
 
4.0%
스 5
 
4.0%
선 4
 
3.2%
위 4
 
3.2%
전 4
 
3.2%
비 4
 
3.2%
설 4
 
3.2%
기 3
 
2.4%
이 3
 
2.4%
용 3
 
2.4%
Other values (67) 86
68.8%
Latin
ValueCountFrequency (%)
R 3
25.0%
V 2
16.7%
P 2
16.7%
I 2
16.7%
D 1
 
8.3%
N 1
 
8.3%
C 1
 
8.3%
Common
ValueCountFrequency (%)
( 5
45.5%
) 5
45.5%
/ 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125
84.5%
ASCII 23
 
15.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
치 5
 
4.0%
스 5
 
4.0%
선 4
 
3.2%
위 4
 
3.2%
전 4
 
3.2%
비 4
 
3.2%
설 4
 
3.2%
기 3
 
2.4%
이 3
 
2.4%
용 3
 
2.4%
Other values (67) 86
68.8%
ASCII
ValueCountFrequency (%)
( 5
21.7%
) 5
21.7%
R 3
13.0%
V 2
 
8.7%
P 2
 
8.7%
I 2
 
8.7%
D 1
 
4.3%
N 1
 
4.3%
/ 1
 
4.3%
C 1
 
4.3%

단위
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
식
15 
대
8 
Km
3 
장치
2 

Length

Max length2
Median length1
Mean length1.1785714
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row식
2nd row식
3rd row장치
4th row장치
5th row대

Common Values

ValueCountFrequency (%)
식 15
53.6%
대 8
28.6%
Km 3
 
10.7%
장치 2
 
7.1%

Length

2024-04-30T01:44:28.419164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T01:44:28.528603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식 15
53.6%
대 8
28.6%
km 3
 
10.7%
장치 2
 
7.1%

1호선
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.642857
Minimum0
Maximum972
Zeros4
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-04-30T01:44:28.670962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.75
median10.5
Q333.5
95-th percentile295.75
Maximum972
Range972
Interquartile range (IQR)28.75

Descriptive statistics

Standard deviation192.20402
Coefficient of variation (CV)2.5749821
Kurtosis18.79011
Mean74.642857
Median Absolute Deviation (MAD)10.5
Skewness4.1455176
Sum2090
Variance36942.386
MonotonicityNot monotonic
2024-04-30T01:44:28.818881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
10 5
17.9%
0 4
14.3%
11 3
10.7%
5 2
 
7.1%
32 2
 
7.1%
22 1
 
3.6%
286 1
 
3.6%
148 1
 
3.6%
56 1
 
3.6%
74 1
 
3.6%
Other values (7) 7
25.0%
ValueCountFrequency (%)
0 4
14.3%
1 1
 
3.6%
2 1
 
3.6%
4 1
 
3.6%
5 2
 
7.1%
10 5
17.9%
11 3
10.7%
22 1
 
3.6%
29 1
 
3.6%
32 2
 
7.1%
ValueCountFrequency (%)
972 1
3.6%
301 1
3.6%
286 1
3.6%
148 1
3.6%
74 1
3.6%
56 1
3.6%
38 1
3.6%
32 2
7.1%
29 1
3.6%
22 1
3.6%

2호선
Text

Distinct24
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-30T01:44:28.984004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.3214286
Min length1

Characters and Unicode

Total characters65
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)75.0%

Sample

1st row2
2nd row50
3rd row19
4th row167
5th row3
ValueCountFrequency (%)
50 3
 
10.7%
2 2
 
7.1%
0 2
 
7.1%
2,029 1
 
3.6%
229 1
 
3.6%
706 1
 
3.6%
282 1
 
3.6%
389 1
 
3.6%
163 1
 
3.6%
14 1
 
3.6%
Other values (14) 14
50.0%
2024-04-30T01:44:29.336483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
20.0%
5 7
10.8%
0 7
10.8%
1 7
10.8%
3 7
10.8%
4 6
9.2%
9 5
 
7.7%
7 5
 
7.7%
6 3
 
4.6%
8 3
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
96.9%
Other Punctuation 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
20.6%
5 7
11.1%
0 7
11.1%
1 7
11.1%
3 7
11.1%
4 6
9.5%
9 5
 
7.9%
7 5
 
7.9%
6 3
 
4.8%
8 3
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
20.0%
5 7
10.8%
0 7
10.8%
1 7
10.8%
3 7
10.8%
4 6
9.2%
9 5
 
7.7%
7 5
 
7.7%
6 3
 
4.6%
8 3
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
20.0%
5 7
10.8%
0 7
10.8%
1 7
10.8%
3 7
10.8%
4 6
9.2%
9 5
 
7.7%
7 5
 
7.7%
6 3
 
4.6%
8 3
 
4.6%

3호선
Text

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-30T01:44:29.493199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.2857143
Min length1

Characters and Unicode

Total characters64
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)92.9%

Sample

1st row2
2nd row33
3rd row29
4th row140
5th row16
ValueCountFrequency (%)
0 2
 
7.1%
2 1
 
3.6%
142 1
 
3.6%
500 1
 
3.6%
382 1
 
3.6%
172 1
 
3.6%
260 1
 
3.6%
107 1
 
3.6%
8 1
 
3.6%
78 1
 
3.6%
Other values (17) 17
60.7%
2024-04-30T01:44:29.819561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
17.2%
2 9
14.1%
1 9
14.1%
0 8
12.5%
5 6
9.4%
4 5
7.8%
6 4
 
6.2%
7 4
 
6.2%
8 4
 
6.2%
9 2
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
96.9%
Other Punctuation 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 11
17.7%
2 9
14.5%
1 9
14.5%
0 8
12.9%
5 6
9.7%
4 5
8.1%
6 4
 
6.5%
7 4
 
6.5%
8 4
 
6.5%
9 2
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 11
17.2%
2 9
14.1%
1 9
14.1%
0 8
12.5%
5 6
9.4%
4 5
7.8%
6 4
 
6.2%
7 4
 
6.2%
8 4
 
6.2%
9 2
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 11
17.2%
2 9
14.1%
1 9
14.1%
0 8
12.5%
5 6
9.4%
4 5
7.8%
6 4
 
6.2%
7 4
 
6.2%
8 4
 
6.2%
9 2
 
3.1%

4호선
Text

Distinct24
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-30T01:44:29.980985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.2142857
Min length1

Characters and Unicode

Total characters62
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)75.0%

Sample

1st row2
2nd row27
3rd row25
4th row104
5th row13
ValueCountFrequency (%)
2 3
 
10.7%
104 2
 
7.1%
26 2
 
7.1%
1,144 1
 
3.6%
61 1
 
3.6%
379 1
 
3.6%
140 1
 
3.6%
207 1
 
3.6%
85 1
 
3.6%
8 1
 
3.6%
Other values (14) 14
50.0%
2024-04-30T01:44:30.275414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
19.4%
1 10
16.1%
6 7
11.3%
4 7
11.3%
3 7
11.3%
0 5
8.1%
7 4
 
6.5%
5 3
 
4.8%
8 3
 
4.8%
9 2
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
96.8%
Other Punctuation 2
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12
20.0%
1 10
16.7%
6 7
11.7%
4 7
11.7%
3 7
11.7%
0 5
8.3%
7 4
 
6.7%
5 3
 
5.0%
8 3
 
5.0%
9 2
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
19.4%
1 10
16.1%
6 7
11.3%
4 7
11.3%
3 7
11.3%
0 5
8.1%
7 4
 
6.5%
5 3
 
4.8%
8 3
 
4.8%
9 2
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
19.4%
1 10
16.1%
6 7
11.3%
4 7
11.3%
3 7
11.3%
0 5
8.1%
7 4
 
6.5%
5 3
 
4.8%
8 3
 
4.8%
9 2
 
3.2%

5호선
Text

Distinct18
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-30T01:44:30.443231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.3214286
Min length1

Characters and Unicode

Total characters65
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)53.6%

Sample

1st row1
2nd row56
3rd row30
4th row158
5th row2
ValueCountFrequency (%)
0 5
17.9%
56 5
17.9%
58 3
 
10.7%
1,214 1
 
3.6%
1 1
 
3.6%
310 1
 
3.6%
765 1
 
3.6%
338 1
 
3.6%
122 1
 
3.6%
1,910 1
 
3.6%
Other values (8) 8
28.6%
2024-04-30T01:44:30.723037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 14
21.5%
1 12
18.5%
0 9
13.8%
6 8
12.3%
8 5
 
7.7%
3 4
 
6.2%
2 4
 
6.2%
, 3
 
4.6%
9 2
 
3.1%
7 2
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
95.4%
Other Punctuation 3
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 14
22.6%
1 12
19.4%
0 9
14.5%
6 8
12.9%
8 5
 
8.1%
3 4
 
6.5%
2 4
 
6.5%
9 2
 
3.2%
7 2
 
3.2%
4 2
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 14
21.5%
1 12
18.5%
0 9
13.8%
6 8
12.3%
8 5
 
7.7%
3 4
 
6.2%
2 4
 
6.2%
, 3
 
4.6%
9 2
 
3.1%
7 2
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 14
21.5%
1 12
18.5%
0 9
13.8%
6 8
12.3%
8 5
 
7.7%
3 4
 
6.2%
2 4
 
6.2%
, 3
 
4.6%
9 2
 
3.1%
7 2
 
3.1%

6호선
Text

Distinct16
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-30T01:44:30.881751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1428571
Min length1

Characters and Unicode

Total characters60
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)42.9%

Sample

1st row0
2nd row38
3rd row12
4th row83
5th row11
ValueCountFrequency (%)
0 6
21.4%
39 5
17.9%
38 3
10.7%
11 2
 
7.1%
12 1
 
3.6%
83 1
 
3.6%
115 1
 
3.6%
107 1
 
3.6%
40 1
 
3.6%
140 1
 
3.6%
Other values (6) 6
21.4%
2024-04-30T01:44:31.151878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
23.3%
1 12
20.0%
3 9
15.0%
9 6
10.0%
8 5
 
8.3%
2 4
 
6.7%
5 3
 
5.0%
7 3
 
5.0%
4 3
 
5.0%
, 1
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
98.3%
Other Punctuation 1
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
23.7%
1 12
20.3%
3 9
15.3%
9 6
10.2%
8 5
 
8.5%
2 4
 
6.8%
5 3
 
5.1%
7 3
 
5.1%
4 3
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
23.3%
1 12
20.0%
3 9
15.0%
9 6
10.0%
8 5
 
8.3%
2 4
 
6.7%
5 3
 
5.0%
7 3
 
5.0%
4 3
 
5.0%
, 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
23.3%
1 12
20.0%
3 9
15.0%
9 6
10.0%
8 5
 
8.3%
2 4
 
6.7%
5 3
 
5.0%
7 3
 
5.0%
4 3
 
5.0%
, 1
 
1.7%

7호선
Text

Distinct19
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-30T01:44:31.300204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.2142857
Min length1

Characters and Unicode

Total characters62
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)57.1%

Sample

1st row1
2nd row42
3rd row22
4th row141
5th row2
ValueCountFrequency (%)
0 5
17.9%
42 4
14.3%
44 3
 
10.7%
248 1
 
3.6%
1 1
 
3.6%
213 1
 
3.6%
558 1
 
3.6%
251 1
 
3.6%
83 1
 
3.6%
1,513 1
 
3.6%
Other values (9) 9
32.1%
2024-04-30T01:44:31.578382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 15
24.2%
1 11
17.7%
2 10
16.1%
0 8
12.9%
5 6
 
9.7%
8 5
 
8.1%
3 3
 
4.8%
, 2
 
3.2%
9 2
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
96.8%
Other Punctuation 2
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 15
25.0%
1 11
18.3%
2 10
16.7%
0 8
13.3%
5 6
 
10.0%
8 5
 
8.3%
3 3
 
5.0%
9 2
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 15
24.2%
1 11
17.7%
2 10
16.1%
0 8
12.9%
5 6
 
9.7%
8 5
 
8.1%
3 3
 
4.8%
, 2
 
3.2%
9 2
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 15
24.2%
1 11
17.7%
2 10
16.1%
0 8
12.9%
5 6
 
9.7%
8 5
 
8.1%
3 3
 
4.8%
, 2
 
3.2%
9 2
 
3.2%

8호선
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.25
Minimum0
Maximum1506
Zeros6
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-04-30T01:44:31.702013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median18.5
Q366.5
95-th percentile399.65
Maximum1506
Range1506
Interquartile range (IQR)61.5

Descriptive statistics

Standard deviation292.83058
Coefficient of variation (CV)2.5630686
Kurtosis20.338779
Mean114.25
Median Absolute Deviation (MAD)18.5
Skewness4.3216487
Sum3199
Variance85749.75
MonotonicityNot monotonic
2024-04-30T01:44:31.813154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 6
21.4%
18 4
14.3%
19 3
10.7%
5 2
 
7.1%
17 2
 
7.1%
1506 1
 
3.6%
347 1
 
3.6%
251 1
 
3.6%
106 1
 
3.6%
38 1
 
3.6%
Other values (6) 6
21.4%
ValueCountFrequency (%)
0 6
21.4%
5 2
 
7.1%
17 2
 
7.1%
18 4
14.3%
19 3
10.7%
34 1
 
3.6%
38 1
 
3.6%
40 1
 
3.6%
54 1
 
3.6%
104 1
 
3.6%
ValueCountFrequency (%)
1506 1
3.6%
428 1
3.6%
347 1
3.6%
251 1
3.6%
118 1
3.6%
106 1
3.6%
104 1
3.6%
54 1
3.6%
40 1
3.6%
38 1
3.6%

Interactions

2024-04-30T01:44:26.492106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:26.014688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:26.231377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:26.566200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:26.086874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:26.305405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:26.642582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:26.155621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:26.400836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T01:44:31.906216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설명장비명단위1호선2호선3호선4호선5호선6호선7호선8호선
연번1.0000.9441.0000.8150.4910.7021.0000.8700.7640.7730.8430.399
시설명0.9441.0001.0000.8970.6850.0001.0000.8760.7950.1930.8110.168
장비명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
단위0.8150.8971.0001.0000.0001.0001.0000.8980.9621.0001.0000.451
1호선0.4910.6851.0000.0001.0001.0001.0001.0001.0001.0001.0001.000
2호선0.7020.0001.0001.0001.0001.0000.9880.9940.9870.9940.9861.000
3호선1.0001.0001.0001.0001.0000.9881.0001.0001.0001.0001.0001.000
4호선0.8700.8761.0000.8981.0000.9941.0001.0000.9480.9800.9531.000
5호선0.7640.7951.0000.9621.0000.9871.0000.9481.0000.9830.9931.000
6호선0.7730.1931.0001.0001.0000.9941.0000.9800.9831.0000.9941.000
7호선0.8430.8111.0001.0001.0000.9861.0000.9530.9930.9941.0001.000
8호선0.3990.1681.0000.4511.0001.0001.0001.0001.0001.0001.0001.000
2024-04-30T01:44:32.026487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번1호선8호선단위
연번1.0000.3610.1430.551
1호선0.3611.0000.6810.000
8호선0.1430.6811.0000.177
단위0.5510.0000.1771.000

Missing values

2024-04-30T01:44:26.852775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T01:44:27.050141image/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

연번시설명장비명단위1호선2호선3호선4호선5호선6호선7호선8호선
01교환설비IP교환기식02221010
12교환설비게이트웨이식1050332756384217
23열차무선기지국장치519292530122218
34열차무선이동국장치321671401041588314140
45열차무선IRCP대53161321125
56재난방송복합통신설비식1137312356384017
67광전송설비전송설비(주/부)식1155362858394419
78무정전전원설비무정전전원설비식1072433259394419
89방송설비방송설비(역사용)식1050342656394218
910배선반배선반식005158394419
연번시설명장비명단위1호선2호선3호선4호선5호선6호선7호선8호선
1819화상모니터링DVR(NVR)대221237863122808338
1920정보통신망방화벽식00020000
2021정보통신망코어스위치식02020000
2122정보통신망백본스위치식214880000
2223정보통신망에지스위치식32163107850000
2324정보통신망워크그룹스위치식743892602070000
2425비상통화장치승강장식56282172140338205251106
2526비상통화장치콜폰대148706382379765501558251
2627음성유도기음성유도기대2869725006041,146721881347
2728열차정보안내시스템열차정보안내시스템식1050352656394218