Overview

Dataset statistics

Number of variables9
Number of observations32
Missing cells26
Missing cells (%)9.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory77.1 B

Variable types

Text7
Categorical1
Numeric1

Dataset

Description파일 다운로드
Author서울교통공사
URLhttps://data.seoul.go.kr/dataList/OA-13231/F/1/datasetView.do

Alerts

합계 has 11 (34.4%) missing valuesMissing
1호선 has 2 (6.2%) missing valuesMissing
2호선 순환선 has 1 (3.1%) missing valuesMissing
2호선 성수지선 has 3 (9.4%) missing valuesMissing
2호선 신정지선 has 4 (12.5%) missing valuesMissing
3호선 has 3 (9.4%) missing valuesMissing
4호선 has 2 (6.2%) missing valuesMissing

Reproduction

Analysis started2024-04-29 16:47:21.772630
Analysis finished2024-04-29 16:47:23.185969
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구 분
Text

Distinct21
Distinct (%)65.6%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-04-30T01:47:23.310428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length8.78125
Min length3

Characters and Unicode

Total characters281
Distinct characters49
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

Unique17 ?
Unique (%)53.1%

Sample

1st row궤동연장 계
2nd row궤동연장 본 선
3rd row궤동연장 측 선
4th row도 상(본선) 계
5th row도 상(본선) 자 갈
ValueCountFrequency (%)
장대레일 7
 
8.6%
최장 6
 
7.4%
최소곡선반경(r 5
 
6.2%
침 4
 
4.9%
도유기 4
 
4.9%
계 4
 
4.9%
상(본선 4
 
4.9%
도 4
 
4.9%
설(본선 4
 
4.9%
목부 4
 
4.9%
Other values (23) 35
43.2%
2024-04-30T01:47:23.605717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49
17.4%
장 21
 
7.5%
선 17
 
6.0%
( 14
 
5.0%
) 14
 
5.0%
최 11
 
3.9%
일 10
 
3.6%
레 10
 
3.6%
도 9
 
3.2%
본 9
 
3.2%
Other values (39) 117
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 197
70.1%
Space Separator 49
 
17.4%
Open Punctuation 14
 
5.0%
Close Punctuation 14
 
5.0%
Uppercase Letter 7
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 21
 
10.7%
선 17
 
8.6%
최 11
 
5.6%
일 10
 
5.1%
레 10
 
5.1%
도 9
 
4.6%
본 9
 
4.6%
기 7
 
3.6%
목 7
 
3.6%
대 7
 
3.6%
Other values (34) 89
45.2%
Uppercase Letter
ValueCountFrequency (%)
R 6
85.7%
N 1
 
14.3%
Space Separator
ValueCountFrequency (%)
49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 197
70.1%
Common 77
 
27.4%
Latin 7
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 21
 
10.7%
선 17
 
8.6%
최 11
 
5.6%
일 10
 
5.1%
레 10
 
5.1%
도 9
 
4.6%
본 9
 
4.6%
기 7
 
3.6%
목 7
 
3.6%
대 7
 
3.6%
Other values (34) 89
45.2%
Common
ValueCountFrequency (%)
49
63.6%
( 14
 
18.2%
) 14
 
18.2%
Latin
ValueCountFrequency (%)
R 6
85.7%
N 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 197
70.1%
ASCII 84
29.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49
58.3%
( 14
 
16.7%
) 14
 
16.7%
R 6
 
7.1%
N 1
 
1.2%
Hangul
ValueCountFrequency (%)
장 21
 
10.7%
선 17
 
8.6%
최 11
 
5.6%
일 10
 
5.1%
레 10
 
5.1%
도 9
 
4.6%
본 9
 
4.6%
기 7
 
3.6%
목 7
 
3.6%
대 7
 
3.6%
Other values (34) 89
45.2%

단 위
Categorical

Distinct8
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
m
8 
위치
6 
km
5 
개
4 
대
4 
Other values (3)
5 

Length

Max length2
Median length1
Mean length1.46875
Min length1

Unique

Unique1 ?
Unique (%)3.1%

Sample

1st rowkm
2nd rowkm
3rd rowkm
4th rowm
5th rowm

Common Values

ValueCountFrequency (%)
m 8
25.0%
위치 6
18.8%
km 5
15.6%
개 4
12.5%
대 4
12.5%
구간 2
 
6.2%
개소 2
 
6.2%
틀 1
 
3.1%

Length

2024-04-30T01:47:23.721744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T01:47:23.824515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 8
25.0%
위치 6
18.8%
km 5
15.6%
개 4
12.5%
대 4
12.5%
구간 2
 
6.2%
개소 2
 
6.2%
틀 1
 
3.1%

합계
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)95.2%
Missing11
Missing (%)34.4%
Infinite0
Infinite (%)0.0%
Mean97524.467
Minimum8
Maximum730311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-30T01:47:23.924179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile23
Q1121.6
median535
Q3134865
95-th percentile390097
Maximum730311
Range730303
Interquartile range (IQR)134743.4

Descriptive statistics

Standard deviation187248.38
Coefficient of variation (CV)1.9200144
Kurtosis5.9423731
Mean97524.467
Median Absolute Deviation (MAD)512
Skewness2.370302
Sum2048013.8
Variance3.5061954 × 1010
MonotonicityNot monotonic
2024-04-30T01:47:24.031389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
283.1 2
 
6.2%
18331.0 1
 
3.1%
23.0 1
 
3.1%
8.0 1
 
3.1%
112.0 1
 
3.1%
143.0 1
 
3.1%
653.0 1
 
3.1%
120.3 1
 
3.1%
535.0 1
 
3.1%
76.0 1
 
3.1%
Other values (10) 10
31.2%
(Missing) 11
34.4%
ValueCountFrequency (%)
8.0 1
3.1%
23.0 1
3.1%
76.0 1
3.1%
112.0 1
3.1%
120.3 1
3.1%
121.6 1
3.1%
143.0 1
3.1%
283.1 2
6.2%
404.7 1
3.1%
535.0 1
3.1%
ValueCountFrequency (%)
730311.0 1
3.1%
390097.0 1
3.1%
307630.0 1
3.1%
283149.0 1
3.1%
145028.0 1
3.1%
134865.0 1
3.1%
32584.0 1
3.1%
18331.0 1
3.1%
3256.0 1
3.1%
653.0 1
3.1%

1호선
Text

MISSING 

Distinct26
Distinct (%)86.7%
Missing2
Missing (%)6.2%
Memory size388.0 B
2024-04-30T01:47:24.188296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.1
Min length1

Characters and Unicode

Total characters93
Distinct characters22
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)73.3%

Sample

1st row19.9
2nd row18.6
3rd row1.3
4th row18580
5th row4580
ValueCountFrequency (%)
4 2
 
6.5%
종각 2
 
6.5%
18.6 2
 
6.5%
2 2
 
6.5%
4k982 1
 
3.2%
선 1
 
3.2%
하 1
 
3.2%
10 1
 
3.2%
64 1
 
3.2%
9.5 1
 
3.2%
Other values (17) 17
54.8%
2024-04-30T01:47:24.519081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
14.0%
2 9
9.7%
4 8
8.6%
8 8
8.6%
5 8
8.6%
6 7
7.5%
0 7
7.5%
9 6
 
6.5%
3 5
 
5.4%
. 5
 
5.4%
Other values (12) 17
18.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
79.6%
Other Letter 10
 
10.8%
Other Punctuation 5
 
5.4%
Lowercase Letter 2
 
2.2%
Space Separator 1
 
1.1%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
17.6%
2 9
12.2%
4 8
10.8%
8 8
10.8%
5 8
10.8%
6 7
9.5%
0 7
9.5%
9 6
8.1%
3 5
 
6.8%
7 3
 
4.1%
Other Letter
ValueCountFrequency (%)
각 2
20.0%
종 2
20.0%
청 1
10.0%
하 1
10.0%
시 1
10.0%
묘 1
10.0%
동 1
10.0%
선 1
10.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 81
87.1%
Hangul 10
 
10.8%
Latin 2
 
2.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
16.0%
2 9
11.1%
4 8
9.9%
8 8
9.9%
5 8
9.9%
6 7
8.6%
0 7
8.6%
9 6
7.4%
3 5
 
6.2%
. 5
 
6.2%
Other values (3) 5
 
6.2%
Hangul
ValueCountFrequency (%)
각 2
20.0%
종 2
20.0%
청 1
10.0%
하 1
10.0%
시 1
10.0%
묘 1
10.0%
동 1
10.0%
선 1
10.0%
Latin
ValueCountFrequency (%)
k 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
89.2%
Hangul 10
 
10.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
15.7%
2 9
10.8%
4 8
9.6%
8 8
9.6%
5 8
9.6%
6 7
8.4%
0 7
8.4%
9 6
7.2%
3 5
 
6.0%
. 5
 
6.0%
Other values (4) 7
8.4%
Hangul
ValueCountFrequency (%)
각 2
20.0%
종 2
20.0%
청 1
10.0%
하 1
10.0%
시 1
10.0%
묘 1
10.0%
동 1
10.0%
선 1
10.0%

2호선 순환선
Text

MISSING 

Distinct30
Distinct (%)96.8%
Missing1
Missing (%)3.1%
Memory size388.0 B
2024-04-30T01:47:24.672654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.6129032
Min length1

Characters and Unicode

Total characters112
Distinct characters30
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

Unique29 ?
Unique (%)93.5%

Sample

1st row101.8
2nd row97.9
3rd row3.9
4th row97908
5th row43050
ValueCountFrequency (%)
97.9 2
 
6.2%
5563 1
 
3.1%
5600 1
 
3.1%
29 1
 
3.1%
35 1
 
3.1%
206 1
 
3.1%
39.2 1
 
3.1%
신촌 1
 
3.1%
홍대 1
 
3.1%
방배 1
 
3.1%
Other values (21) 21
65.6%
2024-04-30T01:47:24.931541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 12
10.7%
9 11
9.8%
0 11
9.8%
3 9
 
8.0%
2 9
 
8.0%
5 9
 
8.0%
1 8
 
7.1%
4 6
 
5.4%
7 6
 
5.4%
8 5
 
4.5%
Other values (20) 26
23.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 86
76.8%
Other Letter 18
 
16.1%
Other Punctuation 5
 
4.5%
Lowercase Letter 2
 
1.8%
Space Separator 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 2
 
11.1%
배 1
 
5.6%
홍 1
 
5.6%
양 1
 
5.6%
신 1
 
5.6%
방 1
 
5.6%
초 1
 
5.6%
서 1
 
5.6%
지 1
 
5.6%
한 1
 
5.6%
Other values (7) 7
38.9%
Decimal Number
ValueCountFrequency (%)
6 12
14.0%
9 11
12.8%
0 11
12.8%
3 9
10.5%
2 9
10.5%
5 9
10.5%
1 8
9.3%
4 6
7.0%
7 6
7.0%
8 5
5.8%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 92
82.1%
Hangul 18
 
16.1%
Latin 2
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 2
 
11.1%
배 1
 
5.6%
홍 1
 
5.6%
양 1
 
5.6%
신 1
 
5.6%
방 1
 
5.6%
초 1
 
5.6%
서 1
 
5.6%
지 1
 
5.6%
한 1
 
5.6%
Other values (7) 7
38.9%
Common
ValueCountFrequency (%)
6 12
13.0%
9 11
12.0%
0 11
12.0%
3 9
9.8%
2 9
9.8%
5 9
9.8%
1 8
8.7%
4 6
6.5%
7 6
6.5%
8 5
5.4%
Other values (2) 6
6.5%
Latin
ValueCountFrequency (%)
k 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 94
83.9%
Hangul 18
 
16.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 12
12.8%
9 11
11.7%
0 11
11.7%
3 9
9.6%
2 9
9.6%
5 9
9.6%
1 8
8.5%
4 6
6.4%
7 6
6.4%
8 5
5.3%
Other values (3) 8
8.5%
Hangul
ValueCountFrequency (%)
대 2
 
11.1%
배 1
 
5.6%
홍 1
 
5.6%
양 1
 
5.6%
신 1
 
5.6%
방 1
 
5.6%
초 1
 
5.6%
서 1
 
5.6%
지 1
 
5.6%
한 1
 
5.6%
Other values (7) 7
38.9%

2호선 성수지선
Text

MISSING 

Distinct27
Distinct (%)93.1%
Missing3
Missing (%)9.4%
Memory size388.0 B
2024-04-30T01:47:25.106166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.3448276
Min length1

Characters and Unicode

Total characters97
Distinct characters22
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)86.2%

Sample

1st row37.4
2nd row13.2
3rd row24.2
4th row13277
5th row10431
ValueCountFrequency (%)
13.2 2
 
6.7%
신설동 2
 
6.7%
37.4 1
 
3.3%
선 1
 
3.3%
내 1
 
3.3%
8 1
 
3.3%
9 1
 
3.3%
30 1
 
3.3%
4.9 1
 
3.3%
동묘 1
 
3.3%
Other values (18) 18
60.0%
2024-04-30T01:47:25.401372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
11.3%
3 11
11.3%
2 11
11.3%
0 10
10.3%
4 9
9.3%
7 7
 
7.2%
9 6
 
6.2%
8 6
 
6.2%
. 5
 
5.2%
동 3
 
3.1%
Other values (12) 18
18.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
77.3%
Other Letter 13
 
13.4%
Other Punctuation 5
 
5.2%
Lowercase Letter 2
 
2.1%
Dash Punctuation 1
 
1.0%
Space Separator 1
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
14.7%
3 11
14.7%
2 11
14.7%
0 10
13.3%
4 9
12.0%
7 7
9.3%
9 6
8.0%
8 6
8.0%
5 3
 
4.0%
6 1
 
1.3%
Other Letter
ValueCountFrequency (%)
동 3
23.1%
설 2
15.4%
신 2
15.4%
선 2
15.4%
입 1
 
7.7%
고 1
 
7.7%
묘 1
 
7.7%
내 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 82
84.5%
Hangul 13
 
13.4%
Latin 2
 
2.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
13.4%
3 11
13.4%
2 11
13.4%
0 10
12.2%
4 9
11.0%
7 7
8.5%
9 6
7.3%
8 6
7.3%
. 5
6.1%
5 3
 
3.7%
Other values (3) 3
 
3.7%
Hangul
ValueCountFrequency (%)
동 3
23.1%
설 2
15.4%
신 2
15.4%
선 2
15.4%
입 1
 
7.7%
고 1
 
7.7%
묘 1
 
7.7%
내 1
 
7.7%
Latin
ValueCountFrequency (%)
k 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
86.6%
Hangul 13
 
13.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
13.1%
3 11
13.1%
2 11
13.1%
0 10
11.9%
4 9
10.7%
7 7
8.3%
9 6
7.1%
8 6
7.1%
. 5
6.0%
5 3
 
3.6%
Other values (4) 5
6.0%
Hangul
ValueCountFrequency (%)
동 3
23.1%
설 2
15.4%
신 2
15.4%
선 2
15.4%
입 1
 
7.7%
고 1
 
7.7%
묘 1
 
7.7%
내 1
 
7.7%

2호선 신정지선
Text

MISSING 

Distinct26
Distinct (%)92.9%
Missing4
Missing (%)12.5%
Memory size388.0 B
2024-04-30T01:47:25.578825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.3214286
Min length1

Characters and Unicode

Total characters93
Distinct characters27
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)85.7%

Sample

1st row35.3
2nd row11.3
3rd row24
4th row11281
5th row8864
ValueCountFrequency (%)
11.3 2
 
6.9%
7 2
 
6.9%
선 1
 
3.4%
1k485 1
 
3.4%
23 1
 
3.4%
5.1 1
 
3.4%
신정네거리 1
 
3.4%
양천구청 1
 
3.4%
246 1
 
3.4%
87 1
 
3.4%
Other values (17) 17
58.6%
2024-04-30T01:47:25.905322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
14.0%
3 8
 
8.6%
4 7
 
7.5%
8 7
 
7.5%
5 7
 
7.5%
2 6
 
6.5%
7 6
 
6.5%
0 6
 
6.5%
6 5
 
5.4%
. 4
 
4.3%
Other values (17) 24
25.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
73.1%
Other Letter 17
 
18.3%
Other Punctuation 4
 
4.3%
Lowercase Letter 2
 
2.2%
Dash Punctuation 1
 
1.1%
Space Separator 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
림 2
11.8%
신 2
11.8%
천 2
11.8%
도 2
11.8%
내 1
 
5.9%
선 1
 
5.9%
양 1
 
5.9%
구 1
 
5.9%
청 1
 
5.9%
정 1
 
5.9%
Other values (3) 3
17.6%
Decimal Number
ValueCountFrequency (%)
1 13
19.1%
3 8
11.8%
4 7
10.3%
8 7
10.3%
5 7
10.3%
2 6
8.8%
7 6
8.8%
0 6
8.8%
6 5
 
7.4%
9 3
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 74
79.6%
Hangul 17
 
18.3%
Latin 2
 
2.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
17.6%
3 8
10.8%
4 7
9.5%
8 7
9.5%
5 7
9.5%
2 6
8.1%
7 6
8.1%
0 6
8.1%
6 5
 
6.8%
. 4
 
5.4%
Other values (3) 5
 
6.8%
Hangul
ValueCountFrequency (%)
림 2
11.8%
신 2
11.8%
천 2
11.8%
도 2
11.8%
내 1
 
5.9%
선 1
 
5.9%
양 1
 
5.9%
구 1
 
5.9%
청 1
 
5.9%
정 1
 
5.9%
Other values (3) 3
17.6%
Latin
ValueCountFrequency (%)
k 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76
81.7%
Hangul 17
 
18.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
17.1%
3 8
10.5%
4 7
9.2%
8 7
9.2%
5 7
9.2%
2 6
7.9%
7 6
7.9%
0 6
7.9%
6 5
 
6.6%
. 4
 
5.3%
Other values (4) 7
9.2%
Hangul
ValueCountFrequency (%)
림 2
11.8%
신 2
11.8%
천 2
11.8%
도 2
11.8%
내 1
 
5.9%
선 1
 
5.9%
양 1
 
5.9%
구 1
 
5.9%
청 1
 
5.9%
정 1
 
5.9%
Other values (3) 3
17.6%

3호선
Text

MISSING 

Distinct28
Distinct (%)96.6%
Missing3
Missing (%)9.4%
Memory size388.0 B
2024-04-30T01:47:26.095093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.8275862
Min length1

Characters and Unicode

Total characters111
Distinct characters25
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)93.1%

Sample

1st row123.3
2nd row77.7
3rd row45.6
4th row77748
5th row42524
ValueCountFrequency (%)
77.7 2
 
6.9%
44k859 1
 
3.4%
123.3 1
 
3.4%
상하선 1
 
3.4%
29 1
 
3.4%
33 1
 
3.4%
185 1
 
3.4%
32.8 1
 
3.4%
종로3가 1
 
3.4%
안국 1
 
3.4%
Other values (18) 18
62.1%
2024-04-30T01:47:26.358234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 13
11.7%
7 11
9.9%
3 11
9.9%
1 10
9.0%
2 10
9.0%
9 9
8.1%
5 8
 
7.2%
6 7
 
6.3%
0 6
 
5.4%
. 5
 
4.5%
Other values (15) 21
18.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90
81.1%
Other Letter 14
 
12.6%
Other Punctuation 5
 
4.5%
Lowercase Letter 2
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 2
14.3%
락 1
 
7.1%
시 1
 
7.1%
장 1
 
7.1%
오 1
 
7.1%
금 1
 
7.1%
안 1
 
7.1%
국 1
 
7.1%
종 1
 
7.1%
로 1
 
7.1%
Other values (3) 3
21.4%
Decimal Number
ValueCountFrequency (%)
4 13
14.4%
7 11
12.2%
3 11
12.2%
1 10
11.1%
2 10
11.1%
9 9
10.0%
5 8
8.9%
6 7
7.8%
0 6
6.7%
8 5
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 95
85.6%
Hangul 14
 
12.6%
Latin 2
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 2
14.3%
락 1
 
7.1%
시 1
 
7.1%
장 1
 
7.1%
오 1
 
7.1%
금 1
 
7.1%
안 1
 
7.1%
국 1
 
7.1%
종 1
 
7.1%
로 1
 
7.1%
Other values (3) 3
21.4%
Common
ValueCountFrequency (%)
4 13
13.7%
7 11
11.6%
3 11
11.6%
1 10
10.5%
2 10
10.5%
9 9
9.5%
5 8
8.4%
6 7
7.4%
0 6
6.3%
. 5
 
5.3%
Latin
ValueCountFrequency (%)
k 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97
87.4%
Hangul 14
 
12.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 13
13.4%
7 11
11.3%
3 11
11.3%
1 10
10.3%
2 10
10.3%
9 9
9.3%
5 8
8.2%
6 7
7.2%
0 6
6.2%
. 5
 
5.2%
Other values (2) 7
7.2%
Hangul
ValueCountFrequency (%)
가 2
14.3%
락 1
 
7.1%
시 1
 
7.1%
장 1
 
7.1%
오 1
 
7.1%
금 1
 
7.1%
안 1
 
7.1%
국 1
 
7.1%
종 1
 
7.1%
로 1
 
7.1%
Other values (3) 3
21.4%

4호선
Text

MISSING 

Distinct29
Distinct (%)96.7%
Missing2
Missing (%)6.2%
Memory size388.0 B
2024-04-30T01:47:26.530291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length3.8333333
Min length1

Characters and Unicode

Total characters115
Distinct characters30
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 (%)93.3%

Sample

1st row87
2nd row64.4
3rd row22.6
4th row64355
5th row35579
ValueCountFrequency (%)
64.4 2
 
6.5%
22.6 1
 
3.2%
87 1
 
3.2%
4 1
 
3.2%
37 1
 
3.2%
49 1
 
3.2%
145 1
 
3.2%
28.8 1
 
3.2%
상계 1
 
3.2%
당고개 1
 
3.2%
Other values (20) 20
64.5%
2024-04-30T01:47:26.827439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 11
9.6%
5 10
 
8.7%
4 10
 
8.7%
0 10
 
8.7%
2 10
 
8.7%
1 9
 
7.8%
9 8
 
7.0%
8 8
 
7.0%
7 7
 
6.1%
3 5
 
4.3%
Other values (20) 27
23.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
76.5%
Other Letter 20
 
17.4%
Other Punctuation 4
 
3.5%
Lowercase Letter 2
 
1.7%
Space Separator 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
문 2
 
10.0%
상 2
 
10.0%
대 2
 
10.0%
고 1
 
5.0%
개 1
 
5.0%
당 1
 
5.0%
선 1
 
5.0%
구 1
 
5.0%
사 1
 
5.0%
입 1
 
5.0%
Other values (7) 7
35.0%
Decimal Number
ValueCountFrequency (%)
6 11
12.5%
5 10
11.4%
4 10
11.4%
0 10
11.4%
2 10
11.4%
1 9
10.2%
9 8
9.1%
8 8
9.1%
7 7
8.0%
3 5
5.7%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 93
80.9%
Hangul 20
 
17.4%
Latin 2
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
문 2
 
10.0%
상 2
 
10.0%
대 2
 
10.0%
고 1
 
5.0%
개 1
 
5.0%
당 1
 
5.0%
선 1
 
5.0%
구 1
 
5.0%
사 1
 
5.0%
입 1
 
5.0%
Other values (7) 7
35.0%
Common
ValueCountFrequency (%)
6 11
11.8%
5 10
10.8%
4 10
10.8%
0 10
10.8%
2 10
10.8%
1 9
9.7%
9 8
8.6%
8 8
8.6%
7 7
7.5%
3 5
5.4%
Other values (2) 5
5.4%
Latin
ValueCountFrequency (%)
k 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 95
82.6%
Hangul 20
 
17.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 11
11.6%
5 10
10.5%
4 10
10.5%
0 10
10.5%
2 10
10.5%
1 9
9.5%
9 8
8.4%
8 8
8.4%
7 7
7.4%
3 5
5.3%
Other values (3) 7
7.4%
Hangul
ValueCountFrequency (%)
문 2
 
10.0%
상 2
 
10.0%
대 2
 
10.0%
고 1
 
5.0%
개 1
 
5.0%
당 1
 
5.0%
선 1
 
5.0%
구 1
 
5.0%
사 1
 
5.0%
입 1
 
5.0%
Other values (7) 7
35.0%

Interactions

2024-04-30T01:47:22.746191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T01:47:26.926962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구 분단 위합계1호선2호선 순환선2호선 성수지선2호선 신정지선3호선4호선
구 분1.0000.8111.0000.7740.8810.9420.0000.9000.909
단 위0.8111.0000.2380.9631.0001.0001.0001.0001.000
합계1.0000.2381.0001.0001.0001.0001.0001.0001.000
1호선0.7740.9631.0001.0001.0001.0000.9891.0001.000
2호선 순환선0.8811.0001.0001.0001.0001.0001.0001.0001.000
2호선 성수지선0.9421.0001.0001.0001.0001.0000.9961.0001.000
2호선 신정지선0.0001.0001.0000.9891.0000.9961.0001.0001.000
3호선0.9001.0001.0001.0001.0001.0001.0001.0001.000
4호선0.9091.0001.0001.0001.0001.0001.0001.0001.000
2024-04-30T01:47:27.037293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
합계단 위
합계1.0000.000
단 위0.0001.000

Missing values

2024-04-30T01:47:22.849221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T01:47:22.977392image/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.
2024-04-30T01:47:23.090235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

구 분단 위합계1호선2호선 순환선2호선 성수지선2호선 신정지선3호선4호선
0궤동연장 계km404.719.9101.837.435.3123.387
1궤동연장 본 선km283.118.697.913.211.377.764.4
2궤동연장 측 선km121.61.33.924.22445.622.6
3도 상(본선) 계m283149.0185809790813277112817774864355
4도 상(본선) 자 갈m145028.04580430501043188644252435579
5도 상(본선) 콘크리트m134865.01400054482284624173426426856
6도 상(본선) 무(교량)m3256.0-376--9601920
7침 목부 설(본선) 계개730311.0546522629163342030045193200156078
8침 목부 설(본선) 콘크리트침목개307630.01388910566117883156658226672266
9침 목부 설(본선) 목침목개32584.0165144183527725062159523
구 분단 위합계1호선2호선 순환선2호선 성수지선2호선 신정지선3호선4호선
22최소곡선반경(R)위치<NA>시청서초동묘양천구청안국당고개
23최소곡선반경(R)위치<NA>종각방배신설동신정네거리종로3가상계
24최소곡선반경(R)위치<NA><NA>홍대<NA><NA><NA><NA>
25최소곡선반경(R)위치<NA><NA>신촌<NA><NA><NA><NA>
26곡 선 연 장km120.39.539.24.95.132.828.8
27곡 선 연 장개소653.0642063023185145
28도유기 계대143.01035973349
29도유기 용출식도유기대112.0229872937
30도유기 레일코팅대8.04<NA><NA><NA><NA>4
31도유기 NR장치대23.0461<NA>48