Overview

Dataset statistics

Number of variables9
Number of observations91
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory76.5 B

Variable types

Numeric2
Categorical2
Text5

Dataset

Description대구교통공사의 호선별 역주소 및 전화번호 등에 대한 데이터로 역명(한글, 영어, 중국어) 및 환승가능 여부, 역 주소, 역 전화번호 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15119035/fileData.do

Alerts

연번 is highly overall correlated with 역번호 and 1 other fieldsHigh correlation
역번호 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
호선 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
환승가능 여부 is highly imbalanced (64.9%)Imbalance
연번 has unique valuesUnique
역 주소(도로명 주소) has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:58:05.487359
Analysis finished2023-12-12 09:58:07.701001
Duration2.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46
Minimum1
Maximum91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-12T18:58:07.824694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.5
Q123.5
median46
Q368.5
95-th percentile86.5
Maximum91
Range90
Interquartile range (IQR)45

Descriptive statistics

Standard deviation26.41338
Coefficient of variation (CV)0.57420392
Kurtosis-1.2
Mean46
Median Absolute Deviation (MAD)23
Skewness0
Sum4186
Variance697.66667
MonotonicityStrictly increasing
2023-12-12T18:58:08.022299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
59 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
61 1
 
1.1%
Other values (81) 81
89.0%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%
82 1
1.1%

호선
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size860.0 B
1
32 
3
30 
2
29 

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 32
35.2%
3 30
33.0%
2 29
31.9%

Length

2023-12-12T18:58:08.205209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:58:08.343676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 32
35.2%
3 30
33.0%
2 29
31.9%

역번호
Real number (ℝ)

HIGH CORRELATION 

Distinct90
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean226.92308
Minimum115
Maximum341
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-12T18:58:08.504912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum115
5-th percentile119.5
Q1138.5
median229
Q3318.5
95-th percentile336.5
Maximum341
Range226
Interquartile range (IQR)180

Descriptive statistics

Standard deviation81.691728
Coefficient of variation (CV)0.35999745
Kurtosis-1.5091747
Mean226.92308
Median Absolute Deviation (MAD)90
Skewness0.022110717
Sum20650
Variance6673.5385
MonotonicityNot monotonic
2023-12-12T18:58:08.708441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
140 2
 
2.2%
115 1
 
1.1%
243 1
 
1.1%
318 1
 
1.1%
317 1
 
1.1%
316 1
 
1.1%
315 1
 
1.1%
314 1
 
1.1%
313 1
 
1.1%
312 1
 
1.1%
Other values (80) 80
87.9%
ValueCountFrequency (%)
115 1
1.1%
116 1
1.1%
117 1
1.1%
118 1
1.1%
119 1
1.1%
120 1
1.1%
121 1
1.1%
122 1
1.1%
123 1
1.1%
124 1
1.1%
ValueCountFrequency (%)
341 1
1.1%
340 1
1.1%
339 1
1.1%
338 1
1.1%
337 1
1.1%
336 1
1.1%
335 1
1.1%
334 1
1.1%
333 1
1.1%
332 1
1.1%

역명(한글)
Text

Distinct88
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size860.0 B
2023-12-12T18:58:09.052284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length4.7472527
Min length2

Characters and Unicode

Total characters432
Distinct characters151
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)93.4%

Sample

1st row설화명곡
2nd row화원
3rd row대곡(정부대구청사)
4th row진천
5th row월배
ValueCountFrequency (%)
청라언덕(신남 2
 
2.2%
반월당 2
 
2.2%
명덕(2·28민주운동기념회관 2
 
2.2%
매천 1
 
1.1%
사월 1
 
1.1%
칠곡운암 1
 
1.1%
동천 1
 
1.1%
팔거(국립농관원·통계청 1
 
1.1%
학정 1
 
1.1%
칠곡경대병원 1
 
1.1%
Other values (78) 78
85.7%
2023-12-12T18:58:09.536288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 24
 
5.6%
( 22
 
5.1%
) 22
 
5.1%
구 16
 
3.7%
원 11
 
2.5%
청 9
 
2.1%
동 9
 
2.1%
성 9
 
2.1%
장 8
 
1.9%
시 7
 
1.6%
Other values (141) 295
68.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 366
84.7%
Open Punctuation 22
 
5.1%
Close Punctuation 22
 
5.1%
Uppercase Letter 9
 
2.1%
Other Punctuation 7
 
1.6%
Decimal Number 6
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 24
 
6.6%
구 16
 
4.4%
원 11
 
3.0%
청 9
 
2.5%
동 9
 
2.5%
성 9
 
2.5%
장 8
 
2.2%
시 7
 
1.9%
산 7
 
1.9%
월 6
 
1.6%
Other values (129) 260
71.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
33.3%
T 1
 
11.1%
G 1
 
11.1%
C 1
 
11.1%
D 1
 
11.1%
S 1
 
11.1%
K 1
 
11.1%
Decimal Number
ValueCountFrequency (%)
2 4
66.7%
8 2
33.3%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Other Punctuation
ValueCountFrequency (%)
· 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 366
84.7%
Common 57
 
13.2%
Latin 9
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 24
 
6.6%
구 16
 
4.4%
원 11
 
3.0%
청 9
 
2.5%
동 9
 
2.5%
성 9
 
2.5%
장 8
 
2.2%
시 7
 
1.9%
산 7
 
1.9%
월 6
 
1.6%
Other values (129) 260
71.0%
Latin
ValueCountFrequency (%)
B 3
33.3%
T 1
 
11.1%
G 1
 
11.1%
C 1
 
11.1%
D 1
 
11.1%
S 1
 
11.1%
K 1
 
11.1%
Common
ValueCountFrequency (%)
( 22
38.6%
) 22
38.6%
· 7
 
12.3%
2 4
 
7.0%
8 2
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 366
84.7%
ASCII 59
 
13.7%
None 7
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 24
 
6.6%
구 16
 
4.4%
원 11
 
3.0%
청 9
 
2.5%
동 9
 
2.5%
성 9
 
2.5%
장 8
 
2.2%
시 7
 
1.9%
산 7
 
1.9%
월 6
 
1.6%
Other values (129) 260
71.0%
ASCII
ValueCountFrequency (%)
( 22
37.3%
) 22
37.3%
2 4
 
6.8%
B 3
 
5.1%
8 2
 
3.4%
T 1
 
1.7%
G 1
 
1.7%
C 1
 
1.7%
D 1
 
1.7%
S 1
 
1.7%
None
ValueCountFrequency (%)
· 7
100.0%

역명(영어)
Text

Distinct90
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size860.0 B
2023-12-12T18:58:09.816628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length36
Mean length16.604396
Min length4

Characters and Unicode

Total characters1511
Distinct characters57
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)97.8%

Sample

1st rowSeolhwa·Myeonggok
2nd rowHwawon
3rd rowDaegok(Central Gov't Office-Daegu)
4th rowJincheon
5th rowWolbae
ValueCountFrequency (%)
station 7
 
4.0%
market 5
 
2.8%
daegu 4
 
2.3%
univ 3
 
1.7%
park 3
 
1.7%
university 3
 
1.7%
paldal 2
 
1.1%
complex 2
 
1.1%
nat'l 2
 
1.1%
kyungpook 2
 
1.1%
Other values (132) 143
81.2%
2023-12-12T18:58:10.196301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 148
 
9.8%
o 126
 
8.3%
a 126
 
8.3%
e 119
 
7.9%
g 86
 
5.7%
86
 
5.7%
i 69
 
4.6%
t 57
 
3.8%
u 52
 
3.4%
l 50
 
3.3%
Other values (47) 592
39.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1135
75.1%
Uppercase Letter 213
 
14.1%
Space Separator 86
 
5.7%
Open Punctuation 22
 
1.5%
Close Punctuation 22
 
1.5%
Other Punctuation 21
 
1.4%
Decimal Number 6
 
0.4%
Dash Punctuation 5
 
0.3%
Initial Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 148
13.0%
o 126
11.1%
a 126
11.1%
e 119
10.5%
g 86
 
7.6%
i 69
 
6.1%
t 57
 
5.0%
u 52
 
4.6%
l 50
 
4.4%
s 36
 
3.2%
Other values (14) 266
23.4%
Uppercase Letter
ValueCountFrequency (%)
S 32
15.0%
D 27
12.7%
M 20
 
9.4%
B 15
 
7.0%
C 14
 
6.6%
H 14
 
6.6%
G 12
 
5.6%
U 9
 
4.2%
P 9
 
4.2%
Y 8
 
3.8%
Other values (12) 53
24.9%
Other Punctuation
ValueCountFrequency (%)
· 8
38.1%
. 7
33.3%
' 5
23.8%
＆ 1
 
4.8%
Decimal Number
ValueCountFrequency (%)
2 4
66.7%
8 2
33.3%
Space Separator
ValueCountFrequency (%)
86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1348
89.2%
Common 163
 
10.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 148
 
11.0%
o 126
 
9.3%
a 126
 
9.3%
e 119
 
8.8%
g 86
 
6.4%
i 69
 
5.1%
t 57
 
4.2%
u 52
 
3.9%
l 50
 
3.7%
s 36
 
2.7%
Other values (36) 479
35.5%
Common
ValueCountFrequency (%)
86
52.8%
( 22
 
13.5%
) 22
 
13.5%
· 8
 
4.9%
. 7
 
4.3%
- 5
 
3.1%
' 5
 
3.1%
2 4
 
2.5%
8 2
 
1.2%
＆ 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1501
99.3%
None 9
 
0.6%
Punctuation 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 148
 
9.9%
o 126
 
8.4%
a 126
 
8.4%
e 119
 
7.9%
g 86
 
5.7%
86
 
5.7%
i 69
 
4.6%
t 57
 
3.8%
u 52
 
3.5%
l 50
 
3.3%
Other values (44) 582
38.8%
None
ValueCountFrequency (%)
· 8
88.9%
＆ 1
 
11.1%
Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

역명(중국어번체)
Text

Distinct85
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size860.0 B
2023-12-12T18:58:10.444569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length2
Mean length4.5604396
Min length2

Characters and Unicode

Total characters415
Distinct characters188
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)90.1%

Sample

1st row舌化椧谷
2nd row花園
3rd row大谷(政府大邱廳舍)
4th row辰泉
5th row月背
ValueCountFrequency (%)
없음 5
 
5.3%
慶大病院 2
 
2.1%
半月堂 2
 
2.1%
靑蘿坡(新南 2
 
2.1%
梅川市場 1
 
1.1%
新梅 1
 
1.1%
東川 1
 
1.1%
八감자거(國立農管院統計廳 1
 
1.1%
鶴亭 1
 
1.1%
漆谷 1
 
1.1%
Other values (78) 78
82.1%
2023-12-12T18:58:10.844084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
大 22
 
5.3%
) 18
 
4.3%
( 18
 
4.3%
驛 8
 
1.9%
場 7
 
1.7%
院 7
 
1.7%
廳 7
 
1.7%
邱 7
 
1.7%
市 7
 
1.7%
· 6
 
1.4%
Other values (178) 308
74.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 354
85.3%
Close Punctuation 18
 
4.3%
Open Punctuation 18
 
4.3%
Other Punctuation 6
 
1.4%
Space Separator 6
 
1.4%
Decimal Number 6
 
1.4%
Uppercase Letter 4
 
1.0%
Lowercase Letter 3
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
大 22
 
6.2%
驛 8
 
2.3%
場 7
 
2.0%
院 7
 
2.0%
廳 7
 
2.0%
邱 7
 
2.0%
市 7
 
2.0%
東 6
 
1.7%
新 6
 
1.7%
山 6
 
1.7%
Other values (165) 271
76.6%
Uppercase Letter
ValueCountFrequency (%)
B 1
25.0%
G 1
25.0%
P 1
25.0%
D 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
33.3%
r 1
33.3%
k 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 4
66.7%
8 2
33.3%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Other Punctuation
ValueCountFrequency (%)
· 6
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 335
80.7%
Common 54
 
13.0%
Hangul 19
 
4.6%
Latin 7
 
1.7%

Most frequent character per script

Han
ValueCountFrequency (%)
大 22
 
6.6%
驛 8
 
2.4%
場 7
 
2.1%
院 7
 
2.1%
廳 7
 
2.1%
邱 7
 
2.1%
市 7
 
2.1%
東 6
 
1.8%
新 6
 
1.8%
山 6
 
1.8%
Other values (154) 252
75.2%
Hangul
ValueCountFrequency (%)
음 5
26.3%
없 5
26.3%
거 1
 
5.3%
자 1
 
5.3%
감 1
 
5.3%
라 1
 
5.3%
파 1
 
5.3%
이 1
 
5.3%
즈 1
 
5.3%
온 1
 
5.3%
Latin
ValueCountFrequency (%)
B 1
14.3%
G 1
14.3%
P 1
14.3%
a 1
14.3%
r 1
14.3%
k 1
14.3%
D 1
14.3%
Common
ValueCountFrequency (%)
) 18
33.3%
( 18
33.3%
· 6
 
11.1%
6
 
11.1%
2 4
 
7.4%
8 2
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
CJK 332
80.0%
ASCII 55
 
13.3%
Hangul 19
 
4.6%
None 6
 
1.4%
CJK Compat Ideographs 3
 
0.7%

Most frequent character per block

CJK
ValueCountFrequency (%)
大 22
 
6.6%
驛 8
 
2.4%
場 7
 
2.1%
院 7
 
2.1%
廳 7
 
2.1%
邱 7
 
2.1%
市 7
 
2.1%
東 6
 
1.8%
新 6
 
1.8%
山 6
 
1.8%
Other values (151) 249
75.0%
ASCII
ValueCountFrequency (%)
) 18
32.7%
( 18
32.7%
6
 
10.9%
2 4
 
7.3%
8 2
 
3.6%
B 1
 
1.8%
G 1
 
1.8%
P 1
 
1.8%
a 1
 
1.8%
r 1
 
1.8%
Other values (2) 2
 
3.6%
None
ValueCountFrequency (%)
· 6
100.0%
Hangul
ValueCountFrequency (%)
음 5
26.3%
없 5
26.3%
거 1
 
5.3%
자 1
 
5.3%
감 1
 
5.3%
라 1
 
5.3%
파 1
 
5.3%
이 1
 
5.3%
즈 1
 
5.3%
온 1
 
5.3%
CJK Compat Ideographs
ValueCountFrequency (%)
蓮 1
33.3%
嶺 1
33.3%
龍 1
33.3%

환승가능 여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
불가능
85 
가능
 
6

Length

Max length3
Median length3
Mean length2.9340659
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
불가능 85
93.4%
가능 6
 
6.6%

Length

2023-12-12T18:58:10.974578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:58:11.074863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불가능 85
93.4%
가능 6
 
6.6%

역 주소(도로명 주소)
Text

UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
2023-12-12T18:58:11.388934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length21.516484
Min length15

Characters and Unicode

Total characters1958
Distinct characters82
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)100.0%

Sample

1st row대구광역시 달성군 비슬로 지하 2476
2nd row대구광역시 달성군 화원읍 비슬로 2600
3rd row대구광역시 달서구 비슬로 지하 2718
4th row대구광역시 달서구 월배로 지하 76
5th row대구광역시 달서구 월배로 지하 143
ValueCountFrequency (%)
대구광역시 88
21.6%
지하 27
 
6.6%
달구벌대로 24
 
5.9%
수성구 18
 
4.4%
달서구 15
 
3.7%
북구 14
 
3.4%
동구 13
 
3.2%
중구 10
 
2.5%
남구 9
 
2.2%
팔거천동로 6
 
1.5%
Other values (134) 184
45.1%
2023-12-12T18:58:11.958237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
318
16.2%
구 203
 
10.4%
대 138
 
7.0%
역 94
 
4.8%
시 91
 
4.6%
로 90
 
4.6%
광 88
 
4.5%
동 69
 
3.5%
지 58
 
3.0%
하 55
 
2.8%
Other values (72) 754
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1277
65.2%
Space Separator 318
 
16.2%
Decimal Number 288
 
14.7%
Open Punctuation 36
 
1.8%
Close Punctuation 36
 
1.8%
Dash Punctuation 2
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 203
15.9%
대 138
10.8%
역 94
 
7.4%
시 91
 
7.1%
로 90
 
7.0%
광 88
 
6.9%
동 69
 
5.4%
지 58
 
4.5%
하 55
 
4.3%
달 51
 
4.0%
Other values (57) 340
26.6%
Decimal Number
ValueCountFrequency (%)
1 51
17.7%
2 50
17.4%
0 45
15.6%
3 26
9.0%
6 25
8.7%
4 22
7.6%
7 20
 
6.9%
8 19
 
6.6%
5 17
 
5.9%
9 13
 
4.5%
Space Separator
ValueCountFrequency (%)
318
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1277
65.2%
Common 681
34.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 203
15.9%
대 138
10.8%
역 94
 
7.4%
시 91
 
7.1%
로 90
 
7.0%
광 88
 
6.9%
동 69
 
5.4%
지 58
 
4.5%
하 55
 
4.3%
달 51
 
4.0%
Other values (57) 340
26.6%
Common
ValueCountFrequency (%)
318
46.7%
1 51
 
7.5%
2 50
 
7.3%
0 45
 
6.6%
( 36
 
5.3%
) 36
 
5.3%
3 26
 
3.8%
6 25
 
3.7%
4 22
 
3.2%
7 20
 
2.9%
Other values (5) 52
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1277
65.2%
ASCII 681
34.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
318
46.7%
1 51
 
7.5%
2 50
 
7.3%
0 45
 
6.6%
( 36
 
5.3%
) 36
 
5.3%
3 26
 
3.8%
6 25
 
3.7%
4 22
 
3.2%
7 20
 
2.9%
Other values (5) 52
 
7.6%
Hangul
ValueCountFrequency (%)
구 203
15.9%
대 138
10.8%
역 94
 
7.4%
시 91
 
7.1%
로 90
 
7.0%
광 88
 
6.9%
동 69
 
5.4%
지 58
 
4.5%
하 55
 
4.3%
달 51
 
4.0%
Other values (57) 340
26.6%

역사 전화번호
Text

Distinct66
Distinct (%)72.5%
Missing0
Missing (%)0.0%
Memory size860.0 B
2023-12-12T18:58:12.282564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1092
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

Unique61 ?
Unique (%)67.0%

Sample

1st row053-634-2674
2nd row053-634-5125
3rd row053-644-7723
4th row053-642-7723
5th row053-642-7732
ValueCountFrequency (%)
053-327-1670 7
 
7.7%
053-327-1667 6
 
6.6%
053-327-1669 6
 
6.6%
053-327-1668 6
 
6.6%
053-327-1671 5
 
5.5%
053-552-2856 1
 
1.1%
053-588-0990 1
 
1.1%
053-582-6215 1
 
1.1%
053-427-0523 1
 
1.1%
053-553-3598 1
 
1.1%
Other values (56) 56
61.5%
2023-12-12T18:58:12.746923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 182
16.7%
3 147
13.5%
5 141
12.9%
7 141
12.9%
0 123
11.3%
6 107
9.8%
2 84
7.7%
1 61
 
5.6%
8 42
 
3.8%
9 39
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 910
83.3%
Dash Punctuation 182
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 147
16.2%
5 141
15.5%
7 141
15.5%
0 123
13.5%
6 107
11.8%
2 84
9.2%
1 61
6.7%
8 42
 
4.6%
9 39
 
4.3%
4 25
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1092
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 182
16.7%
3 147
13.5%
5 141
12.9%
7 141
12.9%
0 123
11.3%
6 107
9.8%
2 84
7.7%
1 61
 
5.6%
8 42
 
3.8%
9 39
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1092
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 182
16.7%
3 147
13.5%
5 141
12.9%
7 141
12.9%
0 123
11.3%
6 107
9.8%
2 84
7.7%
1 61
 
5.6%
8 42
 
3.8%
9 39
 
3.6%

Interactions

2023-12-12T18:58:07.208557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:58:06.995582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:58:07.302685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:58:07.107094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:58:12.898482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선역번호역명(한글)역명(영어)역명(중국어번체)환승가능 여부역 주소(도로명 주소)역사 전화번호
연번1.0000.9340.9060.7890.9450.5680.2331.0000.982
호선0.9341.0001.0000.0000.7600.0000.0001.0001.000
역번호0.9061.0001.0000.8530.9420.8140.0001.0000.998
역명(한글)0.7890.0000.8531.0001.0000.9991.0001.0000.982
역명(영어)0.9450.7600.9421.0001.0001.0001.0001.0000.987
역명(중국어번체)0.5680.0000.8140.9991.0001.0001.0001.0000.957
환승가능 여부0.2330.0000.0001.0001.0001.0001.0001.0000.000
역 주소(도로명 주소)1.0001.0001.0001.0001.0001.0001.0001.0001.000
역사 전화번호0.9821.0000.9980.9820.9870.9570.0001.0001.000
2023-12-12T18:58:13.053893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환승가능 여부호선
환승가능 여부1.0000.000
호선0.0001.000
2023-12-12T18:58:13.168924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번역번호호선환승가능 여부
연번1.0000.9990.8810.167
역번호0.9991.0000.9830.000
호선0.8810.9831.0000.000
환승가능 여부0.1670.0000.0001.000

Missing values

2023-12-12T18:58:07.444883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:58:07.626949image/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

연번호선역번호역명(한글)역명(영어)역명(중국어번체)환승가능 여부역 주소(도로명 주소)역사 전화번호
011115설화명곡Seolhwa·Myeonggok舌化椧谷불가능대구광역시 달성군 비슬로 지하 2476053-634-2674
121116화원Hwawon花園불가능대구광역시 달성군 화원읍 비슬로 2600053-634-5125
231117대곡(정부대구청사)Daegok(Central Gov't Office-Daegu)大谷(政府大邱廳舍)불가능대구광역시 달서구 비슬로 지하 2718053-644-7723
341118진천Jincheon辰泉불가능대구광역시 달서구 월배로 지하 76053-642-7723
451119월배Wolbae月背불가능대구광역시 달서구 월배로 지하 143053-642-7732
561120상인Sangin上仁불가능대구광역시 달서구 월배로 지하 223053-642-7745
671121월촌Wolchon月村불가능대구광역시 달서구 월배로 지하 311053-626-7710
781122송현Songhyeon松峴불가능대구광역시 달서구 월배로 지하 412053-626-7730
891123서부정류장(관문시장)Seobu Bus Terminal(Gwanmun Market)西部客運站(關門市場)불가능대구광역시 남구 월배로 지하501 (대명동)053-651-7736
9101124대명Daemyeong大明불가능대구광역시 남구 대명로 지하71053-627-7746
연번호선역번호역명(한글)역명(영어)역명(중국어번체)환승가능 여부역 주소(도로명 주소)역사 전화번호
81823332건들바위Geondeulbawi없음불가능대구광역시 남구 명덕로 260(이천동)053-327-1670
82833333대봉교Daebonggyo大鳳橋불가능대구광역시 남구 명덕로 330(이천동)053-327-1670
83843334수성시장Suseong Market壽城市場불가능대구광역시 수성구 명덕로 420(수성동2가)053-327-1670
84853335수성구민운동장Suseong District Stadium壽城區民運動場불가능대구광역시 수성구 동대구로 248(범어동)053-327-1670
85863336어린이세상Children's World兒童世界불가능대구광역시 수성구 동대구로 166053-327-1670
86873337황금Hwanggeum黃金불가능대구광역시 수성구 동대구로 100053-327-1671
87883338수성못(TBC)Suseongmot(TBC)없음불가능대구광역시 수성구 동대구로 14(지산동)053-327-1671
88893339지산Jisan池山불가능대구광역시 수성구 지범로 100053-327-1671
89903340범물Beommul凡勿불가능대구광역시 수성구 지범로 194053-327-1671
90913341용지Yongji龍池불가능대구광역시 수성구 범안로 83053-327-1671