Overview

Dataset statistics

Number of variables11
Number of observations3331
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory302.7 KiB
Average record size in memory93.0 B

Variable types

Numeric5
Text4
Categorical2

Dataset

Description대구 시내버스 정류소 경위도 좌표 정보(2022년 7월말 기준) 경위도 좌표체계는 dd.ddddd 형식을 사용하고 있습니다
Author대구광역시
URLhttps://www.data.go.kr/data/15050946/fileData.do

Alerts

시도 has constant value ""Constant
정류소아이디 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 정류소아이디 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 정류소아이디High correlation
구군 is highly overall correlated with 경도High correlation
정류소아이디 is highly skewed (γ1 = -37.621729)Skewed
정류소아이디 has unique valuesUnique
모바일아이디 has unique valuesUnique
정류소명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 22:59:45.803430
Analysis finished2023-12-11 22:59:49.600653
Duration3.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

정류소아이디
Real number (ℝ)

HIGH CORRELATION  SKEWED  UNIQUE 

Distinct3331
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0454101 × 109
Minimum1.5700004 × 109
Maximum7.1810748 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.4 KiB
2023-12-12T07:59:49.663239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5700004 × 109
5-th percentile7.0110046 × 109
Q17.0210128 × 109
median7.0410184 × 109
Q37.0610298 × 109
95-th percentile7.1110686 × 109
Maximum7.1810748 × 109
Range5.6110744 × 109
Interquartile range (IQR)40016900

Descriptive statistics

Standard deviation1.1724026 × 108
Coefficient of variation (CV)0.016640659
Kurtosis1630.0556
Mean7.0454101 × 109
Median Absolute Deviation (MAD)20008400
Skewness-37.621729
Sum2.3468261 × 1013
Variance1.3745279 × 1016
MonotonicityNot monotonic
2023-12-12T07:59:49.787389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7051001500 1
 
< 0.1%
7021057300 1
 
< 0.1%
7021064900 1
 
< 0.1%
7021065000 1
 
< 0.1%
7021065100 1
 
< 0.1%
7021065200 1
 
< 0.1%
7021065300 1
 
< 0.1%
7021008600 1
 
< 0.1%
7021008700 1
 
< 0.1%
7021008800 1
 
< 0.1%
Other values (3321) 3321
99.7%
ValueCountFrequency (%)
1570000400 1
< 0.1%
3690000760 1
< 0.1%
7001000100 1
< 0.1%
7001000200 1
< 0.1%
7001000300 1
< 0.1%
7001000400 1
< 0.1%
7001000500 1
< 0.1%
7001000600 1
< 0.1%
7001000700 1
< 0.1%
7001000800 1
< 0.1%
ValueCountFrequency (%)
7181074801 1
< 0.1%
7181074800 1
< 0.1%
7121000400 1
< 0.1%
7111085300 1
< 0.1%
7111085200 1
< 0.1%
7111085100 1
< 0.1%
7111085000 1
< 0.1%
7111084901 1
< 0.1%
7111084900 1
< 0.1%
7111084700 1
< 0.1%

모바일아이디
Real number (ℝ)

UNIQUE 

Distinct3331
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10484.935
Minimum2
Maximum22027
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.4 KiB
2023-12-12T07:59:49.915672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile427
Q11826.5
median5059
Q320646.5
95-th percentile21744.5
Maximum22027
Range22025
Interquartile range (IQR)18820

Descriptive statistics

Standard deviation9132.5626
Coefficient of variation (CV)0.87101761
Kurtosis-1.8586362
Mean10484.935
Median Absolute Deviation (MAD)4455
Skewness0.20345637
Sum34925317
Variance83403700
MonotonicityNot monotonic
2023-12-12T07:59:50.031759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2354 1
 
< 0.1%
20904 1
 
< 0.1%
22015 1
 
< 0.1%
22017 1
 
< 0.1%
22018 1
 
< 0.1%
22019 1
 
< 0.1%
22020 1
 
< 0.1%
21839 1
 
< 0.1%
21840 1
 
< 0.1%
2136 1
 
< 0.1%
Other values (3321) 3321
99.7%
ValueCountFrequency (%)
2 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
15 1
< 0.1%
22 1
< 0.1%
25 1
< 0.1%
28 1
< 0.1%
29 1
< 0.1%
34 1
< 0.1%
ValueCountFrequency (%)
22027 1
< 0.1%
22026 1
< 0.1%
22025 1
< 0.1%
22024 1
< 0.1%
22023 1
< 0.1%
22022 1
< 0.1%
22021 1
< 0.1%
22020 1
< 0.1%
22019 1
< 0.1%
22018 1
< 0.1%

정류소명
Text

UNIQUE 

Distinct3331
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
2023-12-12T07:59:50.276813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length18
Mean length7.5944161
Min length2

Characters and Unicode

Total characters25297
Distinct characters490
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

Unique3331 ?
Unique (%)100.0%

Sample

1st row대구공공시설관리공단앞
2nd row대명역(1번출구)
3rd row대명초등학교건너
4th rowKT남대구지사건너1
5th row안지랑네거리2
ValueCountFrequency (%)
건너 3
 
0.1%
계명대학교 2
 
0.1%
흥사단 2
 
0.1%
묘1리 2
 
0.1%
칠곡ic 2
 
0.1%
죽전동 2
 
0.1%
국민건강보험공단 2
 
0.1%
북구 2
 
0.1%
경북대학교 2
 
0.1%
팔달시장앞 1
 
< 0.1%
Other values (3333) 3333
99.4%
2023-12-12T07:59:50.714583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
앞 1129
 
4.5%
건 1101
 
4.4%
너 1071
 
4.2%
구 645
 
2.5%
교 603
 
2.4%
대 599
 
2.4%
리 532
 
2.1%
동 495
 
2.0%
1 493
 
1.9%
2 464
 
1.8%
Other values (480) 18165
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23213
91.8%
Decimal Number 1219
 
4.8%
Close Punctuation 318
 
1.3%
Open Punctuation 316
 
1.2%
Uppercase Letter 168
 
0.7%
Space Separator 22
 
0.1%
Other Punctuation 20
 
0.1%
Dash Punctuation 11
 
< 0.1%
Lowercase Letter 8
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 1129
 
4.9%
건 1101
 
4.7%
너 1071
 
4.6%
구 645
 
2.8%
교 603
 
2.6%
대 599
 
2.6%
리 532
 
2.3%
동 495
 
2.1%
학 448
 
1.9%
성 415
 
1.8%
Other values (445) 16175
69.7%
Uppercase Letter
ValueCountFrequency (%)
T 26
15.5%
L 19
11.3%
K 19
11.3%
H 17
10.1%
G 12
7.1%
C 12
7.1%
P 10
 
6.0%
B 9
 
5.4%
I 9
 
5.4%
S 9
 
5.4%
Other values (6) 26
15.5%
Decimal Number
ValueCountFrequency (%)
1 493
40.4%
2 464
38.1%
3 106
 
8.7%
4 60
 
4.9%
5 30
 
2.5%
9 19
 
1.6%
6 17
 
1.4%
8 12
 
1.0%
7 10
 
0.8%
0 8
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 14
70.0%
· 4
 
20.0%
/ 2
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 318
100.0%
Open Punctuation
ValueCountFrequency (%)
( 316
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 8
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23215
91.8%
Common 1906
 
7.5%
Latin 176
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 1129
 
4.9%
건 1101
 
4.7%
너 1071
 
4.6%
구 645
 
2.8%
교 603
 
2.6%
대 599
 
2.6%
리 532
 
2.3%
동 495
 
2.1%
학 448
 
1.9%
성 415
 
1.8%
Other values (446) 16177
69.7%
Common
ValueCountFrequency (%)
1 493
25.9%
2 464
24.3%
) 318
16.7%
( 316
16.6%
3 106
 
5.6%
4 60
 
3.1%
5 30
 
1.6%
22
 
1.2%
9 19
 
1.0%
6 17
 
0.9%
Other values (7) 61
 
3.2%
Latin
ValueCountFrequency (%)
T 26
14.8%
L 19
10.8%
K 19
10.8%
H 17
9.7%
G 12
 
6.8%
C 12
 
6.8%
P 10
 
5.7%
B 9
 
5.1%
I 9
 
5.1%
S 9
 
5.1%
Other values (7) 34
19.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23213
91.8%
ASCII 2078
 
8.2%
None 6
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
앞 1129
 
4.9%
건 1101
 
4.7%
너 1071
 
4.6%
구 645
 
2.8%
교 603
 
2.6%
대 599
 
2.6%
리 532
 
2.3%
동 495
 
2.1%
학 448
 
1.9%
성 415
 
1.8%
Other values (445) 16175
69.7%
ASCII
ValueCountFrequency (%)
1 493
23.7%
2 464
22.3%
) 318
15.3%
( 316
15.2%
3 106
 
5.1%
4 60
 
2.9%
5 30
 
1.4%
T 26
 
1.3%
22
 
1.1%
L 19
 
0.9%
Other values (23) 224
10.8%
None
ValueCountFrequency (%)
· 4
66.7%
㈜ 2
33.3%

영문명
Text

Distinct1881
Distinct (%)56.5%
Missing1
Missing (%)< 0.1%
Memory size26.2 KiB
2023-12-12T07:59:51.067946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length38
Mean length20.722222
Min length3

Characters and Unicode

Total characters69005
Distinct characters70
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique663 ?
Unique (%)19.9%

Sample

1st rowDaegu Public Facilities Corporation
2nd rowDaemyeong Station
3rd rowDaemyeong Elementary School
4th rowKT Namdaegu District Office
5th rowAnjirang (4) Junction
ValueCountFrequency (%)
school 376
 
4.0%
apts 279
 
3.0%
center 241
 
2.6%
station 223
 
2.4%
elementary 187
 
2.0%
daegu 186
 
2.0%
junction 159
 
1.7%
town 156
 
1.7%
market 125
 
1.3%
high 115
 
1.2%
Other values (1579) 7351
78.2%
2023-12-12T07:59:51.589965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6102
 
8.8%
n 6030
 
8.7%
o 5824
 
8.4%
e 5711
 
8.3%
a 4804
 
7.0%
g 3432
 
5.0%
i 3326
 
4.8%
t 2888
 
4.2%
r 2466
 
3.6%
l 2395
 
3.5%
Other values (60) 26027
37.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 51772
75.0%
Uppercase Letter 9217
 
13.4%
Space Separator 6102
 
8.8%
Dash Punctuation 692
 
1.0%
Decimal Number 625
 
0.9%
Close Punctuation 255
 
0.4%
Open Punctuation 255
 
0.4%
Other Punctuation 87
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 6030
11.6%
o 5824
11.2%
e 5711
11.0%
a 4804
 
9.3%
g 3432
 
6.6%
i 3326
 
6.4%
t 2888
 
5.6%
r 2466
 
4.8%
l 2395
 
4.6%
u 2322
 
4.5%
Other values (16) 12574
24.3%
Uppercase Letter
ValueCountFrequency (%)
S 1516
16.4%
C 926
 
10.0%
D 853
 
9.3%
M 651
 
7.1%
H 587
 
6.4%
A 512
 
5.6%
B 492
 
5.3%
G 443
 
4.8%
P 402
 
4.4%
J 388
 
4.2%
Other values (15) 2447
26.5%
Decimal Number
ValueCountFrequency (%)
1 182
29.1%
2 142
22.7%
4 129
20.6%
3 88
14.1%
5 30
 
4.8%
9 19
 
3.0%
6 14
 
2.2%
8 8
 
1.3%
7 7
 
1.1%
0 6
 
1.0%
Other Punctuation
ValueCountFrequency (%)
' 50
57.5%
. 27
31.0%
& 5
 
5.7%
· 4
 
4.6%
/ 1
 
1.1%
Space Separator
ValueCountFrequency (%)
6102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 692
100.0%
Close Punctuation
ValueCountFrequency (%)
) 255
100.0%
Open Punctuation
ValueCountFrequency (%)
( 255
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60989
88.4%
Common 8016
 
11.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 6030
 
9.9%
o 5824
 
9.5%
e 5711
 
9.4%
a 4804
 
7.9%
g 3432
 
5.6%
i 3326
 
5.5%
t 2888
 
4.7%
r 2466
 
4.0%
l 2395
 
3.9%
u 2322
 
3.8%
Other values (41) 21791
35.7%
Common
ValueCountFrequency (%)
6102
76.1%
- 692
 
8.6%
) 255
 
3.2%
( 255
 
3.2%
1 182
 
2.3%
2 142
 
1.8%
4 129
 
1.6%
3 88
 
1.1%
' 50
 
0.6%
5 30
 
0.4%
Other values (9) 91
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69001
> 99.9%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6102
 
8.8%
n 6030
 
8.7%
o 5824
 
8.4%
e 5711
 
8.3%
a 4804
 
7.0%
g 3432
 
5.0%
i 3326
 
4.8%
t 2888
 
4.2%
r 2466
 
3.6%
l 2395
 
3.5%
Other values (59) 26023
37.7%
None
ValueCountFrequency (%)
· 4
100.0%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
대구광역시
3331 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 3331
100.0%

Length

2023-12-12T07:59:51.730474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:59:51.846686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 3331
100.0%

구군
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
달성군
706 
북구
592 
동구
583 
달서구
564 
수성구
415 
Other values (3)
471 

Length

Max length3
Median length3
Mean length2.5058541
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
달성군 706
21.2%
북구 592
17.8%
동구 583
17.5%
달서구 564
16.9%
수성구 415
12.5%
서구 189
 
5.7%
남구 164
 
4.9%
중구 118
 
3.5%

Length

2023-12-12T07:59:51.941938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:59:52.054666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
달성군 706
21.2%
북구 592
17.8%
동구 583
17.5%
달서구 564
16.9%
수성구 415
12.5%
서구 189
 
5.7%
남구 164
 
4.9%
중구 118
 
3.5%

동
Text

Distinct141
Distinct (%)4.2%
Missing2
Missing (%)0.1%
Memory size26.2 KiB
2023-12-12T07:59:52.346743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.525383
Min length2

Characters and Unicode

Total characters11736
Distinct characters100
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대명10동
2nd row대명10동
3rd row대명10동
4th row대명10동
5th row대명10동
ValueCountFrequency (%)
공산동 162
 
4.9%
다사읍 108
 
3.2%
가창면 104
 
3.1%
논공읍 85
 
2.6%
하빈면 80
 
2.4%
화원읍 74
 
2.2%
구지면 66
 
2.0%
유가읍 65
 
2.0%
옥포읍 63
 
1.9%
국우동 63
 
1.9%
Other values (131) 2459
73.9%
2023-12-12T07:59:52.772862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 2689
22.9%
산 544
 
4.6%
2 541
 
4.6%
읍 489
 
4.2%
1 473
 
4.0%
면 250
 
2.1%
3 248
 
2.1%
공 247
 
2.1%
성 244
 
2.1%
신 213
 
1.8%
Other values (90) 5798
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10166
86.6%
Decimal Number 1490
 
12.7%
Other Punctuation 80
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2689
26.5%
산 544
 
5.4%
읍 489
 
4.8%
면 250
 
2.5%
공 247
 
2.4%
성 244
 
2.4%
신 213
 
2.1%
가 205
 
2.0%
안 159
 
1.6%
천 145
 
1.4%
Other values (80) 4981
49.0%
Decimal Number
ValueCountFrequency (%)
2 541
36.3%
1 473
31.7%
3 248
16.6%
4 128
 
8.6%
9 26
 
1.7%
6 26
 
1.7%
5 24
 
1.6%
7 15
 
1.0%
0 9
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10166
86.6%
Common 1570
 
13.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2689
26.5%
산 544
 
5.4%
읍 489
 
4.8%
면 250
 
2.5%
공 247
 
2.4%
성 244
 
2.4%
신 213
 
2.1%
가 205
 
2.0%
안 159
 
1.6%
천 145
 
1.4%
Other values (80) 4981
49.0%
Common
ValueCountFrequency (%)
2 541
34.5%
1 473
30.1%
3 248
15.8%
4 128
 
8.2%
. 80
 
5.1%
9 26
 
1.7%
6 26
 
1.7%
5 24
 
1.5%
7 15
 
1.0%
0 9
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10166
86.6%
ASCII 1570
 
13.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 2689
26.5%
산 544
 
5.4%
읍 489
 
4.8%
면 250
 
2.5%
공 247
 
2.4%
성 244
 
2.4%
신 213
 
2.1%
가 205
 
2.0%
안 159
 
1.6%
천 145
 
1.4%
Other values (80) 4981
49.0%
ASCII
ValueCountFrequency (%)
2 541
34.5%
1 473
30.1%
3 248
15.8%
4 128
 
8.2%
. 80
 
5.1%
9 26
 
1.7%
6 26
 
1.7%
5 24
 
1.5%
7 15
 
1.0%
0 9
 
0.6%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct3328
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.57329
Minimum128.35817
Maximum128.75908
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.4 KiB
2023-12-12T07:59:52.905270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.35817
5-th percentile128.43662
Q1128.52112
median128.57342
Q3128.62705
95-th percentile128.70828
Maximum128.75908
Range0.4009149
Interquartile range (IQR)0.10592925

Descriptive statistics

Standard deviation0.079441242
Coefficient of variation (CV)0.00061786737
Kurtosis-0.52587602
Mean128.57329
Median Absolute Deviation (MAD)0.0531632
Skewness-0.073748162
Sum428277.64
Variance0.0063109109
MonotonicityNot monotonic
2023-12-12T07:59:53.306299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.5161767 2
 
0.1%
128.5569617 2
 
0.1%
128.64795 2
 
0.1%
128.5603346 1
 
< 0.1%
128.5745048 1
 
< 0.1%
128.5856483 1
 
< 0.1%
128.5859217 1
 
< 0.1%
128.5874633 1
 
< 0.1%
128.5877733 1
 
< 0.1%
128.5650823 1
 
< 0.1%
Other values (3318) 3318
99.6%
ValueCountFrequency (%)
128.3581652 1
< 0.1%
128.364737 1
< 0.1%
128.3721701 1
< 0.1%
128.3821042 1
< 0.1%
128.3920289 1
< 0.1%
128.3925317 1
< 0.1%
128.3926933 1
< 0.1%
128.3938983 1
< 0.1%
128.393925 1
< 0.1%
128.3950433 1
< 0.1%
ValueCountFrequency (%)
128.7590801 1
< 0.1%
128.75718 1
< 0.1%
128.7536401 1
< 0.1%
128.7535856 1
< 0.1%
128.7525233 1
< 0.1%
128.7524879 1
< 0.1%
128.7524566 1
< 0.1%
128.7523802 1
< 0.1%
128.752316 1
< 0.1%
128.7522839 1
< 0.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct3329
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.853539
Minimum35.61726
Maximum35.995313
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.4 KiB
2023-12-12T07:59:53.476429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.61726
5-th percentile35.697004
Q135.830393
median35.861257
Q335.888157
95-th percentile35.953206
Maximum35.995313
Range0.37805325
Interquartile range (IQR)0.05776481

Descriptive statistics

Standard deviation0.06737979
Coefficient of variation (CV)0.0018793065
Kurtosis1.6017009
Mean35.853539
Median Absolute Deviation (MAD)0.0288588
Skewness-0.97599585
Sum119428.14
Variance0.0045400361
MonotonicityNot monotonic
2023-12-12T07:59:53.613148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.880625 2
 
0.1%
35.74676 2
 
0.1%
35.83840532 1
 
< 0.1%
35.96289667 1
 
< 0.1%
35.95799333 1
 
< 0.1%
35.95786833 1
 
< 0.1%
35.960545 1
 
< 0.1%
35.960405 1
 
< 0.1%
35.89112503 1
 
< 0.1%
35.89221487 1
 
< 0.1%
Other values (3319) 3319
99.6%
ValueCountFrequency (%)
35.61726 1
< 0.1%
35.61731167 1
< 0.1%
35.61764 1
< 0.1%
35.61774833 1
< 0.1%
35.618055 1
< 0.1%
35.61812 1
< 0.1%
35.62303667 1
< 0.1%
35.62312 1
< 0.1%
35.62363517 1
< 0.1%
35.624565 1
< 0.1%
ValueCountFrequency (%)
35.99531325 1
< 0.1%
35.99519058 1
< 0.1%
35.99274333 1
< 0.1%
35.99271167 1
< 0.1%
35.99265667 1
< 0.1%
35.99255792 1
< 0.1%
35.99252983 1
< 0.1%
35.99241 1
< 0.1%
35.9912465 1
< 0.1%
35.99035823 1
< 0.1%

경유노선수
Real number (ℝ)

Distinct16
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.44281
Minimum1
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.4 KiB
2023-12-12T07:59:53.738065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q35
95-th percentile9
Maximum17
Range16
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.7114403
Coefficient of variation (CV)0.78756607
Kurtosis1.8372824
Mean3.44281
Median Absolute Deviation (MAD)2
Skewness1.4058429
Sum11468
Variance7.3519085
MonotonicityNot monotonic
2023-12-12T07:59:53.876218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 1010
30.3%
2 582
17.5%
3 522
15.7%
4 316
 
9.5%
5 233
 
7.0%
6 217
 
6.5%
7 155
 
4.7%
8 86
 
2.6%
9 76
 
2.3%
10 44
 
1.3%
Other values (6) 90
 
2.7%
ValueCountFrequency (%)
1 1010
30.3%
2 582
17.5%
3 522
15.7%
4 316
 
9.5%
5 233
 
7.0%
6 217
 
6.5%
7 155
 
4.7%
8 86
 
2.6%
9 76
 
2.3%
10 44
 
1.3%
ValueCountFrequency (%)
17 1
 
< 0.1%
15 5
 
0.2%
14 2
 
0.1%
13 29
 
0.9%
12 20
 
0.6%
11 33
 
1.0%
10 44
 
1.3%
9 76
2.3%
8 86
2.6%
7 155
4.7%

경유노선
Text

Distinct1201
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
2023-12-12T07:59:54.103194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length57
Mean length13.423597
Min length3

Characters and Unicode

Total characters44714
Distinct characters30
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

Unique600 ?
Unique (%)18.0%

Sample

1st row306+518+564+600+623+649+651+서구1
2nd row306+518+564+600+623+649+651+서구1
3rd row306+518+564+600+623+649+651+서구1
4th row306+518+564+623+649+651+서구1
5th row306+410-1+518+564+623+649+651+달서4+서구1
ValueCountFrequency (%)
성서2 97
 
2.9%
가창2 72
 
2.2%
팔공1 50
 
1.5%
성서3 46
 
1.4%
달성2 35
 
1.1%
101+101-1 29
 
0.9%
600+655 26
 
0.8%
524 26
 
0.8%
성서1-1 25
 
0.8%
달성7 24
 
0.7%
Other values (1191) 2901
87.1%
2023-12-12T07:59:54.491164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 8137
18.2%
1 3920
 
8.8%
0 3581
 
8.0%
3 3391
 
7.6%
4 2933
 
6.6%
5 2862
 
6.4%
2 2708
 
6.1%
6 2475
 
5.5%
9 1670
 
3.7%
8 1489
 
3.3%
Other values (20) 11548
25.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26433
59.1%
Other Letter 9098
 
20.3%
Math Symbol 8137
 
18.2%
Dash Punctuation 1046
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 1164
12.8%
서 1151
12.7%
구 1129
12.4%
달 911
10.0%
행 571
 
6.3%
급 571
 
6.3%
동 509
 
5.6%
칠 451
 
5.0%
곡 451
 
5.0%
북 379
 
4.2%
Other values (8) 1811
19.9%
Decimal Number
ValueCountFrequency (%)
1 3920
14.8%
0 3581
13.5%
3 3391
12.8%
4 2933
11.1%
5 2862
10.8%
2 2708
10.2%
6 2475
9.4%
9 1670
6.3%
8 1489
 
5.6%
7 1404
 
5.3%
Math Symbol
ValueCountFrequency (%)
+ 8137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1046
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35616
79.7%
Hangul 9098
 
20.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 1164
12.8%
서 1151
12.7%
구 1129
12.4%
달 911
10.0%
행 571
 
6.3%
급 571
 
6.3%
동 509
 
5.6%
칠 451
 
5.0%
곡 451
 
5.0%
북 379
 
4.2%
Other values (8) 1811
19.9%
Common
ValueCountFrequency (%)
+ 8137
22.8%
1 3920
11.0%
0 3581
10.1%
3 3391
9.5%
4 2933
 
8.2%
5 2862
 
8.0%
2 2708
 
7.6%
6 2475
 
6.9%
9 1670
 
4.7%
8 1489
 
4.2%
Other values (2) 2450
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35616
79.7%
Hangul 9098
 
20.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 8137
22.8%
1 3920
11.0%
0 3581
10.1%
3 3391
9.5%
4 2933
 
8.2%
5 2862
 
8.0%
2 2708
 
7.6%
6 2475
 
6.9%
9 1670
 
4.7%
8 1489
 
4.2%
Other values (2) 2450
 
6.9%
Hangul
ValueCountFrequency (%)
성 1164
12.8%
서 1151
12.7%
구 1129
12.4%
달 911
10.0%
행 571
 
6.3%
급 571
 
6.3%
동 509
 
5.6%
칠 451
 
5.0%
곡 451
 
5.0%
북 379
 
4.2%
Other values (8) 1811
19.9%

Interactions

2023-12-12T07:59:48.743053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:46.866221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:47.320498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:47.773245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:48.273763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:48.829180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:46.950130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:47.407332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:47.860644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:48.358052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:48.929494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:47.032577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:47.483259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:47.951934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:48.436449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:49.054567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:47.128737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:47.580372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:48.074340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:48.530514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:49.177860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:47.227090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:47.680562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:48.181767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:59:48.641042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:59:54.598262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정류소아이디모바일아이디구군경도위도경유노선수
정류소아이디1.0000.0000.0000.0000.0000.000
모바일아이디0.0001.0000.3200.2870.2470.246
구군0.0000.3201.0000.7770.7370.264
경도0.0000.2870.7771.0000.7070.361
위도0.0000.2470.7370.7071.0000.280
경유노선수0.0000.2460.2640.3610.2801.000
2023-12-12T07:59:54.743512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정류소아이디모바일아이디경도위도경유노선수구군
정류소아이디1.000-0.011-0.518-0.705-0.2430.000
모바일아이디-0.0111.0000.0050.0290.1570.184
경도-0.5180.0051.0000.3930.1410.518
위도-0.7050.0290.3931.0000.0800.470
경유노선수-0.2430.1570.1410.0801.0000.125
구군0.0000.1840.5180.4700.1251.000

Missing values

2023-12-12T07:59:49.307396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:59:49.450648image/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.
2023-12-12T07:59:49.555883image/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

정류소아이디모바일아이디정류소명영문명시도구군동경도위도경유노선수경유노선
070510015002354대구공공시설관리공단앞Daegu Public Facilities Corporation대구광역시남구대명10동128.56033535.8384058306+518+564+600+623+649+651+서구1
170510031002178대명역(1번출구)Daemyeong Station대구광역시남구대명10동128.56515335.8394058306+518+564+600+623+649+651+서구1
2705100330020031대명초등학교건너Daemyeong Elementary School대구광역시남구대명10동128.56859935.8395788306+518+564+600+623+649+651+서구1
370510035002175KT남대구지사건너1KT Namdaegu District Office대구광역시남구대명10동128.57261335.8394367306+518+564+623+649+651+서구1
470510037002174안지랑네거리2Anjirang (4) Junction대구광역시남구대명10동128.57522335.8392569306+410-1+518+564+623+649+651+달서4+서구1
57051005500638대구차여성병원건너Daegu CHA Woman's hospital대구광역시남구대명10동128.57410535.8406684503+623+서구1+순환3-1
6705100570021228대명1동행정복지센터건너Daemyeong 1-dong Community Service Center대구광역시남구대명10동128.57173535.8422874503+623+서구1+순환3-1
77051006000742두리봉네거리2Duribong Junction대구광역시남구대명10동128.55885935.8391946609+618+650+706+836+남구1
8705100610021227문화예술회관건너Culture and Arts Center대구광역시남구대명10동128.56075735.8416547609+618+650+706+805+836+남구1
97041030100590앞산궁도장건너Apsan Archery Field대구광역시남구대명11동128.5608635.8282652750+달서4
정류소아이디모바일아이디정류소명영문명시도구군동경도위도경유노선수경유노선
3321700100480020051대구역센트럴자이Daegu Station Central Xi대구광역시중구성내3동128.58772535.8753833234+651+653
3322700100490020065성내3동행정복지센터입구Seongnae 3-dong Community Service Center대구광역시중구성내3동128.58742335.8726193234+651+653
3323700100510021880수창초등학교Suchang Elementary School대구광역시중구성내3동128.5822435.8753457300+523+808+836+939+동구2+북구2
3324700100520020064달성공원앞Dalseong Park대구광역시중구성내3동128.58190735.8750156300+523+808+836+939+동구2
3325700100590021879섬유회관건너1Textile Center대구광역시중구성내3동128.58332935.87072513156+240+309+425+524+623+653+724+939+급행1+급행3+급행5+동구2
3326700100700021881적십자혈액원앞Red Cross Blood Center대구광역시중구성내3동128.57842535.8783282204+618
3327700100710020056적십자혈액원건너Red Cross Blood Center대구광역시중구성내3동128.57883735.8780432204+618
3328700100720020052수창공원앞(중구보건소건너)Suchang Park(Jung Community Health Center)대구광역시중구성내3동128.58489135.8769175101-1+204+618+808+북구2
3329700100730020063중구보건소앞Jung Community Health Center대구광역시중구성내3동128.58495135.8770984101+204+618+808
3330700101160020068달성공원건너Dalseong Park대구광역시중구성내3동128.58223635.8725547300+523+808+836+939+동구2+북구2