Overview

Dataset statistics

Number of variables11
Number of observations3311
Missing cells6
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory300.8 KiB
Average record size in memory93.0 B

Variable types

Numeric5
Text4
Categorical2

Dataset

Description대구광역시_시내버스 정류소 위치정보_20220731
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15050946&dataSetDetailId=150509461c6eaf8bddaef&provdMethod=FILE

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 = -46.75270443)Skewed
정류소아이디 has unique valuesUnique
정류소명 has unique valuesUnique

Reproduction

Analysis started2024-04-17 15:09:29.905163
Analysis finished2024-04-17 15:09:33.119367
Duration3.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

정류소아이디
Real number (ℝ)

HIGH CORRELATION  SKEWED  UNIQUE 

Distinct3311
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.046134 × 109
Minimum1.5700001 × 109
Maximum7.1810748 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.2 KiB
2024-04-18T00:09:33.179355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5700001 × 109
5-th percentile7.0110046 × 109
Q17.0210122 × 109
median7.0410177 × 109
Q37.0610288 × 109
95-th percentile7.1110662 × 109
Maximum7.1810748 × 109
Range5.6110747 × 109
Interquartile range (IQR)40016600

Descriptive statistics

Standard deviation1.019891 × 108
Coefficient of variation (CV)0.014474477
Kurtosis2512.6305
Mean7.046134 × 109
Median Absolute Deviation (MAD)20008300
Skewness-46.752704
Sum2.332975 × 1013
Variance1.0401777 × 1016
MonotonicityStrictly increasing
2024-04-18T00:09:33.283109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1570000140 1
 
< 0.1%
7061001100 1
 
< 0.1%
7061000100 1
 
< 0.1%
7061000200 1
 
< 0.1%
7061000300 1
 
< 0.1%
7061000400 1
 
< 0.1%
7061000500 1
 
< 0.1%
7061000600 1
 
< 0.1%
7061000700 1
 
< 0.1%
7061000800 1
 
< 0.1%
Other values (3301) 3301
99.7%
ValueCountFrequency (%)
1570000140 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%
7001000900 1
< 0.1%
ValueCountFrequency (%)
7181074800 1
< 0.1%
7111082900 1
< 0.1%
7111082800 1
< 0.1%
7111082700 1
< 0.1%
7111082600 1
< 0.1%
7111082500 1
< 0.1%
7111082400 1
< 0.1%
7111082300 1
< 0.1%
7111082200 1
< 0.1%
7111082100 1
< 0.1%

모바일아이디
Real number (ℝ)

Distinct3302
Distinct (%)99.8%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean6656.9196
Minimum2
Maximum22004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.2 KiB
2024-04-18T00:09:33.391732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile328.45
Q11500.5
median2898.5
Q39194.75
95-th percentile20605.55
Maximum22004
Range22002
Interquartile range (IQR)7694.25

Descriptive statistics

Standard deviation7493.699
Coefficient of variation (CV)1.1257007
Kurtosis-0.37505359
Mean6656.9196
Median Absolute Deviation (MAD)1957
Skewness1.1576392
Sum22034404
Variance56155525
MonotonicityNot monotonic
2024-04-18T00:09:33.493653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4232 2
 
0.1%
4233 2
 
0.1%
4225 2
 
0.1%
4226 2
 
0.1%
4223 2
 
0.1%
4228 2
 
0.1%
4224 2
 
0.1%
4227 2
 
0.1%
20129 1
 
< 0.1%
3881 1
 
< 0.1%
Other values (3292) 3292
99.4%
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 (%)
22004 1
< 0.1%
22003 1
< 0.1%
22002 1
< 0.1%
22001 1
< 0.1%
21882 1
< 0.1%
21881 1
< 0.1%
21880 1
< 0.1%
21879 1
< 0.1%
21878 1
< 0.1%
21877 1
< 0.1%

정류소명
Text

UNIQUE 

Distinct3311
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size26.0 KiB
2024-04-18T00:09:33.681174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length18
Mean length7.5665962
Min length2

Characters and Unicode

Total characters25053
Distinct characters491
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

Unique3311 ?
Unique (%)100.0%

Sample

1st row감문리
2nd row대명시장앞
3rd row대명시장건너
4th row계명대학교대명캠퍼스앞
5th row계명대학교대명캠퍼스건너
ValueCountFrequency (%)
경북대학교 2
 
0.1%
건너 2
 
0.1%
흥사단 2
 
0.1%
북구 2
 
0.1%
국민건강보험공단 2
 
0.1%
죽전동 2
 
0.1%
칠곡ic 2
 
0.1%
범어역(2번출구 1
 
< 0.1%
성바울로성당건너 1
 
< 0.1%
수성요양병원 1
 
< 0.1%
Other values (3313) 3313
99.5%
2024-04-18T00:09:33.966223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
앞 1120
 
4.5%
건 1104
 
4.4%
너 1072
 
4.3%
구 634
 
2.5%
교 596
 
2.4%
대 583
 
2.3%
리 530
 
2.1%
동 493
 
2.0%
1 473
 
1.9%
2 452
 
1.8%
Other values (481) 17996
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23024
91.9%
Decimal Number 1186
 
4.7%
Close Punctuation 310
 
1.2%
Open Punctuation 308
 
1.2%
Uppercase Letter 162
 
0.6%
Other Punctuation 23
 
0.1%
Space Separator 19
 
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 1120
 
4.9%
건 1104
 
4.8%
너 1072
 
4.7%
구 634
 
2.8%
교 596
 
2.6%
대 583
 
2.5%
리 530
 
2.3%
동 493
 
2.1%
학 443
 
1.9%
지 414
 
1.8%
Other values (446) 16035
69.6%
Uppercase Letter
ValueCountFrequency (%)
T 24
14.8%
L 19
11.7%
H 17
10.5%
K 17
10.5%
C 12
7.4%
G 12
7.4%
P 10
6.2%
I 9
 
5.6%
S 9
 
5.6%
B 9
 
5.6%
Other values (6) 24
14.8%
Decimal Number
ValueCountFrequency (%)
1 473
39.9%
2 452
38.1%
3 110
 
9.3%
4 62
 
5.2%
5 30
 
2.5%
9 17
 
1.4%
6 15
 
1.3%
8 11
 
0.9%
7 9
 
0.8%
0 7
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 17
73.9%
· 4
 
17.4%
/ 2
 
8.7%
Close Punctuation
ValueCountFrequency (%)
) 310
100.0%
Open Punctuation
ValueCountFrequency (%)
( 308
100.0%
Space Separator
ValueCountFrequency (%)
19
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 23026
91.9%
Common 1857
 
7.4%
Latin 170
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 1120
 
4.9%
건 1104
 
4.8%
너 1072
 
4.7%
구 634
 
2.8%
교 596
 
2.6%
대 583
 
2.5%
리 530
 
2.3%
동 493
 
2.1%
학 443
 
1.9%
지 414
 
1.8%
Other values (447) 16037
69.6%
Common
ValueCountFrequency (%)
1 473
25.5%
2 452
24.3%
) 310
16.7%
( 308
16.6%
3 110
 
5.9%
4 62
 
3.3%
5 30
 
1.6%
19
 
1.0%
. 17
 
0.9%
9 17
 
0.9%
Other values (7) 59
 
3.2%
Latin
ValueCountFrequency (%)
T 24
14.1%
L 19
11.2%
H 17
10.0%
K 17
10.0%
C 12
 
7.1%
G 12
 
7.1%
P 10
 
5.9%
I 9
 
5.3%
S 9
 
5.3%
B 9
 
5.3%
Other values (7) 32
18.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23024
91.9%
ASCII 2023
 
8.1%
None 6
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
앞 1120
 
4.9%
건 1104
 
4.8%
너 1072
 
4.7%
구 634
 
2.8%
교 596
 
2.6%
대 583
 
2.5%
리 530
 
2.3%
동 493
 
2.1%
학 443
 
1.9%
지 414
 
1.8%
Other values (446) 16035
69.6%
ASCII
ValueCountFrequency (%)
1 473
23.4%
2 452
22.3%
) 310
15.3%
( 308
15.2%
3 110
 
5.4%
4 62
 
3.1%
5 30
 
1.5%
T 24
 
1.2%
19
 
0.9%
L 19
 
0.9%
Other values (23) 216
10.7%
None
ValueCountFrequency (%)
· 4
66.7%
㈜ 2
33.3%

영문명
Text

Distinct1866
Distinct (%)56.4%
Missing3
Missing (%)0.1%
Memory size26.0 KiB
2024-04-18T00:09:34.234600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length38
Mean length20.734281
Min length3

Characters and Unicode

Total characters68589
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

Unique651 ?
Unique (%)19.7%

Sample

1st rowDaemyeong Market
2nd rowDaemyeong Market
3rd rowKeimyung University Daemyeong Campus
4th rowKeimyung University Daemyeong Campus
5th rowJungbu Fire Station
ValueCountFrequency (%)
school 373
 
4.0%
apts 279
 
3.0%
center 233
 
2.5%
station 212
 
2.3%
elementary 187
 
2.0%
daegu 182
 
1.9%
junction 161
 
1.7%
town 153
 
1.6%
market 126
 
1.3%
high 114
 
1.2%
Other values (1565) 7332
78.4%
2024-04-18T00:09:34.627687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6077
 
8.9%
n 5985
 
8.7%
o 5777
 
8.4%
e 5669
 
8.3%
a 4756
 
6.9%
g 3379
 
4.9%
i 3349
 
4.9%
t 2904
 
4.2%
r 2481
 
3.6%
l 2396
 
3.5%
Other values (60) 25816
37.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 51515
75.1%
Uppercase Letter 9132
 
13.3%
Space Separator 6077
 
8.9%
Dash Punctuation 651
 
0.9%
Decimal Number 616
 
0.9%
Close Punctuation 257
 
0.4%
Open Punctuation 257
 
0.4%
Other Punctuation 84
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 5985
11.6%
o 5777
11.2%
e 5669
11.0%
a 4756
 
9.2%
g 3379
 
6.6%
i 3349
 
6.5%
t 2904
 
5.6%
r 2481
 
4.8%
l 2396
 
4.7%
u 2264
 
4.4%
Other values (16) 12555
24.4%
Uppercase Letter
ValueCountFrequency (%)
S 1476
16.2%
C 915
 
10.0%
D 854
 
9.4%
M 655
 
7.2%
H 583
 
6.4%
A 510
 
5.6%
B 489
 
5.4%
G 447
 
4.9%
P 399
 
4.4%
J 392
 
4.3%
Other values (15) 2412
26.4%
Decimal Number
ValueCountFrequency (%)
1 172
27.9%
2 141
22.9%
4 131
21.3%
3 94
15.3%
5 31
 
5.0%
9 17
 
2.8%
6 12
 
1.9%
8 7
 
1.1%
7 6
 
1.0%
0 5
 
0.8%
Other Punctuation
ValueCountFrequency (%)
' 46
54.8%
. 27
32.1%
& 6
 
7.1%
· 4
 
4.8%
/ 1
 
1.2%
Space Separator
ValueCountFrequency (%)
6077
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 651
100.0%
Close Punctuation
ValueCountFrequency (%)
) 257
100.0%
Open Punctuation
ValueCountFrequency (%)
( 257
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60647
88.4%
Common 7942
 
11.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 5985
 
9.9%
o 5777
 
9.5%
e 5669
 
9.3%
a 4756
 
7.8%
g 3379
 
5.6%
i 3349
 
5.5%
t 2904
 
4.8%
r 2481
 
4.1%
l 2396
 
4.0%
u 2264
 
3.7%
Other values (41) 21687
35.8%
Common
ValueCountFrequency (%)
6077
76.5%
- 651
 
8.2%
) 257
 
3.2%
( 257
 
3.2%
1 172
 
2.2%
2 141
 
1.8%
4 131
 
1.6%
3 94
 
1.2%
' 46
 
0.6%
5 31
 
0.4%
Other values (9) 85
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68585
> 99.9%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6077
 
8.9%
n 5985
 
8.7%
o 5777
 
8.4%
e 5669
 
8.3%
a 4756
 
6.9%
g 3379
 
4.9%
i 3349
 
4.9%
t 2904
 
4.2%
r 2481
 
3.6%
l 2396
 
3.5%
Other values (59) 25812
37.6%
None
ValueCountFrequency (%)
· 4
100.0%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size26.0 KiB
대구광역시
3311 

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 3311
100.0%

Length

2024-04-18T00:09:34.733073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:09:34.805786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 3311
100.0%

구군
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size26.0 KiB
달성군
693 
북구
588 
동구
583 
달서구
561 
수성구
418 
Other values (3)
468 

Length

Max length3
Median length3
Mean length2.5049834
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
달성군 693
20.9%
북구 588
17.8%
동구 583
17.6%
달서구 561
16.9%
수성구 418
12.6%
서구 190
 
5.7%
남구 160
 
4.8%
중구 118
 
3.6%

Length

2024-04-18T00:09:34.888008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T00:09:34.991623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
달성군 693
20.9%
북구 588
17.8%
동구 583
17.6%
달서구 561
16.9%
수성구 418
12.6%
서구 190
 
5.7%
남구 160
 
4.8%
중구 118
 
3.6%

동
Text

Distinct143
Distinct (%)4.3%
Missing2
Missing (%)0.1%
Memory size26.0 KiB
2024-04-18T00:09:35.253049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length3.6576005
Min length2

Characters and Unicode

Total characters12103
Distinct characters97
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 row하빈면
2nd row대명3동
3rd row남산4동
4th row대명3동
5th row남산4동
ValueCountFrequency (%)
공산동 160
 
4.8%
안심3.4동 116
 
3.5%
다사읍 106
 
3.2%
가창면 98
 
3.0%
동천동 86
 
2.6%
논공읍 85
 
2.6%
하빈면 79
 
2.4%
화원읍 75
 
2.3%
현풍면 63
 
1.9%
옥포면 62
 
1.9%
Other values (133) 2379
71.9%
2024-04-18T00:09:35.645108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 2738
22.6%
2 566
 
4.7%
산 535
 
4.4%
1 507
 
4.2%
면 425
 
3.5%
3 363
 
3.0%
읍 300
 
2.5%
성 249
 
2.1%
공 245
 
2.0%
4 231
 
1.9%
Other values (87) 5944
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10117
83.6%
Decimal Number 1771
 
14.6%
Other Punctuation 215
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2738
27.1%
산 535
 
5.3%
면 425
 
4.2%
읍 300
 
3.0%
성 249
 
2.5%
공 245
 
2.4%
가 213
 
2.1%
안 208
 
2.1%
천 198
 
2.0%
심 189
 
1.9%
Other values (77) 4817
47.6%
Decimal Number
ValueCountFrequency (%)
2 566
32.0%
1 507
28.6%
3 363
20.5%
4 231
13.0%
6 30
 
1.7%
5 25
 
1.4%
9 25
 
1.4%
7 15
 
0.8%
0 9
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 215
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10117
83.6%
Common 1986
 
16.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2738
27.1%
산 535
 
5.3%
면 425
 
4.2%
읍 300
 
3.0%
성 249
 
2.5%
공 245
 
2.4%
가 213
 
2.1%
안 208
 
2.1%
천 198
 
2.0%
심 189
 
1.9%
Other values (77) 4817
47.6%
Common
ValueCountFrequency (%)
2 566
28.5%
1 507
25.5%
3 363
18.3%
4 231
11.6%
. 215
 
10.8%
6 30
 
1.5%
5 25
 
1.3%
9 25
 
1.3%
7 15
 
0.8%
0 9
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10117
83.6%
ASCII 1986
 
16.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 2738
27.1%
산 535
 
5.3%
면 425
 
4.2%
읍 300
 
3.0%
성 249
 
2.5%
공 245
 
2.4%
가 213
 
2.1%
안 208
 
2.1%
천 198
 
2.0%
심 189
 
1.9%
Other values (77) 4817
47.6%
ASCII
ValueCountFrequency (%)
2 566
28.5%
1 507
25.5%
3 363
18.3%
4 231
11.6%
. 215
 
10.8%
6 30
 
1.5%
5 25
 
1.3%
9 25
 
1.3%
7 15
 
0.8%
0 9
 
0.5%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct3274
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.57347
Minimum128.3581
Maximum128.75908
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.2 KiB
2024-04-18T00:09:35.759871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.3581
5-th percentile128.43759
Q1128.52131
median128.57339
Q3128.62705
95-th percentile128.70836
Maximum128.75908
Range0.4009818
Interquartile range (IQR)0.10574545

Descriptive statistics

Standard deviation0.07922195
Coefficient of variation (CV)0.00061616092
Kurtosis-0.53108813
Mean128.57347
Median Absolute Deviation (MAD)0.0531546
Skewness-0.069835973
Sum425706.77
Variance0.0062761174
MonotonicityNot monotonic
2024-04-18T00:09:35.874810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.49998 3
 
0.1%
128.4999033 3
 
0.1%
128.4779817 3
 
0.1%
128.4999283 2
 
0.1%
128.50738 2
 
0.1%
128.5071517 2
 
0.1%
128.515925 2
 
0.1%
128.5157983 2
 
0.1%
128.507405 2
 
0.1%
128.5074317 2
 
0.1%
Other values (3264) 3288
99.3%
ValueCountFrequency (%)
128.3580983 1
< 0.1%
128.3647367 1
< 0.1%
128.3722133 1
< 0.1%
128.382105 1
< 0.1%
128.392065 1
< 0.1%
128.3925317 1
< 0.1%
128.3938983 1
< 0.1%
128.393925 1
< 0.1%
128.3950433 1
< 0.1%
128.3951 1
< 0.1%
ValueCountFrequency (%)
128.7590801 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%
128.7520217 1
< 0.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct3293
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.853788
Minimum35.617375
Maximum35.995313
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.2 KiB
2024-04-18T00:09:36.011698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.617375
5-th percentile35.697625
Q135.830666
median35.8614
Q335.888082
95-th percentile35.952688
Maximum35.995313
Range0.37793825
Interquartile range (IQR)0.057415355

Descriptive statistics

Standard deviation0.066723431
Coefficient of variation (CV)0.0018609869
Kurtosis1.5726427
Mean35.853788
Median Absolute Deviation (MAD)0.028785
Skewness-0.96471047
Sum118711.89
Variance0.0044520162
MonotonicityNot monotonic
2024-04-18T00:09:36.136242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.858955 3
 
0.1%
35.90923333 2
 
0.1%
35.88897333 2
 
0.1%
35.87196 2
 
0.1%
35.87933167 2
 
0.1%
35.87196167 2
 
0.1%
35.86268 2
 
0.1%
35.89015167 2
 
0.1%
35.880625 2
 
0.1%
35.87566167 2
 
0.1%
Other values (3283) 3290
99.4%
ValueCountFrequency (%)
35.617375 1
< 0.1%
35.61774833 1
< 0.1%
35.618055 1
< 0.1%
35.62304833 1
< 0.1%
35.623665 1
< 0.1%
35.62498167 1
< 0.1%
35.63367167 1
< 0.1%
35.63370167 1
< 0.1%
35.633795 1
< 0.1%
35.63382333 1
< 0.1%
ValueCountFrequency (%)
35.99531325 1
< 0.1%
35.99521 1
< 0.1%
35.99274333 1
< 0.1%
35.99271167 1
< 0.1%
35.99265667 1
< 0.1%
35.992592 1
< 0.1%
35.992535 1
< 0.1%
35.99241 1
< 0.1%
35.991243 1
< 0.1%
35.99035823 1
< 0.1%

경유노선수
Real number (ℝ)

Distinct19
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6626397
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size29.2 KiB
2024-04-18T00:09:36.236391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q35
95-th percentile10
Maximum20
Range19
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.1108507
Coefficient of variation (CV)0.84934665
Kurtosis3.5965673
Mean3.6626397
Median Absolute Deviation (MAD)2
Skewness1.7407804
Sum12127
Variance9.6773923
MonotonicityNot monotonic
2024-04-18T00:09:36.325143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 987
29.8%
2 572
17.3%
3 489
14.8%
4 311
 
9.4%
5 217
 
6.6%
6 206
 
6.2%
7 186
 
5.6%
8 100
 
3.0%
9 57
 
1.7%
10 46
 
1.4%
Other values (9) 140
 
4.2%
ValueCountFrequency (%)
1 987
29.8%
2 572
17.3%
3 489
14.8%
4 311
 
9.4%
5 217
 
6.6%
6 206
 
6.2%
7 186
 
5.6%
8 100
 
3.0%
9 57
 
1.7%
10 46
 
1.4%
ValueCountFrequency (%)
20 2
 
0.1%
19 1
 
< 0.1%
18 12
 
0.4%
16 10
 
0.3%
15 17
 
0.5%
14 19
0.6%
13 18
 
0.5%
12 28
0.8%
11 33
1.0%
10 46
1.4%

경유노선
Text

Distinct1211
Distinct (%)36.6%
Missing0
Missing (%)0.0%
Memory size26.0 KiB
2024-04-18T00:09:36.497778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length83
Median length66
Mean length14.306252
Min length1

Characters and Unicode

Total characters47368
Distinct characters31
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique610 ?
Unique (%)18.4%

Sample

1st row20+7+9
2nd row509+650+706+805+836+달서4+순환2-1
3rd row509+650+706+805+836+달서4-1+순환2
4th row509+650+706+805+836+달서4+순환2-1
5th row509+650+706+805+836+달서4-1+순환2
ValueCountFrequency (%)
성서2 75
 
2.2%
가창2 67
 
2.0%
팔공1 48
 
1.4%
성서3 44
 
1.3%
달성2 35
 
1.0%
300 29
 
0.9%
101+101-1 29
 
0.9%
524 26
 
0.8%
600+655 26
 
0.8%
성서1-1 25
 
0.7%
Other values (1206) 2951
88.0%
2024-04-18T00:09:37.034370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 8816
18.6%
1 4213
 
8.9%
0 4156
 
8.8%
3 3482
 
7.4%
5 3280
 
6.9%
4 2928
 
6.2%
2 2885
 
6.1%
6 2463
 
5.2%
9 2008
 
4.2%
8 1641
 
3.5%
Other values (21) 11496
24.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28459
60.1%
Other Letter 8914
 
18.8%
Math Symbol 8816
 
18.6%
Dash Punctuation 1135
 
2.4%
Space Separator 44
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1137
12.8%
성 1135
12.7%
구 1123
12.6%
달 887
10.0%
급 534
 
6.0%
행 534
 
6.0%
동 508
 
5.7%
칠 442
 
5.0%
곡 442
 
5.0%
북 375
 
4.2%
Other values (8) 1797
20.2%
Decimal Number
ValueCountFrequency (%)
1 4213
14.8%
0 4156
14.6%
3 3482
12.2%
5 3280
11.5%
4 2928
10.3%
2 2885
10.1%
6 2463
8.7%
9 2008
7.1%
8 1641
 
5.8%
7 1403
 
4.9%
Math Symbol
ValueCountFrequency (%)
+ 8816
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1135
100.0%
Space Separator
ValueCountFrequency (%)
44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38454
81.2%
Hangul 8914
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1137
12.8%
성 1135
12.7%
구 1123
12.6%
달 887
10.0%
급 534
 
6.0%
행 534
 
6.0%
동 508
 
5.7%
칠 442
 
5.0%
곡 442
 
5.0%
북 375
 
4.2%
Other values (8) 1797
20.2%
Common
ValueCountFrequency (%)
+ 8816
22.9%
1 4213
11.0%
0 4156
10.8%
3 3482
 
9.1%
5 3280
 
8.5%
4 2928
 
7.6%
2 2885
 
7.5%
6 2463
 
6.4%
9 2008
 
5.2%
8 1641
 
4.3%
Other values (3) 2582
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38454
81.2%
Hangul 8914
 
18.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 8816
22.9%
1 4213
11.0%
0 4156
10.8%
3 3482
 
9.1%
5 3280
 
8.5%
4 2928
 
7.6%
2 2885
 
7.5%
6 2463
 
6.4%
9 2008
 
5.2%
8 1641
 
4.3%
Other values (3) 2582
 
6.7%
Hangul
ValueCountFrequency (%)
서 1137
12.8%
성 1135
12.7%
구 1123
12.6%
달 887
10.0%
급 534
 
6.0%
행 534
 
6.0%
동 508
 
5.7%
칠 442
 
5.0%
곡 442
 
5.0%
북 375
 
4.2%
Other values (8) 1797
20.2%

Interactions

2024-04-18T00:09:32.441414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:30.563158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:30.936385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:31.401148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:32.023632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:32.516922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:30.632802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:31.049216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:31.685321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:32.104878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:32.586399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:30.704386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:31.121222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:31.760171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:32.187179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:32.674074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:30.783271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:31.208222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:31.845477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:32.274163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:32.756793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:30.862330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:31.312053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:31.931758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T00:09:32.359566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T00:09:37.110421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정류소아이디모바일아이디구군경도위도경유노선수
정류소아이디1.000NaNNaNNaNNaNNaN
모바일아이디NaN1.0000.5080.4240.3420.251
구군NaN0.5081.0000.7770.7380.280
경도NaN0.4240.7771.0000.7080.376
위도NaN0.3420.7380.7081.0000.311
경유노선수NaN0.2510.2800.3760.3111.000
2024-04-18T00:09:37.195166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정류소아이디모바일아이디경도위도경유노선수구군
정류소아이디1.000-0.059-0.520-0.704-0.2400.000
모바일아이디-0.0591.0000.2040.0490.1380.312
경도-0.5200.2041.0000.3920.1350.518
위도-0.7040.0490.3921.0000.0900.471
경유노선수-0.2400.1380.1350.0901.0000.137
구군0.0000.3120.5180.4710.1371.000

Missing values

2024-04-18T00:09:32.864790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T00:09:32.986672image/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.
2024-04-18T00:09:33.073610image/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
01570000140<NA>감문리<NA>대구광역시달성군하빈면128.42402135.890748320+7+9
170010001005191대명시장앞Daemyeong Market대구광역시남구대명3동128.5771335.858697509+650+706+805+836+달서4+순환2-1
2700100020020110대명시장건너Daemyeong Market대구광역시중구남산4동128.57782235.8586537509+650+706+805+836+달서4-1+순환2
370010003002166계명대학교대명캠퍼스앞Keimyung University Daemyeong Campus대구광역시남구대명3동128.58084835.8571127509+650+706+805+836+달서4+순환2-1
470010004002163계명대학교대명캠퍼스건너Keimyung University Daemyeong Campus대구광역시중구남산4동128.58000735.8576757509+650+706+805+836+달서4-1+순환2
5700100050021868중부소방서건너Jungbu Fire Station대구광역시중구대신동128.57555935.8631264250+323+909+성서2
6700100060021869중부소방서앞Jungbu Fire Station대구광역시중구남산4동128.57675635.8630693250+323-1+급행6
7700100070021867대신센트럴자이Daesin Central Xi대구광역시중구대신동128.57835.8637355250+323+909+급행6+성서2
8700100080021866청라언덕(신남)역(1번출구)Cheongna Hill(Sinnam) Station대구광역시중구대신동128.58118335.8646924250+323+909+성서2
9700100090021872엘디스리젠트호텔건너Eldis Regent Hotel대구광역시중구남산2동128.58676135.8660442405+609
정류소아이디모바일아이디정류소명영문명시도구군동경도위도경유노선수경유노선
330171110821004241우록리(숲속전원마을)건너Urok-ri대구광역시달성군가창면128.65725735.7283471가창2
330271110822009306이현고개삼거리(시내방향)Ihyeongogae (3) Junction대구광역시달성군다사읍128.4592235.8794271성서3
330371110823004301서재문화체육센터앞2Seojae Culture&Sports Center대구광역시달성군다사읍128.50153335.8837471성서3
330471110824009315포산서사거리1Posanseo(4)Junction대구광역시달성군유가면128.45422835.6893051급행8-1
330571110825009316포산서사거리2Posanseo(4)Junction대구광역시달성군유가면128.45442735.6891121급행8-1
330671110826009317포산고등학교3Po-san HighSchool대구광역시달성군현풍면128.44922735.6910471급행8-1
330771110827009327상원리(마을회관)2Sangwon-ri대구광역시달성군가창면128.66216535.77851가창2
330871110828009328상원리(전평못식당)2Sangwon-ri대구광역시달성군가창면128.6573835.7738981가창2
330971110829009329단산리입구2Dansan-ri대구광역시달성군가창면128.65340535.7715351가창2
331071810748004145연광시니어타운건너Yeongwang Senior Town대구광역시달성군하빈면128.42781335.927761성서2