Overview

Dataset statistics

Number of variables9
Number of observations6946
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory522.4 KiB
Average record size in memory77.0 B

Variable types

Categorical2
Text4
Numeric3

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-12912/S/1/datasetView.do

Alerts

사용일자 has constant value ""Constant
등록일자 has constant value ""Constant
승차총승객수 is highly overall correlated with 하차총승객수High correlation
하차총승객수 is highly overall correlated with 승차총승객수High correlation
승차총승객수 has 395 (5.7%) zerosZeros
하차총승객수 has 243 (3.5%) zerosZeros

Reproduction

Analysis started2024-05-04 04:38:25.460590
Analysis finished2024-05-04 04:38:32.314212
Duration6.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
20231101
6946 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20231101
2nd row20231101
3rd row20231101
4th row20231101
5th row20231101

Common Values

ValueCountFrequency (%)
20231101 6946
100.0%

Length

2024-05-04T04:38:32.558276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:38:33.040458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20231101 6946
100.0%

노선번호
Text

Distinct87
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
2024-05-04T04:38:33.632419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.5463576
Min length3

Characters and Unicode

Total characters24633
Distinct characters22
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

Unique2 ?
Unique (%)< 0.1%

Sample

1st row100
2nd row7727
3rd row7727
4th row7727
5th row7727
ValueCountFrequency (%)
n26 251
 
3.6%
n37 207
 
3.0%
542 138
 
2.0%
9701 127
 
1.8%
661 125
 
1.8%
441 124
 
1.8%
541 123
 
1.8%
302 122
 
1.8%
9403 119
 
1.7%
107 118
 
1.7%
Other values (77) 5492
79.1%
2024-05-04T04:38:34.713275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 3661
14.9%
0 3625
14.7%
5 3188
12.9%
1 2706
11.0%
2 2599
10.6%
6 2270
9.2%
3 2260
9.2%
4 2174
8.8%
9 808
 
3.3%
N 486
 
2.0%
Other values (12) 856
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23584
95.7%
Uppercase Letter 702
 
2.8%
Other Letter 318
 
1.3%
Dash Punctuation 29
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 3661
15.5%
0 3625
15.4%
5 3188
13.5%
1 2706
11.5%
2 2599
11.0%
6 2270
9.6%
3 2260
9.6%
4 2174
9.2%
9 808
 
3.4%
8 293
 
1.2%
Other Letter
ValueCountFrequency (%)
강 109
34.3%
동 105
33.0%
서 29
 
9.1%
성 28
 
8.8%
북 18
 
5.7%
울 15
 
4.7%
노 7
 
2.2%
원 7
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
N 486
69.2%
B 147
 
20.9%
A 69
 
9.8%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23613
95.9%
Latin 702
 
2.8%
Hangul 318
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
7 3661
15.5%
0 3625
15.4%
5 3188
13.5%
1 2706
11.5%
2 2599
11.0%
6 2270
9.6%
3 2260
9.6%
4 2174
9.2%
9 808
 
3.4%
8 293
 
1.2%
Hangul
ValueCountFrequency (%)
강 109
34.3%
동 105
33.0%
서 29
 
9.1%
성 28
 
8.8%
북 18
 
5.7%
울 15
 
4.7%
노 7
 
2.2%
원 7
 
2.2%
Latin
ValueCountFrequency (%)
N 486
69.2%
B 147
 
20.9%
A 69
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24315
98.7%
Hangul 318
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 3661
15.1%
0 3625
14.9%
5 3188
13.1%
1 2706
11.1%
2 2599
10.7%
6 2270
9.3%
3 2260
9.3%
4 2174
8.9%
9 808
 
3.3%
N 486
 
2.0%
Other values (4) 538
 
2.2%
Hangul
ValueCountFrequency (%)
강 109
34.3%
동 105
33.0%
서 29
 
9.1%
성 28
 
8.8%
북 18
 
5.7%
울 15
 
4.7%
노 7
 
2.2%
원 7
 
2.2%

노선명
Text

Distinct89
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
2024-05-04T04:38:35.513390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length21
Mean length17.002879
Min length12

Characters and Unicode

Total characters118102
Distinct characters187
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row100번(하계동~용산구청)
2nd row7727번(설문동~신촌)
3rd row7727번(설문동~신촌)
4th row7727번(설문동~신촌)
5th row7727번(설문동~신촌)
ValueCountFrequency (%)
542번(군포버스공영차고지~신사역 138
 
1.9%
9701번(가좌동~서울역 127
 
1.8%
n26번(중랑공영차고지~강서공영차고지 126
 
1.7%
n26번(강서공영차고지~중랑공영차고지 125
 
1.7%
661번(부천상동~영등포역,신세계백화점 125
 
1.7%
441번(월암공영차고지~신사사거리 124
 
1.7%
541번(군포공영차고지~강남역 123
 
1.7%
302번(성남~동대문 122
 
1.7%
9403번(구미동차고지~중곡역 119
 
1.6%
107번(민락동차고지~동대문 118
 
1.6%
Other values (82) 5970
82.7%
2024-05-04T04:38:36.977868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 7109
 
6.0%
( 7109
 
6.0%
~ 6946
 
5.9%
번 6591
 
5.6%
동 4440
 
3.8%
고 4207
 
3.6%
지 4148
 
3.5%
차 3912
 
3.3%
7 3661
 
3.1%
0 3625
 
3.1%
Other values (177) 66354
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71633
60.7%
Decimal Number 23733
 
20.1%
Close Punctuation 7109
 
6.0%
Open Punctuation 7109
 
6.0%
Math Symbol 6946
 
5.9%
Uppercase Letter 732
 
0.6%
Other Punctuation 540
 
0.5%
Space Separator 271
 
0.2%
Dash Punctuation 29
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 6591
 
9.2%
동 4440
 
6.2%
고 4207
 
5.9%
지 4148
 
5.8%
차 3912
 
5.5%
영 2989
 
4.2%
역 2888
 
4.0%
공 2646
 
3.7%
대 1685
 
2.4%
서 1619
 
2.3%
Other values (156) 36508
51.0%
Decimal Number
ValueCountFrequency (%)
7 3661
15.4%
0 3625
15.3%
5 3188
13.4%
1 2855
12.0%
2 2599
11.0%
6 2270
9.6%
3 2260
9.5%
4 2174
9.2%
9 808
 
3.4%
8 293
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
N 486
66.4%
B 147
 
20.1%
A 84
 
11.5%
K 15
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 409
75.7%
. 131
 
24.3%
Close Punctuation
ValueCountFrequency (%)
) 7109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7109
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6946
100.0%
Space Separator
ValueCountFrequency (%)
271
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71633
60.7%
Common 45737
38.7%
Latin 732
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 6591
 
9.2%
동 4440
 
6.2%
고 4207
 
5.9%
지 4148
 
5.8%
차 3912
 
5.5%
영 2989
 
4.2%
역 2888
 
4.0%
공 2646
 
3.7%
대 1685
 
2.4%
서 1619
 
2.3%
Other values (156) 36508
51.0%
Common
ValueCountFrequency (%)
) 7109
15.5%
( 7109
15.5%
~ 6946
15.2%
7 3661
8.0%
0 3625
7.9%
5 3188
7.0%
1 2855
6.2%
2 2599
 
5.7%
6 2270
 
5.0%
3 2260
 
4.9%
Other values (7) 4115
9.0%
Latin
ValueCountFrequency (%)
N 486
66.4%
B 147
 
20.1%
A 84
 
11.5%
K 15
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71633
60.7%
ASCII 46469
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 7109
15.3%
( 7109
15.3%
~ 6946
14.9%
7 3661
7.9%
0 3625
7.8%
5 3188
6.9%
1 2855
6.1%
2 2599
 
5.6%
6 2270
 
4.9%
3 2260
 
4.9%
Other values (11) 4847
10.4%
Hangul
ValueCountFrequency (%)
번 6591
 
9.2%
동 4440
 
6.2%
고 4207
 
5.9%
지 4148
 
5.8%
차 3912
 
5.5%
영 2989
 
4.2%
역 2888
 
4.0%
공 2646
 
3.7%
대 1685
 
2.4%
서 1619
 
2.3%
Other values (156) 36508
51.0%

표준버스정류장ID
Real number (ℝ)

Distinct3760
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5298196 × 108
Minimum1 × 108
Maximum9.998 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2024-05-04T04:38:37.913160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1 × 108
5-th percentile1.0100026 × 108
Q11.1200007 × 108
median1.2000004 × 108
Q32.0900022 × 108
95-th percentile2.220006 × 108
Maximum9.998 × 108
Range8.998 × 108
Interquartile range (IQR)97000152

Descriptive statistics

Standard deviation66991179
Coefficient of variation (CV)0.43790248
Kurtosis70.027337
Mean1.5298196 × 108
Median Absolute Deviation (MAD)14000036
Skewness5.9134838
Sum1.0626127 × 1012
Variance4.487818 × 1015
MonotonicityNot monotonic
2024-05-04T04:38:38.973708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
121000010 11
 
0.2%
100000380 10
 
0.1%
121000006 10
 
0.1%
121000013 10
 
0.1%
121000012 10
 
0.1%
121000009 10
 
0.1%
121000008 10
 
0.1%
121000014 10
 
0.1%
121000005 10
 
0.1%
100000384 10
 
0.1%
Other values (3750) 6845
98.5%
ValueCountFrequency (%)
100000001 2
< 0.1%
100000002 2
< 0.1%
100000003 1
 
< 0.1%
100000004 3
< 0.1%
100000005 1
 
< 0.1%
100000006 1
 
< 0.1%
100000007 1
 
< 0.1%
100000008 1
 
< 0.1%
100000015 1
 
< 0.1%
100000016 1
 
< 0.1%
ValueCountFrequency (%)
999800005 2
< 0.1%
999800004 1
 
< 0.1%
999800003 1
 
< 0.1%
999033574 4
0.1%
998501980 2
< 0.1%
998501973 1
 
< 0.1%
998501932 1
 
< 0.1%
998501931 1
 
< 0.1%
998001700 2
< 0.1%
997000041 1
 
< 0.1%

버스정류장ARS번호
Text

Distinct3725
Distinct (%)53.6%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
2024-05-04T04:38:40.166688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.9884826
Min length1

Characters and Unicode

Total characters34650
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

Unique2177 ?
Unique (%)31.3%

Sample

1st row01002
2nd row35633
3rd row35621
4th row13259
5th row13147
ValueCountFrequency (%)
20
 
0.3%
22010 11
 
0.2%
22012 10
 
0.1%
01007 10
 
0.1%
22006 10
 
0.1%
22014 10
 
0.1%
22013 10
 
0.1%
18003 10
 
0.1%
22005 10
 
0.1%
18004 10
 
0.1%
Other values (3715) 6835
98.4%
2024-05-04T04:38:42.009314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6731
19.4%
0 6332
18.3%
2 4509
13.0%
3 3713
10.7%
4 2858
8.2%
6 2654
 
7.7%
5 2400
 
6.9%
7 2055
 
5.9%
8 1883
 
5.4%
9 1495
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34630
99.9%
Math Symbol 20
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6731
19.4%
0 6332
18.3%
2 4509
13.0%
3 3713
10.7%
4 2858
8.3%
6 2654
 
7.7%
5 2400
 
6.9%
7 2055
 
5.9%
8 1883
 
5.4%
9 1495
 
4.3%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34650
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6731
19.4%
0 6332
18.3%
2 4509
13.0%
3 3713
10.7%
4 2858
8.2%
6 2654
 
7.7%
5 2400
 
6.9%
7 2055
 
5.9%
8 1883
 
5.4%
9 1495
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34650
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6731
19.4%
0 6332
18.3%
2 4509
13.0%
3 3713
10.7%
4 2858
8.2%
6 2654
 
7.7%
5 2400
 
6.9%
7 2055
 
5.9%
8 1883
 
5.4%
9 1495
 
4.3%

역명
Text

Distinct6544
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
2024-05-04T04:38:42.646896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length15.129283
Min length9

Characters and Unicode

Total characters105088
Distinct characters545
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6222 ?
Unique (%)89.6%

Sample

1st row창경궁.서울대학교병원(00031)
2nd row행신동(중)(00075)
3rd row대곡역(중)(00031)
4th row현대백화점(00055)
5th row연희동대우아파트(00057)
ValueCountFrequency (%)
광명차고지(00001 6
 
0.1%
하안버스공영차고지(00002 6
 
0.1%
덕은교.은평차고지앞(00002 5
 
0.1%
은평공영차고지(00001 5
 
0.1%
대우.롯데아파트상가(00008 4
 
0.1%
오리초등학교(00006 4
 
0.1%
주공4단지(00004 4
 
0.1%
lg아파트.무지개마을사거리.신한아파트(00003 4
 
0.1%
대원사거리.까치마을(00009 4
 
0.1%
동해운수(00001 4
 
0.1%
Other values (6534) 6900
99.3%
2024-05-04T04:38:44.017635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21996
 
20.9%
) 7196
 
6.8%
( 7196
 
6.8%
1 2531
 
2.4%
. 2383
 
2.3%
2 1812
 
1.7%
3 1637
 
1.6%
4 1541
 
1.5%
5 1501
 
1.4%
6 1446
 
1.4%
Other values (535) 55849
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51500
49.0%
Decimal Number 36189
34.4%
Close Punctuation 7196
 
6.8%
Open Punctuation 7196
 
6.8%
Other Punctuation 2390
 
2.3%
Uppercase Letter 587
 
0.6%
Lowercase Letter 28
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 1357
 
2.6%
동 1323
 
2.6%
교 1273
 
2.5%
지 1115
 
2.2%
구 1023
 
2.0%
파 980
 
1.9%
아 925
 
1.8%
트 922
 
1.8%
학 887
 
1.7%
대 873
 
1.7%
Other values (495) 40822
79.3%
Uppercase Letter
ValueCountFrequency (%)
C 90
15.3%
K 77
13.1%
T 75
12.8%
M 72
12.3%
D 66
11.2%
L 40
6.8%
G 39
6.6%
S 27
 
4.6%
B 25
 
4.3%
A 12
 
2.0%
Other values (11) 64
10.9%
Decimal Number
ValueCountFrequency (%)
0 21996
60.8%
1 2531
 
7.0%
2 1812
 
5.0%
3 1637
 
4.5%
4 1541
 
4.3%
5 1501
 
4.1%
6 1446
 
4.0%
7 1390
 
3.8%
8 1231
 
3.4%
9 1104
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 2383
99.7%
& 6
 
0.3%
? 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 26
92.9%
t 1
 
3.6%
k 1
 
3.6%
Close Punctuation
ValueCountFrequency (%)
) 7196
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7196
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52973
50.4%
Hangul 51500
49.0%
Latin 615
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 1357
 
2.6%
동 1323
 
2.6%
교 1273
 
2.5%
지 1115
 
2.2%
구 1023
 
2.0%
파 980
 
1.9%
아 925
 
1.8%
트 922
 
1.8%
학 887
 
1.7%
대 873
 
1.7%
Other values (495) 40822
79.3%
Latin
ValueCountFrequency (%)
C 90
14.6%
K 77
12.5%
T 75
12.2%
M 72
11.7%
D 66
10.7%
L 40
6.5%
G 39
6.3%
S 27
 
4.4%
e 26
 
4.2%
B 25
 
4.1%
Other values (14) 78
12.7%
Common
ValueCountFrequency (%)
0 21996
41.5%
) 7196
 
13.6%
( 7196
 
13.6%
1 2531
 
4.8%
. 2383
 
4.5%
2 1812
 
3.4%
3 1637
 
3.1%
4 1541
 
2.9%
5 1501
 
2.8%
6 1446
 
2.7%
Other values (6) 3734
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53588
51.0%
Hangul 51500
49.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21996
41.0%
) 7196
 
13.4%
( 7196
 
13.4%
1 2531
 
4.7%
. 2383
 
4.4%
2 1812
 
3.4%
3 1637
 
3.1%
4 1541
 
2.9%
5 1501
 
2.8%
6 1446
 
2.7%
Other values (30) 4349
 
8.1%
Hangul
ValueCountFrequency (%)
역 1357
 
2.6%
동 1323
 
2.6%
교 1273
 
2.5%
지 1115
 
2.2%
구 1023
 
2.0%
파 980
 
1.9%
아 925
 
1.8%
트 922
 
1.8%
학 887
 
1.7%
대 873
 
1.7%
Other values (495) 40822
79.3%

승차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct600
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.08465
Minimum0
Maximum1967
Zeros395
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2024-05-04T04:38:44.636423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q116
median65
Q3157
95-th percentile374
Maximum1967
Range1967
Interquartile range (IQR)141

Descriptive statistics

Standard deviation142.19115
Coefficient of variation (CV)1.2800252
Kurtosis16.926261
Mean111.08465
Median Absolute Deviation (MAD)57
Skewness3.0977579
Sum771594
Variance20218.323
MonotonicityNot monotonic
2024-05-04T04:38:45.303507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 395
 
5.7%
1 202
 
2.9%
2 157
 
2.3%
3 121
 
1.7%
5 105
 
1.5%
4 105
 
1.5%
6 96
 
1.4%
7 82
 
1.2%
8 71
 
1.0%
9 68
 
1.0%
Other values (590) 5544
79.8%
ValueCountFrequency (%)
0 395
5.7%
1 202
2.9%
2 157
 
2.3%
3 121
 
1.7%
4 105
 
1.5%
5 105
 
1.5%
6 96
 
1.4%
7 82
 
1.2%
8 71
 
1.0%
9 68
 
1.0%
ValueCountFrequency (%)
1967 1
< 0.1%
1543 1
< 0.1%
1349 1
< 0.1%
1336 1
< 0.1%
1332 1
< 0.1%
1266 1
< 0.1%
1253 1
< 0.1%
1223 1
< 0.1%
1199 1
< 0.1%
1198 1
< 0.1%

하차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct584
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.42312
Minimum0
Maximum1910
Zeros243
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2024-05-04T04:38:45.988468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q117
median67
Q3148
95-th percentile363
Maximum1910
Range1910
Interquartile range (IQR)131

Descriptive statistics

Standard deviation138.74701
Coefficient of variation (CV)1.2679862
Kurtosis19.221798
Mean109.42312
Median Absolute Deviation (MAD)57
Skewness3.2971812
Sum760053
Variance19250.733
MonotonicityNot monotonic
2024-05-04T04:38:46.619716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 243
 
3.5%
1 193
 
2.8%
2 143
 
2.1%
3 136
 
2.0%
5 114
 
1.6%
4 109
 
1.6%
8 92
 
1.3%
7 85
 
1.2%
6 84
 
1.2%
9 74
 
1.1%
Other values (574) 5673
81.7%
ValueCountFrequency (%)
0 243
3.5%
1 193
2.8%
2 143
2.1%
3 136
2.0%
4 109
1.6%
5 114
1.6%
6 84
 
1.2%
7 85
 
1.2%
8 92
 
1.3%
9 74
 
1.1%
ValueCountFrequency (%)
1910 1
< 0.1%
1514 1
< 0.1%
1502 1
< 0.1%
1470 1
< 0.1%
1419 1
< 0.1%
1348 1
< 0.1%
1317 1
< 0.1%
1157 1
< 0.1%
1132 1
< 0.1%
1128 1
< 0.1%

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
20231104
6946 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20231104
2nd row20231104
3rd row20231104
4th row20231104
5th row20231104

Common Values

ValueCountFrequency (%)
20231104 6946
100.0%

Length

2024-05-04T04:38:47.258925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:38:47.603654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20231104 6946
100.0%

Interactions

2024-05-04T04:38:30.199552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:28.005338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:29.168905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:30.603639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:28.442343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:29.487862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:31.011753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:28.772537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:29.819499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T04:38:47.818053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선명표준버스정류장ID승차총승객수하차총승객수
노선번호1.0001.0000.6740.4030.408
노선명1.0001.0000.6610.4010.407
표준버스정류장ID0.6740.6611.0000.2710.278
승차총승객수0.4030.4010.2711.0000.799
하차총승객수0.4080.4070.2780.7991.000
2024-05-04T04:38:48.174335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준버스정류장ID승차총승객수하차총승객수
표준버스정류장ID1.000-0.216-0.216
승차총승객수-0.2161.0000.548
하차총승객수-0.2160.5481.000

Missing values

2024-05-04T04:38:31.504572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T04:38:32.088225image/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

사용일자노선번호노선명표준버스정류장ID버스정류장ARS번호역명승차총승객수하차총승객수등록일자
020231101100100번(하계동~용산구청)10000000201002창경궁.서울대학교병원(00031)13617820231104
12023110177277727번(설문동~신촌)21800007835633행신동(중)(00075)24025120231104
22023110177277727번(설문동~신촌)21800001235621대곡역(중)(00031)1418720231104
32023110177277727번(설문동~신촌)11200017613259현대백화점(00055)1165320231104
42023110177277727번(설문동~신촌)11200006413147연희동대우아파트(00057)993420231104
520231101100100번(하계동~용산구청)10100000702007서울역버스환승센터.강우규의거터(00076)8213720231104
62023110177277727번(설문동~신촌)11200006113144동교동삼거리연희동방면(00056)18311420231104
72023110177277727번(설문동~신촌)11200003113114연세대학교앞(00053)15820720231104
82023110177277727번(설문동~신촌)11200002813111연희104고지앞.구성산회관(00058)1052120231104
92023110177277727번(설문동~신촌)11200002613109사천교(00059)943520231104
사용일자노선번호노선명표준버스정류장ID버스정류장ARS번호역명승차총승객수하차총승객수등록일자
693620231101540540번(군포공영차고지~강남성모병원)20900000656070호계사거리(00014)1599320231104
693720231101540540번(군포공영차고지~강남성모병원)20900000756078서안이노빌아파트.평촌어바인퍼스트(00013)35425420231104
693820231101540540번(군포공영차고지~강남성모병원)20900001056079농협.홈플러스(00081)33722320231104
693920231101540540번(군포공영차고지~강남성모병원)20900001156602호계사거리(00080)10627220231104
694020231101540540번(군포공영차고지~강남성모병원)20900001256074덕고개사거리(00078)806320231104
694120231101540540번(군포공영차고지~강남성모병원)20900001360015샘마을.대안중학교(00077)6715920231104
694220231101540540번(군포공영차고지~강남성모병원)20900001456073안양남초등학교(00076)23338220231104
694320231101540540번(군포공영차고지~강남성모병원)20900002756058농수산물시장.포일단지입구(00075)12828120231104
694420231101540540번(군포공영차고지~강남성모병원)20900002856056민백마을(00074)13624320231104
694520231101540540번(군포공영차고지~강남성모병원)20900002910164나눔초등학교.오뚜기식품.두산벤처다임(00073)26437520231104