Overview

Dataset statistics

Number of variables9
Number of observations7508
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory564.7 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 498 (6.6%) zerosZeros
하차총승객수 has 349 (4.6%) zerosZeros

Reproduction

Analysis started2024-04-29 16:28:51.384475
Analysis finished2024-04-29 16:28:53.290691
Duration1.91 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.8 KiB
20230201
7508 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20230201
2nd row20230201
3rd row20230201
4th row20230201
5th row20230201

Common Values

ValueCountFrequency (%)
20230201 7508
100.0%

Length

2024-04-30T01:28:53.355188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T01:28:53.433435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20230201 7508
100.0%

노선번호
Text

Distinct92
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size58.8 KiB
2024-04-30T01:28:53.627633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.6172083
Min length3

Characters and Unicode

Total characters27158
Distinct characters23
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

Unique0 ?
Unique (%)0.0%

Sample

1st row601
2nd row9703
3rd row9703
4th row9703
5th row9703
ValueCountFrequency (%)
n26 244
 
3.2%
n15 229
 
3.1%
n37 201
 
2.7%
9408 144
 
1.9%
542 138
 
1.8%
9403 136
 
1.8%
9701 127
 
1.7%
661 125
 
1.7%
441 124
 
1.7%
541 123
 
1.6%
Other values (82) 5917
78.8%
2024-04-30T01:28:53.968945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 4100
15.1%
1 3573
13.2%
5 3449
12.7%
0 3028
11.1%
6 2598
9.6%
2 2484
9.1%
3 2399
8.8%
4 2372
8.7%
9 1007
 
3.7%
N 674
 
2.5%
Other values (13) 1474
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25660
94.5%
Uppercase Letter 893
 
3.3%
Other Letter 590
 
2.2%
Dash Punctuation 15
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 4100
16.0%
1 3573
13.9%
5 3449
13.4%
0 3028
11.8%
6 2598
10.1%
2 2484
9.7%
3 2399
9.3%
4 2372
9.2%
9 1007
 
3.9%
8 650
 
2.5%
Other Letter
ValueCountFrequency (%)
노 148
25.1%
원 148
25.1%
동 106
18.0%
강 98
16.6%
성 29
 
4.9%
은 20
 
3.4%
평 20
 
3.4%
서 15
 
2.5%
남 6
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
N 674
75.5%
B 148
 
16.6%
A 71
 
8.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25675
94.5%
Latin 893
 
3.3%
Hangul 590
 
2.2%

Most frequent character per script

Common
ValueCountFrequency (%)
7 4100
16.0%
1 3573
13.9%
5 3449
13.4%
0 3028
11.8%
6 2598
10.1%
2 2484
9.7%
3 2399
9.3%
4 2372
9.2%
9 1007
 
3.9%
8 650
 
2.5%
Hangul
ValueCountFrequency (%)
노 148
25.1%
원 148
25.1%
동 106
18.0%
강 98
16.6%
성 29
 
4.9%
은 20
 
3.4%
평 20
 
3.4%
서 15
 
2.5%
남 6
 
1.0%
Latin
ValueCountFrequency (%)
N 674
75.5%
B 148
 
16.6%
A 71
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26568
97.8%
Hangul 590
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 4100
15.4%
1 3573
13.4%
5 3449
13.0%
0 3028
11.4%
6 2598
9.8%
2 2484
9.3%
3 2399
9.0%
4 2372
8.9%
9 1007
 
3.8%
N 674
 
2.5%
Other values (4) 884
 
3.3%
Hangul
ValueCountFrequency (%)
노 148
25.1%
원 148
25.1%
동 106
18.0%
강 98
16.6%
성 29
 
4.9%
은 20
 
3.4%
평 20
 
3.4%
서 15
 
2.5%
남 6
 
1.0%

노선명
Text

Distinct96
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size58.8 KiB
2024-04-30T01:28:54.156836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length17.370538
Min length12

Characters and Unicode

Total characters130418
Distinct characters184
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

Unique0 ?
Unique (%)0.0%

Sample

1st row601번(개화동~종로4가)
2nd row9703번(신성교통차고지~서울역)
3rd row9703번(신성교통차고지~서울역)
4th row9703번(신성교통차고지~서울역)
5th row9703번(신성교통차고지~서울역)
ValueCountFrequency (%)
9408번(성남 144
 
1.8%
분당~영등포 144
 
1.8%
n15번(우이동성원아파트~남태령역 142
 
1.8%
542번(군포버스공영차고지~신사역 138
 
1.7%
9403번(성남분당~을지로5가 136
 
1.7%
9701번(가좌동~서울역 127
 
1.6%
661번(부천상동~영등포역,신세계백화점 125
 
1.6%
441번(월암공영차고지~신사사거리 124
 
1.6%
n26번(중랑공영차고지~강서공영차고지 123
 
1.6%
541번(군포공영차고지~강남역 123
 
1.6%
Other values (90) 6602
83.3%
2024-04-30T01:28:54.474375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 7592
 
5.8%
( 7592
 
5.8%
~ 7508
 
5.8%
번 7114
 
5.5%
지 4430
 
3.4%
동 4308
 
3.3%
고 4124
 
3.2%
7 4106
 
3.1%
차 3914
 
3.0%
1 3864
 
3.0%
Other values (174) 75866
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79747
61.1%
Decimal Number 26103
 
20.0%
Close Punctuation 7592
 
5.8%
Open Punctuation 7592
 
5.8%
Math Symbol 7508
 
5.8%
Uppercase Letter 893
 
0.7%
Other Punctuation 548
 
0.4%
Space Separator 420
 
0.3%
Dash Punctuation 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 7114
 
8.9%
지 4430
 
5.6%
동 4308
 
5.4%
고 4124
 
5.2%
차 3914
 
4.9%
영 3228
 
4.0%
역 3140
 
3.9%
공 2767
 
3.5%
서 1571
 
2.0%
대 1520
 
1.9%
Other values (154) 43631
54.7%
Decimal Number
ValueCountFrequency (%)
7 4106
15.7%
1 3864
14.8%
5 3585
13.7%
0 3028
11.6%
6 2598
10.0%
2 2484
9.5%
3 2399
9.2%
4 2382
9.1%
9 1007
 
3.9%
8 650
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
N 674
75.5%
B 148
 
16.6%
A 71
 
8.0%
Other Punctuation
ValueCountFrequency (%)
, 411
75.0%
. 137
 
25.0%
Close Punctuation
ValueCountFrequency (%)
) 7592
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7592
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7508
100.0%
Space Separator
ValueCountFrequency (%)
420
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79747
61.1%
Common 49778
38.2%
Latin 893
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 7114
 
8.9%
지 4430
 
5.6%
동 4308
 
5.4%
고 4124
 
5.2%
차 3914
 
4.9%
영 3228
 
4.0%
역 3140
 
3.9%
공 2767
 
3.5%
서 1571
 
2.0%
대 1520
 
1.9%
Other values (154) 43631
54.7%
Common
ValueCountFrequency (%)
) 7592
15.3%
( 7592
15.3%
~ 7508
15.1%
7 4106
8.2%
1 3864
7.8%
5 3585
7.2%
0 3028
 
6.1%
6 2598
 
5.2%
2 2484
 
5.0%
3 2399
 
4.8%
Other values (7) 5022
10.1%
Latin
ValueCountFrequency (%)
N 674
75.5%
B 148
 
16.6%
A 71
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79747
61.1%
ASCII 50671
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 7592
15.0%
( 7592
15.0%
~ 7508
14.8%
7 4106
8.1%
1 3864
7.6%
5 3585
7.1%
0 3028
 
6.0%
6 2598
 
5.1%
2 2484
 
4.9%
3 2399
 
4.7%
Other values (10) 5915
11.7%
Hangul
ValueCountFrequency (%)
번 7114
 
8.9%
지 4430
 
5.6%
동 4308
 
5.4%
고 4124
 
5.2%
차 3914
 
4.9%
영 3228
 
4.0%
역 3140
 
3.9%
공 2767
 
3.5%
서 1571
 
2.0%
대 1520
 
1.9%
Other values (154) 43631
54.7%

표준버스정류장ID
Real number (ℝ)

Distinct3908
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4838691 × 108
Minimum1 × 108
Maximum9.998 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size66.1 KiB
2024-04-30T01:28:54.595749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1 × 108
5-th percentile1.010001 × 108
Q11.1100093 × 108
median1.19 × 108
Q32.0900001 × 108
95-th percentile2.2200063 × 108
Maximum9.998 × 108
Range8.998 × 108
Interquartile range (IQR)97999074

Descriptive statistics

Standard deviation63734799
Coefficient of variation (CV)0.42951765
Kurtosis72.930351
Mean1.4838691 × 108
Median Absolute Deviation (MAD)9999784.5
Skewness5.9228161
Sum1.114089 × 1012
Variance4.0621246 × 1015
MonotonicityNot monotonic
2024-04-30T01:28:54.719476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
121000005 12
 
0.2%
100000384 12
 
0.2%
121000007 12
 
0.2%
100000380 11
 
0.1%
121000006 11
 
0.1%
121000008 11
 
0.1%
121000009 11
 
0.1%
121000014 10
 
0.1%
121000010 10
 
0.1%
121000013 10
 
0.1%
Other values (3898) 7398
98.5%
ValueCountFrequency (%)
100000001 3
< 0.1%
100000002 2
< 0.1%
100000003 2
< 0.1%
100000004 3
< 0.1%
100000005 3
< 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%
998502944 1
 
< 0.1%
998502062 1
 
< 0.1%
998501980 1
 
< 0.1%
998501932 1
 
< 0.1%
998501931 1
 
< 0.1%
998001700 1
 
< 0.1%

버스정류장ARS번호
Text

Distinct3869
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Memory size58.8 KiB
2024-04-30T01:28:55.018078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.9904102
Min length1

Characters and Unicode

Total characters37468
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

Unique2176 ?
Unique (%)29.0%

Sample

1st row14198
2nd row12026
3rd row12023
4th row12024
5th row12021
ValueCountFrequency (%)
18
 
0.2%
22005 12
 
0.2%
22007 12
 
0.2%
01009 12
 
0.2%
22006 11
 
0.1%
22008 11
 
0.1%
22009 11
 
0.1%
01007 11
 
0.1%
13005 10
 
0.1%
12006 10
 
0.1%
Other values (3859) 7390
98.4%
2024-04-30T01:28:55.434934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7678
20.5%
0 6705
17.9%
2 5226
13.9%
3 3934
10.5%
4 2874
 
7.7%
6 2754
 
7.4%
5 2563
 
6.8%
7 2237
 
6.0%
8 1965
 
5.2%
9 1514
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37450
> 99.9%
Math Symbol 18
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7678
20.5%
0 6705
17.9%
2 5226
14.0%
3 3934
10.5%
4 2874
 
7.7%
6 2754
 
7.4%
5 2563
 
6.8%
7 2237
 
6.0%
8 1965
 
5.2%
9 1514
 
4.0%
Math Symbol
ValueCountFrequency (%)
~ 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37468
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7678
20.5%
0 6705
17.9%
2 5226
13.9%
3 3934
10.5%
4 2874
 
7.7%
6 2754
 
7.4%
5 2563
 
6.8%
7 2237
 
6.0%
8 1965
 
5.2%
9 1514
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37468
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7678
20.5%
0 6705
17.9%
2 5226
13.9%
3 3934
10.5%
4 2874
 
7.7%
6 2754
 
7.4%
5 2563
 
6.8%
7 2237
 
6.0%
8 1965
 
5.2%
9 1514
 
4.0%

역명
Text

Distinct7115
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size58.8 KiB
2024-04-30T01:28:55.638333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length15.007858
Min length9

Characters and Unicode

Total characters112679
Distinct characters545
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

Unique6823 ?
Unique (%)90.9%

Sample

1st row성산2교(00022)
2nd row한전서대문은평.북한산푸르지오(00049)
3rd row불광역3호선.서울혁신파크(00072)
4th row불광역3호선.서울혁신파크(00048)
5th row불광역3.6호선(00073)
ValueCountFrequency (%)
등촌중학교 7
 
0.1%
군포공영차고지(00001 6
 
0.1%
은평공영차고지(00001 5
 
0.1%
덕은교.은평차고지앞(00002 5
 
0.1%
하안버스공영차고지(00002 5
 
0.1%
군포보건소(00002 5
 
0.1%
광명차고지(00001 5
 
0.1%
미금초등학교(00007 4
 
0.1%
동해운수(00001 4
 
0.1%
오리초등학교(00006 4
 
0.1%
Other values (7108) 7467
99.3%
2024-04-30T01:28:55.963228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23763
21.1%
( 7793
 
6.9%
) 7793
 
6.9%
1 2838
 
2.5%
. 2408
 
2.1%
2 2025
 
1.8%
3 1817
 
1.6%
4 1707
 
1.5%
5 1614
 
1.4%
6 1534
 
1.4%
Other values (535) 59387
52.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54865
48.7%
Decimal Number 39140
34.7%
Open Punctuation 7793
 
6.9%
Close Punctuation 7793
 
6.9%
Other Punctuation 2423
 
2.2%
Uppercase Letter 631
 
0.6%
Lowercase Letter 23
 
< 0.1%
Space Separator 9
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1507
 
2.7%
역 1490
 
2.7%
교 1366
 
2.5%
지 1184
 
2.2%
파 1098
 
2.0%
아 1085
 
2.0%
구 1080
 
2.0%
트 1034
 
1.9%
학 967
 
1.8%
서 930
 
1.7%
Other values (493) 43124
78.6%
Uppercase Letter
ValueCountFrequency (%)
C 104
16.5%
T 88
13.9%
K 83
13.2%
M 79
12.5%
D 72
11.4%
G 41
 
6.5%
L 36
 
5.7%
S 30
 
4.8%
B 21
 
3.3%
N 15
 
2.4%
Other values (11) 62
9.8%
Decimal Number
ValueCountFrequency (%)
0 23763
60.7%
1 2838
 
7.3%
2 2025
 
5.2%
3 1817
 
4.6%
4 1707
 
4.4%
5 1614
 
4.1%
6 1534
 
3.9%
7 1404
 
3.6%
8 1278
 
3.3%
9 1160
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 2408
99.4%
& 10
 
0.4%
? 3
 
0.1%
, 2
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 21
91.3%
t 1
 
4.3%
k 1
 
4.3%
Open Punctuation
ValueCountFrequency (%)
( 7793
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7793
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57160
50.7%
Hangul 54865
48.7%
Latin 654
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1507
 
2.7%
역 1490
 
2.7%
교 1366
 
2.5%
지 1184
 
2.2%
파 1098
 
2.0%
아 1085
 
2.0%
구 1080
 
2.0%
트 1034
 
1.9%
학 967
 
1.8%
서 930
 
1.7%
Other values (493) 43124
78.6%
Latin
ValueCountFrequency (%)
C 104
15.9%
T 88
13.5%
K 83
12.7%
M 79
12.1%
D 72
11.0%
G 41
 
6.3%
L 36
 
5.5%
S 30
 
4.6%
B 21
 
3.2%
e 21
 
3.2%
Other values (14) 79
12.1%
Common
ValueCountFrequency (%)
0 23763
41.6%
( 7793
 
13.6%
) 7793
 
13.6%
1 2838
 
5.0%
. 2408
 
4.2%
2 2025
 
3.5%
3 1817
 
3.2%
4 1707
 
3.0%
5 1614
 
2.8%
6 1534
 
2.7%
Other values (8) 3868
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57814
51.3%
Hangul 54865
48.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23763
41.1%
( 7793
 
13.5%
) 7793
 
13.5%
1 2838
 
4.9%
. 2408
 
4.2%
2 2025
 
3.5%
3 1817
 
3.1%
4 1707
 
3.0%
5 1614
 
2.8%
6 1534
 
2.7%
Other values (32) 4522
 
7.8%
Hangul
ValueCountFrequency (%)
동 1507
 
2.7%
역 1490
 
2.7%
교 1366
 
2.5%
지 1184
 
2.2%
파 1098
 
2.0%
아 1085
 
2.0%
구 1080
 
2.0%
트 1034
 
1.9%
학 967
 
1.8%
서 930
 
1.7%
Other values (493) 43124
78.6%

승차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct585
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.947389
Minimum0
Maximum1645
Zeros498
Zeros (%)6.6%
Negative0
Negative (%)0.0%
Memory size66.1 KiB
2024-04-30T01:28:56.112195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median51
Q3138.25
95-th percentile351
Maximum1645
Range1645
Interquartile range (IQR)129.25

Descriptive statistics

Standard deviation136.80103
Coefficient of variation (CV)1.3825633
Kurtosis17.48706
Mean98.947389
Median Absolute Deviation (MAD)48
Skewness3.2370089
Sum742897
Variance18714.521
MonotonicityNot monotonic
2024-04-30T01:28:56.245527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 498
 
6.6%
1 297
 
4.0%
2 247
 
3.3%
3 185
 
2.5%
4 164
 
2.2%
5 163
 
2.2%
6 111
 
1.5%
7 98
 
1.3%
9 91
 
1.2%
8 85
 
1.1%
Other values (575) 5569
74.2%
ValueCountFrequency (%)
0 498
6.6%
1 297
4.0%
2 247
3.3%
3 185
 
2.5%
4 164
 
2.2%
5 163
 
2.2%
6 111
 
1.5%
7 98
 
1.3%
8 85
 
1.1%
9 91
 
1.2%
ValueCountFrequency (%)
1645 1
< 0.1%
1507 1
< 0.1%
1417 1
< 0.1%
1406 1
< 0.1%
1350 1
< 0.1%
1346 1
< 0.1%
1327 1
< 0.1%
1191 1
< 0.1%
1176 1
< 0.1%
1144 1
< 0.1%

하차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct561
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.106287
Minimum0
Maximum1783
Zeros349
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size66.1 KiB
2024-04-30T01:28:56.364585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q110
median54
Q3135
95-th percentile337.65
Maximum1783
Range1783
Interquartile range (IQR)125

Descriptive statistics

Standard deviation130.36563
Coefficient of variation (CV)1.3425045
Kurtosis20.331357
Mean97.106287
Median Absolute Deviation (MAD)49
Skewness3.3449242
Sum729074
Variance16995.197
MonotonicityNot monotonic
2024-04-30T01:28:56.475586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 349
 
4.6%
1 285
 
3.8%
2 220
 
2.9%
3 193
 
2.6%
5 162
 
2.2%
4 162
 
2.2%
6 123
 
1.6%
7 115
 
1.5%
8 107
 
1.4%
9 92
 
1.2%
Other values (551) 5700
75.9%
ValueCountFrequency (%)
0 349
4.6%
1 285
3.8%
2 220
2.9%
3 193
2.6%
4 162
2.2%
5 162
2.2%
6 123
 
1.6%
7 115
 
1.5%
8 107
 
1.4%
9 92
 
1.2%
ValueCountFrequency (%)
1783 1
< 0.1%
1612 1
< 0.1%
1509 1
< 0.1%
1451 1
< 0.1%
1412 1
< 0.1%
1359 1
< 0.1%
1118 1
< 0.1%
1106 1
< 0.1%
1100 1
< 0.1%
1049 1
< 0.1%

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.8 KiB
20230204
7508 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20230204
2nd row20230204
3rd row20230204
4th row20230204
5th row20230204

Common Values

ValueCountFrequency (%)
20230204 7508
100.0%

Length

2024-04-30T01:28:56.581797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T01:28:56.662256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20230204 7508
100.0%

Interactions

2024-04-30T01:28:52.825732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:28:52.105157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:28:52.351201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:28:52.900316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:28:52.180747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:28:52.445224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:28:52.981273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:28:52.261753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:28:52.746173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T01:28:56.720528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선명표준버스정류장ID승차총승객수하차총승객수
노선번호1.0001.0000.7050.4720.454
노선명1.0001.0000.7160.4690.451
표준버스정류장ID0.7050.7161.0000.1780.176
승차총승객수0.4720.4690.1781.0000.479
하차총승객수0.4540.4510.1760.4791.000
2024-04-30T01:28:56.832312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준버스정류장ID승차총승객수하차총승객수
표준버스정류장ID1.000-0.119-0.113
승차총승객수-0.1191.0000.592
하차총승객수-0.1130.5921.000

Missing values

2024-04-30T01:28:53.101762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T01:28:53.226225image/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
020230201601601번(개화동~종로4가)11300010714198성산2교(00022)12316420230204
12023020197039703번(신성교통차고지~서울역)11100093512026한전서대문은평.북한산푸르지오(00049)61220230204
22023020197039703번(신성교통차고지~서울역)11100093412023불광역3호선.서울혁신파크(00072)311120230204
32023020197039703번(신성교통차고지~서울역)11100093312024불광역3호선.서울혁신파크(00048)82720230204
42023020197039703번(신성교통차고지~서울역)11100093212021불광역3.6호선(00073)37320230204
52023020197039703번(신성교통차고지~서울역)11100093112022불광역3.6호선(00047)52820230204
62023020197039703번(신성교통차고지~서울역)11100093012019동명여고.천주교불광동성당(00074)15620230204
72023020197039703번(신성교통차고지~서울역)11100092912020동명여고.천주교불광동성당(00046)71820230204
82023020197039703번(신성교통차고지~서울역)11100092812017연신내역.연서시장(00075)981520230204
92023020197039703번(신성교통차고지~서울역)11100092712018연신내역.연서시장(00045)59620230204
사용일자노선번호노선명표준버스정류장ID버스정류장ARS번호역명승차총승객수하차총승객수등록일자
74982023020123122312번(강동공영차고지~중랑공영차고지)12400013925250고덕자이.상일여고(00010)32420230204
74992023020165156515번(양천차고지~삼막사거리)12000006821170산장아파트(00051)337420230204
75002023020165156515번(양천차고지~삼막사거리)12000006921171삼성산주공아파트(00052)8815620230204
75012023020123112311번(중랑차고지~문정동)12300000424004석촌호수.한솔병원(00047)9619820230204
75022023020123122312번(강동공영차고지~중랑공영차고지)12400014025251고덕자이.상일여고(00097)24120230204
75032023020165156515번(양천차고지~삼막사거리)12000007021172산복터널.관악산휴먼시아2단지(00053)1814320230204
75042023020165156515번(양천차고지~삼막사거리)12000007121173산복터널.관악산휴먼시아2단지(00059)1374320230204
75052023020123122312번(강동공영차고지~중랑공영차고지)12400014125252상일1동주민센터.고덕사회체육센터(00011)31220230204
75062023020165156515번(양천차고지~삼막사거리)12000007221174삼성산주공아파트(00060)1054420230204
75072023020165156515번(양천차고지~삼막사거리)12000007321175산장아파트(00061)117820230204