Overview

Dataset statistics

Number of variables9
Number of observations6784
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory510.3 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 492 (7.3%) zerosZeros
하차총승객수 has 349 (5.1%) zerosZeros

Reproduction

Analysis started2024-05-11 06:04:03.779716
Analysis finished2024-05-11 06:04:06.295353
Duration2.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
20230301
6784 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20230301
2nd row20230301
3rd row20230301
4th row20230301
5th row20230301

Common Values

ValueCountFrequency (%)
20230301 6784
100.0%

Length

2024-05-11T15:04:06.420461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:06.568339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20230301 6784
100.0%

노선번호
Text

Distinct83
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
2024-05-11T15:04:06.865048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.6192512
Min length3

Characters and Unicode

Total characters24553
Distinct characters25
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 row360
2nd row9701
3rd row9701
4th row9701
5th row9701
ValueCountFrequency (%)
n26 248
 
3.7%
n37 192
 
2.8%
n62 176
 
2.6%
4318 176
 
2.6%
542 135
 
2.0%
9701 125
 
1.8%
661 125
 
1.8%
441 120
 
1.8%
9403 119
 
1.8%
9408 119
 
1.8%
Other values (73) 5249
77.4%
2024-05-11T15:04:07.371801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 3564
14.5%
5 2979
12.1%
0 2905
11.8%
1 2862
11.7%
6 2478
10.1%
4 2408
9.8%
2 2338
9.5%
3 2065
8.4%
9 990
 
4.0%
N 616
 
2.5%
Other values (15) 1348
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23144
94.3%
Uppercase Letter 830
 
3.4%
Other Letter 567
 
2.3%
Dash Punctuation 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 118
20.8%
동 111
19.6%
서 61
10.8%
대 61
10.8%
문 61
10.8%
남 41
 
7.2%
작 34
 
6.0%
은 34
 
6.0%
평 34
 
6.0%
노 6
 
1.1%
Decimal Number
ValueCountFrequency (%)
7 3564
15.4%
5 2979
12.9%
0 2905
12.6%
1 2862
12.4%
6 2478
10.7%
4 2408
10.4%
2 2338
10.1%
3 2065
8.9%
9 990
 
4.3%
8 555
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
N 616
74.2%
B 144
 
17.3%
A 70
 
8.4%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23156
94.3%
Latin 830
 
3.4%
Hangul 567
 
2.3%

Most frequent character per script

Common
ValueCountFrequency (%)
7 3564
15.4%
5 2979
12.9%
0 2905
12.5%
1 2862
12.4%
6 2478
10.7%
4 2408
10.4%
2 2338
10.1%
3 2065
8.9%
9 990
 
4.3%
8 555
 
2.4%
Hangul
ValueCountFrequency (%)
강 118
20.8%
동 111
19.6%
서 61
10.8%
대 61
10.8%
문 61
10.8%
남 41
 
7.2%
작 34
 
6.0%
은 34
 
6.0%
평 34
 
6.0%
노 6
 
1.1%
Latin
ValueCountFrequency (%)
N 616
74.2%
B 144
 
17.3%
A 70
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23986
97.7%
Hangul 567
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 3564
14.9%
5 2979
12.4%
0 2905
12.1%
1 2862
11.9%
6 2478
10.3%
4 2408
10.0%
2 2338
9.7%
3 2065
8.6%
9 990
 
4.1%
N 616
 
2.6%
Other values (4) 781
 
3.3%
Hangul
ValueCountFrequency (%)
강 118
20.8%
동 111
19.6%
서 61
10.8%
대 61
10.8%
문 61
10.8%
남 41
 
7.2%
작 34
 
6.0%
은 34
 
6.0%
평 34
 
6.0%
노 6
 
1.1%

노선명
Text

Distinct88
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
2024-05-11T15:04:07.712063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length24
Mean length17.723614
Min length13

Characters and Unicode

Total characters120237
Distinct characters188
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 row360번(송파차고지~여의도)
2nd row9701번(가좌동~서울역)
3rd row9701번(가좌동~서울역)
4th row9701번(가좌동~서울역)
5th row9701번(가좌동~서울역)
ValueCountFrequency (%)
542번(군포버스공영차고지~신사역 135
 
1.9%
n26번(강서공영차고지~중랑공영차고지 126
 
1.8%
9701번(가좌동~서울역 125
 
1.8%
661번(부천상동~영등포역,신세계백화점 125
 
1.8%
n26번(중랑공영차고지~강서공영차고지 122
 
1.7%
441번(월암공영차고지~신사사거리 120
 
1.7%
9403번(구미동차고지~중곡역 119
 
1.7%
9408번(구미동차고지~고속터미널 119
 
1.7%
541번(군포공영차고지~강남역 119
 
1.7%
9703번(신성교통차고지~서울역 118
 
1.7%
Other values (81) 5827
82.6%
2024-05-11T15:04:08.287045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 6848
 
5.7%
) 6848
 
5.7%
~ 6784
 
5.6%
번 6356
 
5.3%
동 4613
 
3.8%
지 4333
 
3.6%
고 4326
 
3.6%
차 3998
 
3.3%
7 3628
 
3.0%
영 3197
 
2.7%
Other values (178) 69306
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74362
61.8%
Decimal Number 23397
 
19.5%
Open Punctuation 6848
 
5.7%
Close Punctuation 6848
 
5.7%
Math Symbol 6784
 
5.6%
Uppercase Letter 882
 
0.7%
Other Punctuation 833
 
0.7%
Space Separator 271
 
0.2%
Dash Punctuation 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 6356
 
8.5%
동 4613
 
6.2%
지 4333
 
5.8%
고 4326
 
5.8%
차 3998
 
5.4%
영 3197
 
4.3%
공 2984
 
4.0%
역 2925
 
3.9%
서 1721
 
2.3%
대 1658
 
2.2%
Other values (156) 38251
51.4%
Decimal Number
ValueCountFrequency (%)
7 3628
15.5%
1 3010
12.9%
5 2979
12.7%
0 2905
12.4%
6 2478
10.6%
4 2449
10.5%
2 2338
10.0%
3 2065
8.8%
9 990
 
4.2%
8 555
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
N 630
71.4%
B 144
 
16.3%
A 82
 
9.3%
C 14
 
1.6%
K 12
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 437
52.5%
. 396
47.5%
Open Punctuation
ValueCountFrequency (%)
( 6848
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6848
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6784
100.0%
Space Separator
ValueCountFrequency (%)
271
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74362
61.8%
Common 44993
37.4%
Latin 882
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 6356
 
8.5%
동 4613
 
6.2%
지 4333
 
5.8%
고 4326
 
5.8%
차 3998
 
5.4%
영 3197
 
4.3%
공 2984
 
4.0%
역 2925
 
3.9%
서 1721
 
2.3%
대 1658
 
2.2%
Other values (156) 38251
51.4%
Common
ValueCountFrequency (%)
( 6848
15.2%
) 6848
15.2%
~ 6784
15.1%
7 3628
8.1%
1 3010
6.7%
5 2979
6.6%
0 2905
6.5%
6 2478
 
5.5%
4 2449
 
5.4%
2 2338
 
5.2%
Other values (7) 4726
10.5%
Latin
ValueCountFrequency (%)
N 630
71.4%
B 144
 
16.3%
A 82
 
9.3%
C 14
 
1.6%
K 12
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74362
61.8%
ASCII 45875
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 6848
14.9%
) 6848
14.9%
~ 6784
14.8%
7 3628
7.9%
1 3010
6.6%
5 2979
6.5%
0 2905
6.3%
6 2478
 
5.4%
4 2449
 
5.3%
2 2338
 
5.1%
Other values (12) 5608
12.2%
Hangul
ValueCountFrequency (%)
번 6356
 
8.5%
동 4613
 
6.2%
지 4333
 
5.8%
고 4326
 
5.8%
차 3998
 
5.4%
영 3197
 
4.3%
공 2984
 
4.0%
역 2925
 
3.9%
서 1721
 
2.3%
대 1658
 
2.2%
Other values (156) 38251
51.4%

표준버스정류장ID
Real number (ℝ)

Distinct3731
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5266061 × 108
Minimum1 × 108
Maximum9.998 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size59.8 KiB
2024-05-11T15:04:08.486877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1 × 108
5-th percentile1.02 × 108
Q11.1200041 × 108
median1.2000044 × 108
Q32.1000036 × 108
95-th percentile2.2200158 × 108
Maximum9.998 × 108
Range8.998 × 108
Interquartile range (IQR)97999950

Descriptive statistics

Standard deviation67909270
Coefficient of variation (CV)0.44483819
Kurtosis71.456092
Mean1.5266061 × 108
Median Absolute Deviation (MAD)10000233
Skewness6.1140764
Sum1.0356496 × 1012
Variance4.611669 × 1015
MonotonicityNot monotonic
2024-05-11T15:04:08.690795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
121000010 10
 
0.1%
121000009 10
 
0.1%
121000007 10
 
0.1%
121000006 10
 
0.1%
121000005 10
 
0.1%
121000013 10
 
0.1%
121000014 10
 
0.1%
121000011 9
 
0.1%
121000012 9
 
0.1%
117000004 9
 
0.1%
Other values (3721) 6687
98.6%
ValueCountFrequency (%)
100000001 2
< 0.1%
100000004 2
< 0.1%
100000006 1
< 0.1%
100000007 1
< 0.1%
100000008 1
< 0.1%
100000015 1
< 0.1%
100000016 1
< 0.1%
100000017 1
< 0.1%
100000018 1
< 0.1%
100000019 1
< 0.1%
ValueCountFrequency (%)
999800005 2
< 0.1%
999800003 1
 
< 0.1%
999033574 4
0.1%
998502964 1
 
< 0.1%
998502907 1
 
< 0.1%
998501980 2
< 0.1%
998501977 1
 
< 0.1%
998501974 1
 
< 0.1%
998501932 1
 
< 0.1%
998003073 1
 
< 0.1%

버스정류장ARS번호
Text

Distinct3692
Distinct (%)54.4%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
2024-05-11T15:04:09.128882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.9876179
Min length1

Characters and Unicode

Total characters33836
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

Unique2115 ?
Unique (%)31.2%

Sample

1st row23280
2nd row13032
3rd row13031
4th row12381
5th row12154
ValueCountFrequency (%)
21
 
0.3%
22007 10
 
0.1%
22009 10
 
0.1%
22010 10
 
0.1%
22013 10
 
0.1%
22014 10
 
0.1%
22005 10
 
0.1%
22006 10
 
0.1%
18003 9
 
0.1%
13035 9
 
0.1%
Other values (3682) 6675
98.4%
2024-05-11T15:04:09.692582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6769
20.0%
0 5451
16.1%
2 4725
14.0%
3 3918
11.6%
4 2798
8.3%
6 2514
 
7.4%
5 2388
 
7.1%
7 1989
 
5.9%
8 1871
 
5.5%
9 1392
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33815
99.9%
Math Symbol 21
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6769
20.0%
0 5451
16.1%
2 4725
14.0%
3 3918
11.6%
4 2798
8.3%
6 2514
 
7.4%
5 2388
 
7.1%
7 1989
 
5.9%
8 1871
 
5.5%
9 1392
 
4.1%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33836
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6769
20.0%
0 5451
16.1%
2 4725
14.0%
3 3918
11.6%
4 2798
8.3%
6 2514
 
7.4%
5 2388
 
7.1%
7 1989
 
5.9%
8 1871
 
5.5%
9 1392
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33836
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6769
20.0%
0 5451
16.1%
2 4725
14.0%
3 3918
11.6%
4 2798
8.3%
6 2514
 
7.4%
5 2388
 
7.1%
7 1989
 
5.9%
8 1871
 
5.5%
9 1392
 
4.1%

역명
Text

Distinct6430
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
2024-05-11T15:04:09.992349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length14.994104
Min length9

Characters and Unicode

Total characters101720
Distinct characters538
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

Unique6152 ?
Unique (%)90.7%

Sample

1st row아가방빌딩.하나은행(00020)
2nd row무악재역(00070)
3rd row무악재역(00058)
4th row녹번역(00054)
5th row녹번초등학교.은평세무서(00052)
ValueCountFrequency (%)
하안버스공영차고지(00002 7
 
0.1%
광명차고지(00001 7
 
0.1%
등촌중학교 6
 
0.1%
군포보건소(00002 5
 
0.1%
덕은교.은평차고지앞(00002 5
 
0.1%
군포공영차고지(00001 5
 
0.1%
은평공영차고지(00001 5
 
0.1%
수색교(00003 4
 
0.1%
lg아파트.무지개마을사거리.신한아파트(00003 4
 
0.1%
대우.롯데아파트상가(00008 4
 
0.1%
Other values (6421) 6738
99.2%
2024-05-11T15:04:10.457774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21475
21.1%
( 7049
 
6.9%
) 7049
 
6.9%
1 2573
 
2.5%
. 2158
 
2.1%
2 1804
 
1.8%
3 1659
 
1.6%
4 1547
 
1.5%
5 1473
 
1.4%
6 1403
 
1.4%
Other values (528) 53530
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49441
48.6%
Decimal Number 35430
34.8%
Open Punctuation 7049
 
6.9%
Close Punctuation 7049
 
6.9%
Other Punctuation 2166
 
2.1%
Uppercase Letter 559
 
0.5%
Lowercase Letter 18
 
< 0.1%
Space Separator 6
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 1352
 
2.7%
동 1328
 
2.7%
교 1254
 
2.5%
지 1069
 
2.2%
구 983
 
2.0%
파 979
 
2.0%
아 933
 
1.9%
트 919
 
1.9%
학 863
 
1.7%
대 799
 
1.6%
Other values (486) 38962
78.8%
Uppercase Letter
ValueCountFrequency (%)
C 92
16.5%
M 72
12.9%
K 70
12.5%
D 68
12.2%
T 67
12.0%
G 35
 
6.3%
L 35
 
6.3%
S 23
 
4.1%
B 21
 
3.8%
A 14
 
2.5%
Other values (11) 62
11.1%
Decimal Number
ValueCountFrequency (%)
0 21475
60.6%
1 2573
 
7.3%
2 1804
 
5.1%
3 1659
 
4.7%
4 1547
 
4.4%
5 1473
 
4.2%
6 1403
 
4.0%
7 1294
 
3.7%
8 1160
 
3.3%
9 1042
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 2158
99.6%
& 5
 
0.2%
, 2
 
0.1%
? 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 16
88.9%
k 1
 
5.6%
t 1
 
5.6%
Open Punctuation
ValueCountFrequency (%)
( 7049
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7049
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51702
50.8%
Hangul 49441
48.6%
Latin 577
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 1352
 
2.7%
동 1328
 
2.7%
교 1254
 
2.5%
지 1069
 
2.2%
구 983
 
2.0%
파 979
 
2.0%
아 933
 
1.9%
트 919
 
1.9%
학 863
 
1.7%
대 799
 
1.6%
Other values (486) 38962
78.8%
Latin
ValueCountFrequency (%)
C 92
15.9%
M 72
12.5%
K 70
12.1%
D 68
11.8%
T 67
11.6%
G 35
 
6.1%
L 35
 
6.1%
S 23
 
4.0%
B 21
 
3.6%
e 16
 
2.8%
Other values (14) 78
13.5%
Common
ValueCountFrequency (%)
0 21475
41.5%
( 7049
 
13.6%
) 7049
 
13.6%
1 2573
 
5.0%
. 2158
 
4.2%
2 1804
 
3.5%
3 1659
 
3.2%
4 1547
 
3.0%
5 1473
 
2.8%
6 1403
 
2.7%
Other values (8) 3512
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52279
51.4%
Hangul 49441
48.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21475
41.1%
( 7049
 
13.5%
) 7049
 
13.5%
1 2573
 
4.9%
. 2158
 
4.1%
2 1804
 
3.5%
3 1659
 
3.2%
4 1547
 
3.0%
5 1473
 
2.8%
6 1403
 
2.7%
Other values (32) 4089
 
7.8%
Hangul
ValueCountFrequency (%)
역 1352
 
2.7%
동 1328
 
2.7%
교 1254
 
2.5%
지 1069
 
2.2%
구 983
 
2.0%
파 979
 
2.0%
아 933
 
1.9%
트 919
 
1.9%
학 863
 
1.7%
대 799
 
1.6%
Other values (486) 38962
78.8%

승차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct426
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.888709
Minimum0
Maximum1137
Zeros492
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size59.8 KiB
2024-05-11T15:04:10.628475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median30
Q381
95-th percentile221
Maximum1137
Range1137
Interquartile range (IQR)74

Descriptive statistics

Standard deviation90.872212
Coefficient of variation (CV)1.4683165
Kurtosis21.994309
Mean61.888709
Median Absolute Deviation (MAD)27
Skewness3.6948738
Sum419853
Variance8257.759
MonotonicityNot monotonic
2024-05-11T15:04:10.797007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 492
 
7.3%
1 340
 
5.0%
2 240
 
3.5%
3 176
 
2.6%
5 156
 
2.3%
4 145
 
2.1%
6 128
 
1.9%
7 110
 
1.6%
9 102
 
1.5%
8 101
 
1.5%
Other values (416) 4794
70.7%
ValueCountFrequency (%)
0 492
7.3%
1 340
5.0%
2 240
3.5%
3 176
 
2.6%
4 145
 
2.1%
5 156
 
2.3%
6 128
 
1.9%
7 110
 
1.6%
8 101
 
1.5%
9 102
 
1.5%
ValueCountFrequency (%)
1137 1
< 0.1%
1131 1
< 0.1%
1010 1
< 0.1%
964 1
< 0.1%
877 1
< 0.1%
873 1
< 0.1%
872 1
< 0.1%
849 1
< 0.1%
793 1
< 0.1%
772 1
< 0.1%

하차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct405
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.780955
Minimum0
Maximum1272
Zeros349
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size59.8 KiB
2024-05-11T15:04:10.957314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median32
Q381
95-th percentile209
Maximum1272
Range1272
Interquartile range (IQR)73

Descriptive statistics

Standard deviation86.677646
Coefficient of variation (CV)1.4260659
Kurtosis26.687009
Mean60.780955
Median Absolute Deviation (MAD)28
Skewness3.9274598
Sum412338
Variance7513.0144
MonotonicityNot monotonic
2024-05-11T15:04:11.176966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 349
 
5.1%
1 269
 
4.0%
2 259
 
3.8%
3 190
 
2.8%
4 177
 
2.6%
5 160
 
2.4%
6 145
 
2.1%
9 119
 
1.8%
7 106
 
1.6%
8 104
 
1.5%
Other values (395) 4906
72.3%
ValueCountFrequency (%)
0 349
5.1%
1 269
4.0%
2 259
3.8%
3 190
2.8%
4 177
2.6%
5 160
2.4%
6 145
2.1%
7 106
 
1.6%
8 104
 
1.5%
9 119
 
1.8%
ValueCountFrequency (%)
1272 1
< 0.1%
1159 1
< 0.1%
997 1
< 0.1%
872 1
< 0.1%
851 1
< 0.1%
820 1
< 0.1%
800 1
< 0.1%
790 1
< 0.1%
771 1
< 0.1%
766 1
< 0.1%

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
20230304
6784 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20230304
2nd row20230304
3rd row20230304
4th row20230304
5th row20230304

Common Values

ValueCountFrequency (%)
20230304 6784
100.0%

Length

2024-05-11T15:04:11.327127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:04:11.453379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20230304 6784
100.0%

Interactions

2024-05-11T15:04:05.525364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:04:04.755548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:04:05.141835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:04:05.695261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:04:04.876430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:04:05.258886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:04:05.828467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:04:05.005294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:04:05.376405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:04:11.525115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선명표준버스정류장ID승차총승객수하차총승객수
노선번호1.0001.0000.7250.4300.431
노선명1.0001.0000.7260.4300.430
표준버스정류장ID0.7250.7261.0000.1500.200
승차총승객수0.4300.4300.1501.0000.407
하차총승객수0.4310.4300.2000.4071.000
2024-05-11T15:04:11.646746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준버스정류장ID승차총승객수하차총승객수
표준버스정류장ID1.000-0.133-0.125
승차총승객수-0.1331.0000.553
하차총승객수-0.1250.5531.000

Missing values

2024-05-11T15:04:06.011942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:04:06.200975image/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
020230301360360번(송파차고지~여의도)12200017723280아가방빌딩.하나은행(00020)2859620230304
12023030197019701번(가좌동~서울역)11200040013032무악재역(00070)7420230304
22023030197019701번(가좌동~서울역)11200039813031무악재역(00058)2620230304
32023030197019701번(가좌동~서울역)11100029112381녹번역(00054)92720230304
42023030197019701번(가좌동~서울역)11100006612154녹번초등학교.은평세무서(00052)252620230304
520230301360360번(송파차고지~여의도)12200018023283역삼역(00021)2297320230304
62023030197019701번(가좌동~서울역)11100006412152하나은행역촌동지점(00050)242720230304
72023030197019701번(가좌동~서울역)11100006312151구산역2번출구.예일여고(00049)427220230304
82023030197019701번(가좌동~서울역)11100006212150역촌중앙시장(00048)174620230304
92023030197019701번(가좌동~서울역)11100006112149구산사거리(00047)132120230304
사용일자노선번호노선명표준버스정류장ID버스정류장ARS번호역명승차총승객수하차총승객수등록일자
677420230301N62N62번(면목동차고지~양천공영차고지)11300050614097홍대입구역(가상)(00051)0220230304
677520230301노원14노원14(청백1단지아파트~세그루학원)10800006709155북부수도사업소(00017)11215320230304
677620230301노원14노원14(청백1단지아파트~세그루학원)10800008909177신창교(00016)764420230304
677720230301N62N62번(면목동차고지~양천공영차고지)11300050814098합정역(가상)(00111)0120230304
677820230301노원14노원14(청백1단지아파트~세그루학원)10800037909903우이3교(00050)86020230304
677920230301노원14노원14(청백1단지아파트~세그루학원)10900012610211쌍문동성원아파트(00035)8119620230304
678020230301105105번(상계동~서울역)10100010402208퇴계로5가(00039)307520230304
678120230301146146번(상계주공7단지~강남역)11000017111271상계주공10단지상가(00003)44220230304
678220230301461461번(장지공영차고지~여의도)11800006819153샛강역1번출구.여의도자이(00064)2338620230304
67832023030120122012번(신내공영차고지~동대문역사문화공원)10600018007275신내동성3차아파트(00100)215920230304