Overview

Dataset statistics

Number of variables9
Number of observations6769
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory509.1 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 462 (6.8%) zerosZeros
하차총승객수 has 291 (4.3%) zerosZeros

Reproduction

Analysis started2024-05-04 04:35:50.307118
Analysis finished2024-05-04 04:35:57.720625
Duration7.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.0 KiB
20230501
6769 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20230501
2nd row20230501
3rd row20230501
4th row20230501
5th row20230501

Common Values

ValueCountFrequency (%)
20230501 6769
100.0%

Length

2024-05-04T04:35:57.935425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:35:58.246658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20230501 6769
100.0%

노선번호
Text

Distinct83
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size53.0 KiB
2024-05-04T04:35:58.858387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.6012705
Min length3

Characters and Unicode

Total characters24377
Distinct characters17
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 row100
2nd row9408
3rd row9408
4th row9408
5th row9408
ValueCountFrequency (%)
n26 241
 
3.6%
n15 205
 
3.0%
n37 195
 
2.9%
542 138
 
2.0%
9701 127
 
1.9%
661 125
 
1.8%
441 124
 
1.8%
541 123
 
1.8%
9403 121
 
1.8%
5623 120
 
1.8%
Other values (73) 5250
77.6%
2024-05-04T04:36:00.069271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 3768
15.5%
1 3150
12.9%
5 3134
12.9%
0 2660
10.9%
6 2512
10.3%
2 2318
9.5%
4 2272
9.3%
3 2163
8.9%
9 969
 
4.0%
N 641
 
2.6%
Other values (7) 790
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23377
95.9%
Uppercase Letter 791
 
3.2%
Other Letter 194
 
0.8%
Dash Punctuation 15
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 3768
16.1%
1 3150
13.5%
5 3134
13.4%
0 2660
11.4%
6 2512
10.7%
2 2318
9.9%
4 2272
9.7%
3 2163
9.3%
9 969
 
4.1%
8 431
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
N 641
81.0%
B 148
 
18.7%
A 2
 
0.3%
Other Letter
ValueCountFrequency (%)
동 97
50.0%
강 77
39.7%
성 20
 
10.3%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23392
96.0%
Latin 791
 
3.2%
Hangul 194
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
7 3768
16.1%
1 3150
13.5%
5 3134
13.4%
0 2660
11.4%
6 2512
10.7%
2 2318
9.9%
4 2272
9.7%
3 2163
9.2%
9 969
 
4.1%
8 431
 
1.8%
Latin
ValueCountFrequency (%)
N 641
81.0%
B 148
 
18.7%
A 2
 
0.3%
Hangul
ValueCountFrequency (%)
동 97
50.0%
강 77
39.7%
성 20
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24183
99.2%
Hangul 194
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 3768
15.6%
1 3150
13.0%
5 3134
13.0%
0 2660
11.0%
6 2512
10.4%
2 2318
9.6%
4 2272
9.4%
3 2163
8.9%
9 969
 
4.0%
N 641
 
2.7%
Other values (4) 596
 
2.5%
Hangul
ValueCountFrequency (%)
동 97
50.0%
강 77
39.7%
성 20
 
10.3%

노선명
Text

Distinct86
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size53.0 KiB
2024-05-04T04:36:00.794490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length21
Mean length17.362092
Min length12

Characters and Unicode

Total characters117524
Distinct characters176
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 row100번(하계동~용산구청)
2nd row9408번(구미동차고지~고속터미널)
3rd row9408번(구미동차고지~고속터미널)
4th row9408번(구미동차고지~고속터미널)
5th row9408번(구미동차고지~고속터미널)
ValueCountFrequency (%)
n15번(우이동성원아파트~남태령역 140
 
2.0%
542번(군포버스공영차고지~신사역 138
 
2.0%
9701번(가좌동~서울역 127
 
1.8%
661번(부천상동~영등포역,신세계백화점 125
 
1.8%
441번(월암공영차고지~신사사거리 124
 
1.8%
541번(군포공영차고지~강남역 123
 
1.7%
n26번(강서공영차고지~중랑공영차고지 121
 
1.7%
9403번(구미동차고지~중곡역 121
 
1.7%
공영차고지~여의도 120
 
1.7%
n26번(중랑공영차고지~강서공영차고지 120
 
1.7%
Other values (79) 5785
82.1%
2024-05-04T04:36:02.247212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 6836
 
5.8%
) 6836
 
5.8%
~ 6769
 
5.8%
번 6491
 
5.5%
동 4354
 
3.7%
고 4288
 
3.6%
지 4200
 
3.6%
차 3979
 
3.4%
7 3768
 
3.2%
1 3222
 
2.7%
Other values (166) 66781
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72094
61.3%
Decimal Number 23449
 
20.0%
Open Punctuation 6836
 
5.8%
Close Punctuation 6836
 
5.8%
Math Symbol 6769
 
5.8%
Uppercase Letter 821
 
0.7%
Other Punctuation 429
 
0.4%
Space Separator 275
 
0.2%
Dash Punctuation 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 6491
 
9.0%
동 4354
 
6.0%
고 4288
 
5.9%
지 4200
 
5.8%
차 3979
 
5.5%
영 2935
 
4.1%
역 2869
 
4.0%
공 2643
 
3.7%
대 1393
 
1.9%
서 1255
 
1.7%
Other values (145) 37687
52.3%
Decimal Number
ValueCountFrequency (%)
7 3768
16.1%
1 3222
13.7%
5 3134
13.4%
0 2660
11.3%
6 2512
10.7%
2 2318
9.9%
4 2272
9.7%
3 2163
9.2%
9 969
 
4.1%
8 431
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
N 641
78.1%
B 148
 
18.0%
A 17
 
2.1%
K 15
 
1.8%
Other Punctuation
ValueCountFrequency (%)
, 298
69.5%
. 131
30.5%
Open Punctuation
ValueCountFrequency (%)
( 6836
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6836
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6769
100.0%
Space Separator
ValueCountFrequency (%)
275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72094
61.3%
Common 44609
38.0%
Latin 821
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 6491
 
9.0%
동 4354
 
6.0%
고 4288
 
5.9%
지 4200
 
5.8%
차 3979
 
5.5%
영 2935
 
4.1%
역 2869
 
4.0%
공 2643
 
3.7%
대 1393
 
1.9%
서 1255
 
1.7%
Other values (145) 37687
52.3%
Common
ValueCountFrequency (%)
( 6836
15.3%
) 6836
15.3%
~ 6769
15.2%
7 3768
8.4%
1 3222
7.2%
5 3134
7.0%
0 2660
 
6.0%
6 2512
 
5.6%
2 2318
 
5.2%
4 2272
 
5.1%
Other values (7) 4282
9.6%
Latin
ValueCountFrequency (%)
N 641
78.1%
B 148
 
18.0%
A 17
 
2.1%
K 15
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72094
61.3%
ASCII 45430
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 6836
15.0%
) 6836
15.0%
~ 6769
14.9%
7 3768
8.3%
1 3222
7.1%
5 3134
6.9%
0 2660
 
5.9%
6 2512
 
5.5%
2 2318
 
5.1%
4 2272
 
5.0%
Other values (11) 5103
11.2%
Hangul
ValueCountFrequency (%)
번 6491
 
9.0%
동 4354
 
6.0%
고 4288
 
5.9%
지 4200
 
5.8%
차 3979
 
5.5%
영 2935
 
4.1%
역 2869
 
4.0%
공 2643
 
3.7%
대 1393
 
1.9%
서 1255
 
1.7%
Other values (145) 37687
52.3%

표준버스정류장ID
Real number (ℝ)

Distinct3665
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5100625 × 108
Minimum1 × 108
Maximum9.998 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size59.6 KiB
2024-05-04T04:36:02.940433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1 × 108
5-th percentile1.010003 × 108
Q11.1200005 × 108
median1.2 × 108
Q32.0900026 × 108
95-th percentile2.2200164 × 108
Maximum9.998 × 108
Range8.998 × 108
Interquartile range (IQR)97000205

Descriptive statistics

Standard deviation65607215
Coefficient of variation (CV)0.43446688
Kurtosis70.852401
Mean1.5100625 × 108
Median Absolute Deviation (MAD)12999926
Skewness5.8974988
Sum1.0221613 × 1012
Variance4.3043066 × 1015
MonotonicityNot monotonic
2024-05-04T04:36:03.534966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
121000007 12
 
0.2%
121000005 11
 
0.2%
121000009 11
 
0.2%
121000008 11
 
0.2%
121000006 11
 
0.2%
121000014 10
 
0.1%
121000013 10
 
0.1%
121000010 10
 
0.1%
112000005 10
 
0.1%
121000003 10
 
0.1%
Other values (3655) 6663
98.4%
ValueCountFrequency (%)
100000001 3
< 0.1%
100000002 1
 
< 0.1%
100000003 1
 
< 0.1%
100000004 3
< 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%
ValueCountFrequency (%)
999800005 2
< 0.1%
999800004 1
 
< 0.1%
999033574 4
0.1%
998502062 1
 
< 0.1%
998501980 1
 
< 0.1%
998501976 1
 
< 0.1%
998501932 1
 
< 0.1%
998501931 1
 
< 0.1%
998001700 1
 
< 0.1%
990070103 1
 
< 0.1%

버스정류장ARS번호
Text

Distinct3628
Distinct (%)53.6%
Missing0
Missing (%)0.0%
Memory size53.0 KiB
2024-05-04T04:36:04.575408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.9893633
Min length1

Characters and Unicode

Total characters33773
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

Unique2101 ?
Unique (%)31.0%

Sample

1st row01002
2nd row06225
3rd row49602
4th row06168
5th row48637
ValueCountFrequency (%)
18
 
0.3%
22007 12
 
0.2%
22009 11
 
0.2%
22006 11
 
0.2%
22005 11
 
0.2%
22008 11
 
0.2%
12006 10
 
0.1%
22010 10
 
0.1%
22013 10
 
0.1%
22014 10
 
0.1%
Other values (3618) 6655
98.3%
2024-05-04T04:36:06.278998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6813
20.2%
0 6039
17.9%
2 4607
13.6%
3 3583
10.6%
4 2643
 
7.8%
6 2573
 
7.6%
5 2324
 
6.9%
7 2042
 
6.0%
8 1797
 
5.3%
9 1334
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33755
99.9%
Math Symbol 18
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6813
20.2%
0 6039
17.9%
2 4607
13.6%
3 3583
10.6%
4 2643
 
7.8%
6 2573
 
7.6%
5 2324
 
6.9%
7 2042
 
6.0%
8 1797
 
5.3%
9 1334
 
4.0%
Math Symbol
ValueCountFrequency (%)
~ 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33773
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6813
20.2%
0 6039
17.9%
2 4607
13.6%
3 3583
10.6%
4 2643
 
7.8%
6 2573
 
7.6%
5 2324
 
6.9%
7 2042
 
6.0%
8 1797
 
5.3%
9 1334
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33773
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6813
20.2%
0 6039
17.9%
2 4607
13.6%
3 3583
10.6%
4 2643
 
7.8%
6 2573
 
7.6%
5 2324
 
6.9%
7 2042
 
6.0%
8 1797
 
5.3%
9 1334
 
3.9%

역명
Text

Distinct6426
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size53.0 KiB
2024-05-04T04:36:07.087443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length15.040479
Min length9

Characters and Unicode

Total characters101809
Distinct characters535
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

Unique6158 ?
Unique (%)91.0%

Sample

1st row창경궁.서울대학교병원(00031)
2nd row성남시청후면(00026)
3rd row성남시청전면(00097)
4th row성남시청후문앞(00096)
5th row공군부대제2정문.면회실(00088)
ValueCountFrequency (%)
군포공영차고지(00001 6
 
0.1%
등촌중학교 6
 
0.1%
군포보건소(00002 5
 
0.1%
하안버스공영차고지(00002 5
 
0.1%
은평공영차고지(00001 5
 
0.1%
덕은교.은평차고지앞(00002 5
 
0.1%
광명차고지(00001 5
 
0.1%
오리초등학교(00006 4
 
0.1%
헬스케어혁신파크.(구)가스공사(00010 4
 
0.1%
미금초등학교(00007 4
 
0.1%
Other values (6419) 6728
99.3%
2024-05-04T04:36:08.340355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21424
 
21.0%
( 7040
 
6.9%
) 7040
 
6.9%
1 2533
 
2.5%
. 2212
 
2.2%
2 1806
 
1.8%
3 1626
 
1.6%
4 1533
 
1.5%
5 1469
 
1.4%
6 1407
 
1.4%
Other values (525) 53719
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49551
48.7%
Decimal Number 35303
34.7%
Open Punctuation 7040
 
6.9%
Close Punctuation 7040
 
6.9%
Other Punctuation 2227
 
2.2%
Uppercase Letter 615
 
0.6%
Lowercase Letter 23
 
< 0.1%
Space Separator 8
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 1333
 
2.7%
동 1328
 
2.7%
교 1220
 
2.5%
지 1068
 
2.2%
구 977
 
2.0%
파 977
 
2.0%
아 916
 
1.8%
트 905
 
1.8%
학 862
 
1.7%
서 824
 
1.7%
Other values (483) 39141
79.0%
Uppercase Letter
ValueCountFrequency (%)
C 103
16.7%
K 85
13.8%
T 83
13.5%
M 81
13.2%
D 76
12.4%
G 41
 
6.7%
L 35
 
5.7%
S 25
 
4.1%
B 17
 
2.8%
A 13
 
2.1%
Other values (11) 56
9.1%
Decimal Number
ValueCountFrequency (%)
0 21424
60.7%
1 2533
 
7.2%
2 1806
 
5.1%
3 1626
 
4.6%
4 1533
 
4.3%
5 1469
 
4.2%
6 1407
 
4.0%
7 1296
 
3.7%
8 1145
 
3.2%
9 1064
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 2212
99.3%
& 11
 
0.5%
, 2
 
0.1%
? 2
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 21
91.3%
k 1
 
4.3%
t 1
 
4.3%
Open Punctuation
ValueCountFrequency (%)
( 7040
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7040
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51620
50.7%
Hangul 49551
48.7%
Latin 638
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 1333
 
2.7%
동 1328
 
2.7%
교 1220
 
2.5%
지 1068
 
2.2%
구 977
 
2.0%
파 977
 
2.0%
아 916
 
1.8%
트 905
 
1.8%
학 862
 
1.7%
서 824
 
1.7%
Other values (483) 39141
79.0%
Latin
ValueCountFrequency (%)
C 103
16.1%
K 85
13.3%
T 83
13.0%
M 81
12.7%
D 76
11.9%
G 41
 
6.4%
L 35
 
5.5%
S 25
 
3.9%
e 21
 
3.3%
B 17
 
2.7%
Other values (14) 71
11.1%
Common
ValueCountFrequency (%)
0 21424
41.5%
( 7040
 
13.6%
) 7040
 
13.6%
1 2533
 
4.9%
. 2212
 
4.3%
2 1806
 
3.5%
3 1626
 
3.1%
4 1533
 
3.0%
5 1469
 
2.8%
6 1407
 
2.7%
Other values (8) 3530
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52258
51.3%
Hangul 49551
48.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21424
41.0%
( 7040
 
13.5%
) 7040
 
13.5%
1 2533
 
4.8%
. 2212
 
4.2%
2 1806
 
3.5%
3 1626
 
3.1%
4 1533
 
2.9%
5 1469
 
2.8%
6 1407
 
2.7%
Other values (32) 4168
 
8.0%
Hangul
ValueCountFrequency (%)
역 1333
 
2.7%
동 1328
 
2.7%
교 1220
 
2.5%
지 1068
 
2.2%
구 977
 
2.0%
파 977
 
2.0%
아 916
 
1.8%
트 905
 
1.8%
학 862
 
1.7%
서 824
 
1.7%
Other values (483) 39141
79.0%

승차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct492
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79.85404
Minimum0
Maximum1845
Zeros462
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size59.6 KiB
2024-05-04T04:36:08.957963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median43
Q3108
95-th percentile288
Maximum1845
Range1845
Interquartile range (IQR)100

Descriptive statistics

Standard deviation111.60563
Coefficient of variation (CV)1.3976203
Kurtosis24.204001
Mean79.85404
Median Absolute Deviation (MAD)39
Skewness3.5599022
Sum540532
Variance12455.817
MonotonicityNot monotonic
2024-05-04T04:36:09.507478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 462
 
6.8%
1 284
 
4.2%
2 213
 
3.1%
3 187
 
2.8%
4 166
 
2.5%
5 122
 
1.8%
6 110
 
1.6%
7 97
 
1.4%
8 86
 
1.3%
11 77
 
1.1%
Other values (482) 4965
73.3%
ValueCountFrequency (%)
0 462
6.8%
1 284
4.2%
2 213
3.1%
3 187
2.8%
4 166
 
2.5%
5 122
 
1.8%
6 110
 
1.6%
7 97
 
1.4%
8 86
 
1.3%
9 65
 
1.0%
ValueCountFrequency (%)
1845 1
< 0.1%
1468 1
< 0.1%
1148 1
< 0.1%
1043 1
< 0.1%
1026 1
< 0.1%
1018 1
< 0.1%
1013 1
< 0.1%
939 1
< 0.1%
867 1
< 0.1%
843 1
< 0.1%

하차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct475
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.264884
Minimum0
Maximum1915
Zeros291
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size59.6 KiB
2024-05-04T04:36:10.114583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q19
median44
Q3105
95-th percentile270
Maximum1915
Range1915
Interquartile range (IQR)96

Descriptive statistics

Standard deviation107.43237
Coefficient of variation (CV)1.3726766
Kurtosis38.653849
Mean78.264884
Median Absolute Deviation (MAD)39
Skewness4.225366
Sum529775
Variance11541.715
MonotonicityNot monotonic
2024-05-04T04:36:10.686495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 291
 
4.3%
1 275
 
4.1%
2 243
 
3.6%
3 214
 
3.2%
4 144
 
2.1%
5 134
 
2.0%
7 119
 
1.8%
6 112
 
1.7%
8 106
 
1.6%
10 79
 
1.2%
Other values (465) 5052
74.6%
ValueCountFrequency (%)
0 291
4.3%
1 275
4.1%
2 243
3.6%
3 214
3.2%
4 144
2.1%
5 134
2.0%
6 112
 
1.7%
7 119
1.8%
8 106
 
1.6%
9 72
 
1.1%
ValueCountFrequency (%)
1915 1
< 0.1%
1903 1
< 0.1%
1251 1
< 0.1%
1103 1
< 0.1%
1020 1
< 0.1%
1017 2
< 0.1%
1007 1
< 0.1%
1000 1
< 0.1%
928 1
< 0.1%
913 1
< 0.1%

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.0 KiB
20230504
6769 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20230504
2nd row20230504
3rd row20230504
4th row20230504
5th row20230504

Common Values

ValueCountFrequency (%)
20230504 6769
100.0%

Length

2024-05-04T04:36:11.275828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:36:11.631240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20230504 6769
100.0%

Interactions

2024-05-04T04:35:55.337318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:35:52.717283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:35:53.867026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:35:55.721336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:35:53.169101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:35:54.222377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:35:56.176522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:35:53.554730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:35:54.532426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T04:36:11.812536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선명표준버스정류장ID승차총승객수하차총승객수
노선번호1.0001.0000.6990.3920.381
노선명1.0001.0000.7000.3890.378
표준버스정류장ID0.6990.7001.0000.1860.122
승차총승객수0.3920.3890.1861.0000.543
하차총승객수0.3810.3780.1220.5431.000
2024-05-04T04:36:12.098586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준버스정류장ID승차총승객수하차총승객수
표준버스정류장ID1.000-0.153-0.143
승차총승객수-0.1531.0000.577
하차총승객수-0.1430.5771.000

Missing values

2024-05-04T04:35:56.650007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T04:35:57.471920image/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
020230501100100번(하계동~용산구청)10000000201002창경궁.서울대학교병원(00031)577620230504
12023050194089408번(구미동차고지~고속터미널)20500024706225성남시청후면(00026)40520230504
22023050194089408번(구미동차고지~고속터미널)20500024549602성남시청전면(00097)73920230504
32023050194089408번(구미동차고지~고속터미널)20500017206168성남시청후문앞(00096)21120230504
42023050194089408번(구미동차고지~고속터미널)20400022248637공군부대제2정문.면회실(00088)6320230504
52023050194089408번(구미동차고지~고속터미널)20400015548612시흥동주민센터(00093)4120230504
62023050194089408번(구미동차고지~고속터미널)20400015448613시흥동주민센터(00030)4320230504
72023050194089408번(구미동차고지~고속터미널)20400006248089성남농협대왕지점.고등동우체국(00090)434220230504
82023050194089408번(구미동차고지~고속터미널)20400005748077공군아파트(00087)121720230504
92023050194089408번(구미동차고지~고속터미널)20400004648085등자리(00034)0320230504
사용일자노선번호노선명표준버스정류장ID버스정류장ARS번호역명승차총승객수하차총승객수등록일자
67592023050124122412번(성수동~세곡동사거리)10400012605219노룬산시장앞(00065)247920230504
67602023050123112311번(중랑차고지~문정동)10600016907264엘지아파트앞(00109)41220230504
67612023050123122312번(강동공영차고지~중랑공영차고지)10600015407249사가정시장(00076)54320230504
67622023050124122412번(성수동~세곡동사거리)10400012805221노룬산시장앞(00013)1633920230504
67632023050124122412번(성수동~세곡동사거리)12200029523402수서역(00051)2425520230504
67642023050123122312번(강동공영차고지~중랑공영차고지)10600017607271성원아파트경남아너스빌앞(00063)13420230504
67652023050124122412번(성수동~세곡동사거리)12200029623403수서역KT수서지점(00028)2624720230504
67662023050124122412번(성수동~세곡동사거리)12200030123408수서역(00029)101333520230504
676720230501603603번(신월동~시청)11300042214015홍대입구역(00032)25326120230504
67682023050123112311번(중랑차고지~문정동)10600017007265신현중학교(00009)32620230504