Overview

Dataset statistics

Number of variables9
Number of observations6745
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory507.3 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 548 (8.1%) zerosZeros
하차총승객수 has 434 (6.4%) zerosZeros

Reproduction

Analysis started2024-05-11 06:05:59.173589
Analysis finished2024-05-11 06:06:02.455438
Duration3.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size52.8 KiB
20240101
6745 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20240101
2nd row20240101
3rd row20240101
4th row20240101
5th row20240101

Common Values

ValueCountFrequency (%)
20240101 6745
100.0%

Length

2024-05-11T15:06:02.571280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:02.748650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20240101 6745
100.0%

노선번호
Text

Distinct82
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size52.8 KiB
2024-05-11T15:06:03.149844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.5796887
Min length3

Characters and Unicode

Total characters24145
Distinct characters18
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row101
2nd row9408
3rd row9408
4th row9408
5th row9408
ValueCountFrequency (%)
n26 252
 
3.7%
n15 226
 
3.4%
n37 183
 
2.7%
542 138
 
2.0%
9701 125
 
1.9%
661 124
 
1.8%
541 123
 
1.8%
441 123
 
1.8%
5623 120
 
1.8%
111 116
 
1.7%
Other values (72) 5215
77.3%
2024-05-11T15:06:03.893366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 3819
15.8%
5 3056
12.7%
1 2950
12.2%
0 2691
11.1%
2 2613
10.8%
6 2398
9.9%
4 2200
9.1%
3 2141
8.9%
9 810
 
3.4%
N 661
 
2.7%
Other values (8) 806
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23055
95.5%
Uppercase Letter 828
 
3.4%
Other Letter 234
 
1.0%
Dash Punctuation 28
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 3819
16.6%
5 3056
13.3%
1 2950
12.8%
0 2691
11.7%
2 2613
11.3%
6 2398
10.4%
4 2200
9.5%
3 2141
9.3%
9 810
 
3.5%
8 377
 
1.6%
Other Letter
ValueCountFrequency (%)
동 105
44.9%
강 89
38.0%
성 28
 
12.0%
서 12
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
N 661
79.8%
B 148
 
17.9%
A 19
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23083
95.6%
Latin 828
 
3.4%
Hangul 234
 
1.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 3819
16.5%
5 3056
13.2%
1 2950
12.8%
0 2691
11.7%
2 2613
11.3%
6 2398
10.4%
4 2200
9.5%
3 2141
9.3%
9 810
 
3.5%
8 377
 
1.6%
Hangul
ValueCountFrequency (%)
동 105
44.9%
강 89
38.0%
성 28
 
12.0%
서 12
 
5.1%
Latin
ValueCountFrequency (%)
N 661
79.8%
B 148
 
17.9%
A 19
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23911
99.0%
Hangul 234
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 3819
16.0%
5 3056
12.8%
1 2950
12.3%
0 2691
11.3%
2 2613
10.9%
6 2398
10.0%
4 2200
9.2%
3 2141
9.0%
9 810
 
3.4%
N 661
 
2.8%
Other values (4) 572
 
2.4%
Hangul
ValueCountFrequency (%)
동 105
44.9%
강 89
38.0%
성 28
 
12.0%
서 12
 
5.1%

노선명
Text

Distinct85
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size52.8 KiB
2024-05-11T15:06:04.338445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length21
Mean length17.248629
Min length12

Characters and Unicode

Total characters116342
Distinct characters179
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row101번(화계사~동대문)
2nd row9408번(구미동차고지~고속터미널)
3rd row9408번(구미동차고지~고속터미널)
4th row9408번(구미동차고지~고속터미널)
5th row9408번(구미동차고지~고속터미널)
ValueCountFrequency (%)
n15번(우이동성원아파트~남태령역 142
 
2.0%
542번(군포버스공영차고지~신사역 138
 
2.0%
n26번(강서공영차고지~중랑공영차고지 130
 
1.9%
9701번(가좌동~서울역 125
 
1.8%
661번(부천상동~영등포역,신세계백화점 124
 
1.8%
541번(군포공영차고지~강남역 123
 
1.8%
441번(월암공영차고지~신사사거리 123
 
1.8%
n26번(중랑공영차고지~강서공영차고지 122
 
1.7%
5623번(군포 120
 
1.7%
공영차고지~여의도 120
 
1.7%
Other values (78) 5753
82.0%
2024-05-11T15:06:04.998644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 6909
 
5.9%
) 6909
 
5.9%
~ 6745
 
5.8%
번 6448
 
5.5%
동 4518
 
3.9%
고 4044
 
3.5%
지 3901
 
3.4%
7 3819
 
3.3%
차 3751
 
3.2%
5 3056
 
2.6%
Other values (169) 66242
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71052
61.1%
Decimal Number 23146
 
19.9%
Open Punctuation 6909
 
5.9%
Close Punctuation 6909
 
5.9%
Math Symbol 6745
 
5.8%
Uppercase Letter 828
 
0.7%
Other Punctuation 450
 
0.4%
Space Separator 275
 
0.2%
Dash Punctuation 28
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 6448
 
9.1%
동 4518
 
6.4%
고 4044
 
5.7%
지 3901
 
5.5%
차 3751
 
5.3%
영 2877
 
4.0%
역 2777
 
3.9%
공 2584
 
3.6%
대 1532
 
2.2%
서 1320
 
1.9%
Other values (149) 37300
52.5%
Decimal Number
ValueCountFrequency (%)
7 3819
16.5%
5 3056
13.2%
1 3041
13.1%
0 2691
11.6%
2 2613
11.3%
6 2398
10.4%
4 2200
9.5%
3 2141
9.2%
9 810
 
3.5%
8 377
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
N 661
79.8%
B 148
 
17.9%
A 19
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 333
74.0%
. 117
 
26.0%
Open Punctuation
ValueCountFrequency (%)
( 6909
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6909
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6745
100.0%
Space Separator
ValueCountFrequency (%)
275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71052
61.1%
Common 44462
38.2%
Latin 828
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 6448
 
9.1%
동 4518
 
6.4%
고 4044
 
5.7%
지 3901
 
5.5%
차 3751
 
5.3%
영 2877
 
4.0%
역 2777
 
3.9%
공 2584
 
3.6%
대 1532
 
2.2%
서 1320
 
1.9%
Other values (149) 37300
52.5%
Common
ValueCountFrequency (%)
( 6909
15.5%
) 6909
15.5%
~ 6745
15.2%
7 3819
8.6%
5 3056
6.9%
1 3041
6.8%
0 2691
 
6.1%
2 2613
 
5.9%
6 2398
 
5.4%
4 2200
 
4.9%
Other values (7) 4081
9.2%
Latin
ValueCountFrequency (%)
N 661
79.8%
B 148
 
17.9%
A 19
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71052
61.1%
ASCII 45290
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 6909
15.3%
) 6909
15.3%
~ 6745
14.9%
7 3819
8.4%
5 3056
6.7%
1 3041
6.7%
0 2691
 
5.9%
2 2613
 
5.8%
6 2398
 
5.3%
4 2200
 
4.9%
Other values (10) 4909
10.8%
Hangul
ValueCountFrequency (%)
번 6448
 
9.1%
동 4518
 
6.4%
고 4044
 
5.7%
지 3901
 
5.5%
차 3751
 
5.3%
영 2877
 
4.0%
역 2777
 
3.9%
공 2584
 
3.6%
대 1532
 
2.2%
서 1320
 
1.9%
Other values (149) 37300
52.5%

표준버스정류장ID
Real number (ℝ)

Distinct3698
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4961992 × 108
Minimum1 × 108
Maximum9.9903357 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size59.4 KiB
2024-05-11T15:06:05.260659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1 × 108
5-th percentile1.0100008 × 108
Q11.1200001 × 108
median1.1900007 × 108
Q32.0900008 × 108
95-th percentile2.2200154 × 108
Maximum9.9903357 × 108
Range8.9903357 × 108
Interquartile range (IQR)97000071

Descriptive statistics

Standard deviation59728267
Coefficient of variation (CV)0.39919997
Kurtosis63.829016
Mean1.4961992 × 108
Median Absolute Deviation (MAD)12000009
Skewness4.9666392
Sum1.0091864 × 1012
Variance3.5674659 × 1015
MonotonicityNot monotonic
2024-05-11T15:06:05.504950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
121000009 11
 
0.2%
121000008 11
 
0.2%
121000007 11
 
0.2%
121000006 11
 
0.2%
100000389 10
 
0.1%
121000013 10
 
0.1%
121000005 10
 
0.1%
121000003 10
 
0.1%
112000005 10
 
0.1%
121000010 10
 
0.1%
Other values (3688) 6641
98.5%
ValueCountFrequency (%)
100000001 3
< 0.1%
100000002 1
 
< 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 (%)
999033574 4
0.1%
998502907 1
 
< 0.1%
998502269 1
 
< 0.1%
998501980 1
 
< 0.1%
998501931 1
 
< 0.1%
998001700 1
 
< 0.1%
990070001 1
 
< 0.1%
990014944 1
 
< 0.1%
277104252 1
 
< 0.1%
277104251 1
 
< 0.1%

버스정류장ARS번호
Text

Distinct3669
Distinct (%)54.4%
Missing0
Missing (%)0.0%
Memory size52.8 KiB
2024-05-11T15:06:06.109294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.9934766
Min length1

Characters and Unicode

Total characters33681
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

Unique2156 ?
Unique (%)32.0%

Sample

1st row06178
2nd row22337
3rd row22336
4th row22334
5th row22333
ValueCountFrequency (%)
22007 11
 
0.2%
22008 11
 
0.2%
22009 11
 
0.2%
11
 
0.2%
22006 11
 
0.2%
01013 10
 
0.1%
22013 10
 
0.1%
12007 10
 
0.1%
12006 10
 
0.1%
12004 10
 
0.1%
Other values (3659) 6640
98.4%
2024-05-11T15:06:06.911222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6727
20.0%
0 6094
18.1%
2 4546
13.5%
3 3548
10.5%
4 2652
 
7.9%
6 2616
 
7.8%
5 2360
 
7.0%
7 2051
 
6.1%
8 1728
 
5.1%
9 1348
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33670
> 99.9%
Math Symbol 11
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6727
20.0%
0 6094
18.1%
2 4546
13.5%
3 3548
10.5%
4 2652
 
7.9%
6 2616
 
7.8%
5 2360
 
7.0%
7 2051
 
6.1%
8 1728
 
5.1%
9 1348
 
4.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33681
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6727
20.0%
0 6094
18.1%
2 4546
13.5%
3 3548
10.5%
4 2652
 
7.9%
6 2616
 
7.8%
5 2360
 
7.0%
7 2051
 
6.1%
8 1728
 
5.1%
9 1348
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33681
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6727
20.0%
0 6094
18.1%
2 4546
13.5%
3 3548
10.5%
4 2652
 
7.9%
6 2616
 
7.8%
5 2360
 
7.0%
7 2051
 
6.1%
8 1728
 
5.1%
9 1348
 
4.0%

역명
Text

Distinct6445
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size52.8 KiB
2024-05-11T15:06:07.298898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length15.13536
Min length9

Characters and Unicode

Total characters102088
Distinct characters544
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

Unique6206 ?
Unique (%)92.0%

Sample

1st row대광고등학교앞(00055)
2nd row헌인마을.서울농업기술센터(00042)
3rd row헌인마을.서울농업기술센터(00078)
4th row헌인릉.강남서초과학화예비군훈련장(00043)
5th row헌인릉.강남서초과학화예비군훈련장(00076)
ValueCountFrequency (%)
은평공영차고지(00001 5
 
0.1%
덕은교.은평차고지앞(00002 5
 
0.1%
군포공영차고지(00001 5
 
0.1%
군포보건소(00002 5
 
0.1%
광명차고지(00001 4
 
0.1%
주공4단지(00004 4
 
0.1%
헬스케어혁신파크.(구)가스공사(00010 4
 
0.1%
대우.롯데아파트상가(00008 4
 
0.1%
오리초등학교(00006 4
 
0.1%
미금초등학교(00007 4
 
0.1%
Other values (6435) 6701
99.3%
2024-05-11T15:06:07.969750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21327
 
20.9%
( 7004
 
6.9%
) 7004
 
6.9%
1 2496
 
2.4%
. 2284
 
2.2%
2 1785
 
1.7%
3 1604
 
1.6%
4 1508
 
1.5%
5 1467
 
1.4%
6 1429
 
1.4%
Other values (534) 54180
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49962
48.9%
Decimal Number 35188
34.5%
Open Punctuation 7004
 
6.9%
Close Punctuation 7004
 
6.9%
Other Punctuation 2297
 
2.3%
Uppercase Letter 607
 
0.6%
Lowercase Letter 24
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 1376
 
2.8%
동 1329
 
2.7%
교 1216
 
2.4%
지 1083
 
2.2%
구 987
 
2.0%
파 975
 
2.0%
아 924
 
1.8%
트 903
 
1.8%
학 871
 
1.7%
서 828
 
1.7%
Other values (494) 39470
79.0%
Uppercase Letter
ValueCountFrequency (%)
C 100
16.5%
M 81
13.3%
K 80
13.2%
T 80
13.2%
D 76
12.5%
G 42
6.9%
L 36
 
5.9%
S 24
 
4.0%
B 19
 
3.1%
N 13
 
2.1%
Other values (11) 56
9.2%
Decimal Number
ValueCountFrequency (%)
0 21327
60.6%
1 2496
 
7.1%
2 1785
 
5.1%
3 1604
 
4.6%
4 1508
 
4.3%
5 1467
 
4.2%
6 1429
 
4.1%
7 1307
 
3.7%
8 1190
 
3.4%
9 1075
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 2284
99.4%
& 11
 
0.5%
? 2
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 22
91.7%
k 1
 
4.2%
t 1
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 7004
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7004
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51495
50.4%
Hangul 49962
48.9%
Latin 631
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 1376
 
2.8%
동 1329
 
2.7%
교 1216
 
2.4%
지 1083
 
2.2%
구 987
 
2.0%
파 975
 
2.0%
아 924
 
1.8%
트 903
 
1.8%
학 871
 
1.7%
서 828
 
1.7%
Other values (494) 39470
79.0%
Latin
ValueCountFrequency (%)
C 100
15.8%
M 81
12.8%
K 80
12.7%
T 80
12.7%
D 76
12.0%
G 42
6.7%
L 36
 
5.7%
S 24
 
3.8%
e 22
 
3.5%
B 19
 
3.0%
Other values (14) 71
11.3%
Common
ValueCountFrequency (%)
0 21327
41.4%
( 7004
 
13.6%
) 7004
 
13.6%
1 2496
 
4.8%
. 2284
 
4.4%
2 1785
 
3.5%
3 1604
 
3.1%
4 1508
 
2.9%
5 1467
 
2.8%
6 1429
 
2.8%
Other values (6) 3587
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52126
51.1%
Hangul 49962
48.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21327
40.9%
( 7004
 
13.4%
) 7004
 
13.4%
1 2496
 
4.8%
. 2284
 
4.4%
2 1785
 
3.4%
3 1604
 
3.1%
4 1508
 
2.9%
5 1467
 
2.8%
6 1429
 
2.7%
Other values (30) 4218
 
8.1%
Hangul
ValueCountFrequency (%)
역 1376
 
2.8%
동 1329
 
2.7%
교 1216
 
2.4%
지 1083
 
2.2%
구 987
 
2.0%
파 975
 
2.0%
아 924
 
1.8%
트 903
 
1.8%
학 871
 
1.7%
서 828
 
1.7%
Other values (494) 39470
79.0%

승차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct332
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.779985
Minimum0
Maximum902
Zeros548
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size59.4 KiB
2024-05-11T15:06:08.265565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median23
Q360
95-th percentile166
Maximum902
Range902
Interquartile range (IQR)55

Descriptive statistics

Standard deviation66.055222
Coefficient of variation (CV)1.4428843
Kurtosis21.726651
Mean45.779985
Median Absolute Deviation (MAD)21
Skewness3.6352981
Sum308786
Variance4363.2923
MonotonicityNot monotonic
2024-05-11T15:06:08.531126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 548
 
8.1%
1 353
 
5.2%
2 294
 
4.4%
3 219
 
3.2%
4 174
 
2.6%
5 163
 
2.4%
6 130
 
1.9%
7 120
 
1.8%
8 111
 
1.6%
9 110
 
1.6%
Other values (322) 4523
67.1%
ValueCountFrequency (%)
0 548
8.1%
1 353
5.2%
2 294
4.4%
3 219
 
3.2%
4 174
 
2.6%
5 163
 
2.4%
6 130
 
1.9%
7 120
 
1.8%
8 111
 
1.6%
9 110
 
1.6%
ValueCountFrequency (%)
902 1
< 0.1%
758 1
< 0.1%
706 1
< 0.1%
660 1
< 0.1%
649 1
< 0.1%
631 1
< 0.1%
598 1
< 0.1%
593 1
< 0.1%
570 1
< 0.1%
563 1
< 0.1%

하차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct316
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.110897
Minimum0
Maximum751
Zeros434
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size59.4 KiB
2024-05-11T15:06:08.798470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median25
Q361
95-th percentile156.8
Maximum751
Range751
Interquartile range (IQR)54

Descriptive statistics

Standard deviation60.374321
Coefficient of variation (CV)1.3383534
Kurtosis19.984114
Mean45.110897
Median Absolute Deviation (MAD)22
Skewness3.4022774
Sum304273
Variance3645.0586
MonotonicityNot monotonic
2024-05-11T15:06:09.369390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 434
 
6.4%
1 303
 
4.5%
2 258
 
3.8%
4 198
 
2.9%
3 189
 
2.8%
5 152
 
2.3%
6 141
 
2.1%
7 139
 
2.1%
8 117
 
1.7%
10 112
 
1.7%
Other values (306) 4702
69.7%
ValueCountFrequency (%)
0 434
6.4%
1 303
4.5%
2 258
3.8%
3 189
2.8%
4 198
2.9%
5 152
 
2.3%
6 141
 
2.1%
7 139
 
2.1%
8 117
 
1.7%
9 106
 
1.6%
ValueCountFrequency (%)
751 1
< 0.1%
734 1
< 0.1%
709 1
< 0.1%
625 1
< 0.1%
595 1
< 0.1%
555 1
< 0.1%
550 1
< 0.1%
545 1
< 0.1%
544 1
< 0.1%
515 1
< 0.1%

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size52.8 KiB
20240104
6745 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20240104
2nd row20240104
3rd row20240104
4th row20240104
5th row20240104

Common Values

ValueCountFrequency (%)
20240104 6745
100.0%

Length

2024-05-11T15:06:09.594210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:06:09.751410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20240104 6745
100.0%

Interactions

2024-05-11T15:06:01.468496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:00.444133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:00.961680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:01.626091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:00.620105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:01.147813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:01.799139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:00.780442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:06:01.306523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:06:09.850607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선명표준버스정류장ID승차총승객수하차총승객수
노선번호1.0001.0000.6960.4330.461
노선명1.0001.0000.6960.4330.461
표준버스정류장ID0.6960.6961.0000.1540.185
승차총승객수0.4330.4330.1541.0000.657
하차총승객수0.4610.4610.1850.6571.000
2024-05-11T15:06:10.020594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준버스정류장ID승차총승객수하차총승객수
표준버스정류장ID1.000-0.163-0.159
승차총승객수-0.1631.0000.545
하차총승객수-0.1590.5451.000

Missing values

2024-05-11T15:06:02.037435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:06:02.333066image/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
020240101101101번(화계사~동대문)10500009206178대광고등학교앞(00055)397620240104
12024010194089408번(구미동차고지~고속터미널)12100026122337헌인마을.서울농업기술센터(00042)1020240104
22024010194089408번(구미동차고지~고속터미널)12100026022336헌인마을.서울농업기술센터(00078)2020240104
32024010194089408번(구미동차고지~고속터미널)12100025822334헌인릉.강남서초과학화예비군훈련장(00043)0220240104
42024010194089408번(구미동차고지~고속터미널)12100025722333헌인릉.강남서초과학화예비군훈련장(00076)2120240104
52024010194089408번(구미동차고지~고속터미널)12100022122297매헌시민의숲.양재꽃시장(00048)61720240104
62024010194089408번(구미동차고지~고속터미널)12100022022296매헌시민의숲.양재꽃시장(00071)16520240104
72024010194089408번(구미동차고지~고속터미널)12100011422190논현역6번출구(00063)4120240104
82024010194089408번(구미동차고지~고속터미널)12100010722183논현역7번출구(00056)1520240104
92024010194089408번(구미동차고지~고속터미널)12100002322023구반포역.세화고등학교(00060)0320240104
사용일자노선번호노선명표준버스정류장ID버스정류장ARS번호역명승차총승객수하차총승객수등록일자
67352024010124122412번(성수동~세곡동사거리)10300010204201뚝도시장구길(00076)11520240104
67362024010124122412번(성수동~세곡동사거리)10300010304202뚝도시장구길(00002)24020240104
67372024010123122312번(강동공영차고지~중랑공영차고지)10600000207002망우역.상봉터미널(00043)181620240104
67382024010124122412번(성수동~세곡동사거리)10300018304286성수동차고지(00001)10120240104
67392024010124122412번(성수동~세곡동사거리)10400009005183자양미소약국.자양골목시장(00061)8810420240104
674020240101602602번(양천공용차고지~시청앞)11800013219217안양천입구(00027)452920240104
67412024010123112311번(중랑차고지~문정동)10400005305146광진경찰서(00076)652920240104
67422024010123122312번(강동공영차고지~중랑공영차고지)10600000307003상봉역.중랑우체국(00067)91220240104
67432024010124122412번(성수동~세곡동사거리)10400009205185국민은행자양지점앞(00060)9216620240104
67442024010124122412번(성수동~세곡동사거리)10400009405187자양하늘채베르아파트앞(00059)7812520240104