Overview

Dataset statistics

Number of variables9
Number of observations6984
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory525.3 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 387 (5.5%) zerosZeros
하차총승객수 has 281 (4.0%) zerosZeros

Reproduction

Analysis started2024-05-11 06:05:11.563295
Analysis finished2024-05-11 06:05:15.026899
Duration3.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
20230901
6984 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20230901
2nd row20230901
3rd row20230901
4th row20230901
5th row20230901

Common Values

ValueCountFrequency (%)
20230901 6984
100.0%

Length

2024-05-11T15:05:15.135573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:15.274126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20230901 6984
100.0%

노선번호
Text

Distinct88
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
2024-05-11T15:05:15.631170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.583047
Min length3

Characters and Unicode

Total characters25024
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 row601
2nd row9409
3rd row9409
4th row9409
5th row9409
ValueCountFrequency (%)
n26 259
 
3.7%
n37 214
 
3.1%
542 138
 
2.0%
9701 127
 
1.8%
661 125
 
1.8%
541 123
 
1.8%
441 123
 
1.8%
9403 121
 
1.7%
5623 120
 
1.7%
9408 119
 
1.7%
Other values (78) 5515
79.0%
2024-05-11T15:05:16.216301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 3823
15.3%
0 3176
12.7%
5 3123
12.5%
1 2820
11.3%
3 2481
9.9%
4 2420
9.7%
2 2356
9.4%
6 2319
9.3%
9 859
 
3.4%
8 757
 
3.0%
Other values (8) 890
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24134
96.4%
Uppercase Letter 699
 
2.8%
Other Letter 176
 
0.7%
Dash Punctuation 15
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 3823
15.8%
0 3176
13.2%
5 3123
12.9%
1 2820
11.7%
3 2481
10.3%
4 2420
10.0%
2 2356
9.8%
6 2319
9.6%
9 859
 
3.6%
8 757
 
3.1%
Other Letter
ValueCountFrequency (%)
강 77
43.8%
동 77
43.8%
서 11
 
6.2%
울 11
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
N 481
68.8%
B 147
 
21.0%
A 71
 
10.2%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24149
96.5%
Latin 699
 
2.8%
Hangul 176
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
7 3823
15.8%
0 3176
13.2%
5 3123
12.9%
1 2820
11.7%
3 2481
10.3%
4 2420
10.0%
2 2356
9.8%
6 2319
9.6%
9 859
 
3.6%
8 757
 
3.1%
Hangul
ValueCountFrequency (%)
강 77
43.8%
동 77
43.8%
서 11
 
6.2%
울 11
 
6.2%
Latin
ValueCountFrequency (%)
N 481
68.8%
B 147
 
21.0%
A 71
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24848
99.3%
Hangul 176
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 3823
15.4%
0 3176
12.8%
5 3123
12.6%
1 2820
11.3%
3 2481
10.0%
4 2420
9.7%
2 2356
9.5%
6 2319
9.3%
9 859
 
3.5%
8 757
 
3.0%
Other values (4) 714
 
2.9%
Hangul
ValueCountFrequency (%)
강 77
43.8%
동 77
43.8%
서 11
 
6.2%
울 11
 
6.2%

노선명
Text

Distinct92
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
2024-05-11T15:05:16.546100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length22
Mean length17.167526
Min length12

Characters and Unicode

Total characters119898
Distinct characters183
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 row601번(개화동~종로4가)
2nd row9409번(구미동차고지~신사역)
3rd row9409번(구미동차고지~신사역)
4th row9409번(구미동차고지~신사역)
5th row9409번(구미동차고지~신사역)
ValueCountFrequency (%)
542번(군포버스공영차고지~신사역 138
 
1.9%
n26번(중랑공영차고지~강서공영차고지 130
 
1.8%
n26번(강서공영차고지~중랑공영차고지 129
 
1.8%
9701번(가좌동~서울역 127
 
1.7%
661번(부천상동~영등포역,신세계백화점 125
 
1.7%
541번(군포공영차고지~강남역 123
 
1.7%
441번(월암공영차고지~신사사거리 123
 
1.7%
9403번(구미동차고지~중곡역 121
 
1.7%
5623번(군포 120
 
1.7%
공영차고지~여의도 120
 
1.7%
Other values (85) 6004
82.7%
2024-05-11T15:05:17.446744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 7137
 
6.0%
) 7137
 
6.0%
~ 6984
 
5.8%
번 6760
 
5.6%
동 4575
 
3.8%
고 4004
 
3.3%
지 3928
 
3.3%
7 3823
 
3.2%
차 3664
 
3.1%
0 3176
 
2.6%
Other values (173) 68710
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72658
60.6%
Decimal Number 24292
 
20.3%
Open Punctuation 7137
 
6.0%
Close Punctuation 7137
 
6.0%
Math Symbol 6984
 
5.8%
Uppercase Letter 729
 
0.6%
Other Punctuation 670
 
0.6%
Space Separator 276
 
0.2%
Dash Punctuation 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 6760
 
9.3%
동 4575
 
6.3%
고 4004
 
5.5%
지 3928
 
5.4%
차 3664
 
5.0%
영 3020
 
4.2%
역 2982
 
4.1%
공 2701
 
3.7%
서 1821
 
2.5%
대 1772
 
2.4%
Other values (152) 37431
51.5%
Decimal Number
ValueCountFrequency (%)
7 3823
15.7%
0 3176
13.1%
5 3123
12.9%
1 2963
12.2%
3 2481
10.2%
4 2435
10.0%
2 2356
9.7%
6 2319
9.5%
9 859
 
3.5%
8 757
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
N 481
66.0%
B 147
 
20.2%
A 86
 
11.8%
K 15
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 411
61.3%
. 259
38.7%
Open Punctuation
ValueCountFrequency (%)
( 7137
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7137
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6984
100.0%
Space Separator
ValueCountFrequency (%)
276
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72658
60.6%
Common 46511
38.8%
Latin 729
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 6760
 
9.3%
동 4575
 
6.3%
고 4004
 
5.5%
지 3928
 
5.4%
차 3664
 
5.0%
영 3020
 
4.2%
역 2982
 
4.1%
공 2701
 
3.7%
서 1821
 
2.5%
대 1772
 
2.4%
Other values (152) 37431
51.5%
Common
ValueCountFrequency (%)
( 7137
15.3%
) 7137
15.3%
~ 6984
15.0%
7 3823
8.2%
0 3176
6.8%
5 3123
6.7%
1 2963
6.4%
3 2481
 
5.3%
4 2435
 
5.2%
2 2356
 
5.1%
Other values (7) 4896
10.5%
Latin
ValueCountFrequency (%)
N 481
66.0%
B 147
 
20.2%
A 86
 
11.8%
K 15
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72658
60.6%
ASCII 47240
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 7137
15.1%
) 7137
15.1%
~ 6984
14.8%
7 3823
8.1%
0 3176
6.7%
5 3123
6.6%
1 2963
6.3%
3 2481
 
5.3%
4 2435
 
5.2%
2 2356
 
5.0%
Other values (11) 5625
11.9%
Hangul
ValueCountFrequency (%)
번 6760
 
9.3%
동 4575
 
6.3%
고 4004
 
5.5%
지 3928
 
5.4%
차 3664
 
5.0%
영 3020
 
4.2%
역 2982
 
4.1%
공 2701
 
3.7%
서 1821
 
2.5%
대 1772
 
2.4%
Other values (152) 37431
51.5%

표준버스정류장ID
Real number (ℝ)

Distinct3686
Distinct (%)52.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5317282 × 108
Minimum1 × 108
Maximum9.998 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T15:05:17.655718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1 × 108
5-th percentile1.0100031 × 108
Q11.120004 × 108
median1.2000043 × 108
Q32.1000008 × 108
95-th percentile2.2200165 × 108
Maximum9.998 × 108
Range8.998 × 108
Interquartile range (IQR)97999682

Descriptive statistics

Standard deviation67504838
Coefficient of variation (CV)0.44071029
Kurtosis71.204896
Mean1.5317282 × 108
Median Absolute Deviation (MAD)10000386
Skewness6.0487211
Sum1.069759 × 1012
Variance4.5569031 × 1015
MonotonicityNot monotonic
2024-05-11T15:05:17.844669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
121000007 11
 
0.2%
100000380 11
 
0.2%
117000003 11
 
0.2%
112000400 10
 
0.1%
112000416 10
 
0.1%
112000408 10
 
0.1%
112000407 10
 
0.1%
112000404 10
 
0.1%
112000402 10
 
0.1%
112000401 10
 
0.1%
Other values (3676) 6881
98.5%
ValueCountFrequency (%)
100000001 2
< 0.1%
100000002 1
< 0.1%
100000003 1
< 0.1%
100000004 2
< 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%
998502944 1
 
< 0.1%
998502907 1
 
< 0.1%
998501980 2
< 0.1%
998501977 1
 
< 0.1%
998501975 1
 
< 0.1%
998501932 1
 
< 0.1%

버스정류장ARS번호
Text

Distinct3650
Distinct (%)52.3%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
2024-05-11T15:05:18.311617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.9879725
Min length1

Characters and Unicode

Total characters34836
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

Unique2050 ?
Unique (%)29.4%

Sample

1st row13017
2nd row22008
3rd row22007
4th row22006
5th row22005
ValueCountFrequency (%)
21
 
0.3%
01007 11
 
0.2%
18003 11
 
0.2%
22007 11
 
0.2%
13034 10
 
0.1%
22010 10
 
0.1%
13028 10
 
0.1%
13029 10
 
0.1%
13040 10
 
0.1%
13030 10
 
0.1%
Other values (3640) 6870
98.4%
2024-05-11T15:05:19.092969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6917
19.9%
0 5939
17.0%
2 4857
13.9%
3 3867
11.1%
4 2866
8.2%
6 2621
 
7.5%
5 2313
 
6.6%
7 2072
 
5.9%
8 1910
 
5.5%
9 1453
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34815
99.9%
Math Symbol 21
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6917
19.9%
0 5939
17.1%
2 4857
14.0%
3 3867
11.1%
4 2866
8.2%
6 2621
 
7.5%
5 2313
 
6.6%
7 2072
 
6.0%
8 1910
 
5.5%
9 1453
 
4.2%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34836
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6917
19.9%
0 5939
17.0%
2 4857
13.9%
3 3867
11.1%
4 2866
8.2%
6 2621
 
7.5%
5 2313
 
6.6%
7 2072
 
5.9%
8 1910
 
5.5%
9 1453
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34836
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6917
19.9%
0 5939
17.0%
2 4857
13.9%
3 3867
11.1%
4 2866
8.2%
6 2621
 
7.5%
5 2313
 
6.6%
7 2072
 
5.9%
8 1910
 
5.5%
9 1453
 
4.2%

역명
Text

Distinct6562
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
2024-05-11T15:05:19.533541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length15.106672
Min length9

Characters and Unicode

Total characters105505
Distinct characters539
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

Unique6229 ?
Unique (%)89.2%

Sample

1st row이대후문(00050)
2nd row래미안아파트.파이낸셜뉴스(중)(00038)
3rd row래미안아파트.파이낸셜뉴스(중)(00048)
4th row뱅뱅사거리(00037)
5th row뱅뱅사거리(00049)
ValueCountFrequency (%)
하안버스공영차고지(00002 6
 
0.1%
군포공영차고지(00001 6
 
0.1%
광명차고지(00001 6
 
0.1%
군포보건소(00002 5
 
0.1%
덕은교.은평차고지앞(00002 5
 
0.1%
은평공영차고지(00001 5
 
0.1%
하얀마을.그랜드빌.벽산빌라(00005 4
 
0.1%
대원사거리.까치마을(00009 4
 
0.1%
대우.롯데아파트상가(00008 4
 
0.1%
헬스케어혁신파크.(구)가스공사(00010 4
 
0.1%
Other values (6552) 6935
99.3%
2024-05-11T15:05:20.120579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22178
 
21.0%
( 7258
 
6.9%
) 7258
 
6.9%
1 2523
 
2.4%
. 2358
 
2.2%
2 1847
 
1.8%
3 1685
 
1.6%
4 1593
 
1.5%
5 1513
 
1.4%
6 1437
 
1.4%
Other values (529) 55855
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51617
48.9%
Decimal Number 36390
34.5%
Open Punctuation 7258
 
6.9%
Close Punctuation 7258
 
6.9%
Other Punctuation 2365
 
2.2%
Uppercase Letter 594
 
0.6%
Lowercase Letter 21
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 1396
 
2.7%
동 1348
 
2.6%
교 1293
 
2.5%
지 1106
 
2.1%
구 1040
 
2.0%
파 988
 
1.9%
아 939
 
1.8%
트 932
 
1.8%
학 903
 
1.7%
대 885
 
1.7%
Other values (489) 40787
79.0%
Uppercase Letter
ValueCountFrequency (%)
C 101
17.0%
M 77
13.0%
K 73
12.3%
D 71
12.0%
T 70
11.8%
G 39
 
6.6%
L 37
 
6.2%
S 27
 
4.5%
B 24
 
4.0%
N 13
 
2.2%
Other values (11) 62
10.4%
Decimal Number
ValueCountFrequency (%)
0 22178
60.9%
1 2523
 
6.9%
2 1847
 
5.1%
3 1685
 
4.6%
4 1593
 
4.4%
5 1513
 
4.2%
6 1437
 
3.9%
7 1339
 
3.7%
8 1194
 
3.3%
9 1081
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 2358
99.7%
& 6
 
0.3%
? 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 19
90.5%
k 1
 
4.8%
t 1
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 7258
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7258
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53273
50.5%
Hangul 51617
48.9%
Latin 615
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 1396
 
2.7%
동 1348
 
2.6%
교 1293
 
2.5%
지 1106
 
2.1%
구 1040
 
2.0%
파 988
 
1.9%
아 939
 
1.8%
트 932
 
1.8%
학 903
 
1.7%
대 885
 
1.7%
Other values (489) 40787
79.0%
Latin
ValueCountFrequency (%)
C 101
16.4%
M 77
12.5%
K 73
11.9%
D 71
11.5%
T 70
11.4%
G 39
 
6.3%
L 37
 
6.0%
S 27
 
4.4%
B 24
 
3.9%
e 19
 
3.1%
Other values (14) 77
12.5%
Common
ValueCountFrequency (%)
0 22178
41.6%
( 7258
 
13.6%
) 7258
 
13.6%
1 2523
 
4.7%
. 2358
 
4.4%
2 1847
 
3.5%
3 1685
 
3.2%
4 1593
 
3.0%
5 1513
 
2.8%
6 1437
 
2.7%
Other values (6) 3623
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53888
51.1%
Hangul 51617
48.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22178
41.2%
( 7258
 
13.5%
) 7258
 
13.5%
1 2523
 
4.7%
. 2358
 
4.4%
2 1847
 
3.4%
3 1685
 
3.1%
4 1593
 
3.0%
5 1513
 
2.8%
6 1437
 
2.7%
Other values (30) 4238
 
7.9%
Hangul
ValueCountFrequency (%)
역 1396
 
2.7%
동 1348
 
2.6%
교 1293
 
2.5%
지 1106
 
2.1%
구 1040
 
2.0%
파 988
 
1.9%
아 939
 
1.8%
트 932
 
1.8%
학 903
 
1.7%
대 885
 
1.7%
Other values (489) 40787
79.0%

승차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct615
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.22036
Minimum0
Maximum1524
Zeros387
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T15:05:20.323226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112
median62
Q3155
95-th percentile383
Maximum1524
Range1524
Interquartile range (IQR)143

Descriptive statistics

Standard deviation145.24908
Coefficient of variation (CV)1.3059576
Kurtosis12.542438
Mean111.22036
Median Absolute Deviation (MAD)56
Skewness2.8271843
Sum776763
Variance21097.295
MonotonicityNot monotonic
2024-05-11T15:05:20.554118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 387
 
5.5%
1 232
 
3.3%
2 177
 
2.5%
3 166
 
2.4%
4 125
 
1.8%
6 107
 
1.5%
7 106
 
1.5%
5 106
 
1.5%
8 80
 
1.1%
10 71
 
1.0%
Other values (605) 5427
77.7%
ValueCountFrequency (%)
0 387
5.5%
1 232
3.3%
2 177
2.5%
3 166
2.4%
4 125
 
1.8%
5 106
 
1.5%
6 107
 
1.5%
7 106
 
1.5%
8 80
 
1.1%
9 69
 
1.0%
ValueCountFrequency (%)
1524 1
< 0.1%
1416 1
< 0.1%
1408 1
< 0.1%
1347 1
< 0.1%
1215 1
< 0.1%
1208 1
< 0.1%
1192 1
< 0.1%
1174 1
< 0.1%
1131 1
< 0.1%
1104 1
< 0.1%

하차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct584
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108.89519
Minimum0
Maximum1636
Zeros281
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T15:05:20.780116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q114
median63
Q3150
95-th percentile372
Maximum1636
Range1636
Interquartile range (IQR)136

Descriptive statistics

Standard deviation142.0352
Coefficient of variation (CV)1.3043294
Kurtosis17.021831
Mean108.89519
Median Absolute Deviation (MAD)55
Skewness3.1822613
Sum760524
Variance20173.997
MonotonicityNot monotonic
2024-05-11T15:05:21.019719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 281
 
4.0%
1 205
 
2.9%
2 168
 
2.4%
3 158
 
2.3%
4 138
 
2.0%
5 109
 
1.6%
6 108
 
1.5%
8 101
 
1.4%
7 91
 
1.3%
10 86
 
1.2%
Other values (574) 5539
79.3%
ValueCountFrequency (%)
0 281
4.0%
1 205
2.9%
2 168
2.4%
3 158
2.3%
4 138
2.0%
5 109
 
1.6%
6 108
 
1.5%
7 91
 
1.3%
8 101
 
1.4%
9 75
 
1.1%
ValueCountFrequency (%)
1636 1
< 0.1%
1582 1
< 0.1%
1503 1
< 0.1%
1471 1
< 0.1%
1403 1
< 0.1%
1326 1
< 0.1%
1239 1
< 0.1%
1234 1
< 0.1%
1175 2
< 0.1%
1149 1
< 0.1%

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
20230904
6984 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20230904
2nd row20230904
3rd row20230904
4th row20230904
5th row20230904

Common Values

ValueCountFrequency (%)
20230904 6984
100.0%

Length

2024-05-11T15:05:21.260181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:21.427384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20230904 6984
100.0%

Interactions

2024-05-11T15:05:14.024641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:12.975960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:13.496385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:14.202377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:13.123693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:13.657745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:14.378391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:13.306139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:13.845400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:05:21.549341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선명표준버스정류장ID승차총승객수하차총승객수
노선번호1.0001.0000.6800.4600.443
노선명1.0001.0000.6800.4610.444
표준버스정류장ID0.6800.6801.0000.2120.202
승차총승객수0.4600.4610.2121.0000.458
하차총승객수0.4430.4440.2020.4581.000
2024-05-11T15:05:21.806746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준버스정류장ID승차총승객수하차총승객수
표준버스정류장ID1.000-0.143-0.133
승차총승객수-0.1431.0000.583
하차총승객수-0.1330.5831.000

Missing values

2024-05-11T15:05:14.646151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:05:14.914248image/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
020230901601601번(개화동~종로4가)11200001713017이대후문(00050)28638720230904
12023090194099409번(구미동차고지~신사역)12100000822008래미안아파트.파이낸셜뉴스(중)(00038)03120230904
22023090194099409번(구미동차고지~신사역)12100000722007래미안아파트.파이낸셜뉴스(중)(00048)30020230904
32023090194099409번(구미동차고지~신사역)12100000622006뱅뱅사거리(00037)11520230904
42023090194099409번(구미동차고지~신사역)12100000522005뱅뱅사거리(00049)10020230904
52023090194099409번(구미동차고지~신사역)12100000422004양재역.서초문화예술회관(00036)02720230904
62023090194099409번(구미동차고지~신사역)12100000322003양재역.서초문화예술회관(00050)41020230904
72023090194099409번(구미동차고지~신사역)12100000222002교육개발원입구(00035)02220230904
82023090194099409번(구미동차고지~신사역)12100000122001교육개발원입구(00051)10120230904
920230901542542번(군포버스공영차고지~신사역)22500024940163군포공영차고지(00001)9020230904
사용일자노선번호노선명표준버스정류장ID버스정류장ARS번호역명승차총승객수하차총승객수등록일자
69742023090143184318번(풍납동출발.풍납동~사당동)12200005623158한양아파트.압구정로데오역(00038)293620230904
69752023090122332233번(면목동~옥수동)10100015102256신당동대우푸르지오.금호여중(00075)552620230904
697620230901N15N15번(남태령역~우이동도선사입구)10000039001015종로3가.탑골공원(00038)56220230904
69772023090143184318번(풍납동출발.풍납동~사당동)12200005723159한양아파트.압구정로데오역(00078)435820230904
69782023090143184318번(풍납동출발.풍납동~사당동)12200006323165청담초등학교(00037)282120230904
697920230901N15N15번(남태령역~우이동도선사입구)10000039101016종로3가.탑골공원(00108)211120230904
69802023090143184318번(풍납동출발.풍납동~사당동)12200006423166청담동주민센터(00036)605520230904
69812023090143184318번(풍납동출발.풍납동~사당동)12200006523167청담동주민센터(00080)806720230904
698220230901160160번(도봉산~온수동)10900000810008신도봉사거리(00115)5219620230904
698320230901602602번(양천공용차고지~시청앞)11200005413137충정로역2호선(00047)1016120230904