Overview

Dataset statistics

Number of variables9
Number of observations6771
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory509.3 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 504 (7.4%) zerosZeros
하차총승객수 has 357 (5.3%) zerosZeros

Reproduction

Analysis started2024-05-04 04:37:59.677770
Analysis finished2024-05-04 04:38:05.877597
Duration6.2 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
20231001
6771 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20231001
2nd row20231001
3rd row20231001
4th row20231001
5th row20231001

Common Values

ValueCountFrequency (%)
20231001 6771
100.0%

Length

2024-05-04T04:38:06.267910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:38:06.878240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20231001 6771
100.0%

노선번호
Text

Distinct82
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size53.0 KiB
2024-05-04T04:38:07.569529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.5764289
Min length3

Characters and Unicode

Total characters24216
Distinct characters16
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

Unique3 ?
Unique (%)< 0.1%

Sample

1st row720
2nd row9408
3rd row9408
4th row9408
5th row9408
ValueCountFrequency (%)
n26 244
 
3.6%
n15 232
 
3.4%
n37 204
 
3.0%
542 137
 
2.0%
9701 127
 
1.9%
661 125
 
1.8%
441 124
 
1.8%
541 123
 
1.8%
9403 120
 
1.8%
5623 120
 
1.8%
Other values (72) 5215
77.0%
2024-05-04T04:38:08.931029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 3811
15.7%
1 3035
12.5%
5 3015
12.5%
0 2692
11.1%
2 2618
10.8%
6 2388
9.9%
4 2241
9.3%
3 2147
8.9%
9 844
 
3.5%
N 680
 
2.8%
Other values (6) 745
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23168
95.7%
Uppercase Letter 828
 
3.4%
Other Letter 204
 
0.8%
Dash Punctuation 16
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 3811
16.4%
1 3035
13.1%
5 3015
13.0%
0 2692
11.6%
2 2618
11.3%
6 2388
10.3%
4 2241
9.7%
3 2147
9.3%
9 844
 
3.6%
8 377
 
1.6%
Other Letter
ValueCountFrequency (%)
동 102
50.0%
강 77
37.7%
성 25
 
12.3%
Uppercase Letter
ValueCountFrequency (%)
N 680
82.1%
B 148
 
17.9%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23184
95.7%
Latin 828
 
3.4%
Hangul 204
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
7 3811
16.4%
1 3035
13.1%
5 3015
13.0%
0 2692
11.6%
2 2618
11.3%
6 2388
10.3%
4 2241
9.7%
3 2147
9.3%
9 844
 
3.6%
8 377
 
1.6%
Hangul
ValueCountFrequency (%)
동 102
50.0%
강 77
37.7%
성 25
 
12.3%
Latin
ValueCountFrequency (%)
N 680
82.1%
B 148
 
17.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24012
99.2%
Hangul 204
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 3811
15.9%
1 3035
12.6%
5 3015
12.6%
0 2692
11.2%
2 2618
10.9%
6 2388
9.9%
4 2241
9.3%
3 2147
8.9%
9 844
 
3.5%
N 680
 
2.8%
Other values (3) 541
 
2.3%
Hangul
ValueCountFrequency (%)
동 102
50.0%
강 77
37.7%
성 25
 
12.3%

노선명
Text

Distinct85
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size53.0 KiB
2024-05-04T04:38:09.608950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length21
Mean length17.308079
Min length12

Characters and Unicode

Total characters117193
Distinct characters175
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

Unique3 ?
Unique (%)< 0.1%

Sample

1st row720번(기자촌~답십리)
2nd row9408번(구미동차고지~고속터미널)
3rd row9408번(구미동차고지~고속터미널)
4th row9408번(구미동차고지~고속터미널)
5th row9408번(구미동차고지~고속터미널)
ValueCountFrequency (%)
n15번(우이동성원아파트~남태령역 139
 
2.0%
542번(군포버스공영차고지~신사역 137
 
1.9%
9701번(가좌동~서울역 127
 
1.8%
661번(부천상동~영등포역,신세계백화점 125
 
1.8%
441번(월암공영차고지~신사사거리 124
 
1.8%
n26번(중랑공영차고지~강서공영차고지 123
 
1.7%
541번(군포공영차고지~강남역 123
 
1.7%
n26번(강서공영차고지~중랑공영차고지 121
 
1.7%
공영차고지~여의도 120
 
1.7%
9403번(구미동차고지~중곡역 120
 
1.7%
Other values (78) 5787
82.1%
2024-05-04T04:38:11.034204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 6925
 
5.9%
) 6925
 
5.9%
~ 6771
 
5.8%
번 6489
 
5.5%
동 4671
 
4.0%
고 4195
 
3.6%
지 4041
 
3.4%
차 3878
 
3.3%
7 3811
 
3.3%
1 3107
 
2.7%
Other values (165) 66380
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71715
61.2%
Decimal Number 23277
 
19.9%
Open Punctuation 6925
 
5.9%
Close Punctuation 6925
 
5.9%
Math Symbol 6771
 
5.8%
Uppercase Letter 860
 
0.7%
Other Punctuation 429
 
0.4%
Space Separator 275
 
0.2%
Dash Punctuation 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 6489
 
9.0%
동 4671
 
6.5%
고 4195
 
5.8%
지 4041
 
5.6%
차 3878
 
5.4%
영 2897
 
4.0%
역 2765
 
3.9%
공 2590
 
3.6%
대 1545
 
2.2%
서 1365
 
1.9%
Other values (144) 37279
52.0%
Decimal Number
ValueCountFrequency (%)
7 3811
16.4%
1 3107
13.3%
5 3015
13.0%
0 2692
11.6%
2 2618
11.2%
6 2388
10.3%
4 2278
9.8%
3 2147
9.2%
9 844
 
3.6%
8 377
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
N 680
79.1%
B 148
 
17.2%
A 16
 
1.9%
K 16
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 296
69.0%
. 133
31.0%
Open Punctuation
ValueCountFrequency (%)
( 6925
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6925
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6771
100.0%
Space Separator
ValueCountFrequency (%)
275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71715
61.2%
Common 44618
38.1%
Latin 860
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 6489
 
9.0%
동 4671
 
6.5%
고 4195
 
5.8%
지 4041
 
5.6%
차 3878
 
5.4%
영 2897
 
4.0%
역 2765
 
3.9%
공 2590
 
3.6%
대 1545
 
2.2%
서 1365
 
1.9%
Other values (144) 37279
52.0%
Common
ValueCountFrequency (%)
( 6925
15.5%
) 6925
15.5%
~ 6771
15.2%
7 3811
8.5%
1 3107
7.0%
5 3015
6.8%
0 2692
 
6.0%
2 2618
 
5.9%
6 2388
 
5.4%
4 2278
 
5.1%
Other values (7) 4088
9.2%
Latin
ValueCountFrequency (%)
N 680
79.1%
B 148
 
17.2%
A 16
 
1.9%
K 16
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71715
61.2%
ASCII 45478
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 6925
15.2%
) 6925
15.2%
~ 6771
14.9%
7 3811
8.4%
1 3107
6.8%
5 3015
6.6%
0 2692
 
5.9%
2 2618
 
5.8%
6 2388
 
5.3%
4 2278
 
5.0%
Other values (11) 4948
10.9%
Hangul
ValueCountFrequency (%)
번 6489
 
9.0%
동 4671
 
6.5%
고 4195
 
5.8%
지 4041
 
5.6%
차 3878
 
5.4%
영 2897
 
4.0%
역 2765
 
3.9%
공 2590
 
3.6%
대 1545
 
2.2%
서 1365
 
1.9%
Other values (144) 37279
52.0%

표준버스정류장ID
Real number (ℝ)

Distinct3675
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4993938 × 108
Minimum1 × 108
Maximum9.998 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size59.6 KiB
2024-05-04T04:38:11.627192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1 × 108
5-th percentile1.010003 × 108
Q11.1200001 × 108
median1.1900008 × 108
Q32.0900006 × 108
95-th percentile2.220016 × 108
Maximum9.998 × 108
Range8.998 × 108
Interquartile range (IQR)97000052

Descriptive statistics

Standard deviation63859083
Coefficient of variation (CV)0.42589934
Kurtosis70.814806
Mean1.4993938 × 108
Median Absolute Deviation (MAD)11000066
Skewness5.7609658
Sum1.0152395 × 1012
Variance4.0779825 × 1015
MonotonicityNot monotonic
2024-05-04T04:38:12.238129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
121000005 12
 
0.2%
121000007 12
 
0.2%
100000380 11
 
0.2%
121000009 11
 
0.2%
121000006 11
 
0.2%
121000008 11
 
0.2%
111000007 10
 
0.1%
121000003 10
 
0.1%
112000005 10
 
0.1%
111000006 10
 
0.1%
Other values (3665) 6663
98.4%
ValueCountFrequency (%)
100000001 3
< 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%
100000017 1
 
< 0.1%
ValueCountFrequency (%)
999800005 2
< 0.1%
999800004 1
 
< 0.1%
999033574 4
0.1%
998502964 1
 
< 0.1%
998501980 1
 
< 0.1%
998501976 1
 
< 0.1%
998501932 1
 
< 0.1%
998501931 1
 
< 0.1%
998001700 1
 
< 0.1%
990070001 2
< 0.1%

버스정류장ARS번호
Text

Distinct3642
Distinct (%)53.8%
Missing0
Missing (%)0.0%
Memory size53.0 KiB
2024-05-04T04:38:13.251143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.9905479
Min length1

Characters and Unicode

Total characters33791
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

Unique2131 ?
Unique (%)31.5%

Sample

1st row12192
2nd row49602
3rd row49606
4th row06168
5th row48637
ValueCountFrequency (%)
16
 
0.2%
22005 12
 
0.2%
22007 12
 
0.2%
22006 11
 
0.2%
22008 11
 
0.2%
22009 11
 
0.2%
01007 11
 
0.2%
22003 10
 
0.1%
01009 10
 
0.1%
12004 10
 
0.1%
Other values (3632) 6657
98.3%
2024-05-04T04:38:14.782921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6731
19.9%
0 6216
18.4%
2 4525
13.4%
3 3550
10.5%
4 2693
8.0%
6 2612
 
7.7%
5 2304
 
6.8%
7 2059
 
6.1%
8 1751
 
5.2%
9 1334
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33775
> 99.9%
Math Symbol 16
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6731
19.9%
0 6216
18.4%
2 4525
13.4%
3 3550
10.5%
4 2693
8.0%
6 2612
 
7.7%
5 2304
 
6.8%
7 2059
 
6.1%
8 1751
 
5.2%
9 1334
 
3.9%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33791
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6731
19.9%
0 6216
18.4%
2 4525
13.4%
3 3550
10.5%
4 2693
8.0%
6 2612
 
7.7%
5 2304
 
6.8%
7 2059
 
6.1%
8 1751
 
5.2%
9 1334
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33791
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6731
19.9%
0 6216
18.4%
2 4525
13.4%
3 3550
10.5%
4 2693
8.0%
6 2612
 
7.7%
5 2304
 
6.8%
7 2059
 
6.1%
8 1751
 
5.2%
9 1334
 
3.9%

역명
Text

Distinct6475
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size53.0 KiB
2024-05-04T04:38:15.569948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length15.103234
Min length9

Characters and Unicode

Total characters102264
Distinct characters542
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

Unique6242 ?
Unique (%)92.2%

Sample

1st row신도중학교(00009)
2nd row성남시청전면(00095)
3rd row모란차량기지앞(00093)
4th row성남시청후문앞(00094)
5th row공군부대제2정문.면회실(00086)
ValueCountFrequency (%)
군포공영차고지(00001 6
 
0.1%
군포보건소(00002 5
 
0.1%
덕은교.은평차고지앞(00002 5
 
0.1%
은평공영차고지(00001 5
 
0.1%
미금초등학교(00007 4
 
0.1%
주공4단지(00004 4
 
0.1%
광명차고지(00001 4
 
0.1%
동해운수(00001 4
 
0.1%
lg아파트.무지개마을사거리.신한아파트(00003 4
 
0.1%
수색교(00003 4
 
0.1%
Other values (6465) 6726
99.3%
2024-05-04T04:38:16.895595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21413
 
20.9%
) 7034
 
6.9%
( 7034
 
6.9%
1 2525
 
2.5%
. 2265
 
2.2%
2 1767
 
1.7%
3 1613
 
1.6%
4 1534
 
1.5%
5 1466
 
1.4%
6 1425
 
1.4%
Other values (532) 54188
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49972
48.9%
Decimal Number 35297
34.5%
Close Punctuation 7034
 
6.9%
Open Punctuation 7034
 
6.9%
Other Punctuation 2278
 
2.2%
Uppercase Letter 623
 
0.6%
Lowercase Letter 24
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 1391
 
2.8%
동 1350
 
2.7%
교 1224
 
2.4%
지 1070
 
2.1%
구 1001
 
2.0%
파 961
 
1.9%
아 919
 
1.8%
트 892
 
1.8%
학 873
 
1.7%
서 841
 
1.7%
Other values (492) 39450
78.9%
Uppercase Letter
ValueCountFrequency (%)
C 101
16.2%
K 84
13.5%
M 81
13.0%
T 81
13.0%
D 76
12.2%
G 41
6.6%
L 38
 
6.1%
S 27
 
4.3%
B 21
 
3.4%
N 13
 
2.1%
Other values (11) 60
9.6%
Decimal Number
ValueCountFrequency (%)
0 21413
60.7%
1 2525
 
7.2%
2 1767
 
5.0%
3 1613
 
4.6%
4 1534
 
4.3%
5 1466
 
4.2%
6 1425
 
4.0%
7 1301
 
3.7%
8 1173
 
3.3%
9 1080
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 2265
99.4%
& 11
 
0.5%
? 2
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 22
91.7%
k 1
 
4.2%
t 1
 
4.2%
Close Punctuation
ValueCountFrequency (%)
) 7034
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7034
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51645
50.5%
Hangul 49972
48.9%
Latin 647
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 1391
 
2.8%
동 1350
 
2.7%
교 1224
 
2.4%
지 1070
 
2.1%
구 1001
 
2.0%
파 961
 
1.9%
아 919
 
1.8%
트 892
 
1.8%
학 873
 
1.7%
서 841
 
1.7%
Other values (492) 39450
78.9%
Latin
ValueCountFrequency (%)
C 101
15.6%
K 84
13.0%
M 81
12.5%
T 81
12.5%
D 76
11.7%
G 41
6.3%
L 38
 
5.9%
S 27
 
4.2%
e 22
 
3.4%
B 21
 
3.2%
Other values (14) 75
11.6%
Common
ValueCountFrequency (%)
0 21413
41.5%
) 7034
 
13.6%
( 7034
 
13.6%
1 2525
 
4.9%
. 2265
 
4.4%
2 1767
 
3.4%
3 1613
 
3.1%
4 1534
 
3.0%
5 1466
 
2.8%
6 1425
 
2.8%
Other values (6) 3569
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52292
51.1%
Hangul 49972
48.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21413
40.9%
) 7034
 
13.5%
( 7034
 
13.5%
1 2525
 
4.8%
. 2265
 
4.3%
2 1767
 
3.4%
3 1613
 
3.1%
4 1534
 
2.9%
5 1466
 
2.8%
6 1425
 
2.7%
Other values (30) 4216
 
8.1%
Hangul
ValueCountFrequency (%)
역 1391
 
2.8%
동 1350
 
2.7%
교 1224
 
2.4%
지 1070
 
2.1%
구 1001
 
2.0%
파 961
 
1.9%
아 919
 
1.8%
트 892
 
1.8%
학 873
 
1.7%
서 841
 
1.7%
Other values (492) 39450
78.9%

승차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct395
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.124206
Minimum0
Maximum1168
Zeros504
Zeros (%)7.4%
Negative0
Negative (%)0.0%
Memory size59.6 KiB
2024-05-04T04:38:17.523418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median29
Q375
95-th percentile207.5
Maximum1168
Range1168
Interquartile range (IQR)68

Descriptive statistics

Standard deviation82.366767
Coefficient of variation (CV)1.441889
Kurtosis22.277642
Mean57.124206
Median Absolute Deviation (MAD)26
Skewness3.6286915
Sum386788
Variance6784.2843
MonotonicityNot monotonic
2024-05-04T04:38:18.232428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 504
 
7.4%
1 324
 
4.8%
2 243
 
3.6%
4 183
 
2.7%
3 180
 
2.7%
5 131
 
1.9%
7 129
 
1.9%
6 114
 
1.7%
9 103
 
1.5%
8 103
 
1.5%
Other values (385) 4757
70.3%
ValueCountFrequency (%)
0 504
7.4%
1 324
4.8%
2 243
3.6%
3 180
 
2.7%
4 183
 
2.7%
5 131
 
1.9%
6 114
 
1.7%
7 129
 
1.9%
8 103
 
1.5%
9 103
 
1.5%
ValueCountFrequency (%)
1168 1
< 0.1%
1069 1
< 0.1%
934 1
< 0.1%
762 1
< 0.1%
752 1
< 0.1%
725 1
< 0.1%
701 1
< 0.1%
686 1
< 0.1%
682 1
< 0.1%
672 1
< 0.1%

하차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct375
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.976518
Minimum0
Maximum964
Zeros357
Zeros (%)5.3%
Negative0
Negative (%)0.0%
Memory size59.6 KiB
2024-05-04T04:38:18.691398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median29
Q374.5
95-th percentile196.5
Maximum964
Range964
Interquartile range (IQR)66.5

Descriptive statistics

Standard deviation77.813542
Coefficient of variation (CV)1.3901104
Kurtosis21.397946
Mean55.976518
Median Absolute Deviation (MAD)25
Skewness3.5984095
Sum379017
Variance6054.9473
MonotonicityNot monotonic
2024-05-04T04:38:19.216559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 357
 
5.3%
1 262
 
3.9%
2 223
 
3.3%
4 206
 
3.0%
3 198
 
2.9%
6 138
 
2.0%
5 134
 
2.0%
7 132
 
1.9%
8 120
 
1.8%
10 110
 
1.6%
Other values (365) 4891
72.2%
ValueCountFrequency (%)
0 357
5.3%
1 262
3.9%
2 223
3.3%
3 198
2.9%
4 206
3.0%
5 134
 
2.0%
6 138
 
2.0%
7 132
 
1.9%
8 120
 
1.8%
9 106
 
1.6%
ValueCountFrequency (%)
964 1
< 0.1%
853 1
< 0.1%
844 1
< 0.1%
804 1
< 0.1%
783 1
< 0.1%
758 1
< 0.1%
751 1
< 0.1%
720 1
< 0.1%
705 1
< 0.1%
703 1
< 0.1%

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.0 KiB
20231004
6771 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20231004
2nd row20231004
3rd row20231004
4th row20231004
5th row20231004

Common Values

ValueCountFrequency (%)
20231004 6771
100.0%

Length

2024-05-04T04:38:19.651433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:38:19.956314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20231004 6771
100.0%

Interactions

2024-05-04T04:38:03.011402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:01.238707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:02.043421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:03.339417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:01.498581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:02.391409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:03.798838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:01.771311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:38:02.702088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T04:38:20.157899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선명표준버스정류장ID승차총승객수하차총승객수
노선번호1.0001.0000.7010.4340.462
노선명1.0001.0000.7010.4310.463
표준버스정류장ID0.7010.7011.0000.2040.190
승차총승객수0.4340.4310.2041.0000.404
하차총승객수0.4620.4630.1900.4041.000
2024-05-04T04:38:20.552304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준버스정류장ID승차총승객수하차총승객수
표준버스정류장ID1.000-0.166-0.160
승차총승객수-0.1661.0000.548
하차총승객수-0.1600.5481.000

Missing values

2024-05-04T04:38:04.410487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T04:38:05.472975image/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
020231001720720번(기자촌~답십리)11100010412192신도중학교(00009)1055520231004
12023100194089408번(구미동차고지~고속터미널)20500024549602성남시청전면(00095)12420231004
22023100194089408번(구미동차고지~고속터미널)20500024449606모란차량기지앞(00093)0420231004
32023100194089408번(구미동차고지~고속터미널)20500017206168성남시청후문앞(00094)1820231004
42023100194089408번(구미동차고지~고속터미널)20400022248637공군부대제2정문.면회실(00086)5720231004
52023100194089408번(구미동차고지~고속터미널)20400015548612시흥동주민센터(00091)0120231004
62023100194089408번(구미동차고지~고속터미널)20400015448613시흥동주민센터(00030)1420231004
72023100194089408번(구미동차고지~고속터미널)20400006248089성남농협대왕지점.고등동우체국(00088)124320231004
82023100194089408번(구미동차고지~고속터미널)20400005748077공군아파트(00085)7520231004
92023100194089408번(구미동차고지~고속터미널)20400004648085등자리(00034)4220231004
사용일자노선번호노선명표준버스정류장ID버스정류장ARS번호역명승차총승객수하차총승객수등록일자
67612023100124122412번(성수동~세곡동사거리)12200069923454대왕초등학교(00039)121320231004
67622023100123122312번(강동공영차고지~중랑공영차고지)10600001807112상봉2동복합청사.도서관(00041)4920231004
67632023100124122412번(성수동~세곡동사거리)12200070123538강남현대힐스테이트에코(00046)2422020231004
67642023100124122412번(성수동~세곡동사거리)12200070223530강남더샵라르고오피스텔(00032)2622520231004
67652023100123112311번(중랑차고지~문정동)10500005706143휘경여중고휘경주공아파트(00099)182920231004
67662023100123122312번(강동공영차고지~중랑공영차고지)10600001907113면목2동주민센터(00069)5420231004
67672023100124122412번(성수동~세곡동사거리)12200071823150고속철도수서역(00049)47812120231004
67682023100124122412번(성수동~세곡동사거리)12200074323440LH수서아파트(00047)53420231004
67692023100123122312번(강동공영차고지~중랑공영차고지)10600002007114중목초등학교(00040)01120231004
67702023100124122412번(성수동~세곡동사거리)12200074423441LH수서아파트(00031)15720231004