Overview

Dataset statistics

Number of variables9
Number of observations6735
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory506.6 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 412 (6.1%) zerosZeros
하차총승객수 has 240 (3.6%) zerosZeros

Reproduction

Analysis started2024-05-04 04:39:06.581595
Analysis finished2024-05-04 04:39:11.767917
Duration5.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size52.7 KiB
20231201
6735 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20231201
2nd row20231201
3rd row20231201
4th row20231201
5th row20231201

Common Values

ValueCountFrequency (%)
20231201 6735
100.0%

Length

2024-05-04T04:39:12.096290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:39:12.522684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20231201 6735
100.0%

노선번호
Text

Distinct86
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size52.7 KiB
2024-05-04T04:39:13.332632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.562435
Min length3

Characters and Unicode

Total characters23993
Distinct characters20
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

Unique7 ?
Unique (%)0.1%

Sample

1st row100
2nd row542
3rd row542
4th row542
5th row542
ValueCountFrequency (%)
n26 252
 
3.7%
n37 209
 
3.1%
542 137
 
2.0%
9701 127
 
1.9%
441 126
 
1.9%
661 125
 
1.9%
302 124
 
1.8%
541 122
 
1.8%
9403 120
 
1.8%
9408 119
 
1.8%
Other values (76) 5274
78.3%
2024-05-04T04:39:14.820737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 3574
14.9%
0 3245
13.5%
5 3127
13.0%
1 2646
11.0%
2 2405
10.0%
4 2273
9.5%
3 2261
9.4%
6 2219
9.2%
9 865
 
3.6%
N 461
 
1.9%
Other values (10) 917
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23043
96.0%
Uppercase Letter 682
 
2.8%
Other Letter 250
 
1.0%
Dash Punctuation 18
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 3574
15.5%
0 3245
14.1%
5 3127
13.6%
1 2646
11.5%
2 2405
10.4%
4 2273
9.9%
3 2261
9.8%
6 2219
9.6%
9 865
 
3.8%
8 428
 
1.9%
Other Letter
ValueCountFrequency (%)
강 77
30.8%
동 77
30.8%
서 47
18.8%
울 47
18.8%
성 1
 
0.4%
북 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N 461
67.6%
B 149
 
21.8%
A 72
 
10.6%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23061
96.1%
Latin 682
 
2.8%
Hangul 250
 
1.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 3574
15.5%
0 3245
14.1%
5 3127
13.6%
1 2646
11.5%
2 2405
10.4%
4 2273
9.9%
3 2261
9.8%
6 2219
9.6%
9 865
 
3.8%
8 428
 
1.9%
Hangul
ValueCountFrequency (%)
강 77
30.8%
동 77
30.8%
서 47
18.8%
울 47
18.8%
성 1
 
0.4%
북 1
 
0.4%
Latin
ValueCountFrequency (%)
N 461
67.6%
B 149
 
21.8%
A 72
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23743
99.0%
Hangul 250
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 3574
15.1%
0 3245
13.7%
5 3127
13.2%
1 2646
11.1%
2 2405
10.1%
4 2273
9.6%
3 2261
9.5%
6 2219
9.3%
9 865
 
3.6%
N 461
 
1.9%
Other values (4) 667
 
2.8%
Hangul
ValueCountFrequency (%)
강 77
30.8%
동 77
30.8%
서 47
18.8%
울 47
18.8%
성 1
 
0.4%
북 1
 
0.4%

노선명
Text

Distinct88
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size52.7 KiB
2024-05-04T04:39:15.556163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length21
Mean length17.003712
Min length12

Characters and Unicode

Total characters114520
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

Unique7 ?
Unique (%)0.1%

Sample

1st row100번(하계동~용산구청)
2nd row542번(군포버스공영차고지~신사역)
3rd row542번(군포버스공영차고지~신사역)
4th row542번(군포버스공영차고지~신사역)
5th row542번(군포버스공영차고지~신사역)
ValueCountFrequency (%)
542번(군포버스공영차고지~신사역 137
 
2.0%
n26번(중랑공영차고지~강서공영차고지 127
 
1.8%
9701번(가좌동~서울역 127
 
1.8%
441번(월암공영차고지~신사사거리 126
 
1.8%
661번(부천상동~영등포역,신세계백화점 125
 
1.8%
n26번(강서공영차고지~중랑공영차고지 125
 
1.8%
302번(성남~동대문 124
 
1.8%
541번(군포공영차고지~강남역 122
 
1.7%
9403번(구미동차고지~중곡역 120
 
1.7%
공영차고지~여의도 119
 
1.7%
Other values (81) 5758
82.1%
2024-05-04T04:39:16.857917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 6900
 
6.0%
) 6900
 
6.0%
~ 6735
 
5.9%
번 6428
 
5.6%
동 4179
 
3.6%
고 3851
 
3.4%
지 3791
 
3.3%
7 3574
 
3.1%
차 3539
 
3.1%
0 3245
 
2.8%
Other values (165) 65378
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69233
60.5%
Decimal Number 23189
 
20.2%
Open Punctuation 6900
 
6.0%
Close Punctuation 6900
 
6.0%
Math Symbol 6735
 
5.9%
Uppercase Letter 718
 
0.6%
Other Punctuation 552
 
0.5%
Space Separator 275
 
0.2%
Dash Punctuation 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 6428
 
9.3%
동 4179
 
6.0%
고 3851
 
5.6%
지 3791
 
5.5%
차 3539
 
5.1%
영 3016
 
4.4%
역 2893
 
4.2%
공 2669
 
3.9%
대 1744
 
2.5%
서 1730
 
2.5%
Other values (144) 35393
51.1%
Decimal Number
ValueCountFrequency (%)
7 3574
15.4%
0 3245
14.0%
5 3127
13.5%
1 2791
12.0%
2 2405
10.4%
4 2274
9.8%
3 2261
9.8%
6 2219
9.6%
9 865
 
3.7%
8 428
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
N 461
64.2%
B 149
 
20.8%
A 90
 
12.5%
K 18
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 415
75.2%
. 137
 
24.8%
Open Punctuation
ValueCountFrequency (%)
( 6900
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6900
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6735
100.0%
Space Separator
ValueCountFrequency (%)
275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69233
60.5%
Common 44569
38.9%
Latin 718
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 6428
 
9.3%
동 4179
 
6.0%
고 3851
 
5.6%
지 3791
 
5.5%
차 3539
 
5.1%
영 3016
 
4.4%
역 2893
 
4.2%
공 2669
 
3.9%
대 1744
 
2.5%
서 1730
 
2.5%
Other values (144) 35393
51.1%
Common
ValueCountFrequency (%)
( 6900
15.5%
) 6900
15.5%
~ 6735
15.1%
7 3574
8.0%
0 3245
7.3%
5 3127
7.0%
1 2791
6.3%
2 2405
 
5.4%
4 2274
 
5.1%
3 2261
 
5.1%
Other values (7) 4357
9.8%
Latin
ValueCountFrequency (%)
N 461
64.2%
B 149
 
20.8%
A 90
 
12.5%
K 18
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69233
60.5%
ASCII 45287
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 6900
15.2%
) 6900
15.2%
~ 6735
14.9%
7 3574
7.9%
0 3245
7.2%
5 3127
6.9%
1 2791
6.2%
2 2405
 
5.3%
4 2274
 
5.0%
3 2261
 
5.0%
Other values (11) 5075
11.2%
Hangul
ValueCountFrequency (%)
번 6428
 
9.3%
동 4179
 
6.0%
고 3851
 
5.6%
지 3791
 
5.5%
차 3539
 
5.1%
영 3016
 
4.4%
역 2893
 
4.2%
공 2669
 
3.9%
대 1744
 
2.5%
서 1730
 
2.5%
Other values (144) 35393
51.1%

표준버스정류장ID
Real number (ℝ)

Distinct3604
Distinct (%)53.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5555136 × 108
Minimum1 × 108
Maximum9.998 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size59.3 KiB
2024-05-04T04:39:17.342251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1 × 108
5-th percentile1.0200001 × 108
Q11.1200041 × 108
median1.2100001 × 108
Q32.1300002 × 108
95-th percentile2.2500001 × 108
Maximum9.998 × 108
Range8.998 × 108
Interquartile range (IQR)1.0099961 × 108

Descriptive statistics

Standard deviation65504791
Coefficient of variation (CV)0.42111357
Kurtosis66.479233
Mean1.5555136 × 108
Median Absolute Deviation (MAD)15000005
Skewness5.5038033
Sum1.0476384 × 1012
Variance4.2908776 × 1015
MonotonicityNot monotonic
2024-05-04T04:39:17.846033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
117000003 11
 
0.2%
121000010 11
 
0.2%
117000002 10
 
0.1%
121000004 10
 
0.1%
121000005 10
 
0.1%
121000006 10
 
0.1%
121000007 10
 
0.1%
121000008 10
 
0.1%
121000009 10
 
0.1%
121000012 10
 
0.1%
Other values (3594) 6633
98.5%
ValueCountFrequency (%)
100000001 2
< 0.1%
100000002 2
< 0.1%
100000003 2
< 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%
999800003 1
 
< 0.1%
999033574 4
0.1%
998502269 1
 
< 0.1%
998501980 2
< 0.1%
998501932 1
 
< 0.1%
998501931 2
< 0.1%
998001700 2
< 0.1%
990032570 1
 
< 0.1%
990014944 1
 
< 0.1%

버스정류장ARS번호
Text

Distinct3571
Distinct (%)53.0%
Missing0
Missing (%)0.0%
Memory size52.7 KiB
2024-05-04T04:39:18.762640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.9899035
Min length1

Characters and Unicode

Total characters33607
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

Unique2013 ?
Unique (%)29.9%

Sample

1st row01002
2nd row22282
3rd row22281
4th row22276
5th row22275
ValueCountFrequency (%)
17
 
0.3%
18003 11
 
0.2%
22010 11
 
0.2%
22009 10
 
0.1%
22007 10
 
0.1%
22006 10
 
0.1%
18002 10
 
0.1%
18004 10
 
0.1%
22004 10
 
0.1%
22008 10
 
0.1%
Other values (3561) 6626
98.4%
2024-05-04T04:39:20.398438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6494
19.3%
0 5864
17.4%
2 4475
13.3%
3 3754
11.2%
4 2772
8.2%
6 2559
 
7.6%
5 2317
 
6.9%
7 2059
 
6.1%
8 1876
 
5.6%
9 1420
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33590
99.9%
Math Symbol 17
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6494
19.3%
0 5864
17.5%
2 4475
13.3%
3 3754
11.2%
4 2772
8.3%
6 2559
 
7.6%
5 2317
 
6.9%
7 2059
 
6.1%
8 1876
 
5.6%
9 1420
 
4.2%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33607
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6494
19.3%
0 5864
17.4%
2 4475
13.3%
3 3754
11.2%
4 2772
8.2%
6 2559
 
7.6%
5 2317
 
6.9%
7 2059
 
6.1%
8 1876
 
5.6%
9 1420
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33607
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6494
19.3%
0 5864
17.4%
2 4475
13.3%
3 3754
11.2%
4 2772
8.2%
6 2559
 
7.6%
5 2317
 
6.9%
7 2059
 
6.1%
8 1876
 
5.6%
9 1420
 
4.2%

역명
Text

Distinct6305
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size52.7 KiB
2024-05-04T04:39:21.140035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length15.134224
Min length9

Characters and Unicode

Total characters101929
Distinct characters541
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

Unique5966 ?
Unique (%)88.6%

Sample

1st row창경궁.서울대학교병원(00031)
2nd row서울시품질시험소한국교원단체총연합회(00057)
3rd row서울시품질시험소한국교원단체총연합회(00082)
4th row우성아파트.양재초등학교(00060)
5th row우성아파트.양재초등학교(00079)
ValueCountFrequency (%)
군포공영차고지(00001 6
 
0.1%
하안버스공영차고지(00002 6
 
0.1%
광명차고지(00001 6
 
0.1%
덕은교.은평차고지앞(00002 5
 
0.1%
군포보건소(00002 5
 
0.1%
은평공영차고지(00001 5
 
0.1%
대우.롯데아파트상가(00008 4
 
0.1%
lg아파트.무지개마을사거리.신한아파트(00003 4
 
0.1%
주공4단지(00004 4
 
0.1%
하얀마을.그랜드빌.벽산빌라(00005 4
 
0.1%
Other values (6295) 6686
99.3%
2024-05-04T04:39:22.311654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21378
 
21.0%
) 7001
 
6.9%
( 7001
 
6.9%
1 2437
 
2.4%
. 2323
 
2.3%
2 1762
 
1.7%
3 1611
 
1.6%
4 1507
 
1.5%
5 1459
 
1.4%
6 1395
 
1.4%
Other values (531) 54055
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49913
49.0%
Decimal Number 35079
34.4%
Close Punctuation 7001
 
6.9%
Open Punctuation 7001
 
6.9%
Other Punctuation 2330
 
2.3%
Uppercase Letter 579
 
0.6%
Lowercase Letter 24
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 1334
 
2.7%
동 1288
 
2.6%
교 1219
 
2.4%
지 1081
 
2.2%
구 1005
 
2.0%
파 949
 
1.9%
아 890
 
1.8%
트 888
 
1.8%
학 853
 
1.7%
대 836
 
1.7%
Other values (491) 39570
79.3%
Uppercase Letter
ValueCountFrequency (%)
C 99
17.1%
K 75
13.0%
M 75
13.0%
D 71
12.3%
T 67
11.6%
G 39
 
6.7%
L 38
 
6.6%
S 26
 
4.5%
B 20
 
3.5%
N 11
 
1.9%
Other values (11) 58
10.0%
Decimal Number
ValueCountFrequency (%)
0 21378
60.9%
1 2437
 
6.9%
2 1762
 
5.0%
3 1611
 
4.6%
4 1507
 
4.3%
5 1459
 
4.2%
6 1395
 
4.0%
7 1305
 
3.7%
8 1168
 
3.3%
9 1057
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 2323
99.7%
& 6
 
0.3%
? 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 22
91.7%
t 1
 
4.2%
k 1
 
4.2%
Close Punctuation
ValueCountFrequency (%)
) 7001
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7001
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51413
50.4%
Hangul 49913
49.0%
Latin 603
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 1334
 
2.7%
동 1288
 
2.6%
교 1219
 
2.4%
지 1081
 
2.2%
구 1005
 
2.0%
파 949
 
1.9%
아 890
 
1.8%
트 888
 
1.8%
학 853
 
1.7%
대 836
 
1.7%
Other values (491) 39570
79.3%
Latin
ValueCountFrequency (%)
C 99
16.4%
K 75
12.4%
M 75
12.4%
D 71
11.8%
T 67
11.1%
G 39
 
6.5%
L 38
 
6.3%
S 26
 
4.3%
e 22
 
3.6%
B 20
 
3.3%
Other values (14) 71
11.8%
Common
ValueCountFrequency (%)
0 21378
41.6%
) 7001
 
13.6%
( 7001
 
13.6%
1 2437
 
4.7%
. 2323
 
4.5%
2 1762
 
3.4%
3 1611
 
3.1%
4 1507
 
2.9%
5 1459
 
2.8%
6 1395
 
2.7%
Other values (6) 3539
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52016
51.0%
Hangul 49913
49.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21378
41.1%
) 7001
 
13.5%
( 7001
 
13.5%
1 2437
 
4.7%
. 2323
 
4.5%
2 1762
 
3.4%
3 1611
 
3.1%
4 1507
 
2.9%
5 1459
 
2.8%
6 1395
 
2.7%
Other values (30) 4142
 
8.0%
Hangul
ValueCountFrequency (%)
역 1334
 
2.7%
동 1288
 
2.6%
교 1219
 
2.4%
지 1081
 
2.2%
구 1005
 
2.0%
파 949
 
1.9%
아 890
 
1.8%
트 888
 
1.8%
학 853
 
1.7%
대 836
 
1.7%
Other values (491) 39570
79.3%

승차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct596
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean107.85212
Minimum0
Maximum1563
Zeros412
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size59.3 KiB
2024-05-04T04:39:22.924578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113
median61
Q3151
95-th percentile369
Maximum1563
Range1563
Interquartile range (IQR)138

Descriptive statistics

Standard deviation141.45355
Coefficient of variation (CV)1.311551
Kurtosis16.673412
Mean107.85212
Median Absolute Deviation (MAD)55
Skewness3.1161521
Sum726384
Variance20009.107
MonotonicityNot monotonic
2024-05-04T04:39:23.555367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 412
 
6.1%
1 192
 
2.9%
2 170
 
2.5%
4 124
 
1.8%
3 121
 
1.8%
6 110
 
1.6%
5 88
 
1.3%
8 81
 
1.2%
7 78
 
1.2%
9 73
 
1.1%
Other values (586) 5286
78.5%
ValueCountFrequency (%)
0 412
6.1%
1 192
2.9%
2 170
2.5%
3 121
 
1.8%
4 124
 
1.8%
5 88
 
1.3%
6 110
 
1.6%
7 78
 
1.2%
8 81
 
1.2%
9 73
 
1.1%
ValueCountFrequency (%)
1563 1
< 0.1%
1522 1
< 0.1%
1521 1
< 0.1%
1491 1
< 0.1%
1484 1
< 0.1%
1438 1
< 0.1%
1400 1
< 0.1%
1274 1
< 0.1%
1206 1
< 0.1%
1179 1
< 0.1%

하차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct566
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105.90557
Minimum0
Maximum1643
Zeros240
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size59.3 KiB
2024-05-04T04:39:24.185336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q115
median62
Q3147
95-th percentile353.3
Maximum1643
Range1643
Interquartile range (IQR)132

Descriptive statistics

Standard deviation137.11048
Coefficient of variation (CV)1.2946485
Kurtosis19.272316
Mean105.90557
Median Absolute Deviation (MAD)54
Skewness3.3239531
Sum713274
Variance18799.284
MonotonicityNot monotonic
2024-05-04T04:39:24.782587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 240
 
3.6%
1 198
 
2.9%
3 150
 
2.2%
2 144
 
2.1%
4 131
 
1.9%
5 109
 
1.6%
6 101
 
1.5%
8 93
 
1.4%
7 91
 
1.4%
10 70
 
1.0%
Other values (556) 5408
80.3%
ValueCountFrequency (%)
0 240
3.6%
1 198
2.9%
2 144
2.1%
3 150
2.2%
4 131
1.9%
5 109
1.6%
6 101
1.5%
7 91
 
1.4%
8 93
 
1.4%
9 66
 
1.0%
ValueCountFrequency (%)
1643 1
< 0.1%
1610 1
< 0.1%
1550 1
< 0.1%
1454 1
< 0.1%
1449 2
< 0.1%
1230 1
< 0.1%
1186 1
< 0.1%
1133 1
< 0.1%
1123 1
< 0.1%
1068 1
< 0.1%

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size52.7 KiB
20231204
6735 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20231204
2nd row20231204
3rd row20231204
4th row20231204
5th row20231204

Common Values

ValueCountFrequency (%)
20231204 6735
100.0%

Length

2024-05-04T04:39:25.309335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:39:25.666075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20231204 6735
100.0%

Interactions

2024-05-04T04:39:10.070134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:39:08.263897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:39:09.190555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:39:10.350512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:39:08.524190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:39:09.468815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:39:10.638842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:39:08.792372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:39:09.764158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T04:39:25.893811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선명표준버스정류장ID승차총승객수하차총승객수
노선번호1.0001.0000.6510.4720.455
노선명1.0001.0000.6510.4710.454
표준버스정류장ID0.6510.6511.0000.2180.223
승차총승객수0.4720.4710.2181.0000.509
하차총승객수0.4550.4540.2230.5091.000
2024-05-04T04:39:26.347615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준버스정류장ID승차총승객수하차총승객수
표준버스정류장ID1.000-0.196-0.202
승차총승객수-0.1961.0000.572
하차총승객수-0.2020.5721.000

Missing values

2024-05-04T04:39:11.018248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T04:39:11.590692image/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
020231201100100번(하계동~용산구청)10000000201002창경궁.서울대학교병원(00031)9814520231204
120231201542542번(군포버스공영차고지~신사역)12100020622282서울시품질시험소한국교원단체총연합회(00057)332220231204
220231201542542번(군포버스공영차고지~신사역)12100020522281서울시품질시험소한국교원단체총연합회(00082)333720231204
320231201542542번(군포버스공영차고지~신사역)12100020022276우성아파트.양재초등학교(00060)1095120231204
420231201542542번(군포버스공영차고지~신사역)12100019922275우성아파트.양재초등학교(00079)246720231204
520231201542542번(군포버스공영차고지~신사역)12100019822274현대빌라.에코맘코리아(00061)606920231204
620231201542542번(군포버스공영차고지~신사역)12100019722273현대빌라.에코맘코리아(00078)264320231204
720231201542542번(군포버스공영차고지~신사역)12100001522015신사역.푸른저축은행(00070)761120231204
820231201542542번(군포버스공영차고지~신사역)12100001422014논현역(00067)1310920231204
920231201542542번(군포버스공영차고지~신사역)12100001322013논현역(00071)913020231204
사용일자노선번호노선명표준버스정류장ID버스정류장ARS번호역명승차총승객수하차총승객수등록일자
67252023120181018101번(도봉보건소~서소문)10000039001015종로3가.탑골공원(00033)2220231204
67262023120181018101번(도봉보건소~서소문)10000038601011종로1가(00031)3020231204
67272023120181018101번(도봉보건소~서소문)10000039101016종로3가.탑골공원(00022)13520231204
67282023120181018101번(도봉보건소~서소문)10000039301018종로4가.종묘(00021)12820231204
67292023120181018101번(도봉보건소~서소문)10100001802110경찰청.동북아역사재단(00026)101620231204
67302023120181018101번(도봉보건소~서소문)10100003802135시청.서소문청사(00025)104520231204
67312023120181018101번(도봉보건소~서소문)10100005802157을지로입구.시청입구(00024)04620231204
67322023120181018101번(도봉보건소~서소문)10100015702262서대문경찰서.농협은행.유관순활동터(00027)4420231204
67332023120181018101번(도봉보건소~서소문)10100026202281서대문역사거리.농협중앙회(00028)201220231204
67342023120181018101번(도봉보건소~서소문)10700000108001길음2동주민센터(00012)15220231204