Overview

Dataset statistics

Number of variables9
Number of observations7178
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory539.9 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 425 (5.9%) zerosZeros
하차총승객수 has 304 (4.2%) zerosZeros

Reproduction

Analysis started2024-05-04 04:39:59.791086
Analysis finished2024-05-04 04:40:06.825883
Duration7.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size56.2 KiB
20240201
7178 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20240201
2nd row20240201
3rd row20240201
4th row20240201
5th row20240201

Common Values

ValueCountFrequency (%)
20240201 7178
100.0%

Length

2024-05-04T04:40:07.044544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:40:07.448003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20240201 7178
100.0%

노선번호
Text

Distinct93
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size56.2 KiB
2024-05-04T04:40:08.145854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.5780162
Min length3

Characters and Unicode

Total characters25683
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row601
2nd row542
3rd row542
4th row542
5th row542
ValueCountFrequency (%)
n26 257
 
3.6%
n37 206
 
2.9%
542 138
 
1.9%
9701 127
 
1.8%
661 125
 
1.7%
441 124
 
1.7%
302 124
 
1.7%
541 123
 
1.7%
9403 121
 
1.7%
5623 120
 
1.7%
Other values (83) 5713
79.6%
2024-05-04T04:40:09.489346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 3844
15.0%
0 3351
13.0%
5 3206
12.5%
1 2947
11.5%
2 2514
9.8%
3 2507
9.8%
4 2383
9.3%
6 2295
8.9%
9 868
 
3.4%
8 739
 
2.9%
Other values (10) 1029
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24654
96.0%
Uppercase Letter 732
 
2.9%
Other Letter 280
 
1.1%
Dash Punctuation 17
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 3844
15.6%
0 3351
13.6%
5 3206
13.0%
1 2947
12.0%
2 2514
10.2%
3 2507
10.2%
4 2383
9.7%
6 2295
9.3%
9 868
 
3.5%
8 739
 
3.0%
Other Letter
ValueCountFrequency (%)
강 77
27.5%
동 77
27.5%
서 48
17.1%
울 48
17.1%
성 15
 
5.4%
북 15
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
N 513
70.1%
B 148
 
20.2%
A 71
 
9.7%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24671
96.1%
Latin 732
 
2.9%
Hangul 280
 
1.1%

Most frequent character per script

Common
ValueCountFrequency (%)
7 3844
15.6%
0 3351
13.6%
5 3206
13.0%
1 2947
11.9%
2 2514
10.2%
3 2507
10.2%
4 2383
9.7%
6 2295
9.3%
9 868
 
3.5%
8 739
 
3.0%
Hangul
ValueCountFrequency (%)
강 77
27.5%
동 77
27.5%
서 48
17.1%
울 48
17.1%
성 15
 
5.4%
북 15
 
5.4%
Latin
ValueCountFrequency (%)
N 513
70.1%
B 148
 
20.2%
A 71
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25403
98.9%
Hangul 280
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 3844
15.1%
0 3351
13.2%
5 3206
12.6%
1 2947
11.6%
2 2514
9.9%
3 2507
9.9%
4 2383
9.4%
6 2295
9.0%
9 868
 
3.4%
8 739
 
2.9%
Other values (4) 749
 
2.9%
Hangul
ValueCountFrequency (%)
강 77
27.5%
동 77
27.5%
서 48
17.1%
울 48
17.1%
성 15
 
5.4%
북 15
 
5.4%

노선명
Text

Distinct96
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size56.2 KiB
2024-05-04T04:40:10.241905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length21
Mean length17.032878
Min length12

Characters and Unicode

Total characters122262
Distinct characters188
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 row542번(군포버스공영차고지~신사역)
3rd row542번(군포버스공영차고지~신사역)
4th row542번(군포버스공영차고지~신사역)
5th row542번(군포버스공영차고지~신사역)
ValueCountFrequency (%)
542번(군포버스공영차고지~신사역 138
 
1.9%
n26번(강서공영차고지~중랑공영차고지 129
 
1.7%
n26번(중랑공영차고지~강서공영차고지 128
 
1.7%
9701번(가좌동~서울역 127
 
1.7%
661번(부천상동~영등포역,신세계백화점 125
 
1.7%
441번(월암공영차고지~신사사거리 124
 
1.7%
302번(성남~동대문 124
 
1.7%
541번(군포공영차고지~강남역 123
 
1.7%
9403번(구미동차고지~중곡역 121
 
1.6%
5623번(군포 120
 
1.6%
Other values (89) 6195
83.1%
2024-05-04T04:40:11.871877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 7344
 
6.0%
) 7344
 
6.0%
~ 7178
 
5.9%
번 6944
 
5.7%
동 4622
 
3.8%
고 3903
 
3.2%
7 3844
 
3.1%
지 3834
 
3.1%
차 3562
 
2.9%
0 3351
 
2.7%
Other values (178) 70336
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73926
60.5%
Decimal Number 24803
 
20.3%
Open Punctuation 7344
 
6.0%
Close Punctuation 7344
 
6.0%
Math Symbol 7178
 
5.9%
Uppercase Letter 732
 
0.6%
Other Punctuation 642
 
0.5%
Space Separator 276
 
0.2%
Dash Punctuation 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 6944
 
9.4%
동 4622
 
6.3%
고 3903
 
5.3%
지 3834
 
5.2%
차 3562
 
4.8%
역 3179
 
4.3%
영 3025
 
4.1%
공 2692
 
3.6%
대 1832
 
2.5%
서 1819
 
2.5%
Other values (158) 38514
52.1%
Decimal Number
ValueCountFrequency (%)
7 3844
15.5%
0 3351
13.5%
5 3206
12.9%
1 3090
12.5%
2 2514
10.1%
3 2507
10.1%
4 2389
9.6%
6 2295
9.3%
9 868
 
3.5%
8 739
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
N 513
70.1%
B 148
 
20.2%
A 71
 
9.7%
Other Punctuation
ValueCountFrequency (%)
, 411
64.0%
. 231
36.0%
Open Punctuation
ValueCountFrequency (%)
( 7344
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7344
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7178
100.0%
Space Separator
ValueCountFrequency (%)
276
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73926
60.5%
Common 47604
38.9%
Latin 732
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 6944
 
9.4%
동 4622
 
6.3%
고 3903
 
5.3%
지 3834
 
5.2%
차 3562
 
4.8%
역 3179
 
4.3%
영 3025
 
4.1%
공 2692
 
3.6%
대 1832
 
2.5%
서 1819
 
2.5%
Other values (158) 38514
52.1%
Common
ValueCountFrequency (%)
( 7344
15.4%
) 7344
15.4%
~ 7178
15.1%
7 3844
8.1%
0 3351
7.0%
5 3206
6.7%
1 3090
6.5%
2 2514
 
5.3%
3 2507
 
5.3%
4 2389
 
5.0%
Other values (7) 4837
10.2%
Latin
ValueCountFrequency (%)
N 513
70.1%
B 148
 
20.2%
A 71
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73926
60.5%
ASCII 48336
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 7344
15.2%
) 7344
15.2%
~ 7178
14.9%
7 3844
8.0%
0 3351
6.9%
5 3206
6.6%
1 3090
6.4%
2 2514
 
5.2%
3 2507
 
5.2%
4 2389
 
4.9%
Other values (10) 5569
11.5%
Hangul
ValueCountFrequency (%)
번 6944
 
9.4%
동 4622
 
6.3%
고 3903
 
5.3%
지 3834
 
5.2%
차 3562
 
4.8%
역 3179
 
4.3%
영 3025
 
4.1%
공 2692
 
3.6%
대 1832
 
2.5%
서 1819
 
2.5%
Other values (158) 38514
52.1%

표준버스정류장ID
Real number (ℝ)

Distinct3810
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5306551 × 108
Minimum1 × 108
Maximum9.998 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size63.2 KiB
2024-05-04T04:40:12.450589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1 × 108
5-th percentile1.02 × 108
Q11.1200014 × 108
median1.2000015 × 108
Q32.100003 × 108
95-th percentile2.2200197 × 108
Maximum9.998 × 108
Range8.998 × 108
Interquartile range (IQR)98000158

Descriptive statistics

Standard deviation65077803
Coefficient of variation (CV)0.42516309
Kurtosis68.889129
Mean1.5306551 × 108
Median Absolute Deviation (MAD)13999689
Skewness5.6743175
Sum1.0987042 × 1012
Variance4.2351204 × 1015
MonotonicityNot monotonic
2024-05-04T04:40:13.115453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
117000003 11
 
0.2%
121000010 11
 
0.2%
112000409 10
 
0.1%
121000012 10
 
0.1%
112000407 10
 
0.1%
112000408 10
 
0.1%
112000401 10
 
0.1%
112000416 10
 
0.1%
112000400 10
 
0.1%
112000398 10
 
0.1%
Other values (3800) 7076
98.6%
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%
998501975 1
 
< 0.1%
998501932 1
 
< 0.1%
998501931 1
 
< 0.1%

버스정류장ARS번호
Text

Distinct3775
Distinct (%)52.6%
Missing0
Missing (%)0.0%
Memory size56.2 KiB
2024-05-04T04:40:14.132519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.9899694
Min length1

Characters and Unicode

Total characters35818
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

Unique2150 ?
Unique (%)30.0%

Sample

1st row14194
2nd row22424
3rd row22291
4th row22288
5th row22287
ValueCountFrequency (%)
18
 
0.3%
18003 11
 
0.2%
22010 11
 
0.2%
22007 10
 
0.1%
13031 10
 
0.1%
13034 10
 
0.1%
13035 10
 
0.1%
13032 10
 
0.1%
13028 10
 
0.1%
22004 10
 
0.1%
Other values (3765) 7068
98.5%
2024-05-04T04:40:15.630544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7019
19.6%
0 6215
17.4%
2 4901
13.7%
3 3938
11.0%
4 2962
8.3%
6 2673
 
7.5%
5 2438
 
6.8%
7 2152
 
6.0%
8 1976
 
5.5%
9 1526
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35800
99.9%
Math Symbol 18
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7019
19.6%
0 6215
17.4%
2 4901
13.7%
3 3938
11.0%
4 2962
8.3%
6 2673
 
7.5%
5 2438
 
6.8%
7 2152
 
6.0%
8 1976
 
5.5%
9 1526
 
4.3%
Math Symbol
ValueCountFrequency (%)
~ 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35818
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7019
19.6%
0 6215
17.4%
2 4901
13.7%
3 3938
11.0%
4 2962
8.3%
6 2673
 
7.5%
5 2438
 
6.8%
7 2152
 
6.0%
8 1976
 
5.5%
9 1526
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35818
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7019
19.6%
0 6215
17.4%
2 4901
13.7%
3 3938
11.0%
4 2962
8.3%
6 2673
 
7.5%
5 2438
 
6.8%
7 2152
 
6.0%
8 1976
 
5.5%
9 1526
 
4.3%

역명
Text

Distinct6738
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size56.2 KiB
2024-05-04T04:40:16.346329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length15.138618
Min length9

Characters and Unicode

Total characters108665
Distinct characters549
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

Unique6389 ?
Unique (%)89.0%

Sample

1st row마포구청역(00057)
2nd row네이처힐5단지(00055)
3rd row일동제약사거리(00077)
4th row식유촌우면성당.서초호반써밋(00052)
5th row식유촌우면성당.서초호반써밋(00087)
ValueCountFrequency (%)
하안버스공영차고지(00002 6
 
0.1%
광명차고지(00001 6
 
0.1%
군포공영차고지(00001 6
 
0.1%
군포보건소(00002 5
 
0.1%
은평공영차고지(00001 5
 
0.1%
덕은교.은평차고지앞(00002 5
 
0.1%
오리초등학교(00006 4
 
0.1%
노온사동차고지(00001 4
 
0.1%
동해운수(00001 4
 
0.1%
더샵분당파크리버.헬스케어혁신파크(00010 4
 
0.1%
Other values (6728) 7129
99.3%
2024-05-04T04:40:17.403349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22818
 
21.0%
( 7444
 
6.9%
) 7444
 
6.9%
1 2642
 
2.4%
. 2454
 
2.3%
2 1916
 
1.8%
3 1730
 
1.6%
4 1606
 
1.5%
5 1537
 
1.4%
6 1461
 
1.3%
Other values (539) 57613
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53264
49.0%
Decimal Number 37420
34.4%
Open Punctuation 7444
 
6.9%
Close Punctuation 7444
 
6.9%
Other Punctuation 2461
 
2.3%
Uppercase Letter 606
 
0.6%
Lowercase Letter 24
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 1441
 
2.7%
동 1385
 
2.6%
교 1322
 
2.5%
지 1137
 
2.1%
구 1081
 
2.0%
파 1031
 
1.9%
아 975
 
1.8%
트 965
 
1.8%
학 922
 
1.7%
대 915
 
1.7%
Other values (499) 42090
79.0%
Uppercase Letter
ValueCountFrequency (%)
C 103
17.0%
M 81
13.4%
D 75
12.4%
K 72
11.9%
T 68
11.2%
G 41
 
6.8%
L 40
 
6.6%
S 28
 
4.6%
B 23
 
3.8%
N 13
 
2.1%
Other values (11) 62
10.2%
Decimal Number
ValueCountFrequency (%)
0 22818
61.0%
1 2642
 
7.1%
2 1916
 
5.1%
3 1730
 
4.6%
4 1606
 
4.3%
5 1537
 
4.1%
6 1461
 
3.9%
7 1360
 
3.6%
8 1226
 
3.3%
9 1124
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 2454
99.7%
& 6
 
0.2%
? 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 22
91.7%
t 1
 
4.2%
k 1
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 7444
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7444
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54771
50.4%
Hangul 53264
49.0%
Latin 630
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 1441
 
2.7%
동 1385
 
2.6%
교 1322
 
2.5%
지 1137
 
2.1%
구 1081
 
2.0%
파 1031
 
1.9%
아 975
 
1.8%
트 965
 
1.8%
학 922
 
1.7%
대 915
 
1.7%
Other values (499) 42090
79.0%
Latin
ValueCountFrequency (%)
C 103
16.3%
M 81
12.9%
D 75
11.9%
K 72
11.4%
T 68
10.8%
G 41
 
6.5%
L 40
 
6.3%
S 28
 
4.4%
B 23
 
3.7%
e 22
 
3.5%
Other values (14) 77
12.2%
Common
ValueCountFrequency (%)
0 22818
41.7%
( 7444
 
13.6%
) 7444
 
13.6%
1 2642
 
4.8%
. 2454
 
4.5%
2 1916
 
3.5%
3 1730
 
3.2%
4 1606
 
2.9%
5 1537
 
2.8%
6 1461
 
2.7%
Other values (6) 3719
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55401
51.0%
Hangul 53264
49.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22818
41.2%
( 7444
 
13.4%
) 7444
 
13.4%
1 2642
 
4.8%
. 2454
 
4.4%
2 1916
 
3.5%
3 1730
 
3.1%
4 1606
 
2.9%
5 1537
 
2.8%
6 1461
 
2.6%
Other values (30) 4349
 
7.9%
Hangul
ValueCountFrequency (%)
역 1441
 
2.7%
동 1385
 
2.6%
교 1322
 
2.5%
지 1137
 
2.1%
구 1081
 
2.0%
파 1031
 
1.9%
아 975
 
1.8%
트 965
 
1.8%
학 922
 
1.7%
대 915
 
1.7%
Other values (499) 42090
79.0%

승차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct583
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.37894
Minimum0
Maximum1433
Zeros425
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size63.2 KiB
2024-05-04T04:40:17.947667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111
median54
Q3143
95-th percentile355
Maximum1433
Range1433
Interquartile range (IQR)132

Descriptive statistics

Standard deviation134.23841
Coefficient of variation (CV)1.3241253
Kurtosis13.84569
Mean101.37894
Median Absolute Deviation (MAD)50
Skewness2.9127554
Sum727698
Variance18019.951
MonotonicityNot monotonic
2024-05-04T04:40:18.517948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 425
 
5.9%
1 263
 
3.7%
2 204
 
2.8%
3 180
 
2.5%
4 137
 
1.9%
5 123
 
1.7%
7 104
 
1.4%
6 94
 
1.3%
9 91
 
1.3%
8 78
 
1.1%
Other values (573) 5479
76.3%
ValueCountFrequency (%)
0 425
5.9%
1 263
3.7%
2 204
2.8%
3 180
2.5%
4 137
 
1.9%
5 123
 
1.7%
6 94
 
1.3%
7 104
 
1.4%
8 78
 
1.1%
9 91
 
1.3%
ValueCountFrequency (%)
1433 1
< 0.1%
1422 1
< 0.1%
1311 1
< 0.1%
1278 1
< 0.1%
1264 1
< 0.1%
1216 1
< 0.1%
1164 1
< 0.1%
1161 1
< 0.1%
1107 1
< 0.1%
1104 1
< 0.1%

하차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct560
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.719142
Minimum0
Maximum1503
Zeros304
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size63.2 KiB
2024-05-04T04:40:18.974316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q112
median56
Q3138
95-th percentile343
Maximum1503
Range1503
Interquartile range (IQR)126

Descriptive statistics

Standard deviation130.82967
Coefficient of variation (CV)1.3119815
Kurtosis17.365394
Mean99.719142
Median Absolute Deviation (MAD)50
Skewness3.1815536
Sum715784
Variance17116.402
MonotonicityNot monotonic
2024-05-04T04:40:19.429774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 304
 
4.2%
1 245
 
3.4%
2 215
 
3.0%
3 159
 
2.2%
5 134
 
1.9%
4 131
 
1.8%
7 115
 
1.6%
6 110
 
1.5%
8 102
 
1.4%
11 82
 
1.1%
Other values (550) 5581
77.8%
ValueCountFrequency (%)
0 304
4.2%
1 245
3.4%
2 215
3.0%
3 159
2.2%
4 131
1.8%
5 134
1.9%
6 110
 
1.5%
7 115
 
1.6%
8 102
 
1.4%
9 68
 
0.9%
ValueCountFrequency (%)
1503 1
< 0.1%
1485 1
< 0.1%
1472 1
< 0.1%
1383 1
< 0.1%
1361 1
< 0.1%
1289 1
< 0.1%
1150 1
< 0.1%
1147 1
< 0.1%
1059 1
< 0.1%
1020 1
< 0.1%

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size56.2 KiB
20240204
7178 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20240204
2nd row20240204
3rd row20240204
4th row20240204
5th row20240204

Common Values

ValueCountFrequency (%)
20240204 7178
100.0%

Length

2024-05-04T04:40:20.056062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:40:20.463957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20240204 7178
100.0%

Interactions

2024-05-04T04:40:04.389823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:40:02.186301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:40:03.120147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:40:04.821056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:40:02.505687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:40:03.509931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:40:05.189089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:40:02.804971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:40:03.980151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T04:40:21.156022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선명표준버스정류장ID승차총승객수하차총승객수
노선번호1.0001.0000.6890.4370.452
노선명1.0001.0000.6880.4350.450
표준버스정류장ID0.6890.6881.0000.2210.221
승차총승객수0.4370.4350.2211.0000.437
하차총승객수0.4520.4500.2210.4371.000
2024-05-04T04:40:21.564554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준버스정류장ID승차총승객수하차총승객수
표준버스정류장ID1.000-0.141-0.141
승차총승객수-0.1411.0000.584
하차총승객수-0.1410.5841.000

Missing values

2024-05-04T04:40:05.748348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T04:40:06.383974image/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
020240201601601번(개화동~종로4가)11300010314194마포구청역(00057)54712720240204
120240201542542번(군포버스공영차고지~신사역)12100095622424네이처힐5단지(00055)687720240204
220240201542542번(군포버스공영차고지~신사역)12100021522291일동제약사거리(00077)463320240204
320240201542542번(군포버스공영차고지~신사역)12100021222288식유촌우면성당.서초호반써밋(00052)182420240204
420240201542542번(군포버스공영차고지~신사역)12100021122287식유촌우면성당.서초호반써밋(00087)6520240204
520240201542542번(군포버스공영차고지~신사역)12100021022286송동마을.서초힐스아파트(00054)331020240204
620240201542542번(군포버스공영차고지~신사역)12100020922285송동마을.서초힐스아파트(00085)533520240204
720240201542542번(군포버스공영차고지~신사역)12100020722283네이처힐3.4단지(00056)1535520240204
820240201542542번(군포버스공영차고지~신사역)12100020622282서울시품질시험소한국교원단체총연합회(00057)232520240204
920240201542542번(군포버스공영차고지~신사역)12100020522281서울시품질시험소한국교원단체총연합회(00082)305120240204
사용일자노선번호노선명표준버스정류장ID버스정류장ARS번호역명승차총승객수하차총승객수등록일자
716820240201N15N15번(남태령역~우이동도선사입구)10700000808008돈암사거리.성신여대입구(00050)26920240204
71692024020143184318번(사당동출발.사당동~풍납동)12300006924158잠실새내역4번출구(00033)15524520240204
71702024020143184318번(사당동출발.사당동~풍납동)12300007524164아시아선수촌아파트(00031)539320240204
71712024020122332233번(면목동~옥수동)10500012106207대한노인회동대문구지회(00091)647620240204
717220240201N15N15번(남태령역~우이동도선사입구)10700008508175삼선동주민센터(00097)2120240204
71732024020143184318번(사당동출발.사당동~풍납동)12300007624165아주중학교(00030)35019220240204
71742024020143184318번(사당동출발.사당동~풍납동)12300014224231올림픽회관(00042)26310220240204
717520240201N15N15번(남태령역~우이동도선사입구)10700008608176삼선동주민센터(00049)7720240204
71762024020143184318번(사당동출발.사당동~풍납동)12300030224393토성오거리(00057)1007120240204
71772024020143184318번(사당동출발.사당동~풍납동)12300030324394풍납토성서성벽(00061)5022620240204