Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory109.0 B

Variable types

DateTime1
Numeric5
Text3
Categorical3

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15245/F/1/datasetView.do

Alerts

이동거리(M) is highly overall correlated with 이용시간(분)High correlation
이용시간(분) is highly overall correlated with 이동거리(M)High correlation
대여구분코드 is highly imbalanced (66.9%)Imbalance
대여시간 has 165 (1.7%) zerosZeros
이동거리(M) has 2302 (23.0%) zerosZeros

Reproduction

Analysis started2023-12-11 08:12:02.149197
Analysis finished2023-12-11 08:12:07.540101
Duration5.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Date

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-02-01 00:00:00
Maximum2022-02-04 00:00:00
2023-12-11T17:12:07.591710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:07.728253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

대여시간
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.6856
Minimum0
Maximum23
Zeros165
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:12:07.868708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q19
median14
Q318
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.4459084
Coefficient of variation (CV)0.39792982
Kurtosis-0.50319611
Mean13.6856
Median Absolute Deviation (MAD)4
Skewness-0.41492222
Sum136856
Variance29.657918
MonotonicityNot monotonic
2023-12-11T17:12:08.013172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
8 911
 
9.1%
18 775
 
7.8%
17 751
 
7.5%
16 738
 
7.4%
15 625
 
6.2%
14 595
 
5.9%
19 559
 
5.6%
13 558
 
5.6%
12 519
 
5.2%
20 498
 
5.0%
Other values (14) 3471
34.7%
ValueCountFrequency (%)
0 165
 
1.7%
1 132
 
1.3%
2 101
 
1.0%
3 54
 
0.5%
4 58
 
0.6%
5 103
 
1.0%
6 222
 
2.2%
7 477
4.8%
8 911
9.1%
9 398
4.0%
ValueCountFrequency (%)
23 211
 
2.1%
22 330
3.3%
21 460
4.6%
20 498
5.0%
19 559
5.6%
18 775
7.8%
17 751
7.5%
16 738
7.4%
15 625
6.2%
14 595
5.9%

대여소번호
Real number (ℝ)

Distinct2221
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1933.0243
Minimum5
Maximum5301
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:12:08.518178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile228
Q1765
median1587.5
Q32821.25
95-th percentile4567
Maximum5301
Range5296
Interquartile range (IQR)2056.25

Descriptive statistics

Standard deviation1391.5287
Coefficient of variation (CV)0.71987131
Kurtosis-0.79036166
Mean1933.0243
Median Absolute Deviation (MAD)985.5
Skewness0.621564
Sum19330243
Variance1936352.2
MonotonicityNot monotonic
2023-12-11T17:12:08.680295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2701 30
 
0.3%
2715 27
 
0.3%
1210 27
 
0.3%
274 25
 
0.2%
2177 24
 
0.2%
502 24
 
0.2%
2102 23
 
0.2%
4217 21
 
0.2%
1166 21
 
0.2%
765 21
 
0.2%
Other values (2211) 9757
97.6%
ValueCountFrequency (%)
5 1
 
< 0.1%
102 6
0.1%
103 9
0.1%
104 6
0.1%
105 4
< 0.1%
106 4
< 0.1%
107 2
 
< 0.1%
108 4
< 0.1%
109 2
 
< 0.1%
111 4
< 0.1%
ValueCountFrequency (%)
5301 4
< 0.1%
5075 3
< 0.1%
5074 4
< 0.1%
5073 3
< 0.1%
5070 2
 
< 0.1%
5067 1
 
< 0.1%
5066 7
0.1%
5064 4
< 0.1%
5063 6
0.1%
5062 6
0.1%

대여소명
Text

Distinct2221
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T17:12:09.007544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.51
Min length7

Characters and Unicode

Total characters155100
Distinct characters569
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique397 ?
Unique (%)4.0%

Sample

1st row2183. 동방1교
2nd row809. 한남 유수지 복개주차장
3rd row302. 경복궁역 4번출구 뒤
4th row1228. 마천사거리
5th row1211. 방이삼거리
ValueCountFrequency (%)
앞 2557
 
8.7%
출구 504
 
1.7%
옆 378
 
1.3%
1번출구 364
 
1.2%
3번출구 257
 
0.9%
뒤 247
 
0.8%
교차로 246
 
0.8%
사거리 241
 
0.8%
2번출구 240
 
0.8%
5번출구 194
 
0.7%
Other values (4459) 24230
82.3%
2023-12-11T17:12:09.535538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19643
 
12.7%
. 10023
 
6.5%
1 8224
 
5.3%
2 6321
 
4.1%
3 4731
 
3.1%
4 4548
 
2.9%
구 3749
 
2.4%
5 3722
 
2.4%
0 3517
 
2.3%
6 3325
 
2.1%
Other values (559) 87297
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79558
51.3%
Decimal Number 42651
27.5%
Space Separator 19643
 
12.7%
Other Punctuation 10149
 
6.5%
Uppercase Letter 1197
 
0.8%
Open Punctuation 822
 
0.5%
Close Punctuation 822
 
0.5%
Lowercase Letter 132
 
0.1%
Dash Punctuation 90
 
0.1%
Connector Punctuation 14
 
< 0.1%
Other values (3) 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3749
 
4.7%
역 3016
 
3.8%
앞 2998
 
3.8%
번 2734
 
3.4%
출 2642
 
3.3%
동 2006
 
2.5%
교 1597
 
2.0%
아 1427
 
1.8%
파 1374
 
1.7%
리 1363
 
1.7%
Other values (495) 56652
71.2%
Uppercase Letter
ValueCountFrequency (%)
S 174
14.5%
K 139
11.6%
T 123
10.3%
C 106
8.9%
D 81
 
6.8%
B 76
 
6.3%
A 72
 
6.0%
I 64
 
5.3%
G 59
 
4.9%
P 58
 
4.8%
Other values (13) 245
20.5%
Lowercase Letter
ValueCountFrequency (%)
e 52
39.4%
s 13
 
9.8%
k 12
 
9.1%
t 9
 
6.8%
l 6
 
4.5%
n 6
 
4.5%
v 5
 
3.8%
g 4
 
3.0%
a 4
 
3.0%
h 3
 
2.3%
Other values (6) 18
 
13.6%
Decimal Number
ValueCountFrequency (%)
1 8224
19.3%
2 6321
14.8%
3 4731
11.1%
4 4548
10.7%
5 3722
8.7%
0 3517
8.2%
6 3325
7.8%
7 3319
7.8%
8 2671
 
6.3%
9 2273
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 10023
98.8%
, 107
 
1.1%
& 10
 
0.1%
? 7
 
0.1%
· 2
 
< 0.1%
Other Number
ValueCountFrequency (%)
① 6
75.0%
② 2
 
25.0%
Math Symbol
ValueCountFrequency (%)
~ 6
60.0%
+ 4
40.0%
Space Separator
ValueCountFrequency (%)
19643
100.0%
Open Punctuation
ValueCountFrequency (%)
( 822
100.0%
Close Punctuation
ValueCountFrequency (%)
) 822
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 14
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79562
51.3%
Common 74209
47.8%
Latin 1329
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3749
 
4.7%
역 3016
 
3.8%
앞 2998
 
3.8%
번 2734
 
3.4%
출 2642
 
3.3%
동 2006
 
2.5%
교 1597
 
2.0%
아 1427
 
1.8%
파 1374
 
1.7%
리 1363
 
1.7%
Other values (496) 56656
71.2%
Latin
ValueCountFrequency (%)
S 174
13.1%
K 139
 
10.5%
T 123
 
9.3%
C 106
 
8.0%
D 81
 
6.1%
B 76
 
5.7%
A 72
 
5.4%
I 64
 
4.8%
G 59
 
4.4%
P 58
 
4.4%
Other values (29) 377
28.4%
Common
ValueCountFrequency (%)
19643
26.5%
. 10023
13.5%
1 8224
11.1%
2 6321
 
8.5%
3 4731
 
6.4%
4 4548
 
6.1%
5 3722
 
5.0%
0 3517
 
4.7%
6 3325
 
4.5%
7 3319
 
4.5%
Other values (14) 6836
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79558
51.3%
ASCII 75528
48.7%
Enclosed Alphanum 8
 
< 0.1%
None 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19643
26.0%
. 10023
13.3%
1 8224
10.9%
2 6321
 
8.4%
3 4731
 
6.3%
4 4548
 
6.0%
5 3722
 
4.9%
0 3517
 
4.7%
6 3325
 
4.4%
7 3319
 
4.4%
Other values (50) 8155
10.8%
Hangul
ValueCountFrequency (%)
구 3749
 
4.7%
역 3016
 
3.8%
앞 2998
 
3.8%
번 2734
 
3.4%
출 2642
 
3.3%
동 2006
 
2.5%
교 1597
 
2.0%
아 1427
 
1.8%
파 1374
 
1.7%
리 1363
 
1.7%
Other values (495) 56652
71.2%
Enclosed Alphanum
ValueCountFrequency (%)
① 6
75.0%
② 2
 
25.0%
None
ValueCountFrequency (%)
㈜ 4
66.7%
· 2
33.3%

대여구분코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기권
8534 
일일권
1369 
단체권
 
49
일일권(비회원)
 
48

Length

Max length8
Median length3
Mean length3.024
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일일권
2nd row정기권
3rd row정기권
4th row일일권
5th row정기권

Common Values

ValueCountFrequency (%)
정기권 8534
85.3%
일일권 1369
 
13.7%
단체권 49
 
0.5%
일일권(비회원) 48
 
0.5%

Length

2023-12-11T17:12:09.691927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:12:09.833378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 8534
85.3%
일일권 1369
 
13.7%
단체권 49
 
0.5%
일일권(비회원 48
 
0.5%

성별
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
M
4176 
<NA>
3737 
F
2083 
m
 
4

Length

Max length4
Median length1
Mean length2.1211
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowF
2nd row<NA>
3rd rowM
4th rowM
5th rowM

Common Values

ValueCountFrequency (%)
M 4176
41.8%
<NA> 3737
37.4%
F 2083
20.8%
m 4
 
< 0.1%

Length

2023-12-11T17:12:09.978575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:12:10.104728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 4180
41.8%
na 3737
37.4%
f 2083
20.8%

연령대코드
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
3280 
30대
2451 
40대
1524 
50대
1042 
기타
974 
Other values (3)
729 

Length

Max length5
Median length3
Mean length2.9486
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30대
2nd row30대
3rd row20대
4th row30대
5th row40대

Common Values

ValueCountFrequency (%)
20대 3280
32.8%
30대 2451
24.5%
40대 1524
15.2%
50대 1042
 
10.4%
기타 974
 
9.7%
~10대 352
 
3.5%
60대 323
 
3.2%
70대이상 54
 
0.5%

Length

2023-12-11T17:12:10.275247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:12:10.438167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 3280
32.8%
30대 2451
24.5%
40대 1524
15.2%
50대 1042
 
10.4%
기타 974
 
9.7%
10대 352
 
3.5%
60대 323
 
3.2%
70대이상 54
 
0.5%

이용건수
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0513
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:12:10.560779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.26622434
Coefficient of variation (CV)0.25323346
Kurtosis154.91126
Mean1.0513
Median Absolute Deviation (MAD)0
Skewness8.9093734
Sum10513
Variance0.070875398
MonotonicityNot monotonic
2023-12-11T17:12:10.704484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 9552
95.5%
2 403
 
4.0%
3 35
 
0.4%
4 7
 
0.1%
9 1
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
1 9552
95.5%
2 403
 
4.0%
3 35
 
0.4%
4 7
 
0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
8 1
 
< 0.1%
5 1
 
< 0.1%
4 7
 
0.1%
3 35
 
0.4%
2 403
 
4.0%
1 9552
95.5%

운동량
Text

Distinct5017
Distinct (%)50.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T17:12:11.154444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.8583
Min length2

Characters and Unicode

Total characters48583
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3543 ?
Unique (%)35.4%

Sample

1st row55.34
2nd row0.00
3rd row91.04
4th row110.74
5th row59.40
ValueCountFrequency (%)
0.00 2251
 
22.5%
n 54
 
0.5%
37.07 12
 
0.1%
22.65 11
 
0.1%
24.45 11
 
0.1%
20.33 11
 
0.1%
17.11 10
 
0.1%
24.71 10
 
0.1%
12.87 10
 
0.1%
15.44 10
 
0.1%
Other values (5007) 7610
76.1%
2023-12-11T17:12:11.705072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9946
20.5%
0 9312
19.2%
1 4539
9.3%
2 4034
8.3%
3 3617
 
7.4%
4 3243
 
6.7%
5 3063
 
6.3%
6 2802
 
5.8%
7 2755
 
5.7%
8 2634
 
5.4%
Other values (3) 2638
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38529
79.3%
Other Punctuation 10000
 
20.6%
Uppercase Letter 54
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9312
24.2%
1 4539
11.8%
2 4034
10.5%
3 3617
 
9.4%
4 3243
 
8.4%
5 3063
 
7.9%
6 2802
 
7.3%
7 2755
 
7.2%
8 2634
 
6.8%
9 2530
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 9946
99.5%
\ 54
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48529
99.9%
Latin 54
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9946
20.5%
0 9312
19.2%
1 4539
9.4%
2 4034
8.3%
3 3617
 
7.5%
4 3243
 
6.7%
5 3063
 
6.3%
6 2802
 
5.8%
7 2755
 
5.7%
8 2634
 
5.4%
Other values (2) 2584
 
5.3%
Latin
ValueCountFrequency (%)
N 54
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48583
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9946
20.5%
0 9312
19.2%
1 4539
9.3%
2 4034
8.3%
3 3617
 
7.4%
4 3243
 
6.7%
5 3063
 
6.3%
6 2802
 
5.8%
7 2755
 
5.7%
8 2634
 
5.4%
Other values (3) 2638
 
5.4%

탄소량
Text

Distinct377
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T17:12:12.132221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9893
Min length2

Characters and Unicode

Total characters39893
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)1.0%

Sample

1st row0.50
2nd row0.00
3rd row0.68
4th row0.76
5th row0.35
ValueCountFrequency (%)
0.00 2259
 
22.6%
0.19 171
 
1.7%
0.16 166
 
1.7%
0.14 165
 
1.7%
0.24 163
 
1.6%
0.20 159
 
1.6%
0.25 156
 
1.6%
0.23 155
 
1.6%
0.21 154
 
1.5%
0.18 153
 
1.5%
Other values (367) 6299
63.0%
2023-12-11T17:12:12.724377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14735
36.9%
. 9946
24.9%
1 3158
 
7.9%
2 2522
 
6.3%
3 2046
 
5.1%
4 1635
 
4.1%
5 1417
 
3.6%
6 1224
 
3.1%
8 1051
 
2.6%
7 1031
 
2.6%
Other values (3) 1128
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29839
74.8%
Other Punctuation 10000
 
25.1%
Uppercase Letter 54
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14735
49.4%
1 3158
 
10.6%
2 2522
 
8.5%
3 2046
 
6.9%
4 1635
 
5.5%
5 1417
 
4.7%
6 1224
 
4.1%
8 1051
 
3.5%
7 1031
 
3.5%
9 1020
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 9946
99.5%
\ 54
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39839
99.9%
Latin 54
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14735
37.0%
. 9946
25.0%
1 3158
 
7.9%
2 2522
 
6.3%
3 2046
 
5.1%
4 1635
 
4.1%
5 1417
 
3.6%
6 1224
 
3.1%
8 1051
 
2.6%
7 1031
 
2.6%
Other values (2) 1074
 
2.7%
Latin
ValueCountFrequency (%)
N 54
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39893
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14735
36.9%
. 9946
24.9%
1 3158
 
7.9%
2 2522
 
6.3%
3 2046
 
5.1%
4 1635
 
4.1%
5 1417
 
3.6%
6 1224
 
3.1%
8 1051
 
2.6%
7 1031
 
2.6%
Other values (3) 1128
 
2.8%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4103
Distinct (%)41.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1885.7661
Minimum0
Maximum46440.06
Zeros2302
Zeros (%)23.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:12:12.913277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1300
median1090
Q32250
95-th percentile6841.114
Maximum46440.06
Range46440.06
Interquartile range (IQR)1950

Descriptive statistics

Standard deviation2784.5283
Coefficient of variation (CV)1.4766032
Kurtosis32.050459
Mean1885.7661
Median Absolute Deviation (MAD)1042.785
Skewness4.260288
Sum18857661
Variance7753598.1
MonotonicityNot monotonic
2023-12-11T17:12:13.067620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2302
 
23.0%
930.0 31
 
0.3%
800.0 30
 
0.3%
600.0 29
 
0.3%
790.0 29
 
0.3%
1020.0 29
 
0.3%
1090.0 29
 
0.3%
810.0 28
 
0.3%
890.0 27
 
0.3%
870.0 26
 
0.3%
Other values (4093) 7440
74.4%
ValueCountFrequency (%)
0.0 2302
23.0%
0.1 2
 
< 0.1%
0.2 2
 
< 0.1%
10.0 5
 
0.1%
20.0 2
 
< 0.1%
30.0 2
 
< 0.1%
40.0 5
 
0.1%
50.0 2
 
< 0.1%
60.0 3
 
< 0.1%
70.0 1
 
< 0.1%
ValueCountFrequency (%)
46440.06 1
< 0.1%
42816.45 1
< 0.1%
38446.7 1
< 0.1%
37635.96 1
< 0.1%
31572.3 1
< 0.1%
29981.6 1
< 0.1%
29222.78 1
< 0.1%
26989.95 1
< 0.1%
26925.4 1
< 0.1%
26010.0 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct163
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.4924
Minimum0
Maximum497
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:12:13.232678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q16
median11
Q326
95-th percentile76.05
Maximum497
Range497
Interquartile range (IQR)20

Descriptive statistics

Standard deviation25.969066
Coefficient of variation (CV)1.2082906
Kurtosis19.76973
Mean21.4924
Median Absolute Deviation (MAD)7
Skewness3.1004497
Sum214924
Variance674.39238
MonotonicityNot monotonic
2023-12-11T17:12:13.381938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 656
 
6.6%
4 623
 
6.2%
6 603
 
6.0%
7 544
 
5.4%
3 532
 
5.3%
8 481
 
4.8%
9 445
 
4.5%
10 422
 
4.2%
11 345
 
3.5%
2 291
 
2.9%
Other values (153) 5058
50.6%
ValueCountFrequency (%)
0 4
 
< 0.1%
1 91
 
0.9%
2 291
2.9%
3 532
5.3%
4 623
6.2%
5 656
6.6%
6 603
6.0%
7 544
5.4%
8 481
4.8%
9 445
4.5%
ValueCountFrequency (%)
497 1
< 0.1%
261 1
< 0.1%
253 1
< 0.1%
247 1
< 0.1%
240 1
< 0.1%
218 1
< 0.1%
210 2
< 0.1%
206 1
< 0.1%
204 1
< 0.1%
203 1
< 0.1%

Interactions

2023-12-11T17:12:06.458560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:03.964425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:04.540278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:05.141514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:05.831149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:06.583324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:04.074876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:04.652417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:05.256197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:05.940677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:06.717078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:04.183343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:04.758521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:05.392037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:06.051930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:06.843905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:04.302814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:04.890312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:05.544976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:06.189961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:06.953459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:04.415610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:05.009477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:05.689653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:12:06.316093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:12:13.514194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여일자대여시간대여소번호대여구분코드성별연령대코드이용건수이동거리(M)이용시간(분)
대여일자1.0000.5250.0160.2290.0260.1080.0350.0810.082
대여시간0.5251.0000.0000.1400.1010.1200.0450.0550.110
대여소번호0.0160.0001.0000.0510.0000.0560.0370.0560.057
대여구분코드0.2290.1400.0511.0000.0820.3310.2600.1840.218
성별0.0260.1010.0000.0821.0000.0930.0000.0000.000
연령대코드0.1080.1200.0560.3310.0931.0000.0390.0530.047
이용건수0.0350.0450.0370.2600.0000.0391.0000.5100.831
이동거리(M)0.0810.0550.0560.1840.0000.0530.5101.0000.656
이용시간(분)0.0820.1100.0570.2180.0000.0470.8310.6561.000
2023-12-11T17:12:13.645948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여구분코드성별연령대코드
대여구분코드1.0000.0240.153
성별0.0241.0000.059
연령대코드0.1530.0591.000
2023-12-11T17:12:13.752775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여시간대여소번호이용건수이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여시간1.000-0.0190.0140.0290.0910.0840.0600.057
대여소번호-0.0191.000-0.005-0.012-0.0310.0310.0000.026
이용건수0.014-0.0051.0000.1500.1730.1810.0000.021
이동거리(M)0.029-0.0120.1501.0000.5180.1190.0000.026
이용시간(분)0.091-0.0310.1730.5181.0000.1510.0000.025
대여구분코드0.0840.0310.1810.1190.1511.0000.0240.153
성별0.0600.0000.0000.0000.0000.0241.0000.059
연령대코드0.0570.0260.0210.0260.0250.1530.0591.000

Missing values

2023-12-11T17:12:07.144508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:12:07.431891image/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

대여일자대여시간대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
177812022-02-021021832183. 동방1교일일권F30대155.340.502150.013
559342022-02-0312809809. 한남 유수지 복개주차장정기권<NA>30대10.000.000.05
694952022-02-0317302302. 경복궁역 4번출구 뒤정기권M20대191.040.682910.016
451292022-02-03712281228. 마천사거리일일권M30대1110.740.763290.023
517412022-02-03912111211. 방이삼거리정기권M40대159.400.351500.010
463452022-02-03814041404. 동일로 지하차도정기권<NA>30대125.380.251068.387
138782022-02-02012691269. 리센츠아파트정기권M~10대3160.531.406040.029
293582022-02-021623332333. 양재역 3번출구 주변정기권M20대1138.000.923960.021
50452022-02-011516011601. 석계역 문화광장 내 자전거 보관소정기권M30대1105.530.954100.025
356522022-02-021913061306. 한성대입구역2번출구정기권F50대1125.930.964130.032
대여일자대여시간대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
14992022-02-011044654465. 건영아파트앞 사거리정기권M30대162.650.411777.5311
591292022-02-031335133513. 상왕십리역 1번출구정기권M50대126.110.21890.866
912062022-02-04840754075. 방학신동아아파트 11동 앞정기권<NA>20대1134.841.225238.7123
483302022-02-038911911. 은평평화공원(역촌역4번출구)정기권M기타147.410.341459.989
128912022-02-012227022702. 마곡 엠밸리2단지정기권M40대143.240.361560.016
450342022-02-03745614561. 양평역 1번출구정기권M기타10.000.000.16
313362022-02-021735733573.광나루안전체험관정기권<NA>40대156.510.472010.025
871022022-02-043956956. 응암시장교차로정기권<NA>30대189.610.923970.033
511762022-02-039258258. 신길역3번출구일일권M기타10.000.000.0128
383022022-02-022111241124. 발산역 6번 출구 뒤정기권<NA>20대139.400.421808.816