Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory976.6 KiB
Average record size in memory100.0 B

Variable types

Categorical4
Numeric4
Text3

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15246/A/1/datasetView.do

Alerts

대여일자 has constant value ""Constant
대여구분코드 has constant value ""Constant
이용건수 is highly overall correlated with 이동거리(M) and 1 other fieldsHigh correlation
이동거리(M) is highly overall correlated with 이용건수 and 1 other fieldsHigh correlation
이용시간(분) is highly overall correlated with 이용건수 and 1 other fieldsHigh correlation
이동거리(M) has 185 (1.8%) zerosZeros

Reproduction

Analysis started2024-05-18 04:52:12.760261
Analysis finished2024-05-18 04:52:25.054078
Duration12.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-01-01
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-01-01
2nd row2023-01-01
3rd row2023-01-01
4th row2023-01-01
5th row2023-01-01

Common Values

ValueCountFrequency (%)
2023-01-01 10000
100.0%

Length

2024-05-18T13:52:25.246382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:52:25.638549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-01-01 10000
100.0%

대여소번호
Real number (ℝ)

Distinct2363
Distinct (%)23.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2104.2082
Minimum102
Maximum6053
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T13:52:26.185059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile254
Q1838
median1665.5
Q33511
95-th percentile4812
Maximum6053
Range5951
Interquartile range (IQR)2673

Descriptive statistics

Standard deviation1497.1251
Coefficient of variation (CV)0.71149094
Kurtosis-0.85856168
Mean2104.2082
Median Absolute Deviation (MAD)1017.5
Skewness0.59779134
Sum21042082
Variance2241383.5
MonotonicityNot monotonic
2024-05-18T13:52:26.811901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2715 19
 
0.2%
1044 18
 
0.2%
4027 18
 
0.2%
1153 17
 
0.2%
1150 16
 
0.2%
5052 16
 
0.2%
2701 16
 
0.2%
3501 15
 
0.1%
787 15
 
0.1%
4565 14
 
0.1%
Other values (2353) 9836
98.4%
ValueCountFrequency (%)
102 6
0.1%
103 4
< 0.1%
104 3
< 0.1%
105 1
 
< 0.1%
106 7
0.1%
107 6
0.1%
108 4
< 0.1%
109 2
 
< 0.1%
111 2
 
< 0.1%
112 3
< 0.1%
ValueCountFrequency (%)
6053 1
 
< 0.1%
5862 5
0.1%
5861 3
 
< 0.1%
5860 2
 
< 0.1%
5859 2
 
< 0.1%
5858 11
0.1%
5857 7
0.1%
5855 1
 
< 0.1%
5854 7
0.1%
5853 3
 
< 0.1%

대여소
Text

Distinct2363
Distinct (%)23.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T13:52:27.453547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length15.608
Min length7

Characters and Unicode

Total characters156080
Distinct characters563
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

Unique393 ?
Unique (%)3.9%

Sample

1st row1406. 망우청소년수련관
2nd row2706.강서공업고등학교 앞
3rd row3798. 그랜드아이파크아파트 앞
4th row3415.동대문역6번출구
5th row1620. 중계동 노원구민체육센터 옆(중1-2)
ValueCountFrequency (%)
앞 2521
 
8.6%
출구 470
 
1.6%
옆 389
 
1.3%
1번출구 332
 
1.1%
교차로 244
 
0.8%
사거리 216
 
0.7%
3번출구 207
 
0.7%
뒤 207
 
0.7%
2번출구 190
 
0.6%
입구 181
 
0.6%
Other values (4756) 24368
83.1%
2024-05-18T13:52:28.882462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19527
 
12.5%
. 10015
 
6.4%
1 8335
 
5.3%
2 5763
 
3.7%
4 4693
 
3.0%
3 4605
 
3.0%
5 3858
 
2.5%
0 3695
 
2.4%
6 3441
 
2.2%
7 3379
 
2.2%
Other values (553) 88769
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80423
51.5%
Decimal Number 42985
27.5%
Space Separator 19527
 
12.5%
Other Punctuation 10145
 
6.5%
Uppercase Letter 1123
 
0.7%
Open Punctuation 816
 
0.5%
Close Punctuation 816
 
0.5%
Lowercase Letter 134
 
0.1%
Dash Punctuation 77
 
< 0.1%
Connector Punctuation 18
 
< 0.1%
Other values (3) 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3361
 
4.2%
앞 2928
 
3.6%
역 2659
 
3.3%
번 2374
 
3.0%
출 2316
 
2.9%
동 2283
 
2.8%
교 1576
 
2.0%
파 1519
 
1.9%
아 1491
 
1.9%
트 1417
 
1.8%
Other values (492) 58499
72.7%
Uppercase Letter
ValueCountFrequency (%)
S 132
11.8%
C 112
10.0%
K 111
9.9%
T 105
9.3%
A 101
9.0%
B 73
 
6.5%
G 71
 
6.3%
M 65
 
5.8%
D 65
 
5.8%
P 56
 
5.0%
Other values (13) 232
20.7%
Lowercase Letter
ValueCountFrequency (%)
e 50
37.3%
s 21
15.7%
k 19
 
14.2%
n 8
 
6.0%
v 7
 
5.2%
f 5
 
3.7%
r 5
 
3.7%
h 5
 
3.7%
t 4
 
3.0%
l 4
 
3.0%
Other values (3) 6
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 8335
19.4%
2 5763
13.4%
4 4693
10.9%
3 4605
10.7%
5 3858
9.0%
0 3695
8.6%
6 3441
8.0%
7 3379
7.9%
8 2743
 
6.4%
9 2473
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 10015
98.7%
, 95
 
0.9%
& 16
 
0.2%
? 11
 
0.1%
· 8
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 6
60.0%
+ 4
40.0%
Other Number
ValueCountFrequency (%)
① 3
75.0%
② 1
 
25.0%
Space Separator
ValueCountFrequency (%)
19527
100.0%
Open Punctuation
ValueCountFrequency (%)
( 816
100.0%
Close Punctuation
ValueCountFrequency (%)
) 816
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 18
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80425
51.5%
Common 74398
47.7%
Latin 1257
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3361
 
4.2%
앞 2928
 
3.6%
역 2659
 
3.3%
번 2374
 
3.0%
출 2316
 
2.9%
동 2283
 
2.8%
교 1576
 
2.0%
파 1519
 
1.9%
아 1491
 
1.9%
트 1417
 
1.8%
Other values (493) 58501
72.7%
Latin
ValueCountFrequency (%)
S 132
 
10.5%
C 112
 
8.9%
K 111
 
8.8%
T 105
 
8.4%
A 101
 
8.0%
B 73
 
5.8%
G 71
 
5.6%
M 65
 
5.2%
D 65
 
5.2%
P 56
 
4.5%
Other values (26) 366
29.1%
Common
ValueCountFrequency (%)
19527
26.2%
. 10015
13.5%
1 8335
11.2%
2 5763
 
7.7%
4 4693
 
6.3%
3 4605
 
6.2%
5 3858
 
5.2%
0 3695
 
5.0%
6 3441
 
4.6%
7 3379
 
4.5%
Other values (14) 7087
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80423
51.5%
ASCII 75643
48.5%
None 10
 
< 0.1%
Enclosed Alphanum 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19527
25.8%
. 10015
13.2%
1 8335
11.0%
2 5763
 
7.6%
4 4693
 
6.2%
3 4605
 
6.1%
5 3858
 
5.1%
0 3695
 
4.9%
6 3441
 
4.5%
7 3379
 
4.5%
Other values (47) 8332
11.0%
Hangul
ValueCountFrequency (%)
구 3361
 
4.2%
앞 2928
 
3.6%
역 2659
 
3.3%
번 2374
 
3.0%
출 2316
 
2.9%
동 2283
 
2.8%
교 1576
 
2.0%
파 1519
 
1.9%
아 1491
 
1.9%
트 1417
 
1.8%
Other values (492) 58499
72.7%
None
ValueCountFrequency (%)
· 8
80.0%
㈜ 2
 
20.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 3
75.0%
② 1
 
25.0%

대여구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기권
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기권 10000
100.0%

Length

2024-05-18T13:52:29.396023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:52:29.738367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 10000
100.0%

성별
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
3674 
M
3601 
F
2721 
m
 
3
f
 
1

Length

Max length4
Median length1
Mean length2.1022
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3674
36.7%
M 3601
36.0%
F 2721
27.2%
m 3
 
< 0.1%
f 1
 
< 0.1%

Length

2024-05-18T13:52:30.217266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:52:30.565952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3674
36.7%
m 3604
36.0%
f 2722
27.2%

연령대
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
3358 
30대
2588 
40대
1616 
50대
851 
~10대
721 
Other values (3)
866 

Length

Max length5
Median length3
Mean length3.0274
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50대
2nd row60대
3rd row30대
4th row40대
5th row30대

Common Values

ValueCountFrequency (%)
20대 3358
33.6%
30대 2588
25.9%
40대 1616
16.2%
50대 851
 
8.5%
~10대 721
 
7.2%
기타 541
 
5.4%
60대 278
 
2.8%
70대이상 47
 
0.5%

Length

2024-05-18T13:52:30.949082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:52:31.436605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 3358
33.6%
30대 2588
25.9%
40대 1616
16.2%
50대 851
 
8.5%
10대 721
 
7.2%
기타 541
 
5.4%
60대 278
 
2.8%
70대이상 47
 
0.5%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5553
Minimum1
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T13:52:32.021096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum17
Range16
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1102546
Coefficient of variation (CV)0.71385235
Kurtosis16.959317
Mean1.5553
Median Absolute Deviation (MAD)0
Skewness3.3237135
Sum15553
Variance1.2326652
MonotonicityNot monotonic
2024-05-18T13:52:32.533918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 6872
68.7%
2 1881
 
18.8%
3 676
 
6.8%
4 288
 
2.9%
5 135
 
1.4%
6 73
 
0.7%
7 28
 
0.3%
8 19
 
0.2%
9 16
 
0.2%
10 6
 
0.1%
Other values (3) 6
 
0.1%
ValueCountFrequency (%)
1 6872
68.7%
2 1881
 
18.8%
3 676
 
6.8%
4 288
 
2.9%
5 135
 
1.4%
6 73
 
0.7%
7 28
 
0.3%
8 19
 
0.2%
9 16
 
0.2%
10 6
 
0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
12 2
 
< 0.1%
11 3
 
< 0.1%
10 6
 
0.1%
9 16
 
0.2%
8 19
 
0.2%
7 28
 
0.3%
6 73
 
0.7%
5 135
1.4%
4 288
2.9%

운동량
Text

Distinct6560
Distinct (%)65.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T13:52:33.615132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.1506
Min length2

Characters and Unicode

Total characters51506
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

Unique4609 ?
Unique (%)46.1%

Sample

1st row55.44
2nd row81.29
3rd row18.77
4th row48.24
5th row31.18
ValueCountFrequency (%)
0.00 193
 
1.9%
n 14
 
0.1%
23.17 13
 
0.1%
19.56 12
 
0.1%
17.25 12
 
0.1%
20.59 12
 
0.1%
21.62 12
 
0.1%
21.88 10
 
0.1%
15.70 10
 
0.1%
36.04 10
 
0.1%
Other values (6550) 9702
97.0%
2024-05-18T13:52:35.415703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9986
19.4%
1 6011
11.7%
2 5035
9.8%
3 4490
8.7%
4 4098
8.0%
5 3896
 
7.6%
0 3843
 
7.5%
6 3681
 
7.1%
7 3571
 
6.9%
8 3507
 
6.8%
Other values (3) 3388
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41492
80.6%
Other Punctuation 10000
 
19.4%
Uppercase Letter 14
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6011
14.5%
2 5035
12.1%
3 4490
10.8%
4 4098
9.9%
5 3896
9.4%
0 3843
9.3%
6 3681
8.9%
7 3571
8.6%
8 3507
8.5%
9 3360
8.1%
Other Punctuation
ValueCountFrequency (%)
. 9986
99.9%
\ 14
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51492
> 99.9%
Latin 14
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9986
19.4%
1 6011
11.7%
2 5035
9.8%
3 4490
8.7%
4 4098
8.0%
5 3896
 
7.6%
0 3843
 
7.5%
6 3681
 
7.1%
7 3571
 
6.9%
8 3507
 
6.8%
Other values (2) 3374
 
6.6%
Latin
ValueCountFrequency (%)
N 14
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51506
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9986
19.4%
1 6011
11.7%
2 5035
9.8%
3 4490
8.7%
4 4098
8.0%
5 3896
 
7.6%
0 3843
 
7.5%
6 3681
 
7.1%
7 3571
 
6.9%
8 3507
 
6.8%
Other values (3) 3388
 
6.6%

탄소량
Text

Distinct393
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T13:52:36.693837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.9972
Min length2

Characters and Unicode

Total characters39972
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

Unique94 ?
Unique (%)0.9%

Sample

1st row0.46
2nd row0.79
3rd row0.18
4th row0.43
5th row0.26
ValueCountFrequency (%)
0.23 190
 
1.9%
0.16 186
 
1.9%
0.00 183
 
1.8%
0.19 176
 
1.8%
0.21 172
 
1.7%
0.20 171
 
1.7%
0.22 169
 
1.7%
0.14 168
 
1.7%
0.18 162
 
1.6%
0.17 158
 
1.6%
Other values (383) 8265
82.7%
2024-05-18T13:52:38.596610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10311
25.8%
. 9986
25.0%
1 4150
10.4%
2 3046
 
7.6%
3 2556
 
6.4%
4 2098
 
5.2%
5 1870
 
4.7%
6 1673
 
4.2%
7 1502
 
3.8%
8 1419
 
3.5%
Other values (3) 1361
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29958
74.9%
Other Punctuation 10000
 
25.0%
Uppercase Letter 14
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10311
34.4%
1 4150
13.9%
2 3046
 
10.2%
3 2556
 
8.5%
4 2098
 
7.0%
5 1870
 
6.2%
6 1673
 
5.6%
7 1502
 
5.0%
8 1419
 
4.7%
9 1333
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 9986
99.9%
\ 14
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39958
> 99.9%
Latin 14
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10311
25.8%
. 9986
25.0%
1 4150
10.4%
2 3046
 
7.6%
3 2556
 
6.4%
4 2098
 
5.3%
5 1870
 
4.7%
6 1673
 
4.2%
7 1502
 
3.8%
8 1419
 
3.6%
Other values (2) 1347
 
3.4%
Latin
ValueCountFrequency (%)
N 14
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39972
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10311
25.8%
. 9986
25.0%
1 4150
10.4%
2 3046
 
7.6%
3 2556
 
6.4%
4 2098
 
5.2%
5 1870
 
4.7%
6 1673
 
4.2%
7 1502
 
3.8%
8 1419
 
3.5%
Other values (3) 1361
 
3.4%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6704
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2662.4539
Minimum0
Maximum28060
Zeros185
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T13:52:39.200991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile390
Q1956.745
median1774.095
Q33306.3475
95-th percentile7938.045
Maximum28060
Range28060
Interquartile range (IQR)2349.6025

Descriptive statistics

Standard deviation2786.7853
Coefficient of variation (CV)1.046698
Kurtosis12.416212
Mean2662.4539
Median Absolute Deviation (MAD)979.135
Skewness2.8874352
Sum26624539
Variance7766172.2
MonotonicityNot monotonic
2024-05-18T13:52:39.698237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 185
 
1.8%
900.0 27
 
0.3%
670.0 27
 
0.3%
800.0 25
 
0.2%
1140.0 24
 
0.2%
1000.0 24
 
0.2%
850.0 24
 
0.2%
1320.0 23
 
0.2%
750.0 23
 
0.2%
860.0 23
 
0.2%
Other values (6694) 9595
96.0%
ValueCountFrequency (%)
0.0 185
1.8%
0.13 4
 
< 0.1%
0.2 1
 
< 0.1%
10.0 2
 
< 0.1%
20.0 4
 
< 0.1%
20.72 1
 
< 0.1%
22.19 1
 
< 0.1%
23.63 1
 
< 0.1%
30.0 1
 
< 0.1%
37.45 1
 
< 0.1%
ValueCountFrequency (%)
28060.0 1
< 0.1%
27080.83 1
< 0.1%
25286.8 1
< 0.1%
24461.03 1
< 0.1%
24316.09 1
< 0.1%
24170.13 1
< 0.1%
24081.57 1
< 0.1%
23986.19 1
< 0.1%
23724.74 1
< 0.1%
23278.4 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct171
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.1859
Minimum0
Maximum696
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T13:52:40.195419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q17
median13
Q327
95-th percentile64
Maximum696
Range696
Interquartile range (IQR)20

Descriptive statistics

Standard deviation25.074023
Coefficient of variation (CV)1.1835241
Kurtosis107.70551
Mean21.1859
Median Absolute Deviation (MAD)8
Skewness6.2733252
Sum211859
Variance628.70661
MonotonicityNot monotonic
2024-05-18T13:52:40.710094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 542
 
5.4%
6 529
 
5.3%
4 504
 
5.0%
7 479
 
4.8%
3 447
 
4.5%
9 437
 
4.4%
8 427
 
4.3%
10 368
 
3.7%
12 367
 
3.7%
11 341
 
3.4%
Other values (161) 5559
55.6%
ValueCountFrequency (%)
0 3
 
< 0.1%
1 102
 
1.0%
2 279
2.8%
3 447
4.5%
4 504
5.0%
5 542
5.4%
6 529
5.3%
7 479
4.8%
8 427
4.3%
9 437
4.4%
ValueCountFrequency (%)
696 1
< 0.1%
647 1
< 0.1%
343 1
< 0.1%
331 1
< 0.1%
329 1
< 0.1%
281 1
< 0.1%
280 1
< 0.1%
264 1
< 0.1%
244 1
< 0.1%
231 1
< 0.1%

Interactions

2024-05-18T13:52:21.520362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:16.200915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:17.642797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:19.178739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:22.408077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:16.500058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:17.946003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:19.799319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:22.857548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:16.867289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:18.389544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:20.270110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:23.399133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:17.247339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:18.764997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:52:20.668773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T13:52:41.002836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호성별연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0300.0660.0590.0390.000
성별0.0301.0000.4590.1490.0490.000
연령대0.0660.4591.0000.2400.0880.067
이용건수0.0590.1490.2401.0000.5460.431
이동거리(M)0.0390.0490.0880.5461.0000.523
이용시간(분)0.0000.0000.0670.4310.5231.000
2024-05-18T13:52:41.381478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령대성별
연령대1.0000.219
성별0.2191.000
2024-05-18T13:52:41.740084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)성별연령대
대여소번호1.000-0.022-0.027-0.0290.0180.032
이용건수-0.0221.0000.5620.5480.0680.082
이동거리(M)-0.0270.5621.0000.8620.0290.042
이용시간(분)-0.0290.5480.8621.0000.0000.037
성별0.0180.0680.0290.0001.0000.219
연령대0.0320.0820.0420.0370.2191.000

Missing values

2024-05-18T13:52:23.940354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T13:52:24.764821image/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

대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
65482023-01-0114061406. 망우청소년수련관정기권F50대155.440.462000.016
66482023-01-0127062706.강서공업고등학교 앞정기권F60대181.290.793421.3228
20592023-01-0137983798. 그랜드아이파크아파트 앞정기권<NA>30대118.770.18790.05
103902023-01-0134153415.동대문역6번출구정기권M40대248.240.431874.3211
101012023-01-0116201620. 중계동 노원구민체육센터 옆(중1-2)정기권M30대131.180.261124.816
41602023-01-0145354535. 목동12단지 아파트정기권F~10대133.750.301311.316
10862023-01-0138163816. 관악 GSfresh정기권<NA>20대350.730.451970.8917
103932023-01-0134233423.현대그룹(본사)정기권M40대1115.911.014368.523
105042023-01-01870870.노들섬 서측 앞정기권M40대133.120.291230.053
58452023-01-0122762276. 영동1교 (양재천근린공원)정기권F40대132.280.291254.099
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
3182023-01-0112871287. 위례아이파크 101동 맞은편정기권<NA>20대149.940.562425.120
100262023-01-0119061906. 신도림역 1번 출구 앞정기권M30대1162.841.566741.3143
20072023-01-0121992199.신봉천주유소 A정기권<NA>30대141.510.411747.1111
76662023-01-0117191719. 신도봉사거리 버스정류장정기권M20대266.820.562401.2213
76992023-01-0119611961. 신도림테크노근린공원정기권M20대5153.901.395955.3439
60252023-01-01797797.목동아파트 1422동 1434동 사잇길정기권F40대375.080.703037.5327
83892023-01-0145144514. 목동성당 앞정기권M20대120.770.21920.04
27782023-01-0113821382.래미안월곡아파트 입구정기권<NA>40대2226.261.616945.641
21122023-01-0140744074. 도봉구육아종합지원센터(창동)정기권<NA>30대143.100.341470.7711
3372023-01-0113681368. 성신여대입구 교차로정기권<NA>20대222.070.23985.826