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

DateTime1
Numeric4
Text3
Categorical3

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15248/F/1/datasetView.do

Alerts

대여일자 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) is highly skewed (γ1 = 20.04092905)Skewed
이용시간(분) is highly skewed (γ1 = 28.4180876)Skewed

Reproduction

Analysis started2024-03-13 12:59:53.111318
Analysis finished2024-03-13 12:59:57.530537
Duration4.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-04-01 00:00:00
Maximum2022-04-01 00:00:00
2024-03-13T21:59:57.580461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:57.682712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct1489
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1072.1768
Minimum3
Maximum2210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T21:59:57.821607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile184
Q1539
median1059
Q31557
95-th percentile2082
Maximum2210
Range2207
Interquartile range (IQR)1018

Descriptive statistics

Standard deviation603.91693
Coefficient of variation (CV)0.56326245
Kurtosis-1.1355213
Mean1072.1768
Median Absolute Deviation (MAD)510
Skewness0.15016234
Sum10721768
Variance364715.65
MonotonicityNot monotonic
2024-03-13T21:59:57.994502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2102 16
 
0.2%
1608 16
 
0.2%
1009 15
 
0.1%
1920 15
 
0.1%
106 15
 
0.1%
1677 15
 
0.1%
1112 15
 
0.1%
1222 15
 
0.1%
108 15
 
0.1%
147 14
 
0.1%
Other values (1479) 9849
98.5%
ValueCountFrequency (%)
3 1
 
< 0.1%
5 2
 
< 0.1%
102 7
0.1%
103 9
0.1%
104 5
 
0.1%
105 6
 
0.1%
106 15
0.1%
107 9
0.1%
108 15
0.1%
109 4
 
< 0.1%
ValueCountFrequency (%)
2210 9
0.1%
2207 4
< 0.1%
2206 4
< 0.1%
2205 3
 
< 0.1%
2203 9
0.1%
2202 6
0.1%
2201 4
< 0.1%
2199 5
0.1%
2198 3
 
< 0.1%
2196 8
0.1%

대여소명
Text

Distinct1489
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T21:59:58.453218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length15.2466
Min length4

Characters and Unicode

Total characters152466
Distinct characters507
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)0.2%

Sample

1st row227. 양평2나들목 보행통로 입구
2nd row806. 전자랜드 본관 앞
3rd row1962. 가리봉동주민센터
4th row809. 한남 유수지 복개주차장
5th row948. 디지털미디어 시티역 4번출구(DMC역)
ValueCountFrequency (%)
앞 2605
 
8.7%
옆 484
 
1.6%
출구 396
 
1.3%
1번출구 280
 
0.9%
교차로 257
 
0.9%
사거리 256
 
0.9%
뒤 243
 
0.8%
3번출구 238
 
0.8%
입구 237
 
0.8%
2번출구 237
 
0.8%
Other values (3072) 24612
82.5%
2024-03-13T21:59:59.047863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20025
 
13.1%
. 10015
 
6.6%
1 9445
 
6.2%
2 5023
 
3.3%
3 3569
 
2.3%
4 3545
 
2.3%
구 3517
 
2.3%
0 3423
 
2.2%
6 3340
 
2.2%
5 3308
 
2.2%
Other values (497) 87256
57.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79112
51.9%
Decimal Number 40155
26.3%
Space Separator 20025
 
13.1%
Other Punctuation 10105
 
6.6%
Uppercase Letter 1251
 
0.8%
Open Punctuation 820
 
0.5%
Close Punctuation 820
 
0.5%
Lowercase Letter 105
 
0.1%
Dash Punctuation 49
 
< 0.1%
Math Symbol 12
 
< 0.1%
Other values (2) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3517
 
4.4%
앞 2985
 
3.8%
역 2649
 
3.3%
번 2398
 
3.0%
출 2319
 
2.9%
동 2009
 
2.5%
교 1750
 
2.2%
리 1331
 
1.7%
원 1300
 
1.6%
파 1261
 
1.6%
Other values (444) 57593
72.8%
Uppercase Letter
ValueCountFrequency (%)
S 169
13.5%
K 159
12.7%
T 119
9.5%
C 114
9.1%
B 90
 
7.2%
A 87
 
7.0%
D 72
 
5.8%
P 60
 
4.8%
G 59
 
4.7%
M 55
 
4.4%
Other values (11) 267
21.3%
Decimal Number
ValueCountFrequency (%)
1 9445
23.5%
2 5023
12.5%
3 3569
 
8.9%
4 3545
 
8.8%
0 3423
 
8.5%
6 3340
 
8.3%
5 3308
 
8.2%
7 3143
 
7.8%
9 2726
 
6.8%
8 2633
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
e 45
42.9%
n 16
 
15.2%
l 12
 
11.4%
y 8
 
7.6%
t 4
 
3.8%
k 4
 
3.8%
s 4
 
3.8%
m 4
 
3.8%
o 4
 
3.8%
c 4
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 10015
99.1%
, 57
 
0.6%
& 14
 
0.1%
? 14
 
0.1%
· 5
 
< 0.1%
Space Separator
ValueCountFrequency (%)
20025
100.0%
Open Punctuation
ValueCountFrequency (%)
( 820
100.0%
Close Punctuation
ValueCountFrequency (%)
) 820
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79118
51.9%
Common 71992
47.2%
Latin 1356
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3517
 
4.4%
앞 2985
 
3.8%
역 2649
 
3.3%
번 2398
 
3.0%
출 2319
 
2.9%
동 2009
 
2.5%
교 1750
 
2.2%
리 1331
 
1.7%
원 1300
 
1.6%
파 1261
 
1.6%
Other values (445) 57599
72.8%
Latin
ValueCountFrequency (%)
S 169
12.5%
K 159
11.7%
T 119
 
8.8%
C 114
 
8.4%
B 90
 
6.6%
A 87
 
6.4%
D 72
 
5.3%
P 60
 
4.4%
G 59
 
4.4%
M 55
 
4.1%
Other values (21) 372
27.4%
Common
ValueCountFrequency (%)
20025
27.8%
. 10015
13.9%
1 9445
13.1%
2 5023
 
7.0%
3 3569
 
5.0%
4 3545
 
4.9%
0 3423
 
4.8%
6 3340
 
4.6%
5 3308
 
4.6%
7 3143
 
4.4%
Other values (11) 7156
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79112
51.9%
ASCII 73343
48.1%
None 11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20025
27.3%
. 10015
13.7%
1 9445
12.9%
2 5023
 
6.8%
3 3569
 
4.9%
4 3545
 
4.8%
0 3423
 
4.7%
6 3340
 
4.6%
5 3308
 
4.5%
7 3143
 
4.3%
Other values (41) 8507
11.6%
Hangul
ValueCountFrequency (%)
구 3517
 
4.4%
앞 2985
 
3.8%
역 2649
 
3.3%
번 2398
 
3.0%
출 2319
 
2.9%
동 2009
 
2.5%
교 1750
 
2.2%
리 1331
 
1.7%
원 1300
 
1.6%
파 1261
 
1.6%
Other values (444) 57593
72.8%
None
ValueCountFrequency (%)
㈜ 6
54.5%
· 5
45.5%

대여구분코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기
4874 
일일(회원)
3803 
단체
1047 
일일(비회원)
 
275
10분이용권
 
1

Length

Max length7
Median length2
Mean length3.6591
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row일일(회원)
2nd row일일(회원)
3rd row정기
4th row정기
5th row정기

Common Values

ValueCountFrequency (%)
정기 4874
48.7%
일일(회원) 3803
38.0%
단체 1047
 
10.5%
일일(비회원) 275
 
2.8%
10분이용권 1
 
< 0.1%

Length

2024-03-13T21:59:59.279487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:59:59.461805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 4874
48.7%
일일(회원 3803
38.0%
단체 1047
 
10.5%
일일(비회원 275
 
2.8%
10분이용권 1
 
< 0.1%

성별
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
\N
2971 
M
2962 
F
2772 
<NA>
1295 

Length

Max length4
Median length1
Mean length1.6856
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row\N
2nd row\N
3rd rowF
4th rowM
5th row\N

Common Values

ValueCountFrequency (%)
\N 2971
29.7%
M 2962
29.6%
F 2772
27.7%
<NA> 1295
13.0%

Length

2024-03-13T21:59:59.690452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:59:59.863943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 2971
29.7%
m 2962
29.6%
f 2772
27.7%
na 1295
13.0%

연령대코드
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
1723 
30대
1652 
40대
1591 
기타
1445 
10대
1247 
Other values (3)
2342 

Length

Max length5
Median length3
Mean length2.9175
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row40대
2nd row60대
3rd row20대
4th row20대
5th row30대

Common Values

ValueCountFrequency (%)
20대 1723
17.2%
30대 1652
16.5%
40대 1591
15.9%
기타 1445
14.4%
10대 1247
12.5%
50대 1219
12.2%
60대 813
8.1%
70대이상 310
 
3.1%

Length

2024-03-13T22:00:00.021349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:00:00.167895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 1723
17.2%
30대 1652
16.5%
40대 1591
15.9%
기타 1445
14.4%
10대 1247
12.5%
50대 1219
12.2%
60대 813
8.1%
70대이상 310
 
3.1%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct357
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.8288
Minimum1
Maximum2000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:00:00.337141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median10
Q334
95-th percentile137
Maximum2000
Range1999
Interquartile range (IQR)31

Descriptive statistics

Standard deviation65.812777
Coefficient of variation (CV)2.0047269
Kurtosis114.51113
Mean32.8288
Median Absolute Deviation (MAD)8
Skewness7.170401
Sum328288
Variance4331.3216
MonotonicityNot monotonic
2024-03-13T22:00:00.514772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1209
 
12.1%
2 1036
 
10.4%
3 607
 
6.1%
4 525
 
5.2%
5 356
 
3.6%
6 347
 
3.5%
7 317
 
3.2%
8 248
 
2.5%
9 222
 
2.2%
10 210
 
2.1%
Other values (347) 4923
49.2%
ValueCountFrequency (%)
1 1209
12.1%
2 1036
10.4%
3 607
6.1%
4 525
5.2%
5 356
 
3.6%
6 347
 
3.5%
7 317
 
3.2%
8 248
 
2.5%
9 222
 
2.2%
10 210
 
2.1%
ValueCountFrequency (%)
2000 1
< 0.1%
1052 1
< 0.1%
958 1
< 0.1%
842 1
< 0.1%
818 1
< 0.1%
772 1
< 0.1%
756 1
< 0.1%
746 1
< 0.1%
692 1
< 0.1%
680 1
< 0.1%

운동량
Text

Distinct9691
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T22:00:01.040515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.3612
Min length2

Characters and Unicode

Total characters63612
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

Unique9455 ?
Unique (%)94.5%

Sample

1st row3584.84
2nd row24.10
3rd row3768.64
4th row6944.72
5th row3461.11
ValueCountFrequency (%)
0.00 50
 
0.5%
n 7
 
0.1%
32.95 6
 
0.1%
22.91 5
 
< 0.1%
170.10 3
 
< 0.1%
66.77 3
 
< 0.1%
45.71 3
 
< 0.1%
40.67 3
 
< 0.1%
266.74 3
 
< 0.1%
81.96 3
 
< 0.1%
Other values (9681) 9914
99.1%
2024-03-13T22:00:01.606214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9993
15.7%
1 7501
11.8%
2 6127
9.6%
3 5749
9.0%
4 5325
8.4%
6 5000
7.9%
5 4991
7.8%
7 4826
7.6%
8 4738
7.4%
9 4693
7.4%
Other values (3) 4669
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53605
84.3%
Other Punctuation 10000
 
15.7%
Uppercase Letter 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7501
14.0%
2 6127
11.4%
3 5749
10.7%
4 5325
9.9%
6 5000
9.3%
5 4991
9.3%
7 4826
9.0%
8 4738
8.8%
9 4693
8.8%
0 4655
8.7%
Other Punctuation
ValueCountFrequency (%)
. 9993
99.9%
\ 7
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63605
> 99.9%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9993
15.7%
1 7501
11.8%
2 6127
9.6%
3 5749
9.0%
4 5325
8.4%
6 5000
7.9%
5 4991
7.8%
7 4826
7.6%
8 4738
7.4%
9 4693
7.4%
Other values (2) 4662
7.3%
Latin
ValueCountFrequency (%)
N 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63612
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9993
15.7%
1 7501
11.8%
2 6127
9.6%
3 5749
9.0%
4 5325
8.4%
6 5000
7.9%
5 4991
7.8%
7 4826
7.6%
8 4738
7.4%
9 4693
7.4%
Other values (3) 4669
7.3%

탄소량
Text

Distinct4035
Distinct (%)40.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T22:00:02.099210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.4668
Min length2

Characters and Unicode

Total characters44668
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

Unique2284 ?
Unique (%)22.8%

Sample

1st row31.63
2nd row0.19
3rd row37.37
4th row59.32
5th row30.66
ValueCountFrequency (%)
0.00 53
 
0.5%
0.45 23
 
0.2%
0.35 23
 
0.2%
0.44 23
 
0.2%
0.24 23
 
0.2%
0.21 22
 
0.2%
0.27 22
 
0.2%
0.36 22
 
0.2%
0.34 22
 
0.2%
0.28 21
 
0.2%
Other values (4025) 9746
97.5%
2024-03-13T22:00:02.742896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9993
22.4%
1 5478
12.3%
0 4133
9.3%
2 4104
9.2%
3 3646
 
8.2%
4 3191
 
7.1%
5 3100
 
6.9%
6 2971
 
6.7%
7 2786
 
6.2%
8 2662
 
6.0%
Other values (3) 2604
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34661
77.6%
Other Punctuation 10000
 
22.4%
Uppercase Letter 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5478
15.8%
0 4133
11.9%
2 4104
11.8%
3 3646
10.5%
4 3191
9.2%
5 3100
8.9%
6 2971
8.6%
7 2786
8.0%
8 2662
7.7%
9 2590
7.5%
Other Punctuation
ValueCountFrequency (%)
. 9993
99.9%
\ 7
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44661
> 99.9%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9993
22.4%
1 5478
12.3%
0 4133
9.3%
2 4104
9.2%
3 3646
 
8.2%
4 3191
 
7.1%
5 3100
 
6.9%
6 2971
 
6.7%
7 2786
 
6.2%
8 2662
 
6.0%
Other values (2) 2597
 
5.8%
Latin
ValueCountFrequency (%)
N 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44668
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9993
22.4%
1 5478
12.3%
0 4133
9.3%
2 4104
9.2%
3 3646
 
8.2%
4 3191
 
7.1%
5 3100
 
6.9%
6 2971
 
6.7%
7 2786
 
6.2%
8 2662
 
6.0%
Other values (3) 2604
 
5.8%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct9626
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95202.505
Minimum0
Maximum12141224
Zeros55
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:00:02.971802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1532.836
Q18592.2075
median30861.68
Q399690.663
95-th percentile377412.78
Maximum12141224
Range12141224
Interquartile range (IQR)91098.455

Descriptive statistics

Standard deviation217522.11
Coefficient of variation (CV)2.284836
Kurtosis960.87252
Mean95202.505
Median Absolute Deviation (MAD)26853.545
Skewness20.040929
Sum9.5202505 × 108
Variance4.7315868 × 1010
MonotonicityNot monotonic
2024-03-13T22:00:03.195558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 55
 
0.5%
890.0 7
 
0.1%
1520.0 6
 
0.1%
2450.0 5
 
0.1%
1280.0 5
 
0.1%
1700.0 5
 
0.1%
1550.0 4
 
< 0.1%
570.0 4
 
< 0.1%
1560.0 4
 
< 0.1%
1250.0 4
 
< 0.1%
Other values (9616) 9901
99.0%
ValueCountFrequency (%)
0.0 55
0.5%
0.48 1
 
< 0.1%
1.24 1
 
< 0.1%
17.41 1
 
< 0.1%
18.39 1
 
< 0.1%
20.0 1
 
< 0.1%
27.2 1
 
< 0.1%
34.45 1
 
< 0.1%
40.0 1
 
< 0.1%
50.0 1
 
< 0.1%
ValueCountFrequency (%)
12141223.81 1
< 0.1%
2824682.8 1
< 0.1%
2777642.02 1
< 0.1%
2718526.68 1
< 0.1%
2566985.64 1
< 0.1%
2400204.96 1
< 0.1%
2381578.14 1
< 0.1%
2277362.14 1
< 0.1%
1974190.83 1
< 0.1%
1902988.62 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2556
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean821.8991
Minimum0
Maximum126700
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:00:03.406469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15
Q183
median283
Q3869
95-th percentile3258.5
Maximum126700
Range126700
Interquartile range (IQR)786

Descriptive statistics

Standard deviation1973.4209
Coefficient of variation (CV)2.4010501
Kurtosis1671.7019
Mean821.8991
Median Absolute Deviation (MAD)242
Skewness28.418088
Sum8218991
Variance3894390
MonotonicityNot monotonic
2024-03-13T22:00:03.588953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11 49
 
0.5%
12 48
 
0.5%
8 45
 
0.4%
9 44
 
0.4%
20 43
 
0.4%
15 43
 
0.4%
10 43
 
0.4%
13 42
 
0.4%
7 42
 
0.4%
14 41
 
0.4%
Other values (2546) 9560
95.6%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 6
 
0.1%
2 11
 
0.1%
3 29
0.3%
4 27
0.3%
5 35
0.4%
6 29
0.3%
7 42
0.4%
8 45
0.4%
9 44
0.4%
ValueCountFrequency (%)
126700 1
< 0.1%
28662 1
< 0.1%
24932 1
< 0.1%
20900 1
< 0.1%
19839 1
< 0.1%
19235 1
< 0.1%
18507 1
< 0.1%
18404 1
< 0.1%
18236 1
< 0.1%
17580 1
< 0.1%

Interactions

2024-03-13T21:59:56.664081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:54.674742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:55.135834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:56.147184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:56.783648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:54.791502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:55.241819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:56.272078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:56.910163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:54.911811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:55.361443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:56.419676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:57.044992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:55.024315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:55.967853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:56.542906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:00:03.730553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호대여구분코드성별연령대코드이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0000.0090.0000.0600.0670.045
대여구분코드0.0001.0000.1740.3010.1030.0400.040
성별0.0090.1741.0000.0570.0420.0000.006
연령대코드0.0000.3010.0571.0000.1520.0990.089
이용건수0.0600.1030.0420.1521.0000.8340.809
이동거리(M)0.0670.0400.0000.0990.8341.0000.968
이용시간(분)0.0450.0400.0060.0890.8090.9681.000
2024-03-13T22:00:03.908155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여구분코드성별연령대코드
대여구분코드1.0000.1320.189
성별0.1321.0000.036
연령대코드0.1890.0361.000
2024-03-13T22:00:04.065897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여소번호1.000-0.028-0.025-0.0400.0000.0050.000
이용건수-0.0281.0000.9370.9360.0660.0280.082
이동거리(M)-0.0250.9371.0000.9770.0330.0000.045
이용시간(분)-0.0400.9360.9771.0000.0330.0060.040
대여구분코드0.0000.0660.0330.0331.0000.1320.189
성별0.0050.0280.0000.0060.1321.0000.036
연령대코드0.0000.0820.0450.0400.1890.0361.000

Missing values

2024-03-13T21:59:57.217551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:59:57.424959image/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

대여일자대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
60552022-04227227. 양평2나들목 보행통로 입구일일(회원)\N40대223584.8431.63136359.841127
306252022-04806806. 전자랜드 본관 앞일일(회원)\N60대124.100.19833.629
708562022-0419621962. 가리봉동주민센터정기F20대1223768.6437.37161013.671500
308192022-04809809. 한남 유수지 복개주차장정기M20대556944.7259.32255796.891620
355812022-04948948. 디지털미디어 시티역 4번출구(DMC역)정기\N30대813461.1130.66131934.491134
142982022-04413413. 상암월드컵파크 3단지 후문정기\N60대5243.962.169329.969
335272022-04900900. 은평예술회관일일(회원)\N50대127.760.251078.4490
369172022-04984984.상신초등학교앞 버스정류장일일(회원)M10대7387.114.5019375.23150
628722022-0416781678. 성서대학교 밀알관정기M60대4277.002.5010761.51153
614182022-0416461646. 삼육대 입구일일(비회원)\N기타213558.2432.09138237.17913
대여일자대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
84632022-04275275. 신동아아파트일일(회원)F기타151779.2317.2174165.59591
548192022-0414221422. 신내우디안아파트 1단지일일(회원)\N50대156.120.461968.2916
283702022-04755755. 목동1단지아파트 상가 앞일일(회원)\N40대151339.7711.6950419.1629
714912022-0419811981. 천왕이펜하우스5단지 앞단체F기타2300.872.7111688.63156
134022022-04393393. 동대문역 8번 출구정기F10대7640.486.5328178.48157
733532022-0420372037. 동작역 5번출구 동작주차공원정기M10대5648.355.5223780.91235
748902022-0420892089.사당역10번출구(금강빌딩)정기M기타451819.8514.5962945.06509
675412022-0418311831. 메이퀸웨딩컨벤션 앞정기F기타9477.974.2018180.12120
174322022-04485485.서울역5번출구정기M50대758099.0968.73296443.332239
230902022-04613613. 신설동역 10번출구 앞정기<NA>60대193.630.602570.029