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

Reproduction

Analysis started2024-03-13 12:59:38.879980
Analysis finished2024-03-13 12:59:43.521669
Duration4.64 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
Minimum2022-05-01 00:00:00
Maximum2022-05-01 00:00:00
2024-03-13T21:59:43.569878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:43.693590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct1378
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean993.2868
Minimum3
Maximum2025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T21:59:43.856744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile181
Q1509
median1001
Q31433
95-th percentile1913
Maximum2025
Range2022
Interquartile range (IQR)924

Descriptive statistics

Standard deviation547.88816
Coefficient of variation (CV)0.5515911
Kurtosis-1.1417413
Mean993.2868
Median Absolute Deviation (MAD)462
Skewness0.12994092
Sum9932868
Variance300181.44
MonotonicityNot monotonic
2024-03-13T21:59:44.567386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1195 18
 
0.2%
1001 17
 
0.2%
1246 17
 
0.2%
1295 17
 
0.2%
293 17
 
0.2%
344 16
 
0.2%
605 16
 
0.2%
223 16
 
0.2%
458 16
 
0.2%
1158 16
 
0.2%
Other values (1368) 9834
98.3%
ValueCountFrequency (%)
3 1
 
< 0.1%
5 1
 
< 0.1%
102 15
0.1%
103 7
0.1%
104 7
0.1%
105 7
0.1%
106 10
0.1%
107 6
 
0.1%
108 3
 
< 0.1%
109 4
 
< 0.1%
ValueCountFrequency (%)
2025 8
0.1%
2024 11
0.1%
2020 12
0.1%
2016 12
0.1%
2015 6
0.1%
2013 2
 
< 0.1%
2012 7
0.1%
2009 6
0.1%
2008 8
0.1%
2007 11
0.1%

대여소명
Text

Distinct1378
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T21:59:44.927683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length15.2967
Min length4

Characters and Unicode

Total characters152967
Distinct characters498
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

Unique13 ?
Unique (%)0.1%

Sample

1st row1736. 버스정류장 앞
2nd row477.앰배서더 호텔 주변
3rd row931. 역촌파출소
4th row950. 구산역 2번 출구 예일여고 버스정류장
5th row508. 성수아카데미타워 앞
ValueCountFrequency (%)
앞 2673
 
8.9%
옆 536
 
1.8%
출구 366
 
1.2%
1번출구 279
 
0.9%
교차로 267
 
0.9%
뒤 255
 
0.8%
4번출구 250
 
0.8%
사거리 232
 
0.8%
2번출구 226
 
0.8%
3번출구 203
 
0.7%
Other values (2856) 24785
82.4%
2024-03-13T21:59:45.465374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20223
 
13.2%
. 10038
 
6.6%
1 9443
 
6.2%
2 4449
 
2.9%
3 3762
 
2.5%
4 3698
 
2.4%
5 3533
 
2.3%
6 3369
 
2.2%
구 3312
 
2.2%
앞 3083
 
2.0%
Other values (488) 88057
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79530
52.0%
Decimal Number 39930
26.1%
Space Separator 20223
 
13.2%
Other Punctuation 10142
 
6.6%
Uppercase Letter 1237
 
0.8%
Close Punctuation 805
 
0.5%
Open Punctuation 805
 
0.5%
Lowercase Letter 203
 
0.1%
Dash Punctuation 57
 
< 0.1%
Math Symbol 15
 
< 0.1%
Other values (2) 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3312
 
4.2%
앞 3083
 
3.9%
역 2534
 
3.2%
번 2333
 
2.9%
출 2247
 
2.8%
동 1992
 
2.5%
교 1671
 
2.1%
리 1387
 
1.7%
원 1332
 
1.7%
파 1323
 
1.7%
Other values (435) 58316
73.3%
Uppercase Letter
ValueCountFrequency (%)
K 159
12.9%
S 155
12.5%
C 112
 
9.1%
T 97
 
7.8%
B 87
 
7.0%
A 77
 
6.2%
D 69
 
5.6%
I 68
 
5.5%
G 59
 
4.8%
M 54
 
4.4%
Other values (11) 300
24.3%
Decimal Number
ValueCountFrequency (%)
1 9443
23.6%
2 4449
11.1%
3 3762
 
9.4%
4 3698
 
9.3%
5 3533
 
8.8%
6 3369
 
8.4%
0 3079
 
7.7%
7 3044
 
7.6%
9 2812
 
7.0%
8 2741
 
6.9%
Lowercase Letter
ValueCountFrequency (%)
e 62
30.5%
n 36
17.7%
l 29
14.3%
y 18
 
8.9%
o 11
 
5.4%
c 11
 
5.4%
t 11
 
5.4%
m 11
 
5.4%
s 7
 
3.4%
k 7
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 10038
99.0%
, 72
 
0.7%
& 18
 
0.2%
· 9
 
0.1%
? 5
 
< 0.1%
Space Separator
ValueCountFrequency (%)
20223
100.0%
Close Punctuation
ValueCountFrequency (%)
) 805
100.0%
Open Punctuation
ValueCountFrequency (%)
( 805
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79537
52.0%
Common 71990
47.1%
Latin 1440
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3312
 
4.2%
앞 3083
 
3.9%
역 2534
 
3.2%
번 2333
 
2.9%
출 2247
 
2.8%
동 1992
 
2.5%
교 1671
 
2.1%
리 1387
 
1.7%
원 1332
 
1.7%
파 1323
 
1.7%
Other values (436) 58323
73.3%
Latin
ValueCountFrequency (%)
K 159
 
11.0%
S 155
 
10.8%
C 112
 
7.8%
T 97
 
6.7%
B 87
 
6.0%
A 77
 
5.3%
D 69
 
4.8%
I 68
 
4.7%
e 62
 
4.3%
G 59
 
4.1%
Other values (21) 495
34.4%
Common
ValueCountFrequency (%)
20223
28.1%
. 10038
13.9%
1 9443
13.1%
2 4449
 
6.2%
3 3762
 
5.2%
4 3698
 
5.1%
5 3533
 
4.9%
6 3369
 
4.7%
0 3079
 
4.3%
7 3044
 
4.2%
Other values (11) 7352
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79530
52.0%
ASCII 73421
48.0%
None 16
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20223
27.5%
. 10038
13.7%
1 9443
12.9%
2 4449
 
6.1%
3 3762
 
5.1%
4 3698
 
5.0%
5 3533
 
4.8%
6 3369
 
4.6%
0 3079
 
4.2%
7 3044
 
4.1%
Other values (41) 8783
12.0%
Hangul
ValueCountFrequency (%)
구 3312
 
4.2%
앞 3083
 
3.9%
역 2534
 
3.2%
번 2333
 
2.9%
출 2247
 
2.8%
동 1992
 
2.5%
교 1671
 
2.1%
리 1387
 
1.7%
원 1332
 
1.7%
파 1323
 
1.7%
Other values (435) 58316
73.3%
None
ValueCountFrequency (%)
· 9
56.2%
㈜ 7
43.8%

대여구분코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기
4730 
일일(회원)
3883 
단체
1118 
일일(비회원)
 
268
10분이용권
 
1

Length

Max length7
Median length2
Mean length3.6876
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
정기 4730
47.3%
일일(회원) 3883
38.8%
단체 1118
 
11.2%
일일(비회원) 268
 
2.7%
10분이용권 1
 
< 0.1%

Length

2024-03-13T21:59:45.642066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:59:45.790244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 4730
47.3%
일일(회원 3883
38.8%
단체 1118
 
11.2%
일일(비회원 268
 
2.7%
10분이용권 1
 
< 0.1%

성별
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
M
3034 
\N
2833 
F
2780 
<NA>
1351 
m
 
2

Length

Max length4
Median length1
Mean length1.6886
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M 3034
30.3%
\N 2833
28.3%
F 2780
27.8%
<NA> 1351
13.5%
m 2
 
< 0.1%

Length

2024-03-13T21:59:45.947926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:59:46.097553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 3036
30.4%
n 2833
28.3%
f 2780
27.8%
na 1351
13.5%

연령대코드
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
1743 
40대
1569 
30대
1546 
기타
1384 
10대
1379 
Other values (3)
2379 

Length

Max length5
Median length3
Mean length2.9252
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row기타
3rd row50대
4th row50대
5th row50대

Common Values

ValueCountFrequency (%)
20대 1743
17.4%
40대 1569
15.7%
30대 1546
15.5%
기타 1384
13.8%
10대 1379
13.8%
50대 1247
12.5%
60대 814
8.1%
70대이상 318
 
3.2%

Length

2024-03-13T21:59:46.283166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:59:46.453817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 1743
17.4%
40대 1569
15.7%
30대 1546
15.5%
기타 1384
13.8%
10대 1379
13.8%
50대 1247
12.5%
60대 814
8.1%
70대이상 318
 
3.2%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct404
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.8127
Minimum1
Maximum1499
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T21:59:46.640120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median12
Q341
95-th percentile170
Maximum1499
Range1498
Interquartile range (IQR)38

Descriptive statistics

Standard deviation74.698356
Coefficient of variation (CV)1.9245854
Kurtosis50.421896
Mean38.8127
Median Absolute Deviation (MAD)10
Skewness5.303923
Sum388127
Variance5579.8444
MonotonicityNot monotonic
2024-03-13T21:59:46.963160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1085
 
10.8%
2 993
 
9.9%
3 533
 
5.3%
4 483
 
4.8%
5 390
 
3.9%
6 343
 
3.4%
7 302
 
3.0%
8 262
 
2.6%
9 206
 
2.1%
10 196
 
2.0%
Other values (394) 5207
52.1%
ValueCountFrequency (%)
1 1085
10.8%
2 993
9.9%
3 533
5.3%
4 483
4.8%
5 390
 
3.9%
6 343
 
3.4%
7 302
 
3.0%
8 262
 
2.6%
9 206
 
2.1%
10 196
 
2.0%
ValueCountFrequency (%)
1499 1
< 0.1%
1382 1
< 0.1%
1007 1
< 0.1%
988 1
< 0.1%
931 1
< 0.1%
886 1
< 0.1%
878 1
< 0.1%
788 1
< 0.1%
716 1
< 0.1%
703 1
< 0.1%

운동량
Text

Distinct9727
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T21:59:47.383481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.4203
Min length2

Characters and Unicode

Total characters64203
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

Unique9498 ?
Unique (%)95.0%

Sample

1st row1743.04
2nd row801.00
3rd row374.75
4th row3457.44
5th row2872.06
ValueCountFrequency (%)
0.00 20
 
0.2%
n 8
 
0.1%
68.98 4
 
< 0.1%
360.70 3
 
< 0.1%
109.14 3
 
< 0.1%
37.64 3
 
< 0.1%
31.36 3
 
< 0.1%
195.30 3
 
< 0.1%
49.70 3
 
< 0.1%
99.36 3
 
< 0.1%
Other values (9717) 9947
99.5%
2024-03-13T21:59:48.027903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9992
15.6%
1 7550
11.8%
2 6380
9.9%
3 5657
8.8%
5 5311
8.3%
4 5210
8.1%
6 4995
7.8%
7 4846
7.5%
8 4766
7.4%
9 4750
7.4%
Other values (3) 4746
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54195
84.4%
Other Punctuation 10000
 
15.6%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7550
13.9%
2 6380
11.8%
3 5657
10.4%
5 5311
9.8%
4 5210
9.6%
6 4995
9.2%
7 4846
8.9%
8 4766
8.8%
9 4750
8.8%
0 4730
8.7%
Other Punctuation
ValueCountFrequency (%)
. 9992
99.9%
\ 8
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64195
> 99.9%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9992
15.6%
1 7550
11.8%
2 6380
9.9%
3 5657
8.8%
5 5311
8.3%
4 5210
8.1%
6 4995
7.8%
7 4846
7.5%
8 4766
7.4%
9 4750
7.4%
Other values (2) 4738
7.4%
Latin
ValueCountFrequency (%)
N 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64203
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9992
15.6%
1 7550
11.8%
2 6380
9.9%
3 5657
8.8%
5 5311
8.3%
4 5210
8.1%
6 4995
7.8%
7 4846
7.5%
8 4766
7.4%
9 4750
7.4%
Other values (3) 4746
7.4%

탄소량
Text

Distinct4333
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T21:59:48.609280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.5154
Min length2

Characters and Unicode

Total characters45154
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

Unique2598 ?
Unique (%)26.0%

Sample

1st row14.19
2nd row7.22
3rd row2.85
4th row27.46
5th row23.66
ValueCountFrequency (%)
0.30 28
 
0.3%
0.62 26
 
0.3%
0.19 25
 
0.2%
0.52 24
 
0.2%
0.40 23
 
0.2%
0.59 22
 
0.2%
0.46 21
 
0.2%
0.28 21
 
0.2%
0.74 21
 
0.2%
0.00 21
 
0.2%
Other values (4323) 9768
97.7%
2024-03-13T21:59:49.606019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9992
22.1%
1 5448
12.1%
2 4243
9.4%
0 3989
 
8.8%
3 3690
 
8.2%
4 3303
 
7.3%
5 3227
 
7.1%
6 2946
 
6.5%
8 2857
 
6.3%
7 2785
 
6.2%
Other values (3) 2674
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35146
77.8%
Other Punctuation 10000
 
22.1%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5448
15.5%
2 4243
12.1%
0 3989
11.3%
3 3690
10.5%
4 3303
9.4%
5 3227
9.2%
6 2946
8.4%
8 2857
8.1%
7 2785
7.9%
9 2658
7.6%
Other Punctuation
ValueCountFrequency (%)
. 9992
99.9%
\ 8
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45146
> 99.9%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9992
22.1%
1 5448
12.1%
2 4243
9.4%
0 3989
 
8.8%
3 3690
 
8.2%
4 3303
 
7.3%
5 3227
 
7.1%
6 2946
 
6.5%
8 2857
 
6.3%
7 2785
 
6.2%
Other values (2) 2666
 
5.9%
Latin
ValueCountFrequency (%)
N 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45154
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9992
22.1%
1 5448
12.1%
2 4243
9.4%
0 3989
 
8.8%
3 3690
 
8.2%
4 3303
 
7.3%
5 3227
 
7.1%
6 2946
 
6.5%
8 2857
 
6.3%
7 2785
 
6.2%
Other values (3) 2674
 
5.9%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION 

Distinct9685
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111933.98
Minimum0
Maximum5708271.9
Zeros26
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T21:59:49.862452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1621.0335
Q19902.575
median36207.98
Q3117794.76
95-th percentile469954.86
Maximum5708271.9
Range5708271.9
Interquartile range (IQR)107892.18

Descriptive statistics

Standard deviation220306.61
Coefficient of variation (CV)1.9681836
Kurtosis80.925474
Mean111933.98
Median Absolute Deviation (MAD)31992.165
Skewness6.3457223
Sum1.1193398 × 109
Variance4.8535004 × 1010
MonotonicityNot monotonic
2024-03-13T21:59:50.134897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 26
 
0.3%
1710.0 6
 
0.1%
1410.0 6
 
0.1%
2250.0 5
 
0.1%
1370.0 5
 
0.1%
2680.0 5
 
0.1%
1980.0 5
 
0.1%
3960.0 4
 
< 0.1%
920.0 4
 
< 0.1%
1420.0 4
 
< 0.1%
Other values (9675) 9930
99.3%
ValueCountFrequency (%)
0.0 26
0.3%
0.1 1
 
< 0.1%
2.41 1
 
< 0.1%
10.0 1
 
< 0.1%
30.0 1
 
< 0.1%
70.0 1
 
< 0.1%
90.0 1
 
< 0.1%
91.44 1
 
< 0.1%
95.71 1
 
< 0.1%
100.0 1
 
< 0.1%
ValueCountFrequency (%)
5708271.87 1
< 0.1%
3979408.76 1
< 0.1%
3409186.14 1
< 0.1%
3194742.33 1
< 0.1%
2972153.92 1
< 0.1%
2446824.78 1
< 0.1%
2425095.27 1
< 0.1%
2322124.21 1
< 0.1%
2268857.72 1
< 0.1%
2203434.0 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct2773
Distinct (%)27.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean930.5337
Minimum1
Maximum44323
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T21:59:50.359166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15
Q192
median318.5
Q3997
95-th percentile3896.05
Maximum44323
Range44322
Interquartile range (IQR)905

Descriptive statistics

Standard deviation1761.1103
Coefficient of variation (CV)1.8925809
Kurtosis74.192359
Mean930.5337
Median Absolute Deviation (MAD)275.5
Skewness6.0438473
Sum9305337
Variance3101509.5
MonotonicityNot monotonic
2024-03-13T21:59:50.553904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 55
 
0.5%
7 52
 
0.5%
11 44
 
0.4%
18 43
 
0.4%
26 42
 
0.4%
12 42
 
0.4%
9 41
 
0.4%
22 39
 
0.4%
21 39
 
0.4%
16 38
 
0.4%
Other values (2763) 9565
95.7%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 18
 
0.2%
3 20
 
0.2%
4 32
0.3%
5 29
0.3%
6 38
0.4%
7 52
0.5%
8 35
0.4%
9 41
0.4%
10 55
0.5%
ValueCountFrequency (%)
44323 1
< 0.1%
32313 1
< 0.1%
26492 1
< 0.1%
24208 1
< 0.1%
22804 1
< 0.1%
22745 1
< 0.1%
20082 1
< 0.1%
17864 1
< 0.1%
17337 1
< 0.1%
16700 1
< 0.1%

Interactions

2024-03-13T21:59:42.653607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:40.835118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:41.404062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:41.945451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:42.795759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:41.000269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:41.565004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:42.190502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:42.931139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:41.134830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:41.699964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:42.394391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:43.043706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:41.279232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:41.819013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:59:42.527396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:59:50.665298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호대여구분코드성별연령대코드이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0150.0390.0220.0070.0660.067
대여구분코드0.0151.0000.1430.3070.1650.1040.108
성별0.0390.1431.0000.0990.0760.0000.000
연령대코드0.0220.3070.0991.0000.2760.2160.221
이용건수0.0070.1650.0760.2761.0000.8710.880
이동거리(M)0.0660.1040.0000.2160.8711.0000.984
이용시간(분)0.0670.1080.0000.2210.8800.9841.000
2024-03-13T21:59:50.815114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여구분코드성별연령대코드
대여구분코드1.0000.1170.194
성별0.1171.0000.045
연령대코드0.1940.0451.000
2024-03-13T21:59:50.934580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여소번호1.000-0.020-0.028-0.0410.0060.0230.010
이용건수-0.0201.0000.9450.9460.1010.0340.095
이동거리(M)-0.0280.9451.0000.9800.0630.0000.074
이용시간(분)-0.0410.9460.9801.0000.0660.0000.076
대여구분코드0.0060.1010.0630.0661.0000.1170.194
성별0.0230.0340.0000.0000.1171.0000.045
연령대코드0.0100.0950.0740.0760.1940.0451.000

Missing values

2024-03-13T21:59:43.205499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:59:43.423559image/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)
671722022-0517361736. 버스정류장 앞정기M기타441743.0414.1961140.22613
176742022-05477477.앰배서더 호텔 주변일일(비회원)\N기타8801.007.2231118.78239
359322022-05931931. 역촌파출소일일(회원)<NA>50대1374.752.8512290.0128
366632022-05950950. 구산역 2번 출구 예일여고 버스정류장정기M50대743457.4427.46118405.551170
190362022-05508508. 성수아카데미타워 앞정기\N50대662872.0623.66101924.631340
521202022-0513081308. 안암로터리 버스정류장 앞단체M40대5497.784.5219490.87191
98092022-05297297.국회3문정기M50대131638.1212.7154811.34350
210302022-05551551. 구의삼성쉐르빌 앞정기F60대136.030.371596.4226
743622022-0519931993. 금강수목원아파트 앞정기M30대633135.0922.4496538.77765
223202022-05577577. 광진청소년수련관일일(회원)M50대122051.9716.6972023.73651
대여일자대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
444992022-0511401140. 목동사거리 버스정류장단체F30대4271.322.4310480.0138
320402022-05815815. LIG강촌아파트 103동앞정기F20대10613149.24132.24569993.033862
694212022-0518271827. 독산보도육교 앞 자전거 보관소일일(회원)<NA>30대4266.272.8112165.275
191742022-05510510. 서울숲 남문 버스정류소 옆정기F20대849636.2395.88413259.83493
450572022-0511531153. 발산역 1번, 9번 인근 대여소일일(회원)<NA>10대223.770.271150.09
432202022-0511111111. 마곡엠밸리6_7단지 마곡중학교정기M40대18412394.12105.09453085.693917
267692022-05680680.꿈마루어린이도서관 앞정기M10대994144.5836.70158088.911288
53662022-05210210. IFC몰정기F70대이상143868.7228.29122007.74691
143372022-05408408. LG CNS앞일일(회원)M10대6273.002.3410086.6981
423192022-0510811081.트레빌빌딩정기M40대614417.6132.88141735.021278