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/A/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 = 25.10974807)Skewed
이용시간(분) is highly skewed (γ1 = 30.824026)Skewed

Reproduction

Analysis started2024-05-18 00:15:09.416350
Analysis finished2024-05-18 00:15:16.837119
Duration7.42 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
2024-05-18T09:15:16.968431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:17.260843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct1491
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1058.0693
Minimum3
Maximum2210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:15:17.619788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile183
Q1534.75
median1032
Q31538.25
95-th percentile2077
Maximum2210
Range2207
Interquartile range (IQR)1003.5

Descriptive statistics

Standard deviation600.9675
Coefficient of variation (CV)0.56798501
Kurtosis-1.1166767
Mean1058.0693
Median Absolute Deviation (MAD)503
Skewness0.18242264
Sum10580693
Variance361161.93
MonotonicityNot monotonic
2024-05-18T09:15:17.959197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2050 18
 
0.2%
1222 15
 
0.1%
1552 15
 
0.1%
1351 15
 
0.1%
1557 15
 
0.1%
1231 14
 
0.1%
2113 14
 
0.1%
1121 14
 
0.1%
1268 14
 
0.1%
2173 14
 
0.1%
Other values (1481) 9852
98.5%
ValueCountFrequency (%)
3 2
 
< 0.1%
5 2
 
< 0.1%
10 1
 
< 0.1%
102 7
0.1%
103 10
0.1%
104 9
0.1%
105 9
0.1%
106 6
0.1%
107 10
0.1%
108 8
0.1%
ValueCountFrequency (%)
2210 6
0.1%
2207 2
 
< 0.1%
2206 6
0.1%
2205 3
 
< 0.1%
2203 4
 
< 0.1%
2202 11
0.1%
2201 3
 
< 0.1%
2199 5
0.1%
2198 6
0.1%
2196 7
0.1%

대여소명
Text

Distinct1491
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:15:18.512983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length15.2192
Min length3

Characters and Unicode

Total characters152192
Distinct characters509
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

Unique19 ?
Unique (%)0.2%

Sample

1st row268. 그랜드컨벤션센터 앞
2nd row191. 서우빌딩
3rd row2016. 신대방삼거리역 3번출구쪽
4th row1833. 독산역 1번출구 앞 자전거보관소
5th row1296. 석촌호수교차로 (송파나루근린공원 앞)
ValueCountFrequency (%)
앞 2650
 
8.9%
옆 498
 
1.7%
출구 387
 
1.3%
1번출구 290
 
1.0%
입구 242
 
0.8%
교차로 241
 
0.8%
2번출구 234
 
0.8%
사거리 232
 
0.8%
3번출구 229
 
0.8%
뒤 218
 
0.7%
Other values (3076) 24611
82.5%
2024-05-18T09:15:19.458374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19999
 
13.1%
. 10027
 
6.6%
1 9149
 
6.0%
2 5059
 
3.3%
3 3686
 
2.4%
4 3486
 
2.3%
5 3473
 
2.3%
6 3381
 
2.2%
구 3380
 
2.2%
0 3318
 
2.2%
Other values (499) 87234
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79145
52.0%
Decimal Number 40020
26.3%
Space Separator 19999
 
13.1%
Other Punctuation 10115
 
6.6%
Uppercase Letter 1202
 
0.8%
Close Punctuation 770
 
0.5%
Open Punctuation 770
 
0.5%
Lowercase Letter 110
 
0.1%
Dash Punctuation 36
 
< 0.1%
Math Symbol 13
 
< 0.1%
Other values (2) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3380
 
4.3%
앞 3061
 
3.9%
역 2533
 
3.2%
번 2333
 
2.9%
출 2248
 
2.8%
동 2092
 
2.6%
교 1785
 
2.3%
리 1406
 
1.8%
원 1261
 
1.6%
아 1254
 
1.6%
Other values (446) 57792
73.0%
Uppercase Letter
ValueCountFrequency (%)
S 167
13.9%
K 164
13.6%
T 111
9.2%
C 108
9.0%
B 87
 
7.2%
A 82
 
6.8%
D 68
 
5.7%
G 61
 
5.1%
I 57
 
4.7%
M 55
 
4.6%
Other values (11) 242
20.1%
Decimal Number
ValueCountFrequency (%)
1 9149
22.9%
2 5059
12.6%
3 3686
9.2%
4 3486
 
8.7%
5 3473
 
8.7%
6 3381
 
8.4%
0 3318
 
8.3%
7 3111
 
7.8%
9 2690
 
6.7%
8 2667
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
e 44
40.0%
l 12
 
10.9%
n 12
 
10.9%
t 6
 
5.5%
c 6
 
5.5%
o 6
 
5.5%
m 6
 
5.5%
y 6
 
5.5%
s 6
 
5.5%
k 6
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 10027
99.1%
, 54
 
0.5%
& 16
 
0.2%
? 12
 
0.1%
· 6
 
0.1%
Space Separator
ValueCountFrequency (%)
19999
100.0%
Close Punctuation
ValueCountFrequency (%)
) 770
100.0%
Open Punctuation
ValueCountFrequency (%)
( 770
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79151
52.0%
Common 71729
47.1%
Latin 1312
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3380
 
4.3%
앞 3061
 
3.9%
역 2533
 
3.2%
번 2333
 
2.9%
출 2248
 
2.8%
동 2092
 
2.6%
교 1785
 
2.3%
리 1406
 
1.8%
원 1261
 
1.6%
아 1254
 
1.6%
Other values (447) 57798
73.0%
Latin
ValueCountFrequency (%)
S 167
12.7%
K 164
12.5%
T 111
 
8.5%
C 108
 
8.2%
B 87
 
6.6%
A 82
 
6.2%
D 68
 
5.2%
G 61
 
4.6%
I 57
 
4.3%
M 55
 
4.2%
Other values (21) 352
26.8%
Common
ValueCountFrequency (%)
19999
27.9%
. 10027
14.0%
1 9149
12.8%
2 5059
 
7.1%
3 3686
 
5.1%
4 3486
 
4.9%
5 3473
 
4.8%
6 3381
 
4.7%
0 3318
 
4.6%
7 3111
 
4.3%
Other values (11) 7040
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79145
52.0%
ASCII 73035
48.0%
None 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19999
27.4%
. 10027
13.7%
1 9149
12.5%
2 5059
 
6.9%
3 3686
 
5.0%
4 3486
 
4.8%
5 3473
 
4.8%
6 3381
 
4.6%
0 3318
 
4.5%
7 3111
 
4.3%
Other values (41) 8346
11.4%
Hangul
ValueCountFrequency (%)
구 3380
 
4.3%
앞 3061
 
3.9%
역 2533
 
3.2%
번 2333
 
2.9%
출 2248
 
2.8%
동 2092
 
2.6%
교 1785
 
2.3%
리 1406
 
1.8%
원 1261
 
1.6%
아 1254
 
1.6%
Other values (446) 57792
73.0%
None
ValueCountFrequency (%)
㈜ 6
50.0%
· 6
50.0%

대여구분코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기
4807 
일일(회원)
3879 
단체
1020 
일일(비회원)
 
293
10분이용권
 
1

Length

Max length7
Median length2
Mean length3.6985
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
정기 4807
48.1%
일일(회원) 3879
38.8%
단체 1020
 
10.2%
일일(비회원) 293
 
2.9%
10분이용권 1
 
< 0.1%

Length

2024-05-18T09:15:19.880424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:15:20.116818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 4807
48.1%
일일(회원 3879
38.8%
단체 1020
 
10.2%
일일(비회원 293
 
2.9%
10분이용권 1
 
< 0.1%

성별
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
M
3063 
\N
2857 
F
2844 
<NA>
1234 
m
 
2

Length

Max length4
Median length1
Mean length1.6559
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M 3063
30.6%
\N 2857
28.6%
F 2844
28.4%
<NA> 1234
12.3%
m 2
 
< 0.1%

Length

2024-05-18T09:15:20.342324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:15:20.588925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 3065
30.6%
n 2857
28.6%
f 2844
28.4%
na 1234
12.3%

연령대코드
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
1776 
30대
1599 
40대
1593 
기타
1469 
50대
1248 
Other values (3)
2315 

Length

Max length5
Median length3
Mean length2.9115
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row70대이상
2nd row20대
3rd row10대
4th row20대
5th row20대

Common Values

ValueCountFrequency (%)
20대 1776
17.8%
30대 1599
16.0%
40대 1593
15.9%
기타 1469
14.7%
50대 1248
12.5%
10대 1236
12.4%
60대 787
7.9%
70대이상 292
 
2.9%

Length

2024-05-18T09:15:20.976096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:15:21.324944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 1776
17.8%
30대 1599
16.0%
40대 1593
15.9%
기타 1469
14.7%
50대 1248
12.5%
10대 1236
12.4%
60대 787
7.9%
70대이상 292
 
2.9%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct348
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.1183
Minimum1
Maximum2340
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:15:21.672121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median10
Q335
95-th percentile138
Maximum2340
Range2339
Interquartile range (IQR)32

Descriptive statistics

Standard deviation68.036718
Coefficient of variation (CV)2.0543542
Kurtosis229.95529
Mean33.1183
Median Absolute Deviation (MAD)8
Skewness9.947433
Sum331183
Variance4628.995
MonotonicityNot monotonic
2024-05-18T09:15:22.023952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1160
 
11.6%
2 1057
 
10.6%
3 603
 
6.0%
4 507
 
5.1%
5 383
 
3.8%
6 338
 
3.4%
7 296
 
3.0%
8 269
 
2.7%
9 224
 
2.2%
11 208
 
2.1%
Other values (338) 4955
49.5%
ValueCountFrequency (%)
1 1160
11.6%
2 1057
10.6%
3 603
6.0%
4 507
5.1%
5 383
 
3.8%
6 338
 
3.4%
7 296
 
3.0%
8 269
 
2.7%
9 224
 
2.2%
10 203
 
2.0%
ValueCountFrequency (%)
2340 1
< 0.1%
1925 1
< 0.1%
1538 1
< 0.1%
692 2
< 0.1%
665 1
< 0.1%
645 1
< 0.1%
631 1
< 0.1%
628 1
< 0.1%
623 1
< 0.1%
620 1
< 0.1%

운동량
Text

Distinct9714
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:15:22.742429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.3738
Min length2

Characters and Unicode

Total characters63738
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

Unique9488 ?
Unique (%)94.9%

Sample

1st row35.20
2nd row77.47
3rd row350.53
4th row1337.19
5th row828.72
ValueCountFrequency (%)
0.00 41
 
0.4%
n 8
 
0.1%
32.95 4
 
< 0.1%
36.12 3
 
< 0.1%
6.84 3
 
< 0.1%
9.27 3
 
< 0.1%
41.82 3
 
< 0.1%
14.67 3
 
< 0.1%
108.94 3
 
< 0.1%
103.73 3
 
< 0.1%
Other values (9704) 9926
99.3%
2024-05-18T09:15:23.847402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9992
15.7%
1 7441
11.7%
2 6180
9.7%
3 5600
8.8%
4 5414
8.5%
5 5113
8.0%
6 4958
7.8%
7 4946
7.8%
0 4751
7.5%
8 4714
7.4%
Other values (3) 4629
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53730
84.3%
Other Punctuation 10000
 
15.7%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7441
13.8%
2 6180
11.5%
3 5600
10.4%
4 5414
10.1%
5 5113
9.5%
6 4958
9.2%
7 4946
9.2%
0 4751
8.8%
8 4714
8.8%
9 4613
8.6%
Other Punctuation
ValueCountFrequency (%)
. 9992
99.9%
\ 8
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63730
> 99.9%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9992
15.7%
1 7441
11.7%
2 6180
9.7%
3 5600
8.8%
4 5414
8.5%
5 5113
8.0%
6 4958
7.8%
7 4946
7.8%
0 4751
7.5%
8 4714
7.4%
Other values (2) 4621
7.3%
Latin
ValueCountFrequency (%)
N 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63738
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9992
15.7%
1 7441
11.7%
2 6180
9.7%
3 5600
8.8%
4 5414
8.5%
5 5113
8.0%
6 4958
7.8%
7 4946
7.8%
0 4751
7.5%
8 4714
7.4%
Other values (3) 4629
7.3%

탄소량
Text

Distinct4086
Distinct (%)40.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:15:24.605060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.4802
Min length2

Characters and Unicode

Total characters44802
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

Unique2345 ?
Unique (%)23.4%

Sample

1st row0.29
2nd row0.70
3rd row2.90
4th row10.65
5th row8.73
ValueCountFrequency (%)
0.00 37
 
0.4%
0.38 25
 
0.2%
0.32 24
 
0.2%
0.33 22
 
0.2%
0.44 22
 
0.2%
0.14 21
 
0.2%
0.63 21
 
0.2%
0.89 21
 
0.2%
0.22 21
 
0.2%
0.52 20
 
0.2%
Other values (4076) 9766
97.7%
2024-05-18T09:15:25.557780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9992
22.3%
1 5472
12.2%
2 4205
9.4%
0 4031
9.0%
3 3643
 
8.1%
4 3266
 
7.3%
5 3122
 
7.0%
6 2912
 
6.5%
7 2761
 
6.2%
8 2718
 
6.1%
Other values (3) 2680
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34794
77.7%
Other Punctuation 10000
 
22.3%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5472
15.7%
2 4205
12.1%
0 4031
11.6%
3 3643
10.5%
4 3266
9.4%
5 3122
9.0%
6 2912
8.4%
7 2761
7.9%
8 2718
7.8%
9 2664
7.7%
Other Punctuation
ValueCountFrequency (%)
. 9992
99.9%
\ 8
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44794
> 99.9%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9992
22.3%
1 5472
12.2%
2 4205
9.4%
0 4031
9.0%
3 3643
 
8.1%
4 3266
 
7.3%
5 3122
 
7.0%
6 2912
 
6.5%
7 2761
 
6.2%
8 2718
 
6.1%
Other values (2) 2672
 
6.0%
Latin
ValueCountFrequency (%)
N 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44802
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9992
22.3%
1 5472
12.2%
2 4205
9.4%
0 4031
9.0%
3 3643
 
8.1%
4 3266
 
7.3%
5 3122
 
7.0%
6 2912
 
6.5%
7 2761
 
6.2%
8 2718
 
6.1%
Other values (3) 2680
 
6.0%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct9627
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98710.87
Minimum0
Maximum13242494
Zeros44
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:15:25.881658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1584.9295
Q19018.265
median32059.915
Q3101940.14
95-th percentile398495.4
Maximum13242494
Range13242494
Interquartile range (IQR)92921.873

Descriptive statistics

Standard deviation262896.99
Coefficient of variation (CV)2.6633033
Kurtosis1072.8422
Mean98710.87
Median Absolute Deviation (MAD)27894.775
Skewness25.109748
Sum9.871087 × 108
Variance6.9114825 × 1010
MonotonicityNot monotonic
2024-05-18T09:15:26.178848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 44
 
0.4%
1620.0 8
 
0.1%
3080.0 6
 
0.1%
1660.0 5
 
0.1%
940.0 5
 
0.1%
640.0 5
 
0.1%
1400.0 5
 
0.1%
1910.0 5
 
0.1%
1380.0 5
 
0.1%
600.0 5
 
0.1%
Other values (9617) 9907
99.1%
ValueCountFrequency (%)
0.0 44
0.4%
0.1 1
 
< 0.1%
0.39 1
 
< 0.1%
30.0 1
 
< 0.1%
50.0 1
 
< 0.1%
59.16 1
 
< 0.1%
64.66 1
 
< 0.1%
70.0 1
 
< 0.1%
88.2 1
 
< 0.1%
111.2 1
 
< 0.1%
ValueCountFrequency (%)
13242493.51 1
< 0.1%
11571660.22 1
< 0.1%
7878975.15 1
< 0.1%
3094716.71 1
< 0.1%
2982563.34 1
< 0.1%
2629543.96 1
< 0.1%
2495489.0 1
< 0.1%
2407453.05 1
< 0.1%
2305086.17 1
< 0.1%
2260455.27 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2600
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean850.8778
Minimum0
Maximum136334
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:15:26.499156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15
Q187
median285
Q3888
95-th percentile3394.15
Maximum136334
Range136334
Interquartile range (IQR)801

Descriptive statistics

Standard deviation2423.7293
Coefficient of variation (CV)2.8485045
Kurtosis1473.6428
Mean850.8778
Median Absolute Deviation (MAD)245
Skewness30.824026
Sum8508778
Variance5874463.5
MonotonicityNot monotonic
2024-05-18T09:15:26.952092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 53
 
0.5%
12 52
 
0.5%
11 46
 
0.5%
25 45
 
0.4%
15 42
 
0.4%
17 41
 
0.4%
20 41
 
0.4%
34 40
 
0.4%
6 39
 
0.4%
5 38
 
0.4%
Other values (2590) 9563
95.6%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 5
 
0.1%
2 19
0.2%
3 31
0.3%
4 34
0.3%
5 38
0.4%
6 39
0.4%
7 35
0.4%
8 31
0.3%
9 38
0.4%
ValueCountFrequency (%)
136334 1
< 0.1%
106491 1
< 0.1%
82975 1
< 0.1%
27937 1
< 0.1%
20628 1
< 0.1%
20595 1
< 0.1%
20348 1
< 0.1%
18578 1
< 0.1%
18555 1
< 0.1%
17565 1
< 0.1%

Interactions

2024-05-18T09:15:14.598315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:11.571922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:12.322726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:13.484233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:14.857752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:11.761829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:12.610278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:13.739691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:15.379256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:11.915067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:12.857438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:14.005561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:15.683431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:12.092979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:13.183358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:15:14.293597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T09:15:27.232500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호대여구분코드성별연령대코드이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0610.0140.0000.0430.0330.033
대여구분코드0.0611.0000.1410.3260.0890.0340.034
성별0.0140.1411.0000.0940.0280.0230.011
연령대코드0.0000.3260.0941.0000.1440.0510.022
이용건수0.0430.0890.0280.1441.0000.9820.980
이동거리(M)0.0330.0340.0230.0510.9821.0000.994
이용시간(분)0.0330.0340.0110.0220.9800.9941.000
2024-05-18T09:15:27.470838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령대코드성별대여구분코드
연령대코드1.0000.0420.207
성별0.0421.0000.115
대여구분코드0.2070.1151.000
2024-05-18T09:15:27.665433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여소번호1.000-0.039-0.033-0.0450.0250.0080.000
이용건수-0.0391.0000.9360.9370.0600.0180.080
이동거리(M)-0.0330.9361.0000.9770.0230.0150.028
이용시간(분)-0.0450.9370.9771.0000.0230.0070.012
대여구분코드0.0250.0600.0230.0231.0000.1150.207
성별0.0080.0180.0150.0070.1151.0000.042
연령대코드0.0000.0800.0280.0120.2070.0421.000

Missing values

2024-05-18T09:15:16.094208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T09:15:16.614928image/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)
81562022-04268268. 그랜드컨벤션센터 앞일일(회원)M70대이상135.200.291270.07
42452022-04191191. 서우빌딩단체<NA>20대277.470.703010.031
727682022-0420162016. 신대방삼거리역 3번출구쪽단체M10대3350.532.9012467.3386
675672022-0418331833. 독산역 1번출구 앞 자전거보관소일일(회원)M20대261337.1910.6545862.67617
501322022-0412961296. 석촌호수교차로 (송파나루근린공원 앞)단체\N20대7828.728.7337617.76633
204442022-04552552. 대림아크로리버 앞일일(회원)<NA>50대154.610.441889.0617
679702022-0418451845. 롯데캐슬골드파크1차 서문일일(회원)M기타9601.034.6920224.87323
166922022-04467467.한국은행정기M10대134.850.351491.513
703572022-0419511951. 천왕이펜하우스 4단지 후문일일(회원)F기타4538.665.0121596.74164
745712022-0420822082.7호선 이수역7번출구일일(회원)M30대262240.4117.4175079.411040
대여일자대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
480332022-0412461246. 문정 법조단지10일일(회원)\N기타91560.2614.6763214.38491
29472022-04161161. 무악재역1번 출구정기\N60대132.950.301280.09
669122022-0418161816. 금천폭포공원 앞정기M30대423364.8325.23108745.75632
13912022-04126126. 서강대 후문 옆정기F20대1314126.7542.80184429.121839
399562022-0410571057. 능골근린공원정기\N60대126.380.17740.085
561202022-0414521452. 겸재교 진입부단체F기타4515.574.7120272.36225
539672022-0413961396.래미안장위퍼스트하이(513동)일일(회원)M30대274265.6233.21143178.681022
353712022-04943943. 은평구청 보건소일일(회원)\N10대278.620.893863.4264
610902022-0416371637. KT 전화국 버스정류장 옆일일(회원)<NA>30대3109.680.994257.3738
207272022-04558558. 성동광진 교육지원청 앞정기\N30대995450.3649.35212719.672035