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) has 395 (4.0%) zerosZeros

Reproduction

Analysis started2024-05-03 22:12:59.616920
Analysis finished2024-05-03 22:13:08.572774
Duration8.96 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
Minimum2022-02-01 00:00:00
Maximum2022-02-01 00:00:00
2024-05-03T22:13:08.835119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:09.089138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct2466
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1994.0031
Minimum3
Maximum4829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:13:09.473775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile229
Q1836.75
median1716
Q32921
95-th percentile4536
Maximum4829
Range4826
Interquartile range (IQR)2084.25

Descriptive statistics

Standard deviation1362.7517
Coefficient of variation (CV)0.68342507
Kurtosis-0.90865795
Mean1994.0031
Median Absolute Deviation (MAD)976
Skewness0.51357332
Sum19940031
Variance1857092.2
MonotonicityNot monotonic
2024-05-03T22:13:09.889604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2702 13
 
0.1%
1150 12
 
0.1%
502 12
 
0.1%
2719 12
 
0.1%
299 12
 
0.1%
147 11
 
0.1%
773 11
 
0.1%
1267 11
 
0.1%
1946 11
 
0.1%
703 11
 
0.1%
Other values (2456) 9884
98.8%
ValueCountFrequency (%)
3 1
 
< 0.1%
5 1
 
< 0.1%
10 1
 
< 0.1%
102 4
< 0.1%
103 3
< 0.1%
104 4
< 0.1%
105 6
0.1%
106 7
0.1%
107 3
< 0.1%
108 4
< 0.1%
ValueCountFrequency (%)
4829 1
 
< 0.1%
4828 1
 
< 0.1%
4827 1
 
< 0.1%
4826 6
0.1%
4825 1
 
< 0.1%
4824 5
0.1%
4823 4
< 0.1%
4821 3
< 0.1%
4820 3
< 0.1%
4819 7
0.1%

대여소명
Text

Distinct2466
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-03T22:13:10.471603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length15.5782
Min length3

Characters and Unicode

Total characters155782
Distinct characters580
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

Unique212 ?
Unique (%)2.1%

Sample

1st row3427.인왕산 아이파크 정문
2nd row907. CJ 드림시티
3rd row1843. 독산고등학교
4th row562. 군자지하보도 앞
5th row4251. 공덕역 경의선숲길 커뮤니티센터
ValueCountFrequency (%)
앞 2733
 
9.3%
출구 411
 
1.4%
옆 385
 
1.3%
1번출구 280
 
1.0%
교차로 262
 
0.9%
입구 239
 
0.8%
사거리 230
 
0.8%
3번출구 191
 
0.7%
2번출구 182
 
0.6%
뒤 169
 
0.6%
Other values (4909) 24210
82.7%
2024-05-03T22:13:11.548642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19458
 
12.5%
. 10030
 
6.4%
1 7863
 
5.0%
2 6276
 
4.0%
3 4949
 
3.2%
4 4668
 
3.0%
5 3541
 
2.3%
0 3521
 
2.3%
6 3393
 
2.2%
7 3283
 
2.1%
Other values (570) 88800
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80424
51.6%
Decimal Number 42535
27.3%
Space Separator 19458
 
12.5%
Other Punctuation 10166
 
6.5%
Uppercase Letter 1221
 
0.8%
Close Punctuation 847
 
0.5%
Open Punctuation 847
 
0.5%
Lowercase Letter 172
 
0.1%
Dash Punctuation 76
 
< 0.1%
Math Symbol 19
 
< 0.1%
Other values (3) 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3212
 
4.0%
앞 3198
 
4.0%
역 2417
 
3.0%
번 2158
 
2.7%
동 2141
 
2.7%
출 2087
 
2.6%
교 1739
 
2.2%
파 1415
 
1.8%
아 1410
 
1.8%
리 1349
 
1.7%
Other values (507) 59298
73.7%
Uppercase Letter
ValueCountFrequency (%)
K 153
12.5%
S 143
11.7%
T 119
9.7%
C 116
9.5%
D 82
 
6.7%
A 78
 
6.4%
G 77
 
6.3%
M 59
 
4.8%
I 58
 
4.8%
P 57
 
4.7%
Other values (13) 279
22.9%
Lowercase Letter
ValueCountFrequency (%)
e 51
29.7%
s 25
14.5%
k 24
14.0%
t 13
 
7.6%
n 10
 
5.8%
g 7
 
4.1%
a 7
 
4.1%
l 7
 
4.1%
f 5
 
2.9%
r 5
 
2.9%
Other values (6) 18
 
10.5%
Decimal Number
ValueCountFrequency (%)
1 7863
18.5%
2 6276
14.8%
3 4949
11.6%
4 4668
11.0%
5 3541
8.3%
0 3521
8.3%
6 3393
8.0%
7 3283
7.7%
8 2592
 
6.1%
9 2449
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 10030
98.7%
, 88
 
0.9%
& 23
 
0.2%
· 14
 
0.1%
? 11
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 11
57.9%
+ 8
42.1%
Space Separator
ValueCountFrequency (%)
19458
100.0%
Close Punctuation
ValueCountFrequency (%)
) 847
100.0%
Open Punctuation
ValueCountFrequency (%)
( 847
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Other Number
ValueCountFrequency (%)
① 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80428
51.6%
Common 73961
47.5%
Latin 1393
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3212
 
4.0%
앞 3198
 
4.0%
역 2417
 
3.0%
번 2158
 
2.7%
동 2141
 
2.7%
출 2087
 
2.6%
교 1739
 
2.2%
파 1415
 
1.8%
아 1410
 
1.8%
리 1349
 
1.7%
Other values (508) 59302
73.7%
Latin
ValueCountFrequency (%)
K 153
 
11.0%
S 143
 
10.3%
T 119
 
8.5%
C 116
 
8.3%
D 82
 
5.9%
A 78
 
5.6%
G 77
 
5.5%
M 59
 
4.2%
I 58
 
4.2%
P 57
 
4.1%
Other values (29) 451
32.4%
Common
ValueCountFrequency (%)
19458
26.3%
. 10030
13.6%
1 7863
10.6%
2 6276
 
8.5%
3 4949
 
6.7%
4 4668
 
6.3%
5 3541
 
4.8%
0 3521
 
4.8%
6 3393
 
4.6%
7 3283
 
4.4%
Other values (13) 6979
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80424
51.6%
ASCII 75336
48.4%
None 18
 
< 0.1%
Enclosed Alphanum 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19458
25.8%
. 10030
13.3%
1 7863
10.4%
2 6276
 
8.3%
3 4949
 
6.6%
4 4668
 
6.2%
5 3541
 
4.7%
0 3521
 
4.7%
6 3393
 
4.5%
7 3283
 
4.4%
Other values (50) 8354
11.1%
Hangul
ValueCountFrequency (%)
구 3212
 
4.0%
앞 3198
 
4.0%
역 2417
 
3.0%
번 2158
 
2.7%
동 2141
 
2.7%
출 2087
 
2.6%
교 1739
 
2.2%
파 1415
 
1.8%
아 1410
 
1.8%
리 1349
 
1.7%
Other values (507) 59298
73.7%
None
ValueCountFrequency (%)
· 14
77.8%
㈜ 4
 
22.2%
Enclosed Alphanum
ValueCountFrequency (%)
① 4
100.0%

대여구분코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기
5704 
일일(회원)
3679 
단체
 
383
일일(비회원)
 
233
10분이용권
 
1

Length

Max length7
Median length2
Mean length3.5885
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
정기 5704
57.0%
일일(회원) 3679
36.8%
단체 383
 
3.8%
일일(비회원) 233
 
2.3%
10분이용권 1
 
< 0.1%

Length

2024-05-03T22:13:12.028626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T22:13:12.400265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 5704
57.0%
일일(회원 3679
36.8%
단체 383
 
3.8%
일일(비회원 233
 
2.3%
10분이용권 1
 
< 0.1%

성별
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
M
3304 
\N
2957 
F
2676 
<NA>
1057 
f
 
3

Length

Max length4
Median length1
Mean length1.6128
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M 3304
33.0%
\N 2957
29.6%
F 2676
26.8%
<NA> 1057
 
10.6%
f 3
 
< 0.1%
m 3
 
< 0.1%

Length

2024-05-03T22:13:12.804636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T22:13:13.320931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 3307
33.1%
n 2957
29.6%
f 2679
26.8%
na 1057
 
10.6%

연령대코드
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
1965 
30대
1764 
기타
1526 
40대
1508 
50대
1234 
Other values (3)
2003 

Length

Max length5
Median length3
Mean length2.8934
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
20대 1965
19.7%
30대 1764
17.6%
기타 1526
15.3%
40대 1508
15.1%
50대 1234
12.3%
10대 1045
10.4%
60대 728
 
7.3%
70대이상 230
 
2.3%

Length

2024-05-03T22:13:13.934669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T22:13:14.712505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 1965
19.7%
30대 1764
17.6%
기타 1526
15.3%
40대 1508
15.1%
50대 1234
12.3%
10대 1045
10.4%
60대 728
 
7.3%
70대이상 230
 
2.3%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct181
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.7658
Minimum1
Maximum288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:13:15.304462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q315
95-th percentile57.05
Maximum288
Range287
Interquartile range (IQR)13

Descriptive statistics

Standard deviation23.811292
Coefficient of variation (CV)1.7297427
Kurtosis24.409712
Mean13.7658
Median Absolute Deviation (MAD)4
Skewness4.1368312
Sum137658
Variance566.97765
MonotonicityNot monotonic
2024-05-03T22:13:15.816068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1964
19.6%
2 1386
13.9%
3 814
 
8.1%
4 634
 
6.3%
5 483
 
4.8%
6 436
 
4.4%
7 318
 
3.2%
8 318
 
3.2%
9 239
 
2.4%
11 225
 
2.2%
Other values (171) 3183
31.8%
ValueCountFrequency (%)
1 1964
19.6%
2 1386
13.9%
3 814
8.1%
4 634
 
6.3%
5 483
 
4.8%
6 436
 
4.4%
7 318
 
3.2%
8 318
 
3.2%
9 239
 
2.4%
10 184
 
1.8%
ValueCountFrequency (%)
288 1
< 0.1%
266 2
< 0.1%
265 1
< 0.1%
263 1
< 0.1%
247 1
< 0.1%
244 1
< 0.1%
243 1
< 0.1%
229 1
< 0.1%
228 1
< 0.1%
220 1
< 0.1%

운동량
Text

Distinct9069
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-03T22:13:16.790591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.9002
Min length2

Characters and Unicode

Total characters59002
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

Unique8586 ?
Unique (%)85.9%

Sample

1st row0.00
2nd row1139.85
3rd row248.48
4th row439.96
5th row1282.74
ValueCountFrequency (%)
0.00 373
 
3.7%
n 25
 
0.2%
25.74 4
 
< 0.1%
70.96 4
 
< 0.1%
48.13 4
 
< 0.1%
35.52 4
 
< 0.1%
18.85 4
 
< 0.1%
24.71 4
 
< 0.1%
32.43 3
 
< 0.1%
183.78 3
 
< 0.1%
Other values (9059) 9572
95.7%
2024-05-03T22:13:18.262731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9975
16.9%
1 6739
11.4%
2 5733
9.7%
3 5078
8.6%
0 5012
8.5%
4 4783
8.1%
5 4524
7.7%
6 4471
7.6%
7 4376
7.4%
8 4181
7.1%
Other values (3) 4130
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48977
83.0%
Other Punctuation 10000
 
16.9%
Uppercase Letter 25
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6739
13.8%
2 5733
11.7%
3 5078
10.4%
0 5012
10.2%
4 4783
9.8%
5 4524
9.2%
6 4471
9.1%
7 4376
8.9%
8 4181
8.5%
9 4080
8.3%
Other Punctuation
ValueCountFrequency (%)
. 9975
99.8%
\ 25
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58977
> 99.9%
Latin 25
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9975
16.9%
1 6739
11.4%
2 5733
9.7%
3 5078
8.6%
0 5012
8.5%
4 4783
8.1%
5 4524
7.7%
6 4471
7.6%
7 4376
7.4%
8 4181
7.1%
Other values (2) 4105
7.0%
Latin
ValueCountFrequency (%)
N 25
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59002
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9975
16.9%
1 6739
11.4%
2 5733
9.7%
3 5078
8.6%
0 5012
8.5%
4 4783
8.1%
5 4524
7.7%
6 4471
7.6%
7 4376
7.4%
8 4181
7.1%
Other values (3) 4130
7.0%

탄소량
Text

Distinct2302
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-03T22:13:19.325625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.1816
Min length2

Characters and Unicode

Total characters41816
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

Unique1057 ?
Unique (%)10.6%

Sample

1st row0.00
2nd row8.64
3rd row2.02
4th row3.67
5th row10.18
ValueCountFrequency (%)
0.00 372
 
3.7%
0.28 46
 
0.5%
0.58 41
 
0.4%
0.51 40
 
0.4%
0.39 40
 
0.4%
0.22 39
 
0.4%
0.24 38
 
0.4%
0.32 35
 
0.4%
0.55 35
 
0.4%
0.72 35
 
0.4%
Other values (2292) 9279
92.8%
2024-05-03T22:13:20.750135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9975
23.9%
0 5655
13.5%
1 4796
11.5%
2 3746
 
9.0%
3 3048
 
7.3%
4 2779
 
6.6%
5 2650
 
6.3%
7 2392
 
5.7%
6 2349
 
5.6%
9 2212
 
5.3%
Other values (3) 2214
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31791
76.0%
Other Punctuation 10000
 
23.9%
Uppercase Letter 25
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5655
17.8%
1 4796
15.1%
2 3746
11.8%
3 3048
9.6%
4 2779
8.7%
5 2650
8.3%
7 2392
7.5%
6 2349
7.4%
9 2212
 
7.0%
8 2164
 
6.8%
Other Punctuation
ValueCountFrequency (%)
. 9975
99.8%
\ 25
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41791
99.9%
Latin 25
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9975
23.9%
0 5655
13.5%
1 4796
11.5%
2 3746
 
9.0%
3 3048
 
7.3%
4 2779
 
6.6%
5 2650
 
6.3%
7 2392
 
5.7%
6 2349
 
5.6%
9 2212
 
5.3%
Other values (2) 2189
 
5.2%
Latin
ValueCountFrequency (%)
N 25
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41816
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9975
23.9%
0 5655
13.5%
1 4796
11.5%
2 3746
 
9.0%
3 3048
 
7.3%
4 2779
 
6.6%
5 2650
 
6.3%
7 2392
 
5.7%
6 2349
 
5.6%
9 2212
 
5.3%
Other values (3) 2214
 
5.3%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8820
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28076.977
Minimum0
Maximum852223.87
Zeros395
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:13:21.307801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile460
Q13556.6725
median11224.5
Q331772.192
95-th percentile112023.56
Maximum852223.87
Range852223.87
Interquartile range (IQR)28215.52

Descriptive statistics

Standard deviation47052.864
Coefficient of variation (CV)1.6758522
Kurtosis31.66099
Mean28076.977
Median Absolute Deviation (MAD)9297.645
Skewness4.3626663
Sum2.8076977 × 108
Variance2.213972 × 109
MonotonicityNot monotonic
2024-05-03T22:13:21.814792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 395
 
4.0%
1380.0 8
 
0.1%
1290.0 8
 
0.1%
850.0 8
 
0.1%
1730.0 8
 
0.1%
1790.0 6
 
0.1%
1680.0 6
 
0.1%
2980.0 6
 
0.1%
1260.0 6
 
0.1%
3220.0 6
 
0.1%
Other values (8810) 9543
95.4%
ValueCountFrequency (%)
0.0 395
4.0%
0.1 2
 
< 0.1%
26.69 1
 
< 0.1%
30.0 1
 
< 0.1%
40.0 1
 
< 0.1%
60.0 1
 
< 0.1%
70.0 1
 
< 0.1%
87.84 1
 
< 0.1%
88.16 1
 
< 0.1%
110.0 1
 
< 0.1%
ValueCountFrequency (%)
852223.87 1
< 0.1%
627285.44 1
< 0.1%
581971.55 1
< 0.1%
528688.14 1
< 0.1%
521551.74 1
< 0.1%
510160.22 1
< 0.1%
496610.88 1
< 0.1%
457511.43 1
< 0.1%
424872.32 1
< 0.1%
405375.31 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct1434
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean291.1189
Minimum0
Maximum10554
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:13:22.376663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q142
median120
Q3324
95-th percentile1166.05
Maximum10554
Range10554
Interquartile range (IQR)282

Descriptive statistics

Standard deviation486.61203
Coefficient of variation (CV)1.6715233
Kurtosis42.522952
Mean291.1189
Median Absolute Deviation (MAD)97
Skewness4.7349858
Sum2911189
Variance236791.27
MonotonicityNot monotonic
2024-05-03T22:13:22.891414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 96
 
1.0%
6 90
 
0.9%
8 88
 
0.9%
7 79
 
0.8%
12 79
 
0.8%
13 77
 
0.8%
9 72
 
0.7%
5 72
 
0.7%
17 70
 
0.7%
26 70
 
0.7%
Other values (1424) 9207
92.1%
ValueCountFrequency (%)
0 3
 
< 0.1%
1 9
 
0.1%
2 42
0.4%
3 47
0.5%
4 66
0.7%
5 72
0.7%
6 90
0.9%
7 79
0.8%
8 88
0.9%
9 72
0.7%
ValueCountFrequency (%)
10554 1
< 0.1%
7240 1
< 0.1%
6138 1
< 0.1%
5031 1
< 0.1%
4968 1
< 0.1%
4800 1
< 0.1%
4785 1
< 0.1%
4764 1
< 0.1%
4697 1
< 0.1%
4681 1
< 0.1%

Interactions

2024-05-03T22:13:06.641026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:03.433893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:04.794513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:05.887823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:06.879988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:03.792506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:05.068289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:06.087691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:07.138995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:04.159337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:05.344749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:06.270694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:07.408358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:04.489582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:05.606747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:13:06.446548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T22:13:23.350293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호대여구분코드성별연령대코드이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0380.0300.0280.0730.0410.038
대여구분코드0.0381.0000.2870.3410.3410.1850.154
성별0.0300.2871.0000.0480.1080.0750.059
연령대코드0.0280.3410.0481.0000.1810.1310.167
이용건수0.0730.3410.1080.1811.0000.7000.694
이동거리(M)0.0410.1850.0750.1310.7001.0000.835
이용시간(분)0.0380.1540.0590.1670.6940.8351.000
2024-05-03T22:13:23.660098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별연령대코드대여구분코드
성별1.0000.0290.110
연령대코드0.0291.0000.217
대여구분코드0.1100.2171.000
2024-05-03T22:13:23.928738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여소번호1.000-0.055-0.071-0.0790.0160.0120.013
이용건수-0.0551.0000.8660.8800.1480.0450.087
이동거리(M)-0.0710.8661.0000.9420.1070.0430.064
이용시간(분)-0.0790.8800.9421.0000.0940.0360.057
대여구분코드0.0160.1480.1070.0941.0000.1100.217
성별0.0120.0450.0430.0360.1101.0000.029
연령대코드0.0130.0870.0640.0570.2170.0291.000

Missing values

2024-05-03T22:13:07.790064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T22:13:08.334949image/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)
750762022-0234273427.인왕산 아이파크 정문일일(회원)F30대10.000.000.07
254212022-02907907. CJ 드림시티일일(회원)<NA>20대91139.858.6437259.94406
511002022-0218431843. 독산고등학교일일(회원)M20대5248.482.028714.1759
156782022-02562562. 군자지하보도 앞정기M60대12439.963.6715914.13103
876592022-0242514251. 공덕역 경의선숲길 커뮤니티센터정기\N30대231282.7410.1843957.94332
704572022-0227392739.수명산파크1단지교차로정기\N30대601619.6713.0756368.71598
93032022-02364364. 창신역 1번출구 앞정기F20대11182.181.807798.4478
736212022-0232013201.당산skv1센터정기M50대312480.6321.3492107.96748
413772022-0214281428. 원묵고등학교정기M40대9554.084.4118987.87221
931802022-0246254625. 용산공원갤러리앞정기F50대2163.722.048796.3399
대여일자대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
611982022-0222942294. 두상빌딩 앞일일(회원)\N30대496.010.833597.341
526582022-0219311931. 개봉역2번출구 A정기<NA>30대6288.782.008579.3178
85992022-02342342. 대학로 마로니에공원정기M기타26973.408.2335545.39444
197312022-02708708. 서울출입국관리사무소 앞일일(회원)M30대21634.945.7324680.91179
464912022-0216561656. 중앙하이츠 아파트 입구일일(회원)M30대91068.289.1139264.92275
709502022-0228092809.항동지구 11단지 1103동 앞정기M30대160.750.552360.027
234572022-02816816. 신용산역 6번출구 앞정기M10대1108.760.803433.045
370102022-0212691269. 리센츠아파트정기M기타282386.8417.5675785.82740
501052022-0217751775.신원리베르텔 앞정기<NA>60대3112.261.044499.6237
874632022-0242394239. 성산2동 주민센터정기\N50대1110.190.863710.051