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 = 22.62774784)Skewed
이용시간(분) is highly skewed (γ1 = 32.37143523)Skewed

Reproduction

Analysis started2024-05-03 22:11:56.727185
Analysis finished2024-05-03 22:12:06.006800
Duration9.28 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
2024-05-03T22:12:06.189123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:12:06.614822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대여소번호
Real number (ℝ)

Distinct1488
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1061.2455
Minimum5
Maximum2210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:12:07.077129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile183
Q1533
median1041
Q31539
95-th percentile2082
Maximum2210
Range2205
Interquartile range (IQR)1006

Descriptive statistics

Standard deviation601.53162
Coefficient of variation (CV)0.56681665
Kurtosis-1.1127235
Mean1061.2455
Median Absolute Deviation (MAD)504
Skewness0.18191671
Sum10612455
Variance361840.28
MonotonicityNot monotonic
2024-05-03T22:12:07.799423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1160 17
 
0.2%
445 17
 
0.2%
1653 15
 
0.1%
1512 15
 
0.1%
2173 14
 
0.1%
474 14
 
0.1%
1259 14
 
0.1%
1395 14
 
0.1%
126 14
 
0.1%
144 14
 
0.1%
Other values (1478) 9852
98.5%
ValueCountFrequency (%)
5 4
 
< 0.1%
11 1
 
< 0.1%
102 6
0.1%
103 7
0.1%
104 7
0.1%
105 8
0.1%
106 11
0.1%
107 6
0.1%
108 10
0.1%
109 6
0.1%
ValueCountFrequency (%)
2210 9
0.1%
2207 2
 
< 0.1%
2206 8
0.1%
2205 8
0.1%
2203 7
0.1%
2202 8
0.1%
2201 3
 
< 0.1%
2199 1
 
< 0.1%
2198 5
0.1%
2196 8
0.1%

대여소명
Text

Distinct1488
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-03T22:12:08.527362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length15.2901
Min length5

Characters and Unicode

Total characters152901
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

Unique14 ?
Unique (%)0.1%

Sample

1st row1287. 위례아이파크 101동 맞은편
2nd row917. 녹번역 3번출구
3rd row367. 독립문역 3-1번출구
4th row1528. 삼각산동 주민센터
5th row1193. 마곡센트럴타워 1차
ValueCountFrequency (%)
앞 2554
 
8.6%
옆 550
 
1.8%
출구 383
 
1.3%
1번출구 277
 
0.9%
사거리 256
 
0.9%
3번출구 248
 
0.8%
4번출구 236
 
0.8%
2번출구 233
 
0.8%
뒤 221
 
0.7%
교차로 220
 
0.7%
Other values (3070) 24643
82.6%
2024-05-03T22:12:09.920012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19997
 
13.1%
. 10026
 
6.6%
1 9304
 
6.1%
2 5120
 
3.3%
3 3618
 
2.4%
4 3602
 
2.4%
구 3500
 
2.3%
5 3448
 
2.3%
0 3410
 
2.2%
6 3259
 
2.1%
Other values (499) 87617
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79539
52.0%
Decimal Number 40145
26.3%
Space Separator 19997
 
13.1%
Other Punctuation 10126
 
6.6%
Uppercase Letter 1175
 
0.8%
Open Punctuation 860
 
0.6%
Close Punctuation 860
 
0.6%
Lowercase Letter 121
 
0.1%
Dash Punctuation 55
 
< 0.1%
Math Symbol 10
 
< 0.1%
Other values (2) 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3500
 
4.4%
앞 2984
 
3.8%
역 2690
 
3.4%
번 2424
 
3.0%
출 2369
 
3.0%
동 2104
 
2.6%
교 1728
 
2.2%
리 1389
 
1.7%
원 1269
 
1.6%
파 1252
 
1.6%
Other values (446) 57830
72.7%
Uppercase Letter
ValueCountFrequency (%)
K 143
12.2%
S 136
11.6%
C 123
10.5%
B 95
8.1%
T 88
 
7.5%
D 82
 
7.0%
A 82
 
7.0%
I 69
 
5.9%
M 66
 
5.6%
G 61
 
5.2%
Other values (11) 230
19.6%
Decimal Number
ValueCountFrequency (%)
1 9304
23.2%
2 5120
12.8%
3 3618
 
9.0%
4 3602
 
9.0%
5 3448
 
8.6%
0 3410
 
8.5%
6 3259
 
8.1%
7 3117
 
7.8%
9 2692
 
6.7%
8 2575
 
6.4%
Lowercase Letter
ValueCountFrequency (%)
e 49
40.5%
l 14
 
11.6%
n 12
 
9.9%
o 8
 
6.6%
c 8
 
6.6%
m 8
 
6.6%
t 8
 
6.6%
y 6
 
5.0%
k 4
 
3.3%
s 4
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 10026
99.0%
, 71
 
0.7%
? 13
 
0.1%
& 12
 
0.1%
· 4
 
< 0.1%
Space Separator
ValueCountFrequency (%)
19997
100.0%
Open Punctuation
ValueCountFrequency (%)
( 860
100.0%
Close Punctuation
ValueCountFrequency (%)
) 860
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79545
52.0%
Common 72060
47.1%
Latin 1296
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3500
 
4.4%
앞 2984
 
3.8%
역 2690
 
3.4%
번 2424
 
3.0%
출 2369
 
3.0%
동 2104
 
2.6%
교 1728
 
2.2%
리 1389
 
1.7%
원 1269
 
1.6%
파 1252
 
1.6%
Other values (447) 57836
72.7%
Latin
ValueCountFrequency (%)
K 143
11.0%
S 136
 
10.5%
C 123
 
9.5%
B 95
 
7.3%
T 88
 
6.8%
D 82
 
6.3%
A 82
 
6.3%
I 69
 
5.3%
M 66
 
5.1%
G 61
 
4.7%
Other values (21) 351
27.1%
Common
ValueCountFrequency (%)
19997
27.8%
. 10026
13.9%
1 9304
12.9%
2 5120
 
7.1%
3 3618
 
5.0%
4 3602
 
5.0%
5 3448
 
4.8%
0 3410
 
4.7%
6 3259
 
4.5%
7 3117
 
4.3%
Other values (11) 7159
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79539
52.0%
ASCII 73352
48.0%
None 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19997
27.3%
. 10026
13.7%
1 9304
12.7%
2 5120
 
7.0%
3 3618
 
4.9%
4 3602
 
4.9%
5 3448
 
4.7%
0 3410
 
4.6%
6 3259
 
4.4%
7 3117
 
4.2%
Other values (41) 8451
11.5%
Hangul
ValueCountFrequency (%)
구 3500
 
4.4%
앞 2984
 
3.8%
역 2690
 
3.4%
번 2424
 
3.0%
출 2369
 
3.0%
동 2104
 
2.6%
교 1728
 
2.2%
리 1389
 
1.7%
원 1269
 
1.6%
파 1252
 
1.6%
Other values (446) 57830
72.7%
None
ValueCountFrequency (%)
㈜ 6
60.0%
· 4
40.0%

대여구분코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기
4829 
일일(회원)
3814 
단체
1046 
일일(비회원)
 
310
10분이용권
 
1

Length

Max length7
Median length2
Mean length3.681
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
정기 4829
48.3%
일일(회원) 3814
38.1%
단체 1046
 
10.5%
일일(비회원) 310
 
3.1%
10분이용권 1
 
< 0.1%

Length

2024-05-03T22:12:10.422145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T22:12:10.835646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 4829
48.3%
일일(회원 3814
38.1%
단체 1046
 
10.5%
일일(비회원 310
 
3.1%
10분이용권 1
 
< 0.1%

성별
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
\N
2939 
F
2921 
M
2912 
<NA>
1226 
m
 
2

Length

Max length4
Median length1
Mean length1.6617
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
\N 2939
29.4%
F 2921
29.2%
M 2912
29.1%
<NA> 1226
12.3%
m 2
 
< 0.1%

Length

2024-05-03T22:12:11.203404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T22:12:11.595748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 2939
29.4%
f 2921
29.2%
m 2914
29.1%
na 1226
12.3%

연령대코드
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
1718 
30대
1619 
40대
1577 
기타
1456 
50대
1277 
Other values (3)
2353 

Length

Max length5
Median length3
Mean length2.9142
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30대
2nd row기타
3rd row기타
4th row기타
5th row50대

Common Values

ValueCountFrequency (%)
20대 1718
17.2%
30대 1619
16.2%
40대 1577
15.8%
기타 1456
14.6%
50대 1277
12.8%
10대 1252
12.5%
60대 802
8.0%
70대이상 299
 
3.0%

Length

2024-05-03T22:12:11.987152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T22:12:12.444485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 1718
17.2%
30대 1619
16.2%
40대 1577
15.8%
기타 1456
14.6%
50대 1277
12.8%
10대 1252
12.5%
60대 802
8.0%
70대이상 299
 
3.0%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct352
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.6616
Minimum1
Maximum2340
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:12:12.979311image/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 deviation64.449962
Coefficient of variation (CV)1.9732641
Kurtosis188.09795
Mean32.6616
Median Absolute Deviation (MAD)8
Skewness8.3232879
Sum326616
Variance4153.7977
MonotonicityNot monotonic
2024-05-03T22:12:13.542225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1226
 
12.3%
2 1033
 
10.3%
3 612
 
6.1%
4 536
 
5.4%
5 396
 
4.0%
6 357
 
3.6%
8 277
 
2.8%
7 262
 
2.6%
9 231
 
2.3%
10 194
 
1.9%
Other values (342) 4876
48.8%
ValueCountFrequency (%)
1 1226
12.3%
2 1033
10.3%
3 612
6.1%
4 536
5.4%
5 396
 
4.0%
6 357
 
3.6%
7 262
 
2.6%
8 277
 
2.8%
9 231
 
2.3%
10 194
 
1.9%
ValueCountFrequency (%)
2340 1
< 0.1%
840 1
< 0.1%
756 2
< 0.1%
751 1
< 0.1%
746 1
< 0.1%
706 1
< 0.1%
668 1
< 0.1%
667 1
< 0.1%
665 1
< 0.1%
628 1
< 0.1%

운동량
Text

Distinct9667
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-03T22:12:14.308598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.3587
Min length2

Characters and Unicode

Total characters63587
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

Unique9418 ?
Unique (%)94.2%

Sample

1st row1693.59
2nd row906.46
3rd row352.46
4th row320.51
5th row3835.39
ValueCountFrequency (%)
0.00 42
 
0.4%
n 12
 
0.1%
15.44 5
 
< 0.1%
33.26 4
 
< 0.1%
32.43 4
 
< 0.1%
29.34 4
 
< 0.1%
599.49 3
 
< 0.1%
177.49 3
 
< 0.1%
57.40 3
 
< 0.1%
120.26 3
 
< 0.1%
Other values (9657) 9917
99.2%
2024-05-03T22:12:15.644876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9988
15.7%
1 7362
11.6%
2 6150
9.7%
3 5666
8.9%
4 5441
8.6%
5 5148
8.1%
6 4881
7.7%
7 4792
7.5%
9 4739
7.5%
8 4724
7.4%
Other values (3) 4696
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53575
84.3%
Other Punctuation 10000
 
15.7%
Uppercase Letter 12
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7362
13.7%
2 6150
11.5%
3 5666
10.6%
4 5441
10.2%
5 5148
9.6%
6 4881
9.1%
7 4792
8.9%
9 4739
8.8%
8 4724
8.8%
0 4672
8.7%
Other Punctuation
ValueCountFrequency (%)
. 9988
99.9%
\ 12
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63575
> 99.9%
Latin 12
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9988
15.7%
1 7362
11.6%
2 6150
9.7%
3 5666
8.9%
4 5441
8.6%
5 5148
8.1%
6 4881
7.7%
7 4792
7.5%
9 4739
7.5%
8 4724
7.4%
Other values (2) 4684
7.4%
Latin
ValueCountFrequency (%)
N 12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63587
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9988
15.7%
1 7362
11.6%
2 6150
9.7%
3 5666
8.9%
4 5441
8.6%
5 5148
8.1%
6 4881
7.7%
7 4792
7.5%
9 4739
7.5%
8 4724
7.4%
Other values (3) 4696
7.4%

탄소량
Text

Distinct4062
Distinct (%)40.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-03T22:12:16.638949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.4652
Min length2

Characters and Unicode

Total characters44652
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

Unique2384 ?
Unique (%)23.8%

Sample

1st row16.98
2nd row9.45
3rd row3.45
4th row3.10
5th row31.68
ValueCountFrequency (%)
0.00 42
 
0.4%
0.37 25
 
0.2%
0.21 25
 
0.2%
0.29 25
 
0.2%
0.38 24
 
0.2%
0.17 23
 
0.2%
0.55 23
 
0.2%
0.45 21
 
0.2%
0.15 21
 
0.2%
0.36 21
 
0.2%
Other values (4052) 9750
97.5%
2024-05-03T22:12:18.197747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9988
22.4%
1 5427
12.2%
2 4141
9.3%
0 4028
9.0%
3 3718
 
8.3%
4 3337
 
7.5%
5 3066
 
6.9%
6 2852
 
6.4%
7 2750
 
6.2%
8 2712
 
6.1%
Other values (3) 2633
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34640
77.6%
Other Punctuation 10000
 
22.4%
Uppercase Letter 12
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5427
15.7%
2 4141
12.0%
0 4028
11.6%
3 3718
10.7%
4 3337
9.6%
5 3066
8.9%
6 2852
8.2%
7 2750
7.9%
8 2712
7.8%
9 2609
7.5%
Other Punctuation
ValueCountFrequency (%)
. 9988
99.9%
\ 12
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44640
> 99.9%
Latin 12
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9988
22.4%
1 5427
12.2%
2 4141
9.3%
0 4028
9.0%
3 3718
 
8.3%
4 3337
 
7.5%
5 3066
 
6.9%
6 2852
 
6.4%
7 2750
 
6.2%
8 2712
 
6.1%
Other values (2) 2621
 
5.9%
Latin
ValueCountFrequency (%)
N 12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44652
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9988
22.4%
1 5427
12.2%
2 4141
9.3%
0 4028
9.0%
3 3718
 
8.3%
4 3337
 
7.5%
5 3066
 
6.9%
6 2852
 
6.4%
7 2750
 
6.2%
8 2712
 
6.1%
Other values (3) 2633
 
5.9%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct9603
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95537.849
Minimum0
Maximum13242494
Zeros52
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:12:18.682254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1501.4155
Q18995.59
median30506.54
Q3100198.81
95-th percentile394614.15
Maximum13242494
Range13242494
Interquartile range (IQR)91203.22

Descriptive statistics

Standard deviation227501.44
Coefficient of variation (CV)2.3812703
Kurtosis1141.8606
Mean95537.849
Median Absolute Deviation (MAD)26390.46
Skewness22.627748
Sum9.5537849 × 108
Variance5.1756904 × 1010
MonotonicityNot monotonic
2024-05-03T22:12:19.224667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 52
 
0.5%
550.0 7
 
0.1%
1080.0 6
 
0.1%
1180.0 6
 
0.1%
730.0 5
 
0.1%
1620.0 5
 
0.1%
1600.0 5
 
0.1%
370.0 5
 
0.1%
1210.0 5
 
0.1%
1260.0 5
 
0.1%
Other values (9593) 9899
99.0%
ValueCountFrequency (%)
0.0 52
0.5%
5.53 1
 
< 0.1%
10.0 1
 
< 0.1%
29.99 1
 
< 0.1%
30.0 1
 
< 0.1%
43.23 1
 
< 0.1%
80.0 1
 
< 0.1%
88.43 1
 
< 0.1%
94.27 1
 
< 0.1%
111.2 2
 
< 0.1%
ValueCountFrequency (%)
13242493.51 1
< 0.1%
3479998.42 1
< 0.1%
2982563.34 1
< 0.1%
2919230.41 1
< 0.1%
2824682.8 1
< 0.1%
2542851.48 1
< 0.1%
2540146.36 1
< 0.1%
2511486.09 1
< 0.1%
2440652.4 1
< 0.1%
2400204.96 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2573
Distinct (%)25.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean819.3263
Minimum0
Maximum136334
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T22:12:19.673327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14
Q185
median274
Q3888
95-th percentile3327.35
Maximum136334
Range136334
Interquartile range (IQR)803

Descriptive statistics

Standard deviation2022.1903
Coefficient of variation (CV)2.4681135
Kurtosis2031.7109
Mean819.3263
Median Absolute Deviation (MAD)235
Skewness32.371435
Sum8193263
Variance4089253.6
MonotonicityNot monotonic
2024-05-03T22:12:20.256721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 52
 
0.5%
11 52
 
0.5%
15 51
 
0.5%
5 49
 
0.5%
7 44
 
0.4%
18 42
 
0.4%
17 42
 
0.4%
6 42
 
0.4%
9 41
 
0.4%
8 40
 
0.4%
Other values (2563) 9545
95.5%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 3
 
< 0.1%
2 26
0.3%
3 29
0.3%
4 29
0.3%
5 49
0.5%
6 42
0.4%
7 44
0.4%
8 40
0.4%
9 41
0.4%
ValueCountFrequency (%)
136334 1
< 0.1%
24932 1
< 0.1%
23863 1
< 0.1%
22926 1
< 0.1%
20903 1
< 0.1%
20628 1
< 0.1%
20494 1
< 0.1%
19839 1
< 0.1%
19748 1
< 0.1%
18984 1
< 0.1%

Interactions

2024-05-03T22:12:03.445458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:11:59.162242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:12:00.412996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:12:02.085137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:12:03.779781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:11:59.413631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:12:00.764480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:12:02.396929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:12:04.116784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:11:59.718696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:12:01.389524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:12:02.757378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:12:04.520875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:12:00.052128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:12:01.703371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T22:12:03.097357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T22:12:20.599687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호대여구분코드성별연령대코드이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0380.0000.0190.0510.0590.062
대여구분코드0.0381.0000.1400.3220.1380.0160.000
성별0.0000.1401.0000.1030.0160.0000.000
연령대코드0.0190.3220.1031.0000.1410.0840.053
이용건수0.0510.1380.0160.1411.0000.7240.784
이동거리(M)0.0590.0160.0000.0840.7241.0000.801
이용시간(분)0.0620.0000.0000.0530.7840.8011.000
2024-05-03T22:12:20.974797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별연령대코드대여구분코드
성별1.0000.0470.115
연령대코드0.0471.0000.204
대여구분코드0.1150.2041.000
2024-05-03T22:12:21.231260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여소번호1.000-0.036-0.034-0.0480.0160.0000.009
이용건수-0.0361.0000.9360.9370.0520.0130.086
이동거리(M)-0.0340.9361.0000.9770.0130.0000.038
이용시간(분)-0.0480.9370.9771.0000.0000.0000.033
대여구분코드0.0160.0520.0130.0001.0000.1150.204
성별0.0000.0130.0000.0000.1151.0000.047
연령대코드0.0090.0860.0380.0330.2040.0471.000

Missing values

2024-05-03T22:12:05.036021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T22:12:05.729874image/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)
497782022-0412871287. 위례아이파크 101동 맞은편정기F30대341693.5916.9873266.03652
344662022-04917917. 녹번역 3번출구일일(회원)F기타16906.469.4540758.04530
124082022-04367367. 독립문역 3-1번출구일일(회원)F기타6352.463.4514888.34173
583302022-0415281528. 삼각산동 주민센터단체M기타4320.513.1013359.72185
455532022-0411931193. 마곡센트럴타워 1차정기\N50대843835.3931.68136406.191160
248242022-04656656. 영휘원 교차로정기\N기타26752.777.3631681.76340
563902022-0414571457. 동원사거리정기\N40대8522.134.5819785.72302
25352022-04150150. 서강대역 2번출구 앞정기F30대523936.7539.47170145.831709
431272022-0411371137. 등촌2동주민센터일일(회원)\N30대5491.505.8225129.87282
386182022-0410251025. 상일초등학교정기<NA>50대6363.802.9112533.3774
대여일자대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
229422022-04609609. 제기2교정기M60대181299.2010.9247011.6438
451392022-0411841184. 마곡13단지정기\N20대36212585.15114.67494302.453486
359842022-04959959. 구파발10단지 인근일일(회원)F기타6333.273.2514059.65155
731912022-0420332033. 사당동 아르테스 웨딩앞정기M70대이상111.160.11461.843
415462022-0410901090.상일동역 2번출구 앞일일(회원)M50대91040.769.0238902.42281
405232022-0410691069.강동경희대학교병원 입구정기M70대이상234.910.301317.411
509462022-0413211321. 국민은행 종암동지점 앞정기\N40대323788.3430.49131408.191059
370822022-04991991.흥국사 정류장일일(회원)M기타5702.186.0526029.14139
97162022-04300300. 정동사거리일일(회원)M40대11585.224.5819753.93190
420162022-0411121112. 마곡엠밸리4단지 정문일일(회원)\N50대133.920.281189.557