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

Categorical4
Numeric4
Text3

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

Reproduction

Analysis started2024-05-18 00:14:11.373428
Analysis finished2024-05-18 00:14:20.441349
Duration9.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022-06
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-06
2nd row2022-06
3rd row2022-06
4th row2022-06
5th row2022-06

Common Values

ValueCountFrequency (%)
2022-06 10000
100.0%

Length

2024-05-18T09:14:20.634445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:14:20.924218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-06 10000
100.0%

대여소번호
Real number (ℝ)

Distinct1498
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1075.0167
Minimum5
Maximum2229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:14:21.382662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile185
Q1542
median1050
Q31552.25
95-th percentile2091
Maximum2229
Range2224
Interquartile range (IQR)1010.25

Descriptive statistics

Standard deviation606.81295
Coefficient of variation (CV)0.56446839
Kurtosis-1.1126953
Mean1075.0167
Median Absolute Deviation (MAD)507
Skewness0.17559292
Sum10750167
Variance368221.95
MonotonicityNot monotonic
2024-05-18T09:14:21.813507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1004 18
 
0.2%
1465 17
 
0.2%
259 16
 
0.2%
641 16
 
0.2%
870 16
 
0.2%
1295 16
 
0.2%
1721 15
 
0.1%
227 15
 
0.1%
1128 14
 
0.1%
1569 14
 
0.1%
Other values (1488) 9843
98.4%
ValueCountFrequency (%)
5 1
 
< 0.1%
102 7
0.1%
103 8
0.1%
104 5
0.1%
105 3
 
< 0.1%
106 10
0.1%
107 4
 
< 0.1%
108 6
0.1%
109 6
0.1%
111 6
0.1%
ValueCountFrequency (%)
2229 7
0.1%
2228 2
 
< 0.1%
2227 8
0.1%
2226 4
 
< 0.1%
2225 4
 
< 0.1%
2223 2
 
< 0.1%
2222 11
0.1%
2221 11
0.1%
2220 4
 
< 0.1%
2219 8
0.1%

대여소명
Text

Distinct1498
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:14:22.340220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length15.2382
Min length7

Characters and Unicode

Total characters152382
Distinct characters508
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 row792.목동트라팰리스 웨스턴에비뉴
2nd row1302. 한성대입구역6번출구 뒤
3rd row2003. 사육신공원앞
4th row1655. 공릉1단지아파트
5th row1768.신동아타워 버스정류소
ValueCountFrequency (%)
앞 2640
 
8.9%
옆 486
 
1.6%
출구 384
 
1.3%
1번출구 295
 
1.0%
2번출구 257
 
0.9%
사거리 240
 
0.8%
뒤 237
 
0.8%
입구 222
 
0.7%
3번출구 222
 
0.7%
4번출구 216
 
0.7%
Other values (3092) 24567
82.5%
2024-05-18T09:14:23.341962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19946
 
13.1%
. 10031
 
6.6%
1 9268
 
6.1%
2 5348
 
3.5%
4 3609
 
2.4%
3 3533
 
2.3%
구 3498
 
2.3%
0 3368
 
2.2%
5 3320
 
2.2%
6 3214
 
2.1%
Other values (498) 87247
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79072
51.9%
Decimal Number 40273
26.4%
Space Separator 19946
 
13.1%
Other Punctuation 10123
 
6.6%
Uppercase Letter 1183
 
0.8%
Open Punctuation 787
 
0.5%
Close Punctuation 787
 
0.5%
Lowercase Letter 125
 
0.1%
Dash Punctuation 62
 
< 0.1%
Math Symbol 10
 
< 0.1%
Other values (2) 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3498
 
4.4%
앞 3006
 
3.8%
역 2635
 
3.3%
번 2382
 
3.0%
출 2304
 
2.9%
동 1947
 
2.5%
교 1662
 
2.1%
리 1334
 
1.7%
원 1248
 
1.6%
파 1242
 
1.6%
Other values (445) 57814
73.1%
Uppercase Letter
ValueCountFrequency (%)
S 165
13.9%
K 152
12.8%
C 107
9.0%
T 93
 
7.9%
B 92
 
7.8%
A 79
 
6.7%
G 71
 
6.0%
I 61
 
5.2%
D 59
 
5.0%
L 54
 
4.6%
Other values (11) 250
21.1%
Decimal Number
ValueCountFrequency (%)
1 9268
23.0%
2 5348
13.3%
4 3609
 
9.0%
3 3533
 
8.8%
0 3368
 
8.4%
5 3320
 
8.2%
6 3214
 
8.0%
7 3140
 
7.8%
9 2786
 
6.9%
8 2687
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
e 46
36.8%
l 13
 
10.4%
o 9
 
7.2%
c 9
 
7.2%
m 9
 
7.2%
t 9
 
7.2%
s 9
 
7.2%
k 9
 
7.2%
n 8
 
6.4%
y 4
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 10031
99.1%
, 63
 
0.6%
& 11
 
0.1%
? 11
 
0.1%
· 7
 
0.1%
Space Separator
ValueCountFrequency (%)
19946
100.0%
Open Punctuation
ValueCountFrequency (%)
( 787
100.0%
Close Punctuation
ValueCountFrequency (%)
) 787
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79078
51.9%
Common 71996
47.2%
Latin 1308
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3498
 
4.4%
앞 3006
 
3.8%
역 2635
 
3.3%
번 2382
 
3.0%
출 2304
 
2.9%
동 1947
 
2.5%
교 1662
 
2.1%
리 1334
 
1.7%
원 1248
 
1.6%
파 1242
 
1.6%
Other values (446) 57820
73.1%
Latin
ValueCountFrequency (%)
S 165
12.6%
K 152
11.6%
C 107
 
8.2%
T 93
 
7.1%
B 92
 
7.0%
A 79
 
6.0%
G 71
 
5.4%
I 61
 
4.7%
D 59
 
4.5%
L 54
 
4.1%
Other values (21) 375
28.7%
Common
ValueCountFrequency (%)
19946
27.7%
. 10031
13.9%
1 9268
12.9%
2 5348
 
7.4%
4 3609
 
5.0%
3 3533
 
4.9%
0 3368
 
4.7%
5 3320
 
4.6%
6 3214
 
4.5%
7 3140
 
4.4%
Other values (11) 7219
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79072
51.9%
ASCII 73297
48.1%
None 13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19946
27.2%
. 10031
13.7%
1 9268
12.6%
2 5348
 
7.3%
4 3609
 
4.9%
3 3533
 
4.8%
0 3368
 
4.6%
5 3320
 
4.5%
6 3214
 
4.4%
7 3140
 
4.3%
Other values (41) 8520
11.6%
Hangul
ValueCountFrequency (%)
구 3498
 
4.4%
앞 3006
 
3.8%
역 2635
 
3.3%
번 2382
 
3.0%
출 2304
 
2.9%
동 1947
 
2.5%
교 1662
 
2.1%
리 1334
 
1.7%
원 1248
 
1.6%
파 1242
 
1.6%
Other values (445) 57814
73.1%
None
ValueCountFrequency (%)
· 7
53.8%
㈜ 6
46.2%

대여구분코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정기
4950 
일일(회원)
3844 
단체
957 
일일(비회원)
 
244
10분이용권
 
5

Length

Max length7
Median length2
Mean length3.6616
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정기 4950
49.5%
일일(회원) 3844
38.4%
단체 957
 
9.6%
일일(비회원) 244
 
2.4%
10분이용권 5
 
0.1%

Length

2024-05-18T09:14:23.747518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:14:24.036036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 4950
49.5%
일일(회원 3844
38.4%
단체 957
 
9.6%
일일(비회원 244
 
2.4%
10분이용권 5
 
< 0.1%

성별
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
M
3062 
\N
2885 
F
2795 
<NA>
1257 
m
 
1

Length

Max length4
Median length1
Mean length1.6656
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
M 3062
30.6%
\N 2885
28.8%
F 2795
28.0%
<NA> 1257
12.6%
m 1
 
< 0.1%

Length

2024-05-18T09:14:24.447094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:14:24.795436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 3063
30.6%
n 2885
28.8%
f 2795
28.0%
na 1257
12.6%

연령대코드
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20대
1784 
40대
1623 
30대
1552 
기타
1402 
50대
1287 
Other values (3)
2352 

Length

Max length5
Median length3
Mean length2.9198
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10대
2nd row50대
3rd row30대
4th row20대
5th row60대

Common Values

ValueCountFrequency (%)
20대 1784
17.8%
40대 1623
16.2%
30대 1552
15.5%
기타 1402
14.0%
50대 1287
12.9%
10대 1284
12.8%
60대 768
7.7%
70대이상 300
 
3.0%

Length

2024-05-18T09:14:25.196090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:14:25.583873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 1784
17.8%
40대 1623
16.2%
30대 1552
15.5%
기타 1402
14.0%
50대 1287
12.9%
10대 1284
12.8%
60대 768
7.7%
70대이상 300
 
3.0%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct363
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.6189
Minimum1
Maximum1368
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:14:25.927222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median11
Q337
95-th percentile147
Maximum1368
Range1367
Interquartile range (IQR)34

Descriptive statistics

Standard deviation64.903913
Coefficient of variation (CV)1.8748115
Kurtosis46.917208
Mean34.6189
Median Absolute Deviation (MAD)9
Skewness5.119229
Sum346189
Variance4212.5179
MonotonicityNot monotonic
2024-05-18T09:14:26.322769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1124
 
11.2%
2 1052
 
10.5%
3 570
 
5.7%
4 494
 
4.9%
5 395
 
4.0%
6 352
 
3.5%
7 289
 
2.9%
8 240
 
2.4%
9 234
 
2.3%
10 218
 
2.2%
Other values (353) 5032
50.3%
ValueCountFrequency (%)
1 1124
11.2%
2 1052
10.5%
3 570
5.7%
4 494
4.9%
5 395
 
4.0%
6 352
 
3.5%
7 289
 
2.9%
8 240
 
2.4%
9 234
 
2.3%
10 218
 
2.2%
ValueCountFrequency (%)
1368 1
< 0.1%
997 1
< 0.1%
803 1
< 0.1%
791 1
< 0.1%
759 1
< 0.1%
750 1
< 0.1%
732 1
< 0.1%
666 1
< 0.1%
656 1
< 0.1%
652 1
< 0.1%

운동량
Text

Distinct9731
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:14:27.091858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.3699
Min length2

Characters and Unicode

Total characters63699
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

Unique9495 ?
Unique (%)95.0%

Sample

1st row2056.00
2nd row2418.44
3rd row4197.32
4th row2783.67
5th row771.04
ValueCountFrequency (%)
0.00 22
 
0.2%
n 5
 
< 0.1%
55.60 4
 
< 0.1%
18.79 3
 
< 0.1%
591.96 3
 
< 0.1%
45.56 3
 
< 0.1%
8.32 3
 
< 0.1%
41.18 3
 
< 0.1%
158.99 3
 
< 0.1%
54.05 3
 
< 0.1%
Other values (9721) 9948
99.5%
2024-05-18T09:14:28.337611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9995
15.7%
1 7409
11.6%
2 6205
9.7%
3 5734
9.0%
4 5358
8.4%
5 5224
8.2%
6 4998
7.8%
8 4754
7.5%
7 4730
7.4%
0 4643
7.3%
Other values (3) 4649
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53694
84.3%
Other Punctuation 10000
 
15.7%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7409
13.8%
2 6205
11.6%
3 5734
10.7%
4 5358
10.0%
5 5224
9.7%
6 4998
9.3%
8 4754
8.9%
7 4730
8.8%
0 4643
8.6%
9 4639
8.6%
Other Punctuation
ValueCountFrequency (%)
. 9995
> 99.9%
\ 5
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
N 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63694
> 99.9%
Latin 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9995
15.7%
1 7409
11.6%
2 6205
9.7%
3 5734
9.0%
4 5358
8.4%
5 5224
8.2%
6 4998
7.8%
8 4754
7.5%
7 4730
7.4%
0 4643
7.3%
Other values (2) 4644
7.3%
Latin
ValueCountFrequency (%)
N 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63699
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9995
15.7%
1 7409
11.6%
2 6205
9.7%
3 5734
9.0%
4 5358
8.4%
5 5224
8.2%
6 4998
7.8%
8 4754
7.5%
7 4730
7.4%
0 4643
7.3%
Other values (3) 4649
7.3%

탄소량
Text

Distinct4128
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:14:29.264314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.4763
Min length2

Characters and Unicode

Total characters44763
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

Unique2432 ?
Unique (%)24.3%

Sample

1st row23.20
2nd row20.08
3rd row34.43
4th row22.48
5th row8.76
ValueCountFrequency (%)
0.21 25
 
0.2%
0.34 24
 
0.2%
0.64 23
 
0.2%
0.65 23
 
0.2%
0.44 22
 
0.2%
0.22 22
 
0.2%
0.31 21
 
0.2%
0.23 21
 
0.2%
0.32 21
 
0.2%
0.19 21
 
0.2%
Other values (4118) 9777
97.8%
2024-05-18T09:14:30.933418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9995
22.3%
1 5491
12.3%
2 4119
9.2%
0 4070
9.1%
3 3643
 
8.1%
4 3359
 
7.5%
5 3032
 
6.8%
6 2921
 
6.5%
7 2792
 
6.2%
9 2678
 
6.0%
Other values (3) 2663
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34758
77.6%
Other Punctuation 10000
 
22.3%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5491
15.8%
2 4119
11.9%
0 4070
11.7%
3 3643
10.5%
4 3359
9.7%
5 3032
8.7%
6 2921
8.4%
7 2792
8.0%
9 2678
7.7%
8 2653
7.6%
Other Punctuation
ValueCountFrequency (%)
. 9995
> 99.9%
\ 5
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
N 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44758
> 99.9%
Latin 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9995
22.3%
1 5491
12.3%
2 4119
9.2%
0 4070
9.1%
3 3643
 
8.1%
4 3359
 
7.5%
5 3032
 
6.8%
6 2921
 
6.5%
7 2792
 
6.2%
9 2678
 
6.0%
Other values (2) 2658
 
5.9%
Latin
ValueCountFrequency (%)
N 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44763
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9995
22.3%
1 5491
12.3%
2 4119
9.2%
0 4070
9.1%
3 3643
 
8.1%
4 3359
 
7.5%
5 3032
 
6.8%
6 2921
 
6.5%
7 2792
 
6.2%
9 2678
 
6.0%
Other values (3) 2663
 
5.9%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION 

Distinct9678
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94747.356
Minimum0
Maximum3612245.9
Zeros23
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:14:31.554028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1540
Q18865.58
median31170.445
Q3103983.89
95-th percentile404213.04
Maximum3612245.9
Range3612245.9
Interquartile range (IQR)95118.31

Descriptive statistics

Standard deviation175765.38
Coefficient of variation (CV)1.8550953
Kurtosis60.374799
Mean94747.356
Median Absolute Deviation (MAD)27262.115
Skewness5.5880927
Sum9.4747356 × 108
Variance3.0893468 × 1010
MonotonicityNot monotonic
2024-05-18T09:14:32.052007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 23
 
0.2%
1540.0 7
 
0.1%
2680.0 6
 
0.1%
2810.0 6
 
0.1%
930.0 6
 
0.1%
1390.0 6
 
0.1%
2180.0 5
 
0.1%
2150.0 5
 
0.1%
1340.0 5
 
0.1%
1020.0 5
 
0.1%
Other values (9668) 9926
99.3%
ValueCountFrequency (%)
0.0 23
0.2%
0.2 1
 
< 0.1%
10.61 1
 
< 0.1%
60.0 2
 
< 0.1%
88.4 1
 
< 0.1%
90.0 1
 
< 0.1%
111.2 1
 
< 0.1%
140.0 1
 
< 0.1%
141.86 1
 
< 0.1%
141.97 1
 
< 0.1%
ValueCountFrequency (%)
3612245.86 1
< 0.1%
3605975.72 1
< 0.1%
2738898.54 1
< 0.1%
2682100.02 1
< 0.1%
2457519.83 1
< 0.1%
2032396.4 1
< 0.1%
1887479.2 1
< 0.1%
1818188.19 1
< 0.1%
1771306.3 1
< 0.1%
1571879.69 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct2609
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean790.8523
Minimum1
Maximum26126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:14:32.528691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14
Q182
median270
Q3877
95-th percentile3398.15
Maximum26126
Range26125
Interquartile range (IQR)795

Descriptive statistics

Standard deviation1386.0222
Coefficient of variation (CV)1.7525677
Kurtosis39.437985
Mean790.8523
Median Absolute Deviation (MAD)233
Skewness4.6570932
Sum7908523
Variance1921057.5
MonotonicityNot monotonic
2024-05-18T09:14:32.964383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 58
 
0.6%
14 53
 
0.5%
11 50
 
0.5%
20 48
 
0.5%
7 46
 
0.5%
27 45
 
0.4%
5 44
 
0.4%
6 44
 
0.4%
21 43
 
0.4%
9 43
 
0.4%
Other values (2599) 9526
95.3%
ValueCountFrequency (%)
1 6
 
0.1%
2 12
 
0.1%
3 29
0.3%
4 27
0.3%
5 44
0.4%
6 44
0.4%
7 46
0.5%
8 43
0.4%
9 43
0.4%
10 58
0.6%
ValueCountFrequency (%)
26126 1
< 0.1%
22699 1
< 0.1%
19460 1
< 0.1%
18434 1
< 0.1%
17480 1
< 0.1%
14199 1
< 0.1%
14076 1
< 0.1%
13667 1
< 0.1%
13353 1
< 0.1%
13350 1
< 0.1%

Interactions

2024-05-18T09:14:18.419874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:14.590847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:15.978632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:17.149212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:18.682482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:14.942479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:16.267947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:17.458745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:18.970217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:15.352153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:16.543271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:17.823309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:19.261688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:15.678666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:16.861120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:14:18.160588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T09:14:33.254775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호대여구분코드성별연령대코드이용건수이동거리(M)이용시간(분)
대여소번호1.0000.0150.0160.0130.0400.0480.074
대여구분코드0.0151.0000.1410.3120.1700.1350.210
성별0.0160.1411.0000.1050.0620.0450.052
연령대코드0.0130.3120.1051.0000.2650.1700.190
이용건수0.0400.1700.0620.2651.0000.7840.884
이동거리(M)0.0480.1350.0450.1700.7841.0000.920
이용시간(분)0.0740.2100.0520.1900.8840.9201.000
2024-05-18T09:14:33.582352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령대코드성별대여구분코드
연령대코드1.0000.0480.197
성별0.0481.0000.115
대여구분코드0.1970.1151.000
2024-05-18T09:14:33.846792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)대여구분코드성별연령대코드
대여소번호1.000-0.028-0.032-0.0450.0060.0100.006
이용건수-0.0281.0000.9400.9440.1050.0280.091
이동거리(M)-0.0320.9401.0000.9780.0780.0290.084
이용시간(분)-0.0450.9440.9781.0000.0890.0310.091
대여구분코드0.0060.1050.0780.0891.0000.1150.197
성별0.0100.0280.0290.0310.1151.0000.048
연령대코드0.0060.0910.0840.0910.1970.0481.000

Missing values

2024-05-18T09:14:19.647524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T09:14:20.206473image/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)
296712022-06792792.목동트라팰리스 웨스턴에비뉴일일(회원)F10대412056.0023.2099982.171076
497672022-0613021302. 한성대입구역6번출구 뒤정기M50대332418.4420.0886584.63557
717672022-0620032003. 사육신공원앞일일(회원)\N30대384197.3234.43148232.851535
610882022-0616551655. 공릉1단지아파트일일(회원)M20대332783.6722.4896852.08731
656102022-0617681768.신동아타워 버스정류소정기F60대6771.048.7637752.29236
21082022-06144144. 공덕역 8번출구일일(회원)\N70대이상3413.824.8520900.24178
210832022-06572572. 국립정신 건강센터 앞정기M기타12762.606.5128114.6272
529742022-0613901390.석관래미안아트리치단체F30대4473.354.4118973.74187
234122022-06628628. 휘봉고등학교 앞정기M10대603085.4727.40118082.841333
399132022-0610701070.(시립)고덕평생학습관일일(회원)<NA>10대3109.880.994269.0637
대여일자대여소번호대여소명대여구분코드성별연령대코드이용건수운동량탄소량이동거리(M)이용시간(분)
215362022-06583583. 청계천 생태교실 앞단체F10대2310.473.0413067.0581
360592022-06977977.신도중학교앞정기\N60대6307.572.8112097.81104
252032022-06673673.안암골벽산아파트(후문)일일(회원)\N50대1171.142.058820.070
68372022-06244244. 영등포삼환아파트 앞정기<NA>50대1164.241.285530.036
24852022-06153153. 성산2교 사거리일일(회원)F60대10.000.000.011
190892022-06526526. 용답토속공원 앞일일(회원)F20대121470.5015.3466167.85461
753122022-0621292129. 낙성대 과학전시관일일(회원)\N60대1146.021.325673.0638
408872022-0610891089.고덕 래미안힐스테이트(201동)정기M기타121172.509.9743011.08543
188172022-06521521. 왕십리역 11번 출구 앞단체\N40대117.940.20871.227
535212022-0614041404. 동일로 지하차도정기\N40대602763.5225.78111148.36898