Overview

Dataset statistics

Number of variables11
Number of observations5293
Missing cells5293
Missing cells (%)9.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory480.8 KiB
Average record size in memory93.0 B

Variable types

Categorical3
Numeric4
Text3
Unsupported1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15246/F/1/datasetView.do

Alerts

대여일자 has constant value ""Constant
대여구분코드 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
성별 has 5293 (100.0%) missing valuesMissing
성별 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 16:27:01.279041
Analysis finished2024-03-13 16:27:04.297824
Duration3.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
2022-09-01
5293 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-01
2nd row2022-09-01
3rd row2022-09-01
4th row2022-09-01
5th row2022-09-01

Common Values

ValueCountFrequency (%)
2022-09-01 5293
100.0%

Length

2024-03-14T01:27:04.354936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:27:04.423878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-01 5293
100.0%

대여소번호
Real number (ℝ)

Distinct2482
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2188.2382
Minimum102
Maximum5857
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2024-03-14T01:27:04.500790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile249
Q1855
median1822
Q33586
95-th percentile4807.4
Maximum5857
Range5755
Interquartile range (IQR)2731

Descriptive statistics

Standard deviation1515.5392
Coefficient of variation (CV)0.69258418
Kurtosis-1.1001056
Mean2188.2382
Median Absolute Deviation (MAD)1144
Skewness0.44448479
Sum11582345
Variance2296859
MonotonicityNot monotonic
2024-03-14T01:27:04.604995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
247 5
 
0.1%
551 5
 
0.1%
1119 5
 
0.1%
1985 5
 
0.1%
2632 5
 
0.1%
1663 5
 
0.1%
549 5
 
0.1%
1721 5
 
0.1%
708 5
 
0.1%
514 5
 
0.1%
Other values (2472) 5243
99.1%
ValueCountFrequency (%)
102 2
< 0.1%
103 2
< 0.1%
104 1
< 0.1%
105 1
< 0.1%
106 2
< 0.1%
107 1
< 0.1%
108 2
< 0.1%
109 2
< 0.1%
111 2
< 0.1%
112 2
< 0.1%
ValueCountFrequency (%)
5857 3
0.1%
5855 2
< 0.1%
5854 3
0.1%
5853 3
0.1%
5852 2
< 0.1%
5851 2
< 0.1%
5753 2
< 0.1%
5752 2
< 0.1%
5751 2
< 0.1%
5313 2
< 0.1%

대여소
Text

Distinct2482
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
2024-03-14T01:27:04.823299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.555828
Min length7

Characters and Unicode

Total characters82337
Distinct characters573
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

Unique651 ?
Unique (%)12.3%

Sample

1st row729. 서부식자재마트 건너편
2nd row733. 신정이펜하우스314동
3rd row734. 신트리공원 입구
4th row735. 영도초등학교
5th row736. 오솔길공원
ValueCountFrequency (%)
앞 1396
 
9.1%
출구 228
 
1.5%
옆 189
 
1.2%
1번출구 138
 
0.9%
교차로 130
 
0.8%
사거리 125
 
0.8%
입구 109
 
0.7%
3번출구 105
 
0.7%
2번출구 93
 
0.6%
4번출구 84
 
0.5%
Other values (4975) 12782
83.1%
2024-03-14T01:27:05.171157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10186
 
12.4%
. 5306
 
6.4%
1 4029
 
4.9%
2 2991
 
3.6%
4 2570
 
3.1%
3 2538
 
3.1%
5 2047
 
2.5%
6 1887
 
2.3%
0 1886
 
2.3%
7 1770
 
2.1%
Other values (563) 47127
57.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42480
51.6%
Decimal Number 22654
27.5%
Space Separator 10186
 
12.4%
Other Punctuation 5376
 
6.5%
Uppercase Letter 664
 
0.8%
Open Punctuation 418
 
0.5%
Close Punctuation 418
 
0.5%
Lowercase Letter 83
 
0.1%
Dash Punctuation 36
 
< 0.1%
Math Symbol 7
 
< 0.1%
Other values (3) 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1647
 
3.9%
앞 1611
 
3.8%
역 1278
 
3.0%
동 1184
 
2.8%
번 1119
 
2.6%
출 1097
 
2.6%
교 881
 
2.1%
파 763
 
1.8%
리 735
 
1.7%
아 730
 
1.7%
Other values (501) 31435
74.0%
Uppercase Letter
ValueCountFrequency (%)
S 76
11.4%
K 72
10.8%
T 66
9.9%
C 60
9.0%
A 54
 
8.1%
D 45
 
6.8%
G 41
 
6.2%
B 38
 
5.7%
P 34
 
5.1%
M 33
 
5.0%
Other values (14) 145
21.8%
Lowercase Letter
ValueCountFrequency (%)
e 26
31.3%
s 14
16.9%
k 14
16.9%
n 6
 
7.2%
t 4
 
4.8%
y 3
 
3.6%
l 3
 
3.6%
v 3
 
3.6%
h 2
 
2.4%
f 2
 
2.4%
Other values (3) 6
 
7.2%
Decimal Number
ValueCountFrequency (%)
1 4029
17.8%
2 2991
13.2%
4 2570
11.3%
3 2538
11.2%
5 2047
9.0%
6 1887
8.3%
0 1886
8.3%
7 1770
7.8%
8 1588
 
7.0%
9 1348
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 5306
98.7%
, 43
 
0.8%
& 16
 
0.3%
· 6
 
0.1%
? 5
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 5
71.4%
+ 2
 
28.6%
Other Number
ValueCountFrequency (%)
① 3
60.0%
② 2
40.0%
Space Separator
ValueCountFrequency (%)
10186
100.0%
Open Punctuation
ValueCountFrequency (%)
( 418
100.0%
Close Punctuation
ValueCountFrequency (%)
) 418
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42484
51.6%
Common 39106
47.5%
Latin 747
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1647
 
3.9%
앞 1611
 
3.8%
역 1278
 
3.0%
동 1184
 
2.8%
번 1119
 
2.6%
출 1097
 
2.6%
교 881
 
2.1%
파 763
 
1.8%
리 735
 
1.7%
아 730
 
1.7%
Other values (502) 31439
74.0%
Latin
ValueCountFrequency (%)
S 76
 
10.2%
K 72
 
9.6%
T 66
 
8.8%
C 60
 
8.0%
A 54
 
7.2%
D 45
 
6.0%
G 41
 
5.5%
B 38
 
5.1%
P 34
 
4.6%
M 33
 
4.4%
Other values (27) 228
30.5%
Common
ValueCountFrequency (%)
10186
26.0%
. 5306
13.6%
1 4029
 
10.3%
2 2991
 
7.6%
4 2570
 
6.6%
3 2538
 
6.5%
5 2047
 
5.2%
6 1887
 
4.8%
0 1886
 
4.8%
7 1770
 
4.5%
Other values (14) 3896
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42480
51.6%
ASCII 39842
48.4%
None 10
 
< 0.1%
Enclosed Alphanum 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10186
25.6%
. 5306
13.3%
1 4029
 
10.1%
2 2991
 
7.5%
4 2570
 
6.5%
3 2538
 
6.4%
5 2047
 
5.1%
6 1887
 
4.7%
0 1886
 
4.7%
7 1770
 
4.4%
Other values (48) 4632
11.6%
Hangul
ValueCountFrequency (%)
구 1647
 
3.9%
앞 1611
 
3.8%
역 1278
 
3.0%
동 1184
 
2.8%
번 1119
 
2.6%
출 1097
 
2.6%
교 881
 
2.1%
파 763
 
1.8%
리 735
 
1.7%
아 730
 
1.7%
Other values (501) 31435
74.0%
None
ValueCountFrequency (%)
· 6
60.0%
㈜ 4
40.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 3
60.0%
② 2
40.0%

대여구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
정기권
5293 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정기권
2nd row정기권
3rd row정기권
4th row정기권
5th row정기권

Common Values

ValueCountFrequency (%)
정기권 5293
100.0%

Length

2024-03-14T01:27:05.277001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:27:05.354797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기권 5293
100.0%

성별
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5293
Missing (%)100.0%
Memory size46.6 KiB

연령대
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
20대
2769 
30대
1847 
~10대
677 

Length

Max length4
Median length3
Mean length3.1279048
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row~10대
2nd row~10대
3rd row~10대
4th row~10대
5th row~10대

Common Values

ValueCountFrequency (%)
20대 2769
52.3%
30대 1847
34.9%
~10대 677
 
12.8%

Length

2024-03-14T01:27:05.429933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T01:27:05.502662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 2769
52.3%
30대 1847
34.9%
10대 677
 
12.8%

이용건수
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.623465
Minimum1
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2024-03-14T01:27:05.588596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q36
95-th percentile15
Maximum84
Range83
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.352936
Coefficient of variation (CV)1.1577758
Kurtosis20.487042
Mean4.623465
Median Absolute Deviation (MAD)2
Skewness3.342404
Sum24472
Variance28.653924
MonotonicityNot monotonic
2024-03-14T01:27:05.686507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 1666
31.5%
2 825
15.6%
3 617
 
11.7%
4 448
 
8.5%
5 319
 
6.0%
6 234
 
4.4%
7 218
 
4.1%
9 155
 
2.9%
8 153
 
2.9%
10 123
 
2.3%
Other values (33) 535
 
10.1%
ValueCountFrequency (%)
1 1666
31.5%
2 825
15.6%
3 617
 
11.7%
4 448
 
8.5%
5 319
 
6.0%
6 234
 
4.4%
7 218
 
4.1%
8 153
 
2.9%
9 155
 
2.9%
10 123
 
2.3%
ValueCountFrequency (%)
84 1
 
< 0.1%
50 1
 
< 0.1%
49 2
< 0.1%
47 3
0.1%
46 1
 
< 0.1%
40 2
< 0.1%
39 2
< 0.1%
38 2
< 0.1%
36 2
< 0.1%
35 3
0.1%

운동량
Text

Distinct4915
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
2024-03-14T01:27:05.994105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.5794445
Min length2

Characters and Unicode

Total characters29532
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

Unique4590 ?
Unique (%)86.7%

Sample

1st row95.79
2nd row103.89
3rd row327.83
4th row76.66
5th row76.38
ValueCountFrequency (%)
0.00 22
 
0.4%
n 5
 
0.1%
26.51 4
 
0.1%
15.68 4
 
0.1%
120.43 4
 
0.1%
33.07 4
 
0.1%
15.75 3
 
0.1%
35.01 3
 
0.1%
19.82 3
 
0.1%
42.17 3
 
0.1%
Other values (4905) 5238
99.0%
2024-03-14T01:27:06.454609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5288
17.9%
1 3434
11.6%
2 2937
9.9%
3 2613
8.8%
4 2408
8.2%
5 2322
7.9%
8 2193
7.4%
6 2168
7.3%
7 2146
7.3%
0 2020
 
6.8%
Other values (3) 2003
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24234
82.1%
Other Punctuation 5293
 
17.9%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3434
14.2%
2 2937
12.1%
3 2613
10.8%
4 2408
9.9%
5 2322
9.6%
8 2193
9.0%
6 2168
8.9%
7 2146
8.9%
0 2020
8.3%
9 1993
8.2%
Other Punctuation
ValueCountFrequency (%)
. 5288
99.9%
\ 5
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29527
> 99.9%
Latin 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 5288
17.9%
1 3434
11.6%
2 2937
9.9%
3 2613
8.8%
4 2408
8.2%
5 2322
7.9%
8 2193
7.4%
6 2168
7.3%
7 2146
7.3%
0 2020
 
6.8%
Other values (2) 1998
 
6.8%
Latin
ValueCountFrequency (%)
N 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29532
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5288
17.9%
1 3434
11.6%
2 2937
9.9%
3 2613
8.8%
4 2408
8.2%
5 2322
7.9%
8 2193
7.4%
6 2168
7.3%
7 2146
7.3%
0 2020
 
6.8%
Other values (3) 2003
 
6.8%

탄소량
Text

Distinct843
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
2024-03-14T01:27:06.800227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0164368
Min length2

Characters and Unicode

Total characters21259
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

Unique254 ?
Unique (%)4.8%

Sample

1st row0.75
2nd row0.92
3rd row2.82
4th row0.80
5th row0.56
ValueCountFrequency (%)
0.13 45
 
0.9%
0.16 43
 
0.8%
0.30 42
 
0.8%
0.25 42
 
0.8%
0.14 42
 
0.8%
0.21 42
 
0.8%
0.29 40
 
0.8%
0.23 39
 
0.7%
0.27 39
 
0.7%
0.37 38
 
0.7%
Other values (833) 4881
92.2%
2024-03-14T01:27:07.235788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5288
24.9%
0 3428
16.1%
1 2294
10.8%
2 1856
 
8.7%
3 1560
 
7.3%
4 1338
 
6.3%
5 1261
 
5.9%
6 1159
 
5.5%
7 1093
 
5.1%
8 995
 
4.7%
Other values (3) 987
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15961
75.1%
Other Punctuation 5293
 
24.9%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3428
21.5%
1 2294
14.4%
2 1856
11.6%
3 1560
9.8%
4 1338
 
8.4%
5 1261
 
7.9%
6 1159
 
7.3%
7 1093
 
6.8%
8 995
 
6.2%
9 977
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 5288
99.9%
\ 5
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21254
> 99.9%
Latin 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 5288
24.9%
0 3428
16.1%
1 2294
10.8%
2 1856
 
8.7%
3 1560
 
7.3%
4 1338
 
6.3%
5 1261
 
5.9%
6 1159
 
5.5%
7 1093
 
5.1%
8 995
 
4.7%
Other values (2) 982
 
4.6%
Latin
ValueCountFrequency (%)
N 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21259
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5288
24.9%
0 3428
16.1%
1 2294
10.8%
2 1856
 
8.7%
3 1560
 
7.3%
4 1338
 
6.3%
5 1261
 
5.9%
6 1159
 
5.5%
7 1093
 
5.1%
8 995
 
4.7%
Other values (3) 987
 
4.6%

이동거리(M)
Real number (ℝ)

HIGH CORRELATION 

Distinct4755
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9059.5337
Minimum0
Maximum138451.51
Zeros26
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2024-03-14T01:27:07.352041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile650
Q12050
median5140
Q311684.88
95-th percentile30239.126
Maximum138451.51
Range138451.51
Interquartile range (IQR)9634.88

Descriptive statistics

Standard deviation11156.174
Coefficient of variation (CV)1.2314292
Kurtosis18.198507
Mean9059.5337
Median Absolute Deviation (MAD)3801.01
Skewness3.2494554
Sum47952112
Variance1.2446022 × 108
MonotonicityNot monotonic
2024-03-14T01:27:07.461289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 26
 
0.5%
1030.0 9
 
0.2%
1100.0 8
 
0.2%
1150.0 7
 
0.1%
1290.0 7
 
0.1%
570.0 7
 
0.1%
720.0 7
 
0.1%
1580.0 6
 
0.1%
3730.0 6
 
0.1%
550.0 6
 
0.1%
Other values (4745) 5204
98.3%
ValueCountFrequency (%)
0.0 26
0.5%
29.04 1
 
< 0.1%
60.0 3
 
0.1%
88.33 1
 
< 0.1%
88.4 1
 
< 0.1%
111.2 1
 
< 0.1%
141.91 1
 
< 0.1%
176.3 1
 
< 0.1%
208.28 1
 
< 0.1%
208.38 1
 
< 0.1%
ValueCountFrequency (%)
138451.51 1
< 0.1%
122029.87 1
< 0.1%
116344.73 1
< 0.1%
114110.82 1
< 0.1%
109985.02 1
< 0.1%
106596.76 1
< 0.1%
105210.82 1
< 0.1%
100617.04 1
< 0.1%
89894.37 1
< 0.1%
85486.59 1
< 0.1%

이용시간(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct400
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.765539
Minimum0
Maximum1082
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2024-03-14T01:27:07.571783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q115
median40
Q391
95-th percentile237.4
Maximum1082
Range1082
Interquartile range (IQR)76

Descriptive statistics

Standard deviation86.893524
Coefficient of variation (CV)1.2455078
Kurtosis16.794954
Mean69.765539
Median Absolute Deviation (MAD)30
Skewness3.16329
Sum369269
Variance7550.4845
MonotonicityNot monotonic
2024-03-14T01:27:07.704330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 130
 
2.5%
4 111
 
2.1%
6 110
 
2.1%
8 109
 
2.1%
5 107
 
2.0%
3 105
 
2.0%
9 104
 
2.0%
10 101
 
1.9%
11 96
 
1.8%
14 88
 
1.7%
Other values (390) 4232
80.0%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 12
 
0.2%
2 63
1.2%
3 105
2.0%
4 111
2.1%
5 107
2.0%
6 110
2.1%
7 130
2.5%
8 109
2.1%
9 104
2.0%
ValueCountFrequency (%)
1082 1
< 0.1%
964 1
< 0.1%
865 1
< 0.1%
803 1
< 0.1%
759 1
< 0.1%
755 1
< 0.1%
732 1
< 0.1%
716 1
< 0.1%
691 1
< 0.1%
682 1
< 0.1%

Interactions

2024-03-14T01:27:03.634133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:02.066441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:02.650337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:03.315031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:03.721900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:02.227328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:02.787225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:03.388824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:03.794184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:02.343650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:02.897435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:03.465813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:03.887859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:02.489362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:03.246447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T01:27:03.553290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T01:27:07.792986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호연령대이용건수이동거리(M)이용시간(분)
대여소번호1.0000.1570.0650.0520.077
연령대0.1571.0000.2450.2900.292
이용건수0.0650.2451.0000.7670.832
이동거리(M)0.0520.2900.7671.0000.956
이용시간(분)0.0770.2920.8320.9561.000
2024-03-14T01:27:07.877701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소번호이용건수이동거리(M)이용시간(분)연령대
대여소번호1.000-0.050-0.059-0.0580.094
이용건수-0.0501.0000.8490.8550.169
이동거리(M)-0.0590.8491.0000.9420.181
이용시간(분)-0.0580.8550.9421.0000.182
연령대0.0940.1690.1810.1821.000

Missing values

2024-03-14T01:27:04.021384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T01:27:04.222381image/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

대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
02022-09-01729729. 서부식자재마트 건너편정기권<NA>~10대295.790.753224.9216
12022-09-01733733. 신정이펜하우스314동정기권<NA>~10대2103.890.923955.1725
22022-09-01734734. 신트리공원 입구정기권<NA>~10대2327.832.8212170.072
32022-09-01735735. 영도초등학교정기권<NA>~10대476.660.803465.7945
42022-09-01736736. 오솔길공원정기권<NA>~10대176.380.562411.0712
52022-09-01742742. 등촌역 5번 출구 뒤정기권<NA>~10대142.730.391660.014
62022-09-01746746. 목동2단지 상가정기권<NA>~10대3183.281.456281.1683
72022-09-01747747. 목동3단지 상가정기권<NA>~10대4241.052.159267.0877
82022-09-01748748. 목동운동장정기권<NA>~10대121.420.241040.011
92022-09-01505505. 자양사거리 광진아크로텔 앞정기권<NA>~10대142.420.371598.916
대여일자대여소번호대여소대여구분코드성별연령대이용건수운동량탄소량이동거리(M)이용시간(분)
52832022-09-0111021102. 방화사거리 마을버스 버스정류장정기권<NA>30대7225.212.5911176.06120
52842022-09-01203203. 국회의사당역 3번출구 옆정기권<NA>30대71027.279.7441967.4178
52852022-09-0111081108. 공항시장역 2번출구 뒤정기권<NA>30대4247.951.998585.0111
52862022-09-0111091109. 공항시장역 4번출구정기권<NA>30대7464.413.7916321.12159
52872022-09-0111111111. 마곡엠밸리6_7단지 마곡중학교정기권<NA>30대251.450.522264.9129
52882022-09-0111121112. 마곡엠밸리4단지 정문정기권<NA>30대12539.965.0721812.5152
52892022-09-0111131113. 서남환경공원 버스정류장정기권<NA>30대4305.502.3310070.8747
52902022-09-0111181118. 증미역 3번출구뒤(등촌두산위브센티움오피스텔)정기권<NA>30대12717.855.8225078.1171
52912022-09-0111181118. 증미역 3번출구뒤(등촌두산위브센티움오피스텔)정기권<NA>30대110.510.14590.03
52922022-09-0111191119. 염창동 한마음아파트 앞정기권<NA>30대6417.943.5315209.95189