Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory986.3 KiB
Average record size in memory101.0 B

Variable types

Categorical4
Text2
Numeric5

Dataset

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

Alerts

'이용건수' is highly overall correlated with '운동량' and 3 other fieldsHigh correlation
'운동량' is highly overall correlated with '이용건수' and 3 other fieldsHigh correlation
'탄소량' is highly overall correlated with '이용건수' and 3 other fieldsHigh correlation
'이동거리(M)' is highly overall correlated with '이용건수' and 3 other fieldsHigh correlation
'이동시간(분)' is highly overall correlated with '이용건수' and 3 other fieldsHigh correlation
'대여구분코드' is highly overall correlated with 'SEX_CD'High correlation
'SEX_CD' is highly overall correlated with '대여구분코드'High correlation

Reproduction

Analysis started2024-05-18 05:07:00.264430
Analysis finished2024-05-18 05:07:10.444653
Duration10.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

'대여일자'
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'2018-06-03'
3125 
'2018-06-02'
3082 
'2018-06-01'
3039 
'2018-06-04'
754 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'2018-06-02'
2nd row'2018-06-01'
3rd row'2018-06-03'
4th row'2018-06-01'
5th row'2018-06-01'

Common Values

ValueCountFrequency (%)
'2018-06-03' 3125
31.2%
'2018-06-02' 3082
30.8%
'2018-06-01' 3039
30.4%
'2018-06-04' 754
 
7.5%

Length

2024-05-18T14:07:10.628594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:07:11.126821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-06-03 3125
31.2%
2018-06-02 3082
30.8%
2018-06-01 3039
30.4%
2018-06-04 754
 
7.5%

'대여소번호'
Text

Distinct1258
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T14:07:11.825862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.5445
Min length5

Characters and Unicode

Total characters55445
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)0.2%

Sample

1st row'241'
2nd row'381'
3rd row'1512'
4th row'2230'
5th row'2028'
ValueCountFrequency (%)
207 25
 
0.2%
3511 23
 
0.2%
2102 23
 
0.2%
1257 20
 
0.2%
419 20
 
0.2%
248 19
 
0.2%
505 19
 
0.2%
700 18
 
0.2%
602 18
 
0.2%
551 18
 
0.2%
Other values (1248) 9797
98.0%
2024-05-18T14:07:12.944182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 20000
36.1%
1 7967
 
14.4%
2 6019
 
10.9%
3 3967
 
7.2%
5 3253
 
5.9%
0 3202
 
5.8%
4 2685
 
4.8%
6 2560
 
4.6%
7 2049
 
3.7%
9 1911
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35445
63.9%
Other Punctuation 20000
36.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7967
22.5%
2 6019
17.0%
3 3967
11.2%
5 3253
9.2%
0 3202
9.0%
4 2685
 
7.6%
6 2560
 
7.2%
7 2049
 
5.8%
9 1911
 
5.4%
8 1832
 
5.2%
Other Punctuation
ValueCountFrequency (%)
' 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 55445
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
' 20000
36.1%
1 7967
 
14.4%
2 6019
 
10.9%
3 3967
 
7.2%
5 3253
 
5.9%
0 3202
 
5.8%
4 2685
 
4.8%
6 2560
 
4.6%
7 2049
 
3.7%
9 1911
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55445
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 20000
36.1%
1 7967
 
14.4%
2 6019
 
10.9%
3 3967
 
7.2%
5 3253
 
5.9%
0 3202
 
5.8%
4 2685
 
4.8%
6 2560
 
4.6%
7 2049
 
3.7%
9 1911
 
3.4%

'대여소'
Text

Distinct1258
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T14:07:13.343422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length27
Mean length12.7209
Min length6

Characters and Unicode

Total characters127209
Distinct characters482
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)0.2%

Sample

1st row' 신길우성1차아파트 앞 공원'
2nd row' 장충체육관'
3rd row' 강북중학교 앞'
4th row'이수역 4번 출구'
5th row' 남성역 2번출구 뒷편'
ValueCountFrequency (%)
9933
31.2%
앞 2787
 
8.8%
옆 600
 
1.9%
1번출구 478
 
1.5%
출구 431
 
1.4%
뒤 312
 
1.0%
2번출구 310
 
1.0%
사거리 305
 
1.0%
교차로 258
 
0.8%
4번출구 252
 
0.8%
Other values (1513) 16142
50.7%
2024-05-18T14:07:14.296568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21841
 
17.2%
' 20000
 
15.7%
구 3868
 
3.0%
앞 3359
 
2.6%
역 3121
 
2.5%
번 2826
 
2.2%
출 2791
 
2.2%
동 1803
 
1.4%
교 1572
 
1.2%
1 1445
 
1.1%
Other values (472) 64583
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78066
61.4%
Space Separator 21841
 
17.2%
Other Punctuation 20062
 
15.8%
Decimal Number 4785
 
3.8%
Uppercase Letter 1137
 
0.9%
Open Punctuation 561
 
0.4%
Close Punctuation 561
 
0.4%
Dash Punctuation 92
 
0.1%
Lowercase Letter 71
 
0.1%
Math Symbol 23
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3868
 
5.0%
앞 3359
 
4.3%
역 3121
 
4.0%
번 2826
 
3.6%
출 2791
 
3.6%
동 1803
 
2.3%
교 1572
 
2.0%
리 1387
 
1.8%
원 1280
 
1.6%
사 1110
 
1.4%
Other values (420) 54949
70.4%
Uppercase Letter
ValueCountFrequency (%)
K 177
15.6%
C 137
12.0%
S 124
10.9%
T 75
 
6.6%
M 69
 
6.1%
A 68
 
6.0%
B 67
 
5.9%
G 64
 
5.6%
L 64
 
5.6%
I 50
 
4.4%
Other values (13) 242
21.3%
Decimal Number
ValueCountFrequency (%)
1 1445
30.2%
2 849
17.7%
3 641
13.4%
4 541
 
11.3%
5 321
 
6.7%
8 229
 
4.8%
0 228
 
4.8%
7 224
 
4.7%
6 205
 
4.3%
9 102
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
e 27
38.0%
t 13
18.3%
k 7
 
9.9%
l 6
 
8.5%
m 6
 
8.5%
o 6
 
8.5%
c 6
 
8.5%
Other Punctuation
ValueCountFrequency (%)
' 20000
99.7%
, 43
 
0.2%
? 10
 
< 0.1%
& 6
 
< 0.1%
@ 3
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 13
56.5%
+ 10
43.5%
Space Separator
ValueCountFrequency (%)
21841
100.0%
Open Punctuation
ValueCountFrequency (%)
( 561
100.0%
Close Punctuation
ValueCountFrequency (%)
) 561
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78066
61.4%
Common 47935
37.7%
Latin 1208
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3868
 
5.0%
앞 3359
 
4.3%
역 3121
 
4.0%
번 2826
 
3.6%
출 2791
 
3.6%
동 1803
 
2.3%
교 1572
 
2.0%
리 1387
 
1.8%
원 1280
 
1.6%
사 1110
 
1.4%
Other values (420) 54949
70.4%
Latin
ValueCountFrequency (%)
K 177
14.7%
C 137
11.3%
S 124
 
10.3%
T 75
 
6.2%
M 69
 
5.7%
A 68
 
5.6%
B 67
 
5.5%
G 64
 
5.3%
L 64
 
5.3%
I 50
 
4.1%
Other values (20) 313
25.9%
Common
ValueCountFrequency (%)
21841
45.6%
' 20000
41.7%
1 1445
 
3.0%
2 849
 
1.8%
3 641
 
1.3%
( 561
 
1.2%
) 561
 
1.2%
4 541
 
1.1%
5 321
 
0.7%
8 229
 
0.5%
Other values (12) 946
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78066
61.4%
ASCII 49143
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21841
44.4%
' 20000
40.7%
1 1445
 
2.9%
2 849
 
1.7%
3 641
 
1.3%
( 561
 
1.1%
) 561
 
1.1%
4 541
 
1.1%
5 321
 
0.7%
8 229
 
0.5%
Other values (42) 2154
 
4.4%
Hangul
ValueCountFrequency (%)
구 3868
 
5.0%
앞 3359
 
4.3%
역 3121
 
4.0%
번 2826
 
3.6%
출 2791
 
3.6%
동 1803
 
2.3%
교 1572
 
2.0%
리 1387
 
1.8%
원 1280
 
1.6%
사 1110
 
1.4%
Other values (420) 54949
70.4%

'대여구분코드'
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'정기'
6318 
'일일(회원)'
2813 
'일일(비회원)'
746 
'단체'
 
123

Length

Max length9
Median length4
Mean length5.4982
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'정기'
2nd row'정기'
3rd row'정기'
4th row'정기'
5th row'일일(회원)'

Common Values

ValueCountFrequency (%)
'정기' 6318
63.2%
'일일(회원)' 2813
28.1%
'일일(비회원)' 746
 
7.5%
'단체' 123
 
1.2%

Length

2024-05-18T14:07:14.634148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:07:14.815269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 6318
63.2%
일일(회원 2813
28.1%
일일(비회원 746
 
7.5%
단체 123
 
1.2%

'SEX_CD'
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'M'
4884 
'F'
4483 
''
633 

Length

Max length3
Median length3
Mean length2.9367
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'F'
2nd row'M'
3rd row'M'
4th row'F'
5th row'F'

Common Values

ValueCountFrequency (%)
'M' 4884
48.8%
'F' 4483
44.8%
'' 633
 
6.3%

Length

2024-05-18T14:07:15.012756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:07:15.310463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 4884
48.8%
f 4483
44.8%
633
 
6.3%

'연령대코드'
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
'20대'
3248 
'30대'
2467 
'40대'
1645 
'50대'
965 
<NA>
746 
Other values (3)
929 

Length

Max length6
Median length5
Mean length4.9873
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row'30대'
2nd row'20대'
3rd row'30대'
4th row'30대'
5th row'20대'

Common Values

ValueCountFrequency (%)
'20대' 3248
32.5%
'30대' 2467
24.7%
'40대' 1645
16.4%
'50대' 965
 
9.7%
<NA> 746
 
7.5%
'~10대' 514
 
5.1%
'60대' 310
 
3.1%
'70대~' 105
 
1.1%

Length

2024-05-18T14:07:15.742188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:07:16.101047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20대 3248
32.5%
30대 2467
24.7%
40대 1645
16.4%
50대 965
 
9.7%
na 746
 
7.5%
10대 514
 
5.1%
60대 310
 
3.1%
70대 105
 
1.1%

'이용건수'
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2608
Minimum1
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T14:07:16.381023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile10
Maximum124
Range123
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.1996604
Coefficient of variation (CV)1.2879233
Kurtosis156.54443
Mean3.2608
Median Absolute Deviation (MAD)1
Skewness8.3726468
Sum32608
Variance17.637147
MonotonicityNot monotonic
2024-05-18T14:07:16.650843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 4009
40.1%
2 1988
19.9%
3 1203
 
12.0%
4 794
 
7.9%
5 494
 
4.9%
6 338
 
3.4%
7 273
 
2.7%
8 198
 
2.0%
9 160
 
1.6%
10 110
 
1.1%
Other values (36) 433
 
4.3%
ValueCountFrequency (%)
1 4009
40.1%
2 1988
19.9%
3 1203
 
12.0%
4 794
 
7.9%
5 494
 
4.9%
6 338
 
3.4%
7 273
 
2.7%
8 198
 
2.0%
9 160
 
1.6%
10 110
 
1.1%
ValueCountFrequency (%)
124 1
< 0.1%
101 1
< 0.1%
96 1
< 0.1%
89 1
< 0.1%
61 1
< 0.1%
59 1
< 0.1%
57 1
< 0.1%
45 1
< 0.1%
43 1
< 0.1%
41 1
< 0.1%

'운동량'
Real number (ℝ)

HIGH CORRELATION 

Distinct8393
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean426.42465
Minimum0
Maximum23839.36
Zeros67
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T14:07:17.016464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile23.5075
Q180.7675
median201.72
Q3467.9025
95-th percentile1622.822
Maximum23839.36
Range23839.36
Interquartile range (IQR)387.135

Descriptive statistics

Standard deviation753.53139
Coefficient of variation (CV)1.7670915
Kurtosis182.9595
Mean426.42465
Median Absolute Deviation (MAD)148.18
Skewness9.2366614
Sum4264246.5
Variance567809.56
MonotonicityNot monotonic
2024-05-18T14:07:17.422348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 67
 
0.7%
45.3 10
 
0.1%
52.51 8
 
0.1%
24.71 8
 
0.1%
21.62 7
 
0.1%
38.87 7
 
0.1%
71.3 7
 
0.1%
17.5 6
 
0.1%
27.8 6
 
0.1%
32.95 6
 
0.1%
Other values (8383) 9868
98.7%
ValueCountFrequency (%)
0.0 67
0.7%
0.87 1
 
< 0.1%
0.89 1
 
< 0.1%
1.09 1
 
< 0.1%
1.75 1
 
< 0.1%
2.22 1
 
< 0.1%
2.93 1
 
< 0.1%
3.04 1
 
< 0.1%
4.38 1
 
< 0.1%
4.51 1
 
< 0.1%
ValueCountFrequency (%)
23839.36 1
< 0.1%
18994.08 1
< 0.1%
17043.42 1
< 0.1%
12855.85 1
< 0.1%
11070.52 1
< 0.1%
10829.26 1
< 0.1%
9457.28 1
< 0.1%
8850.36 1
< 0.1%
7885.85 1
< 0.1%
7218.0 1
< 0.1%

'탄소량'
Real number (ℝ)

HIGH CORRELATION 

Distinct1616
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.791145
Minimum0
Maximum214.88
Zeros67
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T14:07:17.823165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.22
Q10.73
median1.81
Q34.13
95-th percentile14.44
Maximum214.88
Range214.88
Interquartile range (IQR)3.4

Descriptive statistics

Standard deviation6.7969914
Coefficient of variation (CV)1.7928598
Kurtosis203.12978
Mean3.791145
Median Absolute Deviation (MAD)1.31
Skewness9.838283
Sum37911.45
Variance46.199092
MonotonicityNot monotonic
2024-05-18T14:07:18.231058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 67
 
0.7%
0.39 57
 
0.6%
0.29 54
 
0.5%
0.32 54
 
0.5%
0.23 53
 
0.5%
0.26 53
 
0.5%
0.42 51
 
0.5%
0.27 50
 
0.5%
0.33 49
 
0.5%
0.37 47
 
0.5%
Other values (1606) 9465
94.7%
ValueCountFrequency (%)
0.0 67
0.7%
0.01 2
 
< 0.1%
0.02 2
 
< 0.1%
0.03 2
 
< 0.1%
0.04 3
 
< 0.1%
0.05 2
 
< 0.1%
0.06 11
 
0.1%
0.07 14
 
0.1%
0.08 8
 
0.1%
0.09 13
 
0.1%
ValueCountFrequency (%)
214.88 1
< 0.1%
175.55 1
< 0.1%
171.15 1
< 0.1%
132.4 1
< 0.1%
99.78 1
< 0.1%
93.58 1
< 0.1%
75.38 1
< 0.1%
73.59 1
< 0.1%
66.34 1
< 0.1%
65.64 1
< 0.1%

'이동거리(M)'
Real number (ℝ)

HIGH CORRELATION 

Distinct3621
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16341.197
Minimum0
Maximum926160
Zeros67
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T14:07:18.653118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile950
Q13150
median7790
Q317820
95-th percentile62220
Maximum926160
Range926160
Interquartile range (IQR)14670

Descriptive statistics

Standard deviation29297.131
Coefficient of variation (CV)1.7928387
Kurtosis203.11064
Mean16341.197
Median Absolute Deviation (MAD)5640
Skewness9.8378217
Sum1.6341197 × 108
Variance8.5832189 × 108
MonotonicityNot monotonic
2024-05-18T14:07:18.993711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 67
 
0.7%
2610 18
 
0.2%
1440 17
 
0.2%
2170 17
 
0.2%
3280 17
 
0.2%
1760 16
 
0.2%
1170 16
 
0.2%
1680 15
 
0.1%
1620 15
 
0.1%
1290 15
 
0.1%
Other values (3611) 9787
97.9%
ValueCountFrequency (%)
0 67
0.7%
30 1
 
< 0.1%
40 1
 
< 0.1%
70 1
 
< 0.1%
80 1
 
< 0.1%
130 1
 
< 0.1%
150 1
 
< 0.1%
160 1
 
< 0.1%
170 1
 
< 0.1%
190 1
 
< 0.1%
ValueCountFrequency (%)
926160 1
< 0.1%
756530 1
< 0.1%
737920 1
< 0.1%
570520 1
< 0.1%
430090 1
< 0.1%
403290 1
< 0.1%
324870 1
< 0.1%
317180 1
< 0.1%
285990 1
< 0.1%
282940 1
< 0.1%

'이동시간(분)'
Real number (ℝ)

HIGH CORRELATION 

Distinct649
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean107.1006
Minimum0
Maximum8700
Zeros17
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T14:07:19.397208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q124
median58
Q3125
95-th percentile344
Maximum8700
Range8700
Interquartile range (IQR)101

Descriptive statistics

Standard deviation200.95743
Coefficient of variation (CV)1.8763427
Kurtosis547.08136
Mean107.1006
Median Absolute Deviation (MAD)41
Skewness17.071101
Sum1071006
Variance40383.887
MonotonicityNot monotonic
2024-05-18T14:07:19.841044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 142
 
1.4%
11 139
 
1.4%
8 136
 
1.4%
12 133
 
1.3%
6 129
 
1.3%
15 127
 
1.3%
9 125
 
1.2%
7 125
 
1.2%
20 118
 
1.2%
17 115
 
1.1%
Other values (639) 8711
87.1%
ValueCountFrequency (%)
0 17
 
0.2%
1 8
 
0.1%
2 44
 
0.4%
3 66
0.7%
4 102
1.0%
5 111
1.1%
6 129
1.3%
7 125
1.2%
8 136
1.4%
9 125
1.2%
ValueCountFrequency (%)
8700 1
< 0.1%
6489 1
< 0.1%
5611 1
< 0.1%
4929 1
< 0.1%
3758 1
< 0.1%
2409 1
< 0.1%
2322 1
< 0.1%
2225 1
< 0.1%
2015 1
< 0.1%
1918 1
< 0.1%

Interactions

2024-05-18T14:07:08.168229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:02.765502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:04.101211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:05.478196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:06.828944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:08.464442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:03.030183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:04.372002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:05.738639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:07.122593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:08.727892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:03.290980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:04.627689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:06.070375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:07.395096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:08.987613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:03.545486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:04.874763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:06.306147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:07.652082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:09.243045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:03.800818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:05.123834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:06.570820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:07:07.907721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T14:07:20.105398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
'대여일자''대여구분코드''SEX_CD''연령대코드''이용건수''운동량''탄소량''이동거리(M)''이동시간(분)'
'대여일자'1.0000.3430.2350.0860.0470.0180.0050.0050.034
'대여구분코드'0.3431.0000.6270.1880.0560.0840.0660.0660.142
'SEX_CD'0.2350.6271.0000.1260.0530.0850.1280.1280.128
'연령대코드'0.0860.1880.1261.0000.1750.1280.1330.1330.055
'이용건수'0.0470.0560.0530.1751.0000.9440.8920.8920.971
'운동량'0.0180.0840.0850.1280.9441.0000.9770.9770.974
'탄소량'0.0050.0660.1280.1330.8920.9771.0001.0000.946
'이동거리(M)'0.0050.0660.1280.1330.8920.9771.0001.0000.946
'이동시간(분)'0.0340.1420.1280.0550.9710.9740.9460.9461.000
2024-05-18T14:07:20.415652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
'SEX_CD''연령대코드''대여구분코드''대여일자'
'SEX_CD'1.0000.1350.6460.224
'연령대코드'0.1351.0000.1300.059
'대여구분코드'0.6460.1301.0000.139
'대여일자'0.2240.0590.1391.000
2024-05-18T14:07:20.694796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
'이용건수''운동량''탄소량''이동거리(M)''이동시간(분)''대여일자''대여구분코드''SEX_CD''연령대코드'
'이용건수'1.0000.7340.7360.7360.7440.0210.0250.0330.062
'운동량'0.7341.0000.9920.9920.8870.0080.0380.0530.045
'탄소량'0.7360.9921.0001.0000.8970.0030.0420.0560.047
'이동거리(M)'0.7360.9921.0001.0000.8970.0030.0420.0560.047
'이동시간(분)'0.7440.8870.8970.8971.0000.0160.0640.0810.035
'대여일자'0.0210.0080.0030.0030.0161.0000.1390.2240.059
'대여구분코드'0.0250.0380.0420.0420.0640.1391.0000.6460.130
'SEX_CD'0.0330.0530.0560.0560.0810.2240.6461.0000.135
'연령대코드'0.0620.0450.0470.0470.0350.0590.1300.1351.000

Missing values

2024-05-18T14:07:09.611813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T14:07:10.217327image/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

'대여일자''대여소번호''대여소''대여구분코드''SEX_CD''연령대코드''이용건수''운동량''탄소량''이동거리(M)''이동시간(분)'
14428'2018-06-02''241'' 신길우성1차아파트 앞 공원''정기''F''30대'2301.413.071326087
4313'2018-06-01''381'' 장충체육관''정기''M''20대'2167.651.48640071
31384'2018-06-03''1512'' 강북중학교 앞''정기''M''30대'2129.21.01435022
2133'2018-06-01''2230''이수역 4번 출구''정기''F''30대'4200.682.1901067
9353'2018-06-01''2028'' 남성역 2번출구 뒷편''일일(회원)''F''20대'178.710.87375023
31162'2018-06-03''212'' 여의도역 1번출구 옆''정기''M''30대'5460.33.5615380112
19769'2018-06-02''1019'' 다성이즈빌아파트(호원대 대각선 맞은편)''정기''M''50대'125.230.239806
6529'2018-06-01''351'' 청운초교 앞 삼거리''정기''M''40대'150.490.35150010
35705'2018-06-03''314'' 국립현대미술관''일일(회원)''M''20대'4360.972.891245096
38078'2018-06-03''548'' 자양나들목''일일(비회원)'''<NA>2550.334.9621380182
'대여일자''대여소번호''대여소''대여구분코드''SEX_CD''연령대코드''이용건수''운동량''탄소량''이동거리(M)''이동시간(분)'
26511'2018-06-03''158'' 독립문 어린이 공원''정기''F''20대'378.120.82352032
37533'2018-06-03''1955'' 디지털입구 교차로''일일(회원)''M''40대'1115.920.93401016
28776'2018-06-03''136'' 대흥동 주민센터''정기''F''50대'111.540.125302
7987'2018-06-01''2119'' 중앙동 동진빌딩''정기''M''50대'1121.080.91392023
29959'2018-06-03''915'' 증산역 4번출구''정기''M''20대'3100.930.76325023
6449'2018-06-01''2064'' 흑석한강푸르지오 106동앞''정기''M''40대'159.160.3916609
29466'2018-06-03''1343'' 한성대7번출구 앞''정기''M''20대'267.060.56242017
28351'2018-06-03''716''신정6동 주민센터 인근''정기''F''40대'141.580.41175018
6794'2018-06-01''913'' 이마트 은평점''정기''M''40대'91378.2611.7750720264
42226'2018-06-04''3513'' 상왕십리역 1번출구''정기''F''50대'269.780.67289093