Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory732.4 KiB
Average record size in memory75.0 B

Variable types

Text3
DateTime2
Numeric3

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-22244/F/1/datasetView.do

Reproduction

Analysis started2024-01-05 23:59:01.373112
Analysis finished2024-01-05 23:59:07.891287
Duration6.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자전거번호
Text

Distinct2511
Distinct (%)25.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-05T23:59:08.313093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters90000
Distinct characters14
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

Unique684 ?
Unique (%)6.8%

Sample

1st rowSPB-40492
2nd rowSPB-56029
3rd rowSPB-58817
4th rowSPB-52944
5th rowSPB-47314
ValueCountFrequency (%)
spb-58383 56
 
0.6%
spb-33503 41
 
0.4%
spb-41695 30
 
0.3%
spb-53071 30
 
0.3%
spb-52422 30
 
0.3%
spb-45989 29
 
0.3%
spb-55133 28
 
0.3%
spb-48496 28
 
0.3%
spb-55962 27
 
0.3%
spb-58235 27
 
0.3%
Other values (2501) 9674
96.7%
2024-01-05T23:59:09.298393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 10000
11.1%
P 10000
11.1%
B 10000
11.1%
- 10000
11.1%
5 8524
9.5%
3 6799
7.6%
4 6650
7.4%
8 4757
 
5.3%
0 4146
 
4.6%
2 4076
 
4.5%
Other values (4) 15048
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50000
55.6%
Uppercase Letter 30000
33.3%
Dash Punctuation 10000
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 8524
17.0%
3 6799
13.6%
4 6650
13.3%
8 4757
9.5%
0 4146
8.3%
2 4076
8.2%
1 3993
8.0%
6 3865
7.7%
7 3766
7.5%
9 3424
6.8%
Uppercase Letter
ValueCountFrequency (%)
S 10000
33.3%
P 10000
33.3%
B 10000
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60000
66.7%
Latin 30000
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 10000
16.7%
5 8524
14.2%
3 6799
11.3%
4 6650
11.1%
8 4757
7.9%
0 4146
6.9%
2 4076
6.8%
1 3993
 
6.7%
6 3865
 
6.4%
7 3766
 
6.3%
Latin
ValueCountFrequency (%)
S 10000
33.3%
P 10000
33.3%
B 10000
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 10000
11.1%
P 10000
11.1%
B 10000
11.1%
- 10000
11.1%
5 8524
9.5%
3 6799
7.6%
4 6650
7.4%
8 4757
 
5.3%
0 4146
 
4.6%
2 4076
 
4.5%
Other values (4) 15048
16.7%

대여일시
Date

Distinct522
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-03-01 00:00:00
Maximum2022-03-01 10:26:00
2024-01-05T23:59:09.596689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T23:59:10.000730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대여대여소명
Text

Distinct1525
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-05T23:59:10.642333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.4224
Min length7

Characters and Unicode

Total characters154224
Distinct characters510
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique277 ?
Unique (%)2.8%

Sample

1st row215. 여의도고교 앞
2nd row1429. 장안중학교
3rd row847. 국방부민원실옆
4th row207. 여의나루역 1번출구 앞
5th row1666. 노원소방서인근
ValueCountFrequency (%)
앞 2598
 
8.8%
1번출구 573
 
1.9%
출구 462
 
1.6%
옆 390
 
1.3%
교차로 237
 
0.8%
2번출구 218
 
0.7%
입구 214
 
0.7%
3번출구 181
 
0.6%
207 178
 
0.6%
여의나루역 178
 
0.6%
Other values (3140) 24419
82.4%
2024-01-05T23:59:11.643066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19837
 
12.9%
. 10020
 
6.5%
1 8666
 
5.6%
2 6170
 
4.0%
4 4492
 
2.9%
3 4035
 
2.6%
0 3770
 
2.4%
구 3612
 
2.3%
5 3591
 
2.3%
7 3557
 
2.3%
Other values (500) 86474
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79247
51.4%
Decimal Number 42288
27.4%
Space Separator 19837
 
12.9%
Other Punctuation 10077
 
6.5%
Uppercase Letter 924
 
0.6%
Open Punctuation 757
 
0.5%
Close Punctuation 757
 
0.5%
Lowercase Letter 213
 
0.1%
Dash Punctuation 67
 
< 0.1%
Math Symbol 31
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3612
 
4.6%
앞 3052
 
3.9%
역 2889
 
3.6%
번 2553
 
3.2%
출 2511
 
3.2%
동 2108
 
2.7%
교 1792
 
2.3%
파 1309
 
1.7%
원 1289
 
1.6%
리 1277
 
1.6%
Other values (446) 56855
71.7%
Uppercase Letter
ValueCountFrequency (%)
K 167
18.1%
S 125
13.5%
B 88
9.5%
T 80
8.7%
C 72
7.8%
A 59
 
6.4%
D 57
 
6.2%
M 47
 
5.1%
G 45
 
4.9%
P 42
 
4.5%
Other values (12) 142
15.4%
Lowercase Letter
ValueCountFrequency (%)
e 63
29.6%
s 34
16.0%
r 22
 
10.3%
f 22
 
10.3%
h 22
 
10.3%
k 14
 
6.6%
t 8
 
3.8%
c 6
 
2.8%
m 6
 
2.8%
o 6
 
2.8%
Other values (2) 10
 
4.7%
Decimal Number
ValueCountFrequency (%)
1 8666
20.5%
2 6170
14.6%
4 4492
10.6%
3 4035
9.5%
0 3770
8.9%
5 3591
8.5%
7 3557
8.4%
6 3087
 
7.3%
8 2600
 
6.1%
9 2320
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 10020
99.4%
, 52
 
0.5%
& 4
 
< 0.1%
· 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
19837
100.0%
Open Punctuation
ValueCountFrequency (%)
( 757
100.0%
Close Punctuation
ValueCountFrequency (%)
) 757
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 67
100.0%
Math Symbol
ValueCountFrequency (%)
~ 31
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79247
51.4%
Common 73840
47.9%
Latin 1137
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3612
 
4.6%
앞 3052
 
3.9%
역 2889
 
3.6%
번 2553
 
3.2%
출 2511
 
3.2%
동 2108
 
2.7%
교 1792
 
2.3%
파 1309
 
1.7%
원 1289
 
1.6%
리 1277
 
1.6%
Other values (446) 56855
71.7%
Latin
ValueCountFrequency (%)
K 167
14.7%
S 125
 
11.0%
B 88
 
7.7%
T 80
 
7.0%
C 72
 
6.3%
e 63
 
5.5%
A 59
 
5.2%
D 57
 
5.0%
M 47
 
4.1%
G 45
 
4.0%
Other values (24) 334
29.4%
Common
ValueCountFrequency (%)
19837
26.9%
. 10020
13.6%
1 8666
11.7%
2 6170
 
8.4%
4 4492
 
6.1%
3 4035
 
5.5%
0 3770
 
5.1%
5 3591
 
4.9%
7 3557
 
4.8%
6 3087
 
4.2%
Other values (10) 6615
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79247
51.4%
ASCII 74976
48.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19837
26.5%
. 10020
13.4%
1 8666
11.6%
2 6170
 
8.2%
4 4492
 
6.0%
3 4035
 
5.4%
0 3770
 
5.0%
5 3591
 
4.8%
7 3557
 
4.7%
6 3087
 
4.1%
Other values (43) 7751
 
10.3%
Hangul
ValueCountFrequency (%)
구 3612
 
4.6%
앞 3052
 
3.9%
역 2889
 
3.6%
번 2553
 
3.2%
출 2511
 
3.2%
동 2108
 
2.7%
교 1792
 
2.3%
파 1309
 
1.7%
원 1289
 
1.6%
리 1277
 
1.6%
Other values (446) 56855
71.7%
None
ValueCountFrequency (%)
· 1
100.0%

반납일시
Date

Distinct530
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-03-01 00:04:00
Maximum2022-03-01 10:28:00
2024-01-05T23:59:12.035028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T23:59:12.626218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

반납대여소명
Text

Distinct1497
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-05T23:59:12.982753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length15.2446
Min length4

Characters and Unicode

Total characters152446
Distinct characters520
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

Unique268 ?
Unique (%)2.7%

Sample

1st row4496. 잠실 파크리오 120동 앞
2nd row1442. 중랑구 중소기업 창업센터
3rd row2025. 흑석역 1번출구
4th row207. 여의나루역 1번출구 앞
5th row1666. 노원소방서인근
ValueCountFrequency (%)
앞 2686
 
9.2%
출구 539
 
1.8%
1번출구 494
 
1.7%
옆 322
 
1.1%
교차로 317
 
1.1%
뒤 252
 
0.9%
5번출구 224
 
0.8%
3번출구 221
 
0.8%
4번출구 194
 
0.7%
2번출구 178
 
0.6%
Other values (3067) 23906
81.5%
2024-01-05T23:59:13.836569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19457
 
12.8%
. 10002
 
6.6%
1 8148
 
5.3%
2 6132
 
4.0%
3 4512
 
3.0%
4 4205
 
2.8%
0 4069
 
2.7%
구 3848
 
2.5%
5 3691
 
2.4%
7 3411
 
2.2%
Other values (510) 84971
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77961
51.1%
Decimal Number 42004
27.6%
Space Separator 19457
 
12.8%
Other Punctuation 10092
 
6.6%
Uppercase Letter 1028
 
0.7%
Close Punctuation 828
 
0.5%
Open Punctuation 828
 
0.5%
Lowercase Letter 115
 
0.1%
Dash Punctuation 95
 
0.1%
Math Symbol 24
 
< 0.1%
Other values (3) 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3848
 
4.9%
역 3117
 
4.0%
앞 3060
 
3.9%
번 2819
 
3.6%
출 2802
 
3.6%
동 2238
 
2.9%
교 1815
 
2.3%
리 1222
 
1.6%
파 1141
 
1.5%
원 1118
 
1.4%
Other values (455) 54781
70.3%
Uppercase Letter
ValueCountFrequency (%)
S 120
11.7%
K 116
11.3%
T 99
9.6%
C 87
 
8.5%
A 75
 
7.3%
D 74
 
7.2%
B 67
 
6.5%
L 51
 
5.0%
G 49
 
4.8%
I 47
 
4.6%
Other values (11) 243
23.6%
Lowercase Letter
ValueCountFrequency (%)
e 40
34.8%
s 24
20.9%
k 19
16.5%
v 8
 
7.0%
f 6
 
5.2%
h 6
 
5.2%
r 6
 
5.2%
t 2
 
1.7%
c 1
 
0.9%
m 1
 
0.9%
Other values (2) 2
 
1.7%
Decimal Number
ValueCountFrequency (%)
1 8148
19.4%
2 6132
14.6%
3 4512
10.7%
4 4205
10.0%
0 4069
9.7%
5 3691
8.8%
7 3411
8.1%
6 3080
 
7.3%
8 2540
 
6.0%
9 2216
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 10002
99.1%
, 60
 
0.6%
& 23
 
0.2%
· 7
 
0.1%
Space Separator
ValueCountFrequency (%)
19457
100.0%
Close Punctuation
ValueCountFrequency (%)
) 828
100.0%
Open Punctuation
ValueCountFrequency (%)
( 828
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 95
100.0%
Math Symbol
ValueCountFrequency (%)
~ 24
100.0%
Other Number
ValueCountFrequency (%)
① 9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77962
51.1%
Common 73341
48.1%
Latin 1143
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3848
 
4.9%
역 3117
 
4.0%
앞 3060
 
3.9%
번 2819
 
3.6%
출 2802
 
3.6%
동 2238
 
2.9%
교 1815
 
2.3%
리 1222
 
1.6%
파 1141
 
1.5%
원 1118
 
1.4%
Other values (456) 54782
70.3%
Latin
ValueCountFrequency (%)
S 120
 
10.5%
K 116
 
10.1%
T 99
 
8.7%
C 87
 
7.6%
A 75
 
6.6%
D 74
 
6.5%
B 67
 
5.9%
L 51
 
4.5%
G 49
 
4.3%
I 47
 
4.1%
Other values (23) 358
31.3%
Common
ValueCountFrequency (%)
19457
26.5%
. 10002
13.6%
1 8148
11.1%
2 6132
 
8.4%
3 4512
 
6.2%
4 4205
 
5.7%
0 4069
 
5.5%
5 3691
 
5.0%
7 3411
 
4.7%
6 3080
 
4.2%
Other values (11) 6634
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77961
51.1%
ASCII 74468
48.8%
Enclosed Alphanum 9
 
< 0.1%
None 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19457
26.1%
. 10002
13.4%
1 8148
10.9%
2 6132
 
8.2%
3 4512
 
6.1%
4 4205
 
5.6%
0 4069
 
5.5%
5 3691
 
5.0%
7 3411
 
4.6%
6 3080
 
4.1%
Other values (42) 7761
 
10.4%
Hangul
ValueCountFrequency (%)
구 3848
 
4.9%
역 3117
 
4.0%
앞 3060
 
3.9%
번 2819
 
3.6%
출 2802
 
3.6%
동 2238
 
2.9%
교 1815
 
2.3%
리 1222
 
1.6%
파 1141
 
1.5%
원 1118
 
1.4%
Other values (455) 54781
70.3%
Enclosed Alphanum
ValueCountFrequency (%)
① 9
100.0%
None
ValueCountFrequency (%)
· 7
87.5%
㈜ 1
 
12.5%

이동순서
Real number (ℝ)

Distinct208
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.6057
Minimum1
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-05T23:59:14.092778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median13
Q329
95-th percentile72
Maximum500
Range499
Interquartile range (IQR)23

Descriptive statistics

Standard deviation32.264314
Coefficient of variation (CV)1.4272645
Kurtosis59.974924
Mean22.6057
Median Absolute Deviation (MAD)9
Skewness5.9984348
Sum226057
Variance1040.9859
MonotonicityNot monotonic
2024-01-05T23:59:14.369402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 518
 
5.2%
4 501
 
5.0%
1 496
 
5.0%
5 487
 
4.9%
3 481
 
4.8%
6 447
 
4.5%
7 370
 
3.7%
8 362
 
3.6%
9 337
 
3.4%
11 327
 
3.3%
Other values (198) 5674
56.7%
ValueCountFrequency (%)
1 496
5.0%
2 518
5.2%
3 481
4.8%
4 501
5.0%
5 487
4.9%
6 447
4.5%
7 370
3.7%
8 362
3.6%
9 337
3.4%
10 293
2.9%
ValueCountFrequency (%)
500 1
< 0.1%
498 1
< 0.1%
495 1
< 0.1%
494 1
< 0.1%
485 1
< 0.1%
446 1
< 0.1%
443 1
< 0.1%
434 1
< 0.1%
433 1
< 0.1%
416 1
< 0.1%

위도
Real number (ℝ)

Distinct8696
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.549443
Minimum37.434231
Maximum37.695839
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-05T23:59:14.820422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.434231
5-th percentile37.48302
Q137.516524
median37.544618
Q337.574459
95-th percentile37.643567
Maximum37.695839
Range0.261608
Interquartile range (IQR)0.057935

Descriptive statistics

Standard deviation0.046088482
Coefficient of variation (CV)0.0012274079
Kurtosis-0.10647999
Mean37.549443
Median Absolute Deviation (MAD)0.028782
Skewness0.54609711
Sum375494.43
Variance0.0021241481
MonotonicityNot monotonic
2024-01-05T23:59:15.319399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.554585 6
 
0.1%
37.532734 5
 
0.1%
37.505116 5
 
0.1%
37.608059 4
 
< 0.1%
37.54055 4
 
< 0.1%
37.533955 4
 
< 0.1%
37.5051 4
 
< 0.1%
37.639812 4
 
< 0.1%
37.532845 4
 
< 0.1%
37.532707 4
 
< 0.1%
Other values (8686) 9956
99.6%
ValueCountFrequency (%)
37.434231 1
< 0.1%
37.440708 1
< 0.1%
37.445683 1
< 0.1%
37.448925 1
< 0.1%
37.448929 1
< 0.1%
37.448944 1
< 0.1%
37.448948 1
< 0.1%
37.451038 1
< 0.1%
37.451553 1
< 0.1%
37.451782 1
< 0.1%
ValueCountFrequency (%)
37.695839 1
< 0.1%
37.688217 1
< 0.1%
37.685711 1
< 0.1%
37.68475 1
< 0.1%
37.68082 1
< 0.1%
37.680271 1
< 0.1%
37.680088 1
< 0.1%
37.680061 1
< 0.1%
37.679993 1
< 0.1%
37.679375 1
< 0.1%

경도
Real number (ℝ)

Distinct8544
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98731
Minimum126.7986
Maximum127.18489
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-05T23:59:15.737276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.7986
5-th percentile126.84079
Q1126.90947
median126.99676
Q3127.06539
95-th percentile127.1299
Maximum127.18489
Range0.386292
Interquartile range (IQR)0.155926

Descriptive statistics

Standard deviation0.092406619
Coefficient of variation (CV)0.00072768387
Kurtosis-1.1818435
Mean126.98731
Median Absolute Deviation (MAD)0.0774345
Skewness-0.026840786
Sum1269873.1
Variance0.0085389833
MonotonicityNot monotonic
2024-01-05T23:59:16.273142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.145813 8
 
0.1%
127.081856 6
 
0.1%
127.093018 5
 
0.1%
126.915695 5
 
0.1%
126.895836 5
 
0.1%
126.899475 5
 
0.1%
127.073166 5
 
0.1%
126.922424 4
 
< 0.1%
127.145767 4
 
< 0.1%
126.925362 4
 
< 0.1%
Other values (8534) 9949
99.5%
ValueCountFrequency (%)
126.798599 1
< 0.1%
126.799461 1
< 0.1%
126.799706 1
< 0.1%
126.799805 1
< 0.1%
126.80555 1
< 0.1%
126.806229 1
< 0.1%
126.806496 1
< 0.1%
126.80674 1
< 0.1%
126.807762 1
< 0.1%
126.808052 1
< 0.1%
ValueCountFrequency (%)
127.184891 1
< 0.1%
127.184731 1
< 0.1%
127.18457 1
< 0.1%
127.184563 1
< 0.1%
127.184555 1
< 0.1%
127.184441 1
< 0.1%
127.18438 1
< 0.1%
127.181999 1
< 0.1%
127.18119 1
< 0.1%
127.181061 1
< 0.1%

Interactions

2024-01-05T23:59:06.352685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T23:59:04.625493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T23:59:05.499399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T23:59:06.587462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T23:59:04.931175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T23:59:05.782179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T23:59:06.836409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T23:59:05.210541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T23:59:06.056207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-05T23:59:16.569735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이동순서위도경도
이동순서1.0000.1510.192
위도0.1511.0000.611
경도0.1920.6111.000
2024-01-05T23:59:16.720690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이동순서위도경도
이동순서1.000-0.0290.009
위도-0.0291.0000.096
경도0.0090.0961.000

Missing values

2024-01-05T23:59:07.270550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-05T23:59:07.713061image/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

자전거번호대여일시대여대여소명반납일시반납대여소명이동순서위도경도
50292SPB-404922022-03-01 02:22215. 여의도고교 앞2022-03-01 04:184496. 잠실 파크리오 120동 앞9237.519569127.065285
68900SPB-560292022-03-01 09:091429. 장안중학교2022-03-01 09:341442. 중랑구 중소기업 창업센터737.601757127.079163
16994SPB-588172022-03-01 00:52847. 국방부민원실옆2022-03-01 01:162025. 흑석역 1번출구337.532413126.973
13245SPB-529442022-03-01 00:19207. 여의나루역 1번출구 앞2022-03-01 01:06207. 여의나루역 1번출구 앞2037.519173126.941605
11532SPB-473142022-03-01 00:021666. 노원소방서인근2022-03-01 01:021666. 노원소방서인근3137.637566127.059395
31628SPB-514862022-03-01 00:202623.석촌동 주민센터2022-03-01 02:002623.석촌동 주민센터2337.494644127.063232
14704SPB-549422022-03-01 00:57475.DDP 패션몰2022-03-01 01:10530. 청계벽산아파트 앞1237.570087127.026833
39883SPB-535572022-03-01 01:464465. 건영아파트앞 사거리2022-03-01 02:331019. 다성이즈빌아파트(호원대 대각선 맞은편)2037.502171127.109474
82454SPB-480022022-03-01 09:18972. 수색역2022-03-01 10:20495.염리초등학교 앞1437.56646126.899399
73943SPB-329462022-03-01 09:351139. 용문사 버스정류장2022-03-01 09:52785.양천구청, 보건소 사잇길337.533676126.863701
자전거번호대여일시대여대여소명반납일시반납대여소명이동순서위도경도
51314SPB-509832022-03-01 03:12930. 구 서부경찰서 건너편2022-03-01 04:45930. 구 서부경찰서 건너편6637.561882126.898705
60630SPB-371592022-03-01 08:233881. 신자초교입구 교차로2022-03-01 08:493511. 응봉역 1번출구1237.535229127.051559
21131SPB-559702022-03-01 00:384454. 위례 포레샤인 1809동 부근2022-03-01 01:292423.영희초교 사거리(래미안개포루체하임)4637.489735127.082932
70661SPB-561152022-03-01 09:372198.사랑의병원2022-03-01 09:432129. 낙성대 과학전시관437.473946126.959183
45271SPB-484962022-03-01 01:192177. 신대방역 2번 출구2022-03-01 03:06207. 여의나루역 1번출구 앞1937.504261126.921913
22115SPB-426002022-03-01 01:27240. 문래역 4번출구 앞2022-03-01 01:324565. 영등포 신세계백화점637.517982126.903366
52939SPB-553482022-03-01 05:244488. 문현중.고등학교 사이2022-03-01 05:564488. 문현중.고등학교 사이1337.479683127.132919
5078SPB-515492022-03-01 00:044217. 한강공원 망원나들목2022-03-01 00:38175. 홍연2교옆2937.575394126.926132
21800SPB-447142022-03-01 00:481243. 문정 법조단지72022-03-01 01:312639.석촌역 8번출구1337.50499127.107773
63434SPB-581972022-03-01 08:43922. 연신내역 4번출구2022-03-01 09:06934. 신사동 성당2037.598232126.91172