Overview

Dataset statistics

Number of variables13
Number of observations618
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory65.9 KiB
Average record size in memory109.2 B

Variable types

Numeric5
Text3
Boolean1
Categorical2
DateTime2

Dataset

Description세종특별자치시 공공자전거(어울링) 대여소 정보 입니다. 제공정보로는 STATION_NO, STATION_ID, STATION_NAME, ADDR, GPS 정보 입니다.
Author세종도시교통공사
URLhttps://www.data.go.kr/data/15091421/fileData.do

Alerts

주소(구) has constant value ""Constant
대여소 번호 is highly overall correlated with 주소(동)High correlation
위도 is highly overall correlated with 주소(동)High correlation
경도 is highly overall correlated with 권역 and 1 other fieldsHigh correlation
권역 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
지오펜스 거리 is highly overall correlated with 사용유무 and 1 other fieldsHigh correlation
사용유무 is highly overall correlated with 지오펜스 거리 and 1 other fieldsHigh correlation
주소(동) is highly overall correlated with 대여소 번호 and 5 other fieldsHigh correlation
사용유무 is highly imbalanced (91.1%)Imbalance
대여소 번호 has unique valuesUnique
대여소 아이디 has unique valuesUnique
등록일 has unique valuesUnique
권역 has 13 (2.1%) zerosZeros

Reproduction

Analysis started2023-12-12 12:15:12.650783
Analysis finished2023-12-12 12:15:17.089384
Duration4.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여소 번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct618
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean322.73301
Minimum1
Maximum999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T21:15:17.180292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile31.85
Q1157.25
median319.5
Q3476.75
95-th percentile629.15
Maximum999
Range998
Interquartile range (IQR)319.5

Descriptive statistics

Standard deviation192.85982
Coefficient of variation (CV)0.59758318
Kurtosis-0.7171524
Mean322.73301
Median Absolute Deviation (MAD)160
Skewness0.19852298
Sum199449
Variance37194.909
MonotonicityStrictly increasing
2023-12-12T21:15:17.345077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
428 1
 
0.2%
421 1
 
0.2%
422 1
 
0.2%
423 1
 
0.2%
424 1
 
0.2%
425 1
 
0.2%
426 1
 
0.2%
427 1
 
0.2%
429 1
 
0.2%
Other values (608) 608
98.4%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
999 1
0.2%
990 1
0.2%
900 1
0.2%
662 1
0.2%
661 1
0.2%
660 1
0.2%
659 1
0.2%
657 1
0.2%
656 1
0.2%
655 1
0.2%

대여소 아이디
Text

UNIQUE 

Distinct618
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T21:15:17.769202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9902913
Min length6

Characters and Unicode

Total characters4938
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique618 ?
Unique (%)100.0%

Sample

1st rowSJ_00001
2nd rowSJ_00002
3rd rowSJ_00003
4th rowSJ_00004
5th rowSJ_00005
ValueCountFrequency (%)
sj_00001 1
 
0.2%
sj_00424 1
 
0.2%
sj_00418 1
 
0.2%
sj_00419 1
 
0.2%
sj_00435 1
 
0.2%
sj_00420 1
 
0.2%
sj_00421 1
 
0.2%
sj_00422 1
 
0.2%
sj_00423 1
 
0.2%
sj_00425 1
 
0.2%
Other values (608) 608
98.4%
2023-12-12T21:15:18.333562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1465
29.7%
S 617
12.5%
J 617
12.5%
_ 617
12.5%
1 232
 
4.7%
3 226
 
4.6%
2 224
 
4.5%
4 219
 
4.4%
5 199
 
4.0%
6 167
 
3.4%
Other values (6) 355
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3084
62.5%
Uppercase Letter 1236
25.0%
Connector Punctuation 617
 
12.5%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1465
47.5%
1 232
 
7.5%
3 226
 
7.3%
2 224
 
7.3%
4 219
 
7.1%
5 199
 
6.5%
6 167
 
5.4%
7 120
 
3.9%
8 119
 
3.9%
9 113
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
S 617
49.9%
J 617
49.9%
D 1
 
0.1%
M 1
 
0.1%
Connector Punctuation
ValueCountFrequency (%)
_ 617
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3702
75.0%
Latin 1236
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1465
39.6%
_ 617
16.7%
1 232
 
6.3%
3 226
 
6.1%
2 224
 
6.1%
4 219
 
5.9%
5 199
 
5.4%
6 167
 
4.5%
7 120
 
3.2%
8 119
 
3.2%
Other values (2) 114
 
3.1%
Latin
ValueCountFrequency (%)
S 617
49.9%
J 617
49.9%
D 1
 
0.1%
M 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4938
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1465
29.7%
S 617
12.5%
J 617
12.5%
_ 617
12.5%
1 232
 
4.7%
3 226
 
4.6%
2 224
 
4.5%
4 219
 
4.4%
5 199
 
4.0%
6 167
 
3.4%
Other values (6) 355
 
7.2%

대여소 이름
Text

Distinct611
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T21:15:18.620933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length12.794498
Min length2

Characters and Unicode

Total characters7907
Distinct characters325
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique604 ?
Unique (%)97.7%

Sample

1st row보람동_세종시청 정문1
2nd row보람동_시드니하트
3rd row보람동_세종시청 후문
4th row보람동_세종시청후문 잔디광장
5th row보람동_호려울302동 건너편
ValueCountFrequency (%)
앞 56
 
6.4%
건너편 23
 
2.6%
버스정류장 12
 
1.4%
로터리 12
 
1.4%
반곡동_수루배 11
 
1.3%
새롬동_새뜸 8
 
0.9%
정문 8
 
0.9%
공원 7
 
0.8%
옆 6
 
0.7%
보람동_세종시청 6
 
0.7%
Other values (654) 722
82.9%
2023-12-12T21:15:19.054602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 876
 
11.1%
_ 626
 
7.9%
255
 
3.2%
1 252
 
3.2%
앞 246
 
3.1%
0 235
 
3.0%
새 128
 
1.6%
2 126
 
1.6%
정 112
 
1.4%
나 99
 
1.3%
Other values (315) 4952
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5694
72.0%
Decimal Number 980
 
12.4%
Connector Punctuation 626
 
7.9%
Space Separator 255
 
3.2%
Uppercase Letter 253
 
3.2%
Open Punctuation 47
 
0.6%
Close Punctuation 47
 
0.6%
Lowercase Letter 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 876
 
15.4%
앞 246
 
4.3%
새 128
 
2.2%
정 112
 
2.0%
나 99
 
1.7%
가 96
 
1.7%
종 92
 
1.6%
편 90
 
1.6%
건 89
 
1.6%
담 89
 
1.6%
Other values (284) 3777
66.3%
Uppercase Letter
ValueCountFrequency (%)
B 79
31.2%
T 77
30.4%
R 76
30.0%
L 5
 
2.0%
H 5
 
2.0%
S 2
 
0.8%
A 2
 
0.8%
J 2
 
0.8%
W 1
 
0.4%
C 1
 
0.4%
Other values (3) 3
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 252
25.7%
0 235
24.0%
2 126
12.9%
3 95
 
9.7%
6 59
 
6.0%
4 56
 
5.7%
8 50
 
5.1%
5 39
 
4.0%
9 35
 
3.6%
7 33
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
h 1
33.3%
t 1
33.3%
e 1
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 626
100.0%
Space Separator
ValueCountFrequency (%)
255
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5694
72.0%
Common 1957
 
24.8%
Latin 256
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 876
 
15.4%
앞 246
 
4.3%
새 128
 
2.2%
정 112
 
2.0%
나 99
 
1.7%
가 96
 
1.7%
종 92
 
1.6%
편 90
 
1.6%
건 89
 
1.6%
담 89
 
1.6%
Other values (284) 3777
66.3%
Latin
ValueCountFrequency (%)
B 79
30.9%
T 77
30.1%
R 76
29.7%
L 5
 
2.0%
H 5
 
2.0%
S 2
 
0.8%
A 2
 
0.8%
J 2
 
0.8%
W 1
 
0.4%
h 1
 
0.4%
Other values (6) 6
 
2.3%
Common
ValueCountFrequency (%)
_ 626
32.0%
255
13.0%
1 252
12.9%
0 235
 
12.0%
2 126
 
6.4%
3 95
 
4.9%
6 59
 
3.0%
4 56
 
2.9%
8 50
 
2.6%
( 47
 
2.4%
Other values (5) 156
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5694
72.0%
ASCII 2213
 
28.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 876
 
15.4%
앞 246
 
4.3%
새 128
 
2.2%
정 112
 
2.0%
나 99
 
1.7%
가 96
 
1.7%
종 92
 
1.6%
편 90
 
1.6%
건 89
 
1.6%
담 89
 
1.6%
Other values (284) 3777
66.3%
ASCII
ValueCountFrequency (%)
_ 626
28.3%
255
11.5%
1 252
11.4%
0 235
 
10.6%
2 126
 
5.7%
3 95
 
4.3%
B 79
 
3.6%
T 77
 
3.5%
R 76
 
3.4%
6 59
 
2.7%
Other values (21) 333
15.0%

사용유무
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size750.0 B
True
611 
False
 
7
ValueCountFrequency (%)
True 611
98.9%
False 7
 
1.1%
2023-12-12T21:15:19.205384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

주소(구)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
세종
618 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세종 618
100.0%

Length

2023-12-12T21:15:19.336766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:15:19.461124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세종 618
100.0%

주소(동)
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
어진동
75 
나성동
66 
고운동
52 
다정동
48 
도담동
46 
Other values (26)
331 

Length

Max length8
Median length3
Mean length3.2055016
Min length3

Unique

Unique7 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
어진동 75
12.1%
나성동 66
10.7%
고운동 52
 
8.4%
다정동 48
 
7.8%
도담동 46
 
7.4%
새롬동 41
 
6.6%
소담동 40
 
6.5%
보람동 38
 
6.1%
아름동 37
 
6.0%
종촌동 33
 
5.3%
Other values (21) 142
23.0%

Length

2023-12-12T21:15:19.641306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
어진동 75
11.6%
나성동 66
 
10.2%
고운동 52
 
8.0%
다정동 48
 
7.4%
도담동 46
 
7.1%
새롬동 41
 
6.3%
소담동 40
 
6.2%
보람동 38
 
5.9%
아름동 37
 
5.7%
종촌동 33
 
5.1%
Other values (23) 171
26.4%

상세주소
Text

Distinct499
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T21:15:19.914384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length16.140777
Min length11

Characters and Unicode

Total characters9975
Distinct characters77
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique429 ?
Unique (%)69.4%

Sample

1st row세종특별자치시 보람동 702
2nd row세종특별자치시 보람동 616-1
3rd row세종특별자치시 보람동 663
4th row세종특별자치시 보람동 626-2
5th row세종특별자치시 보람동 664-47
ValueCountFrequency (%)
세종특별자치시 616
32.4%
어진동 75
 
3.9%
나성동 66
 
3.5%
고운동 52
 
2.7%
다정동 48
 
2.5%
도담동 46
 
2.4%
새롬동 41
 
2.2%
소담동 40
 
2.1%
보람동 38
 
2.0%
아름동 37
 
1.9%
Other values (497) 840
44.2%
2023-12-12T21:15:20.363696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1283
 
12.9%
종 668
 
6.7%
세 635
 
6.4%
치 631
 
6.3%
특 617
 
6.2%
별 617
 
6.2%
시 617
 
6.2%
자 616
 
6.2%
동 581
 
5.8%
1 297
 
3.0%
Other values (67) 3413
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6337
63.5%
Decimal Number 2148
 
21.5%
Space Separator 1283
 
12.9%
Dash Punctuation 207
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
종 668
10.5%
세 635
10.0%
치 631
10.0%
특 617
9.7%
별 617
9.7%
시 617
9.7%
자 616
9.7%
동 581
9.2%
담 86
 
1.4%
진 75
 
1.2%
Other values (55) 1194
18.8%
Decimal Number
ValueCountFrequency (%)
1 297
13.8%
6 272
12.7%
3 262
12.2%
2 253
11.8%
7 246
11.5%
5 217
10.1%
4 176
8.2%
8 157
7.3%
0 146
6.8%
9 122
5.7%
Space Separator
ValueCountFrequency (%)
1283
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 207
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6337
63.5%
Common 3638
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
종 668
10.5%
세 635
10.0%
치 631
10.0%
특 617
9.7%
별 617
9.7%
시 617
9.7%
자 616
9.7%
동 581
9.2%
담 86
 
1.4%
진 75
 
1.2%
Other values (55) 1194
18.8%
Common
ValueCountFrequency (%)
1283
35.3%
1 297
 
8.2%
6 272
 
7.5%
3 262
 
7.2%
2 253
 
7.0%
7 246
 
6.8%
5 217
 
6.0%
- 207
 
5.7%
4 176
 
4.8%
8 157
 
4.3%
Other values (2) 268
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6337
63.5%
ASCII 3638
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1283
35.3%
1 297
 
8.2%
6 272
 
7.5%
3 262
 
7.2%
2 253
 
7.0%
7 246
 
6.8%
5 217
 
6.0%
- 207
 
5.7%
4 176
 
4.8%
8 157
 
4.3%
Other values (2) 268
 
7.4%
Hangul
ValueCountFrequency (%)
종 668
10.5%
세 635
10.0%
치 631
10.0%
특 617
9.7%
별 617
9.7%
시 617
9.7%
자 616
9.7%
동 581
9.2%
담 86
 
1.4%
진 75
 
1.2%
Other values (55) 1194
18.8%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct616
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.26609
Minimum126.88062
Maximum127.3373
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T21:15:20.573658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.88062
5-th percentile127.23704
Q1127.2501
median127.26021
Q3127.28104
95-th percentile127.31081
Maximum127.3373
Range0.456676
Interquartile range (IQR)0.0309405

Descriptive statistics

Standard deviation0.027945477
Coefficient of variation (CV)0.00021958306
Kurtosis57.668876
Mean127.26609
Median Absolute Deviation (MAD)0.0112965
Skewness-3.7281575
Sum78650.442
Variance0.00078094966
MonotonicityNot monotonic
2023-12-12T21:15:20.756177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.261558 2
 
0.3%
127.26201 2
 
0.3%
127.247528 1
 
0.2%
127.249509 1
 
0.2%
127.248994 1
 
0.2%
127.309493 1
 
0.2%
127.303453 1
 
0.2%
127.29728 1
 
0.2%
127.28665 1
 
0.2%
127.289963 1
 
0.2%
Other values (606) 606
98.1%
ValueCountFrequency (%)
126.880623 1
0.2%
127.229371 1
0.2%
127.229409 1
0.2%
127.229697 1
0.2%
127.229857 1
0.2%
127.22993 1
0.2%
127.230843 1
0.2%
127.230874 1
0.2%
127.231786 1
0.2%
127.231787 1
0.2%
ValueCountFrequency (%)
127.337299 1
0.2%
127.329186 1
0.2%
127.328621 1
0.2%
127.328582 1
0.2%
127.328434 1
0.2%
127.325863 1
0.2%
127.325279 1
0.2%
127.324919 1
0.2%
127.32453 1
0.2%
127.324436 1
0.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct613
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.500217
Minimum36.363496
Maximum37.484362
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T21:15:20.959805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.363496
5-th percentile36.475082
Q136.485518
median36.496
Q336.50758
95-th percentile36.52108
Maximum37.484362
Range1.120866
Interquartile range (IQR)0.02206225

Descriptive statistics

Standard deviation0.045291067
Coefficient of variation (CV)0.0012408438
Kurtosis362.66676
Mean36.500217
Median Absolute Deviation (MAD)0.0109
Skewness16.904883
Sum22557.134
Variance0.0020512808
MonotonicityNot monotonic
2023-12-12T21:15:21.162094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.491393 2
 
0.3%
36.487647 2
 
0.3%
36.497709 2
 
0.3%
36.504864 2
 
0.3%
36.50198 2
 
0.3%
36.47895 1
 
0.2%
36.594918 1
 
0.2%
36.490402 1
 
0.2%
36.491229 1
 
0.2%
36.493333 1
 
0.2%
Other values (603) 603
97.6%
ValueCountFrequency (%)
36.363496 1
0.2%
36.465209 1
0.2%
36.466008 1
0.2%
36.468184 1
0.2%
36.468474 1
0.2%
36.469017 1
0.2%
36.469257 1
0.2%
36.469965 1
0.2%
36.470509 1
0.2%
36.470563 1
0.2%
ValueCountFrequency (%)
37.484362 1
0.2%
36.621048 1
0.2%
36.614142 1
0.2%
36.610198 1
0.2%
36.609976 1
0.2%
36.608603 1
0.2%
36.602844 1
0.2%
36.602414 1
0.2%
36.602172 1
0.2%
36.601647 1
0.2%

권역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7686084
Minimum0
Maximum6
Zeros13
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T21:15:21.312862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9728161
Coefficient of variation (CV)0.55004606
Kurtosis0.48307986
Mean1.7686084
Median Absolute Deviation (MAD)1
Skewness0.89013255
Sum1093
Variance0.94637116
MonotonicityNot monotonic
2023-12-12T21:15:21.441553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 297
48.1%
2 166
26.9%
3 108
 
17.5%
4 32
 
5.2%
0 13
 
2.1%
6 2
 
0.3%
ValueCountFrequency (%)
0 13
 
2.1%
1 297
48.1%
2 166
26.9%
3 108
 
17.5%
4 32
 
5.2%
6 2
 
0.3%
ValueCountFrequency (%)
6 2
 
0.3%
4 32
 
5.2%
3 108
 
17.5%
2 166
26.9%
1 297
48.1%
0 13
 
2.1%

지오펜스 거리
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.386731
Minimum10
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T21:15:21.567499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile15
Q125
median30
Q330
95-th percentile40
Maximum200
Range190
Interquartile range (IQR)5

Descriptive statistics

Standard deviation9.8006525
Coefficient of variation (CV)0.33350604
Kurtosis149.12741
Mean29.386731
Median Absolute Deviation (MAD)0
Skewness8.7994704
Sum18161
Variance96.05279
MonotonicityNot monotonic
2023-12-12T21:15:21.685552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
30 357
57.8%
25 66
 
10.7%
20 61
 
9.9%
40 39
 
6.3%
35 35
 
5.7%
15 32
 
5.2%
50 10
 
1.6%
10 4
 
0.6%
45 4
 
0.6%
60 3
 
0.5%
Other values (7) 7
 
1.1%
ValueCountFrequency (%)
10 4
 
0.6%
15 32
 
5.2%
20 61
 
9.9%
23 1
 
0.2%
25 66
 
10.7%
27 1
 
0.2%
30 357
57.8%
31 1
 
0.2%
32 1
 
0.2%
33 1
 
0.2%
ValueCountFrequency (%)
200 1
 
0.2%
70 1
 
0.2%
60 3
 
0.5%
50 10
 
1.6%
45 4
 
0.6%
40 39
6.3%
35 35
5.7%
33 1
 
0.2%
32 1
 
0.2%
31 1
 
0.2%

등록일
Date

UNIQUE 

Distinct618
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum2018-06-19 19:37:25
Maximum2022-07-29 14:11:12
2023-12-12T21:15:21.837148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:22.005860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일
Date

Distinct270
Distinct (%)43.7%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum2018-10-12 12:52:23
Maximum2022-08-29 15:48:51
2023-12-12T21:15:22.187036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:22.678591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T21:15:16.122463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:13.348121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:14.424346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:15.030315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:15.543100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:16.228991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:13.461198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:14.555640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:15.122279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:15.645562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:16.328122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:13.580495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:14.678785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:15.217538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:15.751322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:16.422944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:13.721638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:14.787376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:15.314829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:15.871390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:16.525332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:14.271960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:14.893944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:15.419929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:15:15.996010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:15:22.812416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소 번호사용유무주소(동)위도경도권역지오펜스 거리
대여소 번호1.0000.5760.8390.7660.7050.5980.625
사용유무0.5761.0000.5990.5430.5460.0740.434
주소(동)0.8390.5991.0000.9790.9920.9510.925
위도0.7660.5430.9791.0000.9000.5980.649
경도0.7050.5460.9920.9001.0000.6500.651
권역0.5980.0740.9510.5980.6501.0000.250
지오펜스 거리0.6250.4340.9250.6490.6510.2501.000
2023-12-12T21:15:22.964545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주소(동)사용유무
주소(동)1.0000.503
사용유무0.5031.000
2023-12-12T21:15:23.101397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소 번호위도경도권역지오펜스 거리사용유무주소(동)
대여소 번호1.0000.2780.110-0.088-0.2080.4330.511
위도0.2781.000-0.3510.443-0.0360.3700.889
경도0.110-0.3511.000-0.687-0.0240.3720.943
권역-0.0880.443-0.6871.0000.0070.0530.777
지오펜스 거리-0.208-0.036-0.0240.0071.0000.5270.725
사용유무0.4330.3700.3720.0530.5271.0000.503
주소(동)0.5110.8890.9430.7770.7250.5031.000

Missing values

2023-12-12T21:15:16.714441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:15:16.991809image/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

대여소 번호대여소 아이디대여소 이름사용유무주소(구)주소(동)상세주소위도경도권역지오펜스 거리등록일수정일
01SJ_00001보람동_세종시청 정문1Y세종보람동세종특별자치시 보람동 702127.28903836.478953302018-06-19 19:37:252021-12-27 15:34:26
12SJ_00002보람동_시드니하트Y세종보람동세종특별자치시 보람동 616-1127.2941136.4840453302018-07-09 20:33:412021-04-20 13:56:15
23SJ_00003보람동_세종시청 후문Y세종보람동세종특별자치시 보람동 663127.28840536.4802583302018-06-21 15:44:322020-12-10 10:24:00
34SJ_00004보람동_세종시청후문 잔디광장Y세종보람동세종특별자치시 보람동 626-2127.2890936.4808423302018-06-21 15:49:042020-12-10 10:24:00
45SJ_00005보람동_호려울302동 건너편Y세종보람동세종특별자치시 보람동 664-47127.28110436.4775183302018-06-21 15:51:542020-12-10 10:24:00
56SJ_00006보람동_세종교육청Y세종보람동세종특별자치시 보람동 664-17127.28618236.4777363252018-06-21 15:56:152020-12-10 10:24:00
67SJ_00007보람동_세종남부경찰서 건너편Y세종보람동세종특별자치시 보람동 623-5127.29188336.4820373302018-06-21 15:59:082022-02-09 15:29:43
78SJ_00008보람동_새샘315동앞Y세종보람동세종특별자치시 보람동 617-5127.29437636.4838993302018-07-09 20:35:582020-12-10 10:24:00
89SJ_00009보람동_호려울8단지 정문Y세종보람동세종특별자치시 보람동 686127.29543936.4782633302018-07-09 20:38:152020-12-10 10:24:00
910SJ_00010보람동_호려울810동Y세종보람동세종특별자치시 보람동 635-8127.29730836.4799513302018-07-09 20:39:232020-12-15 14:07:14
대여소 번호대여소 아이디대여소 이름사용유무주소(구)주소(동)상세주소위도경도권역지오펜스 거리등록일수정일
608655SJ_00655다정동_가온7단지 정문 버스정류장Y세종다정동세종특별자치시 다정동 965127.24978136.4916162302022-05-31 14:00:262022-05-31 14:00:26
609656SJ_00656어진동_세종경찰기동대 인근Y세종어진동세종특별자치시 어진동 627127.26687936.5032811302022-05-31 14:03:122022-05-31 14:56:38
610657SJ_00657집현동_새나루1단지 후문(118동)Y세종반곡동세종특별자치시 반곡동 산 74127.31718436.4838814302022-05-31 14:05:502022-05-31 14:05:50
611659SJ_00659나성동_포드자동차 앞Y세종나성동세종특별자치시 나성동 752127.25917636.4842922302022-05-31 14:09:102022-05-31 14:09:10
612660SJ_00660어진동_한뜰406동 앞 버스정류장Y세종어진동세종특별자치시 어진동 520127.2549236.4990121302022-05-31 14:25:022022-05-31 14:25:02
613661SJ_00661어진동_한뜰401동 앞Y세종어진동세종특별자치시 어진동 520127.25561136.5010821302022-05-31 14:26:392022-07-22 14:33:06
614662SJ_00662집현동_새나루마을 803동 로터리Y세종집현동세종특별자치시 집현동 785-94127.32378736.4897354252022-07-29 14:11:122022-07-29 18:59:20
615900SM_00001삼미N세종가산동서울특별시 금천구 가산동126.88062337.48436212002018-10-12 12:51:302018-10-12 12:52:23
616990DJ_00001두드림N세종장대동대전 유성구 장대동 336-3127.33729936.3634960702018-06-28 13:25:492020-10-14 13:12:06
617999SJ-00000공영자전거 어울링센터Y세종도담동세종특별자치시 도담동 654127.26105436.5158211302018-08-20 15:59:052021-08-04 16:02:06