Overview

Dataset statistics

Number of variables4
Number of observations2612
Missing cells5
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory81.8 KiB
Average record size in memory32.1 B

Variable types

Categorical2
Text2

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15249/F/1/datasetView.do

Alerts

대여소별 대여내역 is highly overall correlated with Unnamed: 1High correlation
Unnamed: 1 is highly overall correlated with 대여소별 대여내역High correlation

Reproduction

Analysis started2024-03-13 09:54:37.468945
Analysis finished2024-03-13 09:54:38.118419
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여소별 대여내역
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
송파구
207 
강서구
 
179
강남구
 
148
영등포구
 
143
서초구
 
140
Other values (25)
1795 

Length

Max length7
Median length3
Mean length3.085758
Min length2

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row구분
3rd row조회구분
4th row총 2607건
5th row대여소 그룹

Common Values

ValueCountFrequency (%)
송파구 207
 
7.9%
강서구 179
 
6.9%
강남구 148
 
5.7%
영등포구 143
 
5.5%
서초구 140
 
5.4%
노원구 124
 
4.7%
마포구 122
 
4.7%
강동구 117
 
4.5%
양천구 105
 
4.0%
종로구 104
 
4.0%
Other values (20) 1223
46.8%

Length

2024-03-13T18:54:38.210751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송파구 207
 
7.9%
강서구 179
 
6.8%
강남구 148
 
5.7%
영등포구 143
 
5.5%
서초구 140
 
5.4%
노원구 124
 
4.7%
마포구 122
 
4.7%
강동구 117
 
4.5%
양천구 105
 
4.0%
종로구 104
 
4.0%
Other values (22) 1225
46.9%

Unnamed: 1
Categorical

HIGH CORRELATION 

Distinct40
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
상암1팀
 
151
학여울2팀
 
125
천호1팀
 
121
천호2팀
 
115
중랑3팀
 
96
Other values (35)
2004 

Length

Max length6
Median length4
Mean length4.2687596
Min length1

Unique

Unique4 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row월
3rd row대여소별
4th row<NA>
5th row팀명

Common Values

ValueCountFrequency (%)
상암1팀 151
 
5.8%
학여울2팀 125
 
4.8%
천호1팀 121
 
4.6%
천호2팀 115
 
4.4%
중랑3팀 96
 
3.7%
학여울1팀 94
 
3.6%
영남3팀 89
 
3.4%
중랑2팀 88
 
3.4%
중랑1팀 85
 
3.3%
이수3팀 84
 
3.2%
Other values (30) 1564
59.9%

Length

2024-03-13T18:54:38.359637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
상암1팀 151
 
5.7%
학여울2팀 125
 
4.7%
천호1팀 121
 
4.5%
천호2팀 115
 
4.3%
중랑3팀 96
 
3.6%
학여울1팀 94
 
3.5%
영남3팀 89
 
3.3%
중랑2팀 88
 
3.3%
중랑1팀 85
 
3.2%
이수3팀 84
 
3.2%
Other values (31) 1615
60.6%

Unnamed: 2
Text

Distinct2610
Distinct (%)100.0%
Missing2
Missing (%)0.1%
Memory size20.5 KiB
2024-03-13T18:54:38.649333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.564751
Min length3

Characters and Unicode

Total characters40624
Distinct characters588
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

Unique2610 ?
Unique (%)100.0%

Sample

1st row일/월
2nd row대여소
3rd row대여소 명
4th row4839. 혜원사거리 열정분식소 앞
5th row9980. 에이텍
ValueCountFrequency (%)
앞 685
 
9.0%
출구 104
 
1.4%
옆 97
 
1.3%
입구 70
 
0.9%
1번출구 62
 
0.8%
교차로 62
 
0.8%
사거리 57
 
0.8%
2번출구 47
 
0.6%
3번출구 44
 
0.6%
뒤 43
 
0.6%
Other values (5204) 6319
83.3%
2024-03-13T18:54:39.066958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4980
 
12.3%
. 2617
 
6.4%
1 1973
 
4.9%
2 1598
 
3.9%
3 1309
 
3.2%
4 1285
 
3.2%
5 954
 
2.3%
0 931
 
2.3%
6 897
 
2.2%
앞 812
 
2.0%
Other values (578) 23268
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20988
51.7%
Decimal Number 11153
27.5%
Space Separator 4980
 
12.3%
Other Punctuation 2649
 
6.5%
Uppercase Letter 333
 
0.8%
Open Punctuation 224
 
0.6%
Close Punctuation 224
 
0.6%
Lowercase Letter 46
 
0.1%
Dash Punctuation 18
 
< 0.1%
Math Symbol 4
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 812
 
3.9%
구 794
 
3.8%
역 582
 
2.8%
동 579
 
2.8%
번 505
 
2.4%
출 492
 
2.3%
교 438
 
2.1%
파 385
 
1.8%
아 373
 
1.8%
리 350
 
1.7%
Other values (513) 15678
74.7%
Uppercase Letter
ValueCountFrequency (%)
K 40
12.0%
S 39
11.7%
T 32
9.6%
C 31
9.3%
A 22
 
6.6%
D 22
 
6.6%
G 19
 
5.7%
M 18
 
5.4%
B 17
 
5.1%
P 17
 
5.1%
Other values (13) 76
22.8%
Lowercase Letter
ValueCountFrequency (%)
e 15
32.6%
s 7
15.2%
k 7
15.2%
t 3
 
6.5%
n 2
 
4.3%
l 2
 
4.3%
v 1
 
2.2%
y 1
 
2.2%
m 1
 
2.2%
o 1
 
2.2%
Other values (6) 6
 
13.0%
Decimal Number
ValueCountFrequency (%)
1 1973
17.7%
2 1598
14.3%
3 1309
11.7%
4 1285
11.5%
5 954
8.6%
0 931
8.3%
6 897
8.0%
7 811
7.3%
8 758
 
6.8%
9 637
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 2617
98.8%
, 18
 
0.7%
& 6
 
0.2%
· 4
 
0.2%
? 3
 
0.1%
/ 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 3
75.0%
+ 1
 
25.0%
Other Number
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%
Space Separator
ValueCountFrequency (%)
4980
100.0%
Open Punctuation
ValueCountFrequency (%)
( 224
100.0%
Close Punctuation
ValueCountFrequency (%)
) 224
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20989
51.7%
Common 19256
47.4%
Latin 379
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 812
 
3.9%
구 794
 
3.8%
역 582
 
2.8%
동 579
 
2.8%
번 505
 
2.4%
출 492
 
2.3%
교 438
 
2.1%
파 385
 
1.8%
아 373
 
1.8%
리 350
 
1.7%
Other values (514) 15679
74.7%
Latin
ValueCountFrequency (%)
K 40
 
10.6%
S 39
 
10.3%
T 32
 
8.4%
C 31
 
8.2%
A 22
 
5.8%
D 22
 
5.8%
G 19
 
5.0%
M 18
 
4.7%
B 17
 
4.5%
P 17
 
4.5%
Other values (29) 122
32.2%
Common
ValueCountFrequency (%)
4980
25.9%
. 2617
13.6%
1 1973
 
10.2%
2 1598
 
8.3%
3 1309
 
6.8%
4 1285
 
6.7%
5 954
 
5.0%
0 931
 
4.8%
6 897
 
4.7%
7 811
 
4.2%
Other values (15) 1901
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20988
51.7%
ASCII 19629
48.3%
None 5
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4980
25.4%
. 2617
13.3%
1 1973
 
10.1%
2 1598
 
8.1%
3 1309
 
6.7%
4 1285
 
6.5%
5 954
 
4.9%
0 931
 
4.7%
6 897
 
4.6%
7 811
 
4.1%
Other values (51) 2274
11.6%
Hangul
ValueCountFrequency (%)
앞 812
 
3.9%
구 794
 
3.8%
역 582
 
2.8%
동 579
 
2.8%
번 505
 
2.4%
출 492
 
2.3%
교 438
 
2.1%
파 385
 
1.8%
아 373
 
1.8%
리 350
 
1.7%
Other values (513) 15678
74.7%
None
ValueCountFrequency (%)
· 4
80.0%
㈜ 1
 
20.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%

Unnamed: 3
Text

Distinct1466
Distinct (%)56.2%
Missing3
Missing (%)0.1%
Memory size20.5 KiB
2024-03-13T18:54:39.477234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.3246455
Min length1

Characters and Unicode

Total characters8674
Distinct characters16
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

Unique789 ?
Unique (%)30.2%

Sample

1st row202203 ~ 202203
2nd row대여 건수
3rd row1
4th row6
5th row13
ValueCountFrequency (%)
239 8
 
0.3%
496 7
 
0.3%
687 7
 
0.3%
246 6
 
0.2%
295 6
 
0.2%
962 6
 
0.2%
571 6
 
0.2%
595 6
 
0.2%
252 6
 
0.2%
255 5
 
0.2%
Other values (1458) 2549
97.6%
2024-03-13T18:54:39.989525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1463
16.9%
2 1059
12.2%
3 864
10.0%
5 812
9.4%
4 790
9.1%
6 783
9.0%
7 746
8.6%
9 742
8.6%
8 713
8.2%
0 694
8.0%
Other values (6) 8
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8666
99.9%
Other Letter 4
 
< 0.1%
Space Separator 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1463
16.9%
2 1059
12.2%
3 864
10.0%
5 812
9.4%
4 790
9.1%
6 783
9.0%
7 746
8.6%
9 742
8.6%
8 713
8.2%
0 694
8.0%
Other Letter
ValueCountFrequency (%)
대 1
25.0%
여 1
25.0%
건 1
25.0%
수 1
25.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8670
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1463
16.9%
2 1059
12.2%
3 864
10.0%
5 812
9.4%
4 790
9.1%
6 783
9.0%
7 746
8.6%
9 742
8.6%
8 713
8.2%
0 694
8.0%
Other values (2) 4
 
< 0.1%
Hangul
ValueCountFrequency (%)
대 1
25.0%
여 1
25.0%
건 1
25.0%
수 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8670
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1463
16.9%
2 1059
12.2%
3 864
10.0%
5 812
9.4%
4 790
9.1%
6 783
9.0%
7 746
8.6%
9 742
8.6%
8 713
8.2%
0 694
8.0%
Other values (2) 4
 
< 0.1%
Hangul
ValueCountFrequency (%)
대 1
25.0%
여 1
25.0%
건 1
25.0%
수 1
25.0%

Correlations

2024-03-13T18:54:40.080874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소별 대여내역Unnamed: 1
대여소별 대여내역1.0000.996
Unnamed: 10.9961.000
2024-03-13T18:54:40.166367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소별 대여내역Unnamed: 1
대여소별 대여내역1.0000.906
Unnamed: 10.9061.000
2024-03-13T18:54:40.244660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소별 대여내역Unnamed: 1
대여소별 대여내역1.0000.906
Unnamed: 10.9061.000

Missing values

2024-03-13T18:54:37.906782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T18:54:37.980964image/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.
2024-03-13T18:54:38.064673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

대여소별 대여내역Unnamed: 1Unnamed: 2Unnamed: 3
0<NA><NA><NA><NA>
1구분월일/월202203 ~ 202203
2조회구분대여소별대여소<NA>
3총 2607건<NA><NA><NA>
4대여소 그룹팀명대여소 명대여 건수
5중랑구중랑3팀4839. 혜원사거리 열정분식소 앞1
6성동구테스트9980. 에이텍6
7금천구천왕3팀3971. 순흥안씨묘 건너편13
8서초구이수1팀4314. 탑성마을 버스정거장 옆14
9서초구이수1팀4322.서울추모공원 입구14
대여소별 대여내역Unnamed: 1Unnamed: 2Unnamed: 3
2602강서구개화1팀1153. 발산역 1번, 9번 인근 대여소5009
2603관악구영남2팀2177. 신대방역 2번 출구5059
2604영등포구영남3팀210. IFC몰5381
2605강서구개화1팀2701. 마곡나루역 5번출구 뒤편5964
2606관악구영남2팀2102. 봉림교 교통섬5987
2607송파구천호2팀1210. 롯데월드타워(잠실역2번출구 쪽)6256
2608마포구상암1팀4217. 한강공원 망원나들목7763
2609강서구개화1팀2715.마곡나루역 2번 출구8019
2610광진구중랑1팀502. 뚝섬유원지역 1번출구 앞8513
2611영등포구영남3팀207. 여의나루역 1번출구 앞9385