Overview

Dataset statistics

Number of variables4
Number of observations2599
Missing cells5
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory81.3 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 09:54:40.948768
Analysis finished2024-03-13 09:54:41.593310
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여소별 대여내역
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
송파구
207 
강서구
 
178
강남구
 
148
영등포구
 
143
서초구
 
140
Other values (25)
1783 

Length

Max length7
Median length3
Mean length3.0865718
Min length2

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row구분
3rd row조회구분
4th row총 2594건
5th row대여소 그룹

Common Values

ValueCountFrequency (%)
송파구 207
 
8.0%
강서구 178
 
6.8%
강남구 148
 
5.7%
영등포구 143
 
5.5%
서초구 140
 
5.4%
노원구 124
 
4.8%
마포구 123
 
4.7%
강동구 117
 
4.5%
종로구 104
 
4.0%
양천구 103
 
4.0%
Other values (20) 1212
46.6%

Length

2024-03-13T18:54:41.649529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송파구 207
 
8.0%
강서구 178
 
6.8%
강남구 148
 
5.7%
영등포구 143
 
5.5%
서초구 140
 
5.4%
노원구 124
 
4.8%
마포구 123
 
4.7%
강동구 117
 
4.5%
종로구 104
 
4.0%
양천구 103
 
4.0%
Other values (22) 1214
46.7%

Unnamed: 1
Categorical

HIGH CORRELATION 

Distinct40
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
상암1팀
 
151
학여울2팀
 
125
천호1팀
 
121
천호2팀
 
115
중랑3팀
 
96
Other values (35)
1991 

Length

Max length6
Median length4
Mean length4.2670258
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
 
4.7%
천호2팀 115
 
4.4%
중랑3팀 96
 
3.7%
학여울1팀 94
 
3.6%
영남3팀 89
 
3.4%
중랑1팀 85
 
3.3%
중랑2팀 85
 
3.3%
이수3팀 84
 
3.2%
Other values (30) 1554
59.8%

Length

2024-03-13T18:54:41.768207image/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
 
4.6%
천호2팀 115
 
4.3%
중랑3팀 96
 
3.6%
학여울1팀 94
 
3.5%
영남3팀 89
 
3.4%
중랑1팀 85
 
3.2%
중랑2팀 85
 
3.2%
이수3팀 84
 
3.2%
Other values (31) 1603
60.5%

Unnamed: 2
Text

Distinct2597
Distinct (%)100.0%
Missing2
Missing (%)0.1%
Memory size20.4 KiB
2024-03-13T18:54:42.029107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.562572
Min length3

Characters and Unicode

Total characters40416
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

Unique2597 ?
Unique (%)100.0%

Sample

1st row일/월
2nd row대여소
3rd row대여소 명
4th row4314. 탑성마을 버스정거장 옆
5th row4322.서울추모공원 입구
ValueCountFrequency (%)
앞 679
 
9.0%
출구 102
 
1.4%
옆 97
 
1.3%
입구 70
 
0.9%
교차로 62
 
0.8%
1번출구 62
 
0.8%
사거리 57
 
0.8%
2번출구 48
 
0.6%
3번출구 44
 
0.6%
뒤 43
 
0.6%
Other values (5176) 6285
83.3%
2024-03-13T18:54:42.433073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4952
 
12.3%
. 2604
 
6.4%
1 1968
 
4.9%
2 1595
 
3.9%
3 1302
 
3.2%
4 1269
 
3.1%
5 950
 
2.4%
0 925
 
2.3%
6 894
 
2.2%
7 807
 
2.0%
Other values (578) 23150
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20880
51.7%
Decimal Number 11097
27.5%
Space Separator 4952
 
12.3%
Other Punctuation 2636
 
6.5%
Uppercase Letter 332
 
0.8%
Open Punctuation 223
 
0.6%
Close Punctuation 223
 
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 805
 
3.9%
구 793
 
3.8%
역 580
 
2.8%
동 574
 
2.7%
번 504
 
2.4%
출 491
 
2.4%
교 438
 
2.1%
파 385
 
1.8%
아 373
 
1.8%
리 349
 
1.7%
Other values (513) 15588
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%
P 17
 
5.1%
B 16
 
4.8%
Other values (13) 76
22.9%
Lowercase Letter
ValueCountFrequency (%)
e 15
32.6%
s 7
15.2%
k 7
15.2%
t 3
 
6.5%
l 2
 
4.3%
n 2
 
4.3%
y 1
 
2.2%
v 1
 
2.2%
h 1
 
2.2%
r 1
 
2.2%
Other values (6) 6
 
13.0%
Decimal Number
ValueCountFrequency (%)
1 1968
17.7%
2 1595
14.4%
3 1302
11.7%
4 1269
11.4%
5 950
8.6%
0 925
8.3%
6 894
8.1%
7 807
7.3%
8 750
 
6.8%
9 637
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 2604
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 (%)
4952
100.0%
Open Punctuation
ValueCountFrequency (%)
( 223
100.0%
Close Punctuation
ValueCountFrequency (%)
) 223
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 20881
51.7%
Common 19157
47.4%
Latin 378
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 805
 
3.9%
구 793
 
3.8%
역 580
 
2.8%
동 574
 
2.7%
번 504
 
2.4%
출 491
 
2.4%
교 438
 
2.1%
파 385
 
1.8%
아 373
 
1.8%
리 349
 
1.7%
Other values (514) 15589
74.7%
Latin
ValueCountFrequency (%)
K 40
 
10.6%
S 39
 
10.3%
T 32
 
8.5%
C 31
 
8.2%
A 22
 
5.8%
D 22
 
5.8%
G 19
 
5.0%
M 18
 
4.8%
P 17
 
4.5%
B 16
 
4.2%
Other values (29) 122
32.3%
Common
ValueCountFrequency (%)
4952
25.8%
. 2604
13.6%
1 1968
 
10.3%
2 1595
 
8.3%
3 1302
 
6.8%
4 1269
 
6.6%
5 950
 
5.0%
0 925
 
4.8%
6 894
 
4.7%
7 807
 
4.2%
Other values (15) 1891
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20880
51.7%
ASCII 19529
48.3%
None 5
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4952
25.4%
. 2604
13.3%
1 1968
 
10.1%
2 1595
 
8.2%
3 1302
 
6.7%
4 1269
 
6.5%
5 950
 
4.9%
0 925
 
4.7%
6 894
 
4.6%
7 807
 
4.1%
Other values (51) 2263
11.6%
Hangul
ValueCountFrequency (%)
앞 805
 
3.9%
구 793
 
3.8%
역 580
 
2.8%
동 574
 
2.7%
번 504
 
2.4%
출 491
 
2.4%
교 438
 
2.1%
파 385
 
1.8%
아 373
 
1.8%
리 349
 
1.7%
Other values (513) 15588
74.7%
None
ValueCountFrequency (%)
· 4
80.0%
㈜ 1
 
20.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%

Unnamed: 3
Text

Distinct1072
Distinct (%)41.3%
Missing3
Missing (%)0.1%
Memory size20.4 KiB
2024-03-13T18:54:42.869697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.0469954
Min length1

Characters and Unicode

Total characters7910
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

Unique434 ?
Unique (%)16.7%

Sample

1st row202202 ~ 202202
2nd row대여 건수
3rd row2
4th row2
5th row3
ValueCountFrequency (%)
368 10
 
0.4%
294 9
 
0.3%
196 9
 
0.3%
290 9
 
0.3%
167 8
 
0.3%
350 8
 
0.3%
63 8
 
0.3%
225 8
 
0.3%
187 8
 
0.3%
188 8
 
0.3%
Other values (1064) 2514
96.7%
2024-03-13T18:54:43.342463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1241
15.7%
2 949
12.0%
3 897
11.3%
4 797
10.1%
5 780
9.9%
6 746
9.4%
7 658
8.3%
8 638
8.1%
9 630
8.0%
0 566
7.2%
Other values (6) 8
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7902
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 1241
15.7%
2 949
12.0%
3 897
11.4%
4 797
10.1%
5 780
9.9%
6 746
9.4%
7 658
8.3%
8 638
8.1%
9 630
8.0%
0 566
7.2%
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 7906
99.9%
Hangul 4
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1241
15.7%
2 949
12.0%
3 897
11.3%
4 797
10.1%
5 780
9.9%
6 746
9.4%
7 658
8.3%
8 638
8.1%
9 630
8.0%
0 566
7.2%
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 7906
99.9%
Hangul 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1241
15.7%
2 949
12.0%
3 897
11.3%
4 797
10.1%
5 780
9.9%
6 746
9.4%
7 658
8.3%
8 638
8.1%
9 630
8.0%
0 566
7.2%
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

2024-03-13T18:54:43.431654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소별 대여내역Unnamed: 1
대여소별 대여내역1.0000.996
Unnamed: 10.9961.000
2024-03-13T18:54:43.509869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소별 대여내역Unnamed: 1
대여소별 대여내역1.0000.906
Unnamed: 10.9061.000
2024-03-13T18:54:43.597433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소별 대여내역Unnamed: 1
대여소별 대여내역1.0000.906
Unnamed: 10.9061.000

Missing values

2024-03-13T18:54:41.347497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T18:54:41.436203image/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.
2024-03-13T18:54:41.539819image/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/월202202 ~ 202202
2조회구분대여소별대여소<NA>
3총 2594건<NA><NA><NA>
4대여소 그룹팀명대여소 명대여 건수
5서초구이수1팀4314. 탑성마을 버스정거장 옆2
6서초구이수1팀4322.서울추모공원 입구2
7동작구영남2팀2063. 대방역 4번출구3
8서초구이수1팀2288. 안골마을입구6
9성동구테스트9980. 에이텍7
대여소별 대여내역Unnamed: 1Unnamed: 2Unnamed: 3
2589영등포구영남1팀230. 영등포구청역 1번출구2871
2590관악구영남2팀2177. 신대방역 2번 출구2907
2591양천구영남1팀770.목동역5번출구 교통정보센터 앞2912
2592관악구영남2팀2102. 봉림교 교통섬2966
2593강서구개화1팀1153. 발산역 1번, 9번 인근 대여소2968
2594송파구천호2팀1210. 롯데월드타워(잠실역2번출구 쪽)3382
2595광진구중랑1팀502. 뚝섬유원지역 1번출구 앞3402
2596영등포구영남3팀207. 여의나루역 1번출구 앞3638
2597강서구개화1팀2701. 마곡나루역 5번출구 뒤편4123
2598강서구개화1팀2715.마곡나루역 2번 출구4924