Overview

Dataset statistics

Number of variables4
Number of observations2621
Missing cells5
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory82.0 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 09:54:29.689026
Analysis finished2024-03-13 09:54:30.306346
Duration0.62 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 size20.6 KiB
송파구
210 
강서구
180 
강남구
 
151
영등포구
 
142
서초구
 
141
Other values (25)
1797 

Length

Max length7
Median length3
Mean length3.0847005
Min length2

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row구분
3rd row조회구분
4th row총 2616건
5th row대여소 그룹

Common Values

ValueCountFrequency (%)
송파구 210
 
8.0%
강서구 180
 
6.9%
강남구 151
 
5.8%
영등포구 142
 
5.4%
서초구 141
 
5.4%
노원구 126
 
4.8%
마포구 122
 
4.7%
강동구 117
 
4.5%
양천구 106
 
4.0%
구로구 103
 
3.9%
Other values (20) 1223
46.7%

Length

2024-03-13T18:54:30.370759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송파구 210
 
8.0%
강서구 180
 
6.9%
강남구 151
 
5.8%
영등포구 142
 
5.4%
서초구 141
 
5.4%
노원구 126
 
4.8%
마포구 122
 
4.7%
강동구 117
 
4.5%
양천구 106
 
4.0%
구로구 103
 
3.9%
Other values (22) 1225
46.7%

Unnamed: 1
Categorical

HIGH CORRELATION 

Distinct40
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size20.6 KiB
상암1팀
 
152
학여울2팀
 
126
천호1팀
 
122
천호2팀
 
116
학여울1팀
 
96
Other values (35)
2009 

Length

Max length6
Median length4
Mean length4.2682182
Min length1

Unique

Unique4 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
상암1팀 152
 
5.8%
학여울2팀 126
 
4.8%
천호1팀 122
 
4.7%
천호2팀 116
 
4.4%
학여울1팀 96
 
3.7%
중랑3팀 94
 
3.6%
영남3팀 88
 
3.4%
중랑2팀 87
 
3.3%
이수3팀 85
 
3.2%
중랑1팀 85
 
3.2%
Other values (30) 1570
59.9%

Length

2024-03-13T18:54:30.475012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
상암1팀 152
 
5.7%
학여울2팀 126
 
4.7%
천호1팀 122
 
4.6%
천호2팀 116
 
4.3%
학여울1팀 96
 
3.6%
중랑3팀 94
 
3.5%
영남3팀 88
 
3.3%
중랑2팀 87
 
3.3%
이수3팀 85
 
3.2%
중랑1팀 85
 
3.2%
Other values (31) 1621
60.7%

Unnamed: 2
Text

Distinct2619
Distinct (%)100.0%
Missing2
Missing (%)0.1%
Memory size20.6 KiB
2024-03-13T18:54:30.751032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.572356
Min length3

Characters and Unicode

Total characters40784
Distinct characters592
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

Unique2619 ?
Unique (%)100.0%

Sample

1st row일/월
2nd row대여소
3rd row대여소 명
4th row943. 은평구청 보건소
5th row2391. 구룡터널 입구(개포1단지아파트)
ValueCountFrequency (%)
앞 688
 
9.0%
출구 104
 
1.4%
옆 99
 
1.3%
입구 70
 
0.9%
교차로 62
 
0.8%
1번출구 61
 
0.8%
사거리 58
 
0.8%
2번출구 48
 
0.6%
3번출구 44
 
0.6%
뒤 43
 
0.6%
Other values (5224) 6343
83.2%
2024-03-13T18:54:31.187195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5001
 
12.3%
. 2626
 
6.4%
1 1972
 
4.8%
2 1603
 
3.9%
3 1315
 
3.2%
4 1285
 
3.2%
5 965
 
2.4%
0 935
 
2.3%
6 900
 
2.2%
7 818
 
2.0%
Other values (582) 23364
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21066
51.7%
Decimal Number 11196
27.5%
Space Separator 5001
 
12.3%
Other Punctuation 2660
 
6.5%
Uppercase Letter 338
 
0.8%
Close Punctuation 225
 
0.6%
Open Punctuation 225
 
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 815
 
3.9%
구 795
 
3.8%
역 582
 
2.8%
동 581
 
2.8%
번 505
 
2.4%
출 492
 
2.3%
교 438
 
2.1%
파 385
 
1.8%
아 373
 
1.8%
리 351
 
1.7%
Other values (517) 15749
74.8%
Uppercase Letter
ValueCountFrequency (%)
K 41
12.1%
S 40
11.8%
T 33
9.8%
C 31
 
9.2%
A 23
 
6.8%
D 21
 
6.2%
G 20
 
5.9%
M 17
 
5.0%
B 17
 
5.0%
P 17
 
5.0%
Other values (13) 78
23.1%
Lowercase Letter
ValueCountFrequency (%)
e 15
32.6%
k 7
15.2%
s 7
15.2%
t 3
 
6.5%
l 2
 
4.3%
n 2
 
4.3%
y 1
 
2.2%
v 1
 
2.2%
r 1
 
2.2%
h 1
 
2.2%
Other values (6) 6
 
13.0%
Decimal Number
ValueCountFrequency (%)
1 1972
17.6%
2 1603
14.3%
3 1315
11.7%
4 1285
11.5%
5 965
8.6%
0 935
8.4%
6 900
8.0%
7 818
7.3%
8 760
 
6.8%
9 643
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 2626
98.7%
, 18
 
0.7%
& 8
 
0.3%
· 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 (%)
5001
100.0%
Close Punctuation
ValueCountFrequency (%)
) 225
100.0%
Open Punctuation
ValueCountFrequency (%)
( 225
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 21067
51.7%
Common 19333
47.4%
Latin 384
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 815
 
3.9%
구 795
 
3.8%
역 582
 
2.8%
동 581
 
2.8%
번 505
 
2.4%
출 492
 
2.3%
교 438
 
2.1%
파 385
 
1.8%
아 373
 
1.8%
리 351
 
1.7%
Other values (518) 15750
74.8%
Latin
ValueCountFrequency (%)
K 41
 
10.7%
S 40
 
10.4%
T 33
 
8.6%
C 31
 
8.1%
A 23
 
6.0%
D 21
 
5.5%
G 20
 
5.2%
M 17
 
4.4%
B 17
 
4.4%
P 17
 
4.4%
Other values (29) 124
32.3%
Common
ValueCountFrequency (%)
5001
25.9%
. 2626
13.6%
1 1972
 
10.2%
2 1603
 
8.3%
3 1315
 
6.8%
4 1285
 
6.6%
5 965
 
5.0%
0 935
 
4.8%
6 900
 
4.7%
7 818
 
4.2%
Other values (15) 1913
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21066
51.7%
ASCII 19711
48.3%
None 5
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5001
25.4%
. 2626
13.3%
1 1972
 
10.0%
2 1603
 
8.1%
3 1315
 
6.7%
4 1285
 
6.5%
5 965
 
4.9%
0 935
 
4.7%
6 900
 
4.6%
7 818
 
4.1%
Other values (51) 2291
11.6%
Hangul
ValueCountFrequency (%)
앞 815
 
3.9%
구 795
 
3.8%
역 582
 
2.8%
동 581
 
2.8%
번 505
 
2.4%
출 492
 
2.3%
교 438
 
2.1%
파 385
 
1.8%
아 373
 
1.8%
리 351
 
1.7%
Other values (517) 15749
74.8%
None
ValueCountFrequency (%)
· 4
80.0%
㈜ 1
 
20.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%

Unnamed: 3
Text

Distinct1908
Distinct (%)72.9%
Missing3
Missing (%)0.1%
Memory size20.6 KiB
2024-03-13T18:54:31.495231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length4
Mean length3.6669213
Min length1

Characters and Unicode

Total characters9600
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

Unique1355 ?
Unique (%)51.8%

Sample

1st row202205 ~ 202205
2nd row대여 건수
3rd row0
4th row9
5th row14
ValueCountFrequency (%)
792 5
 
0.2%
1593 5
 
0.2%
1372 4
 
0.2%
1297 4
 
0.2%
1059 4
 
0.2%
410 4
 
0.2%
915 4
 
0.2%
798 4
 
0.2%
1170 4
 
0.2%
1171 4
 
0.2%
Other values (1900) 2579
98.4%
2024-03-13T18:54:31.953537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1649
17.2%
2 1191
12.4%
3 1070
11.1%
4 880
9.2%
5 859
8.9%
6 826
8.6%
7 823
8.6%
9 774
8.1%
8 765
8.0%
0 755
7.9%
Other values (6) 8
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9592
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 1649
17.2%
2 1191
12.4%
3 1070
11.2%
4 880
9.2%
5 859
9.0%
6 826
8.6%
7 823
8.6%
9 774
8.1%
8 765
8.0%
0 755
7.9%
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 9596
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1649
17.2%
2 1191
12.4%
3 1070
11.2%
4 880
9.2%
5 859
9.0%
6 826
8.6%
7 823
8.6%
9 774
8.1%
8 765
8.0%
0 755
7.9%
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 9596
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1649
17.2%
2 1191
12.4%
3 1070
11.2%
4 880
9.2%
5 859
9.0%
6 826
8.6%
7 823
8.6%
9 774
8.1%
8 765
8.0%
0 755
7.9%
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

2024-03-13T18:54:32.042564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소별 대여내역Unnamed: 1
대여소별 대여내역1.0000.996
Unnamed: 10.9961.000
2024-03-13T18:54:32.127399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소별 대여내역Unnamed: 1
대여소별 대여내역1.0000.905
Unnamed: 10.9051.000
2024-03-13T18:54:32.207524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소별 대여내역Unnamed: 1
대여소별 대여내역1.0000.905
Unnamed: 10.9051.000

Missing values

2024-03-13T18:54:30.087820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T18:54:30.165978image/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.
2024-03-13T18:54:30.250248image/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/월202205 ~ 202205
2조회구분대여소별대여소<NA>
3총 2616건<NA><NA><NA>
4대여소 그룹팀명대여소 명대여 건수
5은평구상암2팀943. 은평구청 보건소0
6강남구학여울1팀2391. 구룡터널 입구(개포1단지아파트)9
7성동구테스트9980. 에이텍14
8서초구이수1팀4314. 탑성마을 버스정거장 옆32
9성동구중랑2팀3527. 왕십리 자이아파트39
대여소별 대여내역Unnamed: 1Unnamed: 2Unnamed: 3
2611송파구천호2팀2622. 올림픽공원역 3번출구11440
2612영등포구영남3팀210. IFC몰11576
2613구로구천왕2팀1911. 구로디지털단지역 앞11772
2614관악구영남2팀2177. 신대방역 2번 출구11991
2615송파구천호2팀1210. 롯데월드타워(잠실역2번출구 쪽)14669
2616관악구영남2팀2102. 봉림교 교통섬14878
2617강서구개화1팀2715.마곡나루역 2번 출구17929
2618마포구상암1팀4217. 한강공원 망원나들목21051
2619영등포구영남3팀207. 여의나루역 1번출구 앞21533
2620광진구중랑1팀502. 뚝섬유원지역 1번출구 앞22589