Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory410.2 KiB
Average record size in memory42.0 B

Variable types

Categorical1
Text1
Numeric2

Dataset

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

Reproduction

Analysis started2024-05-03 23:57:07.834000
Analysis finished2024-05-03 23:57:10.524238
Duration2.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여소 그룹
Categorical

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
송파구
 
632
강서구
 
621
서초구
 
587
강남구
 
556
마포구
 
512
Other values (22)
7092 

Length

Max length6
Median length3
Mean length3.0926
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row마포구
2nd row송파구
3rd row구로구
4th row강남구
5th row광진구

Common Values

ValueCountFrequency (%)
송파구 632
 
6.3%
강서구 621
 
6.2%
서초구 587
 
5.9%
강남구 556
 
5.6%
마포구 512
 
5.1%
영등포구 504
 
5.0%
종로구 449
 
4.5%
구로구 434
 
4.3%
강동구 408
 
4.1%
노원구 396
 
4.0%
Other values (17) 4901
49.0%

Length

2024-05-03T23:57:10.802161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송파구 632
 
6.3%
강서구 621
 
6.2%
서초구 587
 
5.9%
강남구 556
 
5.6%
마포구 512
 
5.1%
영등포구 504
 
5.0%
종로구 449
 
4.5%
구로구 434
 
4.3%
강동구 408
 
4.1%
노원구 396
 
4.0%
Other values (18) 4908
49.0%

대여소 명
Text

Distinct2198
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-03T23:57:11.575198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length15.3392
Min length3

Characters and Unicode

Total characters153392
Distinct characters563
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)0.9%

Sample

1st row425. DMC첨단산업센터
2nd row1253. 오금역 3번 출구 뒤
3rd row1941. 오류동역 2번출구
4th row2429.압구정로데오역 6번출구
5th row593.자양중앙나들목
ValueCountFrequency (%)
앞 2624
 
9.1%
옆 452
 
1.6%
출구 396
 
1.4%
입구 282
 
1.0%
1번출구 258
 
0.9%
사거리 223
 
0.8%
교차로 213
 
0.7%
2번출구 211
 
0.7%
뒤 210
 
0.7%
3번출구 193
 
0.7%
Other values (4307) 23705
82.4%
2024-05-03T23:57:12.580720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18767
 
12.2%
. 10002
 
6.5%
1 8220
 
5.4%
2 6724
 
4.4%
3 4734
 
3.1%
4 3581
 
2.3%
5 3539
 
2.3%
0 3447
 
2.2%
구 3204
 
2.1%
앞 3178
 
2.1%
Other values (553) 87996
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79584
51.9%
Decimal Number 41319
26.9%
Space Separator 18767
 
12.2%
Other Punctuation 10093
 
6.6%
Uppercase Letter 1492
 
1.0%
Close Punctuation 949
 
0.6%
Open Punctuation 949
 
0.6%
Lowercase Letter 146
 
0.1%
Dash Punctuation 60
 
< 0.1%
Math Symbol 24
 
< 0.1%
Other values (2) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3204
 
4.0%
앞 3178
 
4.0%
역 2342
 
2.9%
동 2107
 
2.6%
번 2064
 
2.6%
출 2033
 
2.6%
교 1647
 
2.1%
리 1341
 
1.7%
파 1328
 
1.7%
아 1247
 
1.6%
Other values (495) 59093
74.3%
Uppercase Letter
ValueCountFrequency (%)
K 161
10.8%
C 145
 
9.7%
S 144
 
9.7%
T 137
 
9.2%
A 116
 
7.8%
L 93
 
6.2%
G 88
 
5.9%
P 85
 
5.7%
M 81
 
5.4%
D 79
 
5.3%
Other values (14) 363
24.3%
Lowercase Letter
ValueCountFrequency (%)
e 50
34.2%
k 19
 
13.0%
s 14
 
9.6%
n 14
 
9.6%
l 12
 
8.2%
t 10
 
6.8%
y 7
 
4.8%
v 5
 
3.4%
m 5
 
3.4%
c 5
 
3.4%
Decimal Number
ValueCountFrequency (%)
1 8220
19.9%
2 6724
16.3%
3 4734
11.5%
4 3581
8.7%
5 3539
8.6%
0 3447
8.3%
6 3107
 
7.5%
7 2930
 
7.1%
8 2522
 
6.1%
9 2515
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 10002
99.1%
, 55
 
0.5%
& 17
 
0.2%
? 14
 
0.1%
· 5
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 19
79.2%
+ 5
 
20.8%
Space Separator
ValueCountFrequency (%)
18767
100.0%
Close Punctuation
ValueCountFrequency (%)
) 949
100.0%
Open Punctuation
ValueCountFrequency (%)
( 949
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79589
51.9%
Common 72165
47.0%
Latin 1638
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3204
 
4.0%
앞 3178
 
4.0%
역 2342
 
2.9%
동 2107
 
2.6%
번 2064
 
2.6%
출 2033
 
2.6%
교 1647
 
2.1%
리 1341
 
1.7%
파 1328
 
1.7%
아 1247
 
1.6%
Other values (496) 59098
74.3%
Latin
ValueCountFrequency (%)
K 161
 
9.8%
C 145
 
8.9%
S 144
 
8.8%
T 137
 
8.4%
A 116
 
7.1%
L 93
 
5.7%
G 88
 
5.4%
P 85
 
5.2%
M 81
 
4.9%
D 79
 
4.8%
Other values (25) 509
31.1%
Common
ValueCountFrequency (%)
18767
26.0%
. 10002
13.9%
1 8220
11.4%
2 6724
 
9.3%
3 4734
 
6.6%
4 3581
 
5.0%
5 3539
 
4.9%
0 3447
 
4.8%
6 3107
 
4.3%
7 2930
 
4.1%
Other values (12) 7114
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79584
51.9%
ASCII 73798
48.1%
None 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18767
25.4%
. 10002
13.6%
1 8220
11.1%
2 6724
 
9.1%
3 4734
 
6.4%
4 3581
 
4.9%
5 3539
 
4.8%
0 3447
 
4.7%
6 3107
 
4.2%
7 2930
 
4.0%
Other values (46) 8747
11.9%
Hangul
ValueCountFrequency (%)
구 3204
 
4.0%
앞 3178
 
4.0%
역 2342
 
2.9%
동 2107
 
2.6%
번 2064
 
2.6%
출 2033
 
2.6%
교 1647
 
2.1%
리 1341
 
1.7%
파 1328
 
1.7%
아 1247
 
1.6%
Other values (495) 59093
74.3%
None
ValueCountFrequency (%)
㈜ 5
50.0%
· 5
50.0%

대여 일자 / 월
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean202022.72
Minimum202007
Maximum202101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T23:57:12.956634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202007
5-th percentile202007
Q1202008
median202010
Q3202012
95-th percentile202101
Maximum202101
Range94
Interquartile range (IQR)4

Descriptive statistics

Standard deviation32.19762
Coefficient of variation (CV)0.00015937623
Kurtosis2.073721
Mean202022.72
Median Absolute Deviation (MAD)2
Skewness2.0134654
Sum2.0202272 × 109
Variance1036.6867
MonotonicityNot monotonic
2024-05-03T23:57:13.306127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
202010 1470
14.7%
202101 1444
14.4%
202009 1440
14.4%
202011 1430
14.3%
202012 1421
14.2%
202007 1416
14.2%
202008 1379
13.8%
ValueCountFrequency (%)
202007 1416
14.2%
202008 1379
13.8%
202009 1440
14.4%
202010 1470
14.7%
202011 1430
14.3%
202012 1421
14.2%
202101 1444
14.4%
ValueCountFrequency (%)
202101 1444
14.4%
202012 1421
14.2%
202011 1430
14.3%
202010 1470
14.7%
202009 1440
14.4%
202008 1379
13.8%
202007 1416
14.2%

대여 건수
Real number (ℝ)

Distinct2683
Distinct (%)26.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean952.1149
Minimum0
Maximum15613
Zeros14
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T23:57:13.677102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile94
Q1333
median676
Q31254
95-th percentile2689
Maximum15613
Range15613
Interquartile range (IQR)921

Descriptive statistics

Standard deviation958.90862
Coefficient of variation (CV)1.0071354
Kurtosis24.202679
Mean952.1149
Median Absolute Deviation (MAD)407.5
Skewness3.2937815
Sum9521149
Variance919505.75
MonotonicityNot monotonic
2024-05-03T23:57:14.138315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 21
 
0.2%
263 17
 
0.2%
367 16
 
0.2%
323 16
 
0.2%
189 16
 
0.2%
255 15
 
0.1%
222 15
 
0.1%
495 15
 
0.1%
370 15
 
0.1%
109 15
 
0.1%
Other values (2673) 9839
98.4%
ValueCountFrequency (%)
0 14
0.1%
1 21
0.2%
2 10
0.1%
3 2
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 6
 
0.1%
7 6
 
0.1%
8 3
 
< 0.1%
9 7
 
0.1%
ValueCountFrequency (%)
15613 1
< 0.1%
15447 1
< 0.1%
14779 1
< 0.1%
11167 1
< 0.1%
10418 1
< 0.1%
9909 1
< 0.1%
8384 1
< 0.1%
7908 1
< 0.1%
7807 1
< 0.1%
7741 1
< 0.1%

Interactions

2024-05-03T23:57:09.372458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:57:08.807059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:57:09.656008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:57:09.071012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T23:57:15.205347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소 그룹대여 일자 / 월대여 건수
대여소 그룹1.0000.0000.255
대여 일자 / 월0.0001.0000.185
대여 건수0.2550.1851.000
2024-05-03T23:57:15.387894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여 일자 / 월대여 건수대여소 그룹
대여 일자 / 월1.000-0.3280.000
대여 건수-0.3281.0000.088
대여소 그룹0.0000.0881.000

Missing values

2024-05-03T23:57:10.104590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T23:57:10.398723image/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 그룹대여소 명대여 일자 / 월대여 건수
3090마포구425. DMC첨단산업센터202008360
14060송파구1253. 오금역 3번 출구 뒤202101235
6794구로구1941. 오류동역 2번출구2020101949
2192강남구2429.압구정로데오역 6번출구202008443
4682광진구593.자양중앙나들목2020092921
6165중구472.삼일교(시그니쳐 타워)202009687
5868용산구806. 전자랜드 본관 앞2020091018
544구로구1946. 구로역 광장2020072147
4187강남구2328. 르네상스 호텔 사거리 역삼지하보도 7번출구 앞202009441
13643마포구4210. 가좌행복주택 앞202101122
대여소 그룹대여소 명대여 일자 / 월대여 건수
12447중구383. 신당역 12번 출구 뒤2020121101
8168종로구358. 성대입구 사거리2020101369
12808강북구1547. 꿈의숲 롯데캐슬202101126
12365종로구3421.혜화역 1번출구202012721
3611양천구731. 서울시 도로환경관리센터2020081434
11485마포구439. 마포어린이공원2020121120
6859금천구1804. 독산역 2번출구 자전거주차장2020101552
5175마포구425. DMC첨단산업센터202009624
351강서구2717.LG유플러스 마곡사옥2020071978
1329성북구1338. 용문2교 옆2020071284