Overview

Dataset statistics

Number of variables5
Number of observations8038
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory345.5 KiB
Average record size in memory44.0 B

Variable types

Numeric4
Text1

Dataset

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

Alerts

대여건수 is highly overall correlated with 반납건수High correlation
반납건수 is highly overall correlated with 대여건수High correlation

Reproduction

Analysis started2024-03-13 09:53:53.334854
Analysis finished2024-03-13 09:53:55.821807
Duration2.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여일자
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201808.6
Minimum201806
Maximum201811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.8 KiB
2024-03-13T18:53:55.867145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201806
5-th percentile201806
Q1201807
median201809
Q3201810
95-th percentile201811
Maximum201811
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7206968
Coefficient of variation (CV)8.5263801 × 10-6
Kurtosis-1.2840229
Mean201808.6
Median Absolute Deviation (MAD)1.5
Skewness-0.074226688
Sum1.6221375 × 109
Variance2.9607975
MonotonicityIncreasing
2024-03-13T18:53:55.968821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
201811 1478
18.4%
201810 1421
17.7%
201809 1320
16.4%
201808 1278
15.9%
201807 1274
15.8%
201806 1267
15.8%
ValueCountFrequency (%)
201806 1267
15.8%
201807 1274
15.8%
201808 1278
15.9%
201809 1320
16.4%
201810 1421
17.7%
201811 1478
18.4%
ValueCountFrequency (%)
201811 1478
18.4%
201810 1421
17.7%
201809 1320
16.4%
201808 1278
15.9%
201807 1274
15.8%
201806 1267
15.8%

대여소번호
Real number (ℝ)

Distinct1487
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1243.7759
Minimum101
Maximum3538
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.8 KiB
2024-03-13T18:53:56.088727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile169
Q1551
median1204.5
Q31910
95-th percentile2359
Maximum3538
Range3437
Interquartile range (IQR)1359

Descriptive statistics

Standard deviation790.0451
Coefficient of variation (CV)0.6351989
Kurtosis-0.37382055
Mean1243.7759
Median Absolute Deviation (MAD)661
Skewness0.46210458
Sum9997471
Variance624171.27
MonotonicityNot monotonic
2024-03-13T18:53:56.239378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101 6
 
0.1%
1611 6
 
0.1%
1627 6
 
0.1%
1625 6
 
0.1%
1623 6
 
0.1%
1620 6
 
0.1%
1619 6
 
0.1%
1617 6
 
0.1%
1616 6
 
0.1%
1610 6
 
0.1%
Other values (1477) 7978
99.3%
ValueCountFrequency (%)
101 6
0.1%
102 6
0.1%
103 6
0.1%
104 6
0.1%
105 6
0.1%
106 6
0.1%
107 6
0.1%
108 6
0.1%
109 6
0.1%
110 6
0.1%
ValueCountFrequency (%)
3538 1
< 0.1%
3537 1
< 0.1%
3536 1
< 0.1%
3535 2
< 0.1%
3534 1
< 0.1%
3533 2
< 0.1%
3532 1
< 0.1%
3531 1
< 0.1%
3530 1
< 0.1%
3529 1
< 0.1%

대여소명
Text

Distinct1487
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Memory size62.9 KiB
2024-03-13T18:53:56.531980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length15.343867
Min length8

Characters and Unicode

Total characters123334
Distinct characters517
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)0.8%

Sample

1st row101. (구)합정동 주민센터
2nd row102. 망원역 1번출구 앞
3rd row103. 망원역 2번출구 앞
4th row104. 합정역 1번출구 앞
5th row105. 합정역 5번출구 앞
ValueCountFrequency (%)
앞 2136
 
8.5%
옆 437
 
1.7%
출구 288
 
1.1%
1번출구 276
 
1.1%
사거리 235
 
0.9%
2번출구 217
 
0.9%
뒤 212
 
0.8%
교차로 199
 
0.8%
입구 176
 
0.7%
3번출구 171
 
0.7%
Other values (3268) 20927
82.8%
2024-03-13T18:53:56.909424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17386
 
14.1%
. 8068
 
6.5%
1 7259
 
5.9%
2 5546
 
4.5%
3 3818
 
3.1%
5 2831
 
2.3%
구 2822
 
2.3%
0 2740
 
2.2%
4 2635
 
2.1%
앞 2581
 
2.1%
Other values (507) 67648
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63238
51.3%
Decimal Number 32474
26.3%
Space Separator 17392
 
14.1%
Other Punctuation 8108
 
6.6%
Uppercase Letter 922
 
0.7%
Close Punctuation 514
 
0.4%
Open Punctuation 514
 
0.4%
Lowercase Letter 95
 
0.1%
Dash Punctuation 49
 
< 0.1%
Math Symbol 21
 
< 0.1%
Other values (2) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2822
 
4.5%
앞 2581
 
4.1%
역 2157
 
3.4%
번 1918
 
3.0%
출 1900
 
3.0%
동 1566
 
2.5%
교 1312
 
2.1%
리 1096
 
1.7%
원 1020
 
1.6%
사 935
 
1.5%
Other values (450) 45931
72.6%
Uppercase Letter
ValueCountFrequency (%)
K 125
13.6%
S 108
11.7%
C 104
11.3%
L 67
 
7.3%
G 67
 
7.3%
T 58
 
6.3%
M 54
 
5.9%
A 49
 
5.3%
B 47
 
5.1%
I 38
 
4.1%
Other values (13) 205
22.2%
Decimal Number
ValueCountFrequency (%)
1 7259
22.4%
2 5546
17.1%
3 3818
11.8%
5 2831
 
8.7%
0 2740
 
8.4%
4 2635
 
8.1%
6 2289
 
7.0%
7 1902
 
5.9%
8 1768
 
5.4%
9 1686
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
e 27
28.4%
k 16
16.8%
t 12
12.6%
s 10
 
10.5%
o 8
 
8.4%
l 7
 
7.4%
c 6
 
6.3%
m 6
 
6.3%
n 2
 
2.1%
y 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 8068
99.5%
, 25
 
0.3%
& 7
 
0.1%
@ 6
 
0.1%
․ 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
17386
> 99.9%
  6
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 15
71.4%
+ 6
 
28.6%
Close Punctuation
ValueCountFrequency (%)
) 514
100.0%
Open Punctuation
ValueCountFrequency (%)
( 514
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63239
51.3%
Common 59078
47.9%
Latin 1017
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2822
 
4.5%
앞 2581
 
4.1%
역 2157
 
3.4%
번 1918
 
3.0%
출 1900
 
3.0%
동 1566
 
2.5%
교 1312
 
2.1%
리 1096
 
1.7%
원 1020
 
1.6%
사 935
 
1.5%
Other values (451) 45932
72.6%
Latin
ValueCountFrequency (%)
K 125
12.3%
S 108
 
10.6%
C 104
 
10.2%
L 67
 
6.6%
G 67
 
6.6%
T 58
 
5.7%
M 54
 
5.3%
A 49
 
4.8%
B 47
 
4.6%
I 38
 
3.7%
Other values (23) 300
29.5%
Common
ValueCountFrequency (%)
17386
29.4%
. 8068
13.7%
1 7259
12.3%
2 5546
 
9.4%
3 3818
 
6.5%
5 2831
 
4.8%
0 2740
 
4.6%
4 2635
 
4.5%
6 2289
 
3.9%
7 1902
 
3.2%
Other values (13) 4604
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63238
51.3%
ASCII 60087
48.7%
None 7
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17386
28.9%
. 8068
13.4%
1 7259
12.1%
2 5546
 
9.2%
3 3818
 
6.4%
5 2831
 
4.7%
0 2740
 
4.6%
4 2635
 
4.4%
6 2289
 
3.8%
7 1902
 
3.2%
Other values (44) 5613
 
9.3%
Hangul
ValueCountFrequency (%)
구 2822
 
4.5%
앞 2581
 
4.1%
역 2157
 
3.4%
번 1918
 
3.0%
출 1900
 
3.0%
동 1566
 
2.5%
교 1312
 
2.1%
리 1096
 
1.7%
원 1020
 
1.6%
사 935
 
1.5%
Other values (450) 45931
72.6%
None
ValueCountFrequency (%)
  6
85.7%
㈜ 1
 
14.3%
Punctuation
ValueCountFrequency (%)
․ 2
100.0%

대여건수
Real number (ℝ)

HIGH CORRELATION 

Distinct2197
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean864.06581
Minimum0
Maximum12207
Zeros26
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size70.8 KiB
2024-03-13T18:53:57.043995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile146
Q1394
median693
Q31127
95-th percentile2142.15
Maximum12207
Range12207
Interquartile range (IQR)733

Descriptive statistics

Standard deviation725.97935
Coefficient of variation (CV)0.84018988
Kurtosis24.159816
Mean864.06581
Median Absolute Deviation (MAD)341
Skewness3.2515551
Sum6945361
Variance527046.02
MonotonicityNot monotonic
2024-03-13T18:53:57.204973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 26
 
0.3%
256 19
 
0.2%
434 17
 
0.2%
301 15
 
0.2%
395 15
 
0.2%
240 14
 
0.2%
368 14
 
0.2%
978 13
 
0.2%
396 13
 
0.2%
381 13
 
0.2%
Other values (2187) 7879
98.0%
ValueCountFrequency (%)
0 26
0.3%
1 3
 
< 0.1%
2 6
 
0.1%
3 5
 
0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 3
 
< 0.1%
8 3
 
< 0.1%
9 4
 
< 0.1%
ValueCountFrequency (%)
12207 1
< 0.1%
10958 1
< 0.1%
8707 1
< 0.1%
7523 1
< 0.1%
7508 1
< 0.1%
7438 1
< 0.1%
7089 1
< 0.1%
6680 1
< 0.1%
6610 1
< 0.1%
6539 1
< 0.1%

반납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct2233
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean860.63984
Minimum0
Maximum12332
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size70.8 KiB
2024-03-13T18:53:57.344082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile109
Q1362
median673
Q31140
95-th percentile2198
Maximum12332
Range12332
Interquartile range (IQR)778

Descriptive statistics

Standard deviation770.42808
Coefficient of variation (CV)0.8951806
Kurtosis24.643013
Mean860.63984
Median Absolute Deviation (MAD)363
Skewness3.3222524
Sum6917823
Variance593559.43
MonotonicityNot monotonic
2024-03-13T18:53:57.489087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
223 16
 
0.2%
1 15
 
0.2%
521 14
 
0.2%
832 14
 
0.2%
454 13
 
0.2%
225 13
 
0.2%
740 13
 
0.2%
186 13
 
0.2%
107 12
 
0.1%
480 12
 
0.1%
Other values (2223) 7903
98.3%
ValueCountFrequency (%)
0 4
 
< 0.1%
1 15
0.2%
2 2
 
< 0.1%
3 3
 
< 0.1%
4 6
 
0.1%
5 7
0.1%
6 2
 
< 0.1%
7 2
 
< 0.1%
8 5
 
0.1%
9 4
 
< 0.1%
ValueCountFrequency (%)
12332 1
< 0.1%
12185 1
< 0.1%
8495 1
< 0.1%
8153 1
< 0.1%
7884 1
< 0.1%
7875 1
< 0.1%
7865 1
< 0.1%
7674 1
< 0.1%
7499 1
< 0.1%
7026 1
< 0.1%

Interactions

2024-03-13T18:53:55.067263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:53.840939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:54.244702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:54.679967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:55.154576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:53.938626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:54.345531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:54.773742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:55.242416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:54.068143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:54.473053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:54.881353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:55.332569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:54.157379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:54.580153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T18:53:54.973419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T18:53:57.581820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여일자대여소번호대여건수반납건수
대여일자1.0000.0000.1500.135
대여소번호0.0001.0000.2460.161
대여건수0.1500.2461.0000.939
반납건수0.1350.1610.9391.000
2024-03-13T18:53:57.671168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여일자대여소번호대여건수반납건수
대여일자1.0000.021-0.112-0.107
대여소번호0.0211.000-0.290-0.273
대여건수-0.112-0.2901.0000.973
반납건수-0.107-0.2730.9731.000

Missing values

2024-03-13T18:53:55.699857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T18:53:55.783201image/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

대여일자대여소번호대여소명대여건수반납건수
0201806101101. (구)합정동 주민센터832807
1201806102102. 망원역 1번출구 앞28192568
2201806103103. 망원역 2번출구 앞19771769
3201806104104. 합정역 1번출구 앞16821610
4201806105105. 합정역 5번출구 앞1105925
5201806106106. 합정역 7번출구 앞33843252
6201806107107. 신한은행 서교동금융센터점 앞22472496
7201806108108. 서교동 사거리16371706
8201806109109. 제일빌딩 앞17641718
9201806110110. 사천교843579
대여일자대여소번호대여소명대여건수반납건수
802820181135293529. 어린이대공원정문426314
802920181135303530. 왕십리자이아파트 후문(삼거리)223176
803020181135313531. 논골사거리(금호도서관 입구)12423
803120181135323532. 왕십리KCC스위첸아파트236206
803220181135333533. 건대입구역 사거리(롯데백화점)18301898
803320181135343534. 건대입구역 5번출구 뒤12781277
803420181135353535. 중곡사거리(국민은행)459519
803520181135363536. 중앙농협(자양동)545535
803620181135373537. 아차산 휴먼시아 아파트 옆267204
803720181135383538. 서울숲 IT캐슬11297