Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory664.1 KiB
Average record size in memory68.0 B

Variable types

Text1
Numeric4
DateTime2

Dataset

Description전라남도 여수시 공영자전거 운영 자전거GPS정보(대여 일련번호, 자전거 아이디, 대여위치, 대여일시, 반납위치, 반납일시 등)정보 등을 제공합니다.
Author전라남도 여수시
URLhttps://www.data.go.kr/data/15049726/fileData.do

Alerts

대여 위도 is highly overall correlated with 대여 경도 and 2 other fieldsHigh correlation
대여 경도 is highly overall correlated with 대여 위도 and 2 other fieldsHigh correlation
반납 위도 is highly overall correlated with 대여 위도 and 2 other fieldsHigh correlation
반납 경도 is highly overall correlated with 대여 위도 and 2 other fieldsHigh correlation
대여 위도 is highly skewed (γ1 = 42.43574647)Skewed
반납 위도 is highly skewed (γ1 = -99.37217816)Skewed
반납 경도 is highly skewed (γ1 = -99.7621818)Skewed

Reproduction

Analysis started2023-12-12 02:20:11.603948
Analysis finished2023-12-12 02:20:14.680279
Duration3.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자전거 아이디
Text

Distinct280
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:20:14.954733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters90000
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowYS_000203
2nd rowYS_000217
3rd rowYS_000233
4th rowYS_000054
5th rowYS_000200
ValueCountFrequency (%)
ys_000160 67
 
0.7%
ys_000032 66
 
0.7%
ys_000117 58
 
0.6%
ys_000171 55
 
0.5%
ys_000060 53
 
0.5%
ys_000156 52
 
0.5%
ys_000203 51
 
0.5%
ys_000294 51
 
0.5%
ys_000155 51
 
0.5%
ys_000194 51
 
0.5%
Other values (270) 9445
94.5%
2023-12-12T11:20:15.496299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 35245
39.2%
Y 10000
 
11.1%
S 10000
 
11.1%
_ 10000
 
11.1%
2 5575
 
6.2%
1 5146
 
5.7%
3 2141
 
2.4%
7 2048
 
2.3%
5 2031
 
2.3%
4 2011
 
2.2%
Other values (3) 5803
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60000
66.7%
Uppercase Letter 20000
 
22.2%
Connector Punctuation 10000
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35245
58.7%
2 5575
 
9.3%
1 5146
 
8.6%
3 2141
 
3.6%
7 2048
 
3.4%
5 2031
 
3.4%
4 2011
 
3.4%
6 1980
 
3.3%
8 1931
 
3.2%
9 1892
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
Y 10000
50.0%
S 10000
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70000
77.8%
Latin 20000
 
22.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 35245
50.3%
_ 10000
 
14.3%
2 5575
 
8.0%
1 5146
 
7.4%
3 2141
 
3.1%
7 2048
 
2.9%
5 2031
 
2.9%
4 2011
 
2.9%
6 1980
 
2.8%
8 1931
 
2.8%
Latin
ValueCountFrequency (%)
Y 10000
50.0%
S 10000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 35245
39.2%
Y 10000
 
11.1%
S 10000
 
11.1%
_ 10000
 
11.1%
2 5575
 
6.2%
1 5146
 
5.7%
3 2141
 
2.4%
7 2048
 
2.3%
5 2031
 
2.3%
4 2011
 
2.2%
Other values (3) 5803
 
6.4%

대여 위도
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct4549
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.752679
Minimum34.715065
Maximum36.363464
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:20:15.684113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.715065
5-th percentile34.731023
Q134.742999
median34.746741
Q334.766532
95-th percentile34.776895
Maximum36.363464
Range1.648399
Interquartile range (IQR)0.02353325

Descriptive statistics

Standard deviation0.021452989
Coefficient of variation (CV)0.00061730462
Kurtosis3178.0953
Mean34.752679
Median Absolute Deviation (MAD)0.008073
Skewness42.435746
Sum347526.79
Variance0.00046023074
MonotonicityNot monotonic
2023-12-12T11:20:15.880078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.768302 37
 
0.4%
34.73888 24
 
0.2%
34.745814 17
 
0.2%
34.745811 17
 
0.2%
34.745764 17
 
0.2%
34.72986 17
 
0.2%
34.745785 15
 
0.1%
34.73886 15
 
0.1%
34.74578 14
 
0.1%
34.745808 14
 
0.1%
Other values (4539) 9813
98.1%
ValueCountFrequency (%)
34.715065 1
< 0.1%
34.715067 1
< 0.1%
34.715068 1
< 0.1%
34.715082 1
< 0.1%
34.715099 1
< 0.1%
34.715101 1
< 0.1%
34.715106 1
< 0.1%
34.715109 1
< 0.1%
34.715112 2
< 0.1%
34.715113 1
< 0.1%
ValueCountFrequency (%)
36.363464 1
< 0.1%
34.80178 1
< 0.1%
34.799968 1
< 0.1%
34.799955 2
< 0.1%
34.799952 1
< 0.1%
34.799945 1
< 0.1%
34.799933 1
< 0.1%
34.799928 1
< 0.1%
34.799927 1
< 0.1%
34.79992 2
< 0.1%

대여 경도
Real number (ℝ)

HIGH CORRELATION 

Distinct5016
Distinct (%)50.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.71448
Minimum127.3375
Maximum127.76659
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:20:16.082584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.3375
5-th percentile127.6506
Q1127.66778
median127.72428
Q3127.74925
95-th percentile127.76614
Maximum127.76659
Range0.429089
Interquartile range (IQR)0.08146625

Descriptive statistics

Standard deviation0.040743338
Coefficient of variation (CV)0.00031901894
Kurtosis-0.59789813
Mean127.71448
Median Absolute Deviation (MAD)0.026607
Skewness-0.46010523
Sum1277144.8
Variance0.0016600196
MonotonicityNot monotonic
2023-12-12T11:20:16.247030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.703558 36
 
0.4%
127.724381 17
 
0.2%
127.750839 17
 
0.2%
127.735474 16
 
0.2%
127.656412 13
 
0.1%
127.744652 13
 
0.1%
127.735561 13
 
0.1%
127.750868 12
 
0.1%
127.744714 12
 
0.1%
127.750846 12
 
0.1%
Other values (5006) 9839
98.4%
ValueCountFrequency (%)
127.337499 1
< 0.1%
127.631177 1
< 0.1%
127.631847 1
< 0.1%
127.631848 1
< 0.1%
127.631862 1
< 0.1%
127.631869 1
< 0.1%
127.63187 1
< 0.1%
127.631873 1
< 0.1%
127.631874 1
< 0.1%
127.631879 1
< 0.1%
ValueCountFrequency (%)
127.766588 1
< 0.1%
127.766491 1
< 0.1%
127.766483 1
< 0.1%
127.766377 1
< 0.1%
127.766368 1
< 0.1%
127.766367 1
< 0.1%
127.766361 1
< 0.1%
127.766358 1
< 0.1%
127.766356 1
< 0.1%
127.766355 1
< 0.1%

대여 일시
Date

Distinct9436
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-01-01 02:33:00
Maximum2023-06-30 20:44:00
2023-12-12T11:20:16.401474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:16.560262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

반납 위도
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1400
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.748658
Minimum1.73884
Maximum36.363512
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:20:16.732083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.73884
5-th percentile34.73099
Q134.74293
median34.7467
Q334.763043
95-th percentile34.775751
Maximum36.363512
Range34.624672
Interquartile range (IQR)0.020113

Descriptive statistics

Standard deviation0.33081199
Coefficient of variation (CV)0.0095201371
Kurtosis9917.9678
Mean34.748658
Median Absolute Deviation (MAD)0.00809
Skewness-99.372178
Sum347486.58
Variance0.10943657
MonotonicityNot monotonic
2023-12-12T11:20:16.894666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.73883 111
 
1.1%
34.73882 105
 
1.1%
34.73885 102
 
1.0%
34.743 98
 
1.0%
34.74303 87
 
0.9%
34.73886 87
 
0.9%
34.76833 86
 
0.9%
34.74302 82
 
0.8%
34.76846 71
 
0.7%
34.7683 70
 
0.7%
Other values (1390) 9101
91.0%
ValueCountFrequency (%)
1.73884 1
 
< 0.1%
34.71503 1
 
< 0.1%
34.715063 1
 
< 0.1%
34.71507 4
 
< 0.1%
34.71508 3
 
< 0.1%
34.71509 5
 
0.1%
34.7151 14
0.1%
34.71511 13
0.1%
34.71512 3
 
< 0.1%
34.71513 6
0.1%
ValueCountFrequency (%)
36.363512 1
 
< 0.1%
34.79993 3
< 0.1%
34.79992 3
< 0.1%
34.79991 2
 
< 0.1%
34.7999 2
 
< 0.1%
34.79989 2
 
< 0.1%
34.79988 7
0.1%
34.79987 5
0.1%
34.79986 3
< 0.1%
34.79985 5
0.1%

반납 경도
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1647
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.70394
Minimum27.73542
Maximum127.76705
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:20:17.094018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27.73542
5-th percentile127.65264
Q1127.66764
median127.72594
Q3127.74918
95-th percentile127.76609
Maximum127.76705
Range100.03163
Interquartile range (IQR)0.08154

Descriptive statistics

Standard deviation1.0005789
Coefficient of variation (CV)0.0078351454
Kurtosis9968.2962
Mean127.70394
Median Absolute Deviation (MAD)0.024925
Skewness-99.762182
Sum1277039.4
Variance1.0011582
MonotonicityNot monotonic
2023-12-12T11:20:17.286352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.70351 83
 
0.8%
127.76611 76
 
0.8%
127.76608 68
 
0.7%
127.75082 67
 
0.7%
127.75089 67
 
0.7%
127.75095 66
 
0.7%
127.70348 63
 
0.6%
127.75098 62
 
0.6%
127.70345 61
 
0.6%
127.74474 60
 
0.6%
Other values (1637) 9327
93.3%
ValueCountFrequency (%)
27.73542 1
 
< 0.1%
127.337288 1
 
< 0.1%
127.63188 4
< 0.1%
127.63189 1
 
< 0.1%
127.6319 9
0.1%
127.63191 2
 
< 0.1%
127.63192 3
 
< 0.1%
127.63194 3
 
< 0.1%
127.63195 3
 
< 0.1%
127.63196 2
 
< 0.1%
ValueCountFrequency (%)
127.76705 1
< 0.1%
127.76673 1
< 0.1%
127.76666 1
< 0.1%
127.76651 1
< 0.1%
127.76649 1
< 0.1%
127.76647 1
< 0.1%
127.76646 2
< 0.1%
127.76643 1
< 0.1%
127.76641 1
< 0.1%
127.76639 1
< 0.1%

반납 일시
Date

Distinct9214
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-01-01 02:54:00
Maximum2023-06-30 20:51:00
2023-12-12T11:20:17.508447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:17.697973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T11:20:14.027423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:12.278800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:12.764684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:13.246263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:14.127960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:12.406036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:12.881489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:13.370392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:14.225688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:12.538553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:12.986656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:13.469768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:14.330886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:12.651299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:13.118435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:13.604038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:20:17.836529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여 위도대여 경도반납 위도반납 경도
대여 위도1.0001.0000.0000.000
대여 경도1.0001.0000.0000.000
반납 위도0.0000.0001.0000.707
반납 경도0.0000.0000.7071.000
2023-12-12T11:20:17.950307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여 위도대여 경도반납 위도반납 경도
대여 위도1.000-0.5080.774-0.520
대여 경도-0.5081.000-0.5410.870
반납 위도0.774-0.5411.000-0.519
반납 경도-0.5200.870-0.5191.000

Missing values

2023-12-12T11:20:14.459673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:20:14.614023image/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

자전거 아이디대여 위도대여 경도대여 일시반납 위도반납 경도반납 일시
23325YS_00020334.743069127.7508122023-04-16 11:42:0034.74303127.75082023-04-16 11:48:00
46226YS_00021734.739455127.6495042023-01-21 09:51:0034.74578127.653942023-01-21 10:07:00
8853YS_00023334.766678127.6564682023-06-04 18:29:0034.74673127.673932023-06-04 19:58:00
35583YS_00005434.756727127.6642992023-03-03 14:59:0034.74582127.654012023-03-03 15:18:00
1010YS_00020034.768511127.7035582023-06-24 17:57:0034.76828127.703382023-06-24 17:58:00
43844YS_00020334.763092127.6652542023-02-04 11:49:0034.76345127.665022023-02-04 12:25:00
20997YS_00002934.759717127.667582023-04-26 08:25:0034.75976127.667712023-04-26 08:28:00
36799YS_00025534.743051127.7508262023-02-27 16:25:0034.73882127.735472023-02-27 16:48:00
23526YS_00005534.776994127.6526362023-04-15 17:10:0034.76054127.718732023-04-15 17:53:00
46715YS_00020234.746622127.6738742023-01-17 23:26:0034.74669127.673862023-01-17 23:55:00
자전거 아이디대여 위도대여 경도대여 일시반납 위도반납 경도반납 일시
5178YS_00003634.768393127.6614632023-06-13 11:50:0034.77348127.701712023-06-13 12:22:00
37827YS_00023534.752677127.7490852023-02-25 11:28:0034.75268127.749112023-02-25 11:29:00
6396YS_00009634.73862127.744682023-06-09 23:43:0034.72455127.70942023-06-10 00:55:00
8287YS_00022834.776984127.6525452023-06-05 18:07:0034.77691127.652662023-06-05 19:09:00
18538YS_00015534.738912127.7354862023-05-03 11:58:0034.73885127.735372023-05-03 12:07:00
27255YS_00013334.743009127.7509232023-04-01 18:38:0034.73861127.744642023-04-01 19:01:00
45534YS_00013934.738816127.7356042023-01-26 13:29:0034.73882127.735592023-01-26 14:21:00
35158YS_00028034.730659127.7236912023-03-04 17:49:0034.73108127.717362023-03-04 17:56:00
33997YS_00027034.745802127.653862023-03-08 19:28:0034.76062127.656252023-03-08 19:44:00
12430YS_00006334.768414127.7034812023-05-24 20:01:0034.76832127.703452023-05-24 20:03:00