![weecology](/img/default-banner.jpg)
- Видео 166
- Просмотров 571 805
weecology
Добавлен 30 июн 2012
We are an interdisciplinary ecology and environmental data science research group at the University of Florida consisting of Morgan Ernest’s lab, which studies how ecological systems change through time and has a strong field work focus, and Ethan White’s lab which uses computational and statistical methods to understand ecological systems using large ecological and environmental datasets. We do cutting edge research, collect and publish large open datasets, develop open source software, build websites, train scientists in computational tools, and generally try to make science a better, more efficient, more diverse and inclusive place. Our channel focuses on helping train researchers in the kinds of computational tools we use every day.
Monitoring Ecosystems at Scale Using Airborne Remote Sensing & Computer Vision
An overview of our work monitoring birds and trees at large scales using airborne remote sensing and computer vision. Includes discussion the need to move our focus beyond models to more complete cyberinfrastructure and the tools we use for this.
Imageomics Institute (imageomics.osu.edu/) seminar. Presented February 27, 2023.
Imageomics Institute (imageomics.osu.edu/) seminar. Presented February 27, 2023.
Просмотров: 253
Видео
Monitoring Wading Birds at Scale Using Drones & Artificial Intelligence
Просмотров 242Год назад
Monitoring ecological systems at the large scales required for management and restoration is challenging. We present ongoing research developing systems for large scale monitoring of wading birds in the Everglades using drones, computer vision algorithms, and high performance computing. These methods allow for weekly monitoring of numerous large wading bird colonies and transfer well to other s...
SQL Databases For dplyr Users: Grouping And Summarizing Data Using GROUP BY
Просмотров 1,6 тыс.3 года назад
SQL Databases For dplyr Users: Grouping And Summarizing Data Using GROUP BY
Working With SQL Databases From R: Copying Data From R To A Database
Просмотров 3 тыс.3 года назад
Working With SQL Databases From R: Copying Data From R To A Database
Working With SQL Databases From R: Querying SQL Databases Using dplyr
Просмотров 4,2 тыс.3 года назад
Working With SQL Databases From R: Querying SQL Databases Using dplyr
Working With SQL Databases From R: Running SQL Database Queries From R
Просмотров 9 тыс.3 года назад
Working With SQL Databases From R: Running SQL Database Queries From R
Working With SQL Databases From R: Introduction & Connecting To Databases
Просмотров 37 тыс.3 года назад
The portal.sqlite file can be downloaded here: ndownloader.figshare.com/files/11188550 Notes on how to create a file like this from CSV files are available here: datacarpentry.org/semester-biology/materials/databases-intro-sql/
SQL Databases For dplyr Users: Combining Tables Using JOIN
Просмотров 7553 года назад
SQL Databases For dplyr Users: Combining Tables Using JOIN
SQL Databases For dplyr Users: Order Of SQL Keywords
Просмотров 4783 года назад
SQL Databases For dplyr Users: Order Of SQL Keywords
SQL Databases For dplyr Users: Sorting Using ORDER BY
Просмотров 4853 года назад
SQL Databases For dplyr Users: Sorting Using ORDER BY
SQL Databases For dplyr Users: Filtering Data Using WHERE
Просмотров 6963 года назад
SQL Databases For dplyr Users: Filtering Data Using WHERE
SQL Databases For dplyr Users: Selecting Columns Using SELECT
Просмотров 1,3 тыс.3 года назад
SQL Databases For dplyr Users: Selecting Columns Using SELECT
SQL Databases For dplyr Users: Introduction
Просмотров 3,1 тыс.3 года назад
SQL Databases For dplyr Users: Introduction
Cleaning Data With tidyr: Gappy And Incomplete Data
Просмотров 5143 года назад
Cleaning Data With tidyr: Gappy And Incomplete Data
Cleaning Data Using tidyr: Making Long Data Wide
Просмотров 3903 года назад
Cleaning Data Using tidyr: Making Long Data Wide
Cleaning Data Using tidyr: Combining Data From Multiple Columns
Просмотров 5853 года назад
Cleaning Data Using tidyr: Combining Data From Multiple Columns
Cleaning Data Using tidyr: Separating Data From Within A Column
Просмотров 6343 года назад
Cleaning Data Using tidyr: Separating Data From Within A Column
Cleaning Data Using tidyr: Extracting Data From Within Columns
Просмотров 7683 года назад
Cleaning Data Using tidyr: Extracting Data From Within Columns
Cleaning Data Using tidyr: Pivoting Wide Data to be Longer
Просмотров 9263 года назад
Cleaning Data Using tidyr: Pivoting Wide Data to be Longer
Cleaning Data Using tidyr: Introduction
Просмотров 2,2 тыс.3 года назад
Cleaning Data Using tidyr: Introduction
Introduction to Repeating Things in R: Looping Over Files
Просмотров 15 тыс.3 года назад
Introduction to Repeating Things in R: Looping Over Files
Introduction to Repeating Things in R: Looping Using Functions
Просмотров 3,1 тыс.3 года назад
Introduction to Repeating Things in R: Looping Using Functions
Introduction to Repeating Things in R: Looping Over Multiple Objects
Просмотров 1,2 тыс.3 года назад
Introduction to Repeating Things in R: Looping Over Multiple Objects
Introduction to Repeating Things in R: Looping by Index
Просмотров 2,6 тыс.3 года назад
Introduction to Repeating Things in R: Looping by Index
Introduction to Repeating Things in R: Basic For Loops
Просмотров 1,4 тыс.3 года назад
Introduction to Repeating Things in R: Basic For Loops
Introduction to Repeating Things in R: Combining Your Own Functions With dplyr
Просмотров 1,4 тыс.3 года назад
Introduction to Repeating Things in R: Combining Your Own Functions With dplyr
Introduction to Repeating Things in R: Using mapply For Functions with Multiple Vector Arguments
Просмотров 1,3 тыс.3 года назад
Introduction to Repeating Things in R: Using mapply For Functions with Multiple Vector Arguments
Introduction to Repeating Things in R: Apply Functions
Просмотров 1,1 тыс.3 года назад
Introduction to Repeating Things in R: Apply Functions
Introduction to Repeating Things in R: Using Vectorized Functions
Просмотров 2,3 тыс.3 года назад
Introduction to Repeating Things in R: Using Vectorized Functions
the table is not loading for me and giving me this error "/grid_resource/gridviewer.html?env=&obj=countries&cache_key=26044B56&max_display_columns=50 not found" .. any way to fix this?
I've never seen this type of error before. I'd probably try (re)installing the most recent version of RStudio to see if that fixes it.
Very nice video. very informative and useful
Nice. Any chance of getting a lecture on the use of arrow and duckdb?
goat in my books🐐
Old but still relevant
Please do a video on satellite images using random forest algorithm on R
Sir, I have analysed 800 soil samples for different forms of soil acidity in North East of India which is very remote from mainland India. I don't have any facility to prepare soil acidity map of my analysed data. Could you please help me to learn map making by using R studio ?
Thank you for this great series of carefully taught videos!
You're welcome!
Can you also do this with temperature data too? Is the process the same way?
Yes, everything would work the same way for temperature data
Nice editor 😊
Great thanks!❤❤❤❤! Really it is interesting! Please your email.❤
Awesome❤❤❤❤❤!
Thanks for a wonderful & very informative tutor you shared. Every body can learn from it and others videos you posted. Would you please share your email as I need for your assistance?❤❤❤❤
very good video, i started with R and find your video is the most simple, and good example, easy to understand
Thanks! I’m really glad it’s helpful
Ugh, awesooooome, I want to leaarn use this
am looking at the data which i want to see the children how have never gotten every vaccination and i on want to select the row with variable "no" in 26 columns how can i go about it
If the columns are all next to one another you can use something like: filter(dataframe, across(10:36, ~ . == "no")) Where 10 is the column number of the first column in the block and 36 is the number of the last column in the block. If they aren't all grouped together you can still use across, but you have to name the columns: df_filtered <- df %>% filter(across(c(col1, col2, col3, col4, ... col26), ~ . == "no"))
Thank you for teaching us by explaining the concept in easy way.
You’re welcome!
Thanks! how can we get the dataset?
You’re welcome! This should be the link to the dataset course.naturecast.org/data/portal_timeseries.csv
There is no stars package available in Rstudio. My version is 4.3.3
Did you install the package? If not then run install.packages('stars') and you should be ready to go
My databases are in a .sqlite3 'SQLiteStudio Document' format, would this be a problem/different process? These are great videos, thanks!
You're welcome! I think it should still work, but I don't have any direct experience with that particular case.
Clear! Great!
Thanks!
Whenever I try to change line after using braces to write function body I can't seem to do it I can't seem to separate those braces can anyone help me with this
Is this in RStudio?
IM GOIGN TO SLIDE MY SELF OVER LOL IT ACTUALLY GAV ESUCH PAIN IN THE MUST PRECUS LOL THANKS FOR THE VIDEO YOU ARE AWESOME
You're welcome! Very glad you're enjoying them!
Thank you so much really appreciate you ! Hope there's more coming I am a student eager to learn :)
Thank you so much. I wonder if there a way to plot ROC curve with ggplot.
You're welcome! It is possible to do this in ggplot, but you have to extract the information from dismo instead of doing it automatically. It should look something like this: # Extract the true positive rate (TPR) and false positive rate (FPR) tpr <- evaluation@TPR fpr <- evaluation@FPR # Combine them into a data frame roc_df <- data.frame(FPR = fpr, TPR = tpr) # Use ggplot in the usual way ggplot(roc_df, aes(x = FPR, y = TPR)) + geom_line() + geom_abline(slope = 1, intercept = 0)
Amazing video, thanks a lot I'd been looking for good sources that take into account alternatives to absolute paths and that clearly show examples of how to setup and use Rprojects.
Thanks! So glad it was helpful!
can i have the source code please ?
Source code for this lesson is available in the text version of the tutorial here: course.naturecast.org/lessons/r-intro-to-forecasting/r_tutorial/, but note that it's been updated to use the newer fable package. The text version of this tutorial is available in our GitHub history here: github.com/weecology/forecasting-course/blob/2e7be6bc4f0aeb265ab55836cdf535f4a863d6c9/content/lessons/R-intro-to-forecasting/r_tutorial.md In general you can find text versions of all tutorials at course.naturecast.org/
@@weecology thanks for the immediate response !
@@user-lu5vf6lb4c you're welcome!
It's really helpful. Thanks a lot 🙏
Glad it was helpful!
Excellent explanation!
Thanks!
Fantastic presentation! Thank you! Loved the outtakes 🤣
Glad you enjoyed it!
Thank you so much for simplifying everything!
You’re welcome!
if we want to use for loop meeting conditions of both the rows and columns. how do we do it?
Thanks a lot! These videos are so clear! Feel so lucky to watch them. Best wishes!!
You are welcome!
Thank you boss.....
Great video, I have been suggesting this to some of my students to get into SDM using GLMs :)
Thanks! That’s great to hear!
Thanks a million sir, for your value adding contents and tutorials especially the ones on using functions and for loops in R... They are really helpful and great.
You’re welcome!
Are the in sample predictions at each time point the fitted values? Or how do I get the in sample predictions
The link to dowload the data file used in this video seems to not be working
Thanks for tthis lecture, i kindly want to ask, is there are larger part of this dataset, i want to explore more approaches from all your lecture series..... i mean like, where cam i get the original dataset
You’re welcome! The full dataset is available here: zenodo.org/doi/10.5281/zenodo.1215988 There is a R package designed to make it easy to download and get the pieces of the data you want in useful formats as well: weecology.github.io/portalr/ Let us know if there is anything else we can do to help as you explore the data. You are welcome to email us at portal@weecology.org
Please show me how to create a temp table that starts with #DropTableIfExists
How can I create a data frame on each "i" itereation. For instance if I want to remove same column on each data frame, named data 01, data02, data03, etc etc. Or maybe for this task i-loop is not the best option?, Tank you in advande!
Thank you so much. I learned a lot from the geospatial data series
You're welcome! I'm really glad it was helpful
Are the excel files available for us to follow along ?
Yes, you can find the associated data files here: course.naturecast.org/lessons/r-time-series-data/material/. I'll add them to the Description in a minute.
Hi @weecology thankyou for your excellent explanation of time series this save me for my defense. btw how can i put dygraph for that.
You're welcome! Glad it helped! I don't work with the dygraph package frequently, but here's the basic idea based on my understanding. dygraph takes a group of time-series as input. In this case if you want to plot the predictions (like shown in the Predicted Lunch Deaths example on rstudio.github.io/dygraphs/) then we just need to get them in the right format. To make this simpler let's work with a version of the seasonal Arima that only has 1 set of prediction intervals: # rerun the forecast with just a single prediction internal seasonal_arima_forecast = seasonal_arima_model, h = 36, level = 80) # store the data as a group of time-series forecasts_for_dygraph = cbind(lower = seasonal_arima_forecast$lower, mean = seaonal_arima_forecast$mean, upper = seasonal_arima_forecast$upper) # make a dygraph following the instructions in the example dygraph(forecasts_for_dygraph) %>% dySeries(c("lower", "mean", "upper") Hope that helps!
Thanks my guy
You’re welcome
Getting character(0) when I show tables. Do you know how to fix this? :/
If this is happening when using dbListTables this probably means you didn’t connect to our database file and so R created an empty one. Check that you’ve downloaded the file linked in the description, that it is in your working directory, and that the name when you run dbConnect() matches the file name exactly (including the file extension)
Hello thank you for your help. The tables are now showing, but now I have a new error. When I reference a table it says object not found. Do you know why this is happening? The tables were working fine at first but I had to close and reopen R and that is when the problem arose.@@weecology
@stephensaucedo2746 since you restarted R you’ll need to rerun all of the code to recreate the connection to the database
watch 2024.1.18
watch 2024.1.18
this was helpful thank you
You're welcome!
Creating SQL Database connection using connection panel in RStudio?