From 1b902dda5e6fb12e252d13e3ee0b12171a58273d Mon Sep 17 00:00:00 2001 From: tomvannuenen Date: Tue, 17 Oct 2023 10:34:55 -0700 Subject: [PATCH] add R graph and library --- R.html | 27 +-- R_graph.html | 219 ++++++++++++++++++ index.html | 6 + library.html | 549 ++++++++++++++++++++++++++++++++++++++++++++-- other.html | 24 +- python.html | 17 +- python_graph.html | 59 +++-- 7 files changed, 817 insertions(+), 84 deletions(-) create mode 100644 R_graph.html diff --git a/R.html b/R.html index 6f87cf5..f267400 100644 --- a/R.html +++ b/R.html @@ -63,8 +63,8 @@
Click below to see which D-Lab workshop is best for you!
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- + + @@ -114,14 +114,14 @@

R Fundamentals

+ href="https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FR-Fundamentals&urlpath=rstudio%2F&branch=main"> Datahub + href="https://mybinder.org/v2/gh/dlab-berkeley/R-Fundamentals/HEAD?urlpath=rstudio"> Binder @@ -168,7 +168,7 @@

R Data Wrangling and Manipulation

+ href="https://mybinder.org/v2/gh/dlab-berkeley/R-Fundamentals-Pilot/HEAD?urlpath=rstudio"> Binder @@ -208,14 +208,14 @@

R Data Visualization

+ href="http://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FR-Data-Visualization&urlpath=rstudio%2F"> Datahub + href="ps://mybinder.org/v2/gh/dlab-berkeley/R-Data-Visualization/HEAD?urlpath=rstudio"> Binder @@ -235,7 +235,7 @@

R Data Visualization

R Machine Learning with tidymodels

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Using R for ML!

+

Using R for ML

@@ -337,7 +337,7 @@

R Deep Learning

R Geospatial Fundamentals

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Working with spatial data

+

Working with spatial data in R

@@ -360,14 +360,14 @@

R Geospatial Fundamentals

+ href="http://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FR-Geospatial-Fundamentals&urlpath=rstudio%2F"> Datahub + href="https://mybinder.org/v2/gh/dlab-berkeley/R-Geospatial-Fundamentals/HEAD?urlpath=rstudio"> Binder
@@ -375,13 +375,14 @@

R Geospatial Fundamentals

+ + + - - diff --git a/R_graph.html b/R_graph.html new file mode 100644 index 0000000..db197cc --- /dev/null +++ b/R_graph.html @@ -0,0 +1,219 @@ + + + + + + Interactive Workshop Flowchart + + + + + + + + + +

D-Lab R Workshops

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Click on a workshop to see its prerequisites.
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+ + + + diff --git a/index.html b/index.html index d41a467..ebd1502 100644 --- a/index.html +++ b/index.html @@ -34,6 +34,12 @@

What do you want to learn?

Other +
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+ View All Workshops +
+
+ diff --git a/library.html b/library.html index 84c4db6..333a391 100644 --- a/library.html +++ b/library.html @@ -24,7 +24,7 @@ - -
MaxQDA: Introduction
+ + + +
MaxQDA Fundamentals
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MaxQDA: Introduction

+

MaxQDA Fundamentals

Using MaxQDA for data analysis

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MaxQDA: Introduction

- + Github - + + Slides + + +
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Python Data Visualization
+ +
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+

Python Data Visualization

+

Pandas, Matplotlib, and Seaborn

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+ In this workshop, we provide an introduction to data visualization with Python. First, we'll cover some basics of visualization theory. Then, we'll explore how to plot data in Python using the matplotlib and seaborn packages. +

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+ + Github + + Datahub - + + Binder + +
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+ + + + +
Python Data Wrangling
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+

Python Data Wrangling

+

Manipulate DataFrames using Pandas in Python

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+ In this workshop, we provide an introduction to data wrangling with Python. We will do so largely with the pandas package, which provides a rich set of tools to manipulate and interact with data frames, the most common data structure used when analyzing tabular data. We'll learn how to manipulate, index, merge, group, and plot data frames using pandas functions. +

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+ +
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+ + Github + + + Datahub + + + Binder + +
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Python Deep Learning
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+

Python Deep Learning

+

Create and train neural networks using Tensorflow and Keras

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+ This workshop conveys the basics of deep learning in Python using keras on image datasets. Students are empowered with a general grasp of deep learning, example code that they can modify, a working computational environment, and resources for further study. +

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+ + Github + + + Datahub + + + Binder + +
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Python Fundamentals
+ +
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+

Python Fundamentals

+

The absolute basics

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+ +
+

+ This three-part interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience, with a focus on data science application. It covers the basics of Python and Jupyter, variables and data types, and a gentle introduction to data analysis in Pandas.

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+ + Github + + + Datahub + + + Binder + +
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+ + + + +
Python Geospatial Fundamentals
+ +
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+ +
+

Python Geospatial Fundamentals

+

Analyzing geospatial data using GeoPandas in Python

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+ +
+

+ Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The Python programming language is a great platform for exploring these data and integrating them into your research. +

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+ +
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+ + Github + + + Datahub + + + Binder + +
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+ + + +
Python Intermediate
+ +
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+ +
+

Python Intermediate

+

Building on the basics

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+ +
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+ This three-part interactive workshop series is a follow-up to D-Lab's Python Fundamentals. It is intended for people who want to learn about core structures of Python that underpin data analysis. We cover loops and conditionals, creating your own functions, analysis and visualization in Pandas, and the workflow of a data science project.

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+ +
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+ + Github + + + Datahub + + + Binder + +
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+ + + +
Python Machine Learning
+ +
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+ +
+

Python Machine Learning

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Classification, regression, clustering in Python

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+ +
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+ In this workshop, we provide an introduction to machine learning in Python. First, we'll cover some machine learning basics, including its foundational principles. Then, we'll dive into code, understanding how to perform regression, regularization, preprocessing, and classification. +

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+ +
+
+ + Github + + + Datahub + + Binder
@@ -185,6 +430,212 @@

MaxQDA: Introduction

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Python Web APIs
+ +
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+ +
+

Python Web APIs

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Obtain data from web platforms

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+ +
+

+ In this workshop, we cover how to extract data from the web with APIs using Python. APIs are often official services offered by companies and other entities, which allow you to directly query their servers in order to retrieve their data. Platforms like The New York Times, Twitter and Reddit offer APIs to retrieve data. +

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+ +
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+ + Github + + + Datahub + + + Binder + +
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+ + + + +
Python Web Scraping
+ +
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+ +
+

Python Web Scraping

+

Scrape HTML/CSS data from websites

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+ +
+

+ In this workshop, we cover how to scrape data from the web using Python. Web scraping involves downloading a webpage's source code and sifting through the material to extract desired data. +

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+ +
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+ + Github + + + Datahub + + + Binder + +
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+ + + +
Qualtrics Fundamentals
+ +
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+ +
+

Qualtrics Fundamentals

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Data collection and survey design

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+ This workshop will introduce Qualtrics with an orientation to the main interfaces for web survey design, sample management, corresponding with sample members, and exporting data. +

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+ + Github + + + Slides + + +
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+ + + + +
R Data Visualization
+ +
+
+ +
+

R Data Visualization

+

Visualizing with R

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+ +
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+ This workshop will provide an introduction to graphics in R with ggplot2. Participants will learn how to construct, customize, and export a variety of plot types in order to visualize relationships in data. +

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+ +
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+ + Github + + + Datahub + + + Binder + +
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+
+
+ + + +
R Data Wrangling and Manipulation
+ +
+
+ +
+

R Data Wrangling and Manipulation

+

Working with data

+
+ +
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+ This workshop will introduce packages in R (notably dplyr and tidyr) that make data wrangling and manipulation much easier. +

+
+ +
+
+ + Github + + + Datahub + + +
+
+
+
+ + + +
R Deep Learning
+ +
+
+ +
+

R Deep Learning

+

Working with Keras in R

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+ +
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+ This workshop introduces the basic concepts of Deep Learning — the training and performance evaluation of large neural networks, especially for image classification, natural language processing, and time-series data. Like many other machine learning algorithms, we will use deep learning algorithms to map input data to their appropriately classified outcome labels. +

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+ +
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+ + Github + + + Datahub + + + Binder + + + Slides + +
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+ + +
R Fundamentals
@@ -192,7 +643,7 @@

MaxQDA: Introduction

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Data Manipulation in R

+

R Fundamentals

The absolute basics

@@ -204,13 +655,13 @@

Data Manipulation in R

- + Github - + Datahub - + Binder
@@ -219,6 +670,77 @@

Data Manipulation in R

+ +
R Geospatial Fundamentals
+ +
+
+ +
+

R Geospatial Fundamentals

+

Working with spatial data in R

+
+ +
+

+ Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. +

+
+ +
+
+ + Github + + + Datahub + + + Binder + +
+
+
+
+ + + +
R Machine Learning with tidymodels
+ +
+
+ +
+

R Machine Learning with tidymodels

+

Using R for ML

+
+ +
+

+ This workshop offers an introduction to machine learning algorithms by making use of the tidymodels package. +

+
+ +
+
+ + Github + + + Datahub + + + Binder + + + Slides + +
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+
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+ + @@ -229,7 +751,7 @@

Data Manipulation in R

Stata Fundamentals

-

The absolute basics

+

The basics of Stata

@@ -289,9 +811,6 @@

Stata Fundamentals

integrity="sha384-JZR6Spejh4U02d8jOt6vLEHfe/JQGiRRSQQxSfFWpi1MquVdAyjUar5+76PVCmYl" crossorigin="anonymous"> - - - diff --git a/other.html b/other.html index 5526c50..17db4e7 100644 --- a/other.html +++ b/other.html @@ -62,8 +62,8 @@
Click below to see which D-Lab workshop is best for you!
-

- + +

@@ -364,8 +364,8 @@

Qualtrics Fundamentals

-

MaxQDA: Introduction

-

using MaxQDA for data analysis

+

MaxQDA Fundamentals

+

Using MaxQDA for data analysis

@@ -381,22 +381,15 @@

MaxQDA: Introduction

+ href="https://github.com/dlab-berkeley/maxqda-fundamentals"> Github - Datahub - - - - Binder + href="https://docs.google.com/presentation/d/1rJ_5iOhRzBM5M-RqYoT3NojAhq-hUFwc/edit#slide=id.p1"> + Slides
@@ -404,8 +397,7 @@

MaxQDA: Introduction

- -
+