1. Installation
1.1. R
1.1.1. CRAN-R
1.1.2. RStudio
1.1.2.1. Desktop Version
1.1.2.2. Cloud Version
1.1.2.3. beyond base installation
1.1.2.3.1. install (download and install)
1.1.2.3.2. activate
1.2. Python
1.2.1. Desktop version
1.2.1.1. Anaconda
1.2.1.1.1. Create Environment
1.2.1.1.2. Install Jupyter
1.2.2. Cloud version
1.2.2.1. GoogleColab
1.2.2.2. DataLore
1.2.3. beyond base installation
1.2.3.1. install (download and install)
1.2.3.1.1. from Anaconda
1.2.3.1.2. from Terminal
1.2.3.2. activate
1.2.3.2.1. **import** plotnine
2. Data Types
2.1. Numerical
2.1.1. Real
2.1.1.1. AKA **numeric** / **double** in R
2.1.1.2. AKA **float** in Python
2.1.2. Integer
2.1.3. Complex
2.2. Logical
2.2.1. TRUE / FALSE in **R**
2.2.2. True / False in **Python**
2.2.2.1. AKA **boolean** in Python
2.3. Character or String
2.4. Categorical
2.4.1. AKA **factor** in R
2.4.2. AKA **categorical** in Python
2.5. Date
3. Data Structures
3.1. Simple
3.1.1. Common between R and Python
3.1.1.1. Vector
3.1.1.1.1. Native
3.1.1.1.2. Non-native
3.1.1.2. List
3.1.1.2.1. Native
3.1.2. Only Python
3.1.2.1. Tuple
3.1.2.2. Set
3.1.3. Operations
3.1.3.1. Create
3.1.3.1.1. Python
3.1.3.1.2. R
3.1.3.2. Access
3.1.3.2.1. List
3.1.3.2.2. Vector
3.1.3.2.3. Set
3.1.3.2.4. Tuple
3.1.3.3. Modify
3.1.3.3.1. Replace
3.1.3.3.2. Delete
3.1.3.3.3. Insert
3.1.3.4. Concatenate
3.1.3.4.1. List
3.1.3.4.2. Vector
3.1.3.4.3. Set
3.1.3.4.4. Tuple
3.2. Complex
3.2.1. Only Python
3.2.1.1. Dictionary
3.2.1.1.1. Create
3.2.1.1.2. Access
3.2.1.1.3. Modify
3.2.2. Common between R and Python
3.2.2.1. Data Frame
3.2.2.1.1. Native
3.2.2.1.2. Non-native
3.2.2.1.3. Operations
3.2.2.2. Spatial Data Frame
3.2.2.3. Graphs