Geo python 2023 lesson 2 1 python basics i

### geo python 2023: lesson 2.1 - python basics

in this lesson, we will cover the fundamental aspects of python programming that are essential for working with geospatial data. we'll explore basic syntax, data types, control structures, and functions.

#### 1. basic syntax

python uses indentation to define blocks of code. unlike other programming languages that use curly braces `{}` or keywords to define the scope, python relies on whitespace.

#### 2. data types

python has several built-in data types that are commonly used:

- **integers**: whole numbers (e.g., `5`, `-2`)
- **floats**: decimal numbers (e.g., `3.14`, `-0.001`)
- **strings**: textual data (e.g., `"hello, world!"`)
- **booleans**: true or false values (`true`, `false`)
- **lists**: ordered, mutable collections (e.g., `[1, 2, 3]`)
- **dictionaries**: key-value pairs (e.g., `{"name": "john", "age": 30}`)

##### example of data types:

#### 3. control structures

control structures allow you to dictate the flow of your program. the most common structures are `if` statements, `for` loops, and `while` loops.

##### if statements

##### for loops

##### while loops

#### 4. functions

functions are reusable blocks of code that perform a specific task. they help in organizing your code.

#### 5. practical example: geospatial data

now, let's apply our knowledge to a practical example related to geospatial data. we will create a function that calculates the distance between two geographical points using the haversine formula.

### conclusion

in this lesson, we covered the basics of python programming, including syntax, data types, control structures, and functions. we also explored a practical example relevant to geospatial analysis. understanding these fundamentals will provide a strong foundation for more advanced topics in geospatial python programming.

### next steps

in the following lessons, we will dive deeper into libraries such as `geopandas`, `folium`, and `matplotlib` for geosp ...

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