# Introduction to Shapefiles and Vector Data in Open Source Python

## Welcome to Week 4!

Welcome to week 4 of Earth Analytics! This week, you will dive deeper into working with spatial data in Python. You will learn how to handle data in different coordinate reference systems, how to create custom maps and legends and how to extract data from a raster file. You are on your way towards integrating many different types of data into your analysis which involves knowing how to deal with things like coordinate reference systems and varying data structures.

## What You Need

You will need a computer with internet access to complete this lesson and the spatial-vector-lidar data subset created for the course. Note that the data download below is large (172MB) however it contains data that you will use for the next 2 weeks!

or using the earthpy package:

et.data.get_data("spatial-vector-lidar")

TimeTopicSpeaker
9:30 AMQuestions / PythonLeah
9:45 - 10:15Coordinate reference systems & spatial metadata 101
10:25 - 12:20Python coding session - spatial data in PythonLeah

## Plot 4

2. a url - this is the URL where the data are located. The URL below might look odd as it has two “http” strings in it but it is how the url’s are organized on natural earth and should work.

The download() function will unzip your data for you and place it in the directory that you specify.

# Add this line importing the download package to your top cell with the other packages!

/Users/leah-su/anaconda3/envs/earth-analytics-python/lib/python3.6/site-packages/pandas/core/reshape/merge.py:544: UserWarning: merging between different levels can give an unintended result (1 levels on the left, 2 on the right)