---
title: Get Climate Data Online
subtitle: Climate change is impacting the way people live around the world
learning-goals:
  - Analyze temperature data over time
  - Parse date information so that it is represented as a datetime type
  - Use operators to convert to different units
  - "Resample time-series data to different frequencies"
params:
  id: eda
  project_dirname: 'climate-boulder'
  ncei_filename: "ncei-climate-boulder.csv"
  location: "Boulder, CO"
  station_id: "USC00050848"
  start_date: "1893-10-01"
  end_date: "2023-09-30"
  data_type: "TOBS"
jupyter:
  kernelspec:
    name: learning-portal
    language: python
    display_name: Learning Portal
---

Before we get started, let's define some parameters. You can use these if you want to change how the workflow runs from the top:

```{python}
#| tags: [parameters]
id = 'foundations'
project_dirname = 'climate-boulder'
ncei_filename = 'ncei-climate-boulder.csv'
location = 'Boulder, CO'
station_id = 'USC00050848'
start_date = '1893-10-01'
end_date = '2023-09-30'
data_type = 'TOBS'
```

{{< include _climate-98-download.qmd >}}

{{< include _climate-99-portfolio.qmd >}}
