<commit_before>---
layout: lesson
subtitle: Reading Tabular Data
---

FIXME

*   Teaching: 5 min
*   Exercises: 10 min (because some people will have trouble finding the data set's path)
    *   Read one continent's subset of gapminder CSV data
*   Callout:
    *   How to read data from Excel spreadsheets via export to CSV<commit_msg>Exercises for reading tabular data<commit_after>---
layout: lesson
subtitle: Reading Tabular Data
---
> ## Learning Objectives
>
> * Learner will import the Pandas library.
> * Learner will use Pandas to load a simple CSV data set.
{: .objectives}

FIXME: lesson content.

## Reading Other Data
{: .challenge}

1.  Create a new notebook called `test_loading`.
2.  Create a single Python cell in that notebook that contains
    all the instructions needed to load and display the data in
    `data/gapminder_gdp_oceania.csv'.

## Error Messages
{: .challenge}

The data for your current project is stored in a file called `microbes.csv`,
which is located in a folder called `field_data`.
You are doing analysis in a notebook called `analysis.ipynb`
in a sibling folder called `thesis`:

~~~
your_home_directory
|-- field_data/
|   \-- microbes.csv
|-- thesis/
|   \-- analysis.ipynb
~~~

What value(s) should you pass to `read_csv` to read `microbes.csv` in `analysis.ipynb`?
{'fraction_non_alphanumeric': 0.0916030534351145, 'fraction_numerical': 0.003816793893129771, 'mean_word_length': 3.6989247311827955, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 7, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '2185364', 'n_tokens_mistral': 418, 'n_tokens_neox': 396, 'n_words': 168}