fixed formatting

Author: hfboyce

chapters/en/slides/module1/module1_00.md

@@ -13,16 +13,16 @@ Notes: In this module you will be introduced to dataframes, the Python Pandas pa
 
 By the end of the module, students are expected to:
 
-- Describe the components of a Dataframe.
-- Read a standard `.csv` file using Pandas [`pd.read_csv()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html).
-- Load the `pandas` library into Python.
-- Demonstrate indexing and slicing with `.loc[]` and `.iloc[]`.
-- Demonstrate Selecting columns of a dataframe using `df[]` notation.
-- Obtain values from a dataframe using `.loc[]`.
-- Sort a dataframe using [`.sort_values()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sort_values.html).
-- Create simple summary statistics using [`.describe()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.describe.html).
-- Construct simple visualizations using [Altair](https://altair-viz.github.io/).
-- Create a `.csv` file from a dataframe using [`.to_csv()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_csv.html).
+- Describe the components of a Dataframe. 
+- Read a standard `.csv` file using Pandas [`pd.read_csv()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html).      
+- Load the `pandas` library into Python.      
+- Demonstrate indexing and slicing with `.loc[]` and `.iloc[]`.    
+- Demonstrate Selecting columns of a dataframe using `df[]` notation.      
+- Obtain values from a dataframe using `.loc[]`.      
+- Sort a dataframe using [`.sort_values()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sort_values.html).      
+- Create simple summary statistics using [`.describe()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.describe.html).    
+- Construct simple visualizations using [Altair](https://altair-viz.github.io/).      
+- Create a `.csv` file from a dataframe using [`.to_csv()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_csv.html).     
 
 Notes: