Why does my Pandas DataFrame not display new order using `sort_values`?

New to Pandas, so maybe I'm missing a big idea? I have a Pandas DataFrame of register transactions with shape like (500,4):

Time              datetime64[ns]
Net Total                float64
Tax                      float64
Total Due                float64

I'm working through my code in a Python3 Jupyter notebook. I can't get past sorting any column. Working through the different code examples for sort, I'm not seeing the output reorder when I inspect the df. So, I've reduced the problem to trying to order just one column:

df.sort_values(by='Time')
# OR
df.sort_values(['Total Due'])
# OR
df.sort_values(['Time'], ascending=True)

No matter which column title, or which boolean argument I use, the displayed results never change order.

Thinking it could be a Jupyter thing, I've previewed the results using print(df), df.head(), and HTML(df.to_html()) (the last example is for Jupyter notebooks). I've also rerun the whole notebook from import CSV to this code. And, I'm also new to Python3 (from 2.7), so I get stuck with that sometimes, but I don't see how that's relevant in this case.

Another post has a similar problem, Python pandas dataframe sort_values does not work. In that instance, the ordering was on a column type string. But as you can see all of the columns here are unambiguously sortable.

Why does my Pandas DataFrame not display new order using sort_values?

Solution 1:

df.sort_values(['Total Due']) returns a sorted DF, but it doesn't update DF in place.

So do it explicitly:

df = df.sort_values(['Total Due'])

or

df.sort_values(['Total Due'], inplace=True)