python - How to plot a linear regression with datetimes on the x-axis

Question

My DataFrame object looks like

            amount
date    
2014-01-06  1
2014-01-07  1
2014-01-08  4
2014-01-09  1
2014-01-14  1

I would like a sort of scatter plot with time along the x-axis, and amount on the y, with a line through the data to guide the viewer's eye. If I use the pandas plot df.plot(style="o") it's not quite right, because the line is not there. I would like something like the examples here.

Answer 1

note: this has a lot in common with Ian Thompson's answer but the approach is different enough to have it be a separate answer. I use the DataFrame format provided in the question and avoid changing the index.

Seaborn and other libraries don't deal as well with datetime axes as you might like them to. Here's how I'd work around it:

Start by adding a column of date ordinals

Seaborn will deal better with these than with dates. This is a handy trick for doing all kind of mathy things with dates and libraries that don't love dates.

from datetime import date

df['date_ordinal'] = pd.to_datetime(df['date']).apply(lambda date: date.toordinal())

Make a plot with the ordinals on the date axis

ax = seaborn.regplot(
    data=df,
    x='date_ordinal',
    y='amount',
)
# Tighten up the axes for prettiness
ax.set_xlim(df['date_ordinal'].min() - 1, df['date_ordinal'].max() + 1)
ax.set_ylim(0, df['amount'].max() + 1)

Replace the ordinal X-axis labels with nice, readable dates

ax.set_xlabel('date')
new_labels = [date.fromordinal(int(item)) for item in ax.get_xticks()]
ax.set_xticklabels(new_labels)

ta-daa!