I have a dataframe looks like this:
date score
2017-06-04 90
2017-06-03 80
2017-06-02 70
When I tried this:
Seaborn doesn't support datetimes in regplot
but here's an ugly hack:
df = df.sort_values('date')
df['date_f'] = pd.factorize(df['date'])[0] + 1
mapping = dict(zip(df['date_f'], df['date'].dt.date))
ax = sns.regplot('date_f', 'score', data=df)
labels = pd.Series(ax.get_xticks()).map(mapping).fillna('')
ax.set_xticklabels(labels)
produces
This is the main approach used in time-series regression. If you have daily data, you code day 1 as 1 and increase the number as the days go by. This assumes you have a regularly-spaced time series.