I have daily data that I need to plot with sns.lmplot()
.
The data has the following structure:
df = pd.DataFrame(columns=['date', 'origin', 'group', 'value'],
data = [['2001-01-01', "Peter", "A", 1.0],
['2011-01-01', "Peter", "A", 1.1],
['2011-01-02', "Peter", "B", 1.2],
['2012-01-03', "Peter", "A", 1.3],
['2012-01-01', "Peter", "B", 1.4],
['2013-01-02', "Peter", "A", 1.5],
['2013-01-03', "Peter", "B", 1.6],
['2021-01-01', "Peter", "A", 1.7]])
I now want to plot the data with sns.lmplot()
for monthly averages (my original data is more fine-grained than the toy data) and using the hue
for group
-column. For this, I aggregate by month:
df['date'] = pd.to_datetime(df['date']).dt.strftime('%Y%M').astype(int)
df = df.groupby(['date', 'origin', 'group']).agg(['mean'])
df.columns = ["_".join(pair) for pair in df.columns] # reset col multi-index
df = df.reset_index() # reset index
Then I plot the data:
sns.lmplot(data=df, x="date", y="value", hue="group",
ci=None, truncate=False, scatter_kws={"s": 1}, lowess=True, height=6, aspect=1.25)
plt.title(f"Title.")
plt.ylabel("Value")
plt.show()
This works fine but the dates are messy. I would like them to be displayed as dates rather than int
s.