I am trying to do a plot of values over time using seaborn linear model plot but I get the error
TypeError: invalid type promotion
I have read that it is not possible to plot pandas date objects, but that seems really strange given seaborn requires you pass a pandas DataFrame to the plots.
Below is a simple example. Does anyone know how I can get this to work?
import pandas as pd
import seaborn as sns; sns.set(color_codes=True)
import matplotlib.pyplot as plt
date = ['1975-12-03','2008-08-20', '2011-03-16']
value = [1,4,5]
df = pd.DataFrame({'date':date, 'value': value})
df['date'] = pd.to_datetime(df['date'])
g = sns.lmplot(x="date", y="value", data=df, size = 4, aspect = 1.5)
I am trying to do a plot like this one I created in r using ggplot hence why I want to use sns.lmplot
You need to convert your dates to floats, then format the x-axis to reinterpret and format the floats into dates.
Here's how I would do this:
import pandas
import seaborn
from matplotlib import pyplot, dates
%matplotlib inline
date = ['1975-12-03','2008-08-20', '2011-03-16']
value = [1,4,5]
df = pandas.DataFrame({
'date': pandas.to_datetime(date), # pandas dates
'datenum': dates.datestr2num(date), # maptlotlib dates
'value': value
})
@pyplot.FuncFormatter
def fake_dates(x, pos):
""" Custom formater to turn floats into e.g., 2016-05-08"""
return dates.num2date(x).strftime('%Y-%m-%d')
fig, ax = pyplot.subplots()
# just use regplot if you don't need a FacetGrid
seaborn.regplot('datenum', 'value', data=df, ax=ax)
# here's the magic:
ax.xaxis.set_major_formatter(fake_dates)
# legible labels
ax.tick_params(labelrotation=45)
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