I am trying to add to my several line plots a background that shows a range from value x (column “Min”) to value y (column “Max”) for each year. My dataset looks like that:
Country Model Year Costs Min Max
494 FR 1 1990 300 250 350
495 FR 1 1995 250 300 400
496 FR 1 2000 220 330 640
497 FR 1 2005 210 289 570
498 FR 2 1990 400 250 350
555 JPN 8 1990 280 250 350
556 JPN 8 1995 240 300 400
557 JPN 8 2000 200 330 640
558 JPN 8 2005 200 289 570
I used the following code:
example_1 = sns.relplot(data=example, x = "Year", y = "Costs", hue = "Model", style = "Model", col = "Country", kind="line", col_wrap=4,height = 4, dashes = True, markers = True, palette = palette, style_order = style_order)
I would like something like this with the range being my “Min” and “Max” by year.
Is it possible to do it? Thank you very much !
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Answer
Usually, grid.map
is the tool for this, as shown in many examples in the mutli-plot grids tutorial. But you are using relplot
to combine lineplot
with a FacetGrid
as it is suggested in the docs (last example) which lets you use some extra styling parameters.
Because relplot
processes the data a bit differently than if you would first initiate a FacetGrid
and then map a lineplot
(you can check this with grid.data
), using grid.map(plt.bar, ...)
to plot the ranges is quite cumbersome as it requires editing the grid.data
dataframe as well as the x- and y-axis labels.
The simplest way to plot the ranges is to loop through the grid.axes
. This can be done with grid.axes_dict.items()
which provides the column names (i.e. countries) that you can use to select the appropriate data for the bars (useful if the ranges were to differ, contrary to this example).
The default figure legend does not contain the complete legend including the key for ranges, but the first ax
object does so that one displayed instead of the default legend in the following example. Note that I have edited the data you shared so that the min/max ranges make more sense:
import io
import pandas as pd # v 1.1.3
import matplotlib.pyplot as plt # v 3.3.2
import seaborn as sns # v 0.11.0
data ='''
Country Model Year Costs Min Max
494 FR 1 1990 300 250 350
495 FR 1 1995 250 200 300
496 FR 1 2000 220 150 240
497 FR 1 2005 210 189 270
555 JPN 8 1990 280 250 350
556 JPN 8 1995 240 200 300
557 JPN 8 2000 200 150 240
558 JPN 8 2005 200 189 270
'''
df = pd.read_csv(io.StringIO(data), delim_whitespace=True)
# Create seaborn FacetGrid with line plots
grid = sns.relplot(data=df, x='Year', y='Costs', hue='Model', style='Model',height=3.9,
col='Country', kind='line', markers=True, palette='tab10')
# Loop through axes of the FacetGrid to plot bars for ranges and edit x ticks
for country, ax in grid.axes_dict.items():
df_country = df[df['Country'] == country]
cost_range = df_country['Max']-df_country['Min']
ax.bar(x=df_country['Year'], height=cost_range, bottom=df_country['Min'],
color='black', alpha=0.1, label='Min/maxnrange')
ax.set_xticks(df_country['Year'])
# Remove default seaborn figure legend and show instead full legend stored in first ax
grid._legend.remove()
grid.axes.flat[0].legend(bbox_to_anchor=(2.1, 0.5), loc='center left',
frameon=False, title=grid.legend.get_title().get_text());