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I am having a problem with Facetgrid: when I use the hue parameter, the x-labels show up in the wrong order and do not match the data. Loading the Titanic dataset in ipython:
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
titanic = sns.load_dataset("titanic")
g = sns.FacetGrid(titanic, col='pclass', hue='survived')
g = g.map(sns.swarmplot, 'sex', 'age')
Facetgrid with Hue:
From this it seems that there are more females than males, but this is not true.
If I now remove the hue option, then I get a correct distribution: there are more males than females across all pclasses.
g = sns.FacetGrid(titanic, col='pclass')
g = g.map(sns.swarmplot, 'sex', 'age')
Facetgrid without Hue:
What's going on here? I am using Seaborn 0.7.0
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FacetGrid object takes a dataframe as input and the names of the variables that will form the row, column, or hue dimensions of the grid. The variables should be categorical and the data at each level of the variable will be used for a facet along that axis.
A FacetGrid is a multi-axes grid with subplots visualizing the distribution of variables of a dataset and the relationship between multiple variables.
col_wrapint. “Wrap” the column variable at this width, so that the column facets span multiple rows. Incompatible with a row facet. share{x,y}bool, 'col', or 'row' optional. If true, the facets will share y axes across columns and/or x axes across rows.
In Seaborn, we will plot multiple graphs in a single window in two ways. First with the help of Facetgrid() function and other by implicit with the help of matplotlib. data: Tidy dataframe where each column is a variable and each row is an observation.
If you are going to use FacetGrid with one of the categorical plotting functions, you need to supply order information, either by declaring the variables as categorical or with the order and hue_order parameters:
g = sns.FacetGrid(titanic, col='pclass', hue='survived')
g = g.map(sns.swarmplot, 'sex', 'age', order=["male", "female"], hue_order=[0, 1])
However, it is generally preferable to use factorplot, which will take care of this bookkeeping for you and also save you some typing:
g = sns.factorplot("sex", "age", "survived", col="pclass", data=titanic, kind="swarm")
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