- #53 Control violinplot color | seaborn
- #53 Control violinplot color | seaborn
- #53 Control violinplot color | seaborn
- #53 Control violinplot color | seaborn
Color is probably the first feature you want to control on your seaborn violinplot. Here I give 4 tricks to control it:
- 1/ Use a color palette
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# library & dataset import seaborn as sns df = sns.load_dataset('iris') # Use a color palette sns.violinplot( x=df["species"], y=df["sepal_length"], palette="Blues")
- 2/ Uniform color
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#dataset and library import seaborn as sns df = sns.load_dataset('iris') # plot sns.violinplot( x=df["species"], y=df["sepal_length"], color="skyblue")
- 3/ Specify color of each group
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#dataset and library import seaborn as sns df = sns.load_dataset('iris') # Make a dictionary with one specific color per group: my_pal = {"versicolor": "g", "setosa": "b", "virginica":"m"} #plot it sns.violinplot( x=df["species"], y=df["sepal_length"], palette=my_pal)
- 4/ Highlight a group
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#dataset and library import seaborn as sns df = sns.load_dataset('iris') # make a vector of color: red for the interesting group, blue for others: my_pal = {species: "r" if species == "versicolor" else "b" for species in df.species.unique()} # make the plot sns.violinplot( x=df["species"], y=df["sepal_length"], palette=my_pal)
Awesome vagina plots!