Plot distributions of each series in a Pandas dataframe

plot_distributions.py

# plot the distribution of each feature
def plot_distributions(df, cols=3, width=20, height=20, hspace=0.45, wspace=0.5):
    # generate the figure to draw on
    plt.style.use('seaborn-whitegrid')
    fig = plt.figure(figsize=(width, height))
    fig.subplots_adjust(left=None, bottom=None, right=None, top=None,
                        wspace=wspace, hspace=hspace)
    rows = math.ceil(float(df.shape[1]) / cols)
    
    # add subplot for each series with appropriate formatting
    for i, column in enumerate(df.columns):
        ax = fig.add_subplot(rows, cols, i + 1)
        ax.set_title(column)
        
        if df.dtypes[column] == np.object:
            g = sns.countplot(y=column, data=df)
            substrings = [s.get_text()[:18] for s in g.get_yticklabels()]
            g.set(yticklabels=substrings)
            plt.xticks(rotation=25)
        else:
            g = sns.distplot(df[column].dropna())
            plt.xticks(rotation=25)
    
    # format the figure
    plt.tight_layout()
    plt.show()
    
plot_distribution(df)