linting + simplify

src/klib/describe.py

@@ -15,6 +15,10 @@
 import pandas as pd
 import scipy
 import seaborn as sns
+from matplotlib import ticker
+from matplotlib.colors import LinearSegmentedColormap
+from matplotlib.colors import to_rgb
+
 from klib.utils import _corr_selector
 from klib.utils import _missing_vals
 from klib.utils import _validate_input_bool
@@ -23,9 +27,6 @@
 from klib.utils import _validate_input_range
 from klib.utils import _validate_input_smaller
 from klib.utils import _validate_input_sum_larger
-from matplotlib import ticker
-from matplotlib.colors import LinearSegmentedColormap
-from matplotlib.colors import to_rgb
 
 __all__ = ["cat_plot", "corr_mat", "corr_plot", "dist_plot", "missingval_plot"]
 
@@ -93,12 +94,12 @@ def cat_plot(
 
         if n_unique < top + bottom:
             if bottom > top:
-                lim_top = int(n_unique // 2) if int(n_unique // 2) < top else top
+                lim_top = min(int(n_unique // 2), top)
                 lim_bot = n_unique - lim_top
             else:
-                lim_bot = int(n_unique // 2) if int(n_unique // 2) < bottom else bottom
+                lim_bot = min(int(n_unique // 2), bottom)
                 lim_top = n_unique - lim_bot
-    
+
         value_counts_top = value_counts[:lim_top]
         value_counts_idx_top = value_counts_top.index.tolist()
         value_counts_bot = value_counts[-lim_bot:] if lim_bot > 0 else pd.DataFrame()