# https://www.machinelearningplus.com/plots/top-50-matplotlib-visualizations-the-master-plots-python/

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

import seaborn as sns
import warnings; warnings.filterwarnings(action='once')

# Import Data
df = pd.read_csv("https://raw.githubusercontent.com/selva86/datasets/master/mpg_ggplot2.csv")
df_counts = df.groupby(['hwy', 'cty']).size().reset_index(name='counts')

df.head()

df_counts

/Users/rajacsp/opt/anaconda3/envs/py38_jupyter/lib/python3.8/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)

# Draw Stripplot
fig, ax = plt.subplots(figsize=(16,10), dpi= 80)    
sns.stripplot(df_counts.cty, df_counts.hwy, size=df_counts.counts*2, ax=ax)

# Decorations
plt.title('Counts Plot - Size of circle is bigger as more points overlap', fontsize=22)
plt.show()

/Users/rajacsp/opt/anaconda3/envs/py38_jupyter/lib/python3.8/site-packages/ipykernel/ipkernel.py:287: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.
  and should_run_async(code)



---------------------------------------------------------------------------

ValueError                                Traceback (most recent call last)

<ipython-input-11-74fe28045231> in <module>
      1 # Draw Stripplot
      2 fig, ax = plt.subplots(figsize=(16,10), dpi= 80)
----> 3 sns.stripplot(df_counts.cty, df_counts.hwy, size=df_counts.counts*2, ax=ax)
      4 
      5 # Decorations


~/opt/anaconda3/envs/py38_jupyter/lib/python3.8/site-packages/seaborn/categorical.py in stripplot(x, y, hue, data, order, hue_order, jitter, dodge, orient, color, palette, size, edgecolor, linewidth, ax, **kwargs)
   2796                        linewidth=linewidth))
   2797 
-> 2798     plotter.plot(ax, kwargs)
   2799     return ax
   2800


~/opt/anaconda3/envs/py38_jupyter/lib/python3.8/site-packages/seaborn/categorical.py in plot(self, ax, kws)
   1187     def plot(self, ax, kws):
   1188         """Make the plot."""
-> 1189         self.draw_stripplot(ax, kws)
   1190         self.add_legend_data(ax)
   1191         self.annotate_axes(ax)


~/opt/anaconda3/envs/py38_jupyter/lib/python3.8/site-packages/seaborn/categorical.py in draw_stripplot(self, ax, kws)
   1163                 kws.update(c=palette[point_colors])
   1164                 if self.orient == "v":
-> 1165                     ax.scatter(cat_pos, strip_data, **kws)
   1166                 else:
   1167                     ax.scatter(strip_data, cat_pos, **kws)


~/opt/anaconda3/envs/py38_jupyter/lib/python3.8/site-packages/matplotlib/__init__.py in inner(ax, data, *args, **kwargs)
   1436     def inner(ax, *args, data=None, **kwargs):
   1437         if data is None:
-> 1438             return func(ax, *map(sanitize_sequence, args), **kwargs)
   1439 
   1440         bound = new_sig.bind(ax, *args, **kwargs)


~/opt/anaconda3/envs/py38_jupyter/lib/python3.8/site-packages/matplotlib/cbook/deprecation.py in wrapper(*inner_args, **inner_kwargs)
    409                          else deprecation_addendum,
    410                 **kwargs)
--> 411         return func(*inner_args, **inner_kwargs)
    412 
    413     return wrapper


~/opt/anaconda3/envs/py38_jupyter/lib/python3.8/site-packages/matplotlib/axes/_axes.py in scatter(self, x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, edgecolors, plotnonfinite, **kwargs)
   4446         s = np.ma.ravel(s)
   4447         if len(s) not in (1, x.size):
-> 4448             raise ValueError("s must be a scalar, or the same size as x and y")
   4449 
   4450         c, colors, edgecolors = \


ValueError: s must be a scalar, or the same size as x and y