The most 50 valuable charts drawn by Python Part III

import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import warnings
warnings.filterwarnings(action='once')
plt.style.use('seaborn-whitegrid')
sns.set_style("whitegrid")

x = df.loc[:, ['mpg']]
df['mpg_z'] = (x - x.mean()) / x.std()
df['colors'] = ['red' if x < 0 else 'green' for x in df['mpg_z']]
df.sort_values('mpg_z', inplace=True)
df.reset_index(inplace=True)

# Draw plot
plt.figure(figsize=(10, 6), dpi=80)
plt.hlines(y=df.index,
           xmin=0,
           xmax=df.mpg_z,
           color=df.colors,
           alpha=0.8,
           linewidth=5)

# Decorations
plt.gca().set(ylabel='Model', xlabel='Mileage')
plt.yticks(df.index, df.model, fontsize=12)
plt.xticks(fontsize=12)
plt.title('Diverging Bars of Car Mileage')
plt.grid(linestyle='--', alpha=0.5)
plt.show()

x = df.loc[:, ['mpg']]
df['mpg_z'] = (x - x.mean())/x.std()
df['colors'] = ['red' if x < 0 else 'green' for x in df['mpg_z']]
df.sort_values('mpg_z', inplace=True)
df.reset_index(inplace=True)

# Draw plot
plt.figure(figsize=(10,8), dpi= 80)
plt.hlines(y=df.index, xmin=0, xmax=df.mpg_z,color=df.colors, alpha=0.8, linewidth=5)
for x, y, tex in zip(df.mpg_z, df.index, df.mpg_z):
    t = plt.text(x, y, round(tex, 2), horizontalalignment='right' if x < 0 else 'left', 
                 verticalalignment='center', fontdict={'color':'black' if x < 0 else 'black', 'size':10})

# Decorations    
plt.yticks(df.index, df.model, fontsize=12)
plt.xticks(fontsize=10)
plt.title('Diverging Text Bars of Car Mileage', fontdict={'size':15})
plt.grid(linestyle='--', alpha=0.5)
plt.xlim(-2.5, 2.5)
plt.show()

x = df.loc[:, ['mpg']]
df['mpg_z'] = (x - x.mean()) / x.std()
df['colors'] = ['red' if x < 0 else 'green' for x in df['mpg_z']]
df.sort_values('mpg_z', inplace=True)
df.reset_index(inplace=True)

# Draw plot
plt.figure(figsize=(10, 6), dpi=80)
plt.vlines(x=df.index,
           ymin=0,
           ymax=df.mpg_z,
           color=df.colors,
           alpha=0.8,
           linewidth=5)
for y, x, tex in zip(df.mpg_z, df.index, df.mpg_z):
    t = plt.text(x,
                 y+0.2,
                 round(tex, 1),
                 horizontalalignment='center',
                 fontdict={
                     'color': 'black' if x < 0 else 'black',
                     'size': 8
                 })

# Decorations
plt.xticks(df.index, df.model, fontsize=12, rotation=90)
plt.yticks(fontsize=12)
plt.title('Diverging Text Bars of Car Mileage', fontdict={'size': 12})
plt.grid(linestyle='--', alpha=0.5)
plt.show()

x = df.loc[:, ['mpg']]
df['mpg_z'] = (x - x.mean()) / x.std()
df['colors'] = ['red' if x < 0 else 'darkgreen' for x in df['mpg_z']]
df.sort_values('mpg_z', inplace=True)
df.reset_index(inplace=True)

# Draw plot
plt.figure(figsize=(12, 10), dpi=80)
plt.scatter(df.mpg_z, df.index, s=250, alpha=.6, color=df.colors)
for x, y, tex in zip(df.mpg_z, df.index, df.mpg_z):
    t = plt.text(x,
                 y,
                 round(tex, 1),
                 horizontalalignment='center',
                 verticalalignment='center',
                 fontdict={'color': 'black','size': '10'})

# Decorations
# Lighten borders
plt.gca().spines["top"].set_alpha(.3)
plt.gca().spines["bottom"].set_alpha(.3)
plt.gca().spines["right"].set_alpha(.3)
plt.gca().spines["left"].set_alpha(.3)

plt.yticks(df.index, df.model,fontsize=10)
plt.xticks(fontsize=10)
plt.title('Diverging Dotplot of Car Mileage', fontdict={'size': 15})
plt.xlabel('Mileage',fontsize=10)
plt.grid(linestyle='--', alpha=0.5)
plt.xlim(-2.5, 2.5)
plt.show()

x = df.loc[:, ['mpg']]
df['mpg_z'] = (x - x.mean()) / x.std()
df['colors'] = 'black'

# color fiat differently
df.loc[df.model == 'Fiat X1-9', 'colors'] = 'darkorange'
df.sort_values('mpg_z', inplace=True)
df.reset_index(inplace=True)

# Draw plot
import matplotlib.patches as patches

plt.figure(figsize=(10, 12), dpi=80)
plt.hlines(y=df.index,
           xmin=0,
           xmax=df.mpg_z,
           color=df.colors,
           alpha=0.4,
           linewidth=1)
plt.scatter(df.mpg_z,
            df.index,
            color=df.colors,
            s=[600 if x == 'Fiat X1-9' else 300 for x in df.model],
            alpha=0.6)
plt.yticks(df.index, df.model)
plt.xticks(fontsize=12)

# Annotate
plt.annotate('Mercedes Models',
             xy=(0.0, 11.0),
             xytext=(1.0, 11),
             xycoords='data',
             fontsize=15,
             ha='center',
             va='center',
             bbox=dict(boxstyle='square', fc='firebrick'),
             arrowprops=dict(arrowstyle='-[, widthB=2.0, lengthB=1.5',
                             lw=2.0,
                             color='steelblue'),
             color='white')

# Add Patches
p1 = patches.Rectangle((-2.0, -1),
                       width=.3,
                       height=3,
                       alpha=.2,
                       facecolor='red')
p2 = patches.Rectangle((1.5, 27),
                       width=.8,
                       height=5,
                       alpha=.2,
                       facecolor='green')
plt.gca().add_patch(p1)
plt.gca().add_patch(p2)
plt.xticks(fontsize=10)
plt.yticks(fontsize=10)

# Decorate
plt.title('Diverging Bars of Car Mileage', fontdict={'size': 15})
plt.grid(linestyle='--', alpha=0.5)
plt.show()