stacked_plot

1.py

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

data = pd.read_csv('netflix_titles.csv')

data = data.loc[data['release_year'].isin([*range(2016, 2020)]), ['type', 'release_year']].copy()
data.dropna(inplace=True)
data['release_year'] = data['release_year'].astype('int')
data

10.py

cross_tab_prop.plot(kind='bar', 
                        stacked=True, 
                        colormap='tab10', 
                        figsize=(10, 6))

plt.legend(loc="lower left", ncol=2)
plt.xlabel("Release Year")
plt.ylabel("Proportion")


for n, x in enumerate([*cross_tab.index.values]):
    for (proportion, count, y_loc) in zip(cross_tab_prop.loc[x],
                                          cross_tab.loc[x],
                                          cross_tab_prop.loc[x].cumsum()):
                
        plt.text(x=n - 0.17,
                 y=(y_loc - proportion) + (proportion / 2),
                 s=f'{count}\n({np.round(proportion * 100, 1)}%)', 
                 color="black",
                 fontsize=12,
                 fontweight="bold")

plt.show()

11.py

cross_tab_prop.plot(kind='barh', 
                        stacked=True, 
                        colormap='tab10', 
                        figsize=(10, 6))

plt.legend(loc="lower left", ncol=2)
plt.ylabel("Release Year")
plt.xlabel("Proportion")


for n, x in enumerate([*cross_tab.index.values]):
    for (proportion, count, y_loc) in zip(cross_tab_prop.loc[x],
                                          cross_tab.loc[x],
                                          cross_tab_prop.loc[x].cumsum()):
                
        plt.text(x=(y_loc - proportion) + (proportion / 2),
                 y=n - 0.11,
                 s=f'{count}\n({np.round(proportion * 100, 1)}%)', 
                 color="black",
                 fontsize=12,
                 fontweight="bold")

plt.show()

2.py

cross_tab_prop = pd.crosstab(index=data['release_year'],
                             columns=data['type'],
                             normalize="index")
cross_tab_prop

3.py

cross_tab = pd.crosstab(index=data['release_year'],
                        columns=data['type'])
cross_tab

4.py

cross_tab_prop.plot(kind='bar', 
                    stacked=True, 
                    colormap='tab10', 
                    figsize=(10, 6))

plt.legend(loc="upper left", ncol=2)
plt.xlabel("Release Year")
plt.ylabel("Proportion")
plt.show()

5.py

cross_tab_prop.plot(kind='bar', 
                    stacked=True, 
                    colormap='tab10', 
                    figsize=(10, 6))

plt.legend(loc="upper left", ncol=2)
plt.xlabel("Release Year")
plt.ylabel("Proportion")


for n, x in enumerate([*cross_tab.index.values]):
    for proportion in cross_tab_prop.loc[x]:
                
        plt.text(x=n,
                 y=proportion,
                 s=f'{np.round(proportion * 100, 1)}%', 
                 color="black",
                 fontsize=12,
                 fontweight="bold")

plt.show()

6.py

for n, x in enumerate([*cross_tab.index.values]):
    print(f'n: {n}, x: {x}')

7.py

for n, x in enumerate([*cross_tab.index.values]):
    for proportion in cross_tab_prop.loc[x]:
        print(f'n: {n}, x: {x}, proportion: {proportion}')

8.py

cross_tab_prop.plot(kind='bar', 
                    stacked=True, 
                    colormap='tab10', 
                    figsize=(10, 6))

plt.legend(loc="lower left", ncol=2)
plt.xlabel("Release Year")
plt.ylabel("Proportion")


for n, x in enumerate([*cross_tab.index.values]):
    for (proportion, y_loc) in zip(cross_tab_prop.loc[x],
                                   cross_tab_prop.loc[x].cumsum()):
                
        plt.text(x=n - 0.17,
                 y=y_loc,
                 s=f'{np.round(proportion * 100, 1)}%', 
                 color="black",
                 fontsize=12,
                 fontweight="bold")

plt.show()

9.py

cross_tab_prop.plot(kind='bar', 
                        stacked=True, 
                        colormap='tab10', 
                        figsize=(10, 6))

plt.legend(loc="lower left", ncol=2)
plt.xlabel("Release Year")
plt.ylabel("Proportion")


for n, x in enumerate([*cross_tab.index.values]):
    for (proportion, y_loc) in zip(cross_tab_prop.loc[x],
                                   cross_tab_prop.loc[x].cumsum()):
                
        plt.text(x=n - 0.17,
                 y=(y_loc - proportion) + (proportion / 2),
                 s=f'{np.round(proportion * 100, 1)}%', 
                 color="black",
                 fontsize=12,
                 fontweight="bold")

plt.show()